The measure is a PRE-PM that calculates the percentage of contraceptive care patients who give a “top box” score for their experience of contraceptive counseling received during their clinical encounter. The measure is a four-question survey which asks patients about key components of patient-centered counseling, including respect and adequate information. A “top box” score is defined as a response which gives the highest score for each of the four questions.
Due to data availability issues, we are unable to obtain recent data and are thus unable to submit updated testing required to maintain endorsement at the individual clinician level and have removed that level of analysis.
Since the time of our original endorsement, we have been made aware that our measure and the level at which it is collected, analyzed, and interpreted is more correctly categorized as clinician: group/practice than facility. We have therefore updated this specification to indicate this unit of analysis.
We have updated the age range of eligibility from 15-45 years to 15-44 years for the measure to align with other contraceptive care measures (e.g. CBE #2902, 2903, 2904, 3699, 3682)
Measure Specs
General Information
Contraception is utilized by 90% of women in their lifetimes [1], making contraceptive care a crucial and in-demand healthcare service. However, many gaps exist in access to high-quality contraceptive care. Patients also reported receiving information from their providers that was inadequate to support them in making an informed decision on contraception [2–5], and patients felt dissatisfied with the person-centeredness and adequacy of counseling overall [5–8]. Thus, when assessing quality of contraceptive care, patient experience is an important outcome to measure. Moreover, it is highly valued by patients[2] and is a critical component of patient-centeredness, a core aspect of care quality as defined by the National Academy of Medicine (previously Institute of Medicine) in its report, Crossing the Quality Chasm [9]. Additionally, patient-centeredness of contraceptive counseling has been demonstrated to be associated with contraceptive continuation at six months and use of one’s preferred method [10,11], indicating a relationship between patient experience of counseling and the ability of patients to achieve their own reproductive goals, including pregnancy prevention. Patient experience has also been linked to improved engagement with care in various contexts [12,13]; in the context of contraceptive care, this means that patients who receive patient-centered care may feel more able to continue engaging with the reproductive health care system not only for contraception but also if and when they become pregnant and/or give birth [14] and for their other reproductive health needs. As such, positive patient experience of contraceptive counseling can support positive pregnancy and birth outcomes such as reduced maternal mortality.
Given the important implications of patient-centeredness of contraceptive counseling, both for patient experience and reproductive health outcomes, many healthcare organizations are invested in gathering information on the experiences of their patients and improving those experiences at various levels of aggregation. The Person-Centered Contraceptive Counseling measure (PCCC) (CBE #3543) is a four-item patient-reported experience performance measure (PRE-PM), informed by qualitative work with patients, the input of healthcare experts, and a patient stakeholder group that is designed to give accountable entities an opportunity to understand the quality of their patients’ experience of contraceptive counseling.
The PCCC measure collects information on the quality of care at a specific encounter and is designed for use at the clinician group/practice level. Use of this measure centers the importance of positive patient experience as a measure of quality, and its use encourages providers to invest in high-quality contraceptive care practices. While the PCCC can be used as a stand-alone measure, the measure exists in an ecosystem of person-centered measures working to improve the quality of contraceptive services. This includes measures of contraceptive use and provision, as well as of screening for contraceptive need. Widespread use of validated performance measures for contraceptive care in diverse care contexts has the potential to improve patient experience and reproductive outcomes, particularly in underserved populations. As improvement in the quality of contraceptive care has been shown to improve people’s ability to identify methods that they can use over time and to promote engagement with health care across the reproductive life course [15–17], this will improve people’s reproductive outcomes and therefore would also be expected to have a positive impact on health care costs.
References
1. Frederiksen, B, Ranji U, Long M, Diep K, Salganicoff A. Contraception in the United States: A Closer Look at Experiences, Preferences, and Coverage. KFF; 2022. Accessed April 14, 2026. https://www.kff.org/womens-health-policy/contraception-in-the-united-st…
2. Dehlendorf C, Levy K, Kelley A, Grumbach K, Steinauer J. Women’s preferences for contraceptive counseling and decision making. Contraception. 2013;88(2):250-256. doi:10.1016/j.contraception.2012.10.012
3. Yee LM, Simon MA. Perceptions of coercion, discrimination and other negative experiences in postpartum contraceptive counseling for low-income minority women. J Health Care Poor Underserved. 2011;22(4):1387-1400. doi:10.1353/hpu.2011.0144
4. Guendelman S. Perceptions of hormonal contraceptive safety and side effects among low-income Latina and non-Latina women. Maternal and Child Health Journal. 2000;4(4):233-239. doi:10.1023/A:1026643621387
5. Becker D, Koenig MA, Mi Kim Y, Cardona K, Sonenstein FL. The Quality of Family Planning Services in the United States: Findings from a Literature Review. Perspect Sexual Reproductive. 2007;39(4):206-215. doi:10.1363/3920607
6. Becker D, Tsui AO. Reproductive Health Service Preferences And Perceptions of Quality Among Low-Income Women: Racial, Ethnic and Language Group Differences. Perspectives on Sexual and Reproductive Health. 2008;40(4):202-211. doi:10.1363/4020208
7. Nobili MP, Piergrossi S, Brusati V, Moja EA. The effect of patient-centered contraceptive counseling in women who undergo a voluntary termination of pregnancy. Patient Educ Couns. 2007;65(3):361-368. doi:10.1016/j.pec.2006.09.004
8. Borrero S, Schwarz EB, Creinin M, Ibrahim S. The Impact of Race and Ethnicity on Receipt of Family Planning Services in the United States. Journal of Women’s Health. 2009;18(1):91-96. doi:10.1089/jwh.2008.0976
9. Institute of Medicine (US) Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press (US); 2001. Accessed May 20, 2022. http://www.ncbi.nlm.nih.gov/books/NBK222274/
10. Dehlendorf C, Henderson JT, Vittinghoff E, et al. Association of the quality of interpersonal care during family planning counseling with contraceptive use. Am J Obstet Gynecol. 2016;215(1):78.e1-9. doi:10.1016/j.ajog.2016.01.173
11. Whitfield B, Wilkinson TA, Lindberg LD. Adolescents’ and Young Adults’ Receipt of Person-Centered Contraceptive Counseling. JAMA Netw Open. 2025;8(12):e2551287. doi:10.1001/jamanetworkopen.2025.51287
12. Anhang Price R, Elliott MN, Zaslavsky AM, et al. Examining the role of patient experience surveys in measuring health care quality. Med Care Res Rev. 2014;71(5):522-554. doi:10.1177/1077558714541480
13. Doyle C, Lennox L, Bell D. A systematic review of evidence on the links between patient experience and clinical safety and effectiveness. BMJ Open. 2013;3(1):e001570. doi:10.1136/bmjopen-2012-001570
14. Gomez AM, Wapman M. Under (implicit) pressure: young Black and Latina women’s perceptions of contraceptive care. Contraception. 2017;96(4):221-226. doi:10.1016/j.contraception.2017.07.007
15. Gavin L, Frederiksen B, Robbins C, Pazol K, Moskosky S. New clinical performance measures for contraceptive care: their importance to healthcare quality. Contraception. 2017;96(3):149-157. doi:10.1016/j.contraception.2017.05.013
16. Gavin LE, Ahrens KA, Dehlendorf C, Frederiksen BN, Decker E, Moskosky S. Future directions in performance measures for contraceptive care: a proposed framework. Contraception. 2017;96(3):138-144. doi:10.1016/j.contraception.2017.06.001
17. Moniz MH, Gavin LE, Dalton VK. Performance Measures for Contraceptive Care: A New Tool to Enhance Access to Contraception. Obstetrics & Gynecology. 2017;130(5):1121-1125. doi:10.1097/AOG.0000000000002314
NA
Numerator
The PCCC is a visit-specific measure of patient-centeredness in contraceptive counseling. It specifically measures how many patients report a top-box (i.e., the highest possible) score of patient experience in their contraceptive counseling interaction with a health care provider during their recent visit. Identification in the numerator is determined by patient response to the PCCC.
Identification in the numerator is determined by patient response to the PCCC. The numerator includes only those patients who gave a top-box score for their experience with their health care provider on the PCCC. All other conditions determining inclusion in the numerator also determine inclusion in the denominator.
Denominator
The target population for the PCCC is patients aged 15-44 years who were assigned female at birth, who are not currently pregnant, and who received contraceptive counseling as part of their recent visit.
For the purposes of eligibility screening, patient age, sex, and pregnancy status are determined though patient report to their provider or clinic in the normal course of their care. As these are standard, readily available elements of patient data, entities may rely on their own data to determine eligibility, with the exception if receipt of contraceptive counseling, which is not a standard or readily available element of patient data. Eligible patients are identified through one of two pathways:
1) On the day of appointment: Patients who potentially received contraceptive counseling during their visit are identified by providers and/or staff. This assessment can either happen prospectively (prior to clinical appointment) or retrospectively (after the visit is completed). Specifically, patients are identified through a standardized process that includes pre-emptive staff review of schedules and visit types (e.g. flagging future family planning visits for survey distribution, as contraceptive counseling is likely to take place in such visits), and/or provider or staff identification based on the exam room conversation, depending on clinic protocols and flow. The survey can then either be distributed: 1. on paper as the patient completes their visit; 2. electronically through a QR code, link or tablet provided in clinic; and/or 3. through a message sent over the patient’s portal at the completion of the visit. In the latter case, the survey is considered valid if completed within a week of the appointment.
2) Weekly recruitment: On a weekly basis, all patients with a clinical encounter in the past week, who have an electronic health record (EHR)-recorded sex as female and are between the ages of 15-44 years and not receiving prenatal care receive a request through a patient portal message or text to complete the survey within a week.
In both cases, the patient will then self-identify eligibility. Specifically, at the start of the survey, patients answer the following eligibility question: “Did you talk about options for birth control during your visit?” As the PCCC is intended to measure the quality of counseling for those who did receive counseling, patients who report that they did not receive counseling are not eligible to respond to the PCCC scale, regardless of whether counseling may have been appropriate during their visit.
Exclusions
Patients are excluded if 1) they did not receive contraceptive counseling, 2) are younger than 15 years old or older than 44 years old, 3) if they are currently pregnant.
We have chosen an age range of15-44 years to be consistent with other contraceptive measures (CBE # 2902, 2903, 2904, 3682e, 3699e). This range captures the majority of women of reproductive age who will receive contraceptive counseling.
Pregnant patients are excluded from the denominator for two reasons. First, contraceptive counseling in the context of pregnancy is distinct from that provided to non-pregnant individuals. Specifically, perinatal contraceptive counseling often includes multiple conversations touches over the course of prenatal care and immediate postpartum care. This is appropriate as women, when pregnant, are not immediately at risk of an undesired pregnancy, and therefore there is less time sensitivity to this counseling and is also consistent with women’s preferences for this care [1]. Given this difference in structure of counseling for pregnant women, the use of a visit-specific measure for contraceptive counseling is not appropriate. Second, given distinct issues related to post-partum contraceptive use, including increased risk of blood clots, effect on lactation, and the health impact of birth spacing, counseling pregnant women about future contraceptive use has components distinct from that of non-pregnant women. For these conceptual reasons, the PCCC was designed for use with non-pregnant patients and has not been extensively tested with pregnant patients to determine whether it accurately captures their needs and desires for counseling.
References
1. Yee LM, Farner KC, King E, Simon MA. What do Women Want? Experiences of Low-Income Women with Postpartum Contraception and Contraceptive Counseling. J Pregnancy Child Health. 2015;2(5):191. doi:10.4172/2376-127X.1000191
Staff and providers are instructed not to distribute the survey to patients who have disclosed or discovered during the visit that they are pregnant or to patients outside of the designated age range or sex. When recruiting patients through the EHR, the clinician group/practice can exclude by recruitment strategy by only sending the survey only to patients identified as female, within the designated age ranges and who are not receiving prenatal care. At the start of the survey, patients answer the following eligibility question: “Did you talk about options for birth control during your visit?” Respondents who report no contraceptive counseling are excluded.
Measure Calculation
Measure users should follow these steps in order to obtain measure results:
1) Identification and data collection
Eligible patients are identified through one of two pathways:
a) On the day of appointment:
i) Providers and/or staff identify eligible, non-pregnant patients who have received contraceptive counseling before they leave the clinic following their visit
ii) A team member who is not the provider who provided counseling introduces and distributes the survey to the patient following their visit and/or sends a message through the patient’s portal
iii) Patient completes the survey immediately post-visit or within a week of their appointment
(self-administered via paper or electronically, e.g. on a tablet computer)
b) Weekly recruitment:
i) On a weekly basis, all patients with a clinical encounter in the past week, who have an EMR-recorded sex as female and are between the ages of 15-44 years and not receiving prenatal care receive a request through a patient portal message or text to complete the survey.
ii) Patient completes the survey electronically within a week of receiving the survey
2) Data aggregation
a) Patient responses are aggregated for analysis, either through data entry of paper surveys or collation of responses to electronic survey
3) Measure calculation
a) Patients who indicate they did not receive contraceptive counseling are excluded
b) Incomplete PCCC responses are excluded
c) Measure responses are summed as the total of all PCCC item values (maximum value of 20)
d) PCCC value sums are dichotomized as a maximum value of 20 (top-box score) versus any value less than 20
e) Dichotomized result variable is examined at clinician group/practice level
f) Measure result is calculated as the percentage of patients responding with a top-box score, divided by the total number of patients who gave any response to the survey, on a clinician group/practice level
The measure is not stratified
Eligible patients for the survey are identified in two ways: 1) Patients receiving contraceptive counseling during their visit are identified by providers and/or staff, and patient identification is then communicated to the team member responsible for distributing the PCCC survey to patients. A team member who did not provide contraceptive counseling during the patient visit introduces and distributes the survey to patients, in order to mitigate the risks of social desirability bias and perceived threat to privacy affecting patient responses, as could happen if the same individual who gave counseling were to distribute the survey. 2) The survey is distributed through patient portal message and/or text post-visit and/or to all patients with female sex and documented age between 15-44 years not receiving prenatal care who had an appointment in the previous week. We have assessed whether performance scoring could be affected by recall bias between survey completion on the day of appointment and survey completion delayed by one week through examining scores from a subset of clinician group/practices that switched collection strategies, allowing for a natural experiment. In one entity, performance score was 88% among patients who completed day-of and 86% among patients who completed the survey within a week-post. For the second entity, score was 86% among patients who completed day-of and 90% among patients who completed the survey within a week. In both cases, scores were comparable assessments of performance and there was not consistent directionality in score shifts, and thus not consistent biasing in one direction.
In both verbal and written communication to patients, the anonymous nature of the survey should be emphasized, with assurance that answers to the survey will not be linked to the individual patient and would not impact care. The survey is self-administered either on paper or electronically.
The response rate is calculated as the number of patients to whom a survey is administered who return a completed survey, divided by the number of patients approached to complete a survey
The PCCC is collected using consecutive sampling for identified clinician group/practices. Based on our reliability results reported in section 5 of this application, we recommend a minimum sample size of 30 responses per clinician group/practice
Supplemental Attachment
Measure Record
Point of Contact
Not applicable
Christine Dehlendorf
San Francisco, CA
United States
Christine Dehlendorf
University of California, San Francisco
San Francisco, CA
United States
Importance
Evidence
There are demonstrated gaps in the quality of contraceptive counseling. Analyses utilizing the 2017-2019 wave of National Survey of Family Growth (NSFG), which include a retrospective version of the PCCC (PCCC-RS) found that only 58% rated quality of contraceptive care received over the last year as optimal, demonstrating a gap nationally [1]. A similar national survey conducted by KFF in 2022 and 2024 demonstrates the persistence of this issue; they found only 40% and 42% of respondents reported optimal counseling respectively using the PCCC [2,3]. Use of the PCCC measure (CBE #3543) in a quality improvement context in 2022-2023 found a range of scores from 30% to 95% at the health center level in community health centers across the country, suggesting differential care at the clinician group/practice level [4]. To understand gaps in quality, studies have explored inadequacies in contraceptive counseling. In multiple studies examining patient experience of counseling, patients reported receiving information from their providers that was inadequate to support them in making an informed decision on contraception [5–8], and that patients felt dissatisfied with the patient-centeredness and adequacy of counseling overall [8–11]. Research conducted by our team at UCSF examining quality of counseling via audio recording of patient visits found that providers inconsistently elicited or engaged with patient experiences and preferences during counseling [12,13].
Gaps in quality of contraceptive care are experienced differently by different patient subgroups. Analyses using the PCCC-RS integrated into the 2017-2019 wave of the NSFG have found lower scores among Black, Spanish-speaking Latine, low-income, and gay and bisexual patients [1,14]. Analyses of the latest wave (2022-2023) of NSFG data are nascent, however, one analysis of this same retrospective PCCC found low scores (50%) across all age groups, with adolescents ages 15-19 years having lowest odds of reporting receiving high-quality contraceptive counseling [15]. The 2024 KFF survey reported income disparities similar to those found in the 2017-2019 NSFG analyses (using a similar retrospective measure), and a multi-state longitudinal study conducted from 2018-2023 found similar differences by race/ethnicity [3,16]. Other studies have surfaced indications that poor quality of contraceptive care is differentially experienced by women of color, such as findings that low-income women of color have greater odds of being advised to limit their childbearing [17] and receive a greater emphasis on highly effective methods from providers [11,18]. A randomized controlled trial explored this dynamic explicitly by using a standardized patient approach and found that providers were more likely to recommend an intrauterine device – a provider-controlled option - to standardized patients identified as low-income Black or Latina compared to those identified as white [19]. This is further elucidated in qualitative research, where Black, Latine and low-income patients describe themes of discriminatory and/or coercive contraceptive care practices [20–24]. Scholars have highlighted that these differential practices are rooted in a longstanding history of racial and class discrimination and systemic oppression [25–28]. Thus measuring and monitoring quality of contraceptive counseling is important to address healthcare disparities and promote health equity.
Patient experience is an outcome meaningful and important to patients and aligned with positive health outcomes. Patient experience is an important outcome to measure, in that it is highly valued by patients [5] and is a critical component of patient-centeredness, a core aspect of care quality as defined by the National Academy of Medicine (previously Institute of Medicine) in its report Crossing the Quality Chasm [29]. Further, a large body of evidence demonstrates how patient experience is associated with a range of health outcomes, structures, and processes. This includes two systematic reviews (one UK-based [30] and one US-based [31]), which both found that patient experience was positively associated with outcomes such as seeking and adhering to preventive care treatments, and positive clinical health outcomes, including self-rated health, engaging in health-promoting behavior, and primary care utilization. In addition, a 2009 meta-analysis of 127 studies documented that the quality of provider communication, which is the specific aspect of patient-centeredness measured by the PCCC, was directly associated with patient treatment adherence [32].
Patient experience of high-quality contraceptive counseling enables patients to meet their reproductive goals. In the context of contraceptive care specifically, the patient-centeredness of contraceptive counseling is associated with contraceptive continuation and satisfaction [33,34]. By working to improve patient experience, health care entities can therefore help support their patients achieve their reproductive goals, such as pregnancy prevention. Further, qualitative data suggests that patients who experience non-patient-centered contraceptive care are less likely to return to seek out care for future reproductive health needs [20,35]. This has the potential to negatively impact a range of outcomes, including pregnancy-related morbidity and mortality.
The PCCC provides the ability to monitor contraceptive counseling alongside measures of provision and use in order to provide a more comprehensive picture of contraceptive care quality. The motivation behind the development of the PCCC originated during the Department of Health and Human Services Office of Population Affair’s (OPA’s) development of measures CBE #2903 and #2904, which focus on most and moderately effective contraception and long-acting reversible contraceptive (LARC) methods. The OPA team and others involved in the measure development process foresaw that use of these important measures could have the unintended consequence of incentivizing provider pressure on patients to use more effective methods and away from use of prescription methods. During the Consensus-Based Entity endorsement process, this concern was voiced by stakeholders, including the National Partnership for Women & Families (NPWF). The NPWF submitted a public comment that stated, “It is extremely important to keep in mind that reproductive coercion has a troubling history, and remains an ongoing reality for many, including low-income women, women of color, young women, immigrant women, LGBT people, and incarcerated women. We hope this measure will be paired with a woman-reported ‘balancing measure’ of experience of receiving contraceptive care. Such a measure can be expected to help identify and/or check inappropriate pressure from the health care system.” Since this time, additional person-centered electronic clinical quality measures assessing contraceptive use have been endorsed at the facility and clinician group/practice levels (CBE# 3699e and 3682). The PCCC continues to serve as an important balancing measure to ensure that evaluation of contraceptive care quality includes consideration of how the care was delivered in addition to access to methods.
References
1. Wingo E, Sarnaik S, Michel M, et al. The status of person-centered contraceptive care in the United States: Results from a nationally representative sample. Perspect Sex Reprod Health. 2023;55(3):129-139. doi:10.1363/psrh.12245
2. Frederiksen B, Ranji U, Long M, Diep K, Salganicoff A. Contraception in the United States: A Closer Look at Experiences, Preferences, and Coverage. KFF; 2022. Accessed July 18, 2024. https://www.kff.org/womens-health-policy/report/contraception-in-the-un…
3. Frederiksen B, Diep K, Salganicoff A. Contraceptive Experiences, Coverage, and Preferences: Findings from the 2024 KFF Women’s Health Survey. KFF; 2024.
4. Dehlendorf C, Wingo E, Gibson L, Goetsch-Avila S, Kriz R, Hessler D. Advancing Equitable, Person-Centered Contraceptive Care Using Data-Driven Quality Improvement. J Am Board Fam Med. 2025;38(5):791-801. doi:10.3122/jabfm.2025.250073R1
5. Dehlendorf C, Levy K, Kelley A, Grumbach K, Steinauer J. Women’s preferences for contraceptive counseling and decision making. Contraception. 2013;88(2):250-256. doi:10.1016/j.contraception.2012.10.012
6. Yee LM, Simon MA. Perceptions of coercion, discrimination and other negative experiences in postpartum contraceptive counseling for low-income minority women. J Health Care Poor Underserved. 2011;22(4):1387-1400. doi:10.1353/hpu.2011.0144
7. Guendelman S. Perceptions of hormonal contraceptive safety and side effects among low-income Latina and non-Latina women. Maternal and Child Health Journal. 2000;4(4):233-239. doi:10.1023/A:1026643621387
8. Becker D, Koenig MA, Mi Kim Y, Cardona K, Sonenstein FL. The Quality of Family Planning Services in the United States: Findings from a Literature Review. Perspect Sexual Reproductive. 2007;39(4):206-215. doi:10.1363/3920607
9. Becker D, Tsui AO. Reproductive Health Service Preferences And Perceptions of Quality Among Low-Income Women: Racial, Ethnic and Language Group Differences. Perspectives on Sexual and Reproductive Health. 2008;40(4):202-211. doi:10.1363/4020208
10. Nobili MP, Piergrossi S, Brusati V, Moja EA. The effect of patient-centered contraceptive counseling in women who undergo a voluntary termination of pregnancy. Patient Educ Couns. 2007;65(3):361-368. doi:10.1016/j.pec.2006.09.004
11. Borrero S, Schwarz EB, Creinin M, Ibrahim S. The Impact of Race and Ethnicity on Receipt of Family Planning Services in the United States. Journal of Women’s Health. 2009;18(1):91-96. doi:10.1089/jwh.2008.0976
12. Dehlendorf C, Anderson N, Vittinghoff E, Grumbach K, Levy K, Steinauer J. Quality and Content of Patient-Provider Communication About Contraception: Differences by Race/Ethnicity and Socioeconomic Status. Womens Health Issues. 2017;27(5):530-538. doi:10.1016/j.whi.2017.04.005
13. Dehlendorf C, Kimport K, Levy K, Steinauer J. A qualitative analysis of approaches to contraceptive counseling. Perspect Sex Reprod Health. 2014;46(4):233-240. doi:10.1363/46e2114
14. Welti K, Manlove J, Finocharo J, Faccio B, Kim L. Women’s experiences with person-centered family planning care: Differences by sociodemographic characteristics. Contraception: X. 2022;4:100081. doi:10.1016/j.conx.2022.100081
15. Whitfield B, Wilkinson TA, Lindberg LD. Adolescents’ and Young Adults’ Receipt of Person-Centered Contraceptive Counseling. JAMA Netw Open. 2025;8(12):e2551287. doi:10.1001/jamanetworkopen.2025.51287
16. Kavanaugh ML, Haas M, Douglas-Hall A. Differential associations between experiences of contraceptive care and subsequent contraceptive access and preferences among family planning patients by racial and ethnic identity: Evidence from Arizona, Iowa, and Wisconsin. Ortega-Altamirano DV, ed. PLoS ONE. 2024;19(10):e0312111. doi:10.1371/journal.pone.0312111
17. Downing RA, LaVeist TA, Bullock HE. Intersections of Ethnicity and Social Class in Provider Advice Regarding Reproductive Health. Am J Public Health. 2007;97(10):1803-1807. doi:10.2105/AJPH.2006.092585
18. Rowley S, Broomfield C, Min J, Quinn S, Campbell K, Wood S. Racial Inequities in Adolescent Contraceptive Care Delivery: A Reproductive Justice Issue. Journal of Pediatric and Adolescent Gynecology. 2023;36(3):298-303. doi:10.1016/j.jpag.2022.11.004
19. Dehlendorf C, Ruskin R, Grumbach K, et al. Recommendations for intrauterine contraception: a randomized trial of the effects of patients’ race/ethnicity and socioeconomic status. Am J Obstet Gynecol. 2010;203(4):319.e1-8. doi:10.1016/j.ajog.2010.05.009
20. Gomez AM, Wapman M. Under (implicit) pressure: young Black and Latina women’s perceptions of contraceptive care. Contraception. 2017;96(4):221-226. doi:10.1016/j.contraception.2017.07.007
21. Higgins JA, Kramer RD, Ryder KM. Provider Bias in Long-Acting Reversible Contraception (LARC) Promotion and Removal: Perceptions of Young Adult Women. Am J Public Health. 2016;106(11):1932-1937. doi:10.2105/AJPH.2016.303393
22. Thorburn S, Bogart LM. African American women and family planning services: perceptions of discrimination. Women Health. 2005;42(1):23-39. doi:10.1300/J013v42n01_02
23. Reed R, Osby O, Nelums M, Welchlin C, Konate R, Holt K. Contraceptive care experiences and preferences among Black women in Mississippi: A qualitative study. Contraception. 2022;114:18-25. doi:10.1016/j.contraception.2022.05.009
24. Mann ES, Chen AM, Johnson CL. Doctor knows best? Provider bias in the context of contraceptive counseling in the United States. Contraception. 2022;110:66-70. doi:10.1016/j.contraception.2021.11.009
25. Stern AM. STERILIZED in the Name of Public Health: Race, Immigration, and Reproductive Control in Modern California. Am J Public Health. 2005;95(7):1128-1138. doi:10.2105/AJPH.2004.041608
26. Roberts D. Killing the Black Body. Penguin Random House; 1998.
27. Brandi K, Fuentes L. The history of tiered-effectiveness contraceptive counseling and the importance of patient-centered family planning care. American Journal of Obstetrics and Gynecology. 2020;222(4):S873-S877. doi:10.1016/j.ajog.2019.11.1271
28. Kathawa CA, Arora KS. Implicit Bias in Counseling for Permanent Contraception: Historical Context and Recommendations for Counseling. Health Equity. 2020;4(1):326-329. doi:10.1089/heq.2020.0025
29. Institute of Medicine (US) Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press (US); 2001. Accessed May 20, 2022. http://www.ncbi.nlm.nih.gov/books/NBK222274/
30. Doyle C, Lennox L, Bell D. A systematic review of evidence on the links between patient experience and clinical safety and effectiveness. BMJ Open. 2013;3(1):e001570. doi:10.1136/bmjopen-2012-001570
31. Anhang Price R, Stucky B, Parast L, et al. Development of Valid and Reliable Measures of Patient and Family Experiences of Hospice Care for Public Reporting. Journal of Palliative Medicine. 2018;21(7):924-932. doi:10.1089/jpm.2017.0594
32. Zolnierek KBH, Dimatteo MR. Physician communication and patient adherence to treatment: a meta-analysis. Med Care. 2009;47(8):826-834. doi:10.1097/MLR.0b013e31819a5acc
33. Dehlendorf C, Henderson JT, Vittinghoff E, et al. Association of the quality of interpersonal care during family planning counseling with contraceptive use. American Journal of Obstetrics and Gynecology. 2016;215(1):78.e1-78.e9. doi:10.1016/j.ajog.2016.01.173
34. Oakley LP, Harvey SM, López-Cevallos DF. Racial and Ethnic Discrimination, Medical Mistrust, and Satisfaction with Birth Control Services among Young Adult Latinas. Womens Health Issues. 2018;28(4):313-320. doi:10.1016/j.whi.2018.03.007
35. Baker K, Emery ST, Spike E, Sutton J, Ben-Porath E. Skin tone discrimination and birth control avoidance among women in Harris County, Texas: a cross-sectional study. BMC Public Health. 2024;24(1):2375. doi:10.1186/s12889-024-19765-3
Measure Impact
The choice of a contraceptive method is a highly preference-sensitive decision with multiple medically appropriate options. Each patient has unique preferences regarding key contraceptive method attributes, such as pregnancy prevention, side effects, and menstrual cycle changes. Research also shows the patient experience is influenced by historical and ongoing forceful and coercive practices of pressuring patients, particularly low-income patients and Black and Latine patients, to use contraceptive methods that they do not want [1–6]. The PCCC (CBE#3543) was specifically designed with patient and provider stakeholder input to reflect the individualized nature of contraceptive counseling and ensure that patient-centered care is prioritized, which can help safeguard against care inequities.
Specifically, the PCCC was derived from the Interpersonal Quality of Family Planning scale (IQFP) [7]. The IQFP is a validated 11-item scale of patient experience of contraceptive counseling that addresses three domains of contraceptive counseling preferences: interpersonal connection, decision support, and adequate information. These domains and items were elucidated though qualitative interviews with patients [8]. To create the PCCC, a short form of the IQFP, we conducted cognitive interviews with 33 patients (10 in English, 13 in Spanish, and 10 with bilingual participants with substantial discussion in both languages) to understand which items held the greatest relevance and importance to patients [9]. The items included in the final measure were those that held greatest importance to patients while also continuing to reflect the domains of patient importance identified in the IQFP, as well as maintaining the scientific validity and acceptability.
We tested the relevance of these qualities of the measure through iterative engagement with the Person-Centered Reproductive Health Program’s Patient Stakeholder Group (PSG). The PSG, a standing group individuals assigned female at birth, provided critical feedback on survey elements, ensuring accessibility and relevance. All members of the PSG confirmed that providing feedback on their healthcare experiences with contraceptive counseling at a population level is meaningful, as it informs system-level improvements.
Overall, our patient engagement and review of the literature demonstrates that the target population values the measured outcome and finds the feedback process meaningful in enhancing contraceptive counseling experiences.
References
1. Stern AM. Sterilized in the name of public health: race, immigration, and reproductive control in modern California. Am J Public Health. 2005;95(7):1128-1138. doi:10.2105/AJPH.2004.041608
2. Eeckhaut MCW, Hara Y. Reproductive Oppression Enters the Twenty-First Century: Pressure to Use Long-Acting Reversible Contraception (LARC) in the Context of “LARC First.” Socius: Sociological Research for a Dynamic World. 2023;9:23780231231180378. doi:10.1177/23780231231180378
3. Higgins JA, Kramer RD, Ryder KM. Provider Bias in Long-Acting Reversible Contraception (LARC) Promotion and Removal: Perceptions of Young Adult Women. Am J Public Health. 2016;106(11):1932-1937. doi:10.2105/AJPH.2016.303393
4. Gomez AM, Wapman M. Under (implicit) pressure: young Black and Latina women’s perceptions of contraceptive care. Contraception. 2017;96(4):221-226. doi:10.1016/j.contraception.2017.07.007
5. Borrero S, Schwarz EB, Creinin M, Ibrahim S. The Impact of Race and Ethnicity on Receipt of Family Planning Services in the United States. Journal of Women’s Health. 2009;18(1):91-96. doi:10.1089/jwh.2008.0976
6. Brandi K, Fuentes L. The history of tiered-effectiveness contraceptive counseling and the importance of patient-centered family planning care. American Journal of Obstetrics and Gynecology. 2020;222(4):S873-S877. doi:10.1016/j.ajog.2019.11.1271
7. Dehlendorf C, Henderson JT, Vittinghoff E, Steinauer J, Hessler D. Development of a patient-reported measure of the interpersonal quality of family planning care. Contraception. 2018;97(1):34-40. doi:10.1016/j.contraception.2017.09.005
8. Dehlendorf C, Levy K, Kelley A, Grumbach K, Steinauer J. Women’s preferences for contraceptive counseling and decision making. Contraception. 2013;88(2):250-256. doi:10.1016/j.contraception.2012.10.012
9. Dehlendorf C, Fox E, Silverstein IA, et al. Development of the Person-Centered Contraceptive Counseling scale (PCCC), a short form of the Interpersonal Quality of Family Planning care scale. Contraception. 2021;103(5):310-315. doi:10.1016/j.contraception.2021.01.008
Performance Gap
Performance data were derived from three quality improvement projects completed between 2022 and 2024. The first was a quality improvement learning collaborative with ten community health centers, with PCCC data collection from June-September 2022. The second was an implementation project conducted with the state Title X recipient and collecting data from 13 Title X subrecipient clinician group/practices in one northeastern state from March 2024-June 2025. The third source of data was an implementation project with 12 Title X agencies across the U.S., with data collected from June-September 2024. In all cases the PCCC was fielded as a standalone patient survey using the data collection methods described in section 1.18. In entirety, this includes 35 accountable entities and 2,022 patients.
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Mean Performance Score | 0.728 | 0.370 | 0.383 | 0.523 | 0.683 | 0.712 | 0.763 | 0.833 | 0.868 | 0.886 | 0.895 | 0.966 | 1.00 |
| N of Entities | 35 | 1 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 3 | 1 |
| N of Persons / Encounters / Episodes | 2022 | 62 | 162 | 179 | 142 | 201 | 152 | 140 | 250 | 192 | 206 | 398 | 40 |
Care Gaps
Closing Care Gaps
Evidence of Known Differences
Patient experience of quality contraceptive care is important because it enables patients to meet their reproductive goals, including through contraceptive continuation and satisfaction and continued engagement in reproductive health care [1–4]. Therefore, measuring and monitoring the quality of contraceptive counseling is important to address healthcare disparities. Professional guidelines such as from the American College of Obstetricians and Gynecologists, the Women’s Preventive Services Initiative, as well as the Quality Family Planning Recommendations issued by the Office of Population Affairs have emphasized the importance of person-centered contraceptive counseling [5–7].
Differential experiences of contraceptive care have been well-documented, highlighting key care gaps. Studies have shown that poor quality of contraceptive care has differentially experienced by women of color, such as low-income women of color having greater odds of being advised to limit their childbearing [8] and that providers put greater emphasis on highly-effective methods when counseling of women of color [9,10]. A randomized controlled trial further explored this dynamic by using a standardized patient approach and found that providers were more likely to recommend an intrauterine device – a highly effective, provider-controlled method - to standardized patients identified as low-income Black or Latina than those identified as white [11]. This is further elucidated in qualitative research, where Black, Latine and low-income patients describe themes of discriminatory and/or coercive contraceptive care practices [1,12–15]. Scholars have highlighted that these differential practices are rooted in a longstanding history of racial and class discrimination and systemic oppression [16–19].
Given this differential care, in our initial PCCC application in 2019, we explored differences in PCCC performance scores by race and ethnicity and language. Since our initial application, the Person-Centered Contraceptive Counseling measure (PCCC) has been used to surface and address these gaps in care quality, highlighting persistent differences in reported care quality and highlighting additional subgroups reporting lower rates of high-quality care. Analyses using a retrospective version of the PCCC integrated into the 2017-2019 wave of the National Survey of Family Growth found lower scores among Black and Spanish-speaking Latine individuals, consistent with our analysis in our initial application, as well as lower rates of high-quality care reported by low-income, and gay and bisexual individuals [20,21]. A multi-state longitudinal study conducted from 2018-2023 found similar differences [22]. An analysis by KFF in 2024 also noted differences in reported PCCC by income [23]. Moreover, a recent analysis from the 2022-2023 wave of NSFG data found persistently low scores by Black respondents, low English proficiency respondents and low-income respondents [24]. Another analysis of NSFG data found more specifically that English language proficiency was predictive of receiving higher quality care [25], which is consistent with data from our initial application.
In this maintenance application, we also report additional subgroups where differences in quality of contraceptive counseling has been reported (age category, sexual orientation) [20,26]. We also assessed scores by disability status, given evidence of barriers to high quality contraceptive care among people with disabilities, including coercion [27–29]. While there is evidence that low-income patients are less likely to report high-quality care, we were unable to explore this, as income data has not collected alongside the PCCC in the available data.
Testing Methods
To empirically test differences in performance scores across identified subpopulations:
- We used self-reported demographic variables collected alongside the PCCC, which included patient race or ethnicity, age, disability status, and sexual orientation. For disability status, patients responded to a binary question: “Are you a person with a disability or chronic illness/condition that impacts your learning, working or living activities?” Thus responses are binary in nature. For sexual orientation, we collapsed responses of “gay or lesbian”, “bisexual”, ”queer”, “pansexual” and “asexual” into a “non-heterosexual” category. Experiences of differential care have been similar across these groups and a binary analysis gave us greater power.
- We used chi-square tests of independence to assess the difference in measure performance across subpopulation categories.
- We analyzed tests of independence and associated probabilities to determine whether any observed variations in performance across subpopulations were statistically significant.
- We compared scores to those reported in the PCCC’s initial endorsement application, which was submitted to the National Quality Forum in 2019 by age category, race/ethnicity, and language. Data on sexual orientation and disability status were not collected in the 2019 sample, and thus we are unable to complete the comparison.
Results and Interpretation
Information on clinician group/practices included in these analyses and data collected, please see section 5.1.1. Performance score results by subgroups can be found in Section 7: Supplemental materials, Table 1.
Performance scores varied significantly across racial/ethnic groups (chi-square probability = <0.0001), with White (31% of the population, with a performance rate of 86%) and Asian (3% of the population, with a performance rate of 86%) respondents reporting the highest scores and Latina/Hispanic (40% of the population, with a performance rate of 77%), Black/African American (16% of the population, with a performance rate of 70%),and Middle Eastern (<1% of the population, with a performance rate of 65%), reporting the lowest. Scores within most racial/ethnic categories were consistent (within 5 percentage points) with 2019 reporting, apart from the score from the Asian subgroup (74% in 2019 v. 86% in 2026).
Differences by language spoken were also significantly different (chi-square probability: <0.001) with English speakers more often reporting highest score (80% of the population, with a performance rate of 80%) compared to Spanish speakers (19% of the population, with a performance rate of 74%) and other language speakers (<1% of the population, with a performance rate of 44%). Rates among English speakers were comparable but slightly lower when compared to 2019 (84% in 2019 v. 80% in 2026). and higher among Spanish speakers (68% in 2019 v. 74% in 2026). Comparing these results to our testing during the initial application, there have been slight changes in the performance scores from 2019 to 2026, but none of the population scores in the subpopulations demonstrated statistically significant changes at the 0.05 level. This indicates that performance gaps persist between racial and ethnic groups and by language spoken.
No statistically significant differences in scores were found by age category, sexual orientation, or disability status.
Limitations. We note that in our data sample, there were small cell sizes across a number of subpopulation categories. Scores from within these subcategories may be unreliable. For comparison between 2019 and 2026 submissions, we note that scores are not from the same accountable entities and thus are not directly comparable and differences in scores between these two time periods should be interpreted with caution.
Anticipated impact
Results among a diverse set of health centers suggest differences in quality of care experienced by different racial and ethnic groups and different language speakers persist. We note that these data do not come from the same accountable entities as those reported in the initial endorsement application and thus are not directly comparable, however they do highlight the prevalence and consistency of gaps in care delivery to specific groups.
Exposure to lower-quality contraceptive care may result in these groups being less supported in choosing a contraceptive method and/or pressured to utilize a contraceptive method that they do not want to use, extending a long history of reproductive oppression in healthcare as described above. Alternatively, this poor-quality care may result in these groups not using desired contraception due to negative care experiences. We know that quality of contraceptive counseling is associated with contraceptive continuation and satisfaction [3,30], suggesting that patients are less likely to have their pregnancy prevention needs met in the way they want [24]. One analysis found an association between low quality care and experiencing cost barriers to contraception [31]. Longer term, this may impact patients’ overall engagement in reproductive healthcare [1,4], which may have negative impact a range of outcomes, including pregnancy-related morbidity and mortality for these groups.
Accountable entities can use these findings to identify healthcare disparities and provide resources to improve care for groups within their clinician group/ practices. This may include training providers on person-centeredness of contraceptive counseling practices using a shared-decision-making approach, as well as providing trainings to address bias and deepen understanding and practice of cultural responsiveness and humility.
Accountable entities should also tailor their approaches to contraceptive counseling to the cultural and linguistic needs of the populations they serve. This may be achieved by engaging with patient groups to identify gaps in quality of care and quality improvement targets.
In a quality improvement collaborative, the PCCC was collected before and after a health equity-informed intervention that included targeted quality improvement to improve baseline PCCC scores [32]. Five out of nine participating CHCs improved their scores, in a range of 2.1% - 26.2% after the intervention. This included an improvement of 8.8% among Black patients across all agencies. We published case studies that highlight examples from two of those clinician group/practices: one with focused on improving universal screening and training in person-centered contraceptive counseling, and the other working to improve care delivery to their Spanish-speaking patients by examining and improving the cultural responsiveness of their contraceptive counseling practices. Both of these clinician group/practices improved their overall PCCC scores and scores by racial and ethnic subgroups [33].
References
1. Gomez AM, Wapman M. Under (implicit) pressure: young Black and Latina women’s perceptions of contraceptive care. Contraception. 2017;96(4):221-226. doi:10.1016/j.contraception.2017.07.007
2. Dehlendorf C, Henderson JT, Vittinghoff E, et al. Association of the quality of interpersonal care during family planning counseling with contraceptive use. Am J Obstet Gynecol. 2016;215(1):78.e1-9. doi:10.1016/j.ajog.2016.01.173
3. Oakley LP, Harvey SM, López-Cevallos DF. Racial and Ethnic Discrimination, Medical Mistrust, and Satisfaction with Birth Control Services among Young Adult Latinas. Womens Health Issues. 2018;28(4):313-320. doi:10.1016/j.whi.2018.03.007
4. Baker K, Emery ST, Spike E, Sutton J, Ben-Porath E. Skin tone discrimination and birth control avoidance among women in Harris County, Texas: a cross-sectional study. BMC Public Health. 2024;24(1):2375. doi:10.1186/s12889-024-19765-3
5. American College of Obstetricians and Gynecologists’ Committee on Health Care for Underserved Women, Contraceptive Equity Expert Work Group, and Committee on Ethics. Patient-Centered Contraceptive Counseling: ACOG Committee Statement Number 1. Obstet Gynecol. 2022;139(2):350-353. doi:10.1097/AOG.0000000000004659
6. Nelson H. Contraception: Women’s Preventive Services Initiative Update. Women’s Preventive Services Initiative; 2021. https://www.womenspreventivehealth.org/wp-content/uploads/WPSI-Contrace…
7. Romer SE, Blum J, Borrero S, et al. Providing Quality Family Planning Services in the United States: Recommendations of the U.S. Office of Population Affairs (Revised 2024). American Journal of Preventive Medicine. 2024;67(6):S41-S86. doi:10.1016/j.amepre.2024.09.007
8. Downing RA, LaVeist TA, Bullock HE. Intersections of Ethnicity and Social Class in Provider Advice Regarding Reproductive Health. Am J Public Health. 2007;97(10):1803-1807. doi:10.2105/AJPH.2006.092585
9. Borrero S, Schwarz EB, Creinin M, Ibrahim S. The Impact of Race and Ethnicity on Receipt of Family Planning Services in the United States. Journal of Women’s Health. 2009;18(1):91-96. doi:10.1089/jwh.2008.0976
10. Rowley S, Broomfield C, Min J, Quinn S, Campbell K, Wood S. Racial Inequities in Adolescent Contraceptive Care Delivery: A Reproductive Justice Issue. Journal of Pediatric and Adolescent Gynecology. 2023;36(3):298-303. doi:10.1016/j.jpag.2022.11.004
11. Dehlendorf C, Ruskin R, Grumbach K, et al. Recommendations for intrauterine contraception: a randomized trial of the effects of patients’ race/ethnicity and socioeconomic status. Am J Obstet Gynecol. 2010;203(4):319.e1-8. doi:10.1016/j.ajog.2010.05.009
12. Higgins JA, Kramer RD, Ryder KM. Provider Bias in Long-Acting Reversible Contraception (LARC) Promotion and Removal: Perceptions of Young Adult Women. Am J Public Health. 2016;106(11):1932-1937. doi:10.2105/AJPH.2016.303393
13. Thorburn S, Bogart LM. African American women and family planning services: perceptions of discrimination. Women Health. 2005;42(1):23-39. doi:10.1300/J013v42n01_02
14. Reed R, Osby O, Nelums M, Welchlin C, Konate R, Holt K. Contraceptive care experiences and preferences among Black women in Mississippi: A qualitative study. Contraception. 2022;114:18-25. doi:10.1016/j.contraception.2022.05.009
15. Mann ES, Chen AM, Johnson CL. Doctor knows best? Provider bias in the context of contraceptive counseling in the United States. Contraception. 2022;110:66-70. doi:10.1016/j.contraception.2021.11.009
16. Stern AM. STERILIZED in the Name of Public Health: Race, Immigration, and Reproductive Control in Modern California. Am J Public Health. 2005;95(7):1128-1138. doi:10.2105/AJPH.2004.041608
17. Roberts D. Killing the Black Body. Penguin Random House; 1998.
18. Brandi K, Fuentes L. The history of tiered-effectiveness contraceptive counseling and the importance of patient-centered family planning care. American Journal of Obstetrics and Gynecology. 2020;222(4):S873-S877. doi:10.1016/j.ajog.2019.11.1271
19. Kathawa CA, Arora KS. Implicit Bias in Counseling for Permanent Contraception: Historical Context and Recommendations for Counseling. Health Equity. 2020;4(1):326-329. doi:10.1089/heq.2020.0025
20. Wingo E, Sarnaik S, Michel M, et al. The status of person-centered contraceptive care in the United States: Results from a nationally representative sample. Perspect Sex Reprod Health. 2023;55(3):129-139. doi:10.1363/psrh.12245
21. Welti K, Manlove J, Finocharo J, Faccio B, Kim L. Women’s experiences with person-centered family planning care: Differences by sociodemographic characteristics. Contraception: X. 2022;4:100081. doi:10.1016/j.conx.2022.100081
22. Kavanaugh ML, Haas M, Douglas-Hall A. Differential associations between experiences of contraceptive care and subsequent contraceptive access and preferences among family planning patients by racial and ethnic identity: Evidence from Arizona, Iowa, and Wisconsin. Ortega-Altamirano DV, ed. PLoS ONE. 2024;19(10):e0312111. doi:10.1371/journal.pone.0312111
23. Frederiksen B, Ranji U, Long M, Diep K, Salganicoff A. Contraception in the United States: A Closer Look at Experiences, Preferences, and Coverage. KFF; 2022. Accessed July 18, 2024. https://www.kff.org/womens-health-policy/report/contraception-in-the-un…
24. Whitfield B, Wilkinson TA, Lindberg LD. Adolescents’ and Young Adults’ Receipt of Person-Centered Contraceptive Counseling. JAMA Netw Open. 2025;8(12):e2551287. doi:10.1001/jamanetworkopen.2025.51287
25. Boniface ER, Courchaine K, Hansen K, Darney BG. Intersection of Nativity and English Proficiency With Receipt of Person-Centered Contraceptive Counseling. O&G Open. 2024;1(2):013. doi:10.1097/og9.0000000000000013
26. Whitfield B, Wilkinson TA, Lindberg LD. Adolescents’ and Young Adults’ Receipt of Person-Centered Contraceptive Counseling. JAMA Netw Open. 2025;8(12):e2551287. doi:10.1001/jamanetworkopen.2025.51287
27. Fletcher J, Yee H, Ong B, Roden RC. Centering disability visibility in reproductive health care: Dismantling barriers to achieve reproductive equity. Womens Health (Lond Engl). 2023;19:17455057231197166. doi:10.1177/17455057231197166
28. Horner-Johnson W, Klein KA, Campbell J, Guise JM. “It Would Have Been Nice to Have a Choice”: Barriers to Contraceptive Decision-making among Women with Disabilities. Womens Health Issues. 2022;32(3):261-267. doi:10.1016/j.whi.2022.01.001
29. Cannon LM, Green TL, Bethea ME, Swan LET. “It should have been my decision”: A mixed methods investigation of contraceptive coercion among U.S. patients with and without disabilities. Soc Sci Med. 2026;394:119058. doi:10.1016/j.socscimed.2026.119058
30. Dehlendorf C, Henderson JT, Vittinghoff E, et al. Association of the quality of interpersonal care during family planning counseling with contraceptive use. American Journal of Obstetrics and Gynecology. 2016;215(1):78.e1-78.e9. doi:10.1016/j.ajog.2016.01.173
31. Kavanaugh ML, Pliskin E, Hussain R. Associations between unfulfilled contraceptive preferences due to cost and low-income patients’ access to and experiences of contraceptive care in the United States, 2015–2019. Contraception: X. 2022;4:100076. doi:10.1016/j.conx.2022.100076
32. Dehlendorf C, Wingo E, Gibson L, Goetsch-Avila S, Kriz R, Hessler D. Advancing Equitable, Person-Centered Contraceptive Care Using Data-Driven Quality Improvement. J Am Board Fam Med. 2025;38(5):791-801. doi:10.3122/jabfm.2025.250073R1
33. Wingo E, Gibson L, Dehlendorf C. Heeding lessons of our past: Centering sociohistorical context and health equity in efforts to expand contraceptive access. Contraception. 2026;155:111270. doi:10.1016/j.contraception.2025.111270
Feasibility
Feasibility
The Person-Centered Contraceptive Counseling measure (PCCC) is a patient-reported experience performance measure (PRE-PM) collected through patient surveys; measure calculation is based solely on information provided by patients responding to the instrument and thus cannot be captured from existing electronic sources. Accountable entities identify patients who may have received contraceptive counseling, have a documented female sex, are between 15-44 years and are not currently pregnant. Survey distributors can distribute the survey to patients in clinic on the day of their appointment or utilize their patient portal to identify patients and send them the survey to complete within a week of their appointment. The survey includes an eligibility question (“Did you and your provider talk about your birth control options during your visit?") to identify patients eligible to answer the PCCC survey question. Patients’ PCCC responses may be captured using electronic or paper collection with all eligible patients who report receiving contraceptive counseling receiving the survey. There have been no changes to the measure specifications since the initial application.
We acknowledge that there is the potential for some missing data, given that procedures require administration of a patient-reported outcome measure that is not generally part of routine care. However, missing data has not exceeded 5% in all applications that we are aware of. The brevity of the survey was intentional to mitigate patient burden and facilitate high completion rates.
Additionally, we believe the PCCC has limited susceptibility to inaccuracies. The measure was developed at a 3rd grade reading level and has been well-validated in English and Spanish, with proven face and content validity. The parsimonious nature of the measure, comprised of clear, positively-worded items, suggests it unlikely to be affected by survey-fatigue-related or comprehension-related inaccuracies in self-reported data. Further, the anonymous survey collection minimizes social desirability bias. Data entry errors (from paper responses) can be minimized via double data entry or validation scripts. In electronic formats, entry errors are virtually eliminated.
The PCCC is designed to be low-burden on patients and to be administered by nonclinical staff. Thus the PCCC does not affect clinician workflow, nor does it interfere with diagnostic decisions, provider-patient interactions, or documentation processes.
Barriers and mitigation strategies
Reports from healthcare entities have identified some implementation barriers to PCCC collection.
Staff time and integration into healthcare team workflows. Agencies have reported costs in staff time dedicated to survey collection, data entry, and analysis. Since it is not appropriate for the clinical provider to administer the survey, staff must be designated with the role of data collection. Moreover, communication needed between provider and support staff about who received contraceptive counseling can be an added burden on workflow. However, multiple strategies have been leveraged to reduce this resource burden. Integrating the PCCC into existing patient experience surveys used by clinician group/practices, and/or leveraging existing infrastructure, such as posting notes in the EHR or sending the survey via post-visit patient portal messages, streamlined staff effort in administration. Collecting surveys by electronic means, such as a survey platform (e.g. Qualtrics) decreased data entry burden generated from paper survey collection.
Patient engagement. The PCCC requires patient participation in the completion of the brief survey. Some agencies have reported challenges with patient engagement. Strategies employed to improve patient responsiveness include: sending follow-up texts to patients post-visit, leveraging multimodal data collection strategies, posting QR codes with a link to the survey in the exam room, and encouraging completion at the time of visit.
No barriers have been reported related to PCCC interpretation. The measure is simple to calculate and has a clear higher-is-better interpretation. Actions to improve scores are described in section 6.
PCCC is designed to be administered as an anonymous survey in order to minimize social acceptability bias. Implementation guidance highlights that the survey should not be collected by the same person who conducted the contraceptive counseling and that survey should never be connected to the patient’s electronic health record. Thus, PCCC data collection presents no confidentiality concerns.
For data reporting, the recommended panel size of 30 is sufficient to protect unintentional identification of specific patients. If, for quality improvement purposes, clinician group/practices choose to report PCCC scores disaggregated by patient demographics, we advise that scores are not reported for subgroups with fewer than 5 observations in order to both protect patient confidentiality and to increase reliability of subgroup scores.
Since its initial application, we made changes to the levels of analysis, specifically removing individual: clinician level and replacing facility level with clinician group/practice level. The former was due to the steward's limited ability to gain recent data with which to conduct updated testing and the latter was as a correction to our prior application, as we recognized that our testing and attribution was in fact more appropriately described as clinician group/practice. We also adjusted the eligible age range from 15-45 to 15-44 years to align with other contraceptive care measures. None of these updates were made due to feasibility issues or feedback.
Feasibility strengths of the measure include its short length (4-items), use of plain language, flexibility in terms of collection modality, and simple scoring.
Based on feedback received from the field, we continue to assess the feasibility of the measure and adjust implementation guidance as needed. To support fidelity in and ease of implementation, we provide templates and tutorials on data collection, analysis, and interpretation.
Proprietary Information
Scientific Acceptability
Testing Data
Data used for reliability testing as well as performance gap and closing the care gap analyses (section 2.4 and 3) were derived from three quality improvement projects completed between 2022 and 2024. The first was a quality improvement learning collaborative with ten community health centers, with PCCC data collection from June-September 2022. The second was an implementation project conducted with the state Title X recipient and collecting data from 13 Title X subrecipient clinician group/practices in one northeastern state from March 2024-June 2025. The third source of data was an implementation project with 12 Title X agencies across the U.S., with data collected from June-September 2024. In all cases the PCCC was fielded as a standalone patient survey using the data collection methods described in section 1.18.
Data for validity testing were collected as part of a statewide evaluation of a contraceptive access initiative and were embedded in a broader survey, which was fielded to patients at 24 clinician group/practices in two states ending in Winter 2021. Patients were invited to complete the survey by a staff member from clinic waiting rooms/check in areas prior to their appointment, then completed a survey that included the PCCC post-visit electronically on a tablet.
Project 1: June-September 2022
Project 2: March 2024-June 2025
Project 3: June-September 2024
Statewide evaluation: October 2018- December 2021
We used the composite dataset derived from three quality improvement projects for reliability testing, for performance gap analysis in section 2, and for the closing care gaps analysis in section 3.
The PCCC is commonly fielded as a standalone measure. As a result, available data does not routinely include the additional items needed for accountable-entity validity testing. We were able to use data from a statewide evaluation for validity testing. However, this source used a variation of the response options for the PCCC. Specifically, the questions stems were phrased as declarative statements instead of questions and the standard response options for the currently endorsed PCCC are “Poor”, ”Fair”, “Good”, “Very good”, and “Excellent”, whereas in this survey, it used a Likert response option array of “Disagree” “Slightly disagree”, “Moderately agree”, "Very much agree”, and “Completely agree."
Our sample for reliability testing included 35 clinician group/practices. Clinician group/practices were from 18 states distributed across all regions of the U.S., with the majority in the Northeast: 56% Northeast, 19% Midwest, 12% Southwest, 9% Northwest, and 3% Southeast. Seventeen clinician group/practices were primarily sexual and reproductive health-focused clinician group/practices, 15 were primary care health centers, and 2 were school-based health centers. Clinician group/practices ranged in size and volume, serving between approximately 2,600 and 62,000 patients annually.
Our sample for validity testing included 24 clinician group/practices, including 10 located in South Carolina and 12 in Alabama. Seven were Federally Qualified Health Centers and 17 were Health Department practices. Clinician group/practices ranged in size and volume, serving between approximately 1,900 and 6,500 annually.
The characteristics of the patient respondents by clinician group/practice are provided in Section 7, Supplemental Tables 2a and 2b.
Overall, across the sample used for validity testing, the average age was 28 years. By race and ethnicity, 16% identified as Black or African American, 40% identified as Latina or Hispanic, 31% identified as White, 3% identified as Asian, 7% identified as Multi-racial, less than 1% identified as Native Hawaiian/Pacific Islander, Native American or Alaska Native, or Middle Eastern or Arab, and 2% identified as some other race. Eighty percent completed the survey in English, 19% completed the survey in Spanish, and 1% completed in some other language. Seven percent identified as a person with a disability and 26% identified as gay, lesbian, bisexual, or some other queer identity.
Across the sample used for validity testing, the average age was 26 years. By race and ethnicity, 50% identified as Black or African American, 41% identified as Latina or Hispanic, 31% identified as White, 12% identified as Asian, 1% identified respectively as Native American or Alaska Native or with some other race/ethnicity, and less than 1% identified as Pacific Islander. Twelve percent identified as gay, lesbian, bisexual, or some other queer identity. Data on survey language completion was unavailable and disability status was not collected.
Reliability
Accountable entity reliability
For both conceptual and analytic reasons, our calculation of the performance score used a dichotomous scoring system, in which all surveys reporting the highest rating (20/20) was given for all four questions are considered a positive score, whereas any survey in which a less-than-optimal rating on any of the four questions is considered a negative score. To assess accountable entity reliability, we used the signal-to-noise method suggested by Nieser and Harris [1]. Signal-to-noise is used to estimate how much of the variation in performance scores is due to actual difference between entity performance (signal) and random variation or measurement error (noise). This signal-to-noise ratio ranges between 0 when all of the variability can be attributed to non-performance sources of variation (e.g., measurement error) and 1 when all the variability is due to true differences in quality of care across clinician group/practices. The Nieser and Harris approach is calculated as a function of sample size and beta-binomial parameter estimates and is appropriate for assessing the reliability of the PCCC, as each respondent represents a binary opportunity for a clinician group/practice to achieve a top-box overall rating of highest rating. This approach is aligned with the Partnership for Quality Measurement’s recommendations [2]. To calculate the maximum likelihood estimates of the alpha and beta parameters, we utilized the R code CalcBetaBin, as developed by Nieser and Harris. Sample size was then inserted into the formula to generate reliability estimates for each clinician group/practice.
References
1. Nieser KJ, Harris AHS. Comparing methods for assessing the reliability of health care quality measures. Stat Med. 2024;43(23):4575-4594. doi:10.1002/sim.10197
2. Partnership for Quality Measurement. Reliability Guidance for the Endorsement and Maintenance (E&M) of Clinical Quality Measures. Batelle; 2025. Accessed February 20, 2026. https://p4qm.org/sites/default/files/2025-10/G00200-EM-Educational-Mate…
Table 2 displays the estimates of signal-to-noise reliability by decile of clinician group/practice. Reliability ranged from 0.737 (panel n=16) to 0.979 (panel n=294), with an average reliability of 0.876.
Our results indicate high reliability across our clinician group/practice-level sample (0.727 – 0.979) and exceed the CBE-recommended guidance for endorsement of “greater than or equal to 0.6 for 70% or more of the accountable entities”[1].
Testing submitted with our initial application suggested that a panel size of 50 was necessary to achieve high reliability (we used a conservative threshold of >0.80). However, testing conducting as part of this maintenance submission demonstrates that high reliability can be achieved with a smaller panel size. Based on these testing results and applying the Neiser and Harris formula to a range of panel sizes, we recommend accountable entities utilize a minimum panel size of 30 respondents to achieve the same level of reliability (>0.80).
REFERENCES
1. Partnership for Quality Measurement. Reliability Guidance for the Endorsement and Maintenance (E&M) of Clinical Quality Measures. Batelle; 2025. Accessed February 20, 2026. https://p4qm.org/sites/default/files/2025-10/G00200-EM-Educational-Mate…
Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.876 | 0.727 | 0.741 | 0.826 | 0.857 | 0.873 | 0.891 | 0.897 | 0.900 | 0.914 | 0.917 | 0.958 | 0.979 |
| Mean Performance Score | 0.728 | 0.91 | 0.890 | 0.705 | 0.827 | 0.866 | 0.725 | 0.555 | 0.755 | 0.681 | 0.681 | 0.620 | 0.989 |
| N of Entities | 35 | 2 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 4 | 1 |
| N of Persons / Encounters / Episodes | 2022 | 32 | 52 | 116 | 108 | 166 | 136 | 196 | 157 | 218 | 192 | 681 | 294 |
Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.876 | 0.727 | 0.741 | 0.826 | 0.857 | 0.873 | 0.891 | 0.897 | 0.900 | 0.914 | 0.917 | 0.958 | 0.979 |
| Mean Performance Score | 0.728 | 0.91 | 0.890 | 0.705 | 0.827 | 0.866 | 0.725 | 0.555 | 0.755 | 0.681 | 0.681 | 0.620 | 0.989 |
| N of Entities | 35 | 2 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 4 | 3 | 4 | 1 |
| N of Persons / Encounters / Episodes | 2022 | 32 | 52 | 116 | 108 | 166 | 136 | 196 | 157 | 218 | 192 | 681 | 294 |
Validity
Construct validity
Convergent validity was assessed by examining associations between the PCCC and 1) a measure of patient overall satisfaction with the clinical visit and 2) a measure of contraceptive method satisfaction that were collected in the same modality within the same survey as the PCCC.
Overall satisfaction. Patients were asked "Overall, how satisfied are you with the talk you had today with your provider about birth control methods?” with 5-point Likert-type response options ranging from “Very dissatisfied” to “Very satisfied.” The choice of this measure as a comparator was based on the fact that measures of satisfaction often correlate with measures of patient-centered processes of care but are considered distinct. We conceptualized the PCCC as being more specific than measures of satisfaction, as satisfaction measures tend to be informed by expectation disconfirmation theory (i.e., the extent to which an experience exceeded or fell below expectations [1,2]) and have additional limitations of lack of differentiation and lack of specificity of measured behaviors [3]. In contrast, the items in the PCCC assess the extent to which the patient experienced or perceived specific types of communication and exchanges consistent with patient-centered care. Given their conceptual relationship, we hypothesize these measures to be highly and positively correlated.
Method choice: Patients were given the following statement: “The birth control method I will use after today’s visit is the best method of birth control for me.” With 4-point Likert-type response options ranging from “disagree” to “Very much agree.” The choice of this measure as a comparator was based on the hypothesis that positive experience with contraceptive counseling would correlate with positive feelings toward contraceptive method choice. However, feelings about the material result from the contraceptive counseling (i.e. the birth control method) are distinct from the experience of care provided. We hypothesize a weak to moderate positive correlation.
To align with PCCC scoring, for each of the comparator variables, we created a binary variable, comparing responses in the highest or most positive rating category (“Very satisfied”/ “Very much agree”) to all other responses.
Aligned with guidance for PRO-PMs [4], we first tested the constructs at the individual (Patient Reported Experience Measure [PREM]) level, and then conducted testing at the clinician group/practice 9Patient Reported Experience Performance Measure [PRE-PM]) level, both using the South Carolina dataset (see 5.1.1).
For the PREM level, we conducted two simple univariate logistic regression models with PCCC as the outcome and overall satisfaction with counseling and method satisfaction as predictors respectively.
For the PRE-PM level, we averaged PCCC scores, overall satisfaction, and method satisfaction scores at the unit of analysis (clinician group/practice). We estimated Pearson’s correlation coefficient (r) to assess strength and direction of the linear relationship between the mean PCCC score by clinician group/practice and the mean scores of each of the comparator variables. We then conducted two univariate Ordinary Least Squares regression models with PCCC score (outcome) and overall appointment satisfaction as predictors averaged at the clinician group/practice level.
Analysis of missing data
We identified the extent and distribution of missing items among respondents. Missingness did not exceed 1% for any of the PCCC questions, with overall missingness across the scale of 1.5%. The best birth control variable had a missingness of 4.6% and the overall satisfaction variable had missingness of 7.1%. Given low level of missingness, we conducted a complete case analysis, aligned with best practice of handling item-level missingness [5].
Assessment of Non-Response Bias
This PRE-PM is collected through an anonymous survey and, by design, not connected to other sources of patient information, such as electronic health records. This practice serves to protect data quality and improve response rates, as patients may be concerned about care consequences if they report lower scores and, as a result, choose to either record higher scores that do not reflect quality of care or refuse to respond to the survey if they know or suspect it will be linked to their patient records. Thus, we do not have demographic information on nonrespondents and cannot assess differences between groups. Moreover, the survey is distributed to patients identified as likely having received contraceptive counseling in their clinical visit. This is verified when respondents answer the survey screening question, confirming that they did, in fact, receive counseling. Without confirmation of eligibility of nonrespondents, we do not know the true population of those who received contraceptive counseling among those who were contacted, and thus, cannot directly assess differences between that population of interest and the sample who completed the survey.
To approximate how well the responders accurately reflect the demographics of the target patient population, we compared the demographics of the overall female patient population in the desired age range to PCCC respondents within a subsample of 9 of our testing entities (see Tables 2.a-i in section 5.3.4a). Specifically, we used electronic health data to identify the age and, race and ethnicity among female patients ages 15-44 years from the same time period as PCCC collection at those entities. In addition, eight of the nine sites also provided us the percentage of patients by preferred language.
REFERENCES
1. Kupfer JM, Bond EU. Patient Satisfaction and Patient-Centered Care: Necessary but Not Equal. JAMA. 2012;308(2):139. doi:10.1001/jama.2012.7381
2. Williams S, Weinman J, Dale J, Newman S. Patient expectations: What do primary care patients want from the GP and how far does meeting expectations affect patient satisfaction? Fam Pract. 1995;12(2):193-201. doi:10.1093/fampra/12.2.193
3. Cella DF, Hahn EA, Jensen SE, Butt Z, Nowinski CJ, Rothrock N. Methodological Issues in the Selection, Administration and Use of Patient-Reported Outcomes in Performance Measurement in Health Care Settings. Paper Prepared of the National Quality Forum. 2012.
4. National Quality Forum. Patient Reported Outcomes (PROs) in Performance Measurement. 2013. https://www.qualityforum.org/Publications/2012/12/Patient-Reported_Outc…
5. Heymans MW, Twisk JWR. Handling missing data in clinical research. Journal of Clinical Epidemiology. 2022;151:185-188. doi:10.1016/j.jclinepi.2022.08.016
At the clinician group practice level, the PCCC was strongly correlated with the measure of overall visit satisfaction (r = 0.738) and weakly correlated with the measure of method satisfaction (r = 0.214), See tables in 5.3.4a for full results.
Our construct validity results are largely consistent with our hypotheses, demonstrating validity. First, we found a strong positive association with PCCC and the measure of overall satisfaction (the more conceptually related measure), as hypothesized. Between the PCCC and the best birth control we found a strong correlation at the individual level that was attenuated at the clinician group/practice level, with a weak, positive linear relationship (r=0.21) that was not statistically significant in regression results. This is not inconsistent with our hypothesis of a weak to moderate positive correlation, as feelings about contraceptive methods may be influenced by factors beyond the quality of counseling, such as limitations with the conceptive method options available on the market, resulting in patients having to choose between options that may not align with their preferences, e.g. comparing side effect potential, modality and preference for frequency of dosing, and so forth. Moreover, with a hypothesized small effect size and the results showing the significant relationship at the individual level and lack of statistical significance at the clinician group/practice level suggests the lack of correlation may also be affected by limited sample size (n=24) at the clinician group/practice level. A larger sample would increase precision, stability, and possibly, statistical significance of the correlation.
We note that the response options utilized in the version of the PCCC used for validity testing vary from those used in the endorsed version of the measure, however we do not believe this affects the applicability of the findings. The scale consistently uses five response categories, providing for similar symmetry, and assesses the same construct. Moreover, the use of topbox scoring means any impact of interpretation issues between middle and low values are less relevant and would not affect performance scoring. Also, the distribution of PCCC score across the sample (range: 43.6% - 74.3%) is consistent with the range and distribution of scores of the endorsed version of the measure, such as presented in Section 2.4, suggesting it was interpreted similarly to the endorsed version of the measure. External evidence also supports limited impact of response format. One study looked at the effect of a change from Likert type response options to Item-Specific Response Options, which presents individuals with a direct question (rather than a statement to which they are asked to agree or disagree) and a set of tailored response categories that match its content. While there were some differences in the distribution of responses by response option type, the magnitude was negligible [1].
Moreover, analysis of this data is consistent with peer-reviewed evidence demonstrating that the PCCC has the ability to distinguish between groups who have different experiences of care as depicted by different scores. These findings are supplemented with independent testing conducted externally. Specifically, an independent organization, Upstream USA, conducted validity testing at the individual level with data collected from partner clinics in 2021-2022 [2]. They used a similar measure about experience of care delivered compared to PCCC to assess construct validity and found high levels of correlation (aOR = 1.13, 95% CI: 1.05, 1.22). They used the version of the PCCC endorsed by the CBE. While this analysis was not conducted as part of this application and is not at the clinician group/practice level of analysis, it does illustrate useful correlations that support the interpretation that PCCC continues to be a valid measure.
Nonresponse bias assessment
Demographic distributions of PCCC respondents compared to the target patient population by age and primary language were comparable in most clinician group/practices, Exceptions by age include no capture of 15-20 year olds (5% of target population) by clinician group/practice 3, and underrepresentation of 15-20 year olds by clinician group/practice 5 (2% v. 21%), clinician group/practice 8 (6% v. 17%), and clinician group/practice 9 (8% v. 35%). Exceptions by language are underrepresentation of Spanish-speakers by clinician group/practice 3 (74% v. 94%) and clinician group/practice 6 (2% v. 11%).
Assessment of race/ethnicity was complicated by data quality issues, namely, high levels of missingness in the EHRs for these variables. Race and ethnicity are typically categorized separately in EHRs. However, because Latine/Hispanic identity is a racialized ethnicity [3], the variable used alongside the PCCC is a combined race/ethnicity variable. We attempted to make a comparable variable from cross-referencing race and ethnicity data in the EHR datasets. However, five out of nine sites did not have recorded ethnicity data for more than 50% of observations and three out of nine did not have recorded race data for more than 30% of observations. Thus, we were unable to accurately distinguish a Latine/Hispanic population and build a meaningful comparison variable to the PCCC race/ethnicity variable. Likely, results for those clinician group/practices overestimate the White populations served and underestimate the Latine/Hispanic population. Distributions across other racial categories were fairly comparable, with the exception of Clinician group/practice 7 and 9, each with a 10-point difference is distribution of Black patients, the former underrepresenting and the latter overrepresenting Black patients among PCCC respondents.
With these challenges taken into account, we believe this investigation suggests that PCCC sampling produces a reasonable comparable sample to the demographic profile of patients served.
We interpret these findings alongside our analyses from our initial application, in which we were able to capture survey nonresponse from nine accountable entities. In order to test what effect biased non-response would have on performance scores, we imputed missing data by provider and facility under the conservative assumptions that all individuals with missing data were either 25% more or less likely to give a top-box score than were respondents. Ultimately, we found that survey nonresponse in that sample did not meaningfully under or over-estimates of provider performance.
REFERENCES
1. Aletras V, Chatzopoulos S, Kalouda M, Niakas D, Flokou A. Patient Satisfaction Measurement: A Comparison of Likert and Item-Specific Response Options Scales. Healthcare. 2025;13(23):3017. doi:10.3390/healthcare13233017
2. Shea M, Decker E, LeRoy L, Winter M. Testing the validity and reliability of the Person-Centered Contraceptive Counseling (PCCC) Performance Measure in a Real-World Contraceptive Access Program. Contraception. 2023;123:110039. doi:10.1016/j.contraception.2023.110039
3. Figuereo V, Calvo R. Racialization and Psychological Distress among U.S. Latinxs. J Racial and Ethnic Health Disparities. 2022;9(3):865-873. doi:10.1007/s40615-021-01026-3
Risk Adjustment
We do not believe that risk adjustment is justified. While it is possible that different demographic groups may report different results on the PCCC measure, this would likely represent true differences in patient-centeredness due to the manner in which the questions are framed and the fact that the concepts of respect and attention to preferences and adequate provision of information are generally desirable. This interpretation is supported by prior work demonstrating broad alignment in women’s preferences for contraceptive counseling across race and ethnicity, particularly with respect to respect, attention to preferences, and provision of adequate information [1,2].
With respect to language, we note that our development of the measure included a rigorous process of developing the Spanish language version alongside the English language version [3]. This process included ensuring equivalence of items across languages through cognitive interviews, collecting data on item importance from Spanish and English speakers, and using these data to determine the items included in our measure. We also conducted face validity testing with both Spanish and English speakers. While in our initial testing of the PCCC measure submitted to the National Quality Forum (NQF), some differences by language were observed, these were not consistent across sites. Notably, in at least one site that demonstrated strong attention to language-concordant and culturally responsive care, Spanish-speaking patients reported higher PCCC scores than English-speaking patients.
Combined with our attention to equivalence by language in the development process, this pattern indicates that differences by language are not driven by bias in how the measure captures patient-centeredness, but rather reflect true differences in the quality of care delivered. This interpretation is consistent with our broader analytic framework, in which variation in scores across demographic groups is understood to represent meaningful differences in patient experience rather than limitations of the measure itself.
With respect to the question of stratification, studies suggest that women of color receive poorer quality contraceptive counseling than their white counterparts [4]. These disparities are rooted in the long history in the United States of coercion on the part of the reproductive health care system towards women of color, including forced sterilization and pressure to use long-acting contraceptive methods [5,6]. While this suggests that stratification by race/ethnicity may be desirable to assess differences in care, we currently lack sufficient data to conduct necessary reliability and validity testing on stratified measures. We plan to evaluate stratification by race/ethnicity and language in future applications.
REFERENCES
1. Dehlendorf C, Levy K, Kelley A, Grumbach K, Steinauer J. Women’s preferences for contraceptive counseling and decision making. Contraception. 2013;88(2):250–256. doi:10.1016/j.contraception.2012.10.012
2. Becker D, Klassen AC, Koenig MA, LaVeist TA, Sonenstein FL, Tsui AO. Women’s perspectives on family planning service quality: an exploration of differences by race, ethnicity and language. Perspect Sex Reprod Health. 2009;41(3):158–165. doi:10.1363/4115809
3. Dehlendorf C, Fox E, Silverstein IA, Hoffman A, Campora Pérez MP, Holt K, Reed R, Hessler D. Development of the Person-Centered Contraceptive Counseling scale (PCCC), a short form of the Interpersonal Quality of Family Planning care scale. Contraception. 2021;103(5):310–315. doi:10.1016/j.contraception.2021.01.008
4. Becker D, Tsui AO. Reproductive health service preferences and perceptions of quality among low-income women: racial, ethnic and language group differences. Perspect Sex Reprod Health. 2008;40(4):202–211. doi:10.1363/4020208
5. Stern AM. Sterilized in the name of public health: race, immigration, and reproductive control in modern California. Am J Public Health. 2005;95(7):1128–1138. doi:10.2105/AJPH.2004.041608
6. Roberts D. Killing the black body: race, reproduction, and the meaning of liberty. New York (NY): Pantheon Books; 1997
Use & Usability
Use
PPFA is a national network of affiliates that provide sexual and reproductive healthcare. PPFA utilizes PCCC within their ongoing patient engagement survey fielded by Press Ganey and that is compiled quarterly and used for internal quality improvement.
PPFA affiliates cover all 50 states and Washington, D.C., serving millions of patients annually. In 2024, PPFA collected PCCC surveys from 27,136 patients across affiliates.
clinician group/practice, ambulatory care: clinic
ICAN! Provides workforce development and training to FQHCs with the goal of expanding high-quality contraceptive access in Illinois. They use PCCC as a quality improvement tool as part of their health center workforce development and training program.
ICAN!'s Quality Hub Network includes 24 community health centers serving over 321,000 female patients of reproductive age annually through more than 200 individual health center locations throughout Illinois (Chicago/Cook County, Northwest, Central, and Southern Illinois). 57% of Quality Hub Network patients are on Medicaid, and 18% are uninsured or self-pay. 51% of patients identify as Black, 29% as Hispanic/Latino, 25% as White, and 4% as AAPI. Since 2021, they have collected 900 PCCC surveys across 15 of their 24 partner clinics.
clinician group/practice, ambulatory care: clinic
Upstream USA is a nonprofit that works with healthcare organizations to expand access to patient-centered contraceptive care. They provide training and technical assistance to health centers and use PCCC as a measure within their pre- and post-training/quality improvement efforts with health centers.
Since 2021, Upstream has fielded the PCCC with 155 healthcare organizations across 34 states. As of March 13, 2026, they have received 66,835 patient responses to the PCCC from the above 155 healthcare organizational partners.
clinician group/practice, ambulatory care: clinic
This measure would be appropriate for use in reporting and/or pay for performance accountability programs for ambulatory clinic sites serving female patients aged 15-44 years, measured at the clinician group/practice level, focused on primary care and reproductive health sites.
Usability
The PCCC is measure focused on the quality of contraceptive care delivery. Entities can engage in a diversity of quality improvement activities to improve performance. Quality improvement actions may vary in amount of effort needed to achieve favorable results, in accordance with what scores indicate about performance (e.g. how much improvement is needed) and the size and structure of the accountable entity.
Broadly, entities seeking to improve scores can provide provider training on person-centered contraceptive counseling skills, either provided internally within the agencies or through leveraging existing training materials, such as the e-learning course provided by Partners in Contraceptive Choice and Knowledge (PICCK). For more targeted training, entities can examine PCCC scores by item to identify if patients are reported in a particular deficit in care delivery needs, (e.g. delivering enough information to make a decision about their contraception). An evaluation of a contraceptive access initiative in South Carolina (from which our validity data were drawn), which provided trainings on reproductive autonomy and person-centered contraceptive care, found that post-intervention, patients had higher odds of reporting topbox PCCC scores compared to patients at comparison clinics [1]. Difficulties of this approach include provider time and buy-in; however training can make scaled to meet provider time demands.
For more targeted quality improvement efforts, entities can examine PCCC scores by patient subgroups. If differences in scores are noted by patient subgroup, such as by Spanish-speaking patients, younger patients, or a particular racial or ethnic group, entities should focus quality improvement efforts on improving care within those patient groups. To do so, entities can leverage expertise within staff and engage patient advisory boards to identify what may be contributing to the subpar scores, from which entities can build a quality improvement plan, such as improving language services or providing cultural humility training. In a 2025 publication, we provide an example of an FQHC who utilized engaged staff and patients to develop a quality improvement strategy to improve the score among Spanish-speaking patients [2]. How difficult quality improvement activities are is dependent on the findings of the needs assessment and extent of quality improvement infrastructure.
Lastly, entities may utilize a contraceptive need screening tool such as the Self-Identified Need for Contraception (CBE#4655e) as a means of targeting contraceptive counseling only to those patients who seek want to discuss pregnancy prevention. Since contraception is a preference sensitive decision, patients who do not want to discuss contraception but are engaged in counseling by the provider may report low quality care, as counseling is misaligned with their preferences for their care appointment. Targeting the self-determined appropriate patient population will improve contraceptive care delivery and performance scores. There may be some initial difficulties integrating SINC into the EHR and clinical workflows, however feedback from users suggest the addition into workflows is minor because it’s one question that can be asked during rooming procedures and implementation of SINC may increase provider time and efficiency by focusing on contraceptive counseling only among patients who are interested.
Following the implementation of these interventions, we recommend re-measurement of the PCCC to track change and reevaluate quality. When used in combination other currently endorsed contraceptive access measures, such as the Contraceptive Use electronic clinical quality measures (CU-SINC, CBE #3699e & 3682e), PCCC can also serve as a tool for identifying whether attention to method provision is leading to a decrease in attention to patient-centeredness and allow for intervention if such an effect is observed. In a quality improvement learning collaborative that we ran in 2022-2023 and that included a pre-post assessment of PCCC scores alongside CU-SINC, after nine months, PCCC scores improved from 2% to 26% among healthcare entities that engaged in dedicated training and accountability practices around contraceptive care delivery [3].
References
1. Smith MG, Zeng L, Khoury AJ. Evaluation of patient experiences with contraceptive counseling during the South Carolina Choose Well contraceptive access initiative. Contraception. 2026;155:111246. doi:10.1016/j.contraception.2025.111246
2. Wingo E, Gibson L, Dehlendorf C. Heeding lessons of our past: Centering sociohistorical context and health equity in efforts to expand contraceptive access. Contraception. 2026;155:111270. doi:10.1016/j.contraception.2025.111270
3. Dehlendorf C, Wingo E, Gibson L, Goetsch-Avila S, Kriz R, Hessler D. Advancing Equitable, Person-Centered Contraceptive Care Using Data-Driven Quality Improvement. J Am Board Fam Med. 2025;38(5):791-801. doi:10.3122/jabfm.2025.250073R1
We have obtained feedback on PCCC through multiple means. First, with clinician group/practices that we worked with on PCCC-focused implementation and quality improvement (n=35, across three project cohorts), we solicited group feedback at the end of the projects, as well as conducted individual interviews with clinic representatives about their experience with the measure.
To obtain feedback from entities independently using PCCC, we fielded a survey to entities known to have used the PCCC over the past 5 years. The survey asked about feasibility of measure implementation, use and usability. We conducted individual follow-up calls with a subset of respondents for clarification and further information as needed.
Little concern was raised about the validity of the measure itself or about its specifications. Many entities reflected that the PCCC is a valuable tool that enables meaningful assessment and quality improvement on contraceptive care delivery. Many organizations, including Planned Parenthood Federation of America, the Illinois Contraceptive Access Now (a state-based non-profit contraceptive access initiative), and Upstream (a national non-profit contraceptive access organization that works with federally qualified health centers), integrate PCCC into broader patient experience surveys and track PCCC scores before and after quality improvement interventions, feeling that the PCCC is a valid and reliable instrument for assessing patient experience of contraceptive counseling.
In 2024, some federally qualified health centers in the Massachusetts Department of Health network noted some interpretability concerns with the PCCC among Haitian Creole immigrant patient populations. The FQHCs created and were using their own translation of the PCCC, which has not been validated, to field the survey to this population.
Overall, feedback received primarily focused not on measure specifications, but instead on implementation and sustainability challenges, in the following categories (also described in section 4):
- Challenges in sustained staff engagement necessary to collect PCCC surveys. This was expressed as a concern for the sustainability of collection over time. Depending on the workflow used, healthcare staff are often responsible for identifying potentially eligible patients and providing them with the paper survey or a link to an electronic version of the survey. These staff have many competing priorities, making it sometimes challenging to incorporate the survey into their workflows, particularly if collection is sustained over long periods of time, such as ongoing collection.
- Challenges in patient engagement in completing the survey. Some also report challenges in motivating response from patients to complete the survey.
- Panel size. Minimum of 50 surveys (previously recommended panel size) has been hard to achieve in low-volume clinics.
We did not receive any feedback that called for any changes to measure specifications and have made no changes to the specifications in response to measure feedback. We plan on developing and validating a low-literacy version of the scale to improve capture of accurate data from low-literacy populations and will present that in future maintenance applications. Currently, we recommend clinician group/practices with sizeable low-literacy populations utilize screen reader technology for electronic surveys.
We continuously engage entities using the PCCC and update our implementation guidance in response to feedback to include data collection strategies to meet the needs of different healthcare settings and patient populations. For the challenges raised above, we recommend the following:
Staff engagement: For all clinician group/practices initiating data collection, we recommend: early engagement with staff when incorporating data collection protocols; providing information on the motivation and use of the data to be collected; using accountability milestones and internal communication touchpoints to stay on target, as well as staff incentives to increase motivation. We permit diverse data collection strategies that can rely on staff to a varying degree in order to meet the data collection needs of different clinics and patient populations. For contexts where staff capacity may compromise collection, we recommend low-burden collection strategies, such as incorporating the PCCC into existing patient engagement surveys (if applicable) or utilizing post-visit patient portal messages. To decrease survey burden, guidelines suggest collecting PCCC surveys once or twice a year for monitoring, as opposed to ongoing collection. This serves to capture change over time while limiting potential of collection fatigue that could result from continuous collection.
Patient engagement: In our guidelines, we suggest that clinician group/practices try alternative collection strategies. Feedback has suggested that suitability of collection strategies (paper versus electronic collection) varies by setting (see section 4.1b). Clinics can also offer monetary incentives for completion. We also provide talking points to use with patients that explicate the important role of patient feedback and prompt clinician group/practices to communicate how the data will be used.
Low-volume settings: As a result of our renewed reliability analyses, we now recommend a lower threshold for a high-reliability panel, decreasing the recommended panel size from 50 to 30. This new guideline is more in line with what has been attainable for low volume clinician group/practices.
Across the Planned Parenthood Federation of America affiliates using the Press Ganey survey, between quarter one of 2022 and quarter one of 2026, overall performance scores increased from 71.7% to 76.9%, however significant variation remains by practice. In the same time period, performance scores increased within racial and ethnic subgroups: from 65.8% to 73.0% among Black patients, from 68.3% to 73.1% among Latine patients, and from 77.0% to 83.1% among White patients. However gaps between scores by racial and ethnic group persist, aligned with findings presented in section 3.
We have had no unexpected findings.
Comments
Staff Preliminary Assessment
CBE #3543 Staff Assessment
Importance
Strengths:
- A clear logic model is provided, depicting the relationships between inputs (e.g., collecting person-centered contraceptive care (PCCC) surveys from patients and distributing counseling tools and visual aids), and desired outcomes (e.g., patients who receive contraceptive counseling can report on their counseling experience; improved quality of contraceptive counseling provided; improved reproductive health outcomes). This model demonstrates how the measure’s implementation will lead to the anticipated outcomes.
- The problem this measure addresses presents a significant burden for patients. Data from two national surveys – National Survey of Family Growth from 2017-2019 (included retrospective version of the PCCC (CBE #4825)) and Kaiser Family Foundation (KFF) survey from 2022 and 2024 – demonstrated a gap in optimal counseling with only 58%, 40%, and 42% of respondents, respectively, reporting optimal quality of contraceptive care received. Through the use of the PCCC measure, data from 2022-2023 found a range of scores from 30% to 95% indicating differential care at the clinician group/practice level.
- This measure is supported by a comprehensive literature review, including systematic reviews with high evidence quality and high-quality empirical studies, demonstrating a clear net benefit in terms of improved outcomes such as contraceptive continuation at six months, improved engagement with care in various contexts, and supporting positive pregnancy and birth outcomes (e.g., recued maternal mortality), for patients aged 15-44 years who were assigned female at birth, who are not currently pregnant, and who received contraceptive counseling as part of their visit.
- Data from three quality improvement projects from 2022 to 2024 show a performance gap, with decile ranges from 38.3% to 96.6%, indicating variation in measure performance. The three quality improvement projects that data were derived from are the following:
1. A quality improvement learning collaborative with ten community health centers; data collected from June-September 2022
2. An implementation project conducted with the state Title X recipient and collecting data from 13 Title X subrecipient clinician group/practices in one northeastern state; data collected from March 2024-June 2025
3. An implementation project with 12 Title X agencies across the U.S.; data collected from June-September 2024 - Description of patient input supports the conclusion that the measure PRE-PM is meaningful with at least moderate certainty. Patient input was obtained through cognitive interviews and iterative engagement with the Person-Centered Reproductive Health Program’s Patient Stakeholder Group (PSG), a standing group of individuals assigned female at birth.
Limitations:
- None identified.
Rationale:
- This maintenance measure meeting all criteria for ‘Met’ for importance due to the significance of the problem it addresses and its significant anticipated impact, its robust evidence base, a documented performance gap, and well-articulated logical model, making it essential for addressing patients’ contraceptive counseling experiences.
Closing Care Gaps
Strengths:
- The developer provided evidence of gaps in care related to the measure focus for subgroups, including literature review; randomized controlled trial; qualitative research; and a multi-state longitudinal study, and their claim that the measure has helped close care gaps by highlighting persistent differences in reported care quality and highlighting additional subgroups reporting lower rates of high-quality care is credible.
- The measure’s performance was empirically tested across all identified subgroup variables including patient race or ethnicity, age, disability status, sexual orientation, and language; the developer’s rationale for selecting these subgroups is based on existing evidence. Data from the analyses were from three quality improvement projects (described in the review of importance) completed between 2022 and 2024. The analysis employed chi-square tests of independence to assess differences in measure scores across these subgroups. Developers compared scores from the 2026 submission to the PCCC’s initial endorsement submission in 2019.
- The analysis revealed significant differences in performance score by racial/ethnic groups and spoken language. For example, English speakers more often reported highest score compared to Spanish speakers and other language speakers. No statistically significant differences in scores were found by age, sexual orientation, or disability status.
- Based on the findings, the developer noted recommended actions entities can take to close care gaps, including using these findings to identify healthcare disparities and provide resources to improve care for groups within their clinician group/practices, including training providers on person-centeredness using a shared-decision-making approach, as well as providing trainings to address bias and deepen understanding and practice of cultural responsiveness and humility.
Limitations:
- Data on sexual orientation and disability status were not collected in the 2019 sample, therefore developers were unable to complete the comparison.
- There were small cell sizes across a number of subpopulation categories within the data set, therefore, scores within these subcategories may be unreliable.
Rationale:
- This measure meets all criteria for 'Met' due to sufficient assessment of gaps in care with respect to race/ethnicity, age, disability status, sexual orientation, and language, providing crucial insights into how accountable entities can use this measure to improve differences in care for these subgroups. This includes using the findings to identify disparities and provide resources to improve care, training providers on person-centeredness using a shared-decision-making approach, and training to address bias and deepen understanding and practice of cultural responsiveness and humility.
Feasibility Assessment
Strengths:
- The data elements required for measure calculation are collected through patient surveys, through paper collection or electronically, and measure calculation is based solely on information provided by patients responding to the instrument; therefore, data cannot be captured from existing electronic sources.
The developer described how they changed the level of analysis, removing the individual clinician level due to the steward's limited ability to gain recent data with which to conduct updated testing. The facility level of analysis was replaced with clinician group/practice level, as this level is better aligned with the testing and attribution. The eligible age range was also adjusted from 15-45 years to 15-44 years to align with other contraceptive care measures. None of these updates were made due to feasibility issues or feedback.
The developer stated that no feasibility issues were found requiring adjustment of the final measure specifications. - The developer described the costs and burden associated with data collection and data entry, validation, and analysis. They discussed implementation barriers that have been identified by health care entities which include staff time and integration into health team workflows and patient engagement. They also noted mitigation strategies to overcome the barriers identified. To address the staff time and integration barrier, mitigation strategies include integration of the PCCC into existing patient experience surveys used by clinician/group practices; leveraging existing infrastructure; and collecting surveys by electronic means (e.g., Qualtrics). To address the patient engagement barrier, mitigation strategies include sending follow-up texts to patients following their visit; encouraging completion at the time of their visit; leveraging multimodal data collection strategies; and posting QR codes with a link to the survey within the exam room. There has been no reported barriers related to interpretation of the survey. It was developed at a 3rd grade reading level and has been well-validated in English and Spanish. The measure is simple to calculate and has a clear higher-is-better interpretation.
Limitations:
- None identified.
Rationale:
- This maintenance measure meets all criteria for ‘Met’ for feasibility due to its well-documented feasibility assessment, clear and implementation data collection strategy, and transparent handling of patient confidentiality, burden, licensing, and fees. These factors collectively ensure that the measure can be implemented effectively and sustainably in a real-world healthcare setting.
Scientific Acceptability
Strengths:
- Data sources used for reliability analysis are adequately described and include three quality improvement projects which collected data from June to September 2022, from March 2024 to June 2025, and from June to September 2024, respectively.
- The developer conducted signal-to-noise reliability testing at the accountable entity-level. More than 70% of accountable entities meet the expected threshold of 0.6 for signal-to-noise reliability testing and 100% of entities meet the expected threshold of 0.4 for signal-to-noise reliability testing.
Limitations:
- None identified.
Rationale:
- This maintenance measure is rated as 'Met' for reliability because the developer performed the required reliability testing for this measure and results demonstrate sufficient reliability at the accountable entity-level.
Strengths:
- The developer performed the required accountable entity level testing at the clinician level using data collected between 2018 and 2021 from 24 practices in South Carolina and Alabama as part of an evaluation of a statewide contraceptive access initiative. The developer calculated Pearson's correlation between the PCCC measure and two single Likert-scale items, "Overall, how satisfied are you with the talk you had today with your provider about birth control methods?" ('satisfaction') and "The birth control method I will use after today’s visit is the best method of birth control for me.”
- The developer conducted analyses to support equivalence of Spanish and English language surveys and remove the influence of survey language on the measured outcome.
Limitations:
- The small sample size for accountable entity validity testing (n=24 practices) is likely a factor in the non-significant correlation of PCCC with ideal method; however, of potential concern is the lack of representativeness of the validity testing sample. Specifically, the use of two states that the developer noted offer a limited range of available contraception methods may have truncated variance in the ideal method measure. Support for validity based on this analysis might be strengthened if compared with the correlation between PCCC and ideal method in states that offer a fuller range of contraception methods, where a stronger correlation might be expected.
- The developer did not conduct risk adjustment, case-mix adjustment, or stratification. The developer provided a rationale stating that differences in measure score by demographic groups would likely represent true differences in patient care, due to the design of the survey questions and measure focus on concepts of respect and attention to preferences.
- The developer noted potential variation in measure score by race/ethnicity but currently lacks the data to conduct supporting analysis; the developer noted intent to conduct this analysis in future submissions following appropriate data collection.
Rationale:
- This maintenance measure is rated as ‘Not Met But Addressable’ for validity because the validity testing results partially support an inference of validity for the measure, suggesting that the measure somewhat accurately reflects performance on quality resource use and can distinguish good from poor performance to a limited extent.
- The developer did not conduct risk adjustment or stratification, but provided a reasonable rationale for why, supported the rationale with literature, and acknowledged intent to conduct future analysis pending data collection.
Use and Usability
Strengths:
- The measure is currently used in the Planned Parenthood Federation of America (PPFA). Attributes of a suitable program for this measure are described, and these include reporting and/or pay for performance accountability programs for ambulatory clinic sites serving female patients aged 15-44 years, measured at the clinician group/practice level, focused on primary care and reproductive health sites.
- The developer provided a summary of how accountable entities can use the measure results to improve performance. Specifically, entities can engage in training opportunities through e-learning courses provided by Partners in Contraceptive Choice and Knowledge (PICKK). For more targeting training, entities can examine PCCC scores by item to identify if patients are reported in a particular deficit in care delivery needs. For targeted quality improvement efforts, entities can examine PCCC scores by patient subgroups and leverage expertise within staff and engage patient advisory boards to identify what may be contributing to subpar scores, from which entities can build a quality improvement plan. Entities may also utilize a contraceptive-need screening tool (e.g., CBE #4655e) to target contraceptive counseling only to those patients who want to discuss pregnancy prevention to improve contraceptive care delivery and performance scores.
- The developer has obtained feedback through multiple sources. First, with clinician group/practices that they worked with on PCCC-focused implementation and quality improvement, group feedback was solicited and the end of the projects, in addition to individual interview with clinic representatives to discuss their experience with the measure. Second, to obtain feedback from entities independently using PCCC, the developers fielded a survey to entities known to have used PCCC over the past 5 years, asking questions about feasibility of measure implementation, use and usability. Individual follow-up calls were conducted when necessary for clarification or further information. The developer noted that the feedback did not call for any changes to measure specification, therefore the feedback received did not lead to any changes in the measure specifications.
- The developer reported changes in performance between quarter one of 2022 and quarter one of 2026, in which the overall performance score increased from 71.7% to 76.9%, which supports the argument that this measure is usable. Within the same time period, performance scores within racial and ethnic subgroups increased from: 65.8% to 73.0% among Black patients; 68.3% to 73.1% among Latine patients; and 77.0% to 83.1% among White patients.
- The developer reported no unexpected findings.
Limitations:
- None identified.
Rationale:
- This maintenance measure is rated ‘Met’ for use and usability because it is actively used in at least one accountability application, with a systematic feedback approach that allows for continuous updates based on stakeholder feedback. The measure also demonstrates a positive trend in performance results, affirming its ongoing usability. The developer reported no unexpected findings.
Committee Independent Review
(No subject)
Importance
Closing Care Gaps
There is reasonable expectation that this data will help close gap sin care among subgroup populations based on data reported
Feasibility Assessment
There are some limitations as a patient reported measure, but those are reasonably addressed by the developer
Scientific Acceptability
Use and Usability
(No subject)
Importance
Closing Care Gaps
Feasibility Assessment
Could be less burdensome, but not sure of alternative.
Scientific Acceptability
Need larger sample size
Don't have sufficient sample size to test the validity.= per the measure developer
Is reliable, but reliable at doing what?
Missing data prevented some comparability analyses...not sufficient sample size for testing.
Use and Usability
Need to validate first
(No subject)
Importance
Important topic. Rationale for measure provided.
Closing Care Gaps
Care gap data provided highlighting differences in perceived quality of contraception care provided to patients.
Feasibility Assessment
Measure is currently being used. The review did not identify any feasibility issues. The responses can be collected through a variety of mechanisms. A question would be whether it is being given to all of those eligible. This is hard to assess unless someone else is in the exam room or performs chart review to assess any documentation.
Scientific Acceptability
Data is provided on the reliability of the measure
It is not clear how to necessarily assess the validity of the measure given that it is patient self-report. I am assuming that when the survey was developed, it was felt to be a valid measure and that is why the measure was initially approved. Given that it is already in use and there are differences in scores across certain patient groups, the measure is assessing differences in quality of preconception care.
Use and Usability
These criteria have been met.
Important measure that can be further improved.
Importance
I agree this is an important issue that should be measured.
Closing Care Gaps
Feasibility Assessment
This survey is simple and does not pose a significant burden.
Scientific Acceptability
It is not ideal that the survey used for reliability testing is somewhat different. The developer should try to conduct the testing using the same survey in the future
Nonresponse bias is a real issue that needs to be addressed. It will take more work but it is doable.
Use and Usability
Summary
Reliability testing is not ideal due to using a different survey. Nonresponse bias should be explicitly addressed.
(No subject)
Importance
This is a very important measure.
Closing Care Gaps
Feasibility Assessment
Scientific Acceptability
Use and Usability
Concerned about the wording of the survey and how patients may interpret the questions based on their literacy levels.
Endorsement supported
Importance
Measures patient reported experience with contraceptive counseling and addresses known gaps in care that have been shown to vary widely by practice environment and subpopulation (e.g., racial/ethnic and primary language subgroups)
Closing Care Gaps
This measure can help health care entities identify gaps in care across a wide variety of sociodemographic factors. There is credible evidence that use of this measure leads to closure of identified care gaps through application of evidence-based interventions.
Feasibility Assessment
This measure can help health care entities identify gaps in care across a wide variety of sociodemographic factors. There is credible evidence that use of this measure leads to closure of identified care gaps through application of evidence-based interventions.
Scientific Acceptability
I agree with the Staff Preliminary Assessment of "Met" based on developer demonstrating in results of required reliability testing that there is "sufficient reliability at the accountable entity-level."
I agree with the Staff Preliminary Assessment of "Not met but addressable" based on their concerns regarding validity testing results; the Recommendation Group should address these concerns in its upcoming meeting. I agree with developer's rationale to not perform risk adjustment so as not to mask disparities by subpopulations.
Use and Usability
This measure is currently in use by large health care organizations focused on reproductive care (e.g., PPFA), suboptimal results can be addressed by simple interventions to improve results (e.g., staff training), and measure use for ongoing improvement is sustainable over time. It also includes systematic feedback for measure improvement.
Summary
I support this measure for endorsement because it elicits patient feedback on their experience with contraceptive counseling using a relative brief survey that can be incorporated into existing survey instruments, exposes important disparities in care, has reasonable scientific acceptability (validity concerns should be addressed), and has both short- and long-term usability and applicability to targeted, evidence-based interventions for improvements.
Public Comments
Support for Continued Endorsement of the PCCC (CBE #3543)
We appreciate the opportunity to comment on CBE # 3543: Person-Centered Contraceptive Counseling [PCCC] measure: The percentage of contraceptive care patients giving “top box” scores on a PRE-PM focused on quality of contraceptive care at a specific visit. We support the continued endorsement of this measure as it facilitates assessment of the patient experience of contraceptive counseling, which is essential information to incorporate into any analysis of contraceptive service provision.
Upstream is a nonprofit organization working to expand access to contraception by providing high-quality, patient-centered training and technical assistance to healthcare organizations. Upstream integrated the visit-specific PCCC into our patient survey instrument in 2019. We have administered our virtual patient survey in over 155 healthcare facility settings across 34 states. We have received over 66,800 patient responses to the PCCC since 2021, when we began administering the survey virtually.
Leveraging the PCCC alongside the suite of endorsed contraceptive care measures, including screening (CBE #4655e) and method use (CBE #3699e) enables us to take a multi-dimensional approach to analyzing contraceptive service provision, and, most importantly, it provides a framework for understanding the patient experience related to contraceptive counseling and identifying areas of potential improvement. We rely on the PCCC to provide this uniquely valuable information in our programming and evaluation efforts and fully support its continued endorsement.
Developer response- thank you for your comment
We extend our appreciation to Upstream for their continued support and use of the PCCC. We agree that this measure is valuable and unique in its ability to capture patient experience of contraceptive counseling.
RE: Person-Centered Contraceptive Counseling [PCCC] measure
On behalf of the American College of Obstetricians and Gynecologists (ACOG), representing more than 62,000 physicians and partners dedicated to advancing women’s health and the health of individuals seeking obstetric and gynecologic care, we greatly appreciate the opportunity to comment on the Patient-Centered Contraceptive Counseling (PCCC) measure’s maintenance endorsement.
ACOG recognizes that contraceptive counseling is an important interaction between patients and obstetrician-gynecologists and other health care practitioners. The use of contraception can span reproductive, educational, economic, social, health, and personal goals, along with other non-contraceptive needs. The ability to access contraceptives can also affect how and when an individual uses contraception. Interaction with a clinician is often required to access certain methods. Counseling about an individual’s values, goals, and preferences is therefore a frequent and salient component between ob-gyns and patients.
The PCCC measure is critical to delivering high-quality contraceptive care. It was developed in response to concerns about reproductive coercion, provider bias, and the limitations of contraceptive quality metrics. The use of patient-reported outcome performance measures (PRO-PM) emphasizes the patient’s experience and preferences, reflecting an important step toward advancing equity and person-centered care.
ACOG’s guidance on patient-centered contraceptive counseling emphasizes the intentional application of a reproductive justice framework, which “encourages counselors to explore a person’s reproductive goals and contraceptive priorities and preferences while considering the systemic and structural barriers that may impede their ability to do so.”i This includes acknowledging the historical and ongoing reproductive mistreatment of people of color and other marginalized individuals, as well as recognizing and mitigating provider bias in counseling interactions. ACOG also recommends adherence to an ethical shared decision-making approach that centers patient values, preferences, and lived experiences in contraceptive care.ii While the PCCC measure meaningfully captures these key elements of patient-centered counseling, future iterations could further reflect ACOG’s guidance by incorporating aspects of shared decision-making and equity-focused counseling practices, such as efforts to mitigate undue influence or soliciting individual’s values, preferences, and insights to contraception. As continued endorsement is considered, ACOG encourages ongoing evaluation of how the measure can further support equity by more explicitly incorporating these principles.
PRO-PMs, such as PCCC, offer an opportunity to ensure that quality incentives reflect patient-centered outcomes as health care systems move toward value-based care models.iii The PCCC measure can help reinforce high-quality, preference-aligned care and serve as a meaningful counterbalance to utilization- and process-focused metrics. In this way, broader use of the measure has the potential to promote accountability for patient-centered care and support efforts to reduce bias and coercion in contraceptive counseling, particularly when used to inform quality improvement rather than as a direct determinant of payment.
While PRO-PMs are useful, ACOG recognizes that effective implementation of patient-reported performance measures requires appropriate infrastructure and resources. This is consistent with official Centers for Medicare and Medicaid Services (CMS) guidance that patient-reported measures require significant infrastructure developments, such as tools for survey collection, data storage, and analysis.iv Studies have found existing key barriers to implementing measures like patient-reported measures include the lack of clarity on integrating instruments, and system-level challengesvvi Therefore, addressing these restraints continues to be a challenge for health care practitioners and quality improvement, and may limit equitable uptake of measures intended to advance patient-reported measures. However, the availability of technical assistance offered by PCCC measure developers, UCSF, demonstrates the importance of dedicated infrastructure and implementation support in facilitating adoption of patient-reported measures.vii ACOG encourages continued efforts to expand technical assistance and infrastructure support that is cost-friendly, which is essential for settings serving populations with the greatest needs to successfully adopt and sustain use of the PCCC measure.
PCCC is a validated patient-reported measure that captures patients’ experience of contraceptive counseling and elevates patient voices and autonomy in quality assessment. ACOG supports continued endorsement of the measure and encourages ongoing efforts to strengthen its alignment with shared decision-making.
We appreciate the time taken to consider our comments. If you have any questions or wish to discuss these points further, please reach out to Erin Alston, Senior Manager, Health and Payment Policy ([email protected]).
Developer response to ACOG comment - thank you for your comment
We thank ACOG for uplifting the importance of patient-centeredness in contraceptive counseling and for their support of continued endorsement of this measure. As they reference, we agree that continued endorsement will promote ongoing accountability and improvement in care quality in alignment with reproductive autonomy and patient-centered principles.
As referenced by ACOG, the PCCC is aligned with their guidance for contraceptive counseling. We appreciate the specific emphasis of ACOG on attention to coercion and equity. Our measure is designed to capture these elements. One of the key domains of the PCCC is decision support, which is represented by items 2 through 4 of the scale, and item 3 specifically (“Taking my preferences seriously”) is intended to capture undue clinician influence on decision-making. These items were developed with substantial patient and stakeholder input and rigorous validity testing to ensure the constructs match patient understanding, as described in our development article.
Further, the PCCC can be leveraged to identify inequitable care experiences. Specifically, we recommend that PCCC scores be disaggregated by demographic and lived experience groups and examined to identify potential equity issues. This is described in greater detail in the Closing Care Gaps section of our application.
We also agree that capturing patient reported measures of quality takes infrastructure and investment. We have developed this measure to be parsimonious and easy to calculate and interpret to limit burden on patients and health systems. We have continuously refined implementation guidelines and support. We welcome the opportunity to collaborate with ACOG and other professional organizations to further optimize implementation and use of the measure, including streamlining data collection and analysis, while continuing to uplift patient voices.
Support for thePerson-Centered Contraceptive Counseling Measure
The Coalition to Expand Contraceptive Access (CECA) supports continued endorsement of the PCCC. Maintaining endorsement is key to promoting uptake and use of the PCCC, particularly by state and federal agencies. This serves the field's - and CECA's - goal of uplifting the importance of patient-centered contraceptive care on a national scale. This is particularly important in the current environment in which reproductive autonomy is increasingly being threatened.
Since initial endorsement, the PCCC has been effectively used to monitor the quality of contraceptive counseling, safeguard against an undue focus on contraceptive use, and uplift the importance of patient experience in the assessment of contraceptive care quality. The PCCC is part of an ecosystem of person-centered measures of quality contraceptive services, including measures of contraceptive use and provision, as well as screening for contraceptive need. Broad use of validated contraceptive care measures can improve patient experiences and outcomes, especially in underserved populations. Higher quality counseling helps patients choose methods that are aligned with their preferences and needs and stay engaged in reproductive care.
Developer response to CECA's comment: thank you for your comment
We thank CECA for their support of continued maintenance of PCCC's endorsement. We appreciate CECA's attention to importance of having a broad ecosystem of contraceptive care measures and that PCCC is crucial for the ongoing monitoring and improvement of contraceptive care quality.