Is primary care ready for a potential new public health emergency in the wake of the COVID-19 pandemic, now subsided?

INTRODUCTION: The lingering burden of the COVID-19 pandemic on primary care clinicians and practices poses a public health emergency for the United States. This study uses clinician-reported data to examine changes in primary care demand and capacity. METHODS: From March 2020 to March 2022, 36 electronic surveys were fielded among primary care clinicians responding to survey invitations as posted on listservs and identified through social media and crowd sourcing. Quantitative and qualitative analyses were performed on both closed- and open-ended survey questions. RESULTS: An average of 937 respondents per survey represented family medicine, pediatrics, internal medicine, geriatrics, and other specialties. Responses reported increases in patient health burden, including worsening chronic care management and increasing volume and complexity. A higher frequency of dental- and eyesight-related issues was noted by respondents, as was a substantial increase in mental or emotional health needs. Respondents also noted increased demand, "record high" wait times, and struggles to keep up with patient needs and the higher volume of patient questions. Frequent qualitative statements highlighted the mismatch of patient needs with practice capacity. Staffing shortages and the inability to fill open clinical positions impaired clinicians' ability to meet patient needs and a substantial proportion of respondents indicated an intention to leave the profession or knew someone who had. CONCLUSION: These data signal an urgent need to take action to support the ability of primary care to meet ongoing patient and population health care needs.

You Cannot Function in "Overwhelm": Helping Primary Care Navigate the Slow End of the Pandemic.

GOAL: This study was developed to explicate underlying organizational factors contributing to the deterioration of primary care clinicians' mental health during the COVID-19 pandemic. METHODS: Using data from the Larry A. Green Center for the Advancement of Primary Health Care for the Public Good's national survey of primary care clinicians from March 2020 to March 2022, a multidisciplinary team analyzed more than 11,150 open-ended comments. Phase 1 of the analysis happened in real-time as surveys were returned, using deductive and inductive coding. Phase 2 used grounded theory to identify emergent themes. Qualitative findings were triangulated with the survey's quantitative data. PRINCIPAL FINDINGS: The clinicians shifted from feelings of anxiety and uncertainty at the start of the pandemic to isolation, lack of fulfillment, moral injury, and plans to leave the profession. The frequency with which they spoke of depression, burnout, and moral injury was striking. The contributors to this distress included crushing workloads, worsening staff shortages, and insufficient reimbursement. Consequences, both felt and anticipated, included fatigue and demoralization from the inability to manage escalating workloads. Survey findings identified responses that could alleviate the mental health crisis, namely: (1) measuring and customizing workloads based on work capacity; (2) quantifying resources needed to return to sufficient staffing levels; (3) promoting state and federal support for sustainable practice infrastructures with less administrative burden; and (4) creating patient visits of different lengths to rebuild relationships and trust and facilitate more accurate diagnoses. PRACTICAL APPLICATIONS: Attention to clinicians' mental health should be rapidly directed to on-demand, confidential mental health support so they can receive the care they need and not worry about any stigma or loss of license for accepting that help. Interventions that address work-life balance, workload, and resources can improve care, support retention of the critically important primary care workforce, and attract more trainees to primary care careers.

Patterns of Diagnostic Evaluation and Determinants of Treatment in Older Patients With Non-transfusion Dependent Myelodysplastic Syndromes.

BACKGROUND: Older patients with myelodysplastic syndromes (MDS), particularly those with no or one cytopenia and no transfusion dependence, typically have an indolent course. Approximately, half of these receive the recommended diagnostic evaluation (DE) for MDS. We explored factors determining DE in these patients and its impact on subsequent treatment and outcomes. PATIENTS AND METHODS: We used 2011-2014 Medicare data to identify patients ≥66 years of age diagnosed with MDS. We used Classification and Regression Tree (CART) analysis to identify combinations of factors associated with DE and its impact on subsequent treatment. Variables examined included demographics, comorbidities, nursing home status, and investigative procedures performed. We conducted a logistic regression analysis to identify correlates associated with receipt of DE and treatment. RESULTS: Of 16 851 patients with MDS, 51% underwent DE. patients with MDS with no cytopenia (n = 3908) had the lowest uptake of DE (34.7%). Compared to patients with no cytopenia, those with any cytopenia had nearly 3 times higher odds of receiving DE [adjusted odds ratio (AOR), 2.81: 95% CI, 2.60-3.04] and the odds were higher for men than for women [AOR, 1.39: 95%CI, 1.30-1.48] and for Non-Hispanic Whites [vs. everyone else (AOR, 1.17: 95% CI, 1.06-1.29)]. The CART showed DE as the principal discriminating node, followed by the presence of any cytopenia for receiving MDS treatment. The lowest percentage of treatment was observed in patients without DE, at 14.6%. CONCLUSION: In this select older patients with MDS, we identified disparities in accurate diagnosis by demographic and clinical factors. Receipt of DE influenced subsequent treatment but not survival.

Community Members as Reviewers of Medical Journal Manuscripts: a Randomized Controlled Trial.

BACKGROUND: Community members may provide useful perspectives on manuscripts submitted to medical journals. OBJECTIVE: To determine the impact of community members reviewing medical journal manuscripts. DESIGN: Randomized controlled trial involving 578 original research manuscripts submitted to two medical journals from June 2018 to November 2021. PARTICIPANTS: Twenty-eight community members who were trained, supervised, and compensated. INTERVENTIONS: A total of 289 randomly selected control manuscripts were reviewed by scientific reviewers only. And 289 randomly selected intervention manuscripts were reviewed by scientific reviewers and one community member. Journal editorial teams used all reviews to make decisions about acceptance, revision, or rejection of manuscripts. MAIN MEASURES: Usefulness of reviews to editors, content of community reviews, and changes made to published articles in response to community reviewer comments. KEY RESULTS: Editor ratings of community and scientific reviews averaged 3.1 and 3.3, respectively (difference 0.2, 95% confidence interval [CI] 0.1 to 0.3), on a 5-point scale where a higher score indicates a more useful review. Qualitative analysis of the content of community reviews identified two taxonomies of themes: study attributes and viewpoints. Study attributes are the sections, topics, and components of manuscripts commented on by reviewers. Viewpoints are reviewer perceptions and perspectives on the research described in manuscripts and consisted of four major themes: (1) diversity of study participants, (2) relevance to patients and communities, (3) cultural considerations and social context, and (4) implementation of research by patients and communities. A total of 186 community reviewer comments were integrated into 64 published intervention group articles. Viewpoint themes were present more often in 66 published intervention articles compared to 54 published control articles (2.8 vs. 1.7 themes/article, difference 1.1, 95% CI 0.4 to 1.8). CONCLUSIONS: With training, supervision, and compensation, community members are able to review manuscripts submitted to medical journals. Their comments are useful to editors, address topics relevant to patients and communities, and are reflected in published articles. TRIAL REGISTRATION: ClinicalTrials.gov NCT03432143.

The Role of Primary Care in Improving Population Health.

Policy Points Systems based on primary care have better population health, health equity, and health care quality, and lower health care expenditure. Primary care can be a boundary-spanning force to integrate and personalize the many factors from which population health emerges. Equitably advancing population health requires understanding and supporting the complexly interacting mechanisms by which primary care influences health, equity, and health costs.

Telemedicine in Primary Care: Lessons Learned About Implementing Health Care Innovations During the COVID-19 Pandemic.

PURPOSE: During the COVID-19 pandemic, telemedicine emerged as an important tool in primary care. Technology and policy-related challenges, however, revealed barriers to adoption and implementation. This report describes the findings from weekly and monthly surveys of primary care clinicians regarding telemedicine during the first 2 years of the pandemic. METHODS: From March 2020 to March 2022, we conducted electronic surveys using convenience samples obtained through social networking and crowdsourcing. Unique tokens were used to confidentially track respondents over time. A multidisciplinary team conducted quantitative and qualitative analyses to identify key concepts and trends. RESULTS: A total of 36 surveys resulted in an average of 937 respondents per survey, representing clinicians from all 50 states and multiple specialties. Initial responses indicated general difficulties in implementing telemedicine due to poor infrastructure and reimbursement mechanisms. Over time, attitudes toward telemedicine improved and respondents considered video and telephone-based care important tools for their practice, though not a replacement for in-person care. CONCLUSIONS: The implementation of telemedicine during COVID-19 identified barriers and opportunities for technology adoption and highlighted steps that could support primary care clinics' ability to learn, adapt, and implement technology.

A Cluster Randomized Trial of Primary Care Practice Redesign to Integrate Behavioral Health for Those Who Need It Most: Patients With Multiple Chronic Conditions.

PURPOSE: Patient outcomes can improve when primary care and behavioral health providers use a collaborative system of care, but integrating these services is difficult. We tested the effectiveness of a practice intervention for improving patient outcomes by enhancing integrated behavioral health (IBH) activities. METHODS: We conducted a pragmatic, cluster randomized controlled trial. The intervention combined practice redesign, quality improvement coaching, provider and staff education, and collaborative learning. At baseline and 2 years, staff at 42 primary care practices completed the Practice Integration Profile (PIP) as a measure of IBH. Adult patients with multiple chronic medical and behavioral conditions completed the Patient-Reported Outcomes Measurement Information System (PROMIS-29) survey. Primary outcomes were the change in 8 PROMIS-29 domain scores. Secondary outcomes included change in level of integration. RESULTS: Intervention assignment had no effect on change in outcomes reported by 2,426 patients who completed both baseline and 2-year surveys. Practices assigned to the intervention improved PIP workflow scores but not PIP total scores. Baseline PIP total score was significantly associated with patient-reported function, independent of intervention. Active practices that completed intervention workbooks (n = 13) improved patient-reported outcomes and practice integration (P ≤ .05) compared with other active practices (n = 7). CONCLUSION: Intervention assignment had no effect on change in patient outcomes; however, we did observe improved patient outcomes among practices that entered the study with greater IBH. We also observed more improvement of integration and patient outcomes among active practices that completed the intervention compared to active practices that did not. Additional research is needed to understand how implementation efforts to enhance IBH can best reach patients.

Using Community-Based System Dynamics to Address Structural Racism in Community Health Improvement.

CONTEXT: Structural racism is a profound determinant of health resulting in pervasive health inequities for people of color. Despite the recognition of structural racism as a complex, dynamic system, we lack a shared vision of the system that would enable identification of solutions for equitable systems transformation. POLICY: Through a public health-led community health improvement planning process, a cross-sector consortium implemented community-based system dynamics to provide a systems science lens to guide efforts to eliminate structural racism. IMPLEMENTATION: In group model building sessions involving diverse stakeholders, community-based system dynamics was used to bring together cross-sector stakeholders to create causal loop diagrams of the system of structural racism. Participants identified potential leverage points for actionable focus to eliminate structural racism. EVALUATION: Causal loop diagrams of structural racism generated through group model building demonstrate complex dynamics in the areas of criminal justice, education and economic opportunity, health and health care, quality of life, racial trauma and healing, and a promising system transformative solution through perspective transformation. DISCUSSION: Community-based system dynamics, employed in the context of local community health improvement planning, engages stakeholders in systems thinking through sharing lived experience to create system maps of structural racism and identify leverage points and transportable solutions that foster health equity. These informal maps serve as the foundation for formal computer simulation models that will guide systemic action on high-yield, community-driven solutions to eliminate structural racism.

Measuring Primary Care Across 35 OECD Countries.

PURPOSE: To examine the psychometric properties and scores of the Person-Centered Primary Care Measure (PCPCM) in 28 languages and 35 Organisation for Economic Co-operation and Development (OECD) countries. METHODS: Using a paid online sampling service, we requested age- and sex-representative samples of 360 adults in each country. We administered the Person-Centered Primary Care Measure-a previously validated 11-item, patient-reported measure that was developed using what patients and clinicians said is most important about primary care. We also assessed construct validity through associations with demographics, the Patient-Enablement Instrument, number of years the person had been with their primary care physician and practice, whether the patient thought the doctor knowing the results would improve their care, and whether it was hard to complete the survey. We assessed the psychometric properties of the PCPCM in each country and report the summative and item-specific PCPCM scores for each country. RESULTS: The PCPCM exhibited solid psychometric properties across all languages and countries, with Cronbach's alphas ranging from 0.88 to 0.95, and corrected item-total correlations ranging from 0.47 to 0.81, with the vast majority of countries ranging from the low 0.50s to the high 0.70s. Multiple analyses showed strong evidence of concurrent validity. With a potential range from a low of 1 to a high of 4, the overall mean score was 2.74, with a standard deviation of 0.19. Mean PCPCM scores ranged from the lowest in Sweden (2.28) to the highest in Turkey (3.08), with Germany ranking second (3.01), and the United States third (2.99). CONCLUSION: The internal consistency and concurrent validity of the PCPCM across multiple countries provides strong evidence of the coherence of the breadth of primary care functions that patients and clinicians say are important. The diversity of total and item-specific scores across countries provokes interesting hypotheses about the influence of each different country's policies, practices, demographics, and culture on primary care, and provides a strong impetus for further ecological and individual data analyses using the Person-Centered Primary Care Measure. Annals "Online First" article.

Shared Language for Shared Work in Population Health.

People working on behalf of population health, community health, or public health often experience confusion or ambiguity in the meaning of these and other common terms-the similarities and differences and how they bear on the tasks and division of labor for care delivery and public health. Shared language must be clear enough to help, not hinder people working together as they ultimately come to mutual understanding of roles, responsibilities, and actions in their joint work. Based on an iterative lexicon development process, the authors developed and propose a definitional framework as an aid to navigating among related population and community health terms. These terms are defined, similarities and differences clarified, and then organized into 3 categories that reflect goals, realities, and ways to get the job done. Goals include (a) health as well-being for persons, (b) population health as that goal expressed in measurable terms for groups, and (c) community health as population health for particular communities of interest, geography, or other defining characteristic-groups with shared identity and particular systemic influences on health. Realities are social determinants as influences, health disparities as effects, and health equity as both a goal and a design principle. Ways to get the job done include health care delivery systems for enrollees and public health in population-based civic activities-with a broad zone of collaboration where streams of effort converge in partnership with served communities. This map of terms can enable people to move forward together in a broad zone of collaboration for health with less confusion, ambiguity, and conflict.

Identifying Patient Strengths Instruments and Examining Their Relevance for Chronic Disease Management: A Systematic Review.

INTRODUCTION: Most health care focuses on patients' deficits to encourage behavior change. A strengths-based approach, which relies on identifying patient strengths, has great potential to facilitate behavior change for chronic disease management. Little is known about instruments used to assess patient strengths. We conducted a systematic review to identify validated instruments that assess personal strengths by using a theory elaboration approach. METHODS: We searched 8 databases including Web of Science, Cumulative Index of Nursing and Allied Health (CINAHL), and PsycINFO (through July 2019) to identify peer reviewed, English-language studies that described strength-based instruments. Thereafter, we evaluated the validity and reliability of the instruments according to 18 Scientific Advisory Committee of the Medical Outcome Trust (SACMOT) criteria, and used an inductive, iterative editing process to identify constructs measured by the instruments. RESULTS: We identified 26 instruments that met our inclusion criteria. The instruments were validated in various clinical and nonclinical populations. Only 4 instruments met most of the SACMOT criteria for validation. We extracted 91 unique constructs that fell into 3 domains: inner strengths (49), external strengths (13), and personality constructs (29). CONCLUSION: A limited number of reliable and valid instruments are available to assess strengths for the adult population, particularly for clinical populations. Internal strengths can be leveraged to improve patient health; however, the development and validation of additional instruments to capture personal strengths is necessary to examine the multilevel influence of external strengths on individual behaviors and well-being.

Validating the New Primary Care Measure in the Medical Expenditure Panel Survey.

BACKGROUND: The advancement of primary care research requires reliable and validated measures that capture primary care processes embedded within nationally representative datasets. OBJECTIVE: The objective of this study was to assess the validity of a newly developed measure of primary care processes [Medical Expenditure Panel Survey (MEPS)-PC] with preliminary evidence of moderate to excellent reliability. STUDY DESIGN: A retrospective cohort study of community-dwelling adults with history of office-based provider visit/s using the MEPS (2013-2014). METHODS: The 3 MEPS-PC subscales (Relationship, Comprehensiveness, and Health Promotion) were tested for construct validity against known measures of primary care: Usual Source of Care, Known Provider, and Family-Usual Source of Care. Concurrent and predictive logistic regression analyses were calculated and compared with a priori hypotheses for direction and strength of association. RESULTS: For concurrent validity, all odds ratio estimates conformed with hypotheses, with 91% displaying statistical significance. For predictive validity, all estimates were in the direction of hypotheses, with 92% displaying statistically significant results. Although Relationship and Health Promotion subscales conformed uniformly with hypotheses, the Comprehensiveness subscale yielded significant results in 60% of bivariate odds ratio estimates (P<0.05). CONCLUSION: The MEPS-PC composite measures display modest to strong preliminary evidence of concurrent and predictive validity relative to known indicators of primary care. IMPLICATIONS FOR POLICY AND PRACTICE: The MEPS-PC composite measures display preliminary evidence of concurrent and predictive construct validity, and it may be useful to researchers investigating primary care processes and complexities in the health care environment.

Impact of Instrumental Activities of Daily Living Limitations on Hospital Readmission: an Observational Study Using Machine Learning.

BACKGROUND: Limitations in instrumental activities of daily living (IADL) hinder a person's ability to live independently in the community and self-manage their conditions, but its impact on hospital readmission has not been firmly established. OBJECTIVE: To test the importance of IADL dependency as a predictor of 30-day readmissions and quantify its impact relative to other morbidities. DESIGN: A retrospective cohort study of the population-based Health and Retirement Study linked to Medicare claims data. Random forest was used to rank each predictor variable in terms of its ability to predict readmission. Classification and regression tree (CART) was used to identify complex multimorbidity combinations associated with high or low risk of readmission. Generalized linear regression was used to estimate the adjusted relative risk of readmission for IADL limitations. SUBJECTS: Hospitalizations of adults age 65 and older (n = 20,007), from 6617 unique subjects. MAIN MEASURES: The main outcome was 30-day all-cause unplanned readmission. The main predictor of interest was self-reported IADL limitation. Other key predictors were self-reported complex multimorbidity including chronic diseases, geriatric syndromes, and activities of daily living (ADL) limitations, along with demographic, socioeconomic, and behavioral factors. KEY RESULTS: The overall 30-day readmission rate in the study was 16.4%. Random forest analysis ranked ADLs and IADL limitations as the two most important predictors of 30-day readmission. CART identified hospitalizations of patients with IADL limitations and diabetes as a subgroup at the highest risk of readmission (26% readmitted). Multivariable regression analyses showed that ADL limitations were associated with 1.17 (1.06-1.29) times higher risk of readmission even after adjusting for other patient covariates. Risk prediction was modest though for even the best model (AUC = 0.612). CONCLUSIONS: IADL limitations are key predictors of 30-day readmission as demonstrated using several machine learning methods. Routine assessment of functional abilities in hospital settings could help identify those most at risk.

Physical Distancing With Social Connectedness.

In light of concerns over the potential detrimental effects of declining care continuity, and the need for connection between patients and health care providers, our multidisciplinary group considered the possible ways that relationships might be developed in different kinds of health care encounters.We were surprised to discover many avenues to invest in relationships, even in non-continuity consultations, and how meaningful human connections might be developed even in telehealth visits. Opportunities range from the quality of attention or the structure of the time during the visit, to supporting relationship development in how care is organized at the local or system level and in the use of digital encounters. These ways of investing in relationships can exhibit different manifestations and emphases during different kinds of visits, but most are available during all kinds of encounters.Recognizing and supporting the many ways of investing in relationships has great potential to create a positive sea change in a health care system that currently feels fragmented and depersonalized to both patients and health care clinicians.The current COVID-19 pandemic is full of opportunity to use remote communication to develop healing human relationships. What we need in a pandemic is not social distancing, but physical distancing with social connectedness.

Assessing the Longitudinal Impact of Physician-Patient Relationship on Functional Health.

PURPOSE: Access to a usual source of care is associated with improved health outcomes, but research on how the physician-patient relationship affects a patient's health, particularly long-term, is limited. The aim of this study was to investigate the longitudinal effect of changes in the physician-patient relationship on functional health. METHODS: We conducted a prospective cohort study using the Medical Expenditure Panel Survey (MEPS, 2015-2016). The outcome was 1-year change in functional health (12-Item Short-Form Survey). The predictors were quality of physician-patient relationship, and changes in this relationship, operationalized with the MEPS Primary Care (MEPS-PC) Relationship subscale, a composite measure with preliminary evidence of reliability and validity. Confounders included age, sex, race/ethnicity, educational attainment, insurance status, US region, and multimorbidity. We conducted analyses with survey-weighted, covariate-adjusted, predicted marginal means, used to calculate Cohen effect estimates. We tested differences in trajectories with multiple pairwise comparisons with Tukey contrasts. RESULTS: Improved physician-patient relationships were associated with improved functional health, whereas worsened physician-patient relationships were associated with worsened functional health, with 1-year effect estimates ranging from 0.05 (95% CI, 0-0.10) to 0.08 (95% CI, 0.02-0.13) compared with -0.16 (95% CI, -0.35 to -0.03) to -0.33 (95% CI, -0.47 to -0.02), respectively. CONCLUSION: The quality of the physician-patient relationship is positively associated with functional health. These findings could inform health care strategies and health policy aimed at improving patient-centered health outcomes.

Cancer Survivorship Care Roles for Primary Care Physicians.

PURPOSE: Despite a burgeoning population of cancer survivors and pending shortages of oncology services, clear definitions and systematic approaches for engaging primary care in cancer survivorship are lacking. We sought to understand how primary care clinicians perceive their role in delivering care to cancer survivors. METHODS: We conducted digitally recorded interviews with 38 clinicians in 14 primary care practices that had national reputations as workforce innovators. Interviews took place during intense case study data collection and explored clinicians' perspectives regarding their role in cancer survivorship care. We analyzed verbatim transcripts using an inductive and iterative immersion-crystallization process. RESULTS: Divergent views exist regarding primary care's role in cancer survivor care with a lack of coherence about the concept of survivorship. A few clinicians believed any follow-up care after acute cancer treatment was oncology's responsibility; however, most felt cancer survivor care was within their purview. Some primary care clinicians considered cancer survivors as a distinct population; others felt cancer survivors were like any other patient with a chronic disease. In further interpretative analysis, we discovered a deeply ingrained philosophy of whole-person care that creates a professional identity dilemma for primary care clinicians when faced with rapidly changing specialized knowledge. CONCLUSIONS: This study exposes an emerging identity crisis for primary care that goes beyond cancer survivorship care. Facilitated national conversations might help specialists and primary care develop knowledge translation platforms to support the prioritizing, integrating, and personalizing functions of primary care for patients with highly complicated issues requiring specialized knowledge.

Developing a New Measure of Primary Care Using the Medical Expenditure Panel Survey.

OBJECTIVE: To develop and assess the reliability of a measure of primary care using items from the Medical Expenditure Panel Survey (MEPS), a US representative survey of community-dwelling persons. METHODS: On the basis of the domains from the literature on primary care characteristics, we identified relevant items within the 2013-2014 MEPS family of surveys. In a sample of primary survey respondents with at least 1 office-based physician visit in the last 12 months, we conducted exploratory factor analysis, retaining items with a factor loading of 0.30 and factors ≥3 items. Using a hold-out sample, internal consistency, reproducibility, and confirmatory factor analyses were performed. RESULTS: On the basis of 16 care domains, we found 32 candidate items in the MEPS. Factor analyses of data from 4549 persons meeting inclusion criteria (27.6% of the total sample), yielded 3 unique factors involving 24 items. We named these subscales Relationship, Comprehensiveness, and Health Promotion, displaying internal consistency reliability of 0.86, 0.78, and 0.69, respectively. Confirmatory factor analysis corroborated the stability of the exploratory findings in the hold out sample. Sensitivity analyses showed robustness to differences in underlying correlation structure, alternative approach to missing data, and extension to indirect survey respondents. CONCLUSIONS: The MEPS Primary Care measure with 3 subscales is reliable and may be useful in conducting primary care health services and outcomes research in the rich MEPS dataset. Further validation is needed, and is described in a companion paper.

A New Comprehensive Measure of High-Value Aspects of Primary Care.

PURPOSE: To develop and evaluate a concise measure of primary care that is grounded in the experience of patients, clinicians, and health care payers. METHODS: We asked crowd-sourced samples of 412 patients, 525 primary care clinicians, and 85 health care payers to describe what provides value in primary care, then asked 70 primary care and health services experts in a 2½ day international conference to provide additional insights. A multidisciplinary team conducted a qualitative analysis of the combined data to develop a parsimonious set of patient-reported items. We evaluated items using factor analysis, Rasch modeling, and association analyses among 2 online samples and 4 clinical samples from diverse patient populations. RESULTS: The resulting person-centered primary care measure parsimoniously represents the broad scope of primary care, with 11 domains each represented by a single item: accessibility, advocacy, community context, comprehensiveness, continuity, coordination, family context, goal-oriented care, health promotion, integration, and relationship. Principal axes factor analysis identified a single factor. Factor loadings and corrected item-total correlations were >0.6 in online samples (n = 2,229) and >0.5 in clinical samples (n = 323). Factor scores were fairly normally distributed in online patient samples, and skewed toward higher ratings in point-of-care patient samples. Rasch models showed a broad spread of person and item scores, acceptable item-fit statistics, and little item redundancy. Preliminary concurrent validity analyses supported hypothesized associations. CONCLUSIONS: The person-centered primary care measure reliably, comprehensively, and parsimoniously assesses the aspects of care thought to represent high-value primary care by patients, clinicians, and payers. The measure is ready for further validation and outcome analyses, and for use in focusing attention on what matters about primary care, while reducing measurement burden.