Appendix E
The Health of Primary Care: A U.S. Scorecard
The committee was given the task of creating an implementation plan in addition to the typical task of developing recommendations. An implementation plan needs a set of metrics to track how well it is going and whether its aims are achieved over time. To that end, the committee offers this scorecard of selected measures that would meet both purposes and could be managed by one or more of the sponsoring organizations, federal agencies, or other interested stakeholders. The scorecard covers most report recommendations as objectives and offers data sources and example data, where possible, for dimension-related measures for each objective.
Very few of the 1996 report recommendations, or those for most past Institute of Medicine reports about primary care, have ever been actualized. Tracking on these scorecard dimensions will help achieve the intentions of the report sponsors and stakeholders and the committee’s recommendations, strengthening the foundation of America’s health care system.
SCORECARD PRINCIPLES
The committee proposes suggested measures for this scorecard using the following principles:
- The measures should be previously developed—as opposed to proposed new measures—and each should track the committee’s objectives, either directly or indirectly.
- The measures should be few, easily understood by the general public, and consistent over time.
- Data for the measures must be collected regularly, comprehensively, and reliably for producing assessment at relevant scope or geography; preferably, data will be publicly available and non-proprietary.
- Accountable unit—the measure should be available at the national and state levels, so as to engage advocates and policy makers.
These principles result in a small number of measures and do not address all the committee’s recommendations. Assessing the implementation status of a number of recommendations cannot currently be reliably accomplished. Additional research to accomplish this is a different task from monitoring: the work of developing and testing additional measures is not as important to implementation accountability as effectively deploying existing measures.
For each measure, the committee lists data sources and sample performance from those data sources. The committee does not propose a single data source for those measures where multiple are available. Despite the committee’s emphasis on team-based care and training throughout the report, robust data sources for non-physician team members and team-based care itself continue to pose a challenge. This reality is reflected in the proposed measures below.
The scorecard development process (see Action 5.3 in Chapter 12) should include selecting the appropriate data, prioritizing the frequency and reliability of source data. A comment section for each objective discusses the proposed measures, data sources, and where additional measures are needed.
The committee is not proposing targets for each measure. Establishing a baseline and documenting changes over time are critical to assessing implementation efforts.
THE HEALTH OF PRIMARY CARE: A PROPOSED U.S. SCORECARD
Objective 1: Pay for primary care teams to care for people, not doctors to deliver services.
| Measure 1.1: Percentage of total spend going to primary care—commercial insurance | |
| Potential data sources: | Sample performance: |
| Medical Expenditure Panel Survey (MEPS) (AHRQ, 2021) | MEPS data (2011–2016): |
| 6.0 percent (narrow definition1 of primary care) | |
| 10.2 percent (broad definition2 of primary care) | |
| State-level analysis also available (Jabbarpour et al., 2019) | |
| Health Care Cost Institute (HCCI) (HCCI, 2020) | HCCI data (2017): |
| 4.35 percent (narrow definition)3 | |
| 8.04 percent (broad definition)4 (Reiff et al., 2019) | |
| Truven Health MarketScan (IBM, 2020) (proprietary) | Truven Health MarketScan data (2018) |
| 5.95 percent (The Commonwealth Fund, 2020b) | |
| Measure 1.2: Percentage of total spend going to primary care—Medicare | |
| Potential data sources: | Sample performance: |
| MEPS (AHRQ, 2021) | MEPS data (2011–2016): |
| 4.4 percent (narrow definition) | |
| 6.9 percent (broad definition) | |
| State-level analysis also available (Jabbarpour et al., 2019) | |
| Medicare Master Beneficiary Summary File (MMBSF) (CMS, 2020c) | MMBSF data (2015): |
| 2.12 percent (narrow definition)5 | |
| 4.88 percent (broad definition)6 | |
| (Reid et al., 2019) | |
| Centers for Medicare & Medicaid Services (CMS) Limited Data Set (LDS) (CMS, 2020b) | The Commonwealth Fund (2017) |
| 5.66 percent (The Commonwealth Fund, 2020a) | |
| Measure 1.3: Percentage of total spend going to primary care—Medicaid | |
| Potential data source: | Sample performance (2011–2016): |
| MEPS (AHRQ, 2021) | 6.0 percent (narrow definition) |
| 11.2 percent (broad definition) | |
| State-level analysis also available (Jabbarpour et al., 2019) | |
| Measure 1.4: Percentage of primary care patient care revenue from capitation | |
| Potential data source: | Sample performance: |
| National Ambulatory Medical Care Survey (NAMCS) (CDC, 2020a) | |
| MEPS (AHRQ, 2021) | MEPS (2013): 5.3 percent of office-based visits (Zuvekas and Cohen, 2016) |
Comments:
Definitions are important when calculating the percentage of total health care spending directed to primary care; differences in the definitions used are listed below. The source data also differ, sometimes even within a source; for example, The Commonwealth Fund estimates for Medicare spending derive from the CMS LDS file, which is easier to access and analyze than the MMBSF. The LDS and the MMBSF estimates are not too dissimilar, but the difference may be related to nuanced definitional choices that are more readily assessed using the MMBSF. The percentage of total health spending in primary care for children is typically higher, as children have less chronic care and lower use of high-cost care settings. Medicaid data are important for this assessment of federal payments to primary care, but access to aggregate, national Medicaid data has been difficult until recently.
The scorecard measures related to paying for team-based care and moving away from fee-for-service, volume-based funding focuses on the current insufficiency of funding, points to sources of data about primary care investment across payer types, and also creates a tracking mechanism for capitated, or population-based, payment. The MEPS is a reliable source for longitudinally tracking primary care investment and claims data that are useful for looking at particular sectors, such as the investment made in caring for children (Medicaid) versus older persons (Medicare). The NAMCS also has relevant questions about practice financing and organization. While these data elements are captured by the MEPS and the NAMCS, they are
not typically reported by federal agencies and are currently dependent on outside researchers to produce them from the data.
Apart from the survey sources listed here, with the large number of private and public payers in the United States, no reliable comprehensive source yet exists for more detailed information for how primary care physicians are paid, a key recommendation of the committee.
1 Jabbarpour et al.’s narrow definition of primary care is restricted to physicians practicing family medicine, general practice, geriatrics, general internal medicine, and general pediatrics.
2 Jabbarpour et al.’s broad definition includes the narrow definition plus nurses and nurse practitioners, physician assistants, obstetrician-gynecologists, general psychiatrists, psychologists, and social workers.
3 Reiff et al.’s narrow definition includes evaluation and management visits, vaccinations, care planning, “and other related services” rendered by family practice, geriatric medicine, gynecology, internal medicine, or pediatric physicians; physician assistants; or nurse practitioners.
4 Reiff et al.’s broad definition includes all services rendered by those same primary care clinicians.
5 Reid et al.’s narrow definition involves services to Healthcare Common Procedure Coding System codes on professional claims, including evaluation and management visits, preventive visits, care transition or coordination services, and in-office preventive services, screening, and counseling rendered by physicians practicing family medicine, general practice, general internal medicine, and general pediatrics.
6 Reid et al.’s broad definition includes all services rendered in the narrow definition plus nurses and nurse practitioners, physician assistants, obstetrician-gynecologists, and geriatricians.
Objective 2: Ensure that high-quality primary care is available to every individual and family in every community.
| Measure 2.1: Percentage of adults without a usual source of health care | |
| Potential data source: | Sample performance: |
| National Health Interview Survey (NHIS) (CDC, 2021) | 14.6 percent (2018) (CDC, 2018) |
| Measure 2.2: Percentage of children without a usual source of health care | |
| Potential data source: | Sample performance: |
| NHIS (CDC, 2021) | 4.3 percent (2018) (CDC, 2020b) |
| Measure 2.3: Primary care physicians per 100,000 people in medically underserved areas | |
| Data sources: | No known score |
| Health Resources and Services Administration (HRSA) area resource file (HRSA, 2019), HRSA Medically Underserved Area (MUA) shape files (HRSA, 2020a) | |
| Measure 2.4: Primary care physicians per 100,000 people in areas that are not medically underserved | |
| Data sources: | No known score |
| HRSA area resource file (HRSA, 2019), HRSA MUA shape files (HRSA, 2020a) | |
Comments:
While reliably predictive, these measures do not fully address a key goal of this objective, which is to ensure access to high-quality primary care when needed.
Several efforts have been made to measure high-quality primary care, and this report offers several related recommendations. The committee offers a new definition for high-quality primary care, but there are no established measures to assess its availability.
Regarding need, as discussed in Chapter 3, some recent studies based on national health surveys suggest that visits to primary care have declined significantly in recent years, often associated with a rise in high-deductible health plans (Chou et al., 2019; Ganguli et al., 2019, 2020; Rao et al., 2019; Ray et al., 2020). This reduction is a source of concern if it is also associated with not receiving care when needed, avoiding preventive care, or seeking care in more expensive settings. Wait times for sick and new care-seeker visits could be another way to assess access; however, outside of the U.S. Department of Veterans Affairs, the committee is not aware of any measures that meet its criteria to be included in this scorecard.
Measures 2.3 and 2.4 require further analysis to determine performance; however, this could be done by overlaying HRSA’s MUA shape file over HRSA’s area resource file.
Objective 3: Train primary care teams where people live and work.
| Measure 3.1: Percentage of physicians trained in community-based settings, rural areas, Critical Access Hospitals (CAHs), MUAs | |
| Potential data sources: | Sample performance: |
| Medicare Claims Public Use Files (CMS, 2020a) | More than 3,400 physicians in residency training were identified as having spent time during residency in federally qualified health centers (FQHCs), rural health clinics (RHCs), or CAHs while training between 2001 and 2005, or 2009 using Medicare claims data and the AMA Physician Masterfile (Phillips et al., 2013). While this study did not do so, the AMA Physician Masterfile could be used to determine the total number of residents in a given year to calculate the percentage who trained in FQHCs, RHCs, or CAHs |
| American Medical Association (AMA) Physician Masterfile (AMA, 2021) | |
| Measure 3.2: Percentage of physician (PAs) working in primary cares, nurses, and physician assistants | |
| Potential data sources: | Sample performance: |
| AMA Physician Masterfile (AMA, 2021) | Physicians (2017): 31.9 percent (Petterson et al., 2018) |
| HRSA National Sample Survey of Registered Nurses (HRSA, 2020b) | Nurses (2018): 14.5 percent of registered nurses, 28.8 percent of advanced practice registered nurses (HHS et al., 2020) |
| National Commission on Certification of Physician Assistants (NCCPA) Statistical Profile of Certified Physician Assistants (NCCPA, 2020b) | PAs (2019): 25.0 percent (NCCPA, 2020a) |
| Measure 3.3: Percentage of new physician workforce entering primary care each year | |
| Potential data source: | Sample performance: |
| AMA Physician Masterfile (AMA, 2021) | 25.2 percent (2006–2008) (Chen et al., 2013) |
| Measure 3.4: Residents per 100,000 population by state | |
| Potential data source: | Sample performance: |
| Medicare Provider Cost Report Public Use Files (CMS, 2019) | New York (2010): 77.1 residents in training per 100,000 population North Dakota (2010): 11.5 per 100,000 (Mullan et al., 2013) |
Comments:
The funding for physician training is closely tied to hospitals and not to community-based settings, where most primary care is delivered. No single measure captures training in community-based settings, but Measure 3.1 highlights data sources that could be used together to estimate the proportion of trainees who train in safety net settings. The committee is not aware of comparable data sources for other professions, highlighting the difficulty of measuring progress across the primary care workforce. Measure 3.3’s sample score includes hospitalists and is thus an overestimate. Measure 3.4 highlights the uneven distribution of physician trainees relative to the population. While not primary care specific, this is important because trainees are more likely to practice in locations where they trained.
Objective 4: Design information technology that serves the patient, family, and interprofessional care team.
| The committee is not aware of adequate measures or data sources that capture the use or availability of person-centered digital health in primary care (or any health care) settings, underscoring the urgency for further research in this area. |
Objective 5: Ensure that high-quality primary care is implemented in the United States.
| Measure 5.1: Investment in primary care research by the National Institutes of Health (NIH) in dollars spent and percentage of total projects funded. | |
| Potential data source: | Sample performance: |
| NIH RePORT database (NIH, 2020) | Family medicine received $71 million, 0.22 percent of total funding from NIH (2011–2014) (Cameron et al., 2016) |
| Seven hundred and fifty projects related to primary care, approximately 1 percent of the total, were funded by NIH (fiscal years 2012–2018) (Mendel et al., 2020) | |
Comments:
As the committee recommends in Chapter 12, using this scorecard will itself be a way to track progress of the implementation of this committee’s five objectives. However, Measure 5.1 above gets to the committee’s recommended research action. While this report has cited numerous examples of best practices and presented an evidence-based vision for implementing high-quality primary care, primary care research is woefully underfunded and underdeveloped. Enhancing the evidence base could propel the field, to the benefit of all Americans.
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