Methods for measuring comprehensiveness in primary care: a narrative review
Derek Baughman
1 , Rafay Nasir 2 * , Andrew Bazemore 1
1
2
Abstract
Comprehensiveness in primary care is defined as managing most medical needs in a population while integrating the context of patient’s values, preferences, and beliefs. This study aims to synthesise validated measures for measuring comprehensiveness in primary care to facilitate its practical application.
The objective of this study was to synthesise validated measures for measuring comprehensiveness in primary care, facilitating its practical application.
A narrative-style literature review was employed to conduct a hierarchical review of relevant literature. The process involved several stages: initial term filtering, separation of primary care from specialist care using medical subject heading (MeSH) terms, incorporation of non-MeSH terminology, and a manual review of titles, abstracts, and full articles. Articles were included if they discussed the measurement, assessment, or application of comprehensiveness in primary care and were relevant to primary care and methodologically sound. A multistage PubMed search of ‘comprehensiveness’ (MeSH) with hierarchical sub-term filtering and snowball method gleaning of additional articles from literature-described terminology was conducted.
Thirteen studies met the inclusion criteria. Methodological strategies varied from claims-based approaches for cost and utilisation to surveys assessing the scope of clinical services and patient experience.
Thoroughly measuring comprehensiveness in primary care integrates methods that evaluate the effect of physician ranges of clinical services on the cost and utilisation of health care, and the impact on patient outcomes within the context of the patient experience. Implementing these methods pragmatically can assist communities and health systems in implementing, measuring, and capturing comprehensiveness in primary care.
Keywords: comprehensiveness, family medicine, health services research, health systems, holistic care, integrated care, population health, primary care, range of services, scope of care, value based care, whole person care.
| WHAT GAP THIS FILLS |
| What is already known: Comprehensiveness in primary care is crucial for managing most medical needs in a population while integrating the patient’s context. |
| What this study adds: This study provides a menu of validated options for communities and health systems to appropriately implement, measure, and capture comprehensiveness in primary care. |
Introduction
The concept of comprehensiveness was described as early as the 1960s in US health care.1 The definition was refined nationally and internationally in the 1970s and 1980s by the Institute of Medicine (now National Academy of Medicine, IOM)2 and the World Health Organization,3 where comprehensiveness in primary care meant managing most medical problems within a population. The well-known physician-researcher from Johns Hopkins, Barbara Starfield, popularised the equitability and value-based care aspects of comprehensiveness in the 21st century. Starfield emphasised that the primary care physician’s (PCP’s) role is a comparatively broader scope of care than specialists and that the mainstay of referrals should be temporary.4
Today, comprehensiveness as it relates to primary care includes three primary components: a broad range of services, appropriate utilisation of specialty services, and an emphasis on whole-person care. The relationship between these three components provides a succinct workable definition of comprehensiveness in primary care: managing most of the medical care within a primary care population, and if needed, temporarily complementing care with special integrated services in the context of patient’s values.5
A focus on comprehensive primary care has been linked to improvements across the board within the triple aim of health care, including increased quality of care, reduced cost, and increased accessibility.3 Not only is the delivery of comprehensive primary care linked to improved patient outcomes, it is also linked to increased provider satisfaction.3 However, one challenge in both the study and application of comprehensiveness is identifying quantitative and/or qualitative methods that can conceptually capture the entirety of comprehensiveness, a topic that is inherently broad and abstract.
The objective of this literature review was to reconcile successful, validated methods for measuring the academic concept of comprehensiveness in primary care. The purpose was to highlight the themes and practical applications for clinicians, researchers, and health policy leaders seeking to operationalise comprehensiveness in the era of value-based health care.
Methods
We adopted narrative style literature review methods from Ferrari6 to systematically review published literature on the measurement of comprehensiveness. Only peer-reviewed English-language articles were included if they aligned with the research scope, focusing on comprehensiveness in primary care (family medicine, internal medicine, and paediatrics) as defined by the IOM and Starfield, which involves managing most medical services and coordinating with specialists to meet all healthcare needs.
A primary PubMed query of key terms was completed on 1 December 2022. Thereafter, an article filtering and selection process was completed in hierarchical stages (Fig. 1) to mitigate the over-incorporation of out-of-scope content. The American Board of Family Medicine’s (ABFM’s) medical librarian team ensured search term accuracy and methodological soundness. Snowball methods were used during the review to glean additional relevant articles from national and international experts.
The hierarchical literature review methodology using MeSH terms to explore comprehensiveness and targeted sub-terms. Note, the medical specialty filter for ‘primary care specialties’ only included family medicine, internal medicine, and paediatrics. Figure format adapted from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021; 372: n71. doi:10.1136/bmj.n71.
The following research questions served as guidance for screening and evaluating article content, encompassing the key areas of interest related to comprehensiveness in primary care.
What are the implications of comprehensiveness in primary care, including its impact on healthcare quality, cost-effectiveness, and accessibility?
How can we measure and assess comprehensiveness effectively, considering its multifaceted nature?
What validated methods are available to evaluate comprehensive primary care, covering healthcare cost, utilisation, patient outcomes, and experiences?
Stage 1 of article selection was the primary MeSH query for ‘comprehensiveness’. A high volume of results necessitated term filtering (for example, many articles included the terms ‘comprehensive’ or ‘comprehensiveness’ but were unrelated to the concept of comprehensive primary care).
Stage 2 involved discrete grouped sub-terms to separate primary care from specialist care. This included one arm for primary care (with only the specialties of family medicine, internal medicine, and paediatrics) and another arm with the MeSH term ‘referral and consultation’ to represent specialists.
Stage 3 involved a collection of sub-terms to represent other known measures of comprehensiveness. This included non-MeSH terminology adapted from literature by known experts: ‘depth and breadth of care’, ‘scope of practice’, and two Medicare coding terms (BETOS: Berenson-Eggers Type of Service; HCPCS: Healthcare Common Procedure Coding System).
Stage 4 involved the manual screening of titles and abstracts, which focused on methodological and operational measurement of comprehensiveness.
In stage 5, full article reviews were completed in a structured format. Articles meeting inclusion criteria were reviewed in a standardised format to generate an annotated bibliography (see Supplementary material, section S2). The format included three sections:
Summary – key elements of the study design highlighted findings described succinctly.
Measure – summarises the details of methods used in the context of comprehensiveness.
Application – a statement that generalises the methodological concept.
The content was organised into a summary table, grouping the application statements into four categories (Table 1).
| Comprehensiveness aspect | Cited study | Application | Methods summary | Measure components | |
|---|---|---|---|---|---|
| Cost and utilisationA | 1. Lindner et al.7 A Medicaid alternative payment model program in Oregon led to reduced volume of imaging services | Comparing the cost utilisation of clinical services between practices | Compared price-weighted volume of care amongst beneficiaries within an Oregon state alternate payment model (APM) to traditional Medicaid fee-for-service (FFS) | (Volume of services) × (price) | |
| Cost: Medicaid and Diagnosis Related Group (DRG) pricing, average Current Procedural Terminology (CPT) schedules, averaged CPT pricing | |||||
| Clinical services: claims data and BETOS codes | |||||
| 2. Bazemore et al.8 More comprehensive care among family physicians is associated with lower costs and fewer hospitalizations | Evaluating the impact of practice scope and procedural management breadth on amount and cost of health care | Linked Medicare claims (BETOS categorised) with reported care areas to measure association of comprehensiveness with the odds of hospitalisations and costs | Cost: Medicare Parts A and B claims | ||
| Clinical services: | |||||
| Range of services/scope of careB | 3. Peterson et al.9 Rewarding family medicine while penalizing comprehensiveness? Primary care payment incentives and health reform: the Patient Protection and Affordable Care Act | Medicare incentive payment eligibility can provide a rough baseline estimate of comprehensive PCPs | Measured rural PCP’s evaluation and management (E&M) codes from Part B claims to estimate eligibility for Medicare bonus pay (requires ≥50% of billable services to be primary care) | Clinical services: Primary care E&M codes via Medicare claims data | |
| 4. Shultz and Glazier.10 Identification of physicians providing comprehensive primary care in Ontario: a retrospective analysis using linked administrative data | Distinguishing comprehensive PCPs vs physicians traditionally categorised as primary care | Defined multi-step criteria for comprehensiveness which included a minimum time threshold for PCP practice and two categorical thresholds (discrete clinical services and care venues) | Time threshold: working min 1 day/week + 50% time as PCP | ||
| Clinical services: meeting at least 7 of 66 specific services | |||||
| Clinical areas: 22 unique care service areas | |||||
| 5. Rosenblatt et al.11 Identifying primary care disciplines by analyzing the diagnostic content of ambulatory care | Qualitatively comparing range of services to evaluate practice scope (comprehensiveness) between specialties | Compared proportions of billable primary care diagnostic clusters (generated from National Ambulatory Medical Care Surveys) between internal medicine (IM), family medicine (FM) and generalist ambulatory physicians | Clinical services: Top 20 of 120 commonest International Classification of Diseases (ICD) diagnostic clusters in primary care (claims data) | ||
| 6. Weiner et al.12 Measurement of the primary care roles of office-based physicians | Combining surveys and objective clinical service categorisation offers continuous confirmation of practice scope | Measured various stages of physician engagement (from new visit to referral), self-reported range of services, and percentage of patients using the Patient Centered Medical Home (PCMH) to evaluate the role of office-based PCPs | Clinical services: 3 indexes | ||
| Multi-modal comprehensivenesC | 7. Henry et al.13 Comparing comprehensiveness in primary care specialties and their effects on healthcare costs and hospitalizations in medicare beneficiaries | Estimating physician range of services as a proxy for comprehensiveness | Compared range of services (comprehensiveness) and cost of care between IM and FM PCPs | Cost: Medicare Parts A and B claims | |
| Clinical services: BETOS grouped billing codes | |||||
| 8. O’Malley et al.14 New approaches to measuring the comprehensiveness of primary care physicians | Validated physician-level and patient-level approaches for evaluating comprehensiveness tied to cost and outcomes | Physician-level measures included (1) Involvement in patient conditions, (2) New problem management, (3) Range of services; these were associated with 4 patient-level outcomes: cost, admissions, emergency room (ER) visits, and avoidable hospitalisations (ACSC) | Clinical services: compared percentages of unique ICD codes between physicians | ||
| Cost: total Medicare spending | |||||
| Utilisation: numbers of admissions, ER visits and ACSCs | |||||
| 9. O’Malley et al.15 Practice-site-level measures of primary care comprehensiveness and their associations with patient outcomes | Identifying physicians and practices with National Provider Identifier (NPI) and Tax Identification Number (TIN) data can provide practice-level insight into involvement in patient conditions (IPC) and new problem management (NPM) | Compared associations between comprehensiveness (IPC/NPM) and modelled 3 outcomes (Medicare expenditures, hospitalisation and emergency department (ED) utilisation rates) at the level of PCP (with NPI) and practice level (NPI weighted averages calculated from caseload) | Clinical services and utilisation: Medicare claims (virtual research data) | ||
| Cost: Medicare expenditures | |||||
| 10. Rich et al.16 Primary care practices providing a broader range of services have lower medicare expenditures and emergency department utilization | Linking practice TIN billing and clinical code categories to standardise range of services facilitates beneficiary-practice level association between cost and utilisation | Generated a 5-category list of services from Agency for Healthcare Research and Quality (AHRQ) refined Patient Categorisation Tool (PCAT) surveys and lists of primary care services from 34 countries: immunisations, BH counselling, minor lacerations, skin procedures, joint/tendon injections. Range of services per PCP was scaled 0–5 where performing at least 1 service within the category = 1 point (1 per category, 5 points max) | Clinical services and utilisation: Healthcare Common Procedure Coding System (HCPCS) codes relevant to the 5 categories identified in practitioner’s TIN billings | ||
| Cost: Practice unique TIN | |||||
| Patient experience (descriptive and qualitative)D | 11. Shi et al.17 Validating the Adult primary care assessment tool | A validated qualitative approach to understanding physician multidimensionality from the patient perspective | Measured 4 core primary care domains (contact, longevity, coordination, and comprehensiveness) and 3 ancillary domains (family-centredness, community orientation and cultural competence) | Patient survey: PCAT | |
| 12. O’Malley and Rich.18 Measuring comprehensiveness of primary care: challenges and opportunities | Concludes that robust comprehensiveness measurement includes big data (population level) validated with qualitative patient data and outcome measures | A descriptive evaluation of approaches toward measuring comprehensiveness in the literature highlighting difficulties of the process | Approaches: | ||
| Future considerations: standardised population-level informatics with outcome measures | |||||
| 13. Etz et al.19 A new comprehensive measure of high-value aspects of primary care | An internationally validated, concise survey that can consistently measure comprehensiveness from the patient perspective | Developed from patient, physician, and employer responses to ‘what aspects of primary care are most important’. Content vetted by a multidisciplinary team of experts and validated across multiple psychometric analyses | Patient survey: Person-Centered Primary Care Measure (PCPCM) |
BH = behavioral health.
Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.
Results
Of the 679,607 articles from the initial PubMed query on the MeSH term ‘comprehensiveness’, 96 abstracts met sub-filtering standards and were reviewed for content appropriateness. Thirteen studies met inclusion criteria (Supplementary Table S1) and were thoroughly reviewed (Fig. 1). Twelve were based in the United States and one in Canada. Most study designs focused on evaluating the range of services, cost/utilisation implications, or a combination of these aspects (Table 1). No studies from Australia, the United Kingdom, or New Zealand met inclusion criteria based on our structured search.
Evidence-based strategies: cost and utilisation
Two studies focused on associating comprehensiveness with cost and healthcare services utilisation using a claims-based methodology. These approaches used BETOS20 methods to categorise claims data (visits, procedures, tests, services, etc) and standardise costs.
Lindner et al.7 evaluated comprehensiveness based on cost incentives. Using difference-in-difference analysis and price weighting the claims data, the team made standardised comparisons between beneficiaries in traditional Medicaid versus those in Medicaid alternative payment models (APMs). This claims data tracking across patient care services facilitated analysis down to the practice level. Similarly, Bazemore et al.8 evaluated comprehensiveness and the effect on utilisation (and the cost thereof). Their team tracked Medicare expenditures and hospitalisations but analysed this effect from physician-reported comprehensiveness (range of services provided as reported on medical board recertification surveys). This approach facilitated a dose–response relationship between comprehensiveness (range of services offered) and cost/utilisation outcomes. These effects might be limited to physicians incentivised within APMs.
Evidence-based strategies: range of services/scope of care
Four studies focused on the scope of primary care practice within the context of comprehensiveness. The authors used quantitative (claims-based) or qualitative (survey-based) methods to evaluate the range of clinical services provided by PCPs.
Two authors described the range of services by type of clinical encounter, either the location context or by clinical encounter type. Petterson et al.9 considered types of encounters in multiple locations, estimating practice scope using Medicare claims data to uniquely identify the location of service based on the evaluation and management (E&M) code (outpatient, hospital, nursing home, etc). Petterson et al.9 considered only office settings, estimating practice scope by classifying the range of patient encounter types (new, established, preventive, procedure, etc).
Two authors described the range of services by the type of service provided. Both Shultz and Glazier10 and Rosenblatt et al.11 organised primary care service codes into standardised categories to compare comprehensiveness between physicians. Rosenblatt et al. used 20 ‘diagnostic clusters’,21 where higher proportions of billed services across clusters represented more comprehensiveness. Shultz and Glazier went further by establishing a minimum threshold, where physicians needed at least 7 of 22 categories to meet comprehensive designation.
Evidence-based strategies: multi-modal comprehensiveness
Four studies combined multiple aspects of comprehensiveness to study a simulated dose–response relationship between comprehensiveness and outcomes. Methods built on concepts previously described, using standardised claims-based approaches for measuring the concomitant effects of cost, utilisation, and range of services.
Authors relied on standardised measures to determine range of services. Henry et al.13 used BETOS-derived methodology (representative of the most common PCP services) to standardise the scope of clinical services. The Mathematica team (O’Malley et al.14) developed their own standardisation methods (using claims data from PCPs participating in Medicare’s Comprehensive Primary Care initiative) to measure physician-level scope. This team also developed a practice-level range of services measure based on specific Healthcare Common Procedure Coding System (HCPCS) codes representative categories of PCP services.15
The Mathematica team demonstrated the effect of comprehensiveness at the physician, practice, and population levels across their three publications. The team first demonstrated the effect of comprehensiveness (type, location, and range of services) on the cost and utilisation of health care with a detailed methodology.15 Next, they demonstrated the feasibility of these methods at the practice level using National Provider Identifiers (NPIs) and Taxpayer Identification Numbers (TINs).18
Evidence-based strategies: patient experience
Three studies demonstrated approaches to measuring patient-level perceptions of comprehensiveness. Authors used similar survey or qualitative analysis methods.
The Mathematica team18 highlighted the importance of patient surveys in complementing claims-based approaches to ensure a complete picture when measuring comprehensiveness at large. Shi et al.17 were early publishers of a validated 72-question instrument that specifically measured comprehensiveness. Etz et al.’s19 recent instrument, the Person-Centered Primary Care Measure (PCPCM), has gained international validation22,23 in its ability to capture patient perceived comprehensiveness parsimoniously (11 questions). Other survey instruments have validated aspects of comprehensiveness but have focused on transactional components of the patient experience and are double24 or triple25 the length of the PCPCM.
Discussion
Each of the methodologies identified to measure comprehensiveness have several benefits and drawbacks. Depending on the desired purpose and outcome of any given inquiry, the appropriate methodology should be utilised.
A claims-based methodology based around cost/utilisation outcomes is uniquely quantitative in nature, and thus offers robust data-driven insights. This approach is highly scalable and allows for objective comparisons across various settings and payment models. However, the reliance on quantitative measures may not capture some of the important qualitative and subjective considerations around comprehensiveness, such as patient experience. Furthermore, the accuracy of the claims data will directly impact the quality of the findings. Conversely, measuring comprehensiveness based on patient experience can capture some of the qualitative and subjective aspects of comprehensiveness, but response biases may pose a challenge to the objectivity of the findings. Assessing the range of services and scope of care to measure comprehensiveness can be done through both qualitative and quantitative methodologies, and can produce an objective finding for health systems and governments alike to quickly capture comprehensiveness. Unfortunately, measuring the range of services and/or scope of care alone may not fully capture the full nature of comprehensiveness, which also includes elements of patient experience and cost/utilisation. A multi-modal approach to capture comprehensiveness is ideal, as multiple forms of methodologies can be utilised, both quantitative and qualitative, capturing the full breadth of comprehensiveness. However, this approach can be logistically challenging both due to time and cost involved in conducting such a massive investigation.
Ultimately, the methodology used to measure comprehensiveness can be a unique mix of the above to suit the need of the inquiry being investigated. For example, a government measuring comprehensiveness nationwide may choose to utilise a multimodal approach to truly capture the entirety of comprehensiveness and make overarching policy changes, whereas a small rural primary care group may choose to simply measure patient experience through surveys to implement small changes locally in their practice.
Limitations and future study
This review is limited by a predominance of North American studies. Despite the international relevance of comprehensiveness in primary care, including published global frameworks affiliated with the World Health Organization (eg, Alma-Ata Declaration3), our methods did not identify articles relating to measuring comprehensiveness specifically in regions outside of North America. Our methods might reflect the limitations of PubMed indexing, the impact of excluding non-English language sources, and the inability to capture relevant grey literature. Future research could enhance the international representation of comprehensiveness measurement by incorporating multilingual databases and region-specific search strategies to represent diverse global healthcare systems.
Conclusion
Validated methods of measuring comprehensiveness in primary care include both quantitative and qualitative methods. This narrative review structured aspects of comprehensiveness into key categories – range of clinical services, cost and utilisation of health care, the impact on patient outcomes, and the context of the patient experience – to guide implementation of measurement methods. Practices, health systems, and researchers operationalising comprehensiveness measurement should consider the scope of comprehensiveness in the context of regionality to ensure alignment with local value-based care delivery models and population health priorities.
Data availability
Data sharing is not applicable as no new data were generated or analysed during this study.
References
1 Millis JS. The Millis Commission report. GP 1966; 34(6): 173-188 contd.
| Google Scholar | PubMed |
4 Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q 2005; 83(3): 457-502.
| Crossref | Google Scholar | PubMed |
5 Baughman D, Nasir R, Ngo L, et al. Defining comprehensiveness in primary care: a scoping review. J Prim Health Care 2023; 15(3): 253-261.
| Crossref | Google Scholar | PubMed |
6 Ferrari R. Writing narrative style literature reviews. Med Writ 2015; 24: 230-235.
| Crossref | Google Scholar |
7 Lindner S, Kaufman MR, Marino M, et al. A Medicaid Alternative Payment Model Program in Oregon led to reduced volume of imaging services. Health Aff 2020; 39(7): 1194-1201.
| Crossref | Google Scholar | PubMed |
8 Bazemore A, Petterson S, Peterson LE, et al. More comprehensive care among family physicians is associated with lower costs and fewer hospitalizations. Ann Fam Med 2015; 13(3): 206-213.
| Crossref | Google Scholar | PubMed |
9 Petterson S, Bazemore AW, Phillips RL, et al. Rewarding family medicine while penalizing comprehensiveness? Primary care payment incentives and health reform: the Patient Protection and Affordable Care Act (PPACA). J Am Board Fam Med 2011; 24(6): 637-638.
| Crossref | Google Scholar | PubMed |
10 Schultz SE, Glazier RH. Identification of physicians providing comprehensive primary care in Ontario: a retrospective analysis using linked administrative data. CMAJ Open 2017; 5(4): E856-E863.
| Crossref | Google Scholar | PubMed |
11 Rosenblatt RA, Hart LG, Gamliel S, et al. Identifying primary care disciplines by analyzing the diagnostic content of ambulatory care. J Am Board Fam Pract 1995; 8(1): 34-45.
| Google Scholar | PubMed |
12 Weiner JP, Starfield BH. Measurement of the primary care roles of office-based physicians. Am J Public Health 1983; 73(6): 666-671.
| Crossref | Google Scholar |
13 Henry TL, Petterson S, Phillips RS, et al. Comparing comprehensiveness in primary care specialties and their effects on healthcare costs and hospitalizations in Medicare beneficiaries. J Gen Intern Med 2019; 34(12): 2708-2710.
| Crossref | Google Scholar | PubMed |
14 O’Malley AS, Rich EC, Shang L, et al. New approaches to measuring the comprehensiveness of primary care physicians. Health Serv Res 2019; 54(2): 356-366.
| Crossref | Google Scholar | PubMed |
15 O’Malley AS, Rich EC, Shang L, et al. Practice-site-level measures of primary care comprehensiveness and their associations with patient outcomes. Health Serv Res 2021; 56(3): 371-377.
| Crossref | Google Scholar | PubMed |
16 Rich EC, O'Malley AS, Burkhart C, et al. Primary care practices providing a broader range of services have lower Medicare expenditures and emergency department utilization. J Gen Intern Med 2021; 36(9): 2796-2802.
| Crossref | Google Scholar |
17 Shi L, Starfield B, Xu J. Validating the adult primary care assessment tool. J Fam Pract 2001; 50(2): 15.
| Google Scholar |
18 O’Malley AS, Rich EC. Measuring comprehensiveness of Primary Care: challenges and opportunities. J Gen Intern Med 2015; 30(Suppl 3): 568-575.
| Crossref | Google Scholar | PubMed |
19 Etz RS, Zyzanski SJ, Gonzalez MM, et al. A new comprehensive measure of high-value aspects of primary care. Ann Fam Med 2019; 17(3): 221-230.
| Crossref | Google Scholar | PubMed |
20 Centers for Medicare & Medicaid Services. Restructured BETOS Classification System. Available at https://data.cms.gov/provider-summary-by-type-of-service/provider-service-classifications/restructured-betos-classification-system [accessed 28 November 2022].
21 Schneeweiss R, Rosenblatt RA, Cherkin DC, et al. Diagnosis clusters: a new tool for analyzing the content of ambulatory medical care. Med Care 1983; 21(1): 105-122.
| Crossref | Google Scholar | PubMed |
22 Zyzanski SJ, Gonzalez MM, O’Neal JP, et al. Measuring primary care across 35 OECD countries. Ann Fam Med 2021; 19(6): 547-552.
| Crossref | Google Scholar | PubMed |
23 Tse ETY, Lam CLK, Wong CKH, et al. Exploration of the psychometric properties of the Person-Centred Primary Care Measure (PCPCM) in a Chinese primary care population in Hong Kong: a cross-sectional validation study. BMJ Open 2021; 11(9): e052655.
| Crossref | Google Scholar | PubMed |
24 Agency for Healthcare Research and Quality. What Are CAHPS Surveys? CAHPS Patient Experience Surveys and Guidance. Available at https://www.ahrq.gov/cahps/surveys-guidance/index.html [accessed 26 March 2023].
25 NHS England. GP Patient Survey. Statistical work areas. Available at https://www.england.nhs.uk/statistics/statistical-work-areas/gp-patient-survey/ [accessed 26 March 2023].
