Impact of primary care funding on patient satisfaction: a retrospective longitudinal study of English general practice, 2013-2016.

BACKGROUND: Providing high-quality clinical care and good patient experience are priorities for most healthcare systems. AIM: To understand the relationship between general practice funding and patient-reported experience. DESIGN AND SETTING: Retrospective longitudinal study of English general practice-level data for the financial years 2013-2014 to 2016-2017. METHOD: Data for all general practices in England from the General and Personal Medical Services database were linked to patient experience data from the GP Patient Survey (GPPS). Panel data multivariate regression was used to estimate the impact of general practice funding (current or lagged 1 year) per patient on GPPS-reported patient experience of access, continuity of care, professionalism, and overall satisfaction. Confounding was controlled for by practice, demographic, and GPPS responder characteristics, and for year effects. RESULTS: Inflation-adjusted mean total annual funding per patient was £133.66 (standard deviation [SD] = £39.46). In all models, higher funding was associated with better patient experience. In the model with lagged funding and practice fixed effects (model 6), a 1 SD increase in funding was associated with increases in scores in the domains of access (1.18%; 95% confidence interval [CI] = 0.89 to 1.47), continuity (0.86%; 95% CI = 0.19 to 1.52), professionalism of GP (0.47%; 95% CI = 0.22 to 0.71), professionalism of nurse (0.51%; 95% CI = 0.24 to 0.77), professionalism of receptionist (0.51%; 95% CI = 0.24 to 0.78), and in overall satisfaction (0.88%; 95% CI = 0.52 to 1.24). CONCLUSION: Better-funded general practices were more likely to have higher reported patient experience ratings across a wide range of domains.

Patient chosen gap payments in primary care: Predictions of patient acceptability, uptake and willingness to pay from a discrete choice experiment.

Compulsory co-payments limit access and may compromise quality in primary care. Patient Chosen Gap Payments (PCGPs) allow patients to specify a (voluntary) out-of-pocket contribution, creating an incentive for patient-centred care without the need for complex outcomes-based funding formulae. It is not yet known if widespread use of PCGP services is consistent with consumer preferences. We conducted a discrete choice experiment (DCE) in a sample of the adult Australian general population (n = 1457) during April 2019 to simulate patient choice between alternative primary care services and describe preferences for PCGP services. Participants also completed a supplementary valuation task in which participants reported their intended PCGP contribution for PCGP services. Finally, we conducted policy-simulations to predict market shares when PCGP clinics operate alongside the two existing models of primary care funding in Australia. Results suggest that patients prefer shorter wait time, longer consults, lower compulsory copayments, services with higher patient satisfaction ratings, choice of doctor and $0 suggested voluntary contribution for PCGP services. Policy-simulations suggest that high-quality PCGP services could obtain market share of up to 39% and voluntary contributions of up to $25.36 per service (95%CI: $10.24, $40.47), potentially adding $1.48 billion AUD in revenues and funding for primary care at no cost to government. Low-quality PCGP services are unlikely to capture significant market share and PCGP contributions were lowest for low-quality PCGP services ($12.12, 95%CI: $2.09, $26.34). Further field testing is recommended where (i) patients make consequential choices (e.g. real payments for simulated services), and (ii) dynamic effects on quality of care and utilisation can be observed; particularly in vulnerable populations. We conclude that PCGP services aligned with patient preferences could capture significant market share and substantially increase revenue to general practice.

Relationship between general practice capitation funding and the quality of primary care in England: a cross-sectional, 3-year study.

OBJECTIVE: To explore the relationship between general practice capitation funding and quality ratings based on general practice inspections. DESIGN: Cross-sectional study pooling 3 years of primary care administrative data. SETTING: UK primary care. PARTICIPANTS: 7310 practices (95% of all practices) in England which underwent Care Quality Commission (CQC) inspections between November 2014 and December 2017. MAIN OUTCOME MEASURES: CQC ratings. Ordered logistic regression methods were used to predict the relationship between practice capitation funding and CQC ratings in each of five domains of quality: caring, effective, responsive, safe and well led, together with an overall practice rating. RESULTS: Higher capitation funding per patient was significantly associated with higher CQC ratings across all five quality domains: caring (OR 1.14, 95% CI 1.04 to 1.23), effective (OR 1.08, 95% CI 1.00 to 1.16), responsive (OR 1.09, 95% CI 1.02 to 1.17), safe (OR 1.11, 95% CI 1.05 to 1.18), well led (OR 1.13, 95% CI 1.06 to 1.20) and overall rating (OR 1.13, 95% CI 1.06 to 1.19). CONCLUSION: Higher capitation funding was consistently associated with higher ratings across all CQC domains and in the overall practice rating. This study suggests that measured dimensions of the quality of care are related to the underlying capitation funding allocated to each general practice, implying that additional capitation funding may be associated with higher levels of primary care quality.

Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis.

BACKGROUND: Primary care provides the foundation for most modern health-care systems, and in the interests of equity, it should be resourced according to local need. We aimed to describe spatially the burden of chronic conditions and primary medical care funding in England at a low geographical level, and to measure how much variation in funding is explained by chronic condition prevalence and other patient and regional factors. METHODS: We used multiple administrative data sets including chronic condition prevalence and management data (2014/15), funding for primary-care practices (2015-16), and geographical and area deprivation data (2015). Data were assigned to a low geographical level (average 1500 residents). We investigated the overall morbidity burden across 19 chronic conditions and its regional variation, spatial clustering and association with funding and area deprivation. A linear regression model was used to explain local variation in spending using patient demographics, morbidity, deprivation and regional characteristics. RESULTS: Levels of morbidity varied within and between regions, with several clusters of very high morbidity identified. At the regional level, morbidity was modestly associated with practice funding, with the North East and North West appearing underfunded. The regression model explained 39% of the variability in practice funding, but even after adjusting for covariates, a large amount of variability in funding existed across regions. High morbidity and, especially, rural location were very strongly associated with higher practice funding, while associations were more modest for high deprivation and older age. CONCLUSIONS: Primary care funding in England does not adequately reflect the contemporary morbidity burden. More equitable resource allocation could be achieved by making better use of routinely available information and big data resources. Similar methods could be deployed in other countries where comparable data are collected, to identify morbidity clusters and to target funding to areas of greater need.

Impact of primary care funding on secondary care utilisation and patient outcomes: a retrospective cross-sectional study of English general practice.

BACKGROUND: In international studies, greater investment in primary health care is associated with improved population health outcomes. AIM: To determine whether investment in general practice is associated with secondary care utilisation, patient satisfaction, and clinical outcomes. DESIGN AND SETTING: Retrospective cross-sectional study of general practices in England, 2014-2015. METHOD: Practice-level data were stratified into three groups according to GP contract type: national General Medical Services (GMS) contracts, with or without the capitation supplement (mean practice income guarantee), or local Personal Medical Services (PMS) contracts. Regression models were used to explore associations between practice funding (capitation payments and capitation supplements) and secondary care usage, patient satisfaction (general practice patient survey scores), and clinical outcomes (Quality and Outcomes Framework [QOF] scores). The authors conducted financial modelling to predict secondary care cost savings associated with notional changes in primary care funding. RESULTS: Mean capitation payments per patient were £69.82 in GMS practices in receipt of capitation supplements (n = 2784), £78.79 in GMS practices without capitation supplements (n = 1672), and £84.43 in PMS practices (n = 3022). The mean capitation supplement was £5.72 per patient. Financial modelling demonstrated little or no relationship between capitation payments and secondary care costs. In contrast, notional investment in capitation supplements was associated with modelled savings in secondary care costs. The relationship between funding and patient satisfaction was inconsistent. QOF performance was not associated with funding in any practice type. CONCLUSION: Capitation payments appear to be broadly aligned to patient need in terms of secondary care usage. Supplements to the current capitation formula are associated with reduced secondary care costs.