Impact of a national primary care pay-for-performance scheme on ambulatory care sensitive hospital admissions: a small-area analysis in England

Comparing the clinical practice and prescribing safety of locum and permanent doctors: observational study of primary care consultations in England

BACKGROUND

Temporary doctors, known as locums, are a key component of the medical workforce in the NHS but evidence on differences in quality and safety between locum and permanent doctors is limited. We aimed to examine differences in the clinical practice, and prescribing safety for locum and permanent doctors working in primary care in England.

METHODS

We accessed electronic health care records (EHRs) for 3.5 million patients from the CPRD GOLD database with linkage to Hospital Episode Statistics from 1st April 2010 to 31st March 2022. We used multi-level mixed effects logistic regression to compare consultations with locum and permanent GPs for several patient outcomes including general practice revisits; prescribing of antibiotics; strong opioids; hypnotics; A&E visits; emergency hospital admissions; admissions for ambulatory care sensitive conditions; test ordering; referrals; and prescribing safety indicators while controlling for patient and practice characteristics.

RESULTS

Consultations with locum GPs were 22% more likely to involve a prescription for an antibiotic (OR = 1.22 (1.21 to 1.22)), 8% more likely to involve a prescription for a strong opioid (OR = 1.08 (1.06 to 1.09)), 4% more likely to be followed by an A&E visit on the same day (OR = 1.04 (1.01 to 1.08)) and 5% more likely to be followed by an A&E visit within 1 to 7 days (OR = 1.05 (1.02 to 1.08)). Consultations with a locum were 12% less likely to lead to a practice revisit within 7 days (OR = 0.88 (0.87 to 0.88)), 4% less likely to involve a prescription for a hypnotic (OR = 0.96 (0.94 to 0.98)), 15% less likely to involve a referral (OR = 0.85 (0.84 to 0.86)) and 19% less likely to involve a test (OR = 0.81 (0.80 to 0.82)). We found no evidence that emergency admissions, ACSC admissions and eight out of the eleven prescribing safety indicators were different if patients were seen by a locum or a permanent GP.

CONCLUSIONS

Despite existing concerns, the clinical practice and performance of locum GPs did not appear to be systematically different from that of permanent GPs. The practice and performance of both locum and permanent GPs is likely shaped by the organisational setting and systems within which they work.

Impact of prevention in primary care on costs in primary and secondary care for people with serious mental illness

A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare.

Predicting hospitalisations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study

OBJECTIVE

To predict older adults' risk of avoidable hospitalisation related to ambulatory care sensitive conditions (ACSC) using machine learning applied to administrative health data of Ontario, Canada.

DESIGN, SETTING AND PARTICIPANTS

A retrospective cohort study was conducted on a large cohort of all residents covered under a single-payer system in Ontario, Canada over the period of 10 years (2008-2017). The study included 1.85 million Ontario residents between 65 and 74 years old at any time throughout the study period.

DATA SOURCES

Administrative health data from Ontario, Canada obtained from the (ICES formely known as the Institute for Clinical Evaluative Sciences Data Repository.

MAIN OUTCOME MEASURES

Risk of hospitalisations due to ACSCs 1 year after the observation period.

RESULTS

The study used a total of 1 854 116 patients, split into train, validation and test sets. The ACSC incidence rates among the data points were 1.1% for all sets. The final XGBoost model achieved an area under the receiver operating curve of 80.5% and an area under precision-recall curve of 0.093 on the test set, and the predictions were well calibrated, including in key subgroups. When ranking the model predictions, those at the top 5% of risk as predicted by the model captured 37.4% of those presented with an ACSC-related hospitalisation. A variety of features such as the previous number of ambulatory care visits, presence of ACSC-related hospitalisations during the observation window, age, rural residence and prescription of certain medications were contributors to the prediction. Our model was also able to capture the geospatial heterogeneity of ACSC risk in Ontario, and especially the elevated risk in rural and marginalised regions.

CONCLUSIONS

This study aimed to predict the 1-year risk of hospitalisation from ambulatory-care sensitive conditions in seniors aged 65-74 years old with a single, large-scale machine learning model. The model shows the potential to inform population health planning and interventions to reduce the burden of ACSC-related hospitalisations.

Bridging the impactibility gap in population health management: a systematic review

OBJECTIVES

Assess whether impactibility modelling is being used to refine risk stratification for preventive health interventions.

DESIGN

Systematic review.

SETTING

Primary and secondary healthcare populations.

PAPERS

Articles published from 2010 to 2020 on the use or implementation of impactibility modelling in population health management, reported with the terms 'intervenability', 'amenability', and 'propensity to succeed' (PTS) and associated with the themes 'care sensitivity', 'characteristic responders', 'needs gap', 'case finding', 'patient selection' and 'risk stratification'.

INTERVENTIONS

Qualitative synthesis to identify themes for approaches to impactibility modelling.

RESULTS

Of 1244 records identified, 20 were eligible for inclusion. Identified themes were 'health conditions amenable to care' (n=6), 'PTS modelling' (n=8) and 'comparison or combination with clinical judgement' (n=6). For the theme 'health conditions amenable to care', changes in practice did not reduce admissions, particularly for ambulatory care sensitive conditions, and sometimes increased them, with implementation noted as a possible issue. For 'PTS modelling', high costs and needs did not necessarily equate to high impactibility and targeting a larger number of individuals with disorders associated with lower costs had more potential. PTS modelling seemed to improve accuracy in care planning, estimation of cost savings, engagement and/or care quality. The 'comparison or combination with clinical judgement' theme suggested that models can reach reasonable to good discriminatory power to detect impactable patients. For instance, a model used to identify patients appropriate for proactive multimorbid care management showed good concordance with physicians (c-statistic 0.75). Another model employing electronic health record scores reached 65% concordance with nurse and physician decisions when referring elderly hospitalised patients to a readmission prevention programme. However, healthcare professionals consider much wider information that might improve or impede the likelihood of treatment impact, suggesting that complementary use of models might be optimum.

CONCLUSIONS

The efficiency and equity of targeted preventive care guided by risk stratification could be augmented and personalised by impactibility modelling.

Pay for performance in primary care: the contribution of the Programme for Improving Access and Quality of Primary Care (PMAQ) on avoidable hospitalisations in Brazil, 2009-2018

Background

Evidence on the effect of pay-for-performance (P4P) schemes on provider performance is mixed in low-income and middle-income countries. Brazil introduced its first national-level P4P scheme in 2011 (PMAQ-Brazilian National Programme for Improving Primary Care Access and Quality). PMAQ is likely one of the largest P4P schemes in the world. We estimate the association between PMAQ and hospitalisations for ambulatory care sensitive conditions (ACSCs) based on a panel of 5564 municipalities.

Methods

We conducted a fixed effect panel data analysis over the period of 2009–2018, controlling for coverage of primary healthcare, hospital beds per 10 000 population, education, real gross domestic product per capita and population density. The outcome is the hospitalisation rate for ACSCs among people aged 64 years and under per 10 000 population. Our exposure variable is defined as the percentage of family health teams participating in PMAQ, which captures the roll-out of PMAQ over time. We also provided several sensitivity analyses, by using alternative measures of the exposure and outcome variables, and a placebo test using transport accident hospitalisations instead of ACSCs.

Results

The results show a negative and statistically significant association between the rollout of PMAQ and ACSC rates for all age groups. An increase in PMAQ participating of one percentage point decreased the hospitalisation rate for ACSC by 0.0356 (SE 0.0123, p=0.004) per 10 000 population (aged 0–64 years). This corresponds to a reduction of approximately 60 829 hospitalisations in 2018. The impact is stronger for children under 5 years (−0.0940, SE 0.0375, p=0.012), representing a reduction of around 11 936 hospitalisations. Our placebo test shows that the association of PMAQ on the hospitalisation rate for transport accidents is not statistically significant, as expected.

Conclusion

We find that PMAQ was associated with a modest reduction in hospitalisation for ACSCs.