Primary care mortality and the impact of funding: a national longitudinal study 2013 -2016

Talk Code: 
H.5
Presenter: 
Veline L'Esperance
Co-authors: 
Veline L’Esperance1, Hugh Gravelle2, Peter Schofield1, Mark Ashworth1
Author institutions: 
1. School of Population Health & Environmental Sciences, King’s College London, 2. Centre for Health Economics, University of York

Problem

Previous studies reporting an association between primary care investment and practice-level mortality have relied on estimates of mortality or been confined to small geographical areas. We investigated the relationship between funding and actual mortality rates, both at practice-level, in a national sample of practices in England.

Approach

We combined seven datasets for all general practices in England (n=7310), 2013-2016: (i) General and Personal Medical Services database , providing workforce and patient data; (ii) NHS payments to General Practice, which records payments to practices; (iii) Quality and Outcomes Framework describing performance on clinical achievement indicators in LTCs, (iv) deprivation data for each practice; (v) neighbourhood ethnicity for each practice; (vi) patient experience scores from the General Practice Patient Survey; and (vii)practice-level mortality. We estimated a variety of count data models using longitudinal practice-level data to examine the association between general practice funding and practice-level mortality. These included (a)pooled models; (b) practice fixed effect models; (c) random effects models; and (d) Mundlak specification. We used the Poisson specification for models with practice fixed effects and allowed for over-dispersion of errors by using robust standard errors. Practice-year observations with <5 deaths/year were truncated. We entered the number of general practitioners, nurses and administrative staff in four different ways in the exponential mean function. The goodness of fit for each model was explored using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), both of which penalise the number of coefficients estimated; smaller AIC and BIC scores indicate better fitting models.

Findings

The inflation adjusted mean total funding per patient across the study period was £133.66 (standard deviation £39.46), adjusted to 2016 costs. The mean total deaths per practice increased from 61.23 (SD 46.15) in 2013/14 to 65.78 (SD 50.52) in 2016/17. Premature mortality (deaths in those <75 years) also increased from 19.22(SD 13.09) in 2013/14 to 20.86 (SD14.45) in 2016/17. Reduced practice mortality rates were significantly associated with increased total funding (B coefficient -0.003; %95CI: -0.0004, -0.0001). Other characteristics associated with reduced mortality included: practices in receipt of the capitation supplement, (MPIG) (B coefficient -0.02; %95CI: -0.04, -0.01); practices with less deprived populations (B coefficient 0.011; %95CI: 0.010, 0.011); and practices with increased overall patient experience scores (B coefficient -0.001; %95CI: -0.001, -0.0001). The relationship between mortality and patient age was U-shaped, with extremes of age 0- 4 years (B coefficient 0.03; %95CI: 0.03, 0.04) and ≥75 years (B coefficient 0.10; %95CI:0.10, 0.11) significantly associated with practice mortality.

Consequences

This is the first study to examine general practice funding and practice-level mortality rates in England. We found that practice mortality rates are inversely related to the underlying funding allocated to each general practice. Further work is needed to determine the likely mechanism of any causal relationship between funding and mortality.

Submitted by: 
Veline L&#039;Esperance
Funding acknowledgement: 
The work was funded by the National Institute for Health Research (NIHR) who funded a Doctoral Research Fellowship for VL (reference, DRF-2017-10-132). HG was funded by the UK NIHR Policy Research Programme (Policy Research Unit in the Economics of Health and Social Care Systems: Ref 103/0001).