Estimated impact from the withdrawal of primary care financial incentives on selected indicators of quality of care in Scotland: controlled interrupted time series analysis

Abstract

ObjectiveTo determine whether the withdrawal of the Quality and Outcomes Framework (QOF) scheme in primary care in Scotland in 2016 had an impact on selected recorded quality of care, compared with England where the scheme continued.DesignControlled interrupted time series regression analysis.SettingGeneral practices in Scotland and England.Participants979 practices with 5 599 171 registered patients in Scotland, and 7921 practices with 56 270 628 registered patients in England in 2013-14, decreasing to 864 practices in Scotland and 6873 in England in 2018-19, mainly due to practice mergers.Main outcome measuresChanges in quality of care at one year and three years after withdrawal of QOF financial incentives in Scotland at the end of the 2015-16 financial year for 16 indicators (two complex processes, nine intermediate outcomes, and five treatments) measured annually for financial years from 2013-14 to 2018-19.ResultsA significant decrease in performance was observed for 12 of the 16 quality of care indicators in Scotland one year after QOF was abolished and for 10 of the 16 indicators three years after QOF was abolished, compared with England. At three years, the absolute percentage point difference between Scotland and England was largest for recording (by tick box) of mental health care planning (−40.2 percentage points, 95% confidence interval −45.5 to −35.0) and diabetic foot screening (−22.8, −33.9 to −11.7). Substantial reductions were, however, also observed for intermediate outcomes, including blood pressure control in patients with peripheral arterial disease (−18.5, −22.1 to −14.9), stroke or transient ischaemic attack (−16.6, −20.6 to −12.7), hypertension (−13.7, −19.4 to −7.9), diabetes (−12.7, −15.0 to −12.4), or coronary heart disease (−12.8, −14.9 to −10.8), and for glycated haemoglobin control in people with HbA1clevels ≤75 mmol/mol (−5.0, −8.4 to −1.5). No significant differences were observed between Scotland and England for influenza immunisation and antiplatelet or anticoagulant treatment for coronary heart disease three years after withdrawal of incentives.ConclusionThe abolition of financial incentives in Scotland was associated with reductions in recorded quality of care for most performance indicators. Changes to pay for performance should be carefully designed and implemented to monitor and respond to any reductions in care quality.

Does shortage of GPs matter? A cross-sectional study of practice population life expectancy

“…A recent House of Commons report acknowledged that the number of FTE GPs is insufficient and declining, and that access and continuity had declined. 37 It is thus worrying that the findings in the current study, although cross-sectional, suggest that these declines may have adversely affected life expectancy, even before the pandemic.…”

“…The finding in the current study suggests that further research is required into the potential effects of reducing or withdrawing the QOF scheme before any policy decisions. 37 …”

Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service

“…For researchers, the key implication is to recognise that only using hospital data is likely to seriously under-ascertain many conditions (although it will identify people with more severe disease for some conditions like heart failure), which will particularly matter in studies of multimorbidity or in studies where mental health is important. There are, however, certain circumstances where it is appropriate to use primary care data alone, for example when examining trajectories of workload pressures in primary care [ 39 ] or changes in quality of care in relation to financial incentives offered to general practitioners [ 40 ]. Further research is needed to examine the validity of diagnoses recorded in both primary and secondary care, with accurate estimation of false positive and false negative rates for different choices of data source.…”

What is the role of randomised trials in implementation science?

“…For example, a reanalysis of cluster randomised trials as interrupted time series found that effect estimates were largely concordant [ 36 ]. Rigorous quasi-experimental studies can make important policy contributions where randomisation was not acceptable or feasible, for example, in examining the effects of withdrawing financial incentives on adherence to primary care indicators [ 37 ].…”