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This study examines the effect of hospital mergers on hospital activity and performance in the English secondary care sector. Preliminary results show positive effects on hospital activity and significant improvements in performance. Policy implications suggest that hospital mergers influence the type and quality of services provided. The study acknowledges limitations in the methodology and proposes potential solutions.
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Do mergers affect hospital outcomes? Evidence from the English secondary care sector - Preliminary results - Vanessa Cirulli*, Giorgia Marini***vanessa.cirulli@uniroma1.it**giorgia.marini@uniroma1.it • Italian Health Economics Association (AIES) • 23rd Annual Conference • Naples, 27-29 September 2018
Goal To assess the effect of hospital mergers on hospital outcomes, i.e. on hospital activity and performance. In England, over the past twenty-five years, there have been marked changes in organizational structures and budgetary arrangements in the NHS causing, among other things, a widespread merger activity in the hospital sector. The number of hospital providers in England has in fact decreased by 13% between 2000 and 2008, from 195 acute and specialist Trusts in 2000 to 169 in 2008.
Data • Longitudinal data, available annually for a period of 8 years from 2001 to 2008. It contains information on all acute and specialist hospitals in England • Unique identifier for each hospital • Unique dataset combines information from several data sources (mainly administrative data): • performance indicators (Healthcare commission, CQC) • hospital characteristics (Hospital Episode Statistics - HES) • Hospital Activity Statistics (HAS) • the Medical and Dental Workforce Census (Department of Health data from individual hospitals’ websites)
Policy Variable • merged = 1 if the hospital is the result of a merger in a given year, and it is zero otherwise (snapshot effect) • merged_forward= equals 1 in the year the new merged hospital starts its activity and subsequent years, and zero otherwise (persistent effect)
Control Variables • Number of available beds • Type of hospitals (teaching vs. non-teaching) • Proportion of patients aged 0-14 and 60+ and proportion of females • Number of tests • Number of theatres • Medical and non-medical staff • Median waiting times • ALOS • HHI • FT dummy (ft=1 from year trust gains Foundation status, onwards)
Empirical methodology • DID methodology • We test whether: • there are any differences in the level and in the composition of hospital activity between merged and non-merged Trusts • the merger activity has made any difference at all • there are long-standing differences in the level and in the composition of hospital activity between these different types of organisations, which have made some of them more likely to merge than others
Empirical methodology • We consider 9 different measures of hospital activity • We compare these measures over time for merged Trusts and non-merged Trusts • We explore the robustness of our results by using different combinations of controls and different estimation methods (OLS and fixed effects) • Moreover, we analyze the performance rating (from level 1 = low to 4 = high) by using a multinomial logistic model, considering level 4 the baseline comparison group in which we include hospital characteristics (teaching, specialist and London) and other policy interventions (FT)
Inpatient admissions, 2000-2008 Elective admissions, 2000-2008 Patients attending first outpatient appointment, 2000-2008 Emergency admissions, 2000-2008
Patients first visiting A&E department, 2000-2008 Elective-emergency ratio, 2000-2008 Daycases, 2000-2008 Inpatient-outpatient ratio, 2000-2008 Daycase-elective ratio, 2000-2008
Preliminary conclusions • Policy effects • In the year of merger and onward, the effect on hospital activity is always positive (except for elective-emergency ratio) while the effect on hospital performance is positive and always significant • Policy implications • Preliminary results suggest merging activity in the hospital sector affect the type of service provided • Performance is positively affected by hospital mergers • Limits and possible solutions • Methodological perspective • The DID methodology assumes random assignment to the treatment group, whereas in the context of Trust mergers, assignment of Trusts to the treatment and control groups is not random. The estimation of the effect of Trust mergers may be biased by the existence of confounding factors solution: matching method • Policy perspective • Mergers in the public sector are planned by the regulator: there might be an anticipation effect possible solution: add some lags in the empirical specification • Mergers occurred in different years possible solution: wave analysis
Thank you for your attention Comments are welcome!
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