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Hospital heterogeneity: what drives the quality of health care

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  • Manhal Ali

    (University of Manchester)

  • Reza Salehnejad

    (University of Manchester)

  • Mohaimen Mansur

    (University of Manchester)

Abstract

A major feature of health care systems is substantial variation in health care quality across hospitals. The quality of stroke care widely varies across NHS hospitals. We investigate factors that may explain variations in health care quality using measures of quality of stroke care. We combine NHS trust data from the National Sentinel Stroke Audit with other data sets from the Office for National Statistics, NHS and census data to capture hospitals’ human and physical assets and organisational characteristics. We employ a class of non-parametric methods to explore the complex structure of the data and a set of correlated random effects models to identify key determinants of the quality of stroke care. The organisational quality of the process of stroke care appears as a fundamental driver of clinical quality of stroke care. There are rich complementarities amongst drivers of quality of stroke care. The findings strengthen previous research on managerial and organisational determinants of health care quality.

Suggested Citation

  • Manhal Ali & Reza Salehnejad & Mohaimen Mansur, 2018. "Hospital heterogeneity: what drives the quality of health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(3), pages 385-408, April.
    • Handle: RePEc:spr:eujhec:v:19:y:2018:i:3:d:10.1007_s10198-017-0891-9
    DOI: 10.1007/s10198-017-0891-9
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    1. Guccio, Calogero & Pignataro, Giacomo & Romeo, Domenica & Vidoli, Francesco, 2024. "Is austerity good for efficiency, at least? A counterfactual assessment for the Italian NHS," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    2. Christoph Strumann & Alexander Geissler & Reinhard Busse & Christoph Pross, 2022. "Can competition improve hospital quality of care? A difference-in-differences approach to evaluate the effect of increasing quality transparency on hospital quality," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1229-1242, September.
    3. Angela Meggiolaro & Carl Rudolf Blankart & Tom Stargardt & Jonas Schreyögg, 2023. "An econometric approach to aggregating multiple cardiovascular outcomes in German hospitals," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(5), pages 785-802, July.

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    More about this item

    Keywords

    Health care quality; Stroke; NHS; Machine learning; Regression trees; Panel data; Prediction; Mixed effects model;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • I10 - Health, Education, and Welfare - - Health - - - General
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

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