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06-Jul-2016
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Arch Hellen Med, 33(4), July-August 2016, 489-497 ORIGINAL PAPER "Big data" in health care A. Christodoulakis,1 H. Karanikas,2 A. Billiris,1 E. Thireos,3 N. Pelekis4 |
OBJECTIVE To examine how common key performance indicators (KPIs) change when clinical workload indicators of hospitals, based on diagnosis-related group (DRG) data, are incorporated in the measurement analysis. From the data and knowledge management perspective the available data fulfill all four "V" challenges (volume, velocity, variety, veracity) and the "D" challenge (distribution of data sources) that characterize the "big data" era.
METHOD Analysis was made of the annual detailed financial, operational and patient data as recorded by the ESY.net web application, for 129 Greek National Health System (NHS) hospitals. Four KPIs were calculated based on the hospital financial and patient data. The indicators were then adjusted to the case mix (i.e., clinical workload) of the units, using a hospital clinical weight (HCW) indicator based on the DRG data.
RESULTS Significant changes in the KPIs resulted from adjustment according to DRG, in both percentages and the relative ranking of hospitals as efficient and inefficient. After adjustment, improvement in indicators and relative ranking was observed for hospitals with more severe than average incidents, such as cancer hospitals, cardiac surgery centers, etc., but also for some general hospitals and health centers, while other small health centers and regional hospitals ranked lower after adjustment.
CONCLUSIONS The significant changes in the performance ranking of hospitals observed after adjustment of the KPIs according to the clinical workload of the units, render this tool inappropriate for use by decision makers in the health care sector, i.e., the Ministry of Health (MoH), as they provide misleading information when the diversity in the HCW is not taken into account. The results of the study support the need for re-evaluation of the assessment methodology of Greek NHS hospitals, in order to identify the weaknesses in the system, improve its efficiency and achieve improvement.
Key words: Health big data, Clinical workload indicators, Hospital performance, Key performance indicators.
