Application of the Mantel-Haenszel odds ratio in validation of hospital episode statistics data.
The National Health Service reforms have led to a growing need to determine the efficiency and cost effectiveness of health care provision. Resource utilization and the factors that influence it form a vital part of the information procured by commissioners of health care. Currently the most comprehensive source of routinely collected data is the Hospital Episode Statistics database. This database provides the most complete coverage of all areas of hospital inpatient services; these services account for up to 70% of the health care budget. Several studies have investigated the integrity of these data, but they have been concerned only with a subset of the data or with particular hospitals. This paper derives a method of data validation that can be applied either regionally or nationally to two key fields within the database: in this instance, consultant specialty and principal diagnosis. The process uses the Mantel-Haenszel odds ratio estimate to reveal large anomalies within either specialty of diagnostic coding. Within the West Midlands, it was generally observed that diagnosis codes are coded more consistently than consultant codes. However, problems occur due to incomplete or incorrect diagnostic entries and these anomalies are irregular across provider units. In contrast, anomalies within Korner specialty codes are associated predominantly with maternity, obstetrics, geriatric and general medicine. A large number of these anomalies are well understood within the context of local practice variation. Nevertheless, many anomalies remain within a wide range of other specialties where further investigation is warranted. Where systematic error is found, provider units should be notified in order to improve data consistency and enhance quality for future data users and health care planners.
Gilthorpe
M S
MS
Department of Public Health and Epidemiology, Medical School, University of Birmingham, UK.
D003362:Cost-Benefit Analysis; D003625:Data Collection; D003627:Data Interpretation, Statistical; D003953:Diagnosis-Related Groups / Q000145:classification; D017598:Efficiency, Organizational; D017050:Episode of Care; D005260:Female; D006302:Health Services Research / Q000379:methods*; D006779:Hospitals, Public / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008511:Medicine / Q000706:statistics & numerical data; D016017:Odds Ratio; D013038:Specialization; D013222:State Medicine / Q000706:statistics & numerical data; D006113:United Kingdom