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Objective: To study the impact of casemix variations within primary diagnostic groups on hospital standardised mortality ratios and to improve the current HSMR model., Design: Descriptive, model analysis., Method: We calculated the HSMRs and the standardised mortality ratios at diagnostic group level (SMRs) of 84 Dutch hospitals over a 5-year period using 2 HSMR models. Both models adjusted for severity of diagnosis at admission (primary diagnostic level according to the International Classification of Diseases (ICD-9)) using a severity classification. The severity classification in the current model (model 1) was based on WHO mortality data, whereas our adapted 'Dutch' model (model 2) was based on Dutch hospital mortality data. The HSMRs and SMRs and the corresponding c-statistics of both models were compared in order to test whether the models adequately adjusted for high-risk versus low-risk ICD-9 codes., Results: Model 1 did not adequately adjust for casemix differences on the ICD-9 diagnostic level for 40 out of 48 diagnostic groups analysed; model 2 did not adequately adjust for 25 diagnostic groups. Model 2 showed better c-statistics than model 1. Relative differences between models 1 and 2 in SMR outcomes varied from -63% to 202% when comparing model 2 to model 1. At the HSMR level these differences varied from -6.7% to 4.3%., Conclusion: The HSMR model currently used in the Netherlands does not adequately adjust for casemix differences at the level of ICD-9 primary diagnoses. A model using a severity classification of ICD-9 codes based on actual Dutch hospital mortality allows for a better, albeit not perfect, adjustment. We recommend implementation of the 'Dutch' severity classification in order to improve the HSMR model.

Objective: To investigate the impact of coding variations on 'hospital standardized mortality ratio' (HSMR) and to define variation reduction measures., Design: Retrospective, descriptive., Method: We analysed coding variations in HSMR parameters for main diagnosis, urgency of the admission and comorbidity in the national medical registration (LMR) database of admissions in 6 Dutch top clinical hospitals during 2003-2007. More than a quarter of these admission records had been included in the HSMR calculation. Admissions with ICD-9 main diagnosis codes that were excluded from HSMR calculations were investigated for inter-hospital variability and correct exclusion. Variation in coding admission type was signalled by analyzing admission records with diagnoses that had an emergency nature by their title. Variation in the average number of comorbidity diagnoses per admission was determined as an indicator for coding variation. Interviews with coding teams were used to check whether the conclusions of the analysis were correct., Results: Over 165,000 admissions that were excluded from HSMR calculations showed large variability between hospitals. This figure was 40% of all admissions that were included. Of the admissions with a main diagnosis indicating an emergency, 34% to 93% were recorded as an emergency. The average number of comorbidity diagnoses varied between hospitals from 0.9 to 3.0 per admission., Conclusion: Coding of main diagnoses, urgency of admission and comorbidities showed strong inter-hospital variation with a potentially large impact on the HSMR outcomes of the hospitals. Coding variations originated from differences in interpretation of coding rules, differences in coding capacity, quality of patient records and discharge documentation and timely delivery of these.