[Variations in patient data coding affect hospital standardized mortality ratio (HSMR)].

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.