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Hospital Standardized Mortality Ratios: Sensitivity Analyses on the Impact of Coding
Author(s) -
Bottle Alex,
Jarman Brian,
Aylin Paul
Publication year - 2011
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/j.1475-6773.2011.01295.x
Subject(s) - medicine , funnel plot , case mix index , demography , mortality rate , coding (social sciences) , comorbidity , propensity score matching , standardized mortality ratio , emergency medicine , meta analysis , statistics , publication bias , surgery , nursing , mathematics , sociology
. Hospital standardized mortality ratios (HSMRs) are derived from administrative databases and cover 80 percent of in‐hospital deaths with adjustment for available case mix variables. They have been criticized for being sensitive to issues such as clinical coding but on the basis of limited quantitative evidence.Methods. In a set of sensitivity analyses, we compared regular HSMRs with HSMRs resulting from a variety of changes, such as a patient‐based measure, not adjusting for comorbidity, not adjusting for palliative care, excluding unplanned zero‐day stays ending in live discharge, and using more or fewer diagnoses.Results. Overall, regular and variant HSMRs were highly correlated ( ρ >0.8), but differences of up to 10 points were common. Two hospitals were particularly affected when palliative care was excluded from the risk models. Excluding unplanned stays ending in same‐day live discharge had the least impact despite their high frequency. The largest impacts were seen when capturing postdischarge deaths and using just five high‐mortality diagnosis groups.Conclusions. HSMRs in most hospitals changed by only small amounts from the various adjustment methods tried here, though small‐to‐medium changes were not uncommon. However, the position relative to funnel plot control limits could move in a significant minority even with modest changes in the HSMR.