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The impact of disease severity adjustment on hospital standardised mortality ratios: Results from a service-wide analysis of ischaemic stroke admissions using linked pre-hospital, admissions and mortality data.

ABSTRACT: BACKGROUND:Administrative data are used to examine variation in thirty-day mortality across health services in several jurisdictions. Hospital performance measurement may be error-prone as information about disease severity is not typically available in routinely collected data to incorporate into case-mix adjusted analyses. Using ischaemic stroke as a case study, we tested the extent to which accounting for disease severity impacts on hospital performance assessment. METHODS:We linked all recorded ischaemic stroke admissions between July, 2011 and June, 2014 to death registrations and a measure of stroke severity obtained at first point of patient contact with health services, across New South Wales, Australia's largest health service jurisdiction. Thirty-day hospital standardised mortality ratios were adjusted for either comorbidities, as is typically done, or for both comorbidities and stroke severity. The impact of stroke severity adjustment on mortality ratios was determined using 95% and 99% control limits applied to funnel plots and by calculating the change in rank order of hospital risk adjusted mortality rates. RESULTS:The performance of the stroke severity adjusted model was superior to incorporating comorbidity burden alone (c-statistic = 0.82 versus 0.75; N = 17,700 patients, 176 hospitals). Concordance in outlier classification was 89% and 97% when applying 95% or 99% control limits to funnel plots, respectively. The sensitivity rates of outlier detection using comorbidity adjustment compared with gold-standard severity and comorbidity adjustment was 74% and 83% with 95% and 99% control limits, respectively. Corresponding positive predictive values were 74% and 91%. Hospital rank order of risk adjusted mortality rates shifted between 0 to 22 places with severity adjustment (Median = 4.0, Inter-quartile Range = 2-7). CONCLUSIONS:Rankings of mortality rates varied widely depending on whether stroke severity was taken into account. Funnel plots yielded largely concordant results irrespective of severity adjustment and may be sufficiently accurate as a screening tool for assessing hospital performance.

SUBMITTER: Gattellari M

PROVIDER: S-EPMC6528964 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo illustrate the development and use of standardised mortality rates (SMRs) as a trigger for quality improvement in a network of 27 hospitals.DesignThis research was a retrospective observational study. The primary outcome was in-hospital mortality. SMRs were calculated for All Patient Refined-Diagnosis-Related Groups (APR-DRGs) that reflect 80% of the Flemish hospital network mortality. Hospital mortality was modelled using logistic regression. The metrics were communicated to the member hospitals using a custom-made R-Shiny web application showing results at the level of the hospital, patient groups and individual patients. Experiences with the metric and strategies for improvement were shared in chief medical officer meetings organised by the Flemish hospital network.Setting27 Belgian hospitals.Participants1 198 717 hospital admissions for registration years 2009-2016.ResultsPatient gender, age, comorbidity as well as admission source and type were important predictors of mortality. Altogether the SMR models had a C-statistic of 88%, indicating good discriminatory capability. Seven out of ten APR-DRGs with the highest percentage of hospitals statistically significantly deviating from the benchmark involved malignancy. The custom-built web application and the trusted environment of the Flemish hospital network created an interoperable strategy to get to work with SMR findings. Use of the web application increased over time, with peaks before and after key discussion meetings within the Flemish hospital network. A concomitant reduction in crude mortality for the selected APR-DRGs from 6.7% in 2009 to 5.9% in 2016 was observed.ConclusionsThis study reported on the phased approach for introducing SMR reporting to trigger quality improvement. Prerequisites for the successful use of quality metrics in hospital benchmarks are a collaborative approach based on trust among the participants and a reporting platform that allows stakeholders to interpret and analyse the results at multiple levels.

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The impact of disease severity adjustment on hospital standardised mortality ratios: Results from a service-wide analysis of ischaemic stroke admissions using linked pre-hospital, admissions and mortality data.

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