Cargando…
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
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...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528964/ https://www.ncbi.nlm.nih.gov/pubmed/31112556 http://dx.doi.org/10.1371/journal.pone.0216325 |
_version_ | 1783420308185677824 |
---|---|
author | Gattellari, Melina Goumas, Chris Jalaludin, Bin Worthington, John |
author_facet | Gattellari, Melina Goumas, Chris Jalaludin, Bin Worthington, John |
author_sort | Gattellari, Melina |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6528964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65289642019-05-31 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 Gattellari, Melina Goumas, Chris Jalaludin, Bin Worthington, John PLoS One Research Article 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. Public Library of Science 2019-05-21 /pmc/articles/PMC6528964/ /pubmed/31112556 http://dx.doi.org/10.1371/journal.pone.0216325 Text en © 2019 Gattellari et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Gattellari, Melina Goumas, Chris Jalaludin, Bin Worthington, John 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528964/ https://www.ncbi.nlm.nih.gov/pubmed/31112556 http://dx.doi.org/10.1371/journal.pone.0216325 |
work_keys_str_mv | AT gattellarimelina theimpactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT goumaschris theimpactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT jalaludinbin theimpactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT worthingtonjohn theimpactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT gattellarimelina impactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT goumaschris impactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT jalaludinbin impactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata AT worthingtonjohn impactofdiseaseseverityadjustmentonhospitalstandardisedmortalityratiosresultsfromaservicewideanalysisofischaemicstrokeadmissionsusinglinkedprehospitaladmissionsandmortalitydata |