Literature DB >> 29727371

Mortality Measures to Profile Hospital Performance for Patients With Septic Shock.

Allan J Walkey1, Meng-Shiou Shieh2,3, Vincent X Liu4, Peter K Lindenauer2,3.   

Abstract

OBJECTIVES: Sepsis care is becoming a more common target for hospital performance measurement, but few studies have evaluated the acceptability of sepsis or septic shock mortality as a potential performance measure. In the absence of a gold standard to identify septic shock in claims data, we assessed agreement and stability of hospital mortality performance under different case definitions.
DESIGN: Retrospective cohort study.
SETTING: U.S. acute care hospitals. PATIENTS: Hospitalized with septic shock at admission, identified by either implicit diagnosis criteria (charges for antibiotics, cultures, and vasopressors) or by explicit International Classification of Diseases, 9th revision, codes.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: We used hierarchical logistic regression models to determine hospital risk-standardized mortality rates and hospital performance outliers. We assessed agreement in hospital mortality rankings when septic shock cases were identified by either explicit International Classification of Diseases, 9th revision, codes or implicit diagnosis criteria. Kappa statistics and intraclass correlation coefficients were used to assess agreement in hospital risk-standardized mortality and hospital outlier status, respectively. Fifty-six thousand six-hundred seventy-three patients in 308 hospitals fulfilled at least one case definition for septic shock, whereas 19,136 (33.8%) met both the explicit International Classification of Diseases, 9th revision, and implicit septic shock definition. Hospitals varied widely in risk-standardized septic shock mortality (interquartile range of implicit diagnosis mortality: 25.4-33.5%; International Classification of Diseases, 9th revision, diagnosis: 30.2-38.0%). The median absolute difference in hospital ranking between septic shock cohorts defined by International Classification of Diseases, 9th revision, versus implicit criteria was 37 places (interquartile range, 16-70), with an intraclass correlation coefficient of 0.72, p value of less than 0.001; agreement between case definitions for identification of outlier hospitals was moderate (kappa, 0.44 [95% CI, 0.30-0.58]).
CONCLUSIONS: Risk-standardized septic shock mortality rates varied considerably between hospitals, suggesting that septic shock is an important performance target. However, efforts to profile hospital performance were sensitive to septic shock case definitions, suggesting that septic shock mortality is not currently ready for widespread use as a hospital quality measure.

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Year:  2018        PMID: 29727371      PMCID: PMC6045435          DOI: 10.1097/CCM.0000000000003184

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  43 in total

1.  Variation in the care of septic shock: the impact of patient and hospital characteristics.

Authors:  Tara Lagu; Michael B Rothberg; Brian H Nathanson; Penelope S Pekow; Jay S Steingrub; Peter K Lindenauer
Journal:  J Crit Care       Date:  2012-02-01       Impact factor: 3.425

Review 2.  A Framework for the Development and Interpretation of Different Sepsis Definitions and Clinical Criteria.

Authors:  Derek C Angus; Christopher W Seymour; Craig M Coopersmith; Clifford S Deutschman; Michael Klompas; Mitchell M Levy; Gregory S Martin; Tiffany M Osborn; Chanu Rhee; R Scott Watson
Journal:  Crit Care Med       Date:  2016-03       Impact factor: 7.598

3.  Physician Variation in Time to Antimicrobial Treatment for Septic Patients Presenting to the Emergency Department.

Authors:  Ithan D Peltan; Kristina H Mitchell; Kristina E Rudd; Blake A Mann; David J Carlbom; Catherine L Hough; Thomas D Rea; Samuel M Brown
Journal:  Crit Care Med       Date:  2017-06       Impact factor: 7.598

4.  A combined comorbidity score predicted mortality in elderly patients better than existing scores.

Authors:  Joshua J Gagne; Robert J Glynn; Jerry Avorn; Raisa Levin; Sebastian Schneeweiss
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5.  Quality of Quality Measurement: Impact of Risk Adjustment, Hospital Volume, and Hospital Performance.

Authors:  Laurent G Glance; Yue Li; Andrew W Dick
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6.  The risks of risk adjustment.

Authors:  L I Iezzoni
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7.  Development, validation, and results of a measure of 30-day readmission following hospitalization for pneumonia.

Authors:  Peter K Lindenauer; Sharon-Lise T Normand; Elizabeth E Drye; Zhenqiu Lin; Katherine Goodrich; Mayur M Desai; Dale W Bratzler; Walter J O'Donnell; Mark L Metersky; Harlan M Krumholz
Journal:  J Hosp Med       Date:  2011-01-05       Impact factor: 2.960

8.  Estimating Ten-Year Trends in Septic Shock Incidence and Mortality in United States Academic Medical Centers Using Clinical Data.

Authors:  Sameer S Kadri; Chanu Rhee; Jeffrey R Strich; Megan K Morales; Samuel Hohmann; Jonathan Menchaca; Anthony F Suffredini; Robert L Danner; Michael Klompas
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9.  Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.

Authors:  Robert L McNamara; Yongfei Wang; Chohreh Partovian; Julia Montague; Purav Mody; Elizabeth Eddy; Harlan M Krumholz; Susannah M Bernheim
Journal:  Med Care       Date:  2015-09       Impact factor: 2.983

10.  An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction.

Authors:  Harlan M Krumholz; Yun Wang; Jennifer A Mattera; Yongfei Wang; Lein Fang Han; Melvin J Ingber; Sheila Roman; Sharon-Lise T Normand
Journal:  Circulation       Date:  2006-03-20       Impact factor: 29.690

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1.  Variation in Identifying Sepsis and Organ Dysfunction Using Administrative Versus Electronic Clinical Data and Impact on Hospital Outcome Comparisons.

Authors:  Chanu Rhee; Maximilian S Jentzsch; Sameer S Kadri; Christopher W Seymour; Derek C Angus; David J Murphy; Greg S Martin; Raymund B Dantes; Lauren Epstein; Anthony E Fiore; John A Jernigan; Robert L Danner; David K Warren; Edward J Septimus; Jason Hickok; Russell E Poland; Robert Jin; David Fram; Richard Schaaf; Rui Wang; Michael Klompas
Journal:  Crit Care Med       Date:  2019-04       Impact factor: 7.598

2.  Exploring the Pathways Revealed by International Sepsis Benchmarking.

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Journal:  Crit Care Med       Date:  2019-01       Impact factor: 7.598

3.  Patient Outcomes and Cost-Effectiveness of a Sepsis Care Quality Improvement Program in a Health System.

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Journal:  Crit Care Med       Date:  2019-10       Impact factor: 7.598

4.  Impact of Risk Adjustment Using Clinical vs Administrative Data on Hospital Sepsis Mortality Comparisons.

Authors:  Chanu Rhee; Zhonghe Li; Rui Wang; Yue Song; Sameer S Kadri; Edward J Septimus; Huai-Chun Chen; David Fram; Robert Jin; Russell Poland; Kenneth Sands; Michael Klompas
Journal:  Open Forum Infect Dis       Date:  2020-06-25       Impact factor: 3.835

5.  Risk Adjustment for Sepsis Mortality to Facilitate Hospital Comparisons Using Centers for Disease Control and Prevention's Adult Sepsis Event Criteria and Routine Electronic Clinical Data.

Authors:  Chanu Rhee; Rui Wang; Yue Song; Zilu Zhang; Sameer S Kadri; Edward J Septimus; David Fram; Robert Jin; Russell E Poland; Jason Hickok; Kenneth Sands; Michael Klompas
Journal:  Crit Care Explor       Date:  2019-10-14

6.  Risk-standardized sepsis mortality map of the United States.

Authors:  Jiun-Ruey Hu; Chia-Hung Yo; Hsin-Ying Lee; Chin-Hua Su; Ming-Yang Su; Amy Huaishiuan Huang; Ye Liu; Wan-Ting Hsu; Matthew Lee; Yee-Chun Chen; Chien-Chang Lee
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7.  Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review.

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Review 8.  Surveillance Strategies for Tracking Sepsis Incidence and Outcomes.

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Journal:  J Infect Dis       Date:  2020-07-21       Impact factor: 7.759

Review 9.  U.S. hospital performance methodologies: a scoping review to identify opportunities for crossing the quality chasm.

Authors:  Kelly J Thomas Craig; Mollie M McKillop; Hu T Huang; Judy George; Ekta S Punwani; Kyu B Rhee
Journal:  BMC Health Serv Res       Date:  2020-07-10       Impact factor: 2.655

  9 in total

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