Validation study of German inpatient administrative health data for epidemiological surveillance and measurement of quality of care for sepsis: the OPTIMISE study protocol

Daniel Schwarzkopf; Carolin Fleischmann-Struzek; Peter Schlattmann; Heike Dorow; Dominique Ouart; Andreas Edel; Falk A Gonnert; Jürgen Götz; Matthias Gründling; Markus Heim; Ulrich Jaschinski; Simone Lindau; Patrick Meybohm; Christian Putensen; Michael Sander; Konrad Reinhart; OPTIMISE study group

doi:10.1136/bmjopen-2019-035763

Validation study of German inpatient administrative health data for epidemiological surveillance and measurement of quality of care for sepsis: the OPTIMISE study protocol

BMJ Open. 2020 Oct 5;10(10):e035763. doi: 10.1136/bmjopen-2019-035763.

Authors

Daniel Schwarzkopf^{1

2}, Carolin Fleischmann-Struzek^{3

4}, Peter Schlattmann⁵, Heike Dorow², Dominique Ouart², Andreas Edel⁶, Falk A Gonnert⁷, Jürgen Götz⁸, Matthias Gründling⁹, Markus Heim¹⁰, Ulrich Jaschinski¹¹, Simone Lindau¹², Patrick Meybohm¹³, Christian Putensen¹⁴, Michael Sander¹⁵, Konrad Reinhart^{2

6}; OPTIMISE study group

Affiliations

¹ Center for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany Daniel.Schwarzkopf@med.uni-jena.de.
² Department of Anaesthesiology and Intensive Care Medicine, Jena University Hospital, Jena, Germany.
³ Center for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
⁴ Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany.
⁵ Institute for Medical Statistics, Computer Science and Data Science, Jena University Hospital, Jena, Germany.
⁶ Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
⁷ Department of Anaesthesiology and Intensive Care Medicine, SRH Wald-Klinikum Gera, Gera, Germany.
⁸ Department of Internal Medicine II - Intensive Care, Klinikum Lippe GmbH, Detmold, Germany.
⁹ Department of Anaesthesiology, Intensive Care Medicine, Emergency Medicine and Pain Medicine, University Medicine Greifswald, Greifswald, Germany.
¹⁰ Department of Anaesthesiology and Intensive Care, Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Munchen, Germany.
¹¹ Department of Anaesthesiology and Surgical Intensive Care Medicine, Universitätsklinikum Augsburg, Augsburg, Germany.
¹² Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt am Main, Germany.
¹³ Department of Anaesthesia and Critical Care, University Hospital Würzburg, Würzburg, Germany.
¹⁴ Department of Anaesthesiology and Intensive Care Medicine, University Hospital Bonn, Bonn, Germany.
¹⁵ Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Gießen, UKGM, Justus-Liebig University Gießen, Gießen, Germany.

Abstract

Introduction: Sepsis is a major cause of preventable deaths in hospitals. This study aims to investigate if sepsis incidence and quality of care can be assessed using inpatient administrative health data (IAHD).

Methods and analysis: Design: Retrospective observational validation study using routine data to assess the diagnostic accuracy of sepsis coding in IAHD regarding sepsis diagnosis based on medical record review.

Procedure: A stratified sample of 10 000 patients with an age ≥15 years treated in between 2015 and 2017 in 10 German hospitals is investigated. All available information of medical records is screened by trained physicians to identify true sepsis cases ('gold standard') both according to current ('sepsis-1') definitions and new ('sepsis-3') definitions. Data from medical records are linked to IAHD on patient level using a pseudonym.

Analyses: Proportions of cases with sepsis according to sepsis-1 and sepsis-3 definitions are calculated and compared with estimates from coding of sepsis in IAHD. Predictive accuracy (sensitivity, specificity) of different coding abstraction strategies regarding the gold standard is estimated. Predictive accuracy of mortality risk factors obtained from IAHD regarding the respective risk factors obtained from medical records is calculated. An IAHD-based risk model for hospital mortality is compared with a record-based risk model regarding model-fit and predicted risk of death. Analyses adjust for sampling weights. The obtained estimates of sensitivity and specificity for sepsis coding in IAHD are used to estimate adjusted incidence proportions of sepsis based on German national IAHD.

Ethics and dissemination: The study has been approved by the ethics commission of the Jena University Hospital (No. 2018-1065-Daten). The results of the study will be discussed in an expert panel to write a memorandum on improving the utility of IAHD for epidemiological surveillance and quality management of sepsis care.

Trial registration number: DRKS00017775; Pre-results.

Keywords: adult intensive & critical care; epidemiology; public health; quality in health care.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Hospital Mortality
Humans
Incidence
Inpatients*
Retrospective Studies
Sepsis* / diagnosis
Sepsis* / epidemiology
Sepsis* / therapy

Associated data

DRKS/DRKS00017775