Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA-J Am Med Assoc. 2016;315(8):801–10.

Article  CAS  Google Scholar 

Fleischmann-Struzek C, Thomas-Rüddel DO, Schettler A, Schwarzkopf D, Stacke A, Seymour CW, Haas C, Dennler U, Reinhart K. Comparing the validity of different ICD coding abstraction strategies for sepsis case identification in German claims data. PLoS ONE. 2018;13(7):e0198847.

Article  PubMed  PubMed Central  Google Scholar 

Schwarzkopf D, Rose N, Fleischmann-Struzek C, Boden B, Dorow H, Edel A, Friedrich M, Gonnert FA, Gotz J, Grundling M, et al. Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data. Infection. 2024;52(2):413–27.

Article  PubMed  Google Scholar 

Jolley RJ, Sawka KJ, Yergens DW, Quan H, Jette N, Doig CJ. Validity of administrative data in recording sepsis: a systematic review. Crit Care. 2015;19:12.

Article  Google Scholar 

Kumar A, Hammond N, Grattan S, Finfer S, Delaney A. Accuracy of international classification of disease coding methods to estimate sepsis epidemiology: a scoping review. J Intensive Care Med. 2024;39(1):3–11.

Article  PubMed  Google Scholar 

Rhee C, Murphy MV, Li L, Platt R, Klompas M, Centers for Disease C, Prevention Epicenters P. Comparison of trends in sepsis incidence and coding using administrative claims versus objective clinical data. Clin Infect Dis. 2015;60(1):88–95.

Article  CAS  PubMed  Google Scholar 

Gohil SK, Cao C, Phelan M, Tjoa T, Rhee C, Platt R, Huang SS. Impact of policies on the rise in sepsis incidence, 2000–2010. Clin Infect Dis. 2016;62(6):695–703.

Article  PubMed  PubMed Central  Google Scholar 

Rhee C, Dantes R, Epstein L, Murphy DJ, Seymour CW, Iwashyna TJ, Kadri SS, Angus DC, Danner RL, Fiore AE, et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009–2014. JAMA. 2017;318(13):1241–9.

Article  PubMed  PubMed Central  Google Scholar 

Whittaker SA, Mikkelsen ME, Gaieski DF, Koshy S, Kean C, Fuchs BD. Severe sepsis cohorts derived from claims-based strategies appear to be biased toward a more severely ill patient population. Crit Care Med. 2013;41(4):945–53.

Article  PubMed  Google Scholar 

Qualitätssicherungsverfahren „Diagnostik. Therapie und Nachsorge der Sepsis - Machbarkeitsprüfung - Indikatorenset V2.1 [https://iqtig.org/veroeffentlichungen/abschlussbericht-sepsis/]

Schwarzkopf D, Fleischmann-Struzek C, Schlattmann P, Dorow H, Ouart D, Edel A, Gonnert FA, Gotz J, Grundling M, Heim M, et al. 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;10(10):e035763.

Article  PubMed  PubMed Central  Google Scholar 

Benchimol EI, Smeeth L, Guttmann A, Harron K, Moher D, Petersen I, Sørensen HT, von Elm E, Langan SM, Committee RW. The reporting of studies conducted using observational routinely-collected health data (RECORD) statement. PLoS Med. 2015;12(10):e1001885.

Article  PubMed  PubMed Central  Google Scholar 

Benchimol EI, Manuel DG, To T, Griffiths AM, Rabeneck L, Guttmann A. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol. 2011;64(8):821–9.

Article  PubMed  Google Scholar 

Iwashyna TJ, Odden A, Rohde J, Bonham C, Kuhn L, Malani P, Chen L, Flanders S. Identifying patients with severe sepsis using administrative claims: patient-level validation of the angus implementation of the international consensus conference definition of severe sepsis. Med Care. 2014;52(6):e39-43.

Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, Schein RMH, Sibbald WJ, Abrams JH, Bernard GR et al. American-College of Chest Physicians Society of Critical Care Medicine Consensus Conference - definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Crit Care Med. 1992;20(6):864–874.

Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, Cohen J, Opal SM, Vincent JL, Ramsay G et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med. 2003;31(4):1250–1256.

Shankar-Hari M, Harrison DA, Rubenfeld GD, Rowan K. Epidemiology of sepsis and septic shock in critical care units: comparison between sepsis-2 and sepsis-3 populations using a national critical care database. Br J Anaesth. 2017;119(4):626–36.

Article  CAS  PubMed  Google Scholar 

R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2021.

Google Scholar 

Lumley T. survey: analysis of complex survey samples (version 4.4-2) [Computer software]. Available from: https://cran.r-project.org/web/packages/survey/index.html: The Comprehensive R Archive Network; 2024.

rpart. Recursive partitioning and regression trees [https://cran.r-project.org/web/packages/rpart/index.html]

Beaumont J-F. On the use of data collection process information for the treatment of unit nonresponse through weight adjustment. Surv Methodol. 2004;31(2):227–331.

Google Scholar 

Barbash IJ, Davis BS, Saul M, Hwa R, Brant EB, Seymour CW, Kahn JM. Association between medicare’s sepsis reporting policy (SEP-1) and the documentation of a sepsis diagnosis in the clinical record. Med Care. 2024;62(6):388–95.

Article  PubMed  PubMed Central  Google Scholar 

Mellhammar L, Wollter E, Dahlberg J, Donovan B, Olséen CJ, Wiking PO, Rose N, Schwarzkopf D, Friedrich M, Fleischmann-Struzek C, et al. Estimating sepsis incidence using administrative data and clinical medical record review. JAMA Netw Open. 2023;6(8):e2331168.

Article  PubMed  PubMed Central  Google Scholar 

Jafarzadeh SR, Thomas BS, Marschall J, Fraser VJ, Gill J, Warren DK. Quantifying the improvement in sepsis diagnosis, documentation, and coding: the marginal causal effect of year of hospitalization on sepsis diagnosis. Ann Epidemiol. 2016;26(1):66–70.

Article  PubMed  Google Scholar 

Jolley RJ, Quan H, Jetté N, Sawka KJ, Diep L, Goliath J, Roberts DJ, Yipp BG, Doig CJ. Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data. BMJ Open. 2015;5(12):e009487.

Article  PubMed  PubMed Central  Google Scholar 

Rhee C, Jentzsch MS, Kadri SS, Seymour CW, Angus DC, Murphy DJ, Martin GS, Dantes RB, Epstein L, Fiore AE, et al. Variation in identifying sepsis and organ dysfunction using administrative versus electronic clinical data and impact on hospital outcome comparisons. Crit Care Med. 2019;47(4):493–500.

Article  PubMed  PubMed Central  Google Scholar 

Lindenauer PK, Lagu T, Shieh MS, Pekow PS, Rothberg MB. Association of diagnostic coding with trends in hospitalizations and mortality of patients with pneumonia, 2003–2009. JAMA. 2012;307(13):1405–13.

Article  CAS  PubMed  Google Scholar 

Rothberg MB, Pekow PS, Priya A, Lindenauer PK. Variation in diagnostic coding of patients with pneumonia and its association with hospital risk-standardized mortality rates: a cross-sectional analysis. Ann Intern Med. 2014;160(6):380–8.

Article  PubMed  PubMed Central  Google Scholar 

SepNet Critical Care Trials G. Incidence of severe sepsis and septic shock in German intensive care units: the prospective, multicentre INSEP study. Intensive Care Med. 2016;42(12):1980–9.

Article  Google Scholar 

Bloos F, Ruddel H, Thomas-Ruddel D, Schwarzkopf D, Pausch C, Harbarth S, Schreiber T, Grundling M, Marshall J, Simon P, et al. Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: a cluster randomized trial. Intensive Care Med. 2017;43(11):1602–12.

Article  PubMed  Google Scholar 

Boussina A, Shashikumar SP, Malhotra A, Owens RL, El-Kareh R, Longhurst CA, Quintero K, Donahue A, Chan TC, Nemati S, et al. Impact of a deep learning sepsis prediction model on quality of care and survival. NPJ Digit Med. 2024;7(1):14.

Article  PubMed  PubMed Central  Google Scholar 

Sand J, Kuqi A. Current challenges in sepsis documentation and coding: a review of the literature. Perspect Health Inf Manag. 2023;20(3):1g. eCollection 2023 Summer-Fall.

PubMed Central  Google Scholar 

Kodierleitfaden, Sepsis. 3.0 [https://www.uniklinikum-jena.de/dqs/Publikationen/Sepsis_Kodierleitfaden.html]