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Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia

IMPORTANCE: Administrative databases may offer efficient clinical data collection for studying epidemiology, outcomes, and temporal trends in health care delivery. However, such data have seldom been validated against microbiological laboratory results. OBJECTIVE: To assess the validity of Internati...

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Autores principales: Higgins, Thomas L., Deshpande, Abhishek, Zilberberg, Marya D., Lindenauer, Peter K., Imrey, Peter B., Yu, Pei-Chun, Haessler, Sarah D., Richter, Sandra S., Rothberg, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376393/
https://www.ncbi.nlm.nih.gov/pubmed/32697323
http://dx.doi.org/10.1001/jamanetworkopen.2020.7750
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author Higgins, Thomas L.
Deshpande, Abhishek
Zilberberg, Marya D.
Lindenauer, Peter K.
Imrey, Peter B.
Yu, Pei-Chun
Haessler, Sarah D.
Richter, Sandra S.
Rothberg, Michael B.
author_facet Higgins, Thomas L.
Deshpande, Abhishek
Zilberberg, Marya D.
Lindenauer, Peter K.
Imrey, Peter B.
Yu, Pei-Chun
Haessler, Sarah D.
Richter, Sandra S.
Rothberg, Michael B.
author_sort Higgins, Thomas L.
collection PubMed
description IMPORTANCE: Administrative databases may offer efficient clinical data collection for studying epidemiology, outcomes, and temporal trends in health care delivery. However, such data have seldom been validated against microbiological laboratory results. OBJECTIVE: To assess the validity of International Classification of Diseases, Ninth Revision (ICD-9) organism-specific administrative codes for pneumonia using microbiological data (test results for blood or respiratory culture, urinary antigen, or polymerase chain reaction) as the criterion standard. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional diagnostic accuracy study conducted between February 2017 and June 2019 using data from 178 US hospitals in the Premier Healthcare Database. Patients were aged 18 years or older admitted with pneumonia and discharged between July 1, 2010, and June 30, 2015. Data were analyzed from February 14, 2017, to June 27, 2019. EXPOSURES: Organism-specific pneumonia identified from ICD-9 codes. MAIN OUTCOMES AND MEASURES: Sensitivity, specificity, positive predictive value, and negative predictive value of ICD-9 codes using microbiological data as the criterion standard. RESULTS: Of 161 529 patients meeting inclusion criteria (mean [SD] age, 69.5 [16.2] years; 51.2% women), 35 759 (22.1%) had an identified pathogen. ICD-9–coded organisms and laboratory findings differed notably: for example, ICD-9 codes identified only 14.2% and 17.3% of patients with laboratory-detected methicillin-sensitive Staphylococcus aureus and Escherichia coli, respectively. Although specificities and negative predictive values exceeded 95% for all codes, sensitivities ranged downward from 95.9% (95% CI, 95.3%-96.5%) for influenza virus to 14.0% (95% CI, 8.8%-20.8%) for parainfluenza virus, and positive predictive values ranged downward from 91.1% (95% CI, 89.5%-92.6%) for Staphylococcus aureus to 57.1% (95% CI, 39.4%-73.7%) for parainfluenza virus. CONCLUSIONS AND RELEVANCE: In this study, ICD-9 codes did not reliably capture pneumonia etiology identified by laboratory testing; because of the high specificities of ICD-9 codes, however, administrative data may be useful in identifying risk factors for resistant organisms. The low sensitivities of the diagnosis codes may limit the validity of organism-specific pneumonia prevalence estimates derived from administrative data.
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spelling pubmed-73763932020-08-10 Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia Higgins, Thomas L. Deshpande, Abhishek Zilberberg, Marya D. Lindenauer, Peter K. Imrey, Peter B. Yu, Pei-Chun Haessler, Sarah D. Richter, Sandra S. Rothberg, Michael B. JAMA Netw Open Original Investigation IMPORTANCE: Administrative databases may offer efficient clinical data collection for studying epidemiology, outcomes, and temporal trends in health care delivery. However, such data have seldom been validated against microbiological laboratory results. OBJECTIVE: To assess the validity of International Classification of Diseases, Ninth Revision (ICD-9) organism-specific administrative codes for pneumonia using microbiological data (test results for blood or respiratory culture, urinary antigen, or polymerase chain reaction) as the criterion standard. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional diagnostic accuracy study conducted between February 2017 and June 2019 using data from 178 US hospitals in the Premier Healthcare Database. Patients were aged 18 years or older admitted with pneumonia and discharged between July 1, 2010, and June 30, 2015. Data were analyzed from February 14, 2017, to June 27, 2019. EXPOSURES: Organism-specific pneumonia identified from ICD-9 codes. MAIN OUTCOMES AND MEASURES: Sensitivity, specificity, positive predictive value, and negative predictive value of ICD-9 codes using microbiological data as the criterion standard. RESULTS: Of 161 529 patients meeting inclusion criteria (mean [SD] age, 69.5 [16.2] years; 51.2% women), 35 759 (22.1%) had an identified pathogen. ICD-9–coded organisms and laboratory findings differed notably: for example, ICD-9 codes identified only 14.2% and 17.3% of patients with laboratory-detected methicillin-sensitive Staphylococcus aureus and Escherichia coli, respectively. Although specificities and negative predictive values exceeded 95% for all codes, sensitivities ranged downward from 95.9% (95% CI, 95.3%-96.5%) for influenza virus to 14.0% (95% CI, 8.8%-20.8%) for parainfluenza virus, and positive predictive values ranged downward from 91.1% (95% CI, 89.5%-92.6%) for Staphylococcus aureus to 57.1% (95% CI, 39.4%-73.7%) for parainfluenza virus. CONCLUSIONS AND RELEVANCE: In this study, ICD-9 codes did not reliably capture pneumonia etiology identified by laboratory testing; because of the high specificities of ICD-9 codes, however, administrative data may be useful in identifying risk factors for resistant organisms. The low sensitivities of the diagnosis codes may limit the validity of organism-specific pneumonia prevalence estimates derived from administrative data. American Medical Association 2020-07-22 /pmc/articles/PMC7376393/ /pubmed/32697323 http://dx.doi.org/10.1001/jamanetworkopen.2020.7750 Text en Copyright 2020 Higgins TL et al. JAMA Network Open. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the CC-BY License.
spellingShingle Original Investigation
Higgins, Thomas L.
Deshpande, Abhishek
Zilberberg, Marya D.
Lindenauer, Peter K.
Imrey, Peter B.
Yu, Pei-Chun
Haessler, Sarah D.
Richter, Sandra S.
Rothberg, Michael B.
Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title_full Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title_fullStr Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title_full_unstemmed Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title_short Assessment of the Accuracy of Using ICD-9 Diagnosis Codes to Identify Pneumonia Etiology in Patients Hospitalized With Pneumonia
title_sort assessment of the accuracy of using icd-9 diagnosis codes to identify pneumonia etiology in patients hospitalized with pneumonia
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376393/
https://www.ncbi.nlm.nih.gov/pubmed/32697323
http://dx.doi.org/10.1001/jamanetworkopen.2020.7750
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