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Validation of discharge diagnosis codes to identify serious infections among middle age and older adults
OBJECTIVES: Hospitalisations for serious infections are common among middle age and older adults and frequently used as study outcomes. Yet, few studies have evaluated the performance of diagnosis codes to identify serious infections in this population. We sought to determine the positive predictive...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6009457/ https://www.ncbi.nlm.nih.gov/pubmed/29921683 http://dx.doi.org/10.1136/bmjopen-2017-020857 |
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author | Wiese, Andrew D Griffin, Marie R Stein, C Michael Schaffner, William Greevy, Robert A Mitchel Jr, Edward F Grijalva, Carlos G |
author_facet | Wiese, Andrew D Griffin, Marie R Stein, C Michael Schaffner, William Greevy, Robert A Mitchel Jr, Edward F Grijalva, Carlos G |
author_sort | Wiese, Andrew D |
collection | PubMed |
description | OBJECTIVES: Hospitalisations for serious infections are common among middle age and older adults and frequently used as study outcomes. Yet, few studies have evaluated the performance of diagnosis codes to identify serious infections in this population. We sought to determine the positive predictive value (PPV) of diagnosis codes for identifying hospitalisations due to serious infections among middle age and older adults. SETTING AND PARTICIPANTS: We identified hospitalisations for possible infection among adults >=50 years enrolled in the Tennessee Medicaid healthcare programme (2008–2012) using International Classifications of Diseases, Ninth Revision diagnosis codes for pneumonia, meningitis/encephalitis, bacteraemia/sepsis, cellulitis/soft-tissue infections, endocarditis, pyelonephritis and septic arthritis/osteomyelitis. DESIGN: Medical records were systematically obtained from hospitals randomly selected from a stratified sampling framework based on geographical region and hospital discharge volume. MEASURES: Two trained clinical reviewers used a standardised extraction form to abstract information from medical records. Predefined algorithms served as reference to adjudicate confirmed infection-specific hospitalisations. We calculated the PPV of diagnosis codes using confirmed hospitalisations as reference. Sensitivity analyses determined the robustness of the PPV to definitions that required radiological or microbiological confirmation. We also determined inter-rater reliability between reviewers. RESULTS: The PPV of diagnosis codes for hospitalisations for infection (n=716) was 90.2% (95% CI 87.8% to 92.2%). The PPV was highest for pneumonia (96.5% (95% CI 93.9% to 98.0%)) and cellulitis (91.1% (95% CI 84.7% to 94.9%)), and lowest for meningitis/encephalitis (50.0% (95% CI 23.7% to 76.3%)). The adjudication reliability was excellent (92.7% agreement; first agreement coefficient: 0.91). The overall PPV was lower when requiring microbiological confirmation (45%) and when requiring radiological confirmation for pneumonia (79%). CONCLUSIONS: Discharge diagnosis codes have a high PPV for identifying hospitalisations for common, serious infections among middle age and older adults. PPV estimates for rare infections were imprecise. |
format | Online Article Text |
id | pubmed-6009457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-60094572018-06-25 Validation of discharge diagnosis codes to identify serious infections among middle age and older adults Wiese, Andrew D Griffin, Marie R Stein, C Michael Schaffner, William Greevy, Robert A Mitchel Jr, Edward F Grijalva, Carlos G BMJ Open Research Methods OBJECTIVES: Hospitalisations for serious infections are common among middle age and older adults and frequently used as study outcomes. Yet, few studies have evaluated the performance of diagnosis codes to identify serious infections in this population. We sought to determine the positive predictive value (PPV) of diagnosis codes for identifying hospitalisations due to serious infections among middle age and older adults. SETTING AND PARTICIPANTS: We identified hospitalisations for possible infection among adults >=50 years enrolled in the Tennessee Medicaid healthcare programme (2008–2012) using International Classifications of Diseases, Ninth Revision diagnosis codes for pneumonia, meningitis/encephalitis, bacteraemia/sepsis, cellulitis/soft-tissue infections, endocarditis, pyelonephritis and septic arthritis/osteomyelitis. DESIGN: Medical records were systematically obtained from hospitals randomly selected from a stratified sampling framework based on geographical region and hospital discharge volume. MEASURES: Two trained clinical reviewers used a standardised extraction form to abstract information from medical records. Predefined algorithms served as reference to adjudicate confirmed infection-specific hospitalisations. We calculated the PPV of diagnosis codes using confirmed hospitalisations as reference. Sensitivity analyses determined the robustness of the PPV to definitions that required radiological or microbiological confirmation. We also determined inter-rater reliability between reviewers. RESULTS: The PPV of diagnosis codes for hospitalisations for infection (n=716) was 90.2% (95% CI 87.8% to 92.2%). The PPV was highest for pneumonia (96.5% (95% CI 93.9% to 98.0%)) and cellulitis (91.1% (95% CI 84.7% to 94.9%)), and lowest for meningitis/encephalitis (50.0% (95% CI 23.7% to 76.3%)). The adjudication reliability was excellent (92.7% agreement; first agreement coefficient: 0.91). The overall PPV was lower when requiring microbiological confirmation (45%) and when requiring radiological confirmation for pneumonia (79%). CONCLUSIONS: Discharge diagnosis codes have a high PPV for identifying hospitalisations for common, serious infections among middle age and older adults. PPV estimates for rare infections were imprecise. BMJ Publishing Group 2018-06-19 /pmc/articles/PMC6009457/ /pubmed/29921683 http://dx.doi.org/10.1136/bmjopen-2017-020857 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Research Methods Wiese, Andrew D Griffin, Marie R Stein, C Michael Schaffner, William Greevy, Robert A Mitchel Jr, Edward F Grijalva, Carlos G Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title | Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title_full | Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title_fullStr | Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title_full_unstemmed | Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title_short | Validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
title_sort | validation of discharge diagnosis codes to identify serious infections among middle age and older adults |
topic | Research Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6009457/ https://www.ncbi.nlm.nih.gov/pubmed/29921683 http://dx.doi.org/10.1136/bmjopen-2017-020857 |
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