Dataset Information

Accuracy of diagnosis codes to identify febrile young infants using administrative data.

ABSTRACT:

Background

Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.

Objective

Determine the most accurate International Classification of Diseases, Ninth Revision (ICD-9) diagnosis coding strategies for identification of febrile infants.

Design

Retrospective cross-sectional study.

Setting

Eight emergency departments in the Pediatric Health Information System.

Patients

Infants aged <90 days evaluated between July 1, 2012 and June 30, 2013 were randomly selected for medical record review from 1 of 4 ICD-9 diagnosis code groups: (1) discharge diagnosis of fever, (2) admission diagnosis of fever without discharge diagnosis of fever, (3) discharge diagnosis of serious infection without diagnosis of fever, and (4) no diagnosis of fever or serious infection.

Exposure

The ICD-9 diagnosis code groups were compared in 4 case-identification algorithms to a reference standard of fever ≥100.4°F documented in the medical record.

Measurements

Algorithm predictive accuracy was measured using sensitivity, specificity, and negative and positive predictive values.

Results

Among 1790 medical records reviewed, 766 (42.8%) infants had fever. Discharge diagnosis of fever demonstrated high specificity (98.2%, 95% confidence interval [CI]: 97.8-98.6) but low sensitivity (53.2%, 95% CI: 50.0-56.4). A case-identification algorithm of admission or discharge diagnosis of fever exhibited higher sensitivity (71.1%, 95% CI: 68.2-74.0), similar specificity (97.7%, 95% CI: 97.3-98.1), and the highest positive predictive value (86.9%, 95% CI: 84.5-89.3).

Conclusions

A case-identification strategy that includes admission or discharge diagnosis of fever should be considered for febrile infant studies using administrative data, though underclassification of patients is a potential limitation.

SUBMITTER: Aronson PL

PROVIDER: S-EPMC4715646 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Publications

Accuracy of diagnosis codes to identify febrile young infants using administrative data.

Aronson Paul L PL Williams Derek J DJ Thurm Cary C Tieder Joel S JS Alpern Elizabeth R ER Nigrovic Lise E LE Schondelmeyer Amanda C AC Balamuth Fran F Myers Angela L AL McCulloh Russell J RJ Alessandrini Evaline A EA Shah Samir S SS Browning Whitney L WL Hayes Katie L KL Feldman Elana A EA Neuman Mark I MI

Journal of hospital medicine 20150806 12

<h4>Background</h4>Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.<h4>Objective</h4>Determine the most accurate International Classification of Diseases, Ninth Revision (ICD-9) diagnosis coding strategies for identification of febrile infants.<h4>Design</h4>Retrospective cross-sectional study.<h4>Setting</h4>Eight emergency departments in the Pediatric Health Information System.<h4>Patients</h4>Infants aged <90 d ...[more]

PMID: 26248691

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Project description:ImportanceCommunity-acquired pneumonia (CAP) remains one of the most common indications for pediatric hospitalization in the United States, and it is frequently the focus of research and quality studies. Use of administrative data is increasingly common for these purposes, although proper validation is required to ensure valid study conclusions.ObjectiveTo validate administrative billing data for hospitalizations owing to childhood CAP.Design and settingCase-control study of 4 tertiary care, freestanding children’s hospitals in the United States.ParticipantsA total of 998 medical records of a 25% random sample of 3646 children discharged in 2010 with at least 1 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code representing possible pneumonia were reviewed. Discharges (matched on date of admission) without a pneumonia-related discharge code were also examined to identify potential missed pneumonia cases. Two reference standards, based on provider diagnosis alone (provider confirmed) or in combination with consistent clinical and radiographic evidence of pneumonia (definite), were used to identify CAP.ExposureTwelve ICD-9-CM–based coding strategies, each using a combination of primary or secondary codes representing pneumonia or pneumonia-related complications. Six algorithms excluded children with complex chronic conditions.Main outcomes and measuresSensitivity, specificity, and negative and positive predictive values (NPV and PPV, respectively) of the 12 identification strategies.ResultsFor provider-confirmed CAP (n = 680), sensitivity ranged from 60.7% to 99.7%; specificity, 75.7% to 96.4%; PPV, 67.9% to 89.6%; and NPV, 82.6% to 99.8%. For definite CAP (n = 547), sensitivity ranged from 65.6% to 99.6%; specificity, 68.7% to 93.0%; PPV, 54.6% to 77.9%; and NPV, 87.8% to 99.8%. Unrestricted use of the pneumonia-related codes was inaccurate, although several strategies improved specificity to more than 90% with a variable effect on sensitivity. Excluding children with complex chronic conditions demonstrated the most favorable performance characteristics. Performance of the algorithms was similar across institutions.Conclusions and relevanceAdministrative data are valuable for studying pediatric CAP hospitalizations. The strategies presented here will aid in the accurate identification of relevant and comparable patient populations for research and performance improvement studies.

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Dataset Information

Accuracy of diagnosis codes to identify febrile young infants using administrative data.

Background

Objective

Design

Setting

Patients

Exposure

Measurements

Results

Conclusions

Publications

Accuracy of diagnosis codes to identify febrile young infants using administrative data.

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