Evidence map›Paper›PMID 38556924›Full record

ArticlePharmacoepidemiology and drug safety2024

Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings.

Kirk Benack, Abner Nyandege, Edward Nonnenmacher, Saira Jan, Soko Setoguchi, Tobias Gerhard, Brian L Strom, Daniel B Horton

Open access · hybridAbstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.0field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Kirk BenackDepartment of Anesthesiology, Montefiore Medical Center, Bronx, New York, USA.
Abner NyandegeCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
Edward NonnenmacherCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
Saira JanHorizon Blue Cross Blue Shield of New Jersey, Newark, New Jersey, USA.
Soko SetoguchiCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
Tobias GerhardCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.ORCID 0000-0002-8598-5771
Brian L StromCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
Daniel B HortonCenter for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.ORCID 0000-0002-1831-1339
Rutgers, The State University of New Jersey · USEP Analytics (United States) · USHorizon Blue Cross Blue Shield of New Jersey · USInstitute for Health Economics and Policy · JP

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
Translational Research Support CoreP30ES005022 · NIEHS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI HOWARD M KIPEN · 1988 to 2026
$47.4M
New Jersey Alliance for Clinical Translational Science: NJ ACTSUL1TR003017 · NCATS · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI PANETTIERI, REYNOLD ALEXANDER · 2019 to 2023
$28.9M
Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
Drugs, Germs, and Joints: Antibiotics, Gut Microbiota, and Juvenile Idiopathic ArthritisK23AR070286 · NIAMS · RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL · PI HORTON, DANIEL BENJAMIN · 2016 to 2020
$909k
Deprescribing Bisphosphonates in Older Nursing Home Residents with DementiaK08AG071794 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NIZNIK, JOSHUA DAVID · 2021 to 2025
$724k
NCATS NIH HHS UL1 TR003017NIAMS NIH HHS K23 AR070286NIEHS NIH HHS P30 ES005022
6 · The paper itself

Abstract

purposeTo evaluate the validity of ICD-10-CM code-based algorithms as proxies for influenza in inpatient and outpatient settings in the USA.

methodsAdministrative claims data (2015-2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims-based algorithms defined influenza as presence of an ICD-10-CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test-positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti-influenza medication pharmacy claims were also calculated.

resultsThere were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims-based influenza definition had a sensitivity of 84.9% (95% CI 72.9%-92.1%), specificity of 96.3% (95% CI 93.1%-98.0%), and PPV of 83.3% (95% CI 71.3%-91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%-88.2%), specificity of 96.2% (95% CI 90.6%-98.5%), PPV of 85.2% (95% CI 67.5%-94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%-67.3%), specificity of 99.6% (95% CI 97.7%-99.9%), and PPV of 96.7% (95% CI 83.3%-99.4%). CPT/HCPCS codes and anti-influenza medication claims were present for few outpatient encounters (sensitivity 3%-10%).

conclusionsIn a large US healthcare system, inpatient ICD-10-CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test-positive influenza. Outpatient ICD-10-CM codes were moderately predictive of test-positive influenza.

Indexed as

Influenza, HumanOutpatientsAlgorithmsDatabases, FactualHumansInpatientsInternational Classification of DiseasesalgorithmdiagnosisICD‐10‐CMinfluenzavalidation

Identifiers

PMID38556924
PMCPMC11022168
OpenAlexW4393383731

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.