Evidence map›Paper›PMID 37006594›Full record

ArticleJournal of asthma and allergy2023

Validation of Diagnostic Coding for Asthma in an Electronic Health Record System in Hong Kong.

Wang Chun Kwok, Terence Chi Chun Tam, Chor Wing Sing, Esther Wai Yin Chan, Ching-Lung Cheung

Open access · goldAbstract read
In one paragraph

Article in Journal of asthma and allergy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 21 citations in OpenAlex.

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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

5 authors at 2 institutions in 2 countries.

Wang Chun KwokDepartment of Medicine, Queen Mary Hospital, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, People's Republic of China.ORCID 0000-0002-5611-1637
Terence Chi Chun TamDepartment of Medicine, Queen Mary Hospital, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, People's Republic of China.ORCID 0000-0002-6057-8168
Chor Wing SingDepartment of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, People's Republic of China.ORCID 0000-0002-6233-9144
Esther Wai Yin ChanDepartment of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, People's Republic of China.ORCID 0000-0002-7602-9470
Ching-Lung CheungDepartment of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, People's Republic of China.ORCID 0000-0002-2180-3676
University of Hong Kong · HKQueen Mary Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electronic health record (EHR) databases can facilitate epidemiology research into various diseases including asthma. Given the diagnostic challenges of asthma, the validity of the coding in EHR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying asthma in the territory-wide electronic medical health record system of the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. Methods: Adult patients who had the diagnosis of asthma input from all public hospitals in Hong Kong and those from Queen Mary Hospital in 2011-2020 were identified using the ICD-9 code of 493 (493.0, 493.1, 493.2, and 493.9) by CDARS. Patients' clinical record and spirometry were reviewed by two respiratory specialists to confirm the presence of asthma in the randomly selected cases. Results: There were 43,454 patients who had the diagnostic code of asthma among all public hospitals in Hong Kong and 1852 in Queen Mary Hospital in the same period. A total of 200 cases were randomly selected and validated using medical record and spirometry review by a respiratory specialist. The overall positive predictive value (PPV) was 85.0% (95% CI 80.1-89.9%). Conclusion: This was the first ICD-9 code validation for CDARS (EHR) in Hong Kong on asthma. Our study demonstrated that using ICD-9 code (493.0, 493.1, 493.2 and 493.9) to identify asthma can result in a PPV that was reliable to support the utility of the CDARS database for further research on asthma among the Hong Kong population.

Indexed as

algorithmsasthmaEHRelectronic health recordvalidation

Identifiers

PMID37006594
PMCPMC10065416
OpenAlexW4360984931

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.