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Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
- Source :
- BMJ Open
- Publication Year :
- 2018
- Publisher :
- BMJ, 2018.
-
Abstract
- Objectives To assess the accuracy of International Classification of Diseases 9th Revision–Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer. Design A cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical chart (reference standard). Case ascertainment was based on the presence of a primary nodular lesion in the lung and cytological or histological documentation of cancer from a primary or metastatic site. Setting Three operative units: administrative databases from Umbria Region (890 000 residents), ASL Napoli 3 Sud (NA) (1 170 000 residents) and Friuli Venezia Giulia (FVG) Region (1 227 000 residents). Participants Incident subjects with lung cancer (n=386) diagnosed in primary position between 2012 and 2014 and a population of non-cases (n=280). Outcome measures Sensitivity, specificity and positive predictive value (PPV) for 162.x code. Results 130 cases and 94 non-cases were randomly selected from each database and the corresponding medical charts were reviewed. Most of the diagnoses for lung cancer were performed in medical departments. True positive rates were high for all the three units. Sensitivity was 99% (95% CI 95% to 100%) for Umbria, 97% (95% CI 91% to 100%) for NA, and 99% (95% CI 95% to 100%) for FVG. The false positive rates were 24%, 37% and 23% for Umbria, NA and FVG, respectively. PPVs were 79% (73% to 83%)%) for Umbria, 58% (53% to 63%)%) for NA and 79% (73% to 84%)%) for FVG. Conclusions Case ascertainment for lung cancer based on imaging or endoscopy associated with histological examination yielded an excellent sensitivity in all the three administrative databases. PPV was moderate for Umbria and FVG but lower for NA.
- Subjects :
- Adult
Male
validity
Lung Neoplasms
Databases, Factual
Population
Diagnostic accuracy
computer.software_genre
Sensitivity and Specificity
03 medical and health sciences
0302 clinical medicine
International Classification of Diseases
Research Methods
Humans
Medicine
030212 general & internal medicine
education
Lung cancer
Aged
education.field_of_study
Icd-9-cm
Database
business.industry
Research
Medical record
Clinical Coding
Outcome measures
Cancer
General Medicine
Middle Aged
medicine.disease
Predictive value
Friuli venezia giulia
lung cancer
Cross-Sectional Studies
administrative database
Italy
030220 oncology & carcinogenesis
positive predictive value
Female
business
computer
Subjects
Details
- ISSN :
- 20446055
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- BMJ Open
- Accession number :
- edsair.doi.dedup.....7ff95f9884d856313fd7f2b18f7a58ee