Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study
Abstract Background Diagnosis codes in administrative health data are routinely used to monitor trends in disease prevalence and incidence. The International Classification of Diseases (ICD), which is used to record these diagnoses, have been updated multiple times to reflect advances in health and...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-04-01
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| Series: | BMC Public Health |
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| Online Access: | https://doi.org/10.1186/s12889-022-13118-8 |
| _version_ | 1819210056181219328 |
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| author | Ridwan A. Sanusi Lin Yan Amani F. Hamad Olawale F. Ayilara Viktoriya Vasylkiv Mohammad Jafari Jozani Shantanu Banerji Joseph Delaney Pingzhao Hu Elizabeth Wall-Wieler Lisa M. Lix |
| author_facet | Ridwan A. Sanusi Lin Yan Amani F. Hamad Olawale F. Ayilara Viktoriya Vasylkiv Mohammad Jafari Jozani Shantanu Banerji Joseph Delaney Pingzhao Hu Elizabeth Wall-Wieler Lisa M. Lix |
| author_sort | Ridwan A. Sanusi |
| collection | DOAJ |
| description | Abstract Background Diagnosis codes in administrative health data are routinely used to monitor trends in disease prevalence and incidence. The International Classification of Diseases (ICD), which is used to record these diagnoses, have been updated multiple times to reflect advances in health and medical research. Our objective was to examine the impact of transitions between ICD versions on the prevalence of chronic health conditions estimated from administrative health data. Methods Study data (i.e., physician billing claims, hospital records) were from the province of Manitoba, Canada, which has a universal healthcare system. ICDA-8 (with adaptations), ICD-9-CM (clinical modification), and ICD-10-CA (Canadian adaptation; hospital records only) codes are captured in the data. Annual study cohorts included all individuals 18 + years of age for 45 years from 1974 to 2018. Negative binomial regression was used to estimate annual age- and sex-adjusted prevalence and model parameters (i.e., slopes and intercepts) for 16 chronic health conditions. Statistical control charts were used to assess the impact of changes in ICD version on model parameter estimates. Hotelling’s T2 statistic was used to combine the parameter estimates and provide an out-of-control signal when its value was above a pre-specified control limit. Results The annual cohort sizes ranged from 360,341 to 824,816. Hypertension and skin cancer were among the most and least diagnosed health conditions, respectively; their prevalence per 1,000 population increased from 40.5 to 223.6 and from 0.3 to 2.1, respectively, within the study period. The average annual rate of change in prevalence ranged from -1.6% (95% confidence interval [CI]: -1.8, -1.4) for acute myocardial infarction to 14.6% (95% CI: 13.9, 15.2) for hypertension. The control chart indicated out-of-control observations when transitioning from ICDA-8 to ICD-9-CM for 75% of the investigated chronic health conditions but no out-of-control observations when transitioning from ICD-9-CM to ICD-10-CA. Conclusions The prevalence of most of the investigated chronic health conditions changed significantly in the transition from ICDA-8 to ICD-9-CM. These results point to the importance of considering changes in ICD coding as a factor that may influence the interpretation of trend estimates for chronic health conditions derived from administrative health data. |
| first_indexed | 2024-12-23T06:05:06Z |
| format | Article |
| id | doaj.art-770332e40185473db5f409a91ac19e56 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-12-23T06:05:06Z |
| publishDate | 2022-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-770332e40185473db5f409a91ac19e562022-12-21T17:57:35ZengBMCBMC Public Health1471-24582022-04-0122111110.1186/s12889-022-13118-8Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based studyRidwan A. Sanusi0Lin Yan1Amani F. Hamad2Olawale F. Ayilara3Viktoriya Vasylkiv4Mohammad Jafari Jozani5Shantanu Banerji6Joseph Delaney7Pingzhao Hu8Elizabeth Wall-Wieler9Lisa M. Lix10Department of Community Health Sciences, University of ManitobaDepartment of Community Health Sciences, University of ManitobaDepartment of Community Health Sciences, University of ManitobaDepartment of Community Health Sciences, University of ManitobaDepartment of Community Health Sciences, University of ManitobaDepartment of Statistics, University of ManitobaCancerCare Manitoba Research Institute, Rady Faculty of Health Sciences, University of ManitobaCollege of Pharmacy, University of ManitobaDepartment of Biochemistry and Medical Genetics, University of ManitobaDepartment of Community Health Sciences, University of ManitobaDepartment of Community Health Sciences, University of ManitobaAbstract Background Diagnosis codes in administrative health data are routinely used to monitor trends in disease prevalence and incidence. The International Classification of Diseases (ICD), which is used to record these diagnoses, have been updated multiple times to reflect advances in health and medical research. Our objective was to examine the impact of transitions between ICD versions on the prevalence of chronic health conditions estimated from administrative health data. Methods Study data (i.e., physician billing claims, hospital records) were from the province of Manitoba, Canada, which has a universal healthcare system. ICDA-8 (with adaptations), ICD-9-CM (clinical modification), and ICD-10-CA (Canadian adaptation; hospital records only) codes are captured in the data. Annual study cohorts included all individuals 18 + years of age for 45 years from 1974 to 2018. Negative binomial regression was used to estimate annual age- and sex-adjusted prevalence and model parameters (i.e., slopes and intercepts) for 16 chronic health conditions. Statistical control charts were used to assess the impact of changes in ICD version on model parameter estimates. Hotelling’s T2 statistic was used to combine the parameter estimates and provide an out-of-control signal when its value was above a pre-specified control limit. Results The annual cohort sizes ranged from 360,341 to 824,816. Hypertension and skin cancer were among the most and least diagnosed health conditions, respectively; their prevalence per 1,000 population increased from 40.5 to 223.6 and from 0.3 to 2.1, respectively, within the study period. The average annual rate of change in prevalence ranged from -1.6% (95% confidence interval [CI]: -1.8, -1.4) for acute myocardial infarction to 14.6% (95% CI: 13.9, 15.2) for hypertension. The control chart indicated out-of-control observations when transitioning from ICDA-8 to ICD-9-CM for 75% of the investigated chronic health conditions but no out-of-control observations when transitioning from ICD-9-CM to ICD-10-CA. Conclusions The prevalence of most of the investigated chronic health conditions changed significantly in the transition from ICDA-8 to ICD-9-CM. These results point to the importance of considering changes in ICD coding as a factor that may influence the interpretation of trend estimates for chronic health conditions derived from administrative health data.https://doi.org/10.1186/s12889-022-13118-8Diagnosis codesHotelling’s T2Multivariate control chartNegative binomialTrend analysis |
| spellingShingle | Ridwan A. Sanusi Lin Yan Amani F. Hamad Olawale F. Ayilara Viktoriya Vasylkiv Mohammad Jafari Jozani Shantanu Banerji Joseph Delaney Pingzhao Hu Elizabeth Wall-Wieler Lisa M. Lix Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study BMC Public Health Diagnosis codes Hotelling’s T2 Multivariate control chart Negative binomial Trend analysis |
| title | Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study |
| title_full | Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study |
| title_fullStr | Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study |
| title_full_unstemmed | Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study |
| title_short | Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study |
| title_sort | transitions between versions of the international classification of diseases and chronic disease prevalence estimates from administrative health data a population based study |
| topic | Diagnosis codes Hotelling’s T2 Multivariate control chart Negative binomial Trend analysis |
| url | https://doi.org/10.1186/s12889-022-13118-8 |
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