Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project
Population-based studies of non-cancer chronic disease often rely on self-reported data for disease diagnosis, which may be incomplete, unreliable and suffer from bias. Recently, the British Columbia Generations Project (BCGP; n = 29,736) linked self-reported chronic disease history data to a Chroni...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Epidemiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fepid.2022.1054485/full |
| _version_ | 1798003947439390720 |
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| author | Maryam Darvishian Maryam Darvishian Jessica Chu Jonathan Simkin Jonathan Simkin Ryan Woods Ryan Woods Parveen Bhatti Parveen Bhatti |
| author_facet | Maryam Darvishian Maryam Darvishian Jessica Chu Jonathan Simkin Jonathan Simkin Ryan Woods Ryan Woods Parveen Bhatti Parveen Bhatti |
| author_sort | Maryam Darvishian |
| collection | DOAJ |
| description | Population-based studies of non-cancer chronic disease often rely on self-reported data for disease diagnosis, which may be incomplete, unreliable and suffer from bias. Recently, the British Columbia Generations Project (BCGP; n = 29,736) linked self-reported chronic disease history data to a Chronic Disease Registry (CDR) that applied algorithms to administrative health data to ascertain diagnoses of multiple chronic diseases in the Province of British Columbia. For the 10 diseases captured by both self-report and the CDR, including asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, multiple sclerosis, myocardial infarction, osteoarthritis, osteoporosis, rheumatoid arthritis, and stroke, we calculated Cohen's kappa coefficient to examine concordance of chronic disease status (i.e., ever/never diagnosed) between the data sources. Using CDR data as the gold standard, we also calculated sensitivity, specificity, and positive-predictive value (PPV) for self-reported chronic disease occurrence. The prevalence of each chronic disease was similar across both data sources. Substantial levels of concordance (0.66–0.73) and moderate to high sensitivities (0.64–0.92), specificities (0.98–0.99) and PPVs (0.55–0.84) were observed for diabetes, hypertension, multiple sclerosis, and myocardial infarction. We did observe degree of concordance to vary by age, sex, body mass index (BMI), health perception, and ethnicity across most of the chronic diseases that were evaluated. While administrative health data are imperfect, they are less likely to suffer from bias, making them a reasonable gold standard. Our results demonstrate that for at least some chronic diseases, self-report may be a reasonable method for case ascertainment. However, characteristics of the study population will likely have impacts on the quality of the data. |
| first_indexed | 2024-04-11T12:15:43Z |
| format | Article |
| id | doaj.art-0d62e3b7a5ba49d9968d725e0ba7bfcc |
| institution | Directory Open Access Journal |
| issn | 2674-1199 |
| language | English |
| last_indexed | 2024-04-11T12:15:43Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Epidemiology |
| spelling | doaj.art-0d62e3b7a5ba49d9968d725e0ba7bfcc2022-12-22T04:24:19ZengFrontiers Media S.A.Frontiers in Epidemiology2674-11992022-12-01210.3389/fepid.2022.10544851054485Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations projectMaryam Darvishian0Maryam Darvishian1Jessica Chu2Jonathan Simkin3Jonathan Simkin4Ryan Woods5Ryan Woods6Parveen Bhatti7Parveen Bhatti8Prevention, Screening, and Hereditary Cancer Program, BC Cancer, Vancouver, BC, CanadaCancer Control Research, BC Cancer Research Institute, Vancouver, BC, CanadaCancer Control Research, BC Cancer Research Institute, Vancouver, BC, CanadaCancer Control Research, BC Cancer Research Institute, Vancouver, BC, CanadaSchool of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, CanadaCancer Control Research, BC Cancer Research Institute, Vancouver, BC, CanadaFaculty of Health Sciences, Simon Fraser University, Burnaby, BC, CanadaCancer Control Research, BC Cancer Research Institute, Vancouver, BC, CanadaSchool of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, CanadaPopulation-based studies of non-cancer chronic disease often rely on self-reported data for disease diagnosis, which may be incomplete, unreliable and suffer from bias. Recently, the British Columbia Generations Project (BCGP; n = 29,736) linked self-reported chronic disease history data to a Chronic Disease Registry (CDR) that applied algorithms to administrative health data to ascertain diagnoses of multiple chronic diseases in the Province of British Columbia. For the 10 diseases captured by both self-report and the CDR, including asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, multiple sclerosis, myocardial infarction, osteoarthritis, osteoporosis, rheumatoid arthritis, and stroke, we calculated Cohen's kappa coefficient to examine concordance of chronic disease status (i.e., ever/never diagnosed) between the data sources. Using CDR data as the gold standard, we also calculated sensitivity, specificity, and positive-predictive value (PPV) for self-reported chronic disease occurrence. The prevalence of each chronic disease was similar across both data sources. Substantial levels of concordance (0.66–0.73) and moderate to high sensitivities (0.64–0.92), specificities (0.98–0.99) and PPVs (0.55–0.84) were observed for diabetes, hypertension, multiple sclerosis, and myocardial infarction. We did observe degree of concordance to vary by age, sex, body mass index (BMI), health perception, and ethnicity across most of the chronic diseases that were evaluated. While administrative health data are imperfect, they are less likely to suffer from bias, making them a reasonable gold standard. Our results demonstrate that for at least some chronic diseases, self-report may be a reasonable method for case ascertainment. However, characteristics of the study population will likely have impacts on the quality of the data.https://www.frontiersin.org/articles/10.3389/fepid.2022.1054485/fullcohortself-reportadministrative datachronic diseaseconcordance |
| spellingShingle | Maryam Darvishian Maryam Darvishian Jessica Chu Jonathan Simkin Jonathan Simkin Ryan Woods Ryan Woods Parveen Bhatti Parveen Bhatti Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project Frontiers in Epidemiology cohort self-report administrative data chronic disease concordance |
| title | Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project |
| title_full | Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project |
| title_fullStr | Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project |
| title_full_unstemmed | Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project |
| title_short | Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project |
| title_sort | agreement between self report and administrative health data on occurrence of non cancer chronic disease among participants of the bc generations project |
| topic | cohort self-report administrative data chronic disease concordance |
| url | https://www.frontiersin.org/articles/10.3389/fepid.2022.1054485/full |
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