Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
Background: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. Objective: Our ob...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-01-01
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| Series: | Clinical Parkinsonism & Related Disorders |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590112520300293 |
| _version_ | 1818589875966836736 |
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| author | Brett J. Peterson Walter A. Rocca James H. Bower Rodolfo Savica Michelle M. Mielke |
| author_facet | Brett J. Peterson Walter A. Rocca James H. Bower Rodolfo Savica Michelle M. Mielke |
| author_sort | Brett J. Peterson |
| collection | DOAJ |
| description | Background: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. Objective: Our objective was to assess the validity of using diagnostic codes to identify incident Parkinson's disease (PD) cases in Olmsted County, Minnesota using an established standard for comparison (1976–2005). Methods: Cases were identified solely using computer programs applied to administrative diagnostic code indexes from the Rochester Epidemiology Project (REP). Two codes >30 days apart or one code on the death certificate constituted PD. The standard was a clinical diagnosis by movement disorders specialists based on medical record review. Validity was assessed using positive predictive value (PPV) and sensitivity. Numbers of incident cases and incidence rates were compared between the two ascertainment methods by sex. Results: The codes only method over-counted the number of incident PD cases by 73% (804 versus 464), and this over-counting generally increased with calendar year. Sensitivity was 80% (95% CI [76%, 84%]) and PPV was 46% (95% CI [34%, 50%]). Disease status misclassification accounted for two-thirds of falsely identified cases, where individuals were found to not have PD (43%) or even parkinsonism (23%) after medical record review. The codes only method also over-estimated the incidence rate time trend for men and women by approximately two-fold. Conclusion: In our context, using administrative diagnostic codes only to identify incident PD cases is not recommended unless more accurate algorithms are developed. |
| first_indexed | 2024-12-16T09:47:36Z |
| format | Article |
| id | doaj.art-91d2e76bce084b76a92780033f0b51c8 |
| institution | Directory Open Access Journal |
| issn | 2590-1125 |
| language | English |
| last_indexed | 2024-12-16T09:47:36Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Clinical Parkinsonism & Related Disorders |
| spelling | doaj.art-91d2e76bce084b76a92780033f0b51c82022-12-21T22:36:07ZengElsevierClinical Parkinsonism & Related Disorders2590-11252020-01-013100061Identifying incident Parkinson's disease using administrative diagnostic codes: a validation studyBrett J. Peterson0Walter A. Rocca1James H. Bower2Rodolfo Savica3Michelle M. Mielke4Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USADivision of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USADepartment of Neurology, Mayo Clinic, Rochester, MN, USADivision of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USADivision of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA; Corresponding author at: Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.Background: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. Objective: Our objective was to assess the validity of using diagnostic codes to identify incident Parkinson's disease (PD) cases in Olmsted County, Minnesota using an established standard for comparison (1976–2005). Methods: Cases were identified solely using computer programs applied to administrative diagnostic code indexes from the Rochester Epidemiology Project (REP). Two codes >30 days apart or one code on the death certificate constituted PD. The standard was a clinical diagnosis by movement disorders specialists based on medical record review. Validity was assessed using positive predictive value (PPV) and sensitivity. Numbers of incident cases and incidence rates were compared between the two ascertainment methods by sex. Results: The codes only method over-counted the number of incident PD cases by 73% (804 versus 464), and this over-counting generally increased with calendar year. Sensitivity was 80% (95% CI [76%, 84%]) and PPV was 46% (95% CI [34%, 50%]). Disease status misclassification accounted for two-thirds of falsely identified cases, where individuals were found to not have PD (43%) or even parkinsonism (23%) after medical record review. The codes only method also over-estimated the incidence rate time trend for men and women by approximately two-fold. Conclusion: In our context, using administrative diagnostic codes only to identify incident PD cases is not recommended unless more accurate algorithms are developed.http://www.sciencedirect.com/science/article/pii/S2590112520300293Parkinson's diseaseHealth administrative dataDiagnostic codeValidationIncidence |
| spellingShingle | Brett J. Peterson Walter A. Rocca James H. Bower Rodolfo Savica Michelle M. Mielke Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study Clinical Parkinsonism & Related Disorders Parkinson's disease Health administrative data Diagnostic code Validation Incidence |
| title | Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study |
| title_full | Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study |
| title_fullStr | Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study |
| title_full_unstemmed | Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study |
| title_short | Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study |
| title_sort | identifying incident parkinson s disease using administrative diagnostic codes a validation study |
| topic | Parkinson's disease Health administrative data Diagnostic code Validation Incidence |
| url | http://www.sciencedirect.com/science/article/pii/S2590112520300293 |
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