Dataset Information

Urologic Diseases in Korean Military Population: a 6-year Epidemiological Review of Medical Records.

ABSTRACT: We sought to describe the incidence rate of the urologic disease in the Korean military by reviewing diagnoses made in active duty soldiers from 2008 to 2013. A total of 72,248 first visits were generated in the Defense Medical Statistics Information System (DMSIS) with its gradually increasing trend over 6 years. A sharp increase of first visit was observed after implementation of the regular health check-up for all conscripted soldiers since 2013. Urolithiasis, prostatitis, epididymoorchitis, urethritis, and varicocele were prevalent. Prostatitis was the highest diagnosis made in the outpatient service, while varicocele was ranked the highest in the inpatient service. The incidence rates of urologic disease varied from 12.3 to 34.2 cases per 1,000 person-years. The urologic disease in conscripted men showed different distribution when we separated the population into conscripted and professional soldiers. Epididymoorchitis was the highest disease followed by urolithiasis, dysuresia, and balanoposthitis in 2013. This study underscores that the urologic disease has spent significant amount of health care resources in the Korean military. This calls for further study to find any significant difference and contributing factors of the urologic disease in the military and the civilian population.

SUBMITTER: Choi SY

PROVIDER: S-EPMC5143286 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Publications

Urologic Diseases in Korean Military Population: a 6-year Epidemiological Review of Medical Records.

Choi Se Young SY Yoon Chang Gyo CG

Journal of Korean medical science 20170101 1

We sought to describe the incidence rate of the urologic disease in the Korean military by reviewing diagnoses made in active duty soldiers from 2008 to 2013. A total of 72,248 first visits were generated in the Defense Medical Statistics Information System (DMSIS) with its gradually increasing trend over 6 years. A sharp increase of first visit was observed after implementation of the regular health check-up for all conscripted soldiers since 2013. Urolithiasis, prostatitis, epididymoorchitis, ...[more]

PMID: 27914143

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Project description:BACKGROUND:Administrative health records (AHRs) and electronic medical records (EMRs) are two key sources of population-based data for disease surveillance, but misclassification errors in the data can bias disease estimates. Methods that combine information from error-prone data sources can build on the strengths of AHRs and EMRs. We compared bias and error for four data-combining methods and applied them to estimate hypertension prevalence. METHODS:Our study included rule-based OR and AND methods that identify disease cases from either or both data sources, respectively, rule-based sensitivity-specificity adjusted (RSSA) method that corrects for inaccuracies using a deterministic rule, and probabilistic-based sensitivity-specificity adjusted (PSSA) method that corrects for error using a statistical model. Computer simulation was used to estimate relative bias (RB) and mean square error (MSE) under varying conditions of population disease prevalence, correlation amongst data sources, and amount of misclassification error. AHRs and EMRs for Manitoba, Canada were used to estimate hypertension prevalence using validated case definitions and multiple disease markers. RESULTS:The OR method had the lowest RB and MSE when population disease prevalence was 10%, and the RSSA method had the lowest RB and MSE when population prevalence increased to 20%. As the correlation between data sources increased, the OR method resulted in the lowest RB and MSE. Estimates of hypertension prevalence for AHRs and EMRs alone were 30.9% (95% CI: 30.6-31.2) and 24.9% (95% CI: 24.6-25.2), respectively. The estimates were 21.4% (95% CI: 21.1-21.7), for the AND method, 34.4% (95% CI: 34.1-34.8) for the OR method, 32.2% (95% CI: 31.8-32.6) for the RSSA method, and ranged from 34.3% (95% CI: 34.1-34.5) to 35.9% (95% CI, 35.7-36.1) for the PSSA method, depending on the statistical model. CONCLUSIONS:The OR and AND methods are influenced by correlation amongst the data sources, while the RSSA method is dependent on the accuracy of prior sensitivity and specificity estimates. The PSSA method performed well when population prevalence was high and average correlations amongst disease markers was low. This study will guide researchers to select a data-combining method that best suits their data characteristics.

Dataset Information

Urologic Diseases in Korean Military Population: a 6-year Epidemiological Review of Medical Records.

Publications

Urologic Diseases in Korean Military Population: a 6-year Epidemiological Review of Medical Records.

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