Taiwan’s National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan’s Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.

The aim of this study was to determine the validity of acute myocardial infarction (AMI) diagnosis coding in the National Health Insurance Research Database (NHIRD) by cross-comparisons of discharge diagnoses listed in the NHIRD with those in the medical records obtained from a medical center in Taiwan. This was a cross-sectional study comparing records in the NHIRD and discharge notes in one medical center (DNMC) in the year 2008. Positive predictive values (PPVs) for AMI diagnoses were evaluated by reviewing the relevant clinical and laboratory data recorded in the discharge notes of the medical center. Agreement in comorbidities, cardiac procedures, and antiplatelet agent (aspirin or clopidogrel) prescriptions between the two databases was evaluated. We matched 341 cases of AMI hospitalizations from the two databases, and 338 cases underwent complete chart review. Of these 338 AMI cases, 297 were confirmed with clinical and lab data, which yielded a PPV of 0.88. The consistency rate for coronary intervention, stenting, and antiplatelet prescription at admission was high, yielding a PPV over 0.90. The percentage of consistency in comorbidity diagnoses was 95.9% (324/338) among matched AMI cases. The NHIRD appears to be a valid resource for population research in cardiovascular diseases.

Statins are the most commonly prescribed agents for hypercholesterolemia because of their efficacy and tolerability. As the number of patients in need of statin therapy continues to increase, information regarding the relative efficacy and safety of statins is required for decision-making. This study will use systematic review to compare the efficacy and safety profiles of different statins at different doses and determine the therapeutically equivalent doses of statins to achieve a specific level of low-density lipoprotein cholesterol (LDL-C) lowering effect. Publications of head-to-head randomized controlled trials (RCTs) of statins were retrieved from the Oregon state database (1966-2004), MEDLINE (2005-April of 2006), EMBASE (2005-April of 2006), and the Cochrane Controlled Trials Registry (up to the first quarter of 2006). The publications were evaluated with predetermined criteria by a reviewer before they were included in the review. The mean change in cholesterol level of each statin was calculated and weighted by number of subjects involved in each RCT. Where possible, meta-analysis was performed to generate pooled estimates of the cholesterol lowering effect of statins and the difference between statins. Seventy-five studies reporting RCTs of head-to-head comparisons on statins were included. Most studies had similar baseline characteristics, except the rosuvastatin related studies. A daily dose of atorvastatin 10 mg, fluvastatin 80 mg, lovastatin 40-80 mg, and simvastatin 20 mg could decrease LDL-C by 30-40%, and fluvastatin 40 mg, lovastatin 10-20 mg, pravastatin 20-40 mg, and simvastatin 10 mg could decrease LDL-C by 20-30%. The only two statins that could reduce LDL-C more than 40% were rosuvastatin and atorvastatin at a daily dose of 20 mg or higher. Meta-analysis indicated a statistically significant but clinically minor difference (<7%) between statins in cholesterol lowering effect. Comparisons of coronary heart disease prevention and safety could not be made because of insufficient data. At comparable doses, statins are therapeutically equivalent in reducing LDL-C.