National Health Insurance database in Taiwan: A resource or obstacle for health research?

Realizing the promise of big data: how Taiwan can help the world reduce medical errors and advance precision medicine

Purpose

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

Design/methodology/approach

This study is a narrative review of the literature.

Findings

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

Originality/value

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

Risk of motor vehicle collisions after methadone use

Methadone maintenance treatment (MMT) can alleviate opioid dependence. However, MMT possibly increases the risk of motor vehicle collisions. The current study investigated preliminary estimation of motor vehicle collision incidence rates. Furthermore, in this population-based retrospective cohort study with frequency-matched controls, opiate adults receiving MMT (cases) and those not receiving MMT (controls) were identified at a 1:2 ratio by linking data from several nationwide administrative registry databases. From 2009 to 2016, the crude incidence rate of motor vehicle collisions was the lowest in the general adult population, followed by that in opiate adults, and it was the highest in adults receiving MMT. The incidence rates of motor vehicle collisions were significantly higher in opiate users receiving MMT than in those not receiving MMT. Kaplan–Meier curves of the incidence of motor vehicle collisions differed significantly between groups, with a significant increased risk during the first 90 days of follow-up. In conclusion, drivers receiving MMT have higher motor vehicle collision risk than those not receiving MMT in opiate users, and it is worthy of noticing road safety in such drivers, particularly during the first 90 days of MMT.

In 2019, 58 million people were estimated to use opioids – a group of substances that include drugs like heroin and morphine. Dependence on opioids can be managed using a prescribed dose of an opioid called methadone, which is administered through a controlled treatment plan. This so-called methadone maintenance treatment manages withdrawal symptoms in opioid-dependent individuals and can reduce the occurrences of overdose, criminal activity and transmission of diseases such as HIV.

However, methadone acts on the same brain receptors as other opioids, and individuals receiving methadone may experience impaired motoric and cognitive functioning, including reduced driving ability. It is therefore important to know whether methadone maintenance treatment may increase an individual’s risk to cause road accidents.

To assess motor vehicle collision risk associated with individuals receiving methadone maintenance treatment, Yang et al. analysed data from the Taiwan National Health Insurance Research Database and six Taiwanese administrative registries, including the ministries of health and welfare, interior and justice, and registries in substitution maintenance therapy, road accidents and the National Police Agency.

Initial analyses found that individuals receiving treatment had a higher risk to be involved in car accidents than the general adult population or those without methadone maintenance treatment. Further tests showed that individuals receiving treatment were at three times higher risk of collisions than individuals not receiving treatment, particularly in the first 90 days.

These findings may help individuals undergoing methadone maintenance treatment manage their risk of motor vehicle collisions. Further investigation is needed to reveal the underlying mechanisms of methadone-related impairment of driving ability.

Two Decades of Research Using Taiwan's National Health Insurance Claims Data: Bibliometric and Text Mining Analysis on PubMed

Background

Studies using Taiwan’s National Health Insurance (NHI) claims data have expanded rapidly both in quantity and quality during the first decade following the first study published in 2000. However, some of these studies were criticized for being merely data-dredging studies rather than hypothesis-driven. In addition, the use of claims data without the explicit authorization from individual patients has incurred litigation.

Objective

This study aimed to investigate whether the research output during the second decade after the release of the NHI claims database continues growing, to explore how the emergence of open access mega journals (OAMJs) and lawsuit against the use of this database affect the research topics and publication volume and to discuss the underlying reasons.

Methods

PubMed was used to locate publications based on NHI claims data between 1996 and 2017. Concept extraction using MetaMap was employed to mine research topics from article titles. Research trends were analyzed from various aspects, including publication amount, journals, research topics and types, and cooperation between authors.

Results

A total of 4473 articles were identified. A rapid growth in publications was witnessed from 2000 to 2015, followed by a plateau. Diabetes, stroke, and dementia were the top 3 most popular research topics whereas statin therapy, metformin, and Chinese herbal medicine were the most investigated interventions. Approximately one-third of the articles were published in open access journals. Studies with two or more medical conditions, but without any intervention, were the most common study type. Studies of this type tended to be contributed by prolific authors and published in OAMJs.

Conclusions

The growth in publication volume during the second decade after the release of the NHI claims database was different from that during the first decade. OAMJs appeared to provide fertile soil for the rapid growth of research based on NHI claims data, in particular for those studies with two or medical conditions in the article title. A halt in the growth of publication volume was observed after the use of NHI claims data for research purposes had been restricted in response to legal controversy. More efforts are needed to improve the impact of knowledge gained from NHI claims data on medical decisions and policy making.

Improved medical expenditure and survival with integration of traditional Chinese medicine treatment in patients with heart failure: A nationwide population-based cohort study

Background

No previous studies have evaluated the effects of traditional Chinese medicine (TCM) treatment on patients with heart failure (HF). Hence, in this study, we determined whether TCM treatment affects the healthcare burden and survival of HF patients.

Methods

Samples were retrieved from the registry of catastrophic illness patients of the Taiwan National Health Insurance Research Database (NHIRD). Based on a frequency (1:1) matched case-control design, patients with HF between 2000 and 2010 were designated as cases (TCM users) and controls (non-TCM users). TCM treatment for patients with HF was analyzed.

Results

Among these patients, 312 used TCM for HF treatment and exhibited significantly increased 5-year survival (p < .0001), with multivariate adjustment, compared with those without TCM use. Mean outpatient clinic visits at 1 year and 5 years after HF diagnosis were higher in TCM users, and accumulated medical costs were lower than in non-TCM users at 1 year. The hospitalization cost at 1-year follow-up was lower for TCM users than for non-TCM users. We found that, compared with non-TCM users, TCM users had an 86% reduction in risk of mortality in the compensated group, and a 68% reduction in the decompensated group receiving TCM treatment (aHR 0.32, 95% CI 0.20–0.52). The hazard ratio (HR) of Chinese herbal medicine (CHM) users with HF was significantly lower than that of non-users (aHR 0.24, 95% CI 0.16–0.35). We also analyzed the most commonly used herbal products as well as the HRs associated with their use, thus providing future research avenues.

Conclusions

This nationwide retrospective cohort study finds that combined therapy with TCM may improve survival in HF patients. This study also suggests that TCM may be used as an integral element of HF interventions on health care costs.

Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study

There has been a surge in the academic publication output based on secondary analyses of the data from the Taiwan's National Health Insurance claim records. It has become a challenge to comprehend such a rapid expansion of the literature. Therefore, this study aimed to explore the conceptual content of National Health Insurance Research Database-based cancer research, using the abstract of articles extracted from PubMed between 2002 and 2015. Search terms including "National Health Insurance Research Database (NHIRD) AND Taiwan," "Taiwan AND population-based," and "Taiwan AND nationwide" were used to search in PubMed with the publication date limited to between 1997 and 2015. The retrieved articles were manually screened to retain only those that were cancer-related and were based on secondary data analysis of the NHIRD. A total 589 articles were selected for subsequent text mining using the R software. Among the 589 articles, the top 5 most studied cancer types were breast (16.3%), lung (11.4%), colorectal (10.4%), liver (8.3%), and prostate (7.5%). The articles that received the highest number of citations by PubMed Central articles were cited 92 times. The top 3 most frequently occurred keywords in the abstracts of the 589 articles were cancer, patient, and risk, with 3670, 2535, and 1652 times, respectively. Analysis of key conception indicated that the most common conceptions were diabetes, survival, breast cancer, lung cancer, and colorectal cancer. In conclusion, in this study of 589 published articles on secondary data analysis of the NHIRD, indexed by PubMed between 2002 and 2015, we found that while the risk factors of cancer, treatment of cancer, and survival of cancer patients were popular research topics, end-of-life cancer care issues were less studied. Further studies should explore these areas since they are as important as treatment of the disease itself for many patients.