Impact of National Public-Private Mix and Medical Expense Support Program to Control Tuberculosis in South Korea: An Interrupted Time Series Analysis.

Tuberculosis (TB) remains a major threat to global public health. Various measures at the national level have been implemented to control TB, and no evidence with long-term effectiveness has yet been evaluated on TB control programs. We confirmed the long-term effectiveness of the TB control programs in reducing overall burden in South Korea using interrupted time series analysis. Our finding suggests that, along with the public-private mix, relieving the economic burden of people with TB may complement achieving the End TB Strategy. For countries currently developing strategies for TB control, results may provide important insights in effective TB control.

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders.

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.

Incidence and Healthcare Burden of Pertussis among Older Adults with and without Pre-Existing Chronic Obstructive Pulmonary Disease or Asthma in South Korea.

A retrospective cohort study was conducted to examine trends in the incidence and burden of pertussis among adults ≥50 years in South Korea, with/without pre-existing chronic obstructive pulmonary disease (COPD) or asthma. The nationwide Health Insurance Review and Assessment Service (HIRA) database was used to identify patients ≥50 years diagnosed with pertussis (2009-2018). Mean annual incidence of pertussis per 100 000 persons and overall mean incidence rate ratios (IRR) were calculated for patients with pre-existing COPD or asthma versus those with neither. Incremental healthcare costs (all-cause and pertussis-related) and healthcare utilisation (number of outpatient visits, emergency room visits, and number and length of hospitalisations) up to 12 months after, compared to 3 months before pertussis diagnosis, were also measured for each group (matched on sex, age, and Charlson Comorbidity Index). Of 1011 pertussis cases, 175 had asthma, 96 had COPD (not mutually exclusive), and 796 had neither. Overall mean pertussis incidence was 2.5, 3.4, and 0.5 for adults with pre-existing COPD, asthma, and those with neither. IRR (95% confidence interval) of pertussis for adults with pre-existing COPD and asthma was 4.9 (4.0-|6.1) and 6.7 (5.7-7.9). Both COPD-pertussis and asthma-pertussis groups had higher mean incremental all-cause costs and length of hospitalisations than the general-pertussis group 3 months following pertussis diagnosis. In conclusion, individuals ≥50 years in South Korea with pre-existing COPD or asthma were at an increased risk of being diagnosed with pertussis and had higher healthcare resource utilisation than those without these conditions.

Application of Healthcare 'Big Data' in CNS Drug Research: The Example of the Neurological and mental health Global Epidemiology Network (NeuroGEN).

Neurological and psychiatric (mental health) disorders have a large impact on health burden globally. Cognitive disorders (including dementia) and stroke are leading causes of disability. Mental health disorders, including depression, contribute up to one-third of total years lived with disability. The Neurological and mental health Global Epidemiology Network (NeuroGEN) is an international multi-database network that harnesses administrative and electronic medical records from Australia, Asia, Europe and North America. Using these databases NeuroGEN will investigate medication use and health outcomes in neurological and mental health disorders. A key objective of NeuroGEN is to facilitate high-quality observational studies to address evidence-practice gaps where randomized controlled trials do not provide sufficient information on medication benefits and risks that is specific to vulnerable population groups. International multi-database research facilitates comparisons across geographical areas and jurisdictions, increases statistical power to investigate small subpopulations or rare outcomes, permits early post-approval assessment of safety and effectiveness, and increases generalisability of results. Through bringing together international researchers in pharmacoepidemiology, NeuroGEN has the potential to be paradigm-changing for observational research to inform evidence-based prescribing. The first focus of NeuroGEN will be to address evidence-gaps in the treatment of chronic comorbidities in people with dementia.