Database profile of the Fukuoka-City Information Platform for Community-based Integrated Care

BACKGROUND

The Fukuoka-City Information Platform for Community-based Integrated Care is an advanced big data platform that aggregates information on the health and medical services of Fukuoka citizens. Fukuoka City is engaged in a joint project with Kyushu University to promote policy making through a large-scale real-world data analysis. This paper describes the framework for this cooperative effort and the features of the analytical platform.

METHODS

Fukuoka City is the fifth most populous ordinance-designated city in Japan, with an estimated population of approximately 1.6 million. Under an agreement with Fukuoka City, Kyushu University was granted access to a portion of the city's anonymized healthcare database as secondary-use information. The database contains information on resident registration, health insurance claims, specific health checkups and health checkups for the older adults, specific health guidance, long-term care insurance data, and cancer screenings collected after fiscal year 2012. Each of these constituent datasets can be interlinked using anonymized hashed key variables, allowing individuals to be followed across databases and over time.

CONCLUSIONS

The platform allows longitudinal investigation of the complex association between various aspects of healthcare, such as medical procedures, examinations, interviews, medical costs, long-term care certifications, and care costs. The platform can provide valuable public-health information because it is relatively large for a single database, and because it allows analysis of data across multiple domains and tracing of individuals over time.

Agreement in All-in-One Dataset between Diagnosis and Prescribed Medication for Common Cardiometabolic Diseases in the NDB-K7Ps

The Japanese National Database (NDB), a useful data source for epidemiological studies, contains information on health checkups, disease diagnoses, and medications, which can be used when investigating common cardiometabolic diseases. However, before the initiation of an integrated analysis, we need to combine several pieces of information prepared separately into an all-in-one dataset (AIOD) and confirm the validation of the dataset for the study. In this study, we aimed to confirm the degree of agreement in data entries between diagnoses and prescribed medications and self-reported pharmacotherapy for common cardiometabolic diseases in newly assembled AIODs. The present study included 10,183,619 people who underwent health checkups from April 2018 to March 2019. Over 95% of patients prescribed antihypertensive and antidiabetic medications were diagnosed with each disease. For dyslipidemia, over 95% of patients prescribed medications were diagnosed with at least one of the following: dyslipidemia, hypercholesterolemia, or hyperlipidemia. Similarly, over 95% of patients prescribed medications for hyperuricemia were diagnosed with either hyperuricemia or gout. Additionally, over 90% of patients with self-reported medications for hypertension, diabetes, and dyslipidemia were diagnosed with each disease, although the proportions differed among age groups. Our study demonstrated high levels of agreement between diagnoses and prescribed medications for common cardiometabolic diseases and self-reported pharmacotherapy in our AIOD.

Factors Associated with Refraining from Health Checkups during the COVID-19 Pandemic in Japan

This study aimed to determine the characteristics of people who refrained from having regular checkups due to the spread of the novel coronavirus 2019 (COVID-19) infection and the factors associated with this behavior. We conducted a nationwide internet survey of 4593 males and females aged 20-69 in Japan regarding their health checkups from April 2020 to March 2021, when COVID-19 was widespread. Individuals who received checkups during this time were "the receiving group"; those who did not were "the refraining group". Personal attributes, responses to a health questionnaire and other items were used to compare the groups. The analysis showed that males over 53 refrained from having health checkups compared to those younger. On the other hand, males with higher personal incomes who never skipped breakfast received health checkups. Females with children under 18 years were less likely than those without to receive health checkups. For males, the characteristic factors were economic and health awareness and literacy. Females were less aware of medical checkups. Moreover, they demonstrated an inability to maintain an everyday rhythm. No factors were common to males and females, indicating the need to consider separate strategies for encouraging males and females to obtain annual health checkups.

Effect of reminder letters after health checkups on the consultation behavior of participants with possible hypertension, hyperglycemia, and dyslipidemia: A retrospective cohort study using administrative claims data in Japan

OBJECTIVES

Prevention of and early treatment for noncommunicable diseases such as hypertension, hyperglycemia, and dyslipidemia are important, as these diseases are asymptomatic in early stages but can lead to critical conditions such as macro- and microvascular disorders later on. While screening is conducted worldwide, low rates of hospital visits after screening is a common issue. We aimed to investigate the effect of reminder letters on the consultation behavior of screened participants.

METHODS

We used administrative claims data from a database managed by JMDC Inc for participants of health checkups in 2014, 2015, 2016, and 2017, who belonged to a health insurance society. Reminder letters were sent regularly 6 months after checkups to improve participant consultation behavior. Participants who screened positive for hypertension, hyperglycemia, and dyslipidemia, and who were not taking medication for any of these diseases at the time of health checkups, were included in the analyses.

RESULTS

A total of 1739 participants in 2014, 1693 in 2015, 2002 in 2016, and 2144 in 2017 were included in the analysis for hypertension. The cumulative proportion of hospital visits gradually increased over the course of 12 months after checkups in all years. After 2015, spikes, albeit very small ones, were observed at 6 months after checkups in accordance with the timing of reminder letters. Similar trends were observed for hyperglycemia and dyslipidemia.

CONCLUSIONS

Sending reminder letters is a potentially effective approach to increase hospital visits, but further improvements (ie, multiple reminders) may be necessary to affect enhancements in participant consultation behavior.

Effects of changes in eating speed on obesity in patients with diabetes: a secondary analysis of longitudinal health check-up data

OBJECTIVE

Few studies have examined the causal relationships between lifestyle habits and obesity. With a focus on eating speed in patients with type 2 diabetes, this study aimed to analyse the effects of changes in lifestyle habits on changes in obesity using panel data.

METHODS

Patient-level panel data from 2008 to 2013 were generated using commercially available insurance claims data and health check-up data. The study subjects comprised Japanese men and women (n=59 717) enrolled in health insurance societies who had been diagnosed with type 2 diabetes during the study period. Body mass index (BMI) was measured, and obesity was defined as a BMI of 25 or more. Information on lifestyle habits were obtained from the subjects' responses to questions asked during health check-ups. The main exposure of interest was eating speed ('fast', 'normal' and 'slow'). Other lifestyle habits included eating dinner within 2 hours of sleeping, after-dinner snacking, skipping breakfast, alcohol consumption frequency, sleep adequacy and tobacco consumption. A generalised estimating equation model was used to examine the effects of these habits on obesity. In addition, fixed-effects models were used to assess these effects on BMI and waist circumference.

RESULTS

The generalised estimating equation model showed that eating slower inhibited the development of obesity. The ORs for slow (0.58) and normal-speed eaters (0.71) indicated that these groups were less likely to be obese than fast eaters (P<0.001). Similarly, the fixed-effects models showed that eating slower reduced BMI and waist circumference. Relative to fast eaters, the coefficients of the BMI model for slow and normal-speed eaters were -0.11 and -0.07, respectively (P<0.001).

DISCUSSION

Changes in eating speed can affect changes in obesity, BMI and waist circumference. Interventions aimed at reducing eating speed may be effective in preventing obesity and lowering the associated health risks.