Developing and Validating Risk Scores for Predicting Major Cardiovascular Events Using Population Surveys Linked with Electronic Health Insurance Records.

Hsing-Yi Chang,Wen-Harn Pan,Ching-Yu Huang,Chih-Cheng Hsu,Shao-Yuan Chuang,Hsin-Ling Fang,Chi-Yung Chiang,Hao-Min Cheng,Tzen-Wen Chen,Wei-Cheng Yao

doi:10.3390/ijerph19031319

Abstract

A risk prediction model for major cardiovascular events was developed using population survey data linked to National Health Insurance (NHI) claim data and the death registry. Another set of population survey data were used to validate the model. The model was built using the Nutrition and Health Survey in Taiwan (NAHSIT) collected from 1993–1996 and linked with 10 years of events from NHI data. Major adverse cardiovascular events (MACEs) were identified based on hospital admission or death from coronary heart disease or stroke. The Taiwanese Survey on Hypertension, Hyperglycemia, and Hyperlipidemia (TwSHHH), conducted in 2002 was used for external validation. The NAHSIT data consisted of 1658 men and 1652 women aged 35–70 years. The incidence rates for MACE per 1000 person-years were 13.77 for men and 7.76 for women. These incidence rates for the TwSHHH were 7.27 for men and 3.58 for women. The model had reasonable discrimination (C-indexes: 0.76 for men; 0.75 for women), thus can be used to predict MACE risks in the general population. NHI data can be used to identify disease statuses if the definition and algorithm are clearly defined. Precise preventive health services in Taiwan can be based on this model.

Highlights

Precise preventive health services emphasize managing chronic diseases and developing individualized risk prediction to improve the quality and effectiveness of health care [1]
In the U.S, cardiovascular diseases (CVDs) risk is estimated using the Framingham Risk Score (FRS), which was developed in the U.S when it was facing a high CVD prevalence [2,3]
Coefficients of variation from the blood samples were within acceptable ranges deriving from 5% split blood samples [22]

Summary

Introduction

Precise preventive health services emphasize managing chronic diseases and developing individualized risk prediction to improve the quality and effectiveness of health care [1]. The ideal disease prevention should start with screening risk factors for predicting risk and promote health throughout a patient’s entire life. Cardiovascular disease is a major cause of death and disability worldwide. Recognizes the seriousness of cardiovascular disease (https://www.who.int/cardiovasc ular_diseases/guidelines/Pocket_GL_information/en/, accessed on 30 December 2021). Suggests that most cardiovascular diseases (CVDs) are preventable. A pocket guide can be used to identify people at high risk and provide guidance to prevent heart attacks or strokes. In the U.S, CVD risk is estimated using the Framingham Risk Score (FRS), which was developed in the U.S when it was facing a high CVD prevalence [2,3].

Methods

Discussion

Conclusion