Objective To describe the criteria and procedure for defining an essential healthcare package in the developed and developing countries. Method Search words were chosen by both health policy experts and search coordinators after discussion and pilot. We searched electronic databases, websites of health institutions and governments and search engine Google. Any reports of implemented strategy to develope an essential healthcare package were included. Pre-designed data extraction form was used for collecting strategies and study method of included studies. Then the extracted information was analyzed and described. Result One hundred and sixty-six studies covering 72 countries were included, most of which were studies in the middle and low Countries. In terms of study objective,160 articles aimed to describe strategies, 6 articles aimed to evaluate effectiveness of strategies.Five studies evaluating effectiveness were cross-sectionnary data, and one study was time series. Conclusion An appropriate package should be defined according to both technique criteria and social welfare criteria, considering each country’s healthcare system and market structure, characteristics of the demander and provider, capacity of government’s regulation. The experience in transition countries gives us more high lights.
Observational studies based on real-world data are providing increasing amount of evidence for evaluating therapeutic outcomes, which is important for timely decision-making. Although time and costs for data collection could be saved using real-world data, it is significantly more complex to design real world researches with lower risk of bias. In order to enhance the validity of causal inference and to reduce potential risk of bias in real world studies, the Working Group of China Real world data and studies Alliance (China REAL) has formulated recommendations for designing observational studies to evaluate therapeutic outcomes based on real-world data. This guidance introduces design types commonly used in real world research; recommends key elements to consider in observational studies, including sample selection, specifying and allocating exposures, defining study entry and endpoints, and pre-designing statistical analysis protocols; and summarizes potential biases and corresponding control measures in real-world studies. These recommendations introduces key elements in designing observational studies using real-world data, for the purpose of improving the validity of causal inference. However, the application scope of these recommendations may be limited and warrant constant improvement.
The COSMIN-RoB checklist includes three sections with a total of 10 boxes, which is used to evaluate risk of bias of studies on content validity, internal structure, and other measurement properties. COSMIN classifies reliability, measurement error, criteria validity, hypothesis testing for construct validity, and responsiveness as other measurement properties, which primarily focus on the quality of the (sub)scale as a whole, rather than on the item level. Among the five measurement properties, reliability, measurement error and criteria validity are the most widely used in the studies. Therefore, this paper aims to interpret COSMIN-RoB checklist with examples to guide researchers to evaluate the risk of bias of the studies on reliability, measurement error and criteria validity of PROMs.