The research of the community-home elderly long-term care service system

With the rapid development of the aging of the population, the demand of long-term care services in the elderly is growing. Because of family miniaturization, core, and currently limited social accumulation are difficult to meet the demand of the elderly in long-term care.Community provides the elderly long-term care services, and provides the elderly all kinds of household helping services. They just make up for the inadequacy of the family and society.And how to make the community elderly long-term care services become more suitable for the needs of the elderly at home, provide better service for the elderly, are our current problems to be solved.

Changes and Development of Home and Community Based Elderly Care Service Policies in China

This paper analyzes the current situation of the development of home and community based elderly care service in China,points out the existing problems,and puts forward improvement measures,aiming to deepen the understanding of HCBS and promote the theoretical research and practice of community home-based elderly care service.

A Home for the Aged in a Rural Community

Both in their mid-70s, Shan Baorui and his wife are now living at a model home for the aged in north China.The couple lives in a single room with heating in winter and an indoor toilet. Outside is a garden-like compound with flowers colorfully bright in the refresh- ing breeze.

Lessons learned from the hospital to home community care program in Singapore and the supporting AI multiple readmissions prediction model

In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.

Professional Learning Communities(PLCs)of Chemistry Teachers

The models of Professional Learning Communities(PLCs)are based on principles of learning that emphasize the co-construction of knowledge by learners,who in this case are the teachers themselves.Teachers in a PLC meet regularly to explore their practices and the learning outcomes of their students,analyze their teaching and their students’learning processes,draw conclusions,and make changes in order to improve their teaching and the learning of their students.It was found that participation in a PLC influences teaching practice,so teachers become more student-centered.Moreover,the teaching culture improves as the community increases the degree of cooperation among teachers,and focuses on the processes of learning rather than the accumulation of knowledge.This enables students to be innovative,creative,and critical.In addition,trust is developed among the participants,which enables them to discuss and analyze their students’cognitive and affective problems,misconceptions,and learning outcomes.