Psychological Intervention in Community-Based Treatment of Schizophrenia: a Systematic Narrative Review

Add psychological interventions based mental health services community for treating people with schizophrenia (ODS) can provide positive opportunities in the recovery process. However, there was no systematic literature review for this yet. This article aims to identify and synthesize ODS's psychological interventions in the community to portray held various interventions. A systematic narrative review with the procedure of PRISMA was used in this research. The inclusion criteria are 1) psychological intervention; 2) involvement of a psychologist; 3) community settings. The search was carried out from April- May 2020. Out of 103 journals, 72 journals were reviewed, and a total of 7 journals were analyzed in this study. The involvement of psychologists in crucial positions in community mental health services is rare. Most of the interventions are led by psychiatrists. Psychological interventions include psychoeducation, CBT, SST, social support therapy, and online psychotherapy with "telementalhealth". Psychosocial interventions are given with pharmacotherapy. There was a positive effect of using psychological interventions for ODS in the community. Intervention on ODS in the community must involve multidisciplinary and multi-professional skills. Psychologists' involvement in psychological interventions can improve clinical outcomes and psychological flexibility to provide satisfaction to patients. It supports recovery-oriented mental health services. Keywords: psychological intervention; schizophrenia;                     psychologist; communit

A LITERATURE REVIEW OF TELEMEDICINE IN INDONESIA: PAST, PRESENT, AND FUTURE PROSPECTIVE

Background: Indonesia has a great potential in the development of digital health technologies. However, several challenges might also arise in hand with the development of telemedicine. Aims: We aimed to conduct a literature review of the use of telemedicine in Indonesia in order to know how the start is, the development, and future considerations of its usage. Methods: From the digital databases of PubMed, Google Scholar, and Neliti (Indonesia's Research Repository), each author completed literature searches of telemedicine in Indonesia from 1985 to 2021. Results: A total of 8 studies were included in current literature review. In 1985-1987, Indonesia undertook the first satellite-based telemedicine. During the early twenty-first century, rapid improvements in information technology have expanded to other industries, including health care through telemedicine. Covid-19 dilemma compels physicians to adopt. Through telemedicine, many is experienced the benefit during the pandemic. However, in developing telemedicine system for the future, the use of telemedicine has several challenges, namely related to human resources, infrastructure and ethical regulations. Conclusion: When telehealth is successfully implemented in Indonesia, it will benefit both the developer and the consumer. Despite the benefits, the challenge of implementing and developing a comprehensive eHealth environment in Indonesia might be seen as tremendous, given that the country is currently developing its infrastructure

Medicine Inventory Grouping using Clustering Data Mining

One of the main factors in health services is adequate medicine supplies. Puskesmas is one of the health services that is managed under the district and city health offices to serve patients every day. However, there are obstacles in the process of medicine supply at the Puskesmas. Puskesmas still uses medicine supply techniques manually by looking at the minimum medicine stock. In this way, many medicines are unused and even lacking. The application of data mining can be used as an analysis to determine the medicine supply according to the patient's needs. In the data mining method, the clustering algorithm is one of the most popular to use where the data belonging to the same cluster will be close to each other and will be far from the data about another cluster. For this reason, this study used clustering to classify types of medicines based on the number of medicine uses and requests. The results are obtained in the form of information on the type of medicine with rapid use and model of m with extended usage every month taken from three years of data. Also, information on the types of medicines from the clustering process can be used to improve better patient service