R. Priambodo, P. W. Handayani, D. I. Sensuse, Ryan Randy Suryono, Kautsarina
{"title":"Health Recommender System for Maternal Care Implementation Challenges: A Qualitative Analysis of Physicians' Perspective","authors":"R. Priambodo, P. W. Handayani, D. I. Sensuse, Ryan Randy Suryono, Kautsarina","doi":"10.1109/ICACSIS56558.2022.9923536","DOIUrl":null,"url":null,"abstract":"The World Health Organization (WHO) strategy for Ending Preventable Maternal Mortality (EPMM) accommodates guidelines and objectives to lower the level of the global Maternal Mortality Ratio (MMR). Regular antenatal care (ANC) visits could increase maternal satisfaction, hence activities in ANC include risk identification, prevention, and management of pregnancy-related diseases, which could lead to maternal death. The health recommender system in healthcare helps patients and health professionals perform early predictions and receive meaningful recommendations based on patients' up-to-date health records. However, implementations of this application in maternal care are still few. Therefore, we conducted a semi-structured interview to five physicians working in maternal care to explore the challenge. The interview data were afterwards analyzed using qualitative content analysis. This qualitative study has identified six major challenges related to technological issues, such as the ability to display critical information, simplicity, compatibility, correctness, consistency, and fulfillment of functionalities required to adhere to maternal care guidelines, as well as challenges related to regulations and policies. This study contributes knowledge about the implementation of health recommender systems for maternal care and provides recommendations to application vendors and health regulators for the implementation of this system in Indonesia.","PeriodicalId":165728,"journal":{"name":"2022 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACSIS56558.2022.9923536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The World Health Organization (WHO) strategy for Ending Preventable Maternal Mortality (EPMM) accommodates guidelines and objectives to lower the level of the global Maternal Mortality Ratio (MMR). Regular antenatal care (ANC) visits could increase maternal satisfaction, hence activities in ANC include risk identification, prevention, and management of pregnancy-related diseases, which could lead to maternal death. The health recommender system in healthcare helps patients and health professionals perform early predictions and receive meaningful recommendations based on patients' up-to-date health records. However, implementations of this application in maternal care are still few. Therefore, we conducted a semi-structured interview to five physicians working in maternal care to explore the challenge. The interview data were afterwards analyzed using qualitative content analysis. This qualitative study has identified six major challenges related to technological issues, such as the ability to display critical information, simplicity, compatibility, correctness, consistency, and fulfillment of functionalities required to adhere to maternal care guidelines, as well as challenges related to regulations and policies. This study contributes knowledge about the implementation of health recommender systems for maternal care and provides recommendations to application vendors and health regulators for the implementation of this system in Indonesia.