Mingqi Song , Lutfan Lazuardi , Raymond Francis R. Sarmiento , Brian Sahar Afifah , Gabi Ceria , Razel G. Custodio , Zahrotul Kamilah , Romeo Luis A. Macabasag , Tiara Marthias , Monica B. Sunga , Karen A. Grépin
{"title":"The role of routine health information systems in supporting the COVID-19 pandemic response in the Philippines and Indonesia","authors":"Mingqi Song , Lutfan Lazuardi , Raymond Francis R. Sarmiento , Brian Sahar Afifah , Gabi Ceria , Razel G. Custodio , Zahrotul Kamilah , Romeo Luis A. Macabasag , Tiara Marthias , Monica B. Sunga , Karen A. Grépin","doi":"10.1016/j.ssmhs.2024.100043","DOIUrl":null,"url":null,"abstract":"<div><div>The COVID-19 pandemic highlighted the importance of high-quality, geographically disaggregated, and high-frequency data for real-time evidence-based decision-making in health systems. Routine health information systems (RHIS) collect and aggregate such data but to date there have been few case studies of how RHIS were used to support COVID-19 responses in low and middle-income countries. From July-October 2021, we conducted 112 in-depth key informant interviews (KII) and seven focus group discussions (FGDs) with policymakers in Indonesia and the Philippines to better understand the role of RHIS in supporting national responses to COVID-19. Data were analysed thematically to answer key research questions: (1) How did the pandemic affect RHIS data processes? (2) How were COVID-specific data collected and integrated into RHIS? (3) How were RHIS data used to inform response measures? (4) How did RHIS interact with other health system building blocks? We found that pandemic disrupted RHIS processes, leading to a decline in the quantity, quality, and availability of RHIS data. But the pandemic also increased awareness and appreciation of RHISs, creating opportunities to strengthen and improve the utilization of the system. RHIS data and processes were directly leveraged in critical ways to strengthen the COVID-19 response, such as contact tracing and vaccination. It also indirectly supported responses via other health system building blocks, for example, by providing important data to support the design of a COVID-19 benefit package design. However, the study also identified pre-existing challenges that limited the ability of health system planners and policymakers to optimally leverage RHIS data during the pandemic. Strengthening RHIS should be integrated into future pandemic planning activities as RHIS data and processes played critical roles during the pandemic in both countries.</div></div>","PeriodicalId":101183,"journal":{"name":"SSM - Health Systems","volume":"4 ","pages":"Article 100043"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SSM - Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949856224000369","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The COVID-19 pandemic highlighted the importance of high-quality, geographically disaggregated, and high-frequency data for real-time evidence-based decision-making in health systems. Routine health information systems (RHIS) collect and aggregate such data but to date there have been few case studies of how RHIS were used to support COVID-19 responses in low and middle-income countries. From July-October 2021, we conducted 112 in-depth key informant interviews (KII) and seven focus group discussions (FGDs) with policymakers in Indonesia and the Philippines to better understand the role of RHIS in supporting national responses to COVID-19. Data were analysed thematically to answer key research questions: (1) How did the pandemic affect RHIS data processes? (2) How were COVID-specific data collected and integrated into RHIS? (3) How were RHIS data used to inform response measures? (4) How did RHIS interact with other health system building blocks? We found that pandemic disrupted RHIS processes, leading to a decline in the quantity, quality, and availability of RHIS data. But the pandemic also increased awareness and appreciation of RHISs, creating opportunities to strengthen and improve the utilization of the system. RHIS data and processes were directly leveraged in critical ways to strengthen the COVID-19 response, such as contact tracing and vaccination. It also indirectly supported responses via other health system building blocks, for example, by providing important data to support the design of a COVID-19 benefit package design. However, the study also identified pre-existing challenges that limited the ability of health system planners and policymakers to optimally leverage RHIS data during the pandemic. Strengthening RHIS should be integrated into future pandemic planning activities as RHIS data and processes played critical roles during the pandemic in both countries.