TY - JOUR
T1 - Improving Dengue Surveillance System with Administrative Claim Data in Indonesia
T2 - Opportunities and Challenges
AU - Husnayain, Atina
AU - Fuad, Anis
AU - Laksono, Ida Safitri
AU - Su, Emily Chia Yu
N1 - Publisher Copyright:
© 2020 European Federation for Medical Informatics (EFMI) and IOS Press.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/6/16
Y1 - 2020/6/16
N2 - Administrative claim data is believed as one of the promising data set to augment the mandatory surveillance system which suffered from under-reporting and delay in reporting. Therefore, this study aims to examine whether the Indonesian National Health Insurance (INHI) sample data could complement dengue case-based surveillance system in a more practical way. Afterwards, this analysis also identified several future opportunities and challenges in improving the dengue surveillance system. We utilized the referral care table linked with capitation and non-capitation-based primary care service table from 2015-2016. Data cleaning, query and visualization were performed using Tableau Public and Microsoft Power BI. Result shows that dengue referral pattern is indicating the opportunity to detect dengue cases in an earlier stage and high utilization of referral care disclose the patient behaviour. Therefore, anonymous INHI sample data set potentially to complement dengue traditional surveillance system. A huge number of health facilities as data providers, bridging and interoperability chance and opportunity of early detection are identified as future opportunities. However, we also determine challenges involving how to provide the mechanism for the quick and interoperable reporting system, how to construct supportive regulation and anticipatory approach regarding the change in dengue diagnosis criteria as the implementation of ICD 11 code. Thus, practical approaches should be prepared to support the utilization of INHI sample data.
AB - Administrative claim data is believed as one of the promising data set to augment the mandatory surveillance system which suffered from under-reporting and delay in reporting. Therefore, this study aims to examine whether the Indonesian National Health Insurance (INHI) sample data could complement dengue case-based surveillance system in a more practical way. Afterwards, this analysis also identified several future opportunities and challenges in improving the dengue surveillance system. We utilized the referral care table linked with capitation and non-capitation-based primary care service table from 2015-2016. Data cleaning, query and visualization were performed using Tableau Public and Microsoft Power BI. Result shows that dengue referral pattern is indicating the opportunity to detect dengue cases in an earlier stage and high utilization of referral care disclose the patient behaviour. Therefore, anonymous INHI sample data set potentially to complement dengue traditional surveillance system. A huge number of health facilities as data providers, bridging and interoperability chance and opportunity of early detection are identified as future opportunities. However, we also determine challenges involving how to provide the mechanism for the quick and interoperable reporting system, how to construct supportive regulation and anticipatory approach regarding the change in dengue diagnosis criteria as the implementation of ICD 11 code. Thus, practical approaches should be prepared to support the utilization of INHI sample data.
KW - claim data
KW - Dengue
KW - Indonesia
KW - public health surveillance
KW - Public health surveillance
KW - Claim data
UR - http://www.scopus.com/inward/record.url?scp=85086933088&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086933088&partnerID=8YFLogxK
U2 - 10.3233/SHTI200282
DO - 10.3233/SHTI200282
M3 - Article
C2 - 32570503
AN - SCOPUS:85086933088
SN - 0926-9630
VL - 270
SP - 853
EP - 857
JO - Studies in Health Technology and Informatics
JF - Studies in Health Technology and Informatics
ER -