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      Barriers in Health Information Systems and Technologies to Support Maternal and Neonatal Referrals at Primary Health Centers

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          Abstract

          Objectives

          This study explored health workers’ perceptions and experiences regarding the maternal and neonatal referral system, focusing on barriers of health information systems and technologies (IS/IT) at primary health centers (PHCs) in South Tangerang, Indonesia.

          Methods

          This qualitative study was conducted using semi-structured interviews, which were conducted at the South Tangerang District Health Office and three PHCs. Interviews were conducted with nine participants responsible for maternal and neonatal referrals in their organizations. The data were analyzed using qualitative content analysis.

          Results

          In South Tangerang, the Primary Health Care Information System (SIMPUS) is used to register patients and record data on medical treatment. To facilitate referrals, the PHCs currently use the Integrated Referral Information System (SISRUTE), P-Care, and the Integrated Emergency Management System (SPGDT). The following four IS/IT barriers to support maternal and neonatal referrals were found: technology, human resources, organizational support, and the referral process and implementation.

          Conclusions

          The barriers in technology, human resources, and organizational support cause problems in the maternal and neonatal referral process and in the implementation of referrals. Barriers to referrals can influence patients’ ability to receive appropriate care in a timely fashion and lead to inefficiency in maternal and neonatal referrals. This study contributes knowledge about IS/IT implementation in maternal and neonatal referral systems and provides recommendations to health regulators and application developers for the implementation of IS/IT in Indonesia.

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          Most cited references26

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            Maternity referral systems in developing countries: current knowledge and future research needs.

            A functioning referral system is generally considered to be a necessary element of successful Safe Motherhood programmes. This paper draws on a scoping review of available literature to identify key requisites for successful maternity referral systems in developing countries, to highlight knowledge gaps, and to suggest items for a future research agenda. Key online social science, medical and health system bibliographic databases, and websites were searched in July 2004 for evidence relating to referral systems for maternity care. Documentary evidence on implementation is scarce, but it suggests that many healthcare systems in developing countries are failing to optimise women's rapid access to emergency obstetric care, and that the poor and marginalised are affected disproportionately. Likely requisites for successful maternity referral systems include: a referral strategy informed by the assessment of population needs and health system capabilities; an adequately resourced referral centre; active collaboration between referral levels and across sectors; formalised communication and transport arrangements; agreed setting-specific protocols for referrer and receiver; supervision and accountability for providers' performance; affordable service costs; the capacity to monitor effectiveness; and underpinning all of these, policy support. Theoretically informed social and organisational research is required on the referral care needs of the poor and marginalised, on the maternity workforce and organisation, and on the implications of the mixed economy of healthcare for referral networks. Clinical research is required to determine how maternity referral fits within newborn health priorities and where the needs are different. Finally, research is required to determine how and whether a more integrated approach to emergency care systems may benefit women and their communities.
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              mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial

              Background/objective Guatemala’s indigenous Maya population has one of the highest perinatal and maternal mortality rates in Latin America. In this population most births are delivered at home by traditional birth attendants (TBAs), who have limited support and linkages to public hospitals. The goal of this study was to characterize the detection of maternal and perinatal complications and rates of facility-level referral by TBAs, and to evaluate the impact of a mHealth decision support system on these rates. Methods A pragmatic one-year feasibility trial of an mHealth decisions support system was conducted in rural Maya communities in collaboration with TBAs. TBAs were individually randomized in an unblinded fashion to either early-access or later-access to the mHealth system. TBAs in the early-access arm used the mHealth system throughout the study. TBAs in the later-access arm provided usual care until crossing over uni-directionally to the mHealth system at the study midpoint. The primary study outcome was the monthly rate of referral to facility-level care, adjusted for birth volume. Results Forty-four TBAs were randomized, 23 to the early-access arm and 21 to the later-access arm. Outcomes were analyzed for 799 pregnancies (early-access 425, later-access 374). Monthly referral rates to facility-level care were significantly higher among the early-access arm (median 33 referrals per 100 births, IQR 22–58) compared to the later-access arm (median 20 per 100, IQR 0–30) (p = 0.03). At the study midpoint, the later-access arm began using the mHealth platform and its referral rates increased (median 34 referrals per 100 births, IQR 5–50) with no significant difference from the early-access arm (p = 0.58). Rates of complications were similar in both arms, except for hypertensive disorders of pregnancy, which were significantly higher among TBAs in the early-access arm (RR 3.3, 95% CI 1.10–9.86). Conclusions Referral rates were higher when TBAs had access to the mHealth platform. The introduction of mHealth supportive technologies for TBAs is feasible and can improve detection of complications and timely referral to facility-care within challenging healthcare delivery contexts. Trial registration Clinicaltrials.gov NCT02348840.
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                Author and article information

                Journal
                Healthc Inform Res
                Healthc Inform Res
                Healthcare Informatics Research
                Korean Society of Medical Informatics
                2093-3681
                2093-369X
                April 2021
                30 April 2021
                : 27
                : 2
                : 153-161
                Affiliations
                Faculty of Computer Science, University of Indonesia, Depok, West Java, Indonesia
                Author notes
                Corresponding Author: Nabila Clydea Harahap, Faculty of Computer Science, University of Indonesia, Kampus UI Depok, Pondok Cina, Kecamatan Beji, Kota Depok, Jawa Barat 16424, Indonesia. Tel: +62-85716526799, E-mail: nabila.clydea@ 123456ui.ac.id ( https://orcid.org/0000-0001-7420-0396)
                Author information
                https://orcid.org/0000-0001-7420-0396
                https://orcid.org/0000-0001-5341-3800
                https://orcid.org/0000-0002-5793-9460
                Article
                hir-27-2-153
                10.4258/hir.2021.27.2.153
                8137880
                34015881
                5088603e-2f31-4e57-ad45-7fba0488afa8
                © 2021 The Korean Society of Medical Informatics

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 February 2020
                : 4 January 2021
                : 28 January 2021
                : 29 January 2021
                Categories
                Case Report

                Bioinformatics & Computational biology
                referral and consultation,health information systems,primary health care,maternal health,newborn infant

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