Barriers and challenges to Primary Health Care Information System (PHCIS) adoption from health management perspective: A qualitative study

Afrizal, Sandra Hakiem; Handayani, Putu Wuri; Hidayanto, Achmad Nizar; Eryando, Tris; Budiharsana, Meiwita; Martha, Evi

doi:10.1016/j.imu.2019.100198

Cited by 34 publications

(31 citation statements)

References 19 publications

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“…At the district, provincial and national level, they can enhance monitoring, supportive supervision and feedback [41]. However, uptake of technology-based recording and reporting is hampered by a lack of awareness and organizational support [34,43]. Other barriers include inadequate internet coverage [31,44], telecommunications network coverage [42] and electricity [45], limited budgets for system introduction, maintenance and repair of devices [46][47][48] and limited training of personnel in their use [49,50].…”

Section: Discussionmentioning

confidence: 99%

“…The details of the indicators are outlined in Table 2. A mixed-methods approach using quantitative and qualitative methods was used for this study. Mixed methods research can help address complex, multifaceted issues in health care delivery [31][32][33][34]. A qualitative study using focus group discussions (FGD) and in-depth interviews (IDI) was undertaken to elucidate the underlying reasons for the quantitative ndings using a triangulation [35,36].…”

Section: Data Collectionmentioning

confidence: 99%

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Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

Wangdi

Sarma

Leaburi³

et al. 2020

Preprint

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BackgroundDistrict Health Information Systems 2 (DHIS2) is used for supporting health information management in 67 countries, including Solomon Islands. However, there have been few published evaluations of the performance of DHIS2-enhanced disease reporting systems, in particular for monitoring infectious diseases such as malaria. The aim of this study was to evaluate DHIS2 supported malaria reporting in Solomon Islands and to develop recommendations for improving the system.MethodsThe evaluation was conducted in three administrative areas of Solomon Islands: Honoria City Council, and Malaita and Guadalcanal Provinces. Records of nine malaria indicators from 1st January to 31st December 2016 were extracted from the DHIS2 database. The indicators permitted assessment in four core areas: availability, completeness, timeliness and reliability. To obtain more detailed information on the performance of the malaria case reporting system, focus group discussions were conducted with health centre nurses, whilst in-depth interviews were conducted with stakeholder representatives from government (province and national) staff and WHO officials who were users of DHIS2. ResultsData were extracted from nine health centres in Honoria City Council and 64 health centres in Malaita Province. The completeness and timeliness from the two provinces of all nine indicators were 28.2% and 5.1% respectively. The most reliable indicator in DHIS2 was ‘clinical malaria’ (i.e. numbers of clinically diagnosed malaria cases) with 62.4% reliability. Challenges to completeness were a lack of supervision, limited feedback, high workload, and a lack of training and refresher courses. Health centres located in geographically remote areas, a lack of regular transport, high workload and too many variables in the reporting forms led to delays in timely reporting. Reliability of reports was impacted by a lack of technical professionals such as statisticians and unavailability of tally sheets and reporting forms. ConclusionThe availability, completeness, timeliness and reliability of nine malaria indicators collected in DHIS2 were variable within the study area, but generally low. Continued onsite support, supervision, feedback and additional enhancements such as electronic reporting will be required to further improve the malaria reporting system.

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Section: Discussionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

Wangdi

Sarma

Leaburi³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…At the district, provincial and national level, they can enhance monitoring, supportive supervision and feedback [24]. However, upate of technology-based recording and reporting are hampared by lack of awareness and organizational support [25,26]. Other barriers include internet coverage [27] and electricity [28], limited budgets for system introduction, maintainence and repair of devices [29][30][31] and limited training of personnel in their use [32,33].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the District Health Information System 2 Supported Malaria Reporting System in Solomon Islands

Wangdi

Sarma

Leaburi³

et al. 2020

Preprint

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BackgroundDistrict Health Information Systems 2 (DHIS2) is used for supporting health information management in 67 countries, including Solomon Islands. However, there have been few published evaluations of the performance of DHIS2-enhanced disease reporting systems, in particular for managing infectious diseases such as malaria. The aim of this study was to evaluate DHIS2 supported malaria reporting in Solomon Islands and to develop recommendations for improving the system.MethodsThe evaluation was conducted in three administrative areas of Solomon Islands: Honoria City Council, and Malaita and Gundacanal Provinces. Records of nine malaria indicators from 1st January to 31st December 2016 were extracted from the DHIS2 database. The indicators permitted assessment in four core areas: availability, completeness, timeliness and reliability. To obtain more detailed information on performance of the malaria case reporting system, focus group discussions (FGD) were conducted with health centre nurses, whilst in-depth interviews (IDI) were conducted with stakeholder representatives from government (province and national) staff and WHO officials who were users of DHIS2. ResultsData were extracted from nine health centres in Honoria City Council and 64 health centres in Malaita Province. Overall, completeness of all nine indicators was 28.2% and 5.1% of health centres submitted reports on time. The most reliable indicator in DHIS2 was ‘clinical malaria’ (i.e. numbers of clinically diagnosed malaria cases) with 62.4% reliability. Challenges to completeness were a lack of supervision, limited feedback, high workload, and a lack of training and refresher courses. Health centres located in geographically remote areas, a lack of regular transport, high workload and too many variables in the reporting forms led to delays in timely reporting. Reliability of reports was impacted by a lack of technical professionals such as statisticians and unavailability of tally sheets and reporting forms. ConclusionThe availability, completeness, timeliness and reliability of nine malaria indicators collected in DHIS2 were variable within the study area, but generally low. Continued onsite support, supervision, feedback and additional enhancements such as electronic reporting will be required to further improve the malaria reporting system.

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“…Their framework is based on two models, the HOT-fit model (which investigates the factors that influence management's decision) and the FITT model (which analyses socio-organizational factors that affect IT adoption in healthcare settings). Their results suggest that greater interaction between human resources, infrastructure, organizational support, and process factors is critical to effective adoption [24]. Multicriteria user satisfaction analysis is used to measure user satisfaction and determine the strong and weak points of user satisfaction.…”

Section: Evaluation Frameworkmentioning

confidence: 99%

G3DMS: Design and Implementation of a Data Management System for the Diagnosis of Genetic Disorders

Samra

Soh

2020

Healthcare

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Current health information systems used in genetic research centers and clinics in the Kingdom of Saudi Arabia have failed to enable researchers and health care physicians to utilize genetic and clinical data in their research. In this paper, we aim to design and implement a Genetic Disorders Diagnosis Data Management System (G3DMS) to support clinicians in the process of diagnosing genetic diseases and conducting genetic studies. A case study was undertaken to analyze a health information system in Saudi to understand its design problems via a brainstorming method. We then used the Barker’s system design method and a prototype to validate our proposed system via usability testing. This research has resulted in the development of the G3DMS that comprises: electronic data-capture forms for data entry; a customized query builder to display and modify patient data as well as form research queries; a module that allows historical data to be uploaded in the form of bulk data using a template; export data options to Excel and JavaScript Object Notation (JSON) format; and authorization access for healthcare researchers and clinicians. The G3DMS was implemented in the Princess Al-Jawhara Center of Excellence in Research of Hereditary Disorders, Jeddah, KSA.

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Barriers and challenges to Primary Health Care Information System (PHCIS) adoption from health management perspective: A qualitative study

Cited by 34 publications

References 19 publications

Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

Evaluation of the District Health Information System 2 Supported Malaria Reporting System in Solomon Islands

G3DMS: Design and Implementation of a Data Management System for the Diagnosis of Genetic Disorders

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