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Preparing routine health information systems for immediate health responses to disasters.

ABSTRACT: During disaster times, we need specific information to rapidly plan a disaster response, especially in sudden-onset disasters. Due to the inadequate capacity of Routine Health Information Systems (RHIS), many developing countries face a lack of quality pre-disaster health-related data and efficient post-disaster data processes in the immediate aftermath of a disaster. Considering the significance of local capacity during the early stages of disaster response, RHIS at local, provincial/state and national levels need to be strengthened so that they provide relief personnel up-to-date information to plan, organize and monitor immediate relief activities. RHIS professionals should be aware of specific information needs in disaster response (according to the Sphere Project's Humanitarian Minimum Standards) and requirements in data processes to fulfil those information needs. Preparing RHIS for disasters can be guided by key RHIS-strengthening frameworks; and disaster preparedness must be incorporated into countries' RHIS. Mechanisms must be established in non-disaster times and maintained between RHIS and information systems of non-health sectors for exchanging disaster-related information and sharing technologies and cost.

SUBMITTER: Aung E

PROVIDER: S-EPMC3743306 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Preparing routine health information systems for immediate health responses to disasters.

Aung Eindra E Whittaker Maxine M

Health policy and planning 20120922 5

During disaster times, we need specific information to rapidly plan a disaster response, especially in sudden-onset disasters. Due to the inadequate capacity of Routine Health Information Systems (RHIS), many developing countries face a lack of quality pre-disaster health-related data and efficient post-disaster data processes in the immediate aftermath of a disaster. Considering the significance of local capacity during the early stages of disaster response, RHIS at local, provincial/state and ...[more]

PMID: 23002249

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Project description:BackgroundReliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care.MethodsWe use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria.ResultsPassive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations' financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years.ConclusionsUnderstanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.

Project description:Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012-2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0-6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other sources. We recommend addressing the denominator issues, reducing the complexity of indicators, and aligning indicators to international definitions.

Project description:ObjectiveTo identify recurrent themes, insights, and process recommendations from stakeholders in US organizations during the health information technology (HIT) modernization of an existing electronic health record (EHR) to a commercial-off-the-shelf product in both resource-plentiful settings and in a resource-constrained environment, the US Indian Health Service.Materials and methodsThirteen qualitative interviews with stakeholders in various organizations were conducted about HIT modernization efforts. Using a Theory of Change framework, recurring themes were identified and analyzed.ResultsThe interviewees emphasized the importance of organizational and process revision during modernization, converting historical data, and clinical and leadership involvement. HIT implementation required technological and infrastructure redesign, additional training, and workflow reconfiguration. Motivations for modernization included EHR usability dissatisfaction, revenue enhancements, and improved clinical operations. Decision-making strategies, primarily during HIT selection, included meetings with stakeholders. Successful modernization resulted in improvements in clinical operations, patient experience, and financial outlay.DiscussionExisting implementation frameworks fail to provide experiential feedback, such as implementation challenges, like data conversion, regulatory, functionality, and interoperability requirements. Regardless of the healthcare environment, HIT modernization requires the engagement of leadership and end-users during HIT selection and through all stages of the implementation to prepare people, processes, and technology. Organizations must iteratively define the technological, infrastructure, organizational, and workflow changes required for a successful HIT modernization effort.ConclusionsHIT modernization is an opportunity for organizational and technological change. Successful modernization requires a comprehensive, intentional, well-communicated, and multidisciplinary approach. Resource-constrained environments have the additional challenges of financial burdens, limited staffing, and unstable infrastructure.

Dataset Information

Preparing routine health information systems for immediate health responses to disasters.

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Preparing routine health information systems for immediate health responses to disasters.

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