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      Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia

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          Abstract

          Background

          Health management information system (HMIS) is a system whereby health data are recorded, stored, retrieved and processed to improve decision-making. HMIS data quality should be monitored routinely as production of high quality statistics depends on assessment of data quality and actions taken to improve it. Thus, this study assessed accuracy of the routine HMIS data.

          Methods

          Facility based cross-sectional study was conducted in Southern Nations Nationalities and People’s region in 2017. Document review was done in 163 facilities of different levels. Statistical Package for the Social Sciences (SPSS) for windows version 20 was used to perform data analysis. Data accuracy was presented in terms of mean and standard deviation of data verification factor.

          Results

          Though inaccuracy was noted for all data elements, 96.9 and 84.7% of facilities reported institutional maternal death and skilled birth attendance within acceptable range respectively while confirmed malaria (45.4%), antenatal care fourth visit (46.6%), postnatal care (55.2%), fully immunized (55.8%), severe acute malnutrition (54.6%) and total malaria (50.3%) were reported accurately only by about half of facilities. Antenatal care fourth visit was over reported by 24% while total malaria was under reported by 28%. Reasons for variations included technical, behavioral and organizational factors.

          Conclusions

          Majority of facilities over reported services while under reporting diseases. Data quality should be monitored routinely against data quality parameters quantitatively and/or qualitatively to catch-up country’s information revolution agenda.

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          Most cited references4

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          Design and implementation of a health management information system in Malawi: issues, innovations and results.

          As in many developing countries, lack of reliable data and grossly inadequate appreciation and use of available information in planning and management of health services were two main weaknesses of the health information systems in Malawi. Malawi began strengthening its health management information system with an analysis of the strengths and weaknesses of existing information systems, sharing findings with all stakeholders. All were agreed on the need for reformation of various, vertical programme-specific information systems into a comprehensive, integrated, decentralized and action-oriented simple system. As a first step towards conceptualization and design of the system, a minimum set of indicators was identified and a strategy was formulated for establishing a system in the country. The design focused only on the use of information in planning, management and the improvement of quality and coverage of services. All health and support personnel were trained, employing a training of trainers cascade approach. Information management and use was incorporated into the pre-service training curriculum and the job description of all health workers and support personnel. Quarterly feedback, supportive supervision visits and annual reviews were institutionalized. Civil society organizations were involved in monitoring coverage of health services at local levels. A mid-term review of the achievements of the health information system judged it to be one of the best in Africa. For the first time in Malawi, the health sector has information by facility by month. Yet very little improvement has been noted in use of information in rationalizing decisions. The conclusion is that, no matter how good the design of an information system, it will not be effective unless there is internal desire, dedication and commitment of leadership to have an effective and efficient health service management system.
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            An assessment of routine primary care health information system data quality in Sofala Province, Mozambique

            Background Primary health care is recognized as a main driver of equitable health service delivery. For it to function optimally, routine health information systems (HIS) are necessary to ensure adequate provision of health care and the development of appropriate health policies. Concerns about the quality of routine administrative data have undermined their use in resource-limited settings. This evaluation was designed to describe the availability, reliability, and validity of a sample of primary health care HIS data from nine health facilities across three districts in Sofala Province, Mozambique. HIS data were also compared with results from large community-based surveys. Methodology We used a methodology similar to the Global Fund to Fight AIDS, Tuberculosis and Malaria data verification bottom-up audit to assess primary health care HIS data availability and reliability. The quality of HIS data was validated by comparing three key indicators (antenatal care, institutional birth, and third diptheria, pertussis, and tetanus [DPT] immunization) with population-level surveys over time. Results and discussion The data concordance from facility clinical registries to monthly facility reports on five key indicators--the number of first antenatal care visits, institutional births, third DPT immunization, HIV testing, and outpatient consults--was good (80%). When two sites were excluded from the analysis, the concordance was markedly better (92%). Of monthly facility reports for immunization and maternity services, 98% were available in paper form at district health departments and 98% of immunization and maternity services monthly facility reports matched the Ministry of Health electronic database. Population-level health survey and HIS data were strongly correlated (R = 0.73), for institutional birth, first antenatal care visit, and third DPT immunization. Conclusions Our results suggest that in this setting, HIS data are both reliable and consistent, supporting their use in primary health care program monitoring and evaluation. Simple, rapid tools can be used to evaluate routine data and facilitate the rapid identification of problem areas.
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              Improving the quality of health information: a qualitative assessment of data management and reporting systems in Botswana

              Background Ensuring that data collected through national health information systems are of sufficient quality for meaningful interpretation is a challenge in many resource-limited countries. An assessment was conducted to identify strengths and weaknesses of the health data management and reporting systems that capture and transfer routine monitoring and evaluation (M&E) data in Botswana. Methods This was a descriptive, qualitative assessment. In-depth interviews were conducted at the national (n = 27), district (n = 31), and facility/community (n = 71) levels to assess i) M&E structures, functions, and capabilities; ii) indicator definitions and reporting guidelines; iii) data collection forms and tools; iv) data management processes; and v) links with the national reporting system. A framework analysis was conducted using ATLAS.ti v6.1. Results Health programs generally had standardized data collection and reporting tools and defined personnel for M&E responsibilities at the national and district levels. Best practices unique to individual health programs were identified and included a variety of relatively low-resource initiatives such as attention to staffing patterns, making health data more accessible for evidence-based decision-making, developing a single source of information related to indicator definitions, data collection tools, and management processes, and utilization of supportive supervision visits to districts and facilities. Weakness included limited ownership of M&E-related duties within facilities, a lack of tertiary training programs to build M&E skills, few standard practices related to confidentiality and document storage, limited dissemination of indicator definitions, and limited functionality of electronic data management systems. Conclusions Addressing fundamental M&E system issues, further standardization of M&E practices, and increasing health services management responsiveness to time-sensitive information are critical to sustain progress related to health service delivery in Botswana. In addition to high-resource initiatives, such as investments in electronic medical record systems and tertiary training programs, there are a variety of low-resource initiatives, such as regular data quality checks, that can strengthen national health information systems. Applying best practices that are effective within one health program to data management and reporting systems of other programs is a practical approach for strengthening health informatics and improving data quality.
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                Author and article information

                Contributors
                misganuendrias@yahoo.com
                alanoabraham@yahoo.com
                emekonnen62@yahoo.com
                sinafik_a@yahoo.com
                temesegenkelaye@yahoo.com
                meknnn3@yahoo.com
                tebejemisga@gmail.com
                tekish_samuel@yahoo.com
                tesfahunhailemariam@gmail.com
                samuelthehawassa@gmail.com
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                18 March 2019
                18 March 2019
                2019
                : 19
                : 175
                Affiliations
                [1 ]GRID grid.463592.f, SNNPR Health Bureau, ; Hawassa, Ethiopia
                [2 ]Hawassa Health Science College, Hawassa, Ethiopia
                Article
                3991
                10.1186/s12913-019-3991-7
                6423785
                30885204
                4bb71d8d-6aa7-4a5d-80a9-2aa9c43c74fb
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 August 2018
                : 6 March 2019
                Funding
                Funded by: SNNPR Health Bureau
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Health & Social care
                data quality,accuracy,snnpr,verification factor,hmis,performance data,performance monitoring,evidence-based decision-making

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