scholarly journals Addressing missing values in routine health information system data: an evaluation of imputation methods using data from the Democratic Republic of the Congo during the COVID-19 pandemic

2021 ◽  
Author(s):  
Shuo Feng ◽  
Celestin Hategeka ◽  
Karen Ann Grépin
Keyword(s):  
Information System ◽  
Multiple Imputation ◽  
Health Information ◽  
Missing Values ◽  
Health Management ◽  
Health Management Information System ◽  
Middle Income ◽  
Imputation Methods ◽  
Mean Imputation ◽  
Republic Of The Congo

Abstract Background : Poor data quality is limiting the greater use of data sourced from routine health information systems (RHIS), especially in low and middle-income countries. An important part of this issue comes from missing values, where health facilities, for a variety of reasons, miss their reports into the central system. Methods : Using data from the Health Management Information System (HMIS) and the advent of COVID-19 pandemic in the Democratic Republic of the Congo (DRC) as an illustrative case study, we implemented six commonly-used imputation methods using the DRC’s HMIS datasets and evaluated their performance through various statistical techniques, i.e., simple linear regression, segmented regression which is widely used in interrupted time series studies, and parametric comparisons through t-tests and non-parametric comparisons through Wilcoxon Rank-Sum tests. We also examined the performance of these six imputation methods under different missing mechanisms and tested their stability to changes in the data. Results : For regression analyses, there was no substantial difference found in the results generated from all methods except mean imputation and exclusion & interpolation when the RHIS dataset contained less than 20% missing values. However, as the missing proportion grew, machine learning methods such as missForest and k -NN started to produce biased estimates, and they were found to be also lack of robustness to minimal changes in data or to consecutive missingness. On the other hand, multiple imputation generated the overall most unbiased estimates and was the most robust to all changes in data. For comparing group means through t-tests, the results from mean imputation and exclusion & interpolation disagreed with the true inference obtained using the complete data, suggesting that these two methods would not only lead to biased regression estimates but also generate unreliable t-test results. Conclusions : We recommend the use of multiple imputation in addressing missing values in RHIS datasets. In cases necessary computing resources are unavailable to multiple imputation, one may consider seasonal decomposition as the next best method. Mean imputation and exclusion & interpolation, however, always produced biased and misleading results in the subsequent analyses, and thus their use in the handling of missing values should be discouraged. Keywords : Missing Data; Routine Health Information Systems (RHIS); Health Management Information System (HMIS); Health Services Research; Low and middle-income countries (LMICs); Multiple imputation

scholarly journals Using Routine Health Information Data for Research in Low- and Middle-Income Countries: A Systematic Review

2020 ◽  
Author(s):  
Yuen Wai Hung ◽  
Klesta Hoxha ◽  
Bridget R. Irwin ◽  
Michael R. Law ◽  
Karen Ann Grépin
Keyword(s):  
Systematic Review ◽  
Information System ◽  
Health Information ◽  
Health Information System ◽  
Sub Saharan Africa ◽  
Health Conditions ◽  
Health Management Information System ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

Abstract Background: Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications. Methods: Using terms ‘routine health information system’, ‘health information system’, or ‘health management information system’ and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 20 2019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form.Results: We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last five years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored. Conclusions: Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems.

scholarly journals Using Routine Health Information Data for Research in Low- and Middle-Income Countries: A Systematic Review

2020 ◽  
Author(s):  
Yuen Wai Hung ◽  
Klesta Hoxha ◽  
Bridget R. Irwin ◽  
Michael R. Law ◽  
Karen Ann Grépin
Keyword(s):  
Systematic Review ◽  
Information System ◽  
Health Information ◽  
Health Information System ◽  
Sub Saharan Africa ◽  
Health Conditions ◽  
Health Management Information System ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

Abstract Background : Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications. Methods : Using terms ‘routine health information system’, ‘health information system’, or ‘health management information system’ and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 20 2019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form. Results : We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last five years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored. Conclusions : Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems.

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2020 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically.Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2019 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

scholarly journals Health information system as an integral component of cardiovascular surveillance system in Nepal

2019 ◽  
Vol 16 (1) ◽  
pp. 7-10
Author(s):  
Sahadeb Prasad Dhungana ◽  
Robin Man Karmacharya ◽  
Prajjwal Pyakurel ◽  
Archana Shrestha ◽  
Abhinav Vaidya
Keyword(s):  
Information System ◽  
Health Information ◽  
Swot Analysis ◽  
Health Management ◽  
Care Delivery ◽  
Health Information System ◽  
Health Care Delivery System ◽  
Health Management Information System ◽  
District Health ◽  
Public And Private

Introduction: Nepal lacks a comprehensive, integrated health information system (HIS) to address the growing burden of cardiovascular diseases (CVDs).  Method: We performed a literature search and reviewed papers, government reports, and websites related to HIS. We included existing situations of HIS, major gaps, strength weakness opportunity threat (SWOT) analysis and role of different stakeholders to address CVD burden in Nepal. Results: Health data from different health facility level are filled in district health information software (DHIS-2). DHIS-2 has been implemented in 10 districts in full-fledged manner and partial phase in 22 districts. Data are collected by means of paper-based registers, tally sheets, and monthly data collation forms. The collated data are sent monthly to the district level and entered into the computer using DHIS-2 software and submitted to the national health departments. Major gaps in health management information system (HMIS) are lack of separate heading of CVDs and lack of implementation of the existing data collection system. The strengths of the HIS are robust and decentralized health care delivery system in a good number of medical institutions. Weakness is lack of public and private partnership, concrete policy on health information and dissemination. Opportunities are the existence of policies and regulations mandating health facilities to report indicators, the involvement of private institutions and the expansion of existing DHIS-2 system.  Conclusion: Nepal currently lacks reliable and accurate data on timely manner to address the growing burden of CVDs. There is a need to strengthen the existing DHIS with a commitment from expertise and leadership.

Integration of the UNHCR Refugee Health Information System into the National Health Information Management System for Uganda

2019 ◽  
pp. 183335831988781
Author(s):  
Caroline Kyozira ◽  
Catherine Kabahuma ◽  
Jamiru Mpiima
Keyword(s):  
Information System ◽  
Data Management ◽  
Health Information ◽  
National Health ◽  
Health Management ◽  
Health Information System ◽  
Health Data ◽  
Refugee Health ◽  
Health Management Information System ◽  
District Health

Background: The Uganda Government, together with development partners, has provided continuing support services (including protection, food, nutrition, healthcare, water and sanitation) to refugee-hosting Districts to successfully manage refugees from different neighbouring countries in established settlements. This service has increased the need for timely and accurate information to facilitate planning, resource allocation and decision-making. Complexity in providing effective public health interventions in refugee settings coupled with increased funding requirements has created demands for better data and improved accountability. Health data management in refugee settings is faced with several information gaps that require harmonisation of the Ugandan National Health Management Information System (UHMIS) and United Nations High Commission for Refugees (UNHCR) Refugee Health Information System (RHIS). This article discusses the rationale for harmonisation of the UNHCR RHIS, which currently captures refugee data, with the UHMIS. It also provides insights into how refugee health data management can be harmonised within a country’s national health management information system. Method: A consultative meeting with various stakeholders, including the Ugandan Ministry of Health, district health teams, representatives from UNHCR, the United Nations Children Education Fund (UNICEF), United States Government and civil society organisations, was held with an aim to review the UHMIS and UNHCR RHIS health data management systems and identify ways to harmonise the two to achieve an integrated system for monitoring health service delivery in Uganda. Results: Several challenges facing refugee-hosting district health teams with regard to health data management were identified, including data collection, analysis and reporting. There was unanimous agreement to prioritise an integrated data management system and harmonisation of national refugee stakeholder data requirements, guided by key recommendations developed at the meeting. Conclusion: This article outlines a proposed model that can be used to harmonise the UNHCR RHIS with the UHMIS. The national refugee stakeholder data requirements have been harmonised, and Uganda looks forward to achieving better health data quality through a more comprehensive national UHMIS to inform policy planning and evidence-based decision-making.

scholarly journals Utilization of Health Management Information System and Associated Factors in Hadiya Zone Health Centers, Southern Ethiopia

2016 ◽  
Vol 1 (2) ◽  
pp. 98 ◽  
Author(s):  
Ermias Abera ◽  
Kidist Daniel ◽  
Taye Letta ◽  
Desalegn Tsegaw
Keyword(s):  
Information System ◽  
Health Information ◽  
Management Information System ◽  
Health Management ◽  
Health Information System ◽  
Health Centers ◽  
Southern Ethiopia ◽  
Health Management Information System ◽  
Management Information ◽  
Key Indicators

<p><strong><em>Background:</em></strong><em> Health Information systems are increasingly important for measuring and </em><em>improving the quality and coverage of health services. Reliable and timely health information </em><em>is vital for operational and strategic decision making that save lives and enhances health. In Ethiopia information quality and use remain weak, particularly at district health offices and </em><em>primary health care facilities to facilitate decision making. Therefore this study will be designed to greatly signal the current status of Health Management Information System (HMIS) in study area.</em></p><p><strong><em>Objective:</em></strong><em> </em><em>To assess the utilization of health management information systems and associated factors at health centers in Hadiya zone, </em><em>Southern Ethiopia, 2014.</em></p><p><strong><em>Methods:</em></strong><em> A cross sectional study was conducted in health institutions by interviewing </em><em>units/departments of health centers from </em><em>April to June, 2014. Quantitative data was collected using structured </em><em>questionnaires, check lists, observation and interview guide by trained data collectors. Data </em><em>was analyzed using SPSS version 20 and descriptive and logistic regression analysis was carried out.</em></p><p><strong><em>Results:</em></strong><em> The finding of the study revealed that utilization of health management information was 242(69.3%) in all the study units/departments of health centers. Health center units/department had key indicators (AOR=3.67; 95%CI: 2.11, 6.39), completeness of data format (AOR=3.42; 95%CI: 1.65, 7.08), consistency of data (AOR=1.91; 95%CI: 1.05, 3.48)</em><em> were found to be significantly associated with utilization of health information system at 95% level of significance. </em></p><p class="Default"><strong><em>Conclusion:</em></strong><em> Health center units/departments </em><em>had key indicators, completeness of data and consistency of data were predictors of utilization of health management information</em><em> </em><em>system. Therefore, in-service training and updating of staff involved in Health Management Information System (HMIS) at district, strengthening health information system inputs, timely and concrete feedbacks with establishment of functional Health Management Information System (HMIS).</em></p><strong><em></em></strong>

scholarly journals Using Routine Health Information Data for Research in Low- and Middle-Income Countries: A Systematic Review

2020 ◽  
Author(s):  
Yuen Wai Hung ◽  
Klesta Hoxha ◽  
Bridget R. Irwin ◽  
Michael R. Law ◽  
Karen Ann Grépin
Keyword(s):  
Systematic Review ◽  
Information System ◽  
Health Information ◽  
Health Information System ◽  
Health Conditions ◽  
Health Management Information System ◽  
Time Data ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

Abstract Background: Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years and the growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications. Methods: Using terms ‘routine health information system’, ‘health information system’, or ‘health management information system’ and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 20 2019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed based on pre-determined eligibility criteria. Identified characteristics were extracted using a piloted data extraction form. Results: We identified 132 studies that met our inclusion criteria in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan African countries and were published in the last five years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored. Conclusions: Our study identified an increasing use of RHIS data in research with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessment of services, and epidemiology in LMICs. RHIS data represent an underused source of data and should be further embraced by the research community to gain insights from LMIC health systems.

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