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 ◽  
Program Effectiveness ◽  
National Level ◽  
Digital Data ◽  
Quality Data ◽  
Health Management Information System ◽  
District Health ◽  
Implementation Framework

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy.In 2009 Bangladesh’s health management information system (HMIS) adopted the District Health Information Software, Version 2 (DHIS2) to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality and reporting. We aimed to understand the facilitators and barriers to implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal, newborn, child, and adolescent health (RMNCAH) 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 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 technology among staff. Quality checks and feedback loops at multiple levels of data gathering points are helpful for minimizing data errors. Introducing a dashboard makes DHIS2 compatible to use as a monitoring tool. Barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to DHIS2 versions, and maintaining both manual and electronic system side-by-side. The data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel HMIS 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 a responsive HMIS. 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 ◽  
Health Information ◽  
Program Effectiveness ◽  
National Level ◽  
Digital Data ◽  
Quality Data ◽  
Health Management Information System ◽  
District Health ◽  
Frequent Change ◽  
Implementation Framework

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh Health Management information System (HMIS) has adopted District Health Information software 2 (DHIS) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aim to understand the facilitators and barriers on implementing DHIS2 as a way to retrieve meaningful and accurate data for the Reproductive, Maternal and Child Health (RMCAH) services. Methods: This qualitative study was done among two districts of Bangladesh from September 2017 to 2018. Data collection method were key informant interview (n=11); in-depth interview (n=23); focus group discussion (n=2). Study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. Results: DHIS 2could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support and positive attitude of staffs. Quality checks and feedback loops at multiple levels of data gathering points was helpful to minimize data errors. Introducing dashboard makes the DHIS2 compatible to use as monitoring tool. However, the barriers to DHIS 2 implementation were lack of human resources, slow Internet connectivity, and frequent change of DHIS 2 versions, maintaining both manual and electronic system side by side. The collected data remains incomplete as private health facilities are not covered. The parallel presence of two MISs to report same RMNCAH indicators is a threat to achieve quality data and increases workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS 2 implementation and building responsive HMIS. To sustain the achievements of digital data culture, focused strategic direction is needed. Periodic refresher trainings, incentives for increased performance, 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 DHIS 2 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 ◽  
Health Information ◽  
Program Effectiveness ◽  
National Level ◽  
Digital Data ◽  
Quality Data ◽  
Health Management Information System ◽  
District Health ◽  
Frequent Change ◽  
Implementation Framework

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh Health Management information System (HMIS) has adopted District Health Information software 2 (DHIS) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aim to understand the facilitators and barriers on implementing DHIS2 as a way to retrieve meaningful and accurate data for the Reproductive, Maternal and Child Health (RMCAH) services. Methods: This qualitative study was done among two districts of Bangladesh from September 2017 to 2018. Data collection method were key informant interview (n=11); in-depth interview (n=23); focus group discussion (n=2). Study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. Results: DHIS 2could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support and positive attitude of staffs. Quality checks and feedback loops at multiple levels of data gathering points was helpful to minimize data errors. Introducing dashboard makes the DHIS2 compatible to use as monitoring tool. However, the barriers to DHIS 2 implementation were lack of human resources, slow Internet connectivity, and frequent change of DHIS 2 versions, maintaining both manual and electronic system side by side. The collected data remains incomplete as private health facilities are not covered. The parallel presence of two MISs to report same RMNCAH indicators is a threat to achieve quality data and increases workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS 2 implementation and building responsive HMIS. To sustain the achievements of digital data culture, focused strategic direction is needed. Periodic refresher trainings, incentives for increased performance, 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 DHIS 2 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

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.

Quality of Routine Health Information System Data and Associated Factors Among Departments in Public Health Facilities of Harari Region, Ethiopia

2021 ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background: Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia.Methods: A cross-sectional study was conducted in all public health facilities in Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation check-lists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P-value <0.05. Result: The study found a good quality data in 51.35% (95% CI, 44.6-58.1) of the departments in public health facilities in Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to departments found in the health posts. The presence of trained staffs able to fill reporting formats (AOR=2.474; 95%CI: 1.124-5.445) and provision of feedback (AOR=3.083; 95%CI: 1.549-6.135) were also significantly associated with data quality. Conclusion: The level of good data quality in the public health facilities was less than the expected national level. Training should be provided to increase the knowledge and skills of the health workers.

scholarly journals Implementing the routine immunisation data module and dashboard of DHIS2 in Nigeria, 2014–2019

2020 ◽  
Vol 5 (7) ◽  
pp. e002203
Author(s):  
Faisal Shuaib ◽  
Abdullahi Bulama Garba ◽  
Emmanuel Meribole ◽  
Samuel Obasi ◽  
Adamu Sule ◽  
...  
Keyword(s):  
Information System ◽  
Real Time ◽  
National Level ◽  
Health Management Information System ◽  
Government Ownership ◽  
Time Data ◽  
District Health ◽  
Routine Immunisation ◽  
Real Time Data ◽  
The Government

In 2010, Nigeria adopted the use of web-based software District Health Information System, V.2 (DHIS2) as the platform for the National Health Management Information System. The platform supports real-time data reporting and promotes government ownership and accountability. To strengthen its routine immunisation (RI) component, the US Centers for Disease Control and Prevention (CDC) through its implementing partner, the African Field Epidemiology Network-National Stop Transmission of Polio, in collaboration with the Government of Nigeria, developed the RI module and dashboard and piloted it in Kano state in 2014. The module was scaled up nationally over the next 4 years with funding from the Bill & Melinda Gates Foundation and CDC. One implementation officer was deployed per state for 2 years to support operations. Over 60 000 RI healthcare workers were trained on data collection, entry and interpretation and each local immunisation officer in the 774 local government areas (LGAs) received a laptop and stock of RI paper data tools. Templates for national-level and state-level RI bulletins and LGA quarterly performance tools were developed to promote real-time data use for feedback and decision making, and enhance the performance of RI services. By December 2017, the DHIS2 RI module had been rolled out in all 36 states and the Federal Capital Territory, and all states now report their RI data through the RI Module. All states identified at least one government DHIS2 focal person for oversight of the system’s reporting and management operations. Government officials routinely collect RI data and use them to improve RI vaccination coverage. This article describes the implementation process—including planning and implementation activities, achievements, lessons learnt, challenges and innovative solutions—and reports the achievements in improving timeliness and completeness rates.

scholarly journals Data for decision making: using a dashboard to strengthen routine immunisation in Nigeria

2018 ◽  
Vol 3 (5) ◽  
pp. e000807 ◽  
Author(s):  
Sulaiman Etamesor ◽  
Chibuzo Ottih ◽  
Ismail Ndalami Salihu ◽  
Arnold Ikedichi Okpani
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Workers ◽  
Health Information System ◽  
Routine Data ◽  
Health Management Information System ◽  
District Health ◽  
Implementation Framework ◽  
Routine Immunisation ◽  
Management Platform

Availability of reliable data has for a long time been a challenge for health programmes in Nigeria. Routine immunisation (RI) data have always been characterised by conflicting coverage figures for the same vaccine across different routine data reporting platforms.Following the adoption of District Health Information System version 2 (DHIS2) as a national electronic data management platform, the DHIS2 RI Dashboard Project was initiated to address the absence of some RI-specific indicators on DHIS2. The project was also intended to improve visibility and monitoring of RI indicators as well as strengthen the broader national health management information system by promoting the use of routine data for decision making at all governance levels. This paper documents the process, challenges and lessons learnt in implementing the project in Nigeria.A multistakeholder technical working group developed an implementation framework with clear preimplementation; implementation and postimplementation activities. Beginning with a pilot in Kano state in 2014, the project has been scaled up countrywide.Nearly 34 000 health workers at all administrative levels were trained on RI data tools and DHIS2 use. The project contributed to the improvement in completeness of reports on DHIS2 from 53 % in first quarter 2014 to 81 % in second quarter 2017.The project faced challenges relating to primary healthcare governance structures at the subnational level, infrastructure and human resource capacity. Our experience highlights the need for early and sustained advocacy to stakeholders in a decentralised health system to promote ownership and sustainability of a centrally coordinated systems strengthening initiative.

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 Assessment of quality of routine health information system data and associated factors among departments in public health facilities of Harari region, Ethiopia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera Abaerei ◽  
Teferi Gebru Gebremeskel ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia. Methods A cross-sectional study was conducted in all public health facilities in the Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation checklists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P value < 0.05. Result The study found good quality data in 51.35% (95% CI 44.6–58.1) of the departments in public health facilities in the Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to those found in the health posts. The presence of trained staffs able to fill reporting formats (AOR = 2.474; 95% CI 1.124–5.445) and provisions of feedbacks (AOR = 3.083; 95% CI 1.549–6.135) were also significantly associated with data quality. Conclusion The level of good data quality in the public health facilities was less than the expected national level. Lack of trained personnel able to fill the reporting format and feedback were the factors that are found to be affecting data quality. Therefore, training should be provided to increase the knowledge and skills of the health workers. Regular supportive supervision and feedback should also be maintained.

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