Polio Data Quality Improvement in the African Region

The polio Eradication Initiative (PEI) is one of the most important public health interventions in Africa. Quality data is necessary to monitor activities and key performance indicators and access year by year progress made. This process has been possible with a solid polio health information system that has been consolidated over the years. This study describes the whole process to have data for decision making. The main components are the data flow, the role of the different levels, data capture and tools, standards and codes, the data cleaning process, the integration of data from various sources, the introduction of innovative technologies, feedback and information products and capacity building. The results show the improvement in the timeliness of reporting data to the next level, the availability of quality data for analysis to monitor key surveillance performance indicators, the output of the data cleaning exercise pointing out data quality gaps, the integration of data from various sources to produce meaningful outputs and feedback for information dissemination. From the review of the process, it is observed an improvement in the quality of polio data resulting from a well-defined information system with standardized tools and Standard Operating Procedures (SOPs) and the introduction of innovative technologies. However, there is room for improvement; for example, multiple data entries from the field to the surveillance unit and the laboratory. Innovative technologies are implemented for the time being in areas hard to reach due to the high cost of the investment. A strong information system has been put in place from the community level to the global level with a link between surveillance, laboratory and immunization coverage data. To maintain standards in Polio Information system, there is need for continuous training of the staff on areas of surveillance, information systems, data analysis and information sharing. The use of innovative technologies on web-based system and mobile devices with validation rules and information check will avoid multiple entries.

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

10.21203/rs.3.rs-576218/v1 ◽

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.

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Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

10.21203/rs.2.21463/v2 ◽

2020 ◽

Author(s):

Brian Bongwong Tamfon ◽

Chanceline Bilounga Ndongo ◽

Serge Marcial Bataliack ◽

Marie Nicole Ngoufack ◽

Georges Nguefack-Tsague

Keyword(s):

Decision Making ◽

Information System ◽

Health Information ◽

Information Dissemination ◽

Health Sector ◽

Health Information System ◽

Health Facilities ◽

World Health ◽

Quality Data ◽

Health Related

Abstract Background: Management of health data and its use for informed decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods: A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results: A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions: The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

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Routine health information system in the health facilities in Yaoundé–Cameroon: assessing the gaps for strengthening

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-020-01351-3 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Brian Bongwong Tamfon ◽

Chanceline Bilounga Ndongo ◽

Serge Marcial Bataliack ◽

Marie Nicole Ngoufack ◽

Georges Nguefack-Tsague

Keyword(s):

Decision Making ◽

Information System ◽

Health Information ◽

Information Dissemination ◽

Health Sector ◽

Health Information System ◽

Health Facilities ◽

World Health ◽

Quality Data ◽

Health Related

Abstract Background Management of health data and its use for informed-decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a routine health information system (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results A total of 111 HFs were selected for the study. Respondents aged 24–60 years with an average of 38.3 ± 9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7 and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

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Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

10.21203/rs.2.21463/v1 ◽

2020 ◽

Author(s):

Brian Bongwong Tamfon ◽

Chanceline Bilounga Ndongo ◽

Serge Marcial Bataliack ◽

Marie Nicole Ngoufack ◽

Georges Nguefack-Tsague

Keyword(s):

Decision Making ◽

Information System ◽

Health Information ◽

Information Dissemination ◽

Health Sector ◽

Health Information System ◽

Health Facilities ◽

World Health ◽

Quality Data ◽

Health Related

Abstract Background Management of health data and its use for informed decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

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

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01651-2 ◽

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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Routine Health Information System in the Health Facilities in Yaoundé-Cameroon: Assessing the Gaps for Strengthening

10.21203/rs.2.21463/v3 ◽

2020 ◽

Author(s):

Brian Bongwong Tamfon ◽

Chanceline Bilounga Ndongo ◽

Serge Marcial Bataliack ◽

Marie Nicole Ngoufack ◽

Georges Nguefack-Tsague

Keyword(s):

Decision Making ◽

Information System ◽

Health Information ◽

Information Dissemination ◽

Health Sector ◽

Health Information System ◽

Health Facilities ◽

World Health ◽

Quality Data ◽

Health Related

Abstract Background: Management of health data and its use for informed-decision making is a challenging health sector aspect in developing countries. Monitoring and evaluation of health interventions for meeting health-related Sustainable Development Goals (SDGs), and Cameroon Health Sector Strategy (HSS) targets is facilitated through evidence-based decision-making and public health action. Thus, a Routine Health Information System (RHIS) producing quality data is imperative. The objective of this study was to assess the RHIS in the health facilities (HFs) in Yaoundé in order to identify gaps and weaknesses and to propose measures for strengthening. Methods: A health facility-based cross-sectional descriptive study was carried out in the six health districts (HDs) of Yaoundé; followed by a qualitative aspect consisting of in-depth interviews of key informants at the Regional Health Office. HFs were selected using a stratified sampling method with probability proportional to the size of each HD. Data were collected (one respondent per HF) using the World Health Organization (WHO) and MEASURE Evaluation RHIS rapid assessment tool. Data were entered into Microsoft Excel 2013 and analyzed with IBM-SPSS version 20. Results: A total of 111 HFs were selected for the study. Respondents aged 24-60 years with an average of 38.3±9.3 years; 58 (52.3%) male and 53(47.7%) female. Heads of HFs and persons in charge of statistics/data management were most represented with 45.0% and 21.6% respectively. All the twelve subdomains of the RHIS were adequately functioning at between 7% and 30%. These included Human Resources (7%), Data Analysis (10%), Information and Communication Technology (11%), Standards and System Design (15%), Policies and Planning (15%), Information Dissemination (16%), Data Demand and Use (16%), Management (18%), Data Needs (18%), Data Quality Assurance (20%), Collection and Management of Individual Client Data (26%), Collection, Management, and Reporting of Aggregated Facility Data (30%). Conclusions: The level of functioning of subdomains of the RHIS in Yaoundé was low; thus, immediate and district-specific strengthening actions should be implemented if health-related SDGs and HSS targets are to be met. A nation-wide assessment should be carried out in order to understand the determinants of these poor performances and to strengthen the RHIS.

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Concept and implementation of a single source information system in nuclear medicine for myocardial scintigraphy (SPECT-CT data)

Applied Clinical Informatics ◽

10.4338/aci-2009-12-ra-0017 ◽

2010 ◽

Vol 01 (01) ◽

pp. 50-67 ◽

Cited By ~ 4

Author(s):

K. Rahbar ◽

L. Stegger ◽

M. Schäfers ◽

M. Dugas ◽

S. Herzberg

Keyword(s):

Information System ◽

Data Quality ◽

Medical History ◽

Myocardial Scintigraphy ◽

Research Data ◽

Quality Data ◽

Single Source ◽

Source Information ◽

Documentation System ◽

Ct Data

Summary Objective: Data for clinical documentation and medical research are usually managed in separate systems. We developed, implemented and assessed a documentation system for myocardial scintigraphy (SPECT/CT-data) in order to integrate clinical and research documentation. This paper presents concept, implementation and evaluation of this single source system including methods to improve data quality by plausibility checks. Methods: We analyzed the documentation process for myocardial scintigraphy, especially for collecting medical history, symptoms and medication as well as stress and rest injection protocols. Corresponding electronic forms were implemented in our hospital information system (HIS) including plausibility checks to support correctness and completeness of data entry. Research data can be extracted from routine data by dedicated HIS reports. Results: A single source system based on HIS-electronic documentation merges clinical and scientific documentation and thus avoids multiple documentation. Within nine months 495 patients were documented with our system by 8 physicians and 6 radiographers (466 medical history protocols, 466 stress and 414 rest injection protocols). Documentation consists of 295 attributes, three quarters are conditional items. Data quality improved substantially compared to previous paper-based documentation. Conclusion: A single source system to collect routine and research data for myocardial scintigraphy is feasible in a real-world setting and can generate high-quality data through online plausibility checks.

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