The Experts below are selected from a list of 521337 Experts worldwide ranked by ideXlab platform

Lisa R Hirschhorn - One of the best experts on this subject based on the ideXlab platform.

  • toward utilization of data for Program Management and evaluation quality assessment of five years of health Management information system data in rwanda
    Global Health Action, 2014
    Co-Authors: Marie Paul Nisingizwe, Paulin Basinga, Lisa R Hirschhorn, Hari S Iyer, Modeste Gashayija, Cheryl Amoroso, Randy Wilson, Eric Rubyutsa, Eric Gaju, A Muhire
    Abstract:

    Background : Health data can be useful for effective service delivery, decision making, and evaluating existing Programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health Management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda’s HMIS data over a 5-year period. Methods : The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. Results : Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% ( p <0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications : Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data. Keywords: health Management information system; global health; data quality; quality improvement; data use; Rwanda (Published: 19 November 2014) Citation: Glob Health Action 2014, 7 : 25829 - http://dx.doi.org/10.3402/gha.v7.25829

  • utilizing community health worker data for Program Management and evaluation systems for data quality assessments and baseline results from rwanda
    Social Science & Medicine, 2013
    Co-Authors: Tisha Mitsunaga, Bethany L Hedtgauthier, Elias Ngizwenayo, Didi Bertrand Farmer, Adolphe Karamaga, Peter Drobac, Paulin Basinga, Lisa R Hirschhorn
    Abstract:

    Community health workers (CHWs) have and continue to play a pivotal role in health services delivery in many resource-constrained environments. The data routinely generated through these Programs are increasingly relied upon for providing information for Program Management, evaluation and quality assurance. However, there are few published results on the quality of CHW-generated data, and what information exists suggests quality is low. An ongoing challenge is the lack of routine systems for CHW data quality assessments (DQAs). In this paper, we describe a system developed for CHW DQAs and results of the first formal assessment in southern Kayonza, Rwanda, May–June 2011. We discuss considerations for other Programs interested in adopting such systems. While the results identified gaps in the current data quality, the assessment also identified opportunities for strengthening the data to ensure suitable levels of quality for use in Management and evaluation.

Peter Drobac - One of the best experts on this subject based on the ideXlab platform.

  • utilizing community health worker data for Program Management and evaluation systems for data quality assessments and baseline results from rwanda
    Social Science & Medicine, 2013
    Co-Authors: Tisha Mitsunaga, Bethany L Hedtgauthier, Elias Ngizwenayo, Didi Bertrand Farmer, Adolphe Karamaga, Peter Drobac, Paulin Basinga, Lisa R Hirschhorn
    Abstract:

    Community health workers (CHWs) have and continue to play a pivotal role in health services delivery in many resource-constrained environments. The data routinely generated through these Programs are increasingly relied upon for providing information for Program Management, evaluation and quality assurance. However, there are few published results on the quality of CHW-generated data, and what information exists suggests quality is low. An ongoing challenge is the lack of routine systems for CHW data quality assessments (DQAs). In this paper, we describe a system developed for CHW DQAs and results of the first formal assessment in southern Kayonza, Rwanda, May–June 2011. We discuss considerations for other Programs interested in adopting such systems. While the results identified gaps in the current data quality, the assessment also identified opportunities for strengthening the data to ensure suitable levels of quality for use in Management and evaluation.

Paulin Basinga - One of the best experts on this subject based on the ideXlab platform.

  • toward utilization of data for Program Management and evaluation quality assessment of five years of health Management information system data in rwanda
    Global Health Action, 2014
    Co-Authors: Marie Paul Nisingizwe, Paulin Basinga, Lisa R Hirschhorn, Hari S Iyer, Modeste Gashayija, Cheryl Amoroso, Randy Wilson, Eric Rubyutsa, Eric Gaju, A Muhire
    Abstract:

    Background : Health data can be useful for effective service delivery, decision making, and evaluating existing Programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health Management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda’s HMIS data over a 5-year period. Methods : The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. Results : Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% ( p <0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications : Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data. Keywords: health Management information system; global health; data quality; quality improvement; data use; Rwanda (Published: 19 November 2014) Citation: Glob Health Action 2014, 7 : 25829 - http://dx.doi.org/10.3402/gha.v7.25829

  • utilizing community health worker data for Program Management and evaluation systems for data quality assessments and baseline results from rwanda
    Social Science & Medicine, 2013
    Co-Authors: Tisha Mitsunaga, Bethany L Hedtgauthier, Elias Ngizwenayo, Didi Bertrand Farmer, Adolphe Karamaga, Peter Drobac, Paulin Basinga, Lisa R Hirschhorn
    Abstract:

    Community health workers (CHWs) have and continue to play a pivotal role in health services delivery in many resource-constrained environments. The data routinely generated through these Programs are increasingly relied upon for providing information for Program Management, evaluation and quality assurance. However, there are few published results on the quality of CHW-generated data, and what information exists suggests quality is low. An ongoing challenge is the lack of routine systems for CHW data quality assessments (DQAs). In this paper, we describe a system developed for CHW DQAs and results of the first formal assessment in southern Kayonza, Rwanda, May–June 2011. We discuss considerations for other Programs interested in adopting such systems. While the results identified gaps in the current data quality, the assessment also identified opportunities for strengthening the data to ensure suitable levels of quality for use in Management and evaluation.

Tisha Mitsunaga - One of the best experts on this subject based on the ideXlab platform.

  • utilizing community health worker data for Program Management and evaluation systems for data quality assessments and baseline results from rwanda
    Social Science & Medicine, 2013
    Co-Authors: Tisha Mitsunaga, Bethany L Hedtgauthier, Elias Ngizwenayo, Didi Bertrand Farmer, Adolphe Karamaga, Peter Drobac, Paulin Basinga, Lisa R Hirschhorn
    Abstract:

    Community health workers (CHWs) have and continue to play a pivotal role in health services delivery in many resource-constrained environments. The data routinely generated through these Programs are increasingly relied upon for providing information for Program Management, evaluation and quality assurance. However, there are few published results on the quality of CHW-generated data, and what information exists suggests quality is low. An ongoing challenge is the lack of routine systems for CHW data quality assessments (DQAs). In this paper, we describe a system developed for CHW DQAs and results of the first formal assessment in southern Kayonza, Rwanda, May–June 2011. We discuss considerations for other Programs interested in adopting such systems. While the results identified gaps in the current data quality, the assessment also identified opportunities for strengthening the data to ensure suitable levels of quality for use in Management and evaluation.

A Muhire - One of the best experts on this subject based on the ideXlab platform.

  • toward utilization of data for Program Management and evaluation quality assessment of five years of health Management information system data in rwanda
    Global Health Action, 2014
    Co-Authors: Marie Paul Nisingizwe, Paulin Basinga, Lisa R Hirschhorn, Hari S Iyer, Modeste Gashayija, Cheryl Amoroso, Randy Wilson, Eric Rubyutsa, Eric Gaju, A Muhire
    Abstract:

    Background : Health data can be useful for effective service delivery, decision making, and evaluating existing Programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health Management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda’s HMIS data over a 5-year period. Methods : The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. Results : Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% ( p <0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications : Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data. Keywords: health Management information system; global health; data quality; quality improvement; data use; Rwanda (Published: 19 November 2014) Citation: Glob Health Action 2014, 7 : 25829 - http://dx.doi.org/10.3402/gha.v7.25829