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Data assessment tools to monitor and improve data quality and patient care Authors Owengah E. 1,2, Kibaara C. 1,2, Blat C. 1,3, Mutegi E. 1,2, Armes M.

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Presentation on theme: "Data assessment tools to monitor and improve data quality and patient care Authors Owengah E. 1,2, Kibaara C. 1,2, Blat C. 1,3, Mutegi E. 1,2, Armes M."— Presentation transcript:

1 Data assessment tools to monitor and improve data quality and patient care Authors Owengah E. 1,2, Kibaara C. 1,2, Blat C. 1,3, Mutegi E. 1,2, Armes M. 1,3, Wafula E. 1,2, Jelagat J. 1,2,Ahomo M. 4, Shade S. 1,3, Lewis-Kulzer J. 1,3 Institutions Family AIDS Care and Education Services (FACES), Kisumu, Kenya Kenya Medical Research Institute (KEMRI), Kisumu, Kenya University of California San Francisco, CA, USA Ministry Of Health, Kenya 4th Annual KASH Conference, Nairobi Presenter: Owengah Evelyne Date: 7/2/2014

2 Background FACES is a collaboration between KEMRI and UCSF HIV prevention, care, and treatment program Technical assistance and capacity building for comprehensive HIV related services Partnerships with MOH, FBOs, NGOs, CBOs, and private health facilities in Nyanza and Nairobi 140 health facilities supported; 138 in Nyanza and 2 in Nairobi Funded by CDC/PEPFAR through a cooperative agreement

3 Introduction Standard processes to assess and ensure for data quality are needed Critical components of data integrity and health outcome monitoring Ensuring medical records are completed well and accurately Data entered accurately at electronic medical record (EMR) sites Data flow at FACES supported sites EMR sites: Patient charts are filled by clinicians and then entered into EMR system by data clerks Non-EMR sites: Patient charts are filled by clinicians

4 Study Objective Evaluate the effectiveness of interventions to improve data quality at electronic medical records (EMR) sites and non-EMR sites

5 Material & Methods Three assessments introduced to improve data quality between September 2011 – October Database queries from EMR sites of 12 key fields related to good patient care E.g. Last CD4 count, WHO disease stage, referral source Baseline: September MOH257 Bluecard file audits sampled from EMR and non-EMR sites Baseline: September Data entry accuracy audits at EMR sites Assessment feedback given to sites monthly Performance results (satisfactory = >95%) Targeted completion protocol reinforcement Baseline: October 2012 Baseline and six month findings were compared to evaluate impact

6 Results Assessment MeasureBaseli ne 6-month Follow up Percent change Database queries (fields combined) 87.0%94.6%(+8%) Last CD467.5%96.1%(+28%) WHO Stage86.9%96.1%(+9%) Referral source94.2%99.0%(+4%) Discontinuation reason88.9%96.2%(+8%) EMR Blue card completion89.4%94.7%(+5%) Non-EMR site Blue card completion 79.5%77.5%(-2%) EMR data accuracy99.6%99.8%(+.2%)

7 Discussion Medical record completion improved at EMR sites Data accuracy remained high at EMR sites Medical record completion declined somewhat at non-EMR sites

8 Conclusion & Recommendations Data quality interventions at EMR sites are yielding positive results, however additional strategies are needed to facilitate better performance at non-EMR sites Kisumu East District Hospital

9 Acknowledgments Kenyan Ministry of Health (MOH) Family AIDS Care and Education Services (FACES) Kenya Medical Research Institute (KEMRI) University of California San Francisco (UCSF) U.S. Presidents Emergency Plan for AIDS Relief (PEPFAR) U.S. Centers for Disease Control and Prevention (CDC) Beth Novey for photographs The women, men and children in the communities served The findings and conclusions in this presentation are those of the author(s) and do not necessarily represent the official position of U.S. Centers for Disease Control and Prevention/the and the Government of Kenya This research has been supported by the Presidents Emergency Plan for AIDS Relief (PEPFAR) through the U.S Centers for Disease Control under the terms of Cooperative Agreement # PS001913

10 Thank You! FROM THE FACES TEAM


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