Data assessment tools to monitor and improve data quality and patient care

AuthorsOwengah 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, NairobiPresenter: Owengah Evelyne

Date: 7/2/2014

Background

FACES is a collaboration between KEMRI and UCSF

HIV prevention, care, and treatment programTechnical assistance and capacity building for

comprehensive HIV related servicesPartnerships with MOH, FBOs, NGOs, CBOs, and

private health facilities in Nyanza and Nairobi140 health facilities supported; 138 in Nyanza

and 2 in NairobiFunded by CDC/PEPFAR through a cooperative

agreement

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) sitesData 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

Study Objective

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

Material & Methods

Three assessments introduced to improve data quality between September 2011 – October 2012

1. 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 2011

2. MOH257 Bluecard file audits sampled from EMR and non-EMR sites

Baseline: September 2012

3. 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

Results

Assessment Measure Baseline

6-month Follow up

Percent change

Database queries (fields combined)

87.0% 94.6% (+8%)

Last CD4 67.5% 96.1% (+28%)

WHO Stage 86.9% 96.1% (+9%)

Referral source 94.2% 99.0% (+4%)

Discontinuation reason 88.9% 96.2% (+8%)

EMR Blue card completion

89.4% 94.7% (+5%)

Non-EMR site Blue card completion

79.5% 77.5% (-2%)

EMR data accuracy 99.6% 99.8% (+.2%)

Discussion

Medical record completion improved at EMR sites

Data accuracy remained high at EMR sitesMedical record completion declined

somewhat at non-EMR sites

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

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. President’s 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 President’s Emergency Plan for AIDS Relief (PEPFAR) through the U.S Centers for Disease Control under the terms of Cooperative

Agreement # PS001913

Thank You!

FROM THE FACES TEAM