A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches

Leonard King’Wara

doi:10.11648/j.cmr.20160504.11

Abstract

Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.

Highlights

There are indications that healthcare service delivery is still weak due to lack of accurate and credible data to inform essential health products supply and this has continued to cost lives [1] especially among children at risk of HIV injuries
The Early Infant Diagnosis (EID) program, which is one of the several health programs aimed at monitoring the impact of PMTCT (Prevention of Mother to Child Transmission) is among the health information systems characterized by incoherent and incomplete data [4]
Eligibility criteria included a child who has attended the respective facility for EID services between the month of May and August 2012, below 18 months of age and a health care worker dealing with EID services between the periods of the study

Summary

Introduction

There are indications that healthcare service delivery is still weak due to lack of accurate and credible data to inform essential health products supply and this has continued to cost lives [1] especially among children at risk of HIV injuries. The Early Infant Diagnosis (EID) program, which is one of the several health programs aimed at monitoring the impact of PMTCT (Prevention of Mother to Child Transmission) is among the health information systems characterized by incoherent and incomplete data [4] This has forced most decision makers to use approximation and at times guesswork leading to inadequate allocation, over allocation or wastage of resources that would have otherwise been channeled towards other important livelihood factors [3]. As a result of inaccurate health records, the Kenyan government invested heavily in the pharmaceuticals but failed to invest in non-pharmaceuticals in 2006 due to lack of funds putting patient care in jeopardy [3] This buttress the fact that about 75% of patients and health care providers considered the data records within the health facilities to be fragmented, convoluted, and plagued by duplication of effort, poor communication and conflicting advice [2]. These inefficiencies have resulted in double digit inflation of cost of health care worldwide making it almost impossible for an individual or even governments to provide health services adequately to its citizenry [5]

Objectives

Methods

Results