Enhancing health facility-based data quality and use for decision making at primary health care units to improve health service delivery of maternal newborn child and adolescent health, Tigray Ethiopia 2018

Abstract

Objective: information use is fundamental for evidence based decision making but data quality and information use in health facility is limited in low and middle income countries. Therefore, a facility based cross sectional using mixed approach was conducted to assess data quality and use for decision making in 12 selected health facilities of Tigray, Ethiopia, 2018. Results: District Health Information System 2 (DHIS2) software was practiced in 12 of the facilities. Completeness and consistency rate of register and reports was 53.5%, 56.3%, and 38.9%. Respectively. The lot of quality assurance system of service and disease report was 7(61.1%). The performance monitoring team is established decision-making rate on key coverage indicators was 42.9%. Comparisons of performance in a district /national targets were 5(41.5a high rate of incompleteness, inconsistencies, low lots of data assurance and low use of data for decision making. Therefore, DHIS2 tool needs to be used to generate a report, use data and disseminating platforms both inside and outside health facilities using the website and other channels.

The quality of health data before and after the implementation of the electronic health management information system for the fistula program in Tanzania

“…Generally, the study findings indicate that the quality of data collected manually in paper based and reported in HIS was poor as compared to the data collected directly using the current electronic system. These findings support evidence from previous observations which showed that the quality of HIS data gathering and reporting was poor in low and middle income countries (Assefa Ayalew et al, 2020;Begum et al, 2020;Manya & Nielsen, 2016;Ouedraogo et al, 2019) when using the paper system as compared to using the electronic system. Indications are that inadequate information may be available for decision-making purposes at the health facility if data are collected using paper based systems.…”

“…Another study reported that the completeness rate of register and reports was 53.5%, and 56.3% respectively, and the overall consistency rate was 38.9% (Assefa Ayalew et al, 2020). Furthermore, another study on antenatal care fourth visit, postnatal care, fully immunized and total malaria revealed the most inaccurate data elements (Endriyas et al, 2019).…”

“…In Ethiopia, it was revealed that the documentation completion rate significantly increased from 46.48% pre‐intervention to 78.6% after the staff training and development of new clinical forms (Getahun, 2018). Another study reported that the completeness rate of register and reports was 53.5%, and 56.3% respectively, and the overall consistency rate was 38.9% (Assefa Ayalew et al, 2020). Furthermore, another study on antenatal care fourth visit, postnatal care, fully immunized and total malaria revealed the most inaccurate data elements (Endriyas et al, 2019).…”

“…With the paper‐based system of data collection, it is difficult to attain the required standards of data quality (Kikoba et al, 2019a). However, the research shows that the quality of HIS data gathering and reporting in a health facility is often poor in low and middle‐income countries (Assefa Ayalew et al, 2020; Begum et al, 2020; Manya & Nielsen, 2016; Ouedraogo et al, 2019). According to Mashoufi et al (2019) it was found that that the data quality in emergency medical services was not at a high level, with the following ratings: sound data (6.23), dependable data (6.28), useful data (6.30), and usable data (6.35) in Iran, with 0 being the lowest possible score and 10 being the highest.…”

Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study

“… 23 24 While inadequate knowledge of RHIS is a cross-cutting issue, it proved more problematic at lower levels of the health system, where data are generated. Other studies report that not understanding indicators 25 and poor competency in recording 26 affect data quality.…”