The Use of Data for Planning and Services Improvement in Tanzanian Primary Healthcare Facilities: Experience from Star Rating Assessment

Abstract

Background: The use of data for planning and improving healthcare delivery is sub-optimal among developing countries. In 2015, Tanzania started to implement the Star Rating Assessment (SRA) process for Primary Health Care (PHC) facilities to improve various dimensions of quality of services, including the use of data. We aimed at assessing the extent and predictors of data use in Tanzanian PHC facilities. Methods: We used the most current national SRA data available in DHIS2 that was collected in 2017/2018 from all 7289 PHC facilities. A facility was considered using data if gained 80% of the allocated scores. Other dependent variables were the three components that together contribute to the use of data (If PHC facility has Health Management Information Systems (HMISs) functional, disseminates information, and has proper medical records). We determined the association between data use and facility ownership status (public or private), location of the facility (rural or urban), gender of the facility in charge, and facility service level (dispensary, health centre, or hospital). Results are presented as proportions of facilities that

Electronic medical record systems data use in decision-making and associated factors among health managers at public primary health facilities, Dodoma region: a cross-sectional analytical study

“…A study conducted in Tanzania on paper-based HMIS data use in decision-making revealed that about 56.9% of the facilities had functional HMIS, 18% of the facilities had used their data for planning and services improvement, 26.3% had disseminated data, and about 9.1% of the facilities had proper medical records. The level of the facility was associated with the use of data, with hospitals and health centers showing higher use ( 15 ). Another study ( 16 ) on paper-based data use in decision-making revealed that 60% of the respondents reported using HMIS data in decision-making, of which data was most used to compare service coverage (53%).…”

Determinants of COVID-19 data quality in the District Health Information Management System version 2 in Ahafo Region, Ghana

“…Similarly, as of May 1, 2020, the United States of America lacked a standardized system for COVID-19 data reporting, leading to significant discrepancies in data quality among different states and counties (8,10). Although there is no perfect health data due to missing values, bias, measurement, transcription, and human entry errors, most of these data problems chiefly occur in developing countries (11–14). Poor data quality in the health sector can be attributed to various factors, including inadequate training of data managers and healthcare staff, limited access to resources such as technology and reporting tools, and data fragmentation due to disparate systems (2,11,15,16).…”

Improvements in Obstetric and Newborn Health Information Documentation following the Implementation of the Safer Births Bundle of Care at 30 Facilities in Tanzania

“…In Tanzania, facility-based routine medical records [17,18] are abstracted from the facility registers and uploaded into the national health information database, namely, the district health information system (DHIS-2) [19]. However, the system faces data quality challenges including low accuracy, poor reliability, incomplete records, and delayed data registration [13,17].…”

“…This study is nested within the implementation of a three-year continuous quality improvement (CQI) project, the "Safer Births Bundle of Care" (SBBC) project [20]. The rollout in 30 healthcare facilities in five regions is led by Haydom Lutheran Hospital in close collaboration with the Ministry of Health and UNICEF in Tanzania [9][10][11][12][13][14][15][16][17][18][19][20][21][22]. During the implementation of the SBBC package, it has become clear that data are not always captured as intended and as needed, compromising their potential to guide improvement.…”