Abstract

BackgroundHealth Information System is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it.MethodA cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The single population proportion formula was applied to estimate the sample size taking into account the proportion of data use 0.69, margin of error 0.05, and the critical value 1.96 at the 95% CI. The final sample size was estimated at 394 by considering 1.5 as a design effect and 5% non-response. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p value < 0.05 were considered as predictors of routine health information system use.ResultProportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR = 12.42, 95% CI [5.52, 27.98]) and performance (AOR = 1.68; 95% CI [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR = 2.29; 95% CI [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR = 3.53; 95% CI [1.61, 7.75]), receiving senior management directives (AOR = 3.56; 95% CI [1.76, 7.19]), supervision (AOR = 2.84; 95% CI [1.33, 6.07]), using HMIS data for target setting (AOR = 3.43; 95% CI [1.66, 7.09]), and work location (AOR = 0.16; 95% CI [0.07, 0.39]) were organizational (level-2) explanatory variables.ConclusionThe proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.

Highlights

  • Health Information System is the key to making evidence-based decisions

  • The Health Management Information System (HMIS) was one of the seven components of the Health Sector Development Program-III (HSDPIII) and is one of the four transformation agendas (Information Revolution) that the country has formulated in its Health Sector Transformation Plan (HSTP), 2015–2019

  • Revising key performance monitoring indicators, standardizing data recording and reporting tools, conducting capacity building training, implementing electronic Medical records, introducing District Health Information System (­DHIS2), and installing SMART care at health facility levels were some of the efforts exerted among others [5,6,7]

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Summary

Introduction

Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. Health Information System (HIS) is the basis of the health system and the key to making evidence-based health policy decisions [1]. Ethiopia has implemented the Health Management Information System (HMIS) since 2008 to collect routine data as a primary source of information in public and private facilities [5]. Revising key performance monitoring indicators, standardizing data recording and reporting tools, conducting capacity building training, implementing electronic Medical records (eMR), introducing District Health Information System (­DHIS2), and installing SMART care at health facility levels were some of the efforts exerted among others [5,6,7]

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