Use of routine health information for decision making among health care workers in Marsabit county, Kenya

Abstract

Background: In Kenya today, public health facilities at different levels collect a large amount of routine health (RH) data. However, with the introduction of district health information software (DHIS2), recent evidence has shown low levels of data are used by the targeted stockholders in Kenya. The therefore study aims to examine the association of human resource and information technology factors associated with the frequent use of RH data in decision-making among health-workers in Marsabit county.Methods: The study employed a cross-sectional design. Researchers purposively stratified 201 health workers by cadre, then probability proportionate sampling was applied to get the required number from every cadre. Both qualitative and quantitative data were collected and entered into the SPSS software, descriptive measurement and Chi square test were used to analyze the dataResults: The majority (74%) of respondents had basic computer skills but 80% of respondent lacked training in health information management. The study found that training increases the likelihoods of healthcare workers utilizing RH data. The type of software (DHIS2 and MedBoss) in use had a significant association with the frequent use of RH data at a p (0.047<0.05).Conclusions: The study revealed that the health facilities lacked ample IT accessories even though internet and electricity connectivity was not limited, however, RHI use was not optimal in health facilities. The study found that the majority of respondents lacked training in RH data implying that training may influence the overall use of the routine data. The study also observed that RH data were used for decision-making frequently for a range of management functions.

The Influence of ICT Infrastructure Support for Management of Essential Medicine Supply Chain in Health Facilities in Kenya

“…These results indicate that most public health facilities in Kenya lack dependable internet connectivity to support digital health information management for essential medicine supply chains. This corroborates the observations of Aila and Kithuka (2021), who suggest that unreliable internet connections hinder the production, transmission, and efficient utilization of health information for planning and service delivery. Kuyo et al ( 2020) also identified challenges in Uasin Gishu County hospitals related to the use of information from DHIS2, citing factors such as unreliable internet connectivity (47.1%), inadequate user skills (48.6%), non-connected computers (36.7%), and insufficient management support (34.3%).…”

“…Suhlrie et al ( 2018) cite examples from Malawi where public health facilities are often connected to off-grid electricity systems compared to facilities managed by other entities. Aila and Kithuka (2021) and Muinga et al (2020) note that inconsistent electricity supply challenges hinder the effective use of computers, data analysis, and health information critical for planning and service delivery.…”

“…Furthermore, Aila and Kithuka (2021) suggest that unreliable internet connections hamper the production, transmission, and efficient use of health information for planning and service delivery. Kuyo et al ( 2020) report challenges at Uasin Gishu County hospitals related to the use of information from DHIS2, including unreliable internet connectivity, inadequate user skills, non-connected computers, and insufficient management support.…”

Factors Influencing Utilization of Routine Health Information For Decision Making Among Health Workers: A Case Study of Health Facilities in Moyo District, Uganda

“…This implies that receiving training HMIS (data collection and reporting), data analysis and data presentation equips health workers with adequate skills and expertise on how to utilize routine health information while making decisions. The findings also agree with Aila (2021) who argued that training that improves health workers skills in data gathering, analysis, interpretation, and information management increases their likelihoods of utilizing routine health data in making decisions.…”