Abstract
Introduction:
Digital health technology including electronic community health information
system (eCHIS) are promising for improving healthcare services. However,
developing countries including Ethiopia encounter different challenges to
employ digital health technologies. As a result, burdens on health care
services such as low provider effectiveness, inability to track clients and provide
quality service, disparities in health service coverage, and poor quality of
data for decision making have been major issues. Therefore, this study aimed to
assess health extension workers intention to use electronic community health
information system and associated factors in Ethiopia.
Methods:
A facility based cross sectional study was conducted on 649 health extension
workers from March
10 to April 12, 2023 at West Gojam Zone, Amhara, Ethiopia. A Simple random sampling
technique was used to select participants. Self-administered questionnaire was
used to collect data. Descriptive statistics were produced using SPSS version
25 software and presented using tables and pie charts. Structural equation
modeling analysis with SPSS AMOS version 26 software was employed to identify
predictors associated with intention to use electronic community health
information system in Ethiopia.
Results:
A total of 612 health extension workers, with a 94.3% response rate,
participated in the study. The percentage of HEWs with intention to use electronic
community health information system was 70.8% (95%: CI: 67.0–74.3). Attitude (β
=0.60, P < 0.001, 95%: CI: [0.47, 0.74)], social influence (β = 0.16, P <
0.05, 95%: CI: [0.01, 0.34]), and facilitating condition (β = 0.17, P <
0.001, 95% CI: [0.08, 0.30]) had a positive direct relationship with intention
to use electronic community health information system. Facilitating condition and
performance expectancy were positively moderated by age.
Conclusion:
Generally, it was encouraging to see that health extension workers intended to
use electronic community health information systems. The intention to use
electronic community health information system was positively related to Attitude,
facilitating conditions, and social influence. Thus, increasing health
extension workers utilization of it could be achieved through capacity
building, access to technology, and technical support.
Keywords:
Intention to use, Electronic community
health information system, Health extension workers, Ethiopia
1.
Introduction
Mobile health (mHealth) is defined by the world
health organization (WHO) as the health-related use of mobile telecommunications
and multimedia technologies within health service delivery and public health
systems1. mHealth applications are defined as tools that
assist in medicine and public health via mobile devices. Mobile devices, such
as cellphones, tablets, personal digital assistants (PDAs), and wearable
devices, such as smart watches, are widely used for health care information,
and data collection2. Electronic
Community Health Information System (eCHIS) is a digitized version of paper-based
community health information system (CHIS) in which its content is digitized
into a mobile platform application
that works in online and offline environments for use by health extension
workers (HEWs)3. Worldwide there are
burdens on primary health care services especially in hard-to-reach
low-resource settings including low provider effectiveness, unimproved tracking
and service provision, inequity of coverage of their target populations, and
low quality of the health-related information provided4,5.
Successful eCHIS interventions resulted in
improvements in reproductive,
maternal, newborn and child health (RMNCH) and nutrition in India5,6, breastfeeding in China7, maternal and child health care attendance in
Rwanda8, antenatal care services in Nigeria9, and Maternal and Neonatal Health (MNH) monitoring
in Kenya10, maternal health care in
Ethiopia11.
Ethiopia began to implement eCHIS in September
2018 and took an important and guiding program management, policy development
to extract and use data for decision making, and national electronic health management
information system to promote one of the five transformation agendas in the
country’s second health sector transformation plan (HSTP II) which is
“Information Revolution”12. eCHIS is
a high-priority initiative and is taken as one of the major programs of the
National Digital Health Strategy of the Ethiopian Ministry of Health (MOH) to
improve the quality of health services provided through HEP at the community
level13.
In the context of developing countries
like Ethiopia, with limited resources, deployment of mobile technology, needs
users' intention to use mobile technologies including eCHIS. Health extension
workers better understanding and intention in using eCHIS can influence the
adoption of the technology14. A study
conducted in Ghana shows healthcare providers intention to use EHRs was high
(85%)15. In contrast a study conducted in Ethiopia
shows healthcare providers intention to use EMRs was low (40%)16. Evidences revealed that health professionals’
low intention to use new technology is the major barrier to implement it successfully17,18.
In spite of the fact that mHealth
applications are a well-established technology supported by a community of
software developers and healthcare professionals, many nations are still having
difficulty in implementing them due to a variety of obstacles, including
cultural, technological, personal, organizational, and social issues19. The majority of health professionals in
developing countries who want to employ mHealth technology encounter challenges
such as inadequate ICT infrastructure, lack of technical assistance and
training, skill and experience gaps in mobile technology20. According to the findings of various studies
performance expectancy, effort expectancy, social influence, facilitating
conditions and attitude are determinant factors in healthcare providers’
intention to use mHealth application including Echis21-25.
In Ethiopia favorable attitude, internet
access, computer training, the technical skill of healthcare provider, and
availability of IT support staff were the most notable factors of mHealth application
use26; User resistance, shortage of
infrastructure, technical
difficulty, gaps in routine monitoring, inadequate training, and poor
supportive supervision were also reported to be the primary hindering factors against
the successful implementation of eCHIS3,27.
According to the program manager and
office reports; eCHIS deployment and distribution are still in their early
stages. To implement proven eCHIS interventions there should have confirmed the
intention of health extension workers. However, it has not been scientifically well
studied in Ethiopia in general and in West Gojam Zone in particular. Therefore,
this study aimed to assess intentions to use electronic community health
information system and associated factors among health extension workers of West
Gojam Zone, Amhara, Ethiopia.
The findings of this study are anticipated
to benefit West Gojam Zone primary health care units (PHCU) and their
administrative health office by offering support for the creation of
interventions and policies that are based on health extension workers’ (HEWs)
intentions to use electronic community health information system (eCHIS). Additionally, it offers important information
for Amhara Regional Health Bureau regarding the current situation, the justifications
for intention to use eCHIS, and the difficulties in doing so.
The findings of this study will help the
PHCUs in West Gojam Zone to understand the factors that influence the intention
to use eCHIS. This will provide opportunities to solve the issues and perhaps
implement the approach throughout all health posts. Moreover, the study
benefits health institutions, by helping them to identify their weakness to
improve intention to use eCHIS and provide scientifically sound information and
recommendation on determinant factors of intention to use the eCHIS. Furthermore,
this study will have greater input to program managers for designing,
implementing and evaluating eCHIS programs; and also serve as base line for
further study.
The Unified Theory of Acceptance and Use
of Technology (UTAUT) has been introduced in 2003 as a model. It contains four
constructs (performance expectancy, effort expectancy, social influence and
facilitating conditions)28. In this
study, the original UTAUT model was adapted and modified by adding one
construct (attitude). In the modified UTAUT model, performance expectancy was
assessed with four indicators (PE1: effectiveness in healthcare delivery,
PE2: quality in
work, PE3: timelines to accomplish tasks, PE4: usefulness in job), effort
expectancy was assessed with four indicators (EE1: easiness for use, EE2: clarity and understandability for use, EE3: easiness
to become skillful, EE: flexibility to interact with), social influence was
assessed with three indicators (SI1: recommendation from important people, SI2:
belief by
colleagues, SI3: motivation by senior management), facilitating condition was
assessed with four indicators (FC1: knowledge and experience in using smart
phone/tablet, FC2: availability
of IT support staff, FC3: attendance of training on eCHIS, FC4: availability of
technical and organizational infrastructure), attitude was
assessed with four indicators (ATT1: having good idea at work, ATT2: having interest in the work, ATT3: having enjoyment
during work, ATT4: thinking with the current system is better than the old one ).
The modified model measures the intention
of HEWs to use eCHIS (IU) using three indicators (IU1: start thinking to use
eCHIS, IU2: plan to use eCHIS, IU3: aspire to use eCHIS).
The degree to which a person expects that
using the system would enable him or her to improve performance at work is
known as performance expectancy29. According
to the study conducted in China,
India and Korea Performance expectancy (PE) has a significant effect on health
workers intention to use mHealth technology and or EHR20,21,23,25,30,31. In contrast the study
conducted in Tanzania reveals that PE has an insignificant effect on health workers
intention to use the mHealth app in the case of eIDSR32. Additionally, the study conducted in
Cameroon, Kenya and Burundi shows that PE has significant effect on health professional’s
intention to use DHIS2 and or mobile health technology24,33-35. In contrast another study conducted in
Tanzania (mobile app in case of DHIS2) and Kenya reveals PE has an insignificant
effect on health workers intention to use DHIS232,36.
The study conducted in Ethiopia shows that PE has a significant effect on health
professionals’ intention to use EMR37,38.
The direct effect of PE was moderated by age33,37,39-42.
Effort expectancy is defined as “the
degree of ease associated with the use of the system”28. According
to the study conducted in India, Korea and Tanzania EE has a significant effect
on health workers intention to use mHealth technology and or EHR20,23,25,30-32,39.
In contrast the study conducted in China
reveals that EE has an insignificant effect on health workers intention to use
mobile nursing applications21. Additionally,
the study conducted in Cameroon, Kenya and Burundi shows that EE has a significant
effect on health professional’s intention to use DHIS2 and or mobile health
technology33-36. In contrast the
study conducted in Tanzania reveals that EE has an insignificant effect on
health workers intention to use DHIS232.
The study conducted in Ethiopia shows that EE has a significant effect on
health professionals’ intention to use EMR37,38.
The direct effect of EE was moderated by age33,34,39-42.
Social influence is the degree of
importance a person place on the beliefs of other people ( peers, colleagues,
and family members, etc.) and how this influences their decision to use
technology43,44. According to the
study conducted in India, China, Bangladesh and Korea SI has a significant
effect on the intention to use mHealth technology and or EHR20,21,23,25,30,31,39,45.
In contrast; the study conducted in
Tanzania reveals SI has an insignificant effect on health workers intention to
use a mobile app in the case of eIDSR32.
Additionally; the study conducted in Cameroon and Kenya shows that SI has a significant
effect on health professionals’ intention to use DHIS224,33,34,36. According to a study conducted in
Ethiopia SI has significant effect on the intention to use EMR(37, 38).
The direct effect of SI was moderated by age33,34,39,40,42,44.
Facilitating conditions include
perceptions of existing infrastructure, internal and external resource
constraints, or skills, resources, and opportunities necessary to use the
existing technology46. According to
the study conducted in china, India, Korea, and Bangladesh FC has a significant
effect on the intention to use mHealth technology and or EHR19,20,21,23,30,37,39,45. According to a study
conducted in Tanzania FC has a significant effect on the intention to use
mobile applications in the case of eIDSR; in the same study FC has an insignificant
effect on the intention to use DHIS232.
Additionally, the study conducted in Ethiopia shows FC has significant effect
on health professionals’ intention to use EMR37.
The direct effect of FC was moderated by age29,40.
Attitude is an individual's positive or
negative feelings about performing the system28,47.
According to the study conducted in Taiwan, Korea, Ghana, and Ethiopia ATT has a
significant effect on the intention to use eHealth/mHealth technology30,38,48-50.
Intension to use is a measurement of user’s
conscious intent to engage in a particular future behavior for using technology37. It is the extent to which a person has made
conscious decisions to engage in or refrain from engaging in a particular
future conduct51.
According to a study conducted in china nurses’
intention to use mobile nurse applications was 70.2%21. Additionally, the study conducted in India
shows that Physicians’ Intention to use mobile-based information technology was
56%20, medical doctors Intention to
use ICT was 47.5%39, clinical staffs
Intention to use EHR and TM was 48%52,
medical doctors Intention to use EHR was25. Furthermore, the study conducted in Taiwan
reveals medical staffs’ intention to use an online reporting system was 38%53. The study conducted in Belgium shows
healthcare professionals intention to use web-based systems for personal data
records and sharing was 30.8%54. The
study conducted in Pakistan shows physicians intention to use E-prescription
was 56.10%23. The study conducted in America shows doctors
intention to use EMR was 44%40.
According to the study conducted in Cameroon
health professionals intention to use DHIS2 was 81.9%(24).
Another study conducted in Cameroon showed that health professionals intention
to use web-based HIS was 46%.(34)
Additionally the study conducted in Kenya reveals health professionals
intention to use DHIS2 was 63.4%(36).
Another study conducted in Kenya shows
health workers intention to use DHIS2 was 30.9% and up to 37% when moderated by
age and gender. (33).
Furthermore the study conducted in Tanzania reveals health professionals
intention to use mobile health applications in the case of eIDSR was 72.2%(32).
The study conducted in Ethiopia shows that health workers intention to use EMR
was 40.2%(38).