Determinants of Acceptance and Use of Routine HIS in Developing Countries

239 Pages·2015·2.72 MB·English

UNIVERSITY OF NAIROBI
SCHOOL OF COMPUTING AND INFORMATICS

Determinants of Acceptance and Use of Routine HIS in
Developing Countries: The Case of DHIS2 in Kenya

BY
JOSEPHINE WANGARI KARURI
P80/85062/2012

THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE
DOCTOR OF PHILOSOPHY DEGREE IN INFORMATION SYSTEMS, SCHOOL OF
COMPUTING AND INFORMATICS, UNIVERSITY OF NAIROBI

AUGUST 2015
DECLARATION
I declare that this thesis is my original work except where due references are cited.
It has not been presented for a degree in any other university. No part of this thesis
may be reproduced without the prior permission of the author or the University of
Nairobi

NAME OF STUDENT

Josephine Wangari Karuri: Signature: Date: 15 August 2015

This thesis has been submitted for examination with our approval as the University
Supervisors.

NAMES OF SUPERVISORS

Prof. Peter Waiganjo Wagacha: Signature: Date: 15 August 2015

Dr. Daniel Orwa Ochieng: Signature: Date: 15 August 2015

University of Nairobi
School of Computing & Informatics
P. O. Box 30197 – 00100 GPO
Nairobi
ii
Dedication

To our three lovely daughters:
Lisa, Anna and Sara. Your
unconditional love inspires me to
reach for excellence in all spheres
of my life.

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ABSTRACT
The process of implementing ICT in the healthcare sector of developing countries has
in the past been often fragmented and ill-managed, leading to weak systems that
provide inaccurate, incomplete and untimely information. The increasing application
of ICT to manage these countries’ routine health information systems (HIS) is
expected to improve efficiencies, leading to availability of quality health information
for monitoring, evaluation and delivery of healthcare services and programs.

In 2010, Kenya initiated the process of adoption and implementation of a web-based
system (DHIS2) as the national HIS that will facilitate management of routine health
information for evidence-based decision making. For maximum benefits to be
reaped from this implementation, DHIS2 needs to gain acceptance from all
categories of targeted users. This study sought to develop a new technology
acceptance model that can better explain the key determinants of acceptance and
use of DHIS2 in Kenya. The findings from this case study can be extended to explain
acceptance and use of health IT in other similar settings.

The overall objective of this research was “to enhance knowledge and
understanding of health I.T. adoption by building and validating a technology
adoption model to study determinants of acceptance and use of national HIS in a
developing country context’. The specific objectives were to:
i. To develop a technology adoption model than can predict the complex
relationships that affect adoption of routine HIS in a developing country’s
healthcare context
ii. Validate the model through Structural Equation Modeling (SEM) using
empirical data collected from public health care workers in Kenya
iii. Generate the final model and evaluate the strength of the relationships
between the exogenous and endogenous constructs, hence deduce the
factors that most contribute to the HIS Adoption and Use process
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iv. Cross-validate the extended model across different categories of healthcare
workers via multi-group analysis.

The study was conducted primarily through the use of quantitative methods, but
qualitative data was also collected in the pre-study through conducting Key
Informant Interviews (KII) to provide the background and contextual information
used in refining the conceptual model. An exploratory study design was
subsequently used to determine the existence of relationships between the
dependent and independent variables in the model. In the pilot phase of the study,
focus group discussions and quantitative analysis of data collected from twenty two
DHIS2 users was used to establish the survey instrument’s understandability and
Completion Time; test the instrument’s content validity; and also establish the
reliability of construct measurement through measures of composite reliability as
well as internal consistency reliability (Cronbach’s alpha). Findings from the pilot
phase were used to further refine the survey instrument and the conceptual model.

In the main phase the study, a questionnaire was administered to health workers
through a cross-sectional survey both at national and county / sub-county levels. The
total number of valid questionnaires returned was 266 against a target of 250. This
number represents slightly more than 20% of the approximately 1100 health
workers who have been trained on DHIS2 in Kenya, and these were drawn from at
least 10 of Kenya’s 47 counties. The resulting quantitative data was used to
empirically test the research model and the associated hypotheses. Data analysis for
both the pilot and main survey phases was done in two parts: descriptive analysis of
the data was performed using SPSS statistical analysis tool, for the purpose of
obtaining the frequencies, means, standard deviation, skewness and kurtosis; with
the latter two measures being used to test for distribution normality of each
indicator’s data. Subsequently Structural Equation Modeling (SEM), and specifically
Partial Least Square path modeling (PLS), was used for analysis of the conceptual
model and testing of the proposed hypotheses.
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By the end of the study, a technology adoption model had been adapted, tested and
validated to explain HIS adoption in a developing country context. The specific
significance of this study is that it:
 Contributes to research on technology acceptance by extending UTAUT
theoretical model
 Identifies the complex structural and contextual factors that contribute most
significantly to adoption of public health IT in developing countries context
 Tests the validity of UTAUT in the unique context of public health IT in
developing countries context
 Provides public health IT implementers and policy makers with a basis on
which to identify factors that can be manipulated to enhance acceptance of
such systems in developing countries

Key Words: Technology Acceptance; DHIS2; UTAUT; Health Information Systems;
Structural Equation Modeling;

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ACKNOWLEDGEMENTS
There are many who have inspired and supported me in this PhD journey. Here I
mention only but a few.
First and foremost, I would like express my deepest gratitude to my first supervisor,
Professor Peter Waiganjo Wagacha, for his trust in me and selfless commitment that
prodded me to reach for excellence. This work would not have been completed
without his invaluable support and encouragement that never wavered. I am also
indebted to my second supervisor, Dr. Daniel Orwa Ochieng, who wholeheartedly
shared with me his vast knowledge on technology adoption and got me moving in
the right direction. He provided me with never ending support and advice whenever
I needed it.
Additionally I thank all the other faculty members at University of Nairobi’s School of
Computing and Informatics (SCI), especially those who took time to provide my
colleagues and I with invaluable tips and guidelines on how to conduct PhD research:
Prof. Waema, Dr. Wanjiku Ng’ang’a, Dr. Wausi, Dr. Omwenga and Dr. Omwansa.
And to other faculty members who provided support in different capacities,
including Dr. Opiyo, Dr. Mwaura, Mr. Ogutu, Mr. Mburu and others. Special thanks
to the SCI director, Professor Okello–Odongo, for ensuring that the school provides a
most conducive environment for academic excellence. And to my colleagues and
fellow sojourners in the PhD journey – thank you for the mutual support and
encouragement.
I am also greatly indebted to all the different survey respondents who graciously
consented to participate in different phases of this study – without their invaluable
support this research would never have seen the light of day. Many thanks for the
immense support received from MoH officers, both past and present, at the Ministry
of Health’s Division of Health Informatics and M&E. We look forward to even
greater partnership in the coming days.
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Many thanks too to my friends and family near and far, too many to name
individually, who gave me constant support and encouragement throughout this
long research journey. And especially to my mum and dad, Mr. & Mrs. Ann and
Dedan Karuri, who have unwavering love and faith in us, their children.
And special thanks to my three lovely daughters, for their great patience and love,
spiced with some gentle nudging to hasten the PhD completion process and resume
‘normal’ life. And to my dear husband, Dr. V. Mark Gacii, thank you for holding
down the fort so willingly and so ably while I burnt the midnight oil.
Last but most important I thank the Lord Almighty, who gave me the conviction, the
faith and the strength I needed to undertake this journey. To Him be all the Glory.

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RESEARCH SUMMARY
The World Health Organization (WHO) defines Health Information System (HIS) as a
system that integrates data collection, processing, reporting and use of the
information necessary for improving health service effectiveness and efficiency
through better management at all levels of health services. A national HIS is usually
founded on routine data collection systems but complemented by information from
other sources such as community surveys, clinical studies, health systems research,
census, and other periodic or population-based surveys. The process of
implementing national Health Information Systems (HIS) in developing countries has
in the past been often paper-based, fragmented and ill-managed, leading to weak
systems that provide inaccurate, incomplete and untimely information. The
increasing application of ICT to manage developing countries’ routine HIS is expected
to improve efficiencies and effectiveness of such systems, leading to availability of
quality health information for efficient monitoring, evaluation and delivery of
healthcare services and programs in these countries. In 2010, Kenya initiated the
process of adoption and implementation of a web-based system (DHIS2) as the
national Health Information System that will facilitate management of routine health
information for evidence-based decision making. For maximum benefits to be
reaped from this implementation, DHIS2 needs to gain acceptance from all
categories of targeted users.

Researchers agree that one major factor leading to failure of systems
implementation is the inadequate understanding of the socio-technical aspects of
information technology (IT), particularly how people and organizations adopt IT.
Technology acceptance studies have been conducted widely and various models
developed in an attempt to predict the critical determinants of technology
acceptance, specifically from the users’ perspective. One such model is the Unified
Theory of Acceptance and Use of Technology (UTAUT) which reportedly was able to
explain up to 69% of user intention to use technology under different settings.
These settings did not however include the healthcare domain in a developing
country context, with all the unique challenges of implementing ICT under such
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settings. This study undertook a rigorous evaluation of an extended UTAUT model to
establish the key factors and their complex relationships in determining the
acceptance and use of DHIS2 in Kenya. The findings from this case study can be
extending to explain acceptance and use of health IT in other similar settings,
particularly in sub-Saharan Africa.

The overall objective of this research was “to enhance knowledge and
understanding of health I.T. adoption by building and validating a technology
adoption model to study determinants of acceptance and use of national HIS in a
developing country context”.

The specific objectives were to:
i. To develop a technology adoption model than can predict the complex
relationships that affect adoption of routine HIS in a developing country’s
healthcare context
ii. Validate the model through Structural Equation Modeling (SEM) using
empirical data collected from public health care workers in Kenya
iii. Generate the final model and evaluate the strength of the relationships
between the exogenous and endogenous constructs, hence deduce the
factors that most contribute to the HIS Adoption and Use process
iv. Cross-validate the model across different categories of healthcare workers
via multi-group analysis.

The study was conducted primarily through the use of quantitative methods, but
qualitative data was also collected in the explorative pre-study through conducting
Key Informant Interviews (KII) to provide the background and contextual information
used in refining the conceptual model. An exploratory study design was
subsequently used to determine the existence of relationships between the
dependent and independent variables in the model.

x