1.1 Introduction
Health information is the processed data and knowledge that an individual or group use to support their decisions in the health sector (Wyatt et al., 2005; WHO, 2010). Health information system is a system that allows for the collection, storage, compilation, transmission, analysis and usage of health data that assist decision makers and stakeholders manage and plan resources at every level of health service (Wyatt et al., 2005). The adoption of health information systems has become a pivotal aspect of modern healthcare delivery, promising enhanced efficiency, improved patient care, and better health outcomes. However, the successful implementation and utilization of these systems are contingent upon various factors that influence their adoption within healthcare organizations. Understanding these factors is crucial for policymakers, healthcare administrators, and IT professionals to devise strategies that promote effective HIS adoption and utilization.
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Research hypothesis and questions, Limitation of the study and Definition of terms.
1.2 Background of Study
The landscape of healthcare delivery is continually evolving, with technological advancements playing a pivotal role in shaping its trajectory. Health Information Systems (HIS) have emerged as indispensable tools in modern healthcare, offering a means to streamline processes, improve patient care, and facilitate data-driven decision-making. However, the adoption of HIS within healthcare organizations is a complex process influenced by a myriad of factors ranging from organizational culture and resources to technological infrastructure and regulatory frameworks.
The Health Metrics Network (HMN), the first global health partnership for developing and strengthening of health information system in low and low-middle income countries was set up to set international standards (WHO, 2012). Health Management Information System (HMIS) was set up to enhance effective health services planning and decision making. Under ideal circumstances health data should be collected from several Health Service delivery units (Shaikh & rRabbani, 2005). These would include government, NGO, and private health units including hospitals, private clinics, drugs shops, Village Health Teams Traditional Healer and formally Traditional Birth Attendants' Reports (Ssali & Kalere, 2013).
Generally, despite the volume and variety of data generated through the routine Health Management Information System, the information is systematically under-analyzed and under-utilized for planning and programme reviews (Ranganayakulu, 2017). Completeness, timeliness and quality of reporting are often described as problematic, and the data are inevitably biased because they relate only to the populations using public health services. Investments in the information system are often minimal, and there are major lacunae in the availability and statistical capabilities of those charged with collecting, compiling and analysing the statistics. As a result, data generated through the routine system are rarely assessed for their quality and used to support decision-making (Mendhoza, 2015).
The overall goal of any HIMS is to enable health facilities make decisions in a more transparent and efficient approach, based on evidence with the objective of producing timely, relevant and quality information to support decision making. There has been a strong acknowledgement for the need of quality data right from the beginning of initiation of sector reforms; this is an essential part of the planning, management and policy development of the health system processes that were being introduced. Investments in terms of communication infrastructure and human resource for management and utilization of heath information however remain limited and uncoordinated. Public health decision-making is seriously reliant on a timely availability of sound data, and globally significant human and financial resources have been invested to improve health information systems (Lærum et al., 2004).
Therefore, in Nigeria where the research was carried out, the activities that was conducted is to assess the Factors Influencing Health Information System Adoption.
1.3 Statement of Problems
Investigation revealed that resistance to change within healthcare organizations often poses a substantial barrier to HIS adoption. This resistance can stem from entrenched workflows, lack of leadership buy-in, and concerns about job security or loss of autonomy among healthcare professionals. Also, limited financial resources, inadequate IT infrastructure, and a shortage of skilled personnel can impede the successful adoption of HIS. Healthcare organizations may struggle to invest in the necessary technology, training, and support systems required for effective implementation.
Additionally, the lack of interoperability between different HIS platforms and existing systems within healthcare ecosystems hampers data exchange and integration. Incompatibility between systems can lead to data silos, duplication of efforts, and inefficiencies in care delivery.
Furthermore, healthcare organizations must navigate complex regulatory frameworks and privacy laws governing the collection, storage, and sharing of patient health information. Data breaches, cyber security threats, and compliance challenges can undermine trust in HIS and deter adoption efforts. Addressing these problems requires a comprehensive understanding of the multifaceted factors influencing HIS adoption and the development of targeted strategies to overcome barriers and promote successful implementation.
1.4 Aim and Objectives of Study
The aim of the study is to investigate the factors influencing Health Information System (HIS) adoption in healthcare settings, with the goal of providing insights to inform strategies for promoting successful implementation and utilization. In achieving this aim, the following specific objectives were laid out as follows:
- To assess the readiness of healthcare organizations for HIS adoption by examining factors such as leadership support, organizational culture, and change management practices;
- To assess the perspectives of healthcare professionals and other stakeholders regarding health information system adoption;
- To establish the type of health data/information generated at the health units and how it is processed and stored;
- To evaluate the technological infrastructure and capabilities of healthcare organizations; and
- To propose recommendations and strategies for promoting successful HIS adoption in healthcare settings, addressing identified barriers and leveraging facilitators to optimize implementation and utilization.
1.5 Research Questions
The study came up with research questions so as to be able to ascertain the above stated objectives. The specific research questions for the study are stated below as follows:
- What are the levels of utilization of health data/information in the study area?
- What is the technological infrastructure and capabilities of healthcare organizations?
- What is the readiness of healthcare organizations for HIS adoption by examining factors such as leadership support, organizational culture, and change management practices?
- What are the perspectives of healthcare professionals and other stakeholders regarding health information system adoption?
- What is the type of health data/information generated at the health units and how it is processed and stored?
1.6 Research Hypothesis
In order to pursue the objective of this study, the following generalized statements have been designed to guide and aids in obtaining the result for the experiment to be conducted. For this work, the null hypothesis will be represented with H0 while the alternative hypothesis will be represented with hypothesis H1.
Hypothesis One
- H0: Healthcare organizations with a culture that values innovation, collaboration, and continuous improvement will not exhibit higher rates of Health Information System (HIS) adoption compared to organizations with more traditional or resistant cultures
- H1: Healthcare organizations with a culture that values innovation, collaboration, and continuous improvement will exhibit higher rates of Health Information System (HIS) adoption compared to organizations with more traditional or resistant cultures.
1.7 Significance of Study
The study on factors influencing Health Information System (HIS) adoption holds significant implications for healthcare practice, policy, and research. Understanding these factors and their impact on adoption processes is crucial for several reasons:
- Improving Healthcare Delivery: Successful adoption of HIS can lead to improved healthcare delivery by enhancing efficiency, coordination, and quality of care. Identifying factors that facilitate or hinder adoption can inform strategies to optimize HIS implementation and maximize its benefits for patient outcomes.
- Enhancing Organizational Performance: HIS adoption has the potential to streamline administrative processes, reduce errors, and facilitate evidence-based decision-making within healthcare organizations.
- Informing Policy and Regulation: Insights into the factors influencing HIS adoption can inform the development of policies and regulations aimed at promoting the use of health information technology. Policymakers can use this knowledge to design incentives, standards, and support mechanisms to facilitate widespread adoption and interoperability.
- Optimizing Resource Allocation: Healthcare organizations operate within resource-constrained environments, and investments in HIS must be justified by their potential return on investment.
- Advancing Research and Innovation: Research on HIS adoption contributes to the advancement of knowledge in health informatics and technology implementation science.
The study will also provide empirical, theoretical and conceptual framework, which will contribute to the existing knowledge in other related fields. The outcome of this research would help to identify ideal methods of managing electronic health records.
1.8 Scope of Study
The scope of the research is focused on the Factors Influencing Health Information System Adoption using Some selected Hospital in Makurdi, Benue State as a case study.
1.9 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet, questionnaire and interview).
1.10 Operational Definition of Terms
Electronic Health Records:
This is an electronic store of patient's health records, which are created, stored, managed and controlled by health personnel.
Records Management Practices:
It refers a range of activities which an organization performs or carried out to properly manage its records. The key activities include records creation, use, storage, maintenance, retrieval and disposal.
Health Information System (HIS):
A health information system is a comprehensive system designed to manage and process health data, facilitate communication and decision-making among healthcare providers, and support the delivery of healthcare services.
Adoption:
Adoption refers to the process by which individuals, organizations, or societies accept and integrate a new innovation, technology, or practice into their existing systems or routines.
Factors:
Factors are the elements or variables that influence the adoption of health information systems. These factors can include organizational characteristics, technological capabilities, user perceptions, regulatory requirements, and external environmental factors.
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