160 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) ISSN (Print) 2313-4410, ISSN (Online) 2313-4402 © Global Society of Scientific Research and Researchers http://asrjetsjournal.org/ Factors Influencing the Adoption of Electronic Health Record Systems in Developing Countries: A Case of Uganda Hussein Muhaise a* , Dr. Margaret Kareyo b , Professor Johnie Wycliffe Frank Muwanga-Zake c a School of Computing and Information Technology, Kampala international University b Senior Lecturer, School of Computing and Information Technology, Kampala international University c Professor, School of Computing and Information Technology, Kampala international University a Email: hmuhaise@yahoo.com b Email: magsterkami@gmail.com c Email: tebiggwawo@gmail.com Abstract Electronic Health Records Systems are important Technology that is beneficial to improving the health care delivery inline of (i) providing accurate, up to date and complete data, (ii)sharing electronic information between patients and clinicians securely (iii) helping providers to effectively diagnose patients, reduce medical errors and provide safer care (iv) quick access to patient records for more coordinated efficient care (v) improving patient and provider interaction and communication (vi) enabling safer more reliable prescriptions (vii) reduction of costs, reduced paper work, reduced duplication of testing and general improved health. Despite all the benefits provided by Technology, there is little interest and limited adoption of Electronic Health Record Systems by the Health Sector in developing countries to compete in today’s market globally geared by new technology. The aim of this paper is to review factors for low adoption of Electronic Health Record Systems in context of developing countries. The factors that can influence the adoption include the need for involvement and participation of all stake holders in the health sector, availability of dedicated users and having a good change management strategy and leadership, effective leadership and effective communication, training staff and time management are key, also evaluation of organizational needs is important for fostering the implementation of electronic health record systems. Keywords: Electronic health record systems; EHR adoption; develooping countries; EHR implementation. ------------------------------------------------------------------------ * Corresponding author American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 161 1. Introduction The Health Sector around the world are increasingly adopting the Electronic Health Records systems (EHR) driven by the advancements in Information and Communication Technologies (ICTs). Electronic Health Records System is a digital mechanism of capturing patient information, storing and continued use by authorized health care providers to effectively deliver health care services [14]. However, it is a big challenge to implement the EHR systems in Health care service centre in context of developing countries because technology adoption and use depends on a number of factors. For example, the acceptance of technology at organizational and individual levels may be influenced by the factors in the area in which the EHR is implemented [13]. Low usage of EHR in the developing countries is a consequence of poor adoption by organizations and users [4,5]. Developing countries is a general terms used to refer to a group of countries that require equitable and sustainable social and economic growth. Reference [15] classified such countries as low income countries with the national income (GNI) per capita $995 or less. 2. Methodology A systematic literature review, based on papers published from 2010 to 2019, concerning the facilitators and barriers for the adoption and use of Electronic Health Records in developing countries was conducted. Data was gathered using five databases: Google scholar, Journals of Health and Medical Informatics, BMC Health services research, Pub Med Health, EBSCO. Studies were included in the analysis if they had issues relation to adoption facilitators and barriers of EHR in developing countries, implementation of EHR in developing countries and factors affecting implementation of EHR in developing countries. 3. Findings The findings were summarized in the facilitators and barriers table after the authors choice of articles for the literature review. Before creation of the findings table duplicate articles were taken care of not to confuse the findings. Then analysis of individual articles was done to identify the factors affecting the adoption and use of EHR in developing countries. The factors were compiled into a frequency table to aid the analysis and discussion of findings. Results are summarized in table 1 and the factors the frequency table 2. The systematic analysis of literature revealed many facilitators and barriers of adoption and use EHR in context of the developing countries. The facilitators to adoption and use of EHR included accesses to complete information, accurate and error free information, efficiency and quality health services cost saving, and information security while the barriers included inadequate ICT skills and training, inadequate financial and equipments, poor implementation planning, negative perceptions. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 162 Table 1: Results from the review of Literature Authors Facilitators Barriers Boonstra & BroeKhius, 2010 Change management Emerging payment methods Perceived ease of use Costs of ICT equipment Inadequate training and skills Attitude Resistance Organisational barriers Castilo, Martinez & Pulido, 2010 Error reduction Quality Efficiency Better health outcomes Attitude Interoperability Lack of enough time Lack of expert support Cultural Yan, Gardner & Baier, 2012 Emerging payment methods Good communication with EHR developers Efficiency Quality Costs Attitude Skills and training Lack of interoperability Resistance Unreliable power supply Security Staff retention Improper planning Understaffing Boonstra, Versluis and Vos, 2014 Efficiency Quality Error reduction Costs Skills and training Attitude Skills and training Namakulla and Kituyi, 2014 Quality Efficiency Perceived ease of use Time saving Skills and training Attitude Resistance Cultural Costs Security Kiberu and his colleagues 2014 Quality Efficiency Error reduction Skills and training Lack of interoperability Resistance Unreliable power supply Akomolafe, 2014 Quality Efficiency Attitude Risks Improper implementation Cost Security Kihuba, 2014 Quality Efficiency Time saving Skills and training Lack of interoperability Resistance Unreliable power supply Improper planning Hsieh, 2015 Perceived ease of use Perceived usefulness Attitude Risks Improper implementation Cost Political influence Cultural Cucciniello, Lapsley, Nasi and Pagliari, 2015 Efficiency Management & staff support Training programs Error reduction Attitude Cultural Costs Technophobia Improper planning Understaffing American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 163 Muhaise and Habiinka,2016 Management support Quality Efficiency Training staff Costs Attitude Skills and training Lack of interoperability Resistance Unreliable power supply Mosweu, Bwalya and Mutshwewa, 2017 Perceived usefulness Attitude Technophobia Resistance Improper planning Mathal, Shiratudin and Sohel, 2017 Quality Efficiency Perceived ease of use Attitude Resistance Costs Security Understaffing Ondieki F, 2017 Efficiency Quality Time saving Time Resistance Cost Skills and training Muhaise and Kareyo, 2017 Efficiency Quality Perceived usefulness Resource supply Management support Training staff Costs Skills and training Power supply Security Attitude Resistance Lack of expert support Furusa and Coleman, 2018 Efficiency Quality Perceived usefulness Time saving Skills and training Understaffing Costs Power supply Lack of expert support Katurura and Cilliers , 2018 Institutional pressure and completion Chromic care management Perceived ease of use Skills and training Costs Power supply Political influence Resistance Improper implementation Adedeji, Irionye, Ikono and Komolafe, 2018 Efficiency Quality Patient follow up Skills and training Resistance Attitude Lack of expert support Security American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 164 Table 2: factors frequency Factors Total Occurrences Facilitators Better health outcomes 1 Change management 1 Chromic care management 1 Efficiency 14 Emerging payment methods 2 Error reduction 5 Good communication with EHR developers 1 Institutional pressure and competition 1 Management & staff support 1 Management support 2 Patient follow up 1 Perceived ease of use 5 Perceived usefulness 4 Quality 13 Resource supply 3 Time saving 4 Training programs 6 Barriers Attitude 13 Costs 13 Cultural 4 Improper implementation 3 Improper planning 4 Inadequate training and skills 5 Interoperability 6 Lack of enough time 2 Lack of expert support 4 Organisational barriers 1 Political influence 2 Power supply 3 Resistance 12 Risks 2 Security 5 Skills and training 12 Staff retention 3 Time 2 Technophobia 2 Unreliable power supply 4 Understaffing 5 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 165 3.1 Facilitators The facilitating factors identified included: better health outcomes change management, chromic care management, efficiency, emerging payment methods, error reduction, good communication with EHR developers, institutional pressure and competition, management & staff support, patient follow up, perceived ease of use, perceived usefulness, quality, time saving, training programs. The factors better health outcomes change management, chromic care management, efficiency, quality patient follow up form are concerned with ability of EHR to facilitate quality health services provision in terms of easy to access patient records and management, rapid information exchange, electronic schedule of patients’ appointments and alerts for adherence to drugs and likely drug side effects. Error reduction was another benefit cited: the error reduction in form of patient prescriptions, drug dispensing and records capture. Perceived ease of use and perceived usefulness 3.2 Barriers The barriers indentified through the review to influence the adoption and use of EHR in developing countries include: attitude, costs, cultural, improper implementation, improper planning, inadequate training and skills, interoperability, lack of enough time, lack of expert support, organizational barriers, political influence, power supply, resistance, risks, security, skills and training, staff retention, time, technophobia, unreliable power supply, understaffing. Negative attitude towards the technology innovations in health were identified as a critical issue, costs for start up of EHR projects in terms of purchase of required ICT infrastructures and resources like internet, inadequate financing, organizational cultures and resistance to change. Some health practitioners preferred the status quo of using manual forms citing insecurity about patient records and the practitioners’ fallback position in case things go wrong about patient management. Lack of skills and training in ICT facilities usage was another issue seen. Lack of expert support related to technical support from the software developers, absence of ICT technical staff 4. Conclusions The review examined factors that influence the adoption and use of EHR in context of developing countries. The information generated by this study is paramount for MoH Uganda to benchmark and effectively take decision as policy makers to increase the adoption and use of EHR in all health facilities in Uganda. References [1]. Boonstra A and Broekhuis. Barriers to the acceptance of electronic medical records by Physicians from systematic review taxonomy and interventions. BMC Health Serv Res.2010 Aug6;10:231. doi 10.1186/1472-6963-10-231 [2]. Castillo VH, Martinez-Garcia AI and Pulido R. A knowledge-based taxonomy for adopting electronic health record systems by physicians: A systematic literature review. MC Med inform Decis Mask. 2010 Oct 15;1060. doi 10.1186/1472-6947-10-60. [3]. Hsieh PJ. Physicians’ acceptance of electronic medical records exchange: an extension of decomposed TPB model with institutional trust and perceived risk. Int Med Inform. 2015 Jan;84(1):1-14.doi American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2019) Volume 61, No 1, pp 160-166 166 10.1016/j.ijmedinf.2014.08.008 [4]. Hussein Muhaise and Margaret Kareyo (2017) Electronic Health Information Systems critical implementation issues (eHMIS): District Health Information software version 2.0 in the greater Bushenyi Districts, American Scientific Research Journal for Engineering, Technology and Sciences, Vol 34, pg 205-212 [5]. Hussein Muhaise, Annabella Habinka Ejiri (2016) Factors influencing District Health information software version 2.0 success. A case of the greater Bushenyi Districts, American Scientific Research Journal for Engineering, Technology and Sciences, Vol 26, pg 166 -178 [6]. Katurura MC and Cilliers L. Electronic health record system in the public health care sector of South Africa: A systematic literature review. Afr J Prm Health Care Fam Med. 2018;10(1), a1746. https://doi.org/10.4102/ phcfm.v10i1.1746 [7]. Kihuba et al.,. Assessing the ability of Health Management Information systems in Hospital to support evidence based – informed decisions in Kenya:Glob Health Action 2014, 7: 24859 - http://dNo.doi.org/10.3402/gha.v7.24859 [8]. Mathai N, Shiratudin MF and Sohel F. Electronic Health Record Management: expectations, Issues and Challenges. JMed Informat8:265.doi 104172/2175-7420.1000265 [9]. Mayowa Olayemi Akomolafe. The Implementation of Electronic Health Record Systems: the factors influencing the successful electronic health record systems. The International Journal of Science & Engineering Research, vol 5, issue march-2014 [10]. Namakula ., S, Kituyi G, . Examining health information systems success factors in Uganda health care systems. Journal of global health care systems. 2014, 4: 1 [11]. Olefhile Mosweu, Kelvin J Bwalya and Athulang Mutshwewa. A probe into factors for adoption and usage of electronic document and records management systems in the Botswana context. Information development 2017, Vol.33(1) 97-110. SAGE publications [12]. Ondieki F. Effects of Health Records Management on Service delivery: A case study of Kisii teaching and referral Hospital. JHosp Med Manage.2017,3:1 [13]. Peter Adedeji, Omolola Irinoye, Rhoda Ikono and Abiola Komolafe. Factors influencing the use of electronic health records among nurses in a teaching hospital in Nigeria. Journal of Health Informatics in Developing countries. Vol. 12 No.2, 2018 [14]. Samuel S.Furusa and Alfred Cole. Factors influencing e-health implementation by medical doctors in public hospitals in Zimbabwe. Afr J Prm Health Care Fam Med. 2018;10(1), a1746. https://doi.org/10.4102/ phcfm.v10i1.1746 [15]. World Bank (2018). Country Classification. Available at http://data.worldbank.org/about/country- classification. (Retrieved on 28.04.19). [16]. Yan H, Gardner R and Baier R. Beyond the focus group: understanding physicians barriers to electronic medical records. Jt Comm J Qual Patient Saf.2012 Apr; 38(4):184-19 http://dx.doi.org/10.3402/gha.v7.24859 http://data.worldbank.org/about/country-%20classification http://data.worldbank.org/about/country-%20classification