Health Information Technology Acceptance Framework for diabetes management

Abstract

This study examined the level of acceptance of Health Information Technology (HIT) as tools for diabetes care and management, in six selected tertiary hospitals in southwestern zone of Nigeria. Using both quantitative and qualitative methods, this study was conducted amongst selected healthcare stakeholders namely Nurses, Doctors, Laboratory Scientists, Pharmacists, ICT unit Professionals, Medical Record Officers, and Type-2 diabetes out-patients available in the designated hospitals. Adapting Technology Acceptance and Chronic Care Models, the level of HIT acceptance by the respondents in the study area was measured in terms of Perceived Ease-of-Use, Perceived Usefulness, and the Perceived Unintended Consequences relating to HIT, while also considering the roles of the government, community and healthcare organizations. One hundred and fifty (150) respondents were examined, each for both Staff and Patients, and the factor variables studied on a 5-point Likert rating scale of measurement from 1 (Strongly Disagree) to 5 (Strongly Agree). The results revealed strong perception of Staff and Patients about HIT implementation and acceptance and showed that in some cases, the perception of Staff and patients about HIT acceptance are the same, while different in some. The study concluded that for acceptability of HIT, hospitals have to embark on 'continuous' training for the HIT users, so that users would familiarize themselves with the system, and it will be fully incorporated into their workflow. Based on the findings, a conceptual Health Information Technology Acceptance Framework for Chronic diseases' management, especially for diabetes mellitus was developed.

Keywords: Health profession; Information science.

Fig. 1

Technology acceptance model (Modified after Davis et al., 1989).

Fig. 2

The Chronic Care Model, CCM (Wagner, 1998).

Fig. 3

Health Information Technology Acceptance Framework for Chronic diseases' management, especially diabetes (Adapted from Davis et al, 1989 and Wagner, 1998). KEY/LEGEND; Perceived Ease-of-Use: CU – Clear Use, UN – Understandable Navigation, FI – Flexible Interaction, SL – Skill Learning, EL – Easy to Learn; Perceived Usefulness: TA – Task Accomplishment, JI – Job Improvement, JP – Job Productivity, JE – Job Effectiveness, EJ – Easiness of Job; Perceived Unintended Consequences of HIT: CD – Communication Disruption, EG – Error Generation, TP – Third Party, TT – Time Taken, SB – Security Breaches, JB – Job Loss; Readiness to Change Behaviour after Implementation: PT – Poor Typing, EU – EMR-features Usage, WR – Workflow Readjustment, IU – Internet Usage, PI – Patient Involvement, EC – Erroneous Copying; Prevention of Unintended Consequences of HIT: TE – Thought Expression, DI – Doctor-patient Interaction, MA – Medical Accuracy, SC – Security and Confidentiality; Success Factors of HIT: CR – Complete Records, NE – Needed Expertise, HN – Hospitals' Network, SC – Security and Confidentiality, PI – Patient Involvement, PC – Patient-Doctor Communication, PE – Patient Education, DP – Delivery Process, RA – Records Accessibility, ET – Effective Treatment, AD – Accurate Decision, TD – True Diagnosis, CP- Clear Prescription; Delivery System Design: EA – Expertise Availability, PR – Staff-Patient Ratio, OS – Organisational Structure, SC – Security Consciousness.