Different information technologies (ITs) are being implemented into the healthcare systems of developing countries (1). A patient portal is one of them that helps patients manage their personal health information, request prescription refills, schedule appointments, communicate with their health care provider, receive laboratory result, improve medication adherence (2–5). It provides for patients greater access to health care services and enables them to engage in their health care process as well as increase patient’s health literacy (2, 6–8). And also have a significant effect on improving self-management, especially for chronic diseases like diabetes (9) and increase patient satisfaction (10). In addition to this, it’s important to minimize medical error and medical fraud as a whole to improve patient outcomes in the healthcare process(11).
The management of diabetes is a lifelong task, and patients are responsible on a regular basis. This requires more patient self-management and active engagement in their healthcare processes (12). Today, information and communications technology (ICT) is increasingly being used in the management of diabetes mellitus to improve the quality of care (12, 13). Routine controls and follow-ups can be done remotely to reduce patient’s unnecessary hospital visits. Care providers can check their patients’ health status digitally with wearable remote patient monitoring devices integrated with the patient portal system. (14, 15).
Diabetes mellitus is a chronic disease in which the body is unable to control the amount of glucose, and its essential symptom is high blood glucose levels. The pancreas does not produce insulin in type 1 diabetes, while it does less in type 2 diabetes. Commonly, it can lead to serious damage to the body's organs (16, 17). It is becoming a major global public health issue, with more than a half billion adults living with it and 1.5 million deaths attributed to it each year (16, 18, 19). According to a World Health Organization report, more than 24 million adults are living with diabetes in Africa, and it's anticipated to reach 55 million by the year 2045 (20, 21). Similarly, according to the International Diabetes Federation report, Ethiopia is one of the leading countries among the top five most prevalent nations in Africa(20).
Effective diabetes management requires continuous communication between patient and care provider. As a result, ICT is increasingly being used in diabetes patients’ care. As well as, promoting patient-centered care and empowering patient’s engagement are important to improve quality of care(22), and health information technologies have a significant role to play in achieving these goals and also helping patients manage their health more effectively(2, 23).
Despite the increasing availability of the patient portal, provider enthusiasm, and the tool’s potential benefits, its adaption is very low (24) and little is known about it by patients. According to the literature, patient portals were being used by less than 7% of the total number of healthcare consumers worldwide (25, 26). Moreover, adopting portal technology is still facing difficulties in developing countries (27). Patient portals, one initiative of the Ethiopian Federal Ministry of Health's digital health plan to provide patients access to their medical records, offer great promise to improve patient health and satisfaction with their care, as well as professional and organizational effectiveness in the health care system (6). However, currently, the patient portal is not implemented in Ethiopia, but different EMR systems are being implemented in the health care institution, which are being used, managed, and accessed only by health care professionals. This EMR system doesn’t promote patient-centered healthcare by itself since it denies patients the right to access their health care data. So in order to give access rights to the patient, those EMR systems have to integrate with the patient portal.
The possible barriers at the patient and provider levels that are associated with low adoption of patient portals have been identified in several studies. Lower socioeconomic status, older age, rural residence, male gender, and public or no insurance are consistently linked to lower adoption of patient portals (28–30). There are also numerous barriers identified by studies, including low digital literacy, a lack of internet access, privacy concerns, and the existence of multiple provider-specific portals (31–34). The studies done by UTAUT2 show that performance expectancy, effort expectancy, facilitating condition, social influence, price value, habit, hedonic motivation, and self-perception are indicated as possible factors for low patients’ behavioral intention to use the patient (35, 36).
Among the various factors contributing to the successful implementation of technologies, the user’s perception and acceptance are important for sustainable technology adoption. According to the Unified Theory of Acceptance and Use of Technology, the adoption of new technology is dependent on the user's behavioral intention(37). Effective technology use is also the result of an intention, and this intention is influenced by different factors(37, 38). Therefore, in order to adapt and implement the patient portal for our country's healthcare system, it is crucial to understand how patients intention to use it and identify the predictors that influence their intention to use patient portals. So the aim of this study is to determine the intention to use a patient portal and its predictors among diabetes mellitus patients in Ethiopia.
1.1 Theoretical model background
To determine the association between the independent and dependent variables, the "Unified Theory of Acceptance and Use of Technology" has been introduced as one of the most widely accepted model (38). This model was derived from eight other theoretical models, including the Theory of Reasoned Action, Social Cognitive Theory, Technology Acceptance Model, Theory of Planned Behavior, Motivational Model, Model of PC Utilization, Combined TAM and TPB, and Innovation Diffusion Theory (37, 38). A unified theory of acceptance and use of technology was introduced by Venkatesh to predict acceptance and use of technology (37).
The Unified Theory of Acceptance and Use of Technology Extended (UTAUT2) theory has three main structural components, such as exogenous, endogenous, and moderators, similar to the original UTAUT model, with substantial modifications in constructs and moderators. As a result, the UTAUT2 model added three significant constructs, including hedonic motivation, price value, and habit, as independent variables in addition to the four variables shared with UTAUT (performance expectancy, effort expectancy, social influence, and facilitating conditions), with moderators age, sex, and experience(37).
In this study, we adapt the Venkatesh UTAUT2 model into eight independent constructs, one dependent construct, and two moderators. Actual use behavior, which was considered a dependent variable and moderator experience in the original UTAUT2, was not assessed in this study due to the fact that the investigated technology was a predicted technology that has not been implemented currently in Ethiopia, and there is no current actual use of the patient portal in the referral hospitals under the study. Digital literacy was used as an independent construct in addition to the original UTAUT2 model constructs in our study as indicated in Fig. 1.
According to the literature, the potential user’s intention towards the technology is the most important determinants of its acceptance and sustainability(37, 39). The user's desire to use technology in the future is explained by their intention to use it. In this study, behavioral intention to use patient portal was used as an outcome variable since it has been found to be a substantial determinant of actual patient portal usage (40–42). In general the adoption of patient portals has varied from country to country due to different factors, and the factors affecting consumer behavioral intention to use and actual use behavior may also vary(7, 11). So it’s important to investigate the level of patients’ intentions and predictors in the context of our country in order to adapt the technology.
According to technology acceptance literature, predictors that are affecting the patients’ intention to use the patient portal are perceived usefulness, perceived ease of use, facilitating condition, social influence, hedonic motivation, price value, and habit (36, 37, 43). And the moderators’ age, gender, and experience have an effect on the association between behavioral intention to use the patient portal and its predictors. These moderators can alter the intensity and direction of the association. The effects of PE on behavioral intention were moderated by age, gender, and experience, with a greater effect among younger males (37, 38). Incomparable to this, the impact of EE on behavioral intention was moderated by age and gender, with younger women experiencing a higher impact (37, 38, 44). The influence of SI on behavioral intention was moderated by age and gender, with older women experiencing a higher impact (37, 38). Although the influence of FC on behavioral intention was moderated by gender and age, with older women being more strongly affected (37). And also, the impact of HM on behavioral intention was moderated by age and gender, with younger males experiencing a higher impact (37).
Performance expectancy is defined as the degree to which using a technology will provide benefits to consumers in carrying out certain activities (38, 43, 45, 46). According to our literature review health care consumers are more likely to adapt e-Health technologies that provide clear benefits, such as obtaining an electronic medical prescription through patient portals (23, 47–49). The following are the proposed hypothesis to test the effect of PE on behavioral intention to use patient portal.
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H1: performance expectancy has a positive influence on patients’ intentions to use the patient portal.
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H2: The effect of performance expectancy on diabetes patients' intentions to use the patient portal is moderated by gender.
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H3: The effect of performance expectancy on diabetes patients' intentions to use the patient portal is moderated by age.
Effort Expectancy (EE): Effort expectancy is the level of comfort a consumer can expect when using technology (38, 46). The easier it is for consumers to understand and use an e-Health technology, the more likelihood that consumers to adapt it (23, 43, 48–50). The following are the proposed hypothesis to test the effect of EE on behavioral intention to use patient portal.
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H4: Effort expectancy has a positive influence on patients’ intentions to use the patient portal.
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H5: The effect of effort expectancy on diabetes patients' intentions to use the patient portal is moderated by gender.
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H6: The effect of effort expectancy on diabetes patients' intentions to use the patient portal is moderated by age.
Social Influence (SI): refers to how much a consumer believes others who are significant to them such as friends and family, believe they should use a particular technology(37). In the context of e-Health, this can also be a crucial concept because people who have the same diseases tend to be influenced by others who also have the conditions (51–53). In the other study it’s not significant predictor of behavioral intention to use the technology (35). The following are the proposed hypothesis to test the effect of SI on behavioral intention to use patient portal.
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H7: SI has a positive influence on patients’ intentions to use the patient portal.
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H8: The effect of social influence on diabetes patients' intentions to use the patient portal is moderated by gender.
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H9: The effect of social influence on diabetes patients' intentions to use the patient portal is moderated by age.
Facilitating Condition (FC): is defined as the individual perception of the support available for using a technology activity (37). The lack of resources for consumers to access these platforms is one of the obstacles to their use of health services over the Internet, suggesting that users with better access to e-Health technologies will favor the adoption of EHR portals(48). In another study facilitating condition has no significant effect on behavioral intention to use portal (35). The following are the proposed hypothesis to test the effect of FC on behavioral intention to use patient portal.
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H10: Facilitating condition has a positive influence on patients’ intentions to use the patient portal.
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H11: The effect of facilitating condition on diabetes patients' intentions to use the patient portal is moderated by gender.
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H12: The effect of facilitating condition on diabetes patients' intentions to use the patient portal is moderated by age.
Hedonic motivation (HM): is defined as intrinsic motivation (enjoyment) and has been taken into account as a significant predictor in many of studies on consumer behavior (37). When a patient has a chronic disease, getting and handling information about their health status using e-Health technologies may or may not be a pleasant process. Hedonic motivation, however, was discovered to have a significant influence on behavioral intention in a recent study with UTAUT2 in e-Health (54). On the contrary in another study shows that there is no meaningful correlation exists between hedonic motivation and behavioral intention. Patients don't seem to enjoy using portals, which is likely due to the fact that the presence of a disease drives much of the usage of portals (35, 55, 56). The following are the proposed hypothesis to test the effect of HM on behavioral intention to use patient portal.
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H13: Hedonic motivation has a positive influence on patients’ intentions to use the patient portal.
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H14: The effect of hedonic motivation on diabetes patients' intentions to use the patient portal is moderated by gender.
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H15: The effect of hedonic motivation on diabetes patients' intentions to use the patient portal is moderated by age.
Price value (PV): in a consumer use environment is also a relevant factor as, unlike workplace technologies, consumers must bear the costs related with the purchase of devices and services(37). If patients can obtain their medical prescription, appointment and other service via patient portal, they can save transportation costs by avoiding unnecessary travel to a health institution. The better health care service consumer has about the price value of an e-Health technology can help save money, the more likely they intend to use it (57), older people tend to give more importance to price in e-Health (58). On another study PV has no significant effect on behavioral intention to use the technology(35). The following are the proposed hypothesis to test the effect of PV on behavioral intention to use patient portal.
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H16: PV has a positive influence on patients’ intentions to use the patient portal.
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H17: The effect of price value on diabetes patients' intentions to use the patient portal is moderated by gender.
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H18: The effect of price value on diabetes patients' intentions to use the patient portal is moderated by age.
Habit (HA): is the degree to which people carry out behaviors unconsciously after learning (37). Since habit is a concept that should not be exclusive to an IT technology, we can anticipate that habit will positively influence e-Health adaption, as it has in other IT adoption fields. According to the review of the literature, women and younger people have a habit of using e-Health technologies more frequently (59, 60). The following are the proposed hypothesis to test the effect of HA on behavioral intention to use patient portal.
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H19: Habit has a positive influence on patients’ intentions to use the patient portal.
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H20: The effect of habit on diabetes patients' intentions to use the patient portal is moderated by gender.
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H21: The effect of habit on diabetes patients' intentions to use the patient portal is moderated by age.
Digital literacy: is the awareness, attitude, and skill of individual to use digital technologies and facilities to identify, access, manage, integrate, evaluate, and synthesize digital information, create new knowledge, communicate with others, and use in the context of certain health or other life activity(61, 62). Many studies have explored the relationship of digital literacy and intention to use. A study’s reports that digital literacy positively impact the intention to use digital technology(63, 64). And also in other study stated that a higher digital literacy would have a positive impact on users’ effectiveness and a direct influence on their intention to use digital technology (65).
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H22: Digital literacy has a positive influence on patients’ intentions to use the patient portal.
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H23: The effect of digital literacy on diabetes patients' intentions to use the patient portal is moderated by gender.
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H24: The effect of digital literacy on diabetes patients' intentions to use the patient portal is moderated by age.