An institutional-based cross-sectional study design was used.

The study was conducted in all 5 public hospitals in the East Wollega Zone of western Ethiopia, specifically 2 referral hospitals and 3 primary hospitals, from March 2024 to June 2024. The selected hospitals were Wollega Comprehensive Specialized Hospital, Nekemte Specialized Hospital, Gida Hospital, Arjo Hospital, and Sire Hospital. These public health facilities provide preventive, primary, general, referral, and specialized services, staffed by a total of 2917 health care providers. They serve a population of 1,500,999, comprising 726,741 females and 774,258 males, in both urban and rural areas of East Wollega Zone.

The study included all 5 public hospitals in East Wollega Zone. The sampling frame consisted of a list of health care professionals working in these hospitals. Based on the nature of service delivery, health care professionals included were physicians, medical laboratory technologists, anesthetists and anesthesiologists, pharmacists, nurses, and midwives. Informed consent was obtained from all selected participants.

For sampling and sample size calculation, the sampling frame was obtained from the respective human resources administrative offices, which provided the total number of health care providers working in the selected public hospitals of the East Wollega Zone; this was calculated to be 916. The total sample was calculated using proportional allocation and systematic random sampling techniques across all 5 hospitals.

To achieve proportional allocation, the constant K value was calculated, resulting in a value of 2. An initial number was randomly selected from 1 to 2, and a study participant was chosen at every second interval from all selected public health facilities in the East Wollega Zone. A total sample size of 422 was calculated from each hospital: Nekemte Specialized Hospital (n=159, 37.7%), Wollega University Comprehensive Specialized Hospital (n=122, 28.9 %), Sire Hospital (n=41, 10%), Arjo Hospital (n=47, 11%), and Gida Hospital (n=53, 13%)

In this study, the data collection used a comprehensive 3-part questionnaire designed to gather relevant information from participants. The first part of the questionnaire focused on demographic information, where participants provided details about their personal and professional backgrounds. This section included questions regarding their names, ages, sex, designations, computer knowledge, and professions, allowing for a thorough understanding of the respondents.

The second part aimed to assess the knowledge level of the participants regarding telehealth, validated and adapted from a previous study [17]. It comprised 11 statements, each requiring a “1=Yes” or “0=No” response. This scoring system enabled participants to achieve a minimum score of 0 and a maximum score of 11, reflecting their knowledge about telehealth. Although we used surveys with identical items from those published in the literature, formal psychometric validation of this measure was not conducted. Therefore, observed differences should be interpreted as descriptive rather than indicative of true differences in the underlying of this construct.

The third part evaluated the respondents’ perceptions of telemedicine through 11 statements, adopted from previously validated tools [18]. Participants responded using a 5-point Likert scale, ranging from 0 (strongly disagree) to 4 (strongly agree). This section allowed for a cumulative score between 0 and 44, providing insights into how health care professionals perceived telehealth. Although we used surveys with identical items from those published in the literature, formal psychometric validation of this measure was not conducted. Therefore, observed differences should be interpreted as descriptive rather than indicative of true differences in the underlying of this construct.

To facilitate the data collection process, trained data collectors distributed the structured questionnaires to participants. A team of 4 data collectors and 2 supervisors was recruited to carry out this task over a period of 2 consecutive months.

Official approval to conduct this study was obtained from the Office of Research and Technology Transfer Vice President at Wollega University. A letter of permission was then distributed to the respective hospitals, ensuring that all necessary approvals were in place to proceed with the study. Informed consent was obtained from all study participants, making it clear that their participation was voluntary and that they could withdraw at any time. The privacy of the study participants was ensured by removing personal identities, and their data were not disclosed to other parties. Moreover, participants' confidentiality was upheld by protecting their data, which was only shared for the purpose of the study based on the consent obtained.

To ensure the quality of the data collected, all questionnaires were developed in English and subsequently translated into Afan Oromo, the local language. This translation was then retranslated back into English by experts to verify accuracy. A pretest was conducted with 5% of the sample size at Ghimbi General Hospital prior to the main data collection. Data collectors and supervisors received 1 day of training to prepare them for their roles. During the data collection phase, the data were cleaned, coded, and checked for consistency and completeness. A double-entry method was used to enhance data quality, allowing for cross-checking of any inconsistent entries and responses.

After data collection, the information was cleaned, edited, coded, and entered into EpiData (version 3.1; EpiData Association). It was then exported to SPSS Windows version 24 (IBM Corp) for analysis. Descriptive statistics, including percentages, ratios, frequency distributions, and pie charts, were used to summarize the data. The Hosmer and Lemeshow test will be used to evaluate the homogeneity of the variables. All variables that are significant at a P<.05 in the bivariable analysis were included in the multivariate logistic regression analysis. To ascertain the most suitable variables for the multivariate logistic regression, a backward stepwise goodness-of-fit approach was used. Finally, multivariate logistic regression analysis was conducted, reporting adjusted odds ratios (AORs) at 95% CIs, with a significance level set at P<.05.

The final report of the study was submitted in both soft and hard copies to the Wollega University Institute of Health Sciences Research Affairs Directorate, School of Nursing and Midwifery, Department of Nursing. The document was also distributed to each hospital participating in the study. In addition, the findings were presented in national and international workshops and conferences.

A total of 397 participants were enrolled in the study, resulting in a response rate of 94.1%. Among the respondents, the majority were male participants (n=238, 59.9%). Approximately half of the participants, 199 out of 397 (50.1%), were aged between 30 and 39 years. In terms of ethnic background, 382 out of 397 (96%) participants identified as Oromo, and Afan Oromo was the predominant language spoken by 383 out of 397 (96.5%) participants.

Regarding professional affiliation, most participants were nurses, comprising 221 out of 397 (55.7%), followed by physicians, who accounted for 60 out of 397 (15.1%). In addition, over half of the respondents, 227 out of 397 (57.2%), identified as Protestant. In relation to work experience, nearly half, 197 out of 397 (49.6%), reported serving for a duration of 6 to 10 years, with the majority earning a monthly wage between Ethiopian Birr 7001 and 9000 (a currency exchange rate of Ethiopian Birr 52=US $1 during the study period; Table 1).

Participants’ familiarity with various types of information technology services is essential for the effective implementation of telehealth among health professionals. Regarding smartphone use, the majority, 246 out of 397 (62%), reported owning a smartphone. However, more than half, 220 out of 397 (55.2%), had never participated in training on computer systems and ICT, while over a third, 150 out of 397 (37.8%), had received introductory-level training. In addition, a significant portion, 305 out of 397 (76.8%), did not use computers regularly. Among those who did, 137 out of 397 (34.5%) primarily used computers for word processing and database management, while 113 out of 397 (28.5%) used them for entertainment purposes.

In terms of internet use, 167 out of 397 (42.1%) accessed the internet daily, followed by 72 out of 397 (18.1%) who reported weekly use. When examining the types of internet applications, more than half, 212 out of 397 (53.4%), indicated they used social media, followed by email and messaging services, which were used by 79 out of 397 (19.9%). Furthermore, regarding the use of medical-related websites, nearly two-thirds, 260 out of 397 (65.5%), reported that they had not visited such sites (Table 2).

In the context of increasing digitalization and technological advancements in health care, telehealth presents a range of clinical applications. This study revealed that the majority of telehealth applications—160 out of 397 (40.3%) participants—are focused on chronic conditions, followed by gynecological diseases, which accounted for 93 out of 397 (23.4%) participants. When considering the specific purposes of telehealth, nearly two-thirds, or 119 out of 397 (30%) participants, viewed it as a means to enhance accessibility and convenience, while one-fourth, 100 out of 397 (25.2%), believed it improves patients’ quality of life.

Regarding sources of information about telehealth, nearly two-thirds of participants reported that they learned about it from the internet (141 out of 397, 35.5%) and from colleagues (134 out of 397, 33.8%). Furthermore, more than two-thirds of the study participants, totaling 267 out of 397 (67.3%), had not attended telemedicine consultation sessions (Table 3).

The findings of this study revealed that 270 (68.01%) health professionals had a good level of knowledge about telemedicine, while 127 (32%) were poorly knowledgeable. Regarding perceptions of telehealth medicine implementation, 247 (62%) professionals expressed a positive perception, whereas 150 (38%) had a negative view.

In the bivariable logistic regression analysis, several variables were found to be significantly associated with knowledge of implementing telehealth. Specifically, the factors identified include sex, educational level, work experience, computer and ICT training, level of income, computer use, previous attendance at telemedicine consultations, and smartphone use; all with a significance level of P<.05 (Table 4). These findings suggest that demographic and training-related factors may play a crucial role in enhancing health care professionals’ understanding and implementation of telehealth practices.

All variables significant at a P<.05 in the bivariable logistic regression were included in the multivariable logistic regression analysis. The following factors were found to be significantly associated with knowledge of implementing telehealth: higher educational level (Master’s degree and above), higher income level, access to computer usage, attendance at telehealth consultation sessions, and access to smartphone use.

Individuals with a higher educational status, such as MD and above, were nearly 3 times more likely to have knowledge of implementing telehealth compared to those with only a diploma (AOR 2.797, 95% CI 2.019-26.872). Those holding an MD and above were about as likely to be knowledgeable about implementing telehealth compared to diploma holders (AOR 4.22, 95% CI 3.45-13.12). Regarding income level, individuals earning between 7000 and 9000 birr monthly were more than 4 times more likely to be knowledgeable about implementing telehealth compared to those earning between 3000 and 5000 birr (AOR 4.11, 95% CI 1.23-9.12).

In terms of computer use, individuals with experience using computers were over twice as likely to be knowledgeable about implementing telehealth compared to those without such experience (AOR 2.414, 95% CI 1.046-14.764). Moreover, those who had attended telehealth consultation sessions were more than twice as likely to possess knowledge about implementing telemedicine compared to those who had not attended such sessions (AOR 2.389, 95% CI 1.961-10.158). Finally, smartphone users were nearly 3 times more likely to be knowledgeable about implementing telehealth compared to nonusers (AOR 3.027, 95% CI 2.797-14.729; Table 5).

In the bivariable logistic regression analysis, several variables were found to be significantly associated with the perception of implementing telehealth. Specifically, the factors identified include sex, work experience, computer and ICT training, level of income, computer usage, previous attendance at telehealth consultations, daily internet use, perceived benefits of telemedicine for improving quality of life, accessibility of services, convenience, and smartphone use at a significance level of P<.05 (Table 6).

All variables that were significant at a P value of <.05 in the bivariable logistic regression were included in the multivariable logistic regression analysis. The following factors were found to be significantly associated with perceptions of implementing telehealth: higher income level, work experience, attendance at telehealth consultation sessions, perceived benefits of telehealth, and access to smartphone use.

Individuals with 1 to 5 years of experience were less likely to have a positive perception of implementing telehealth compared to those with more than 16 years of experience (AOR 0.0562, 95% CI 0.020-0.233). Regarding income level, individuals earning more than 9000 birr monthly were nearly 3 times more likely to have a positive perception of implementing telehealth compared to those earning between 3000 and 5000 birr (AOR 2.675, 95% CI 2.271-19.277).

In terms of the perceived benefits of telemedicine, individuals who experienced its use for improving quality of life were nearly twice as likely to have a positive perception of implementing telehealth compared to those who perceived it primarily for ensuring data safety and security (AOR 1.786, 95% CI 1.575-22.587). In addition, individuals who perceived telehealth as a means of improving accessibility and convenience were 1.244 times more likely to have a positive perception compared to those focused on data safety and security (AOR 1.244, 95% CI 1.061-11.333).

Moreover, those who had attended telehealth consultation sessions were nearly twice as likely to possess a positive perception of implementing telehealth compared to those who had not attended such sessions (AOR 4.777, 95% CI 2.318-15.062). Finally, smartphone users were nearly 2 times more likely to have a positive perception of implementing telehealth compared to nonusers (AOR 3.836, 95% CI 2.900-13.573)(Table 7).

The limited implementation of telehealth in Ethiopia, with less than 10% adoption, can be attributed to several factors hindering its advancement [20,21]. In this cross-sectional study, we aimed to assess the level of knowledge and perception of health professionals regarding telemedicine implementation in the East Wollega Zone of the Oromia region, western Ethiopia. We identified significant factors associated with the knowledge and perception of telehealth implementation among targeted individuals, which contribute to the digitalization of global health care systems for better access to health care services.

The results indicated that approximately 68.01% (270/397) of participants possessed a good level of knowledge, which exceeds that reported in previous research conducted in referral hospitals in northwest Ethiopia (56.4%, 37.6%, 65.8%, and 40.7%), and Saudi Arabia (46.1%) [18,22-25]. Conversely, the knowledge level in our study was higher than findings from Nigeria and Iran (34.5% and 3.9%, respectively) [26,27] . This disparity may be linked to lower accessibility to information and training regarding telehealth at the national level, geographical impact to access relevant resources, and impact of the COVID-19 pandemic, as studies conducted during the outbreak.

Furthermore, our findings revealed that 62% (247/397) of health professionals held a positive perception of implementing telehealth, surpassing the results of a study conducted in Addis Ababa, Ethiopia, where approximately 60.9% of professionals expressed a positive perception toward telehealth [28,29]. In contrast, it was lower compared to the studies reported in India, where 73.14% of participants had a positive perception, and in Saudi Arabia, where the figure was 90%; another study reported 65.2% positive perception of implementing telemedicine in India [18,29,30]. These differences may reflect variations in technological advancement, accessibility, and economic conditions across the regions studied.

In this study, higher educational status was identified as an independent factor associated with knowledge of telehealth, considering the joint effects of other variables. Professionals with a higher level of education were 3 times more likely to possess good knowledge of implementing telemedicine compared to those with a lower educational level, such as a diploma. This finding aligns with a study conducted in northern Ethiopia, which revealed that individuals with a degree or higher had significantly increased knowledge scores related to telehealth [31]. These similarities suggest that a higher educational level contributes to greater exposure to various sources of information about telehealth, thereby enhancing understanding.

Moreover, the findings of this study indicated that health professionals with access to smartphones were nearly twice as likely to have a positive perception of implementing telehealth compared to non-users. This is consistent with a study conducted in central Ethiopia, which found that participants with sufficient access to computers or smartphones were more likely to have a favorable perception of using telehealth than those lacking adequate devices (32). This similar finding underscores the importance of accessibility to technological resources for exchanging information and disseminating knowledge about the purpose of telehealth, thereby enhancing positive beliefs toward its implementation [28].

This study has several limitations as follows:

In conclusion, the findings of the study revealed a relatively higher level of knowledge and perception in implementing telehealth. Educational status, income, computer and smartphone use, and exposure to telehealth training were factors associated with the knowledge of implementing telehealth, whereas income level, work experience, exposure to telehealth training sessions, perceived benefits of telehealth, and access to smartphone use were factors associated with the perception of telemedicine.

Based on the study’s findings, it is recommended to enhance educational programs for health professionals to improve their knowledge of telehealth, particularly targeting those with lower educational backgrounds. Increasing access to smartphones and computers, along with providing regular training sessions and awareness campaigns about the benefits of telehealth, will further bolster positive perceptions. In addition, addressing income disparities and fostering collaborative learning environments can significantly contribute to a more favorable attitude toward telehealth implementation.