The high burden of emerging and re-emerging infectious diseases in Nigeria underscores the need for electronic health. This study determined the knowledge and utilization of e-Health care delivery among health care professionals in federal teaching hospital Abakaliki (FETHA) Ebonyi State. A self-developed questionnaire was used for the study. Two specific objectives with four null –hypotheses were postulated to guide the study. Out of a population of 2092 health workers in FETHA, 209 representing 10% were drawn through a multistage sampling technique and were studied. Frequency and percentage were used to answer research question one, Mean statistic was used to answer research questions two, Analysis of Variance (ANOVA) was used in testing null-hypotheses one and two while Binomial Logistics Regression was used in testing hypotheses three and four at .05 level of significance and appropriate degree of freedom. The findings indicated that health care professionals in FETHA possessed good knowledge of e-Health care delivery with an overall per cent (85.6%). The findings further show that utilization of e-Health care delivery was low (x̅= 2.14). The four null-hypotheses tested shows that there is no statistical significant difference in level of knowledge by age (P=.236 >0.05), level of utilization by age (P-value =.087>0.05), level of knowledge by gender (P-value=.051>0.05), level of utilization by gender (P-value = .908>0.05). The study concluded among others that Nigerian government at all level, through their various ministries of health should organize intensive ICT training and retraining of health workers regarding e-Health use in health care delivery.
Keywords: E-Health care delivery, e-Health Tools, Knowledge and Utilization, Health care professionals, Federal teaching hospital, Ebonyi State Nigeria.
Received: 20 May 2020 / Revised: 23 June 2020 / Accepted: 27 July 2020/ Published: 18 August 2020
This Study Contributes to the Existing Literature by Evaluating the Knowledge and Utilization of E-Health Care Delivery among Health Care Professionals in Federal Teaching Hospital Abakaliki, Ebonyi State, Nigeria.
The application of information communication technology (ICT) in health care delivery is not merely about technology but a means to solve the critical data management and clinical communication challenges in health care organizations [1]. Over the years, technology has touched the acme of human development and now it is not confined to developed countries. In developing countries healthcare providers can no longer ignore the application of information technology to healthcare delivery hence the concept e-Health, or electronic health[2].
E-Health is the leveraging of information and communication technology (ICT) to connect providers, patients, and governments; to educate and inform health care professionals, managers and consumers; to stimulate innovation in health care delivery and health system management [3]. E-Health which serves as a medical record used to capture, store, and share information among healthcare providers also serves in delivering of healthcare services to patients[4-6].
E-Health has a broad areas of services such as electronic health records to ensure continuity of patient care across time, mobile health (m-Health) services, telehealth, health research, consumer health informatics to support individuals in health decision making, eLearning by health workers Computerized physician order entry, ePrescribing, Clinical decision support system, Telemedicine, Health knowledge management, Virtual health care teams, Medical research using grids, Health informatics/health care information systems[7]. With the development of this new technology including Web 2.0 and 3.0 communication media, the field of e-Health has emerged and with it a plethora of new opportunities for individuals to access and exchange health information, manage their health through electronic platforms, and participate in peer-to-peer health care[8-10]. These online opportunities have been identified as a means to better enable health care providers/patient empowerment and self-management of care without face-face contact [11].
The wide areas of e-Health has enabled public health and medical practitioners to communicate with patients in both traditional and novel ways to address health concerns such as diabetes management, heart health, cancer prevention, smoking cessation, health promotion activities among others[12-18] . This Online strategies including adaptations of more traditional communication methods such as the delivery of tailored information and the creation of support networks, such as the implementation of Smartphone applications for disease prevention and management has yielded much benefits in health care delivery [19-21] .
Studies have observed that the use of e-Health care delivery is growing and has recorded a huge success in health care systems in developed countries [22-25] .However, in developing countries including Nigeria it has been reported that its implementation have achieved little success with low utilization[22-24] . Given the high burden of disease incidence/prevalence in Nigeria including emerging and re-emerging infectious diseases and the high rate of contact cases among health care professionals and the emerging trends in the nation’s healthcare systems and the low number of skilled personnel, e-Health is believed and has been identified to improve health care by strengthening the health system, supporting delivery of care, and improving communication without necessarily face-to-face contact among health care providers with patient.
Studies in developing countries have highlighted the following drawbacks as the factors affecting e-Health care delivery such as: lack of knowledge about ICT; unreliable ICT equipment; lack of availability of ICT equipment, high cost of ICT; low level of skills of potential users; technology compatibility; and limited access to ICT as challenges hindering e-Health use [26-29] . Studies also further highlighted lack of ICT infrastructure, access, skills and reluctance to use e-Health in healthcare services have been reported also as challenges in the use of ICT in health care delivery [30, 31]. It has been observed that the success of any new technology depends on many factors including the knowledge and understanding of the concept, skills, working environment and the effective utilization of the technology in health care delivery by the health care professionals [30-32] .
It is therefore not known if health care professionals in FETHA possessed good knowledge and have effective use of e-health care delivery in FETHA Ebonyi State, Nigeria. Hence, Ebonyi State, Nigeria is a new State with its own health system at the developmental stage; therefore, it is essential to determine the knowledge and utilization of e-Health care delivery among health care professionals in Federal Teaching Hospital Abakalik (FETHA) Ebonyi State. To the best knowledge of this researcher, no such studies have been carried out in FETHA, Ebonyi State. It is therefore not known if the factors highlighted above influences e-Health care delivery among health care professionals in FETHA, Ebonyi State. Again, for the fact that Ebonyi State is a new State with its own health system at the developmental stage, it is not unlikely that the factors reviewed above may be influencing e-Health care delivery among health care professionals in FETHA, Ebonyi State. The present studytherefore examined the knowledge and utilization of e-Health care delivery among health care professionals in FETHA, Ebonyi State, Nigeria.
2.1. Research Design
A descriptive cross sectional research design was conducted between August 12th 2018 – January 11th 2019 on knowledge and utilization of e-health care delivery among health care professionals in Federal Teaching hospital Abakaliki (FETHA), Ebonyi State, Nigeria.
2.2. Research Area
The area of the study is Federal Teaching Hospital Abakaliki (FETHA), Ebonyi State, Nigeria. FETHA is located in the heart of Abakaliki, the capital of Ebonyi State.It is the federal and the biggest hospital in Ebonyi State with about 608 beds. It is also a training institution for medical students, nursing students, medical laboratory science students among others. Just recently, it started receiving students from the new Federal University, Ndufu Alike Ikwo in Ebonyi State. Generally, the hospital renders primary as well as specialist services to those in need within and outside Ebonyi State. Being the largest tertiary and federal hospitals in the state, it receive clients directly and referrals from general hospital and nooks and crannies of the 13 local government areas of Ebonyi State and beyond.
2.3. Population of the Study
The population of the study consisted of 2,092 staff comprising of 200 consultants in various specialties, 467 resident doctors undergoing residency training, 1,070 Nurses, 189 Med Lab, 56 Radiographers and 110 Pharmacists totaling 2,092 health care professionals in FETHA.
2.4. Sampling Technique and Sample Size
The sample for this study is 209 health care professionals in FETHA. This represented 10 per cent of the total population. This is in line with the rule of the thumb which stated that, when a population is in a few thousand, five to ten per cent of the population will be deemed appropriate to determine the sample size[33].The total sampling was stratified into different departments where 10% were proportionately drawn from the population of each of the department or unit. These are consultant 20, resident’s doctors 47, nursing 107, medical laboratory 19, radiography 7, and pharmacy 11 staff. This process gave a total of 209 sampled staff that was studied.
2.5. Instrument for Data Collection
A self developed instrument was used for data collection. The instrument was titled,Knowledge and Utilization of e-Health Care Delivery Questionnaire (KUEHCDQ). A pilot study was done among 20 health care professionals working in National Fistula Center (NAFIC), Abakaliki who were not included in the study but possessed similar characteristics. The internal consistency of each subscale was computed separately. The overall reliability coefficient of the instrument was 0.72. The instrument was then considered reliable to be distributed to the research participants from FETHA. This was in consonance with the assertion that in reliability test, if the reliability co-efficient index of an instrument is .60 and above, the instrument should be deemed reliable enough to be used in a study [34].
2.6. Method of Data Collection
An approval letter to carry out this study was collected from Research and Ethics Committee (REC) of the hospital. The letter enabled the researcher to gain access to head of different departments concerned and the respondent. Informed consent was explained in writing and obtained from all participants. The (KUEHCDQ) was administered by the researcher and two research assistant to all eligible respondent in FETHA on a unit basis.
2.7. Data Analysis
The completed copies of the KUEHCDQ were collected and crosschecked for completeness of information and responses. All statistical analysis was done using the Statistical Package for Social Science (SPSS) batch system. Frequency and percentage were used to answer research question one, where a percentage between 0.1 and 50 was adjudged poor knowledge while between 51 and 100% was adjudged good knowledge. Mean was used to answer research questions two, where a mean between 2.4 and below was adjudged low utilization of e-Health tools while mean between 2.5 and above was adjudged good levels of utilization of e-Health. The Analysis of Variance (ANOVA) was used in testing null hypotheses one and two while Binomial Logistics Regression was used in testing hypotheses three and four at .05 level of significance and appropriate degree of freedom. The results were illustrated using tables.
2.8. Ethical Consideration
The Institutional Research and Ethics Committee (REC) of Federal Teaching Hospital Abakaliki (FETHA) provided ethical approval with clearance numbers FETHA/REC/VOL.2/2018/079 and REC APPROVAL NUMBER 11/07/2018- 30/07/2018 respectively.
Research Question 1: What is the knowledge of health care professionals about e-Health use in health care delivery in FETHA?
Table-1. Mean Responses regarding knowledge of health care professionals about e-Health use in health care delivery in FETHA.
| S/N | Meaning of E-health | Yes |
% Rating |
No |
% Rating |
| 7. | E-Health is the use of electronic health in health care delivery | 183 (91.5%) |
Good |
17 (8.5%) |
Poor |
| 8. | It is the application of information and communication technologies (ICT) for health | 203 (97.1%) |
Good |
6 (2.8%) |
Poor |
| 9. | E- health could also mean mobile health | 172 (83.5%) |
Good |
34 (16.5%) |
Poor |
| 10. | e-health is a part of health system and services | 196 (95.1%) |
Good |
10 (4.9%) |
Poor |
| 11. | It is a relatively recent healthcare practice that uses electronic processes and communication | 203 (96.7%) |
Good |
6(2.9%) |
Poor |
| Cluster % and ratings | 92.8% |
Good |
7.2% |
Poor |
|
| E-health services | |||||
| 12. | Provides easy communication of patient data between different healthcare professionals | 208 (99.5%) |
Good |
1(.5%) |
Poor |
| 13. | Offers platform for requesting diagnostic tests and treatments electronically and receiving the results | 198 (94.7%) |
Good |
11 (5.3%) |
Poor |
| 14. | E-health offers access to prescribing options and printing prescriptions to patients | 192 (93.7%) |
Good |
13 (6.3%) |
Poor |
| 15. | E-health services include electronic transmission of prescriptions from doctors to pharmacists | 182 (88.3%) |
Good |
24 (11.7%) |
Poor |
| 16. | It provides information electronically about protocols and standards for healthcare professionals to use in diagnosing and treating patients | 193 (92.8%) |
Good |
15 (7.2%) |
Poor |
| 17. | It provides physical and psychological diagnosis and treatments at a distance, including tele-monitoring of patients functions; | 155 (74.9%) |
Good |
52 (25.1%) |
Poor |
| 18. | Health knowledge management is an importance service of e-health | 194 (93.7%) |
Good |
12 (5.8%) |
Poor |
| 19. | E health offers solutions for appointment scheduling, patient data management, work schedule management and other administrative tasks surrounding health | 187 (92.1%) |
Good |
16 (7.9%) |
Poor |
| Cluster % and ratings | 91.2% |
Good |
8.8% |
Poor |
|
| Channels of E-health Delivery | |||||
| 20. | E-health can be delivered through visual communication | 154 (76.2%) |
Good |
48 (23.8%) |
Poor |
| 21. | Internet can be used to deliver e-health services | 196 (94.2%) |
Good |
12 (5.8%) |
Poor |
| 22. | E-health can be provided through Facebook | 164 (80.8%) |
Good |
39 (19.2%) |
Poor |
| 23. | Landline Phone can be used to deliver health care | 161 (79.7%) |
Good |
41 (20.3%) |
Poor |
| 24. | Twitter is another good means of delivering e-health service | 169 (82.8%) |
Good |
35 (17.2%) |
Poor |
| 25. | Instagram is a means of proving health care services | 168 (82.4%) |
Good |
36 (17.6%) |
Poor |
| 26. | Health care can be carried-out through Email | 176 (87.6%) |
Good |
25 (12.4%) |
Poor |
| 27. | Fax is used to deliver e-health services | 158 (78.2%) |
Good |
44 (21.8%) |
Poor |
| 28. | Paper post can also be used to deliver e health services | 97 (48.7%) |
Poor |
102 (51.3%) |
Good |
| Cluster % and % | 79% |
Good |
21% |
Poor |
|
| Areas e-health can be applied | |||||
| 29. | Clinical area | 170 (84.6%) |
Good |
31 (15.4%) |
Poor |
| 30. | Health education | 192 (92.8%) |
Good |
15 (7.2%) |
Poor |
| 31. | Health care administration | 184 (89.8%) |
Good |
21 (10.2%) |
Poor |
| 32. | Health Policy making | 177 (85.9%) |
Good |
29 (14.1%) |
Poor |
| 33. | Research | 185 (92.5%) |
Good |
15 (7.5%) |
Poor |
| Cluster % and ratings | 89.1% |
Good |
10.9% |
Poor |
|
| Examples of E-health applications | |||||
| 34. | Electronic health records is one of the applications of e-health | 179 (89.1%) |
Good |
21 (10.4%) |
Poor |
| 35. | Electronic medical records is not an example of e-health application | 98 (49.0%) |
Poor |
102 (51.0%) |
Good |
| 36. | Software systems is another example of e-health application | 161 (81.7%) |
Good |
36 (18.3%) |
Poor |
| 37. | Apple’s new health kit is also an example of e-health application | 158 (83.2%) |
Good |
27 (14.2%) |
Poor |
| Cluster % and ratings | 75.8% |
Good |
24.2% |
Poor |
|
| Overall % and ratings | 85.6% |
Good |
14.4% |
Poor |
Source: Field work, 2019.
Data in Table 1shows an overall percentage of 85.6% which indicated that health care professionals in FETHA generally possessed a good level ofknowledge of e-Health care delivery while 14.4% possessed a poor knowledge of e-Health care delivery. Specifically, the table indicated through clusters that health care professional possessed a good knowledge of the meaning of e-Health care delivery, (92.8%); e-Health services, (91.2%); channels of e-Health delivery (79%); Areas of e-Health application (89.1%); and examples of e-Health application (75.8%).
Research Question 2: What is the level of e-Health Utilization in health care delivery among health care professionals?
Table-2. Mean Responses regarding level of e-Health Utilization in health care delivery among health care professionals.
| S/N | Item Statement | SD |
Dec |
|
| 58 | Body scanner | 1.73 |
1.06 |
Low |
| 59 | Printer | 2.48 |
1.08 |
Low |
| 60 | Projector | 2.59 |
1.06 |
High |
| 61 | Telemedicine (for radiology, stroke assessment etc.) | 1.80 |
1.11 |
Low |
| 62 | Tele-health (remote monitoring of vital signs, video conference) | 2.02 |
1.03 |
Low |
| 63 | Mobile health | 2.10 |
.93 |
Low |
| 64 | Health IT system | 2.04 |
.94 |
Low |
| 65 | Hybrid operating rooms | 1.65 |
.89 |
Low |
| 66 | Health staff management technology | 1.93 |
1.02 |
Low |
| 67 | Infection detecting technology | 1.68 |
.95 |
Low |
| 68 | Patient-friendly technology | 1.73 |
.98 |
Low |
| 69 | Surgical and service technology | 1.66 |
.92 |
Low |
| 70 | Fax machine | 1.67 |
1.02 |
Low |
| 71 | Application of smart phones in health care delivery | 2.47 |
1.22 |
Low |
| 72 | SPSS/Epi Info | 2.37 |
1.19 |
Low |
| 73 | Electronic personal health records and patient portals | 2.19 |
1.06 |
Low |
| 74 | 2.54 |
1.14 |
High |
|
| 75 | Social media (WhatsApp, Face book etc.) | 2.46 |
1.12 |
Low |
| 76 | Consumer-focused wireless app | 2.03 |
1.08 |
Low |
| 77 | Internet search | 2.63 |
1.14 |
High |
| 78 | Computerize databases | 2.58 |
3.31 |
High |
| 79 | Computerize sensor | 1.94 |
1.09 |
Low |
| 80 | E-leaning or E-Journal | 2.31 |
1.17 |
Low |
| 81 | Microsoft access | 2.41 |
1.19 |
Low |
| 82 | Microsoft excels | 2.38 |
1.15 |
Low |
| Overall % and X | 2.14 |
.46 |
Low |
Source: Field work, 2019.
The data in Table 2above shows the overall mean of ( x̅= 2.14) which implies that the utilization of e-Health care delivery among health care professionals in FETHA is low. Specifically, the Table shows that “Body scanner ( x̅ =173); “Printer (x̅=2.48); “Telemedicine (for radiology, stroke assessment etc.) (x̅= 1.80); “Tele-health (remote monitoring of vital signs, video conference) (x̅= 2.02); “Mobile health (x̅= 2.10); “Health IT system (2.04); “Hybrid operating rooms (x̅= 1.65); “Health staff management technology (x̅= 1.93); “Infection detecting technology (x̅= 1.68);“Patient-friendly technology (x̅= 1.73 );“Surgical and service technology (x̅= 1.66); “Fax machine (1.67); “Application of smart phones in health care delivery (2.47); “SPSS/Epi Info (2.37); “Electronic personal health records and patient portals (x̅= 2.19); “Social media (WhatsApp, Face book etc.) (x̅=2.46); “Consumer-focused wireless app (x̅= 2.03); “Computerize sensor (x̅= 1.94); “E-leaning or E-Journal (x̅= 2.31); “Microsoft access (x̅= 2.41); “Microsoft excels (x̅= 2.38), indicated low utilization of e-Health care delivery as their mean scores fall below 2.5 cut-off point. Furthermore, the Health professional indicate high utilization of “Projector (x̅= 2.59); “E-mail (x̅=2.54); “Internet search (x̅=2.63);” Computerize databases (x̅= 2.58) in e-Health care delivery as their mean score fall within 2.5 and above.
Hypothesis 1: There is no significant difference in the level of knowledge of e-Health care delivery among health care professionals in FETHA by age.
Table-3. Summary of one-way Analysis of Variance (ANOVA) testing the hypothesis that there is no significant difference in the level of knowledge of e-Health care delivery among health care professionals in FETHA by age.
Level of knowledge |
Sum Between Groups |
Squares Within Groups |
df |
Mean Between Groups |
Squares Within Groups |
F |
P-value |
Age |
151.727 |
7237.330 |
3 |
50.576 |
35.477 |
1.426 |
.236** |
Note:** = Not Significant at .05 level.
Data in Table 3above shows that the probability value of.236 is greater than the significant level of 0.05 (P-value =.236 >0.05). This means that the earlier stated null hypothesis will be accepted. Hence, there is no statistical significant difference in level of knowledge of e-Health care delivery among health care professionals in FETHA by age.
Hypothesis 2: There is no significant difference in the level of utilization of e-Health care delivery among health care professionals in FETHA by age.
Table-4. Summary of one-way Analysis of Variance (ANOVA) testing the hypothesis that there is no significant difference in the level of utilization of e-Health care delivery among health care professionals in FETHA by age.
Level of Utilization |
Sum Between Groups |
Squares Within Groups |
df |
Mean Between Groups |
Squares Within Groups |
F |
P-value |
Age |
4791.289 |
51315.516 |
3 |
1597.096 |
702.952 |
2.272 |
.087** |
Note: ** = Significant at .05 level.
Data in Table 4above shows that the probability value .087 is greater than the significant level of 0.05 (P-value =.087>0.05). This implies that the earlier stated null hypothesis will be accepted. Therefore, there is no statistical significant difference in the level of utilization of e-Health care delivery among health care professionals in FETHA by age.
Hypothesis 3: There is no significant difference in the level of knowledge of e-Health care delivery among health care professionals in FETHA by gender.
Table-5. Summary of Binomial Logistics Regression table testing the hypothesis that there is no significant difference in the level of knowledge of e-Health care delivery among health care professionals in FETHA by gender.
Variables in the Equation
Sex |
N |
B |
S.E. |
Wald |
df |
Sig. |
Male |
116 |
|||||
-.276 |
.141 |
3.819 |
1 |
.051* |
||
Female |
88 |
Note:* = Significant at .05 level.
Data in Table 5above shows that the probability value .051 is greater than the significant level of 0.05 (P-value=.051>0.05). This implies that the earlier stated null hypothesis will be accepted. Therefore, there is no statistical significant difference in level of knowledge of e-Health care delivery among health care professionals in FETHA by gender.
Hypothesis 4: There is no significant difference in level of utilization of e-Health care delivery among health care professionals in FETHA by gender.
Table-6. Summary of Binomial Logistics Regression table testing the hypothesis that there is no significant difference in level of utilization of e-Health care delivery among health care professionals in FETHA by gender.
Variables in the Equation
Sex |
N |
B |
S.E. |
Wald |
df |
Sig. |
Male |
38 |
|||||
-.027 |
.231 |
.013 |
1 |
.908** |
||
Female |
37 |
Note:** = Significant at .05 level.
Data in Table 6above shows that the probability value .908 is greater than the significant level of 0.05 (P-value = .908>0.05). This implies that the earlier stated null hypothesis will be accepted. Therefore, there is no statistical significant difference in level of utilization of e-Health care delivery among health care professionals in FETHA by gender.
The study found that health care professionals in FETHA possessed goodknowledge of e-Health care delivery.This finding of the study is in consonance with the studies by Adeleke, et al. [35]; Alwan, et al. [36]; Kirubel and Abetu [37] who reported good knowledge of e-Health care delivery among health care professionals. However, the findings contradict the studies [26, 27]who observed lack of knowledge about ICT as challenges hindering ICT use in health care delivery.
The study also found that there was low utilization of e-Health care delivery among health care professionals in FETHA. The finding of the study is in consonance with the studies [22-24] who reported low utilization of ICT in health care delivery in developing countries. The study is also in line with the studies[26-29] whohighlighted factors affecting e-Health care delivery utilization such as: lack of availability of ICT equipment, high cost of ICT; low level of skills of potential users; technology compatibility; and limited access to ICT as challenges hindering e-Health utilization in health care delivery.
The study indicated that there is no statistical significant difference in level of knowledge of e-Health care delivery among health care professionals in FETHA by age. The findings were in consonance with the studies[38-42] who indicated age not to be a significant influencing factor for the e-Health care delivery. The study disagree with the study[43] who reported that the younger population is more aware of e-Health possibilities compared to older persons who have less knowledge about e-Health.
The study also indicated that there is no statistical significant difference in the level of utilization of e-Health care delivery among health care professionals in FETHA by age. However, the following studies [38-42] indicated age not to be a significant influencing factor for e-Health care utilization. This study disagree with the study of Fabienne, et al. [25] who indicated age to be a significant factor that influences the utilization of e-Health care delivery. The study is also at variant with the studies [44-50] who revealed that younger people are more willing and have more experience and interest in using e-Health care delivery compared to older people. The study also disagrees with Terschüren, et al. [43] who report that older people are afraid of losing personal contact with their physician when they start using e-Health. Also disagree in the study of Goyal, et al. [51] who observed that older persons, once they adopt the technology, adhere longer to a risk management app than younger people who, although they download the app more often, also lose interest more often.
The study further indicated that there is no statistical significant difference in level of knowledge of e-Health care delivery among health care professionals in FETHA by gender. This finding is however, surprising and not expected, hence there is evidence that women usually bear primary responsibility for family care and health and other family factors that are capable of depriving women the knowledge of e-Health care delivery. The finding is at variant with the findings of Khatun, et al. [52] who reported that gender differences existed in the knowledge of e-Health care delivery irrespective of education and socioeconomic status. The study is also in disagreement with Khatun, et al. [52] who also observed that women with high education and those of higher socioeconomic status also have low knowledge of mHealth services, which indicates that available mHealth services are not focused appropriately for women to be aware about the mHealth program.Although there is a lack of mobile phone ownership, low awareness of mobile phone use in healthcare and low knowledge about available mHealth services, there is a high probability of women in every socioeconomic and education group being interested in joining the mHealth program in future.
The study also found that there is no statistical significant difference in level of utilization of e-Health care delivery among health care professionals in FETHA by gender. Finding is however, surprising and not expected; hence studies indicated that traditional gender roles may result in women lagging behind men in the utilization of modern technologies, especially in developing countries[52]. More so females and males behave differently and play different roles in society [53]. Males are more prone to adventure, use of technology, and exploring new things than females. Also in Abakaliki, Ebonyi State, Nigeria where the present study is conducted gender inequality is pronounced; women are meant to understand that they are weaker sex in so many areas. This disagree with the studies [51, 54, 55] who reported that women are more engaged with eHealth applications and use them more often than men. The study also at variant with the studies[43, 45]who reported men to be more likely to accept telemonitoring than women and that Males are more prone to adventure, use of technology, and exploring new things than females.
E-health is a new and specialized concept in healthcare delivery, and its application has not been explored in health care delivery in FETHA and in Nigeria health sector hence the present study focused on knowledge and utilization of e-health care delivery among health care professionals in Federal Teaching Hospital Abakaliki, Ebonyi State, Nigeria.However our respondents reported a goodknowledge of e-Health care delivery and low utilizationdespite the multitude of structural and systemic difficulties in nations health care systems. Based on our findings, much work is needed to be done to providing awareness, training and retraining and continuous follow-up among health care professionals on the utilization of e-Health care delivery in the nation’s health sector. Also there is need for e-Health to be fully integrated in the healthcare system in Federal Teaching Hospital Abakaliki (FETHA), Ebonyi State and Nigerian hospital in general given the high burden of disease incidence/prevalence including emerging and re-emerging diseases in Nigeria and the rate of contact cases among health workers, e-Health is believed and has been identified to improve health care by strengthening the health system, improving communication among different health care organizations and professionals and supporting delivery of care to patients without necessarily face to face contact.
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
Acknowledgement: All authors contributed equally to the conception and design of the study. |
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