| Literature DB >> 36105540 |
Bayou Tilahun Assaye1, Aynadis Worku Shimie1.
Abstract
Background: Digitizing healthcare has been a potential solution for transforming healthcare service delivery in the era of COVID-19 pandemics. To limit and minimize the virus spread, telemedicine helps control and prevent the pandemic by delivering healthcare services over long distances using Information communication technology. The objective of the study was to determine the level of telemedicine utilization among health professionals in the era of the COVID-19 Pandemic and the factors associated with it.Entities:
Keywords: COVID-19; Ethiopia; Healthcare professionals; Pandemic; Telemedicine system; Telemedicine use
Year: 2022 PMID: 36105540 PMCID: PMC9462923 DOI: 10.1016/j.imu.2022.101085
Source DB: PubMed Journal: Inform Med Unlocked ISSN: 2352-9148
Socio-demographic characteristics of the health professional at Addis Ababa public health facility, Central Ethiopia 2021 (N = 737).
| Variables | Categories | Frequency (#) | Percentages (%) |
|---|---|---|---|
| Gender | Male | 507 | 62.8% |
| Female | 230 | 31.2% | |
| Age (years) | 20–29 | 350 | 47.4% |
| 30–39 | 314 | 42.5% | |
| Age>40 | 73 | 9.9% | |
| Professional | Medical Doctor | 150 | 20.4% |
| Nurse | 155 | 21.0% | |
| Radiologic technologists | 70 | 9.5% | |
| Allied and other health professionals | 362 | 49.1% | |
| Educational status | Specialist | 80 | 10.9% |
| Resident | 44 | 6.0% | |
| GP | 42 | 5.7% | |
| Master's Degree | 166 | 22.5% | |
| Bachelor degree | 380 | 51.6% | |
| others | 25 | 3.4% | |
| Work experience (years) | <5 | 341 | 46.3% |
| 6–10 | 169 | 22.9% | |
| 11–15 | 71 | 9.6% | |
| >16 | 156 | 21.2% |
*Other1 = Diploma, Ph.D..
Fig. 1Level of telemedicine utilization among health professionals working at public health facilities.
Basic Computer skills and internet use among health professionals public health facility, Central, Ethiopia 2021 (N = 737).
| Variable categories | Frequency(#) | Percentages (%) | |
|---|---|---|---|
| ICT Training | Introductory level | 457 | 62% |
| Certificated in the ICT | 102 | 13.8% | |
| Never attended training in the ICT | 178 | 24.2% | |
| Accessibility of Computers, | Yes | 701 | 95.1% |
| No | 36 | 4.9% | |
| Activities Performed By their Computers | Microsoft-office | 317 | 21.0% |
| Internet access | 647 | 42.8% | |
| Entertainment like use social media | 492 | 32.6% | |
| Others | 54 | 3.6% | |
| Frequency of Search Health Information on the Internet | Always | 95 | 12.9% |
| Often | 233 | 31.6% | |
| Sometimes | 321 | 43.6% | |
| Rarely | 13 | 1.8% | |
| Never | 75 | 10.2% | |
| Reasons for Searching Information on Internet | Obtaining information to give patients care | 584 | 29.7% |
| Patient consultation | 541 | 27.5% | |
| Literature search | 495 | 25.1% | |
| Maintaining knowledge and skills | 349 | 17.7% | |
| Frequency of Interact with Patients via e-mail Or through Social Media | Always | 145 | 19.7% |
| often | 127 | 17.2% | |
| Sometimes | 238 | 32.3% | |
| rarely | 128 | 17.4% | |
| Never | 99 | 13.4% | |
| Requested by Patients For Online Advice During The Covid-19 Pandemic | Yes | 578 | 78.4% |
| No | 159 | 21.6% | |
Level of understanding of e-Health Among health professionals at a public health facility, Central Ethiopia 2021 (N = 737).
| VARIABLE | CATEGORIES | FREQUENCY (#) | PERCENTAGES (%) |
|---|---|---|---|
| KNOWLEDGE OF E-HEALTH. | Yes | 497 | 67.4% |
| No | 240 | 32.6% | |
| SOURCE OF INFORMATION FOR E-HEALTH | Internet | 505 | 23.6% |
| Colleagues | 456 | 21.3% | |
| Medical Literature | 364 | 17.0% | |
| Professional Training/Conference | 273 | 12.7% | |
| Seminar/Workshop | 277 | 12.9% | |
| Radio Or Tv | 267 | 12.5% | |
| VISITING WEBSITE RELATED TO TELEMEDICINE | Yes | 306 | 60.59% |
| No | 199 | 39.41% | |
| INFORMATION SHARING DURING COVID-19 | Yes | 555 | 75.3% |
| No | 182 | 24.3% | |
| TYPE OF TELEMEDICINE APPROACH | Store And Forward | 531 | 29.3% |
| Real-Time | 333 | 18.45 | |
| Remote Patient Monitoring | 373 | 20.6% | |
| Communication Via Telephone | 553 | 30.6% | |
| I Don't Know | 20 | 1.1% |
Organizational-related variables among health professionals at Addis Ababa public health facility, Central Ethiopia 2021 (N = 737).
| VARIABLE CATEGORIES | FREQUENCY (#) | PERCENTAGES (%) | |
|---|---|---|---|
| ACCESSIBILITY OF COMPUTERS | Yes | 514 | 69.7% |
| No | 223 | 30.3% | |
| INTERNET ACCESS | Yes | 525 | 71.2% |
| No | 212 | 28.8% | |
| TYPE OF INTERNET ACCESS | Wi-Fi | 182 | 34.66% |
| Broadband | 102 | 19.42% | |
| Both | 241 | 45.90% | |
| TRAINING IN THE E-HEALTH | Yes | 461 | 62.6% |
| No | 276 | 37.4% | |
| ICT SUPPORTING STAFF | Yes | 498 | 67.6% |
| No | 239 | 32.4% | |
Factors associated use of telemedicine among health professionals working at a public health facility, Central Ethiopia 2021 (N = 737).
| Variables | Categories | telemedicine Use | COR (95%CI) | AOR (95%CI) | |
|---|---|---|---|---|---|
| Good | Poor | ||||
| Gender | Male | 366 | 141 | 2.98(2.15–4.13) | 1.55(0.87–2.75) |
| female | 107 | 123 | 1 | 1 | |
| Work experience (years) | <5 | 238 | 103 | 0.82(0.54–1.26) | 3.19(.65–6.17) |
| 6–10 | 71 | 98 | 0.26(0.16–0.41) | 2.59(0.62–5.36) | |
| 11–15 | 49 | 22 | 0.79(0.43–1.47) | 1.20(0.51–2.87) | |
| >16 | 115 | 41 | 1 | 1 | |
| Training on ICT | Introductory level | 359 | 98 | 13.05(8.58–19.86) | 4.15(2.13–8.02)* |
| Certificated in the ICT area | 75 | 27 | 9.9(5.63–17.43) | 1.25(0.51–3.11) | |
| never attended ICT training | 39 | 139 | 1 | 1 | |
| Frequency of searching health information | Always | 75 | 20 | 12.79(6.16–26.59) | 6.19(2.13–18.07)* |
| Often | 150 | 83 | 6.16(3.37–11.27) | 7.10(2.68–18.90)* | |
| Sometimes | 255 | 96 | 7.99(4.43–14.49) | 4.53(1.85–11.09)* | |
| Rarely | 6 | 7 | 2.93(0.86–9.87) | 0.21(0.13–1.04) | |
| Never | 17 | 58 | 1 | 1 | |
| Frequency of use of social media | Always | 120 | 25 | 15.01(7.98–28.16) | 3.46(1.43–8.32)* |
| Often | 196 | 42 | 14.58(8.26–25.57) | 0.87(0.37–2.03) | |
| Sometimes | 84 | 43 | 6.10(3.39–10.9) | 11.90(5.29–26.72) | |
| Rarely | 49 | 29 | 1.93(1.08–3.45) | 3.73(1.68–8.27) | |
| Never | 24 | 75 | 1 | 1 | |
| Health Information sharing during COVID-19 | Yes | 403 | 152 | 4.24(2.98–6.03) | 1.63(0.92–2.88) |
| No | 70 | 112 | 1 | 1 | |
| Internet access | Yes | 419 | 106 | 11.5(7.56–16.82) | 2.97(1.54–5.78)* |
| No | 54 | 158 | 1 | 1 | |
| Training on telemedicine/E-health | Yes | 225 | 51 | 3.79(2.66–5.40) | 1.06(0.60–1.87) |
| No | 248 | 213 | 1 | ||
| Availability of ICT supporting staff | Yes | 411 | 87 | 13.5(9.3–19.5) | 8.32(4.77–14.52)*** |
| No | 62 | 177 | 1 | ||
Note: 1 = reference; * ** P-value = 0.01, *; p-value ≤0.05.
| Terms | Operational Definition |
|---|---|
| Health professional: | Employees with at least a diploma certificate in the health professions who provide healthcare services in the study settings were defined as health professionals [ |
| Allied and other health professionals: | Midwives, pharmacists, medical laboratory technicians, anesthesia, psychiatry, and health informatics/health information techniques were among the allied and other health professionals included in the study. |
| Knowledge of e-Health. | Study participants who know, that E-health includes telemedicine, Mobile health, electronic health records, and health information exchange system are categorized as “Yes” and categorized “No” the participant who said e-health does not include telemedicine, Mobile health, electronic health records, and health information exchange system [ |
| Telemedicine system | the use of ICT infrastructure to support long-distance clinical health care and public health education through the use of video conferencing, the internet, email, store-and-forward imaging, and wireless communications (online or offline) [ |
| Telemedicine: | is the use of teleconsultation, Tele-education, any mobile-health application, and other telemedicine component that includes interactive video conferencing, a store and forward method, or a remote patient monitoring application ([ |
| Telemedicine utilization | Study participants who scored above the mean on the 10 ″yes” or “No” items (100%) of telemedicine were categorized as good telemedicine utilization and those who scored below the mean were categorized as poor telemedicine utilization [ |