| Literature DB >> 35804345 |
Rajmohan Panda1, Nivedita Mishra2, Supriya Lahoti3, Rajath R Prabhu3, Arti Mishra3, Kalpana Singh4, Kumud Rai3.
Abstract
BACKGROUND: The Coronavirus Disease 2019 (COVID-19) has severely challenged healthcare delivery systems worldwide. Healthcare Workers were unable to assess and manage the cases due to limited knowledge of treating the virus and inadequate infrastructure. Digital interventions played a crucial role in the training of healthcare workers to get through the pandemic. Project Extension for Community Healthcare Outcomes (ECHO) initiated the COVID-ECHO telementoring program for strengthening the knowledge and skills of healthcare workers. The study aimed at assessing the effects of the ECHO telementoring model in the capacity building of healthcare workers in the context of COVID-19 in India.Entities:
Keywords: COVID-19; Capacity building; ECHO Telementoring; Healthcare workers; Mixed-method study
Mesh:
Year: 2022 PMID: 35804345 PMCID: PMC9264289 DOI: 10.1186/s12913-022-08288-5
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.908
Participants demographic characteristics
| Characteristics | Doctors | Nurses | Total |
|---|---|---|---|
| 306 | 217 | 523 | |
| Age, mean (SD)a | 36.9 (10.6) | 35.2 (9.4) | 36.2 (10.1) |
| Gender | |||
| Male | 161 (52.6%) | 18 (8.3%) | 179 (34.2%) |
| Female | 145 (47.4%) | 199 (91.7%) | 344 (65.8%) |
| Education Qualification | |||
| MBBS | 202 (66.2%) | - | 202 (38.7%) |
| MD | 88 (28.9%) | - | 88 (16.9%) |
| BDS | 15 (4.9%) | - | 15 (2.9%) |
| Diploma-Nursing | - | 135 (62.2%) | 135 (25.9%) |
| BSc-Nursing | - | 71 (32.7%) | 71 (13.6%) |
| MSc-Nursing | - | 11 (5.1%) | 11 (2.1%) |
| Caste | |||
| General | 171 (59.4%) | 120 (55.6%) | 291 (57.7%) |
| SC/ST | 39 (13.5%) | 35 (16.2%) | 74 (14.7%) |
| OBC | 78 (27.1%) | 61 (28.2%) | 139 (27.6%) |
| Site of Practice | |||
| Primary | 107 (35.7%) | 107 (49.5%) | 214 (41.5%) |
| Secondary | 29 (9.7%) | 31 (14.4%) | 60 (11.6%) |
| Tertiary | 143 (47.7%) | 55 (25.5%) | 198 (38.4%) |
| Private | 17 (5.7%) | 19 (8.8%) | 36 (7.0%) |
| Others | 4 (1.3%) | 4 (1.9%) | 8 (1.6%) |
| Location of Practice | |||
| Rural | 136 (44.9%) | 115 (53.0%) | 251 (48.3%) |
| Urban | 167 (55.1%) | 102 (47.0%) | 269 (51.7%) |
| Work Experience, mean (SD)a | 8.1 (8.8) | 7.5 (8.2) | 7.8 (8.5) |
| Source of ECHO sessions | |||
| Internet/ECHO Website | 174 (57.4%) | 65 (30.0%) | 239 (46.0%) |
| Colleagues | 47 (15.5%) | 61 (28.1%) | 108 (20.8%) |
| Social Media | 32 (10.6%) | 13 (6.0%) | 45 (8.7%) |
| Others | 50 (16.5%) | 78 (35.9%) | 128 (24.6%) |
aIn completed years
Fig. 1Participant's average learning, competence, satisfaction, and performance associated with the use of COVID-ECHO program
T-test and ANOVA summary—Doctors
| 0.096 | 0.12 | 0.15 | |||||
| Male | 161 | 52.3 (5.4) | 17.4 (1.9) | 30.4 (3.2) | |||
| Female | 145 | 53.4 (5.9) | 17.8 (2.1) | 31.0 (3.6) | |||
| MBBS | 202 | 52.2 (5.6) | 17.3 (1.9) | 30.3 (3.3) | |||
| MD | 88 | 53.7 (5.5) | 18.0 (2.0) | 31.3 (3.4) | |||
| BDS | 15 | 57.2 (4.8) | 18.9 (2.0) | 32.9 (3.8) | |||
| 0.11 | 0.087 | 0.083 | |||||
| General | 171 | 53.7 (5.5) | 17.9 (2.0) | 31.2 (3.3) | |||
| SC/ST | 39 | 52.5 (6.0) | 17.6 (2.1) | 30.4 (3.4) | |||
| OBC & Others | 78 | 52.1 (5.8) | 17.3 (2.0) | 30.2 (3.7) | |||
| Primary facility | 107 | 51.3 (5.5) | 17.2 (1.9) | 29.8 (3.5) | |||
| Secondary facility | 29 | 53.9 (5.9) | 17.8 (2.1) | 31.4 (3.3) | |||
| Tertiary facility | 143 | 53.7 (5.5) | 17.8 (2.0) | 31.0 (3.3) | |||
| Private facility | 17 | 54.6 (6.0) | 18.4 (2.2) | 32.9 (3.0) | |||
| Rural | 136 | 52.0 (5.9) | 17.3 (2.0) | 30.0 (3.4) | |||
| Urban | 167 | 53.6 (5.4) | 17.9 (2.0) | 31.3 (3.3) | |||
T-test and ANOVA summary – Nurses
| Male | 18 | 43.9 (4.2) | 0.89 | 17.7 (1.9) | 0.64 | 30.4 (2.5) | 0.64 |
| Female | 199 | 43.8 (4.2) | 17.5 (1.7) | 30.8 (3.2) | |||
| Diploma Nursing | 135 | 44.0 (4.3) | 0.74 | 17.4 (1.6) | 0.82 | 30.8 (3.1) | 0.64 |
| BSc. Nursing | 71 | 43.6 (3.9) | 17.6 (1.8) | 30.9 (3.4) | |||
| MSc. Nursing | 11 | 43.1 (5.7) | 17.4 (2.0) | 29.9 (2.9) | |||
| General | 120 | 43.7 (3.9) | 0.17 | 17.4 (1.5) | 0.34 | 30.7 (3.1) | 0.64 |
| SC/ST | 35 | 45.0 (4.7) | 17.9 (1.8) | 31.3 (3.5) | |||
| OBC & Others | 61 | 43.4 (4.5) | 17.4 (1.9) | 30.7 (3.0) | |||
| Primary facility | 107 | 44.0 (4.3) | 0.48 | 17.6 (1.7) | 0.29 | 31.0 (3.2) | 0.22 |
| Secondary facility | 31 | 44.5 (3.5) | 17.7 (1.5) | 31.1 (3.0) | |||
| Tertiary facility | 55 | 43.6 (4.8) | 17.4 (1.9) | 30.7 (3.3) | |||
| Private facility | 19 | 42.6 (3.1) | 16.8 (1.5) | 29.2 (2.5) | |||
| Rural | 115 | 44.3 (4.3) | 0.093 | 17.6 (1.7) | 0.48 | 31.2 (3.2) | |
| Urban | 102 | 43.3 (4.1) | 17.4 (1.7) | 30.3 (3.1) | |||
Summary of challenges
| Theme | ||
|---|---|---|
| Limited interaction | Sessions were less interactive as compared to face-to-face sessions | |
| Difficult to follow-up | Follow up with the participants to assess the practical implications of the training program is difficult | |
| Time constraint | Session’s time conflicts with their duty hours | |
| Technical issues | Internet connectivity is the biggest limitation of the program | |
| Need for physical training | Face-to-face training is appropriate for gaining skills in the clinical domain |
Recommended strategies to improve model
| Theme | ||
|---|---|---|
| Timing of sessions | Duration of 30 to 60 min, preferably post-lunch was considered appropriate | |
| Interactive sessions | Compulsory use of video cameras by participants and offering recorded sessions | |
| Hybrid sessions | Hybrid model blending both synchronous and asynchronous models of training | |
| Publicity of program | Publicizing the ECHO platform through various media sources | |
| Feedback mechanism | Strengthen the existing feedback mechanism and ensure the collection of responses from the participants | |
| Inclusion of CME | CME accreditation for the ECHO program can enhance participation as well as help in better branding of the program |