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1.
Cureus ; 15(4): e37915, 2023 Apr.
Article in English | MEDLINE | ID: covidwho-2326076

ABSTRACT

Background Since the beginning of the novel coronavirus disease in Wuhan city of China in 2019 and its spreading worldwide and taking the form of a pandemic, many healthcare workers (HCWs) were affected by coronavirus disease 2019 (COVID-19) infection. Though we have used many types of personal protective equipment (PPE) kits while taking care of COVID-19 patients, we have seen COVID-19 susceptibility in different working areas were different. The pattern of infection in different working areas depended on HCWs following COVID-19 appropriate behavior. Therefore, we planned to estimate the susceptibility of front-line HCWs and second-line HCWs to getting COVID-19 infection. Aim To determine the risk of COVID-19 in front-line healthcare workers as compared to second-line healthcare workers. Method and materials We planned a retrospective cross-sectional analysis of COVID-19-positive healthcare workers from our institute within six months. Their nature of duty was analyzed and they were divided into two groups: 1) Front-line HCWs were defined as those who were working or who have worked in screening areas of the outpatient department (OPD) or COVID-19 isolation wards within the prior 14 days and provided direct care to patients with confirmed or suspected COVID-19. 2) Second-line HCWs were those who were working in the general OPD or non-COVID-19 areas of our hospital and did not have contact with COVID-19-positive patients. Results A total of 59 HCWs became COVID-19 positive during the study period, 23 as front-line and 36 as second-line HCWs. The mean (SD) duration of work as a front-line worker was 51 and as a second-line worker was 84.4 hours. Fever, cough, body ache, loss of taste, loose stools, palpitation, throat pain, vertigo, vomiting, lung disease, generalized weakness, breathing difficulty, loss of smell, headache, and running nose were present in 21 (35.6%), 15 (25.4%), 9 (15.3%), 10 (16.9%), 3 (5.1%), 5 (8.5%), 5 (8.5%), 1 (1.7%), 4 (6.8%), 2 (3.4%), 11 (18.6%), 4 (6.8%), 9 (15.3%), 6 (10.2%) and 3 (5.1%), respectively. To predict the risk of getting COVID-19 infection in HCWs, binary logistic regression with COVID-19 diagnosis as the output variable was modeled with hours of working in COVID-19 wards as front-line and second-line workers as independent variables. The results showed that there was a 1.18 times increased risk of acquiring the disease for every one-hour excess of working as a front-line worker, whereas, for second-line workers, it was slightly lower, with a 1.11 times increased risk for developing COVID-19 disease with every one hour increase in duty hours. Both these associations were statistically significant (p=0.001 for front-line and 0.006 for second-line HCWs). Conclusion COVID-19 has taught us the importance of COVID-19 appropriate behavior in preventing the spread of respiratory organisms. Our study has shown that both the front-line and second-line HCWs are at increased risk of getting the infection and proper use of a PPE kit or mask can decrease the spread of such respiratory pathogens.

2.
Cureus ; 14(11): e31720, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2203324

ABSTRACT

BACKGROUND: Telemedicine service was historically started for ambulatory and hospice care patients. Since 2020, we have been in the midst of the COVID-19 pandemic. The availability of healthcare facilities became limited due to repeated locked down during the COVID-19 pandemic. Thus, telemedicine service has gained tremendous popularity among healthcare services. Telemedicine service was started at All India Institute of Medical Sciences (AIIMS), Deoghar, as a COVID Helpline facility to provide guidance and care to the home isolated COVID-19 patients during the second wave of COVID-19. But we observed that more than 40% of calls were due to non-COVID-19-related problems, but we managed the non-COVID-19-related calls by discussing with a specialist in conference calls or WhatsApp consultation. Therefore, we planned to compare individual satisfaction with telemedicine services in patients with COVID-19 and non-COVID-19-related problems. METHODS AND MATERIALS: This study was a cross-sectional retrospective analysis of the register of telemedicine maintained in AIIMS, Deoghar, callers were grouped into two- COVID-19 and non-COVID-19-related problems. We obtained feedback from the patients and recorded it in a google form, collected data were analyzed in both groups. Telephonic consent was taken for participating in the study. The sample size was calculated to be 252, the COVID-19 group: 126, and the non-COVID-19 group: 126, and simple random sampling was used to choose the participants from the 730 total callers of the first month of telemedicine service. Their response was graded on 4 points Likert scale (1=Poor, 2=fair, 3=Good, 4=Excellent) and outcomes were analyzed by IBM SPSS (version 20.0) software. A p-value of <0.05 was considered statistically significant. OBJECTIVE: The primary objective is to estimate the level of satisfaction in both groups and compare their level of satisfaction. The secondary objective is to determine the department-specific telemedicine services requirement for people in need. RESULTS: Out of a total of 252 patients, most (54%) callers were 18-45 years old, and 44% were above 45 years old. 64% of patients were male. 90% of callers were from urban or semi-urban districts. 90% of callers had a 10th-grade or more education. 89% of patients were willing to use telemedicine services in the future. An Independent sample t-test was used to compare the means of both the groups showed a significant difference (p < 0.05) in the level of satisfaction in the COVID-19 group to the non-COVID-19 group. It showed that satisfaction in the COVID-19 group was higher than the group with non-COVID-19-related problems. CONCLUSION: COVID-19 has changed the whole spectrum of healthcare needs of the community. Our study findings showed that there is a need for separate department-wise telemedicine services to provide satisfactory service for attending to problems related to that department. For example, problems with diabetes should be attended to by an endocrinologist or an internal medicine specialist. This study finding helped us to change the policy and start department-wise telemedicine service.

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