| Literature DB >> 35682226 |
Ahmed Farrasyah Mohd Kutubudin1, Wan Mohd Zahiruddin Wan Mohammad1, Siti Suraiya Md Noor2, Mohd Nazri Shafei1.
Abstract
Sharp injury is a serious occupational risk for healthcare workers (HCWs). This study aimed to determine the distribution and associated factors of sharp injury cases among HCWs working at a teaching hospital in northeastern Malaysia. This was a retrospective cohort study on all reported sharp injury cases from 2015 to 2020. The secondary data were examined using descriptive and multiple logistic regression. Statistical significance was determined for associated factors of HCWs who did not attend immediate treatment after a sharp injury or any of the subsequent follow-up variables, with a p-value of less than 0.05. A total of 286 cases fulfilled the study criteria. The mean (SD) age of sharp injury was 29.4 (5.38) years. The overall defaulted rate for follow-up was 51.4%. Multiple logistic regression revealed a significant relationship between defaulted follow up on sharp injury management and job category as well as the type of device used. Being a doctor (Adj OR 2.37; 95% CI: 1.40, 4.03; p = 0.010) and those using other sharp instruments such as Coupland and drip sets (Adj OR 4.55; 95% CI: 1.59, 13.02; p = 0.005) had a higher odds to default follow up on sharp injury management. In conclusion, although there is a link between defaulting the follow-up and both the work category and the type of device that caused the injury, a deeper analysis is needed to uncover any additional factors and determine the appropriate intervention strategies to ensure follow up adherence.Entities:
Keywords: defaulted follow up; health care worker; needle stick; sharp injury
Mesh:
Year: 2022 PMID: 35682226 PMCID: PMC9180157 DOI: 10.3390/ijerph19116641
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Characteristics of sharp injury cases among HCWs in Hospital USM and follow up distribution (n = 286).
| Variables | n (%) | Defaulted | Completed |
|---|---|---|---|
| n (%) | n (%) | ||
| Age (years) | |||
| <25 | 23 (8.1) | 8 (5.4) | 15 (10.8) |
| 25–29 | 152 (53.1) | 82 (55.8) | 70 (50.4) |
| 30–34 | 68 (23.8) | 39 (26.5) | 29 (20.8) |
| ≥35 | 43 (15.0) | 18 (12.3) | 25 (18.0) |
| Gender | |||
| Female | 186 (65.0) | 94 (63.9) | 92 (66.2) |
| Male | 100 (35.0) | 53 (36.1) | 47 (33.8) |
| Ethnicity | |||
| Malay | 245 (85.6) | 125 (85.0) | 120 (86.3) |
| Chinese | 30 (10.5) | 15 (10.2) | 15 (10.8) |
| Indian | 11 (3.9) | 7 (4.8) | 4 (2.9) |
| Job Category | |||
| House officer | 111 (38.8) | 67 (45.6) | 44 (31.7) |
| Medical officer | 62 (21.7) | 37 (25.2) | 25 (18.0) |
| Specialist | 11 (3.8) | 6 (4.0) | 5 (3.6) |
| Nurse | 66 (23.2) | 26 (17.7) | 40 (28.8) |
| Dentist | 17 (5.9) | 5 (3.4) | 12 (8.6) |
| Others | 19 (6.6) | 6 (3.1) | 13 (9.3) |
| Location of Event | |||
| Outpatient clinic | 25 (8.7) | 12 (8.2) | 13 (9.4) |
| Ward/inpatient | 160 (55.9) | 80 (54.4) | 80 (57.6) |
| A&E | 29 (10.2) | 17 (11.6) | 12 (8.6) |
| OT | 56 (19.6) | 32 (21.8) | 24 (17.2) |
| Others | 16 (5.6) | 6 (4.0) | 10 (7.2) |
| Department | |||
| Multidisciplinary | 64 (22.4) | 35 (23.8) | 29 (20.9) |
| Medical based | 104 (36.4) | 53 (36.1) | 51 (36.7) |
| Surgical Based | 118 (41.2) | 59 (40.1) | 59 (42.4) |
| Type of Device | |||
| Branula & needle | 207 (72.4) | 106 (72.1) | 101 (72.7) |
| Surgical Instrument | 55 (19.2) | 34 (23.1) | 21 (15.1) |
| Others | 24 (8.4) | 7 (4.8) | 17 (12.2) |
| Device Contamination | |||
| Yes | 282 (98.6) | 147 (100.0) | 135 (97.1) |
| No | 4 (1.4) | 0 (0.0) | 4 (2.9) |
| Procedure Conducted | |||
| Handling patient | 116 (40.6) | 57 (38.8) | 59 (42.4) |
| Handling equipment | 64 (22.4) | 30 (20.4) | 34 (24.5) |
| Disposal related | 46 (16.1) | 22 (15.0) | 24 (17.3) |
| Inoperative field | 43 (15.0) | 28 (19.0) | 15 (10.8) |
| Others | 17 (5.9) | 10 (6.8) | 7 (5.0) |
| Contamination Source | |||
| Known | 272 (95.1) | 141 (95.9) | 131 (94.2) |
| Unknown | 14 (4.9) | 6 (4.1) | 8 (5.8) |
Figure 1Prevalence of defaulted follow ups for sharp injuries among HCWs by year (n = 147).
Variables associated with defaulting the sharp injury follow-up among HCWs using simple and multiple logistic regression analyses (n = 286).
| Variables | Defaulted | Crude OR a | Adjusted OR b | |
|---|---|---|---|---|
| Age (years) | ||||
| ≥40 | 5/12 | 1 | ||
| <40 | 142/274 | 1.06 (0.39, 2.91) | ||
| Gender | ||||
| Female | 94/186 | 1 | ||
| Male | 53/100 | 1.10 (0.68, 1.80) | ||
| Ethnicity | ||||
| Non-Malay | 22/41 | 1 | ||
| Malay | 125/245 | 0.90 (0.46, 1.75) | ||
| Job Category | ||||
| Non-medical doctor | 37/102 | 1 | 1 | |
| Medical Doctor | 110/184 | 2.22 (1.32, 3.73) | 2.38 (1.40, 4.03) | 0.001 |
| Location of Event | ||||
| Outpatient | 12/25 | 1 | ||
| Ward/inpatient | 129/245 | 1.93 (0.62, 6.07) | ||
| Others | 6/16 | 1.80 (0.63, 5.11) | ||
| Department | ||||
| Multidisciplinary | 35/64 | 1 | ||
| Medical based | 53/104 | 0.86 (0.46, 1.61) | ||
| Surgical based | 59/118 | 0.83 (0.45, 1.53) | ||
| Type of Device | ||||
| Branula & needle | 106/207 | 1 | 1 | |
| Surgical Instrument | 34/55 | 2.55 (1.01, 6.41) | 2.96 (1.16, 7.53) | 0.023 |
| Others | 7/24 | 3.93 (1.40, 11.07) | 4.55(1.59, 13.02) | 0.005 |
| Procedure Conducted | ||||
| Disposal related | 32/63 | 1 | ||
| Handling patient | 57/116 | 1.04 (0.50, 2.14) | ||
| Handling equipment | 58/107 | 1.27 (0.66, 2.45) | ||
| Contamination Source | ||||
| Unknown | 6/14 | 1 | ||
| Known | 141/272 | 1.44 (0.49, 4.25) |
a Simple Logistic Regression. b Multiple Logistic Regression. Constant = −1.63. Forward LR and Backward LR Multiple Logistic Regression was applied. No multicollinearity and no interaction. Hosmer–Lemeshow test, p-value = 0.991. Classification Table (overall correctly classified percentage = 65.1%). Area under the curve = 63.3%.