We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Forecasting the rate of hand injuries in Singapore.
- Authors
Glen, Liau Zi Qiang; Wong, Joel Yat Seng; Tay, Wei Xuan; Weng, Jiayi; Cox, Gregory; Cheah, Andre Eu Jin
- Abstract
Purpose: This study aims to analyse the correlation between the incidence rate of hand injuries and various major economic indicators in Singapore. We hypothesise that the number of hand injuries is correlated to activity in the construction and manufacturing industries in Singapore. Methods: Twenty thousand seven hundred sixty-four patients who underwent hand surgeries in a tertiary institution between 2012 to 2018 were reviewed. Two independent, blinded observers extracted the frequency of hand surgeries performed from Electronic Medical Records. Economic indicators pertinent to Singapore's economic activity were collected and smoothed by simple moving average of the prior 3 months. Results were analysed using IBM SPSS v25.0. Results: Significant independent univariate variables were Purchasing-Manager-Index and Industrial-Production-Index. Multiple linear regression of quarterly reported figures showed that Total-Livestock-Slaughtered, Total-Seafood-Handled, Purchasing-Manger-Index, Industrial-Production-Index, Gas-Tariffs, Construction-Index, Consumer-Price-Index, Total-Air-Cargo-Handled, Total-Container-Throughput, Total-Road-Traffic-Accident-Casualties, Food-&-Beverage-Services-Index were significantly correlated (p < 0.05) with hand injuries, with R2 = 62.3%. Conclusion: Quarterly economic indicators from major economic industries can be used to predict the incidence of hand injuries with a 62.3% correlation. These findings may be useful for anticipating healthcare resource allocation to treat hand injuries. Type of study and level of evidence: Economic and decision, Level II.
- Subjects
SINGAPORE; STATISTICS; HAND injuries; MANUFACTURING industries; MULTIPLE regression analysis; HAND surgery; TERTIARY care; FORECASTING; ELECTRONIC health records; DATA analysis software
- Publication
Journal of Occupational Medicine & Toxicology, 2022, Vol 17, Issue 1, p1
- ISSN
1745-6673
- Publication type
Article
- DOI
10.1186/s12995-022-00350-6