Predicting return to work. A long-term follow-up study of railroad workers after low back injuries.
METHODS
Evaluation of the long-term outcomes of 178 railroad employees with low back injury who had completed a multidisciplinary rehabilitation program.


OBJECTIVE
To study two major areas: 1) outcomes of the rehabilitation program in terms of the patient's improvement in function and rate of return to work and 2) factors that predict long-term retention at work, both at the railroad and elsewhere.


BACKGROUND
Several studies have been published examining rehabilitation outcomes of individuals covered under workers' compensation law, but few exist that have examined railroad workers covered by the Federal Employers Liability Act, and few studies exist with follow-up periods longer than 3 years.


METHODS
Physical/medical, self-reported, and employment/financial data were collected on each patient from medical and employment records. Follow-up data regarding employment status were obtained either from the employer or from the patient by telephone interview.


RESULTS
On average, the patients improved in all objective and subjective measures after rehabilitation. Improvements in these measures were not predictive of return to work. At follow-up examination, 89% of the contacted patients were employed--61% still at the rail-road. The employment factors of lost work days and length of employment and the financial factor of wage rate were the most predictive of long-term work status.


CONCLUSIONS
The multidisciplinary program in the current study was found to improve patient physical functioning and reduce pain. However, success in these measures was not predictive of long-term work status, suggesting that other factors have an impact on work status. Clinicians must be aware that employment and financial factors may have a strong influence on return-to-work outcomes.
Hunter
S J
SJ
Intermountain Health Care, Salt Lake City, Utah, USA.
Shaha
S
S
Flint
D
D
Tracy
D M
DM
D000062:Accidents, Occupational / Q000706:statistics & numerical data; D000328:Adult; D019567:Back Injuries / Q000191:economics / Q000453:epidemiology / Q000534:rehabilitation*; D004651:Employment / Q000706:statistics & numerical data; D005500:Follow-Up Studies; D006801:Humans; D016015:Logistic Models; D008297:Male; D011890:Railroads; D013997:Time Factors; D014937:Work / Q000706:statistics & numerical data*; D014942:Workers' Compensation / Q000191:economics / Q000706:statistics & numerical data