Epidemiology and socioeconomic consequences of work-related pelvic and acetabular fractures recorded in the German Social Accident Insurance

[Accident pension after fracture of the pelvic ring and acetabulum : Changes in pension claims and costs following isolated fractures of the pelvic ring and acetabulum in work-related accidents from 2013 to 2019-A DGUV registry analysis]

BACKGROUND

It is known that fractures of the pelvic ring and acetabulum in work-related accidents are associated with long periods of incapacity to work, a high rate of reduction in earning capacity (MdE) and high costs for pension/severance pay.

OBJECTIVE

Investigation of changes in pension claims and costs from 2013 to 2019 after isolated fractures of the pelvic ring and acetabulum in work-related accidents in Germany.

MATERIAL AND METHODS

For all patients from the German Social Accident Insurance (DGUV) registry with isolated fractures of the pelvic ring or acetabulum in work-related accidents, linear trend analyses were carried out among others for the proportion of MdE ≥20%, the proportion of cases receiving pension/severance pay and total costs for pension/severance pay from 2013 to 2019. A logistic regression analysis for the likelihood of receiving a pension was also performed.

RESULTS

The proportion of MdE ≥20% decreased for fractures of the pelvic ring and acetabulum in total from 14.3% for 2013 to 8.2% for 2019 and there was a decreasing trend for the proportion of cases receiving pension/severance pay for fractures of the pelvic ring and acetabulum in total from 23.1% for 2013 to 13.6% for 2019 as well as for both fracture types individually. There was also a decrease in the costs for pensions/severance pay for fractures of the pelvic ring and acetabulum in total from € 1,542,531 for 2013 to € 1,006,887 for 2019. The likelihood of receiving a pension decreased by 8% per subsequent accident year between 2013 and 2019.

CONCLUSION

The proportion of pension claims and thus the costs for pensions/severance pay decreased for isolated fractures of the pelvic ring and acetabulum in work-related accidents from 2013 to 2019. The DGUV seems to fulfil its guideline Rehabilitation before pension.

Return to work following traumatic hip dislocation: a prognostic outcome study

BACKGROUND

Traumatic hip dislocations are associated with high morbidity and overall limitations of daily living activities. Residual disability inhibits returning to work after severe injuries and minimizes financial independence and social involvement, which are both related to well-being and good health. The aim of this study was to analyze epidemiological and socioeconomic status following traumatic hip dislocations to identify predictors for return to work.

PATIENTS AND METHODS

Patients with traumatic hip dislocations from three level one trauma centers from 2009 to 2021 were followed up in terms of epidemiological data, return to work, change of work, and predictors of socioeconomic outcome. Inclusion criteria were age ≥ 18 years, employed patients, and a minimum follow-up of ≥ 2 years. Patients with incomplete or missing medical records, including radiological imaging and retired patients, were excluded. 107 patients met the inclusion criteria and 67 (63%) patients were available for follow-up.

RESULTS

A total of 81 male and 26 female patients with a mean age of 41.82 years (SD ± 15.65) were finally evaluated. A work-related accident was found in 28 patients (26%). Demographic data and treatment course did not differ significantly between the work-related and non-work-related accidents. Sixty-seven (63%) patients (51 male and 16 female) with a mean age of 42 years (SD ± 15.79) were included in the follow-up. Eighteen patients (27%) had not returned to their previous job and 12 patients (18%) had reduced income. Higher age and Body Mass Index (BMI) were significantly associated with a lower return rate to the pre-accident job (p < 0.05). Furthermore, lower Tegner Activity Scale, pain score, and modified Harris Hip Score were also significantly associated with lower return to work rate (p < 0.001) and reduced income.

CONCLUSION

Traumatic hip dislocations are associated with high rates of work-related injury and unsatisfactory low rates of return to previous work. Younger age, lower BMI, higher Patient reported outcome measures and lower pain levels may predict a successful return to previous job and a reduced risk of reduction in earning capacity. Understanding the predictive factors is crucial to identify patients at risk of not returning to work and to develop strategies that may help improve their chances of successfully returning to their previous employment.

Wearable activity data can predict functional recovery after musculoskeletal injury: Feasibility of a machine learning approach

Delayed functional recovery after injury is associated with significant personal and socioeconomic burden. Identification of patients at risk for a prolonged recovery after a musculoskeletal injury is thus of high relevance. The aim of the current study was to show the feasibility of using a machine learning assisted model to predict functional recovery based on the pre- and immediate post injury patient activity as measured with wearable systems in trauma patients. Patients with a pre-existing wearable (smartphone and/or body-worn sensor), data availability of at least 7 days prior to their injury, and any musculoskeletal injury of the upper or lower extremity were included in this study. Patient age, sex, injured extremity, time off work and step count as activity data were recorded continuously both pre- and post-injury. Descriptive statistics were performed and a logistic regression machine learning model was used to predict the patient's functional recovery status after 6 weeks based on their pre- and post-injury activity characteristics. Overall 38 patients (7 upper extremity, 24 lower extremity, 5 pelvis, 2 combined) were included in this proof-of-concept study. The average follow-up with available wearable data was 85.4 days. Based on the activity data, a predictive model was constructed to determine the likelihood of having a recovery of at least 50 % of the pre-injury activity state by post injury week 6. Based on the individual activity by week 3 a predictive accuracy of over 80 % was achieved on an independent test set (F1=0,82; AUC=0,86; ACC=8,83). The employed model is feasible to assess the principal risk for a slower recovery based on readily available personal wearable activity data. The model has the potential to identify patients requiring additional aftercare attention early during the treatment course, thus optimizing return to the pre-injury status through focused interventions. Additional patient data is needed to adapt the model to more specifically focus on different fracture entities and patient groups.