The role of frailty risk for fracture-related hospital readmission and mortality after a hip fracture

Differing risk factors for potentially preventable and fall-related injury readmissions of older residents in long-term care facilities after hip fracture

BACKGROUND

Although most fall-related injury readmissions are preventable, there may be differences between risk factors for other potentially preventable readmissions (PPR) and fall-related injury readmissions. This study examined the differences between risk factors for 30-day PPR and fall-related injury readmissions among older adults living in residential aged care facilities (RACFs) after a hip fracture.

METHODS

This retrospective cohort study used linked hospitalization and mortality data in New South Wales, Australia. Residents aged ≥65 years who live in RACFs and were admitted after a hip fracture between 2014 and 2023. Demographic data, the number of Charlson comorbidities, and frailty risk were used. The 30-day PPR was identified using 22 conditions as defined by the Australian government, and three additional conditions (pressure injury, dehydration, sepsis). Multivariable logistic regression examined the predictors for 30-day PPR and fall-related injury readmissions.

RESULTS

Among 12,335 residents, there were 266 residents who experienced PPR, and 361 residents who experienced fall-related injury readmissions. Although residents with one (odds ratios: 1.98, 95 % confidence interval: 1.50-2.61) or ≥2 comorbidities (2.38, 1.67-3.37) had a higher risk of 30-day PPR than residents without comorbidities, there was no association of comorbidities with 30-day fall-related injury readmissions. Frailty risk was not associated with 30-day PPR, but residents with high (0.58, 0.37-0.92) and moderate frailty risk (0.63, 0.40-0.99) were less likely to experience fall-related injury readmissions than residents with no frailty risk.

CONCLUSIONS

Targeted approaches for 30-day PPR and fall-related injury readmissions should be optimized based on their specific predictors for preventing 30-day readmissions.

Impact of COVID-19 public health restrictions on fall-related hip fracture hospitalizations: An interrupted time series analysis

PURPOSE

There is limited evidence regarding the impact of public health restrictions on hip fracture hospitalization by place of fracture occurrence. This study aimed to examine the impact of COVID-19 public health restrictions on fall-related hip fracture hospitalization rates by place of occurrence.

METHODS

This retrospective cohort study was conducted using hospitalization data in New South Wales, Australia, between January 2014 and June 2022. Older adults aged ≥65 years admitted to hospital following a fall-related hip fracture. An interrupted time-series analysis using autoregressive integrated moving average models evaluated the impact of public health restrictions on fall-related hip fracture hospitalization by place of fracture occurrence (home/residence, residential aged care facility (RACF), or away from usual residence).

RESULTS

The mean observed fall-related hip fracture hospitalization rate during COVID-19 public health restrictions (36.3 per 100,000 people per month) was 13.4 % lower than the forecasted rate (41.1 per 100,000 people per month). The mean observed hospitalization rates for fall-related hip fractures at home/residence, at a RACF, and away from the usual residence were 3.8 %, 18.5 %, and 40.1 % lower than the forecasted rates, respectively. Level changes in the fall-related hip fracture hospitalization rates at RACFs and away from usual residences were -0.9 per 100,000 people per month (95 % CI -1.6 to -0.2) and -1.7 per 100,000 people per month (95 % CI -2.5 to -0.9), respectively.

CONCLUSIONS

There was a decline in fall-related hip fracture hospitalization rates among older adults, where the fracture occurred at RACFs and away from a person's usual residence during COVID-19 public health restrictions.

Group-based trajectories of potentially preventable hospitalisations among older adults after a hip fracture

Key predictors of three trajectory group membership of potentially preventable hospitalisations were age, the number of comorbidities, the presence of chronic obstructive pulmonary disease and congestive heart failure, and frailty risk at the occurrence of hip fracture. These predictors of their trajectory group could be used in targeting prevention strategies.

PURPOSE

Although older adults with hip fracture have a higher risk of multiple readmissions after index hospitalisation, little is known about potentially preventable hospitalisations (PPH) after discharge. This study examined group-based trajectories of PPH during a five-year period after a hip fracture among older adults and identified factors predictive of their trajectory group membership.

METHODS

This retrospective cohort study was conducted using linked hospitalisation and mortality data in New South Wales, Australia, between 2013 and 2021. Patients aged ≥ 65 years who were admitted after a hip fracture and discharged between 2014 and 2016 were identified. Group-based trajectory models were derived based on the number of subsequent PPH following the index hospitalisation. Multinominal logistic regression examined factors predictive of trajectory group membership.

RESULTS

Three PPH trajectory groups were revealed among 17,591 patients: no PPH (89.5%), low PPH (10.0%), and high PPH (0.4%). Key predictors of PPH trajectory group membership were age, number of comorbidities, dementia, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), frailty risk, place of incident, surgery, rehabilitation, and length of hospital stay. The high PPH had a higher proportion of patients with ≥ 2 comorbidities (OR: 1.86, 95% confidence interval (CI): 1.04-3.32) and COPD (OR: 2.97, 95%CIs: 1.76-5.04) than the low PPH, and the low and high PPHs were more likely to have CHF and high frailty risk as well as ≥ 2 comorbidities and COPD than the no PPH.

CONCLUSIONS

Identifying trajectories of PPH after a hip fracture and factors predictive of trajectory group membership could be used to target strategies to reduce multiple readmissions.