Effect of Race/ethnicity, Insurance Status, and Area Deprivation on Hip Fracture Outcomes Among Older Adults in the United States

Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study

Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value < .05). The most robust associations were between metastatic carcinoma and mild liver disease, myocardial infarction and congestive heart failure, and hemi/paraplegia and cerebrovascular disease (OER > 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.

Association of patient characteristics with the receipt of regional anesthesia

BACKGROUND

Regional anesthesia (RA) may improve patient-related outcomes, including decreased operative complications, shortened recovery times, and lower hospital readmission rates. More analyses are needed using a diverse set of databases to examine characteristics associated with the receipt of RA.

METHODS

A national hospital database was queried for patients 18 years or older who underwent total shoulder arthroplasty (TSA), total knee arthroplasty (TKA), anterior cruciate ligament reconstruction (ACLR), carpal tunnel release, ankle open reduction, and internal fixation and arteriovenous fistula creation between January 2016 and June 2021. Regional techniques included neuraxial anesthesia and various upper and lower extremity peripheral nerve blocks to create a binary variable of RA receipt. Univariate statistics were used to compare characteristics associated based on RA receipt and multivariable regression identified factors associated with RA receipt.

RESULTS

A total of 51 776 patients were included in the analysis, of which 2111 (4.1%) received RA. Factors associated with decreased odds of RA receipt included black race (vs white race; OR 0.73, 95% CI 0.62 to 0.86), other non-white race (vs white race; OR 0.71, 95% CI 0.61 to 0.86), American Society of Anesthesiologists (ASA) class (vs ASA 1; OR 0.85, 95% CI 0.79 to 0.93), and Medicaid insurance (vs private insurance; OR 0.65, 95% CI 0.51 to 0.82) (all p<0.05). When compared with TKA, ACLR (OR 0.67, 95% CI 0.53 to 0.84), ankle open reduction and internal fixation (OR 0.68, 95% CI 0.58 to 0.81), and carpal tunnel release (OR 0.68, 95% CI 0.59 to 0.78) demonstrated lower odds of RA receipt, whereas TSA (OR 1.31, 95% CI 1.08 to 1.58) demonstrated higher odds of RA receipt (all p<0.05).

CONCLUSION

RA use varies with respect to race, insurance status, and type of surgery.

Impact of Dementia on Long-Term Hip Fracture Surgery Outcomes: An Electronic Health Record Analysis

OBJECTIVE

Older adults with dementia are at higher risk for sustaining hip fracture and their long-term health outcomes after surgery are usually worse than those without dementia. Widespread adoption of electronic health records (EHRs) may allow hospitals to better monitor long-term health outcomes in patients with dementia after hospitalization. This study aimed to (1) estimate how dementia influences discharge location, mortality, and readmission 180 days and 1 year after hip fracture surgery in older adults, and (2) demonstrate the feasibility of using selection-bias reduced EHR data for research and long-term health outcomes monitoring.

DESIGN

Retrospective observational cohort study using EHRs.

SETTING AND PARTICIPANTS

A cohort of 1171 patients over age 65 years who had an initial hip fracture surgery between October 2015 and December 2018 was extracted from EHRs of one health system; 376 of these patients had dementia.

METHODS

Logistic regression was applied to estimate influences of dementia on discharge disposition and Cox proportional hazards model for mortality. The Fine and Gray regression model was used to analyze readmission, accounting for the competing risk of death. To reduce selection bias in EHRs, inverse probability of treatment weighting using propensity scores was implemented before modeling.

RESULTS

Dementia had significant impacts on all outcomes: being discharged to facilities [odds ratio (OR) = 2.11, 95% confidence interval (CI) 1.19-3.74], 180-day mortality [hazard ratio (HR) = 1.69, 95% CI 1.20-2.38], 1-year mortality (HR = 1.78, 95% CI 1.33-2.38), 180-day readmission (HR = 1.62, 95% CI 1.39-1.89), and 1 year readmission (HR = 1.39, 95% CI 1.21-1.58).

CONCLUSIONS AND IMPLICATIONS

Dementia was a significant risk factor for worse long-term outcomes. The inverse probability of treatment weighting approach can be used to reduce selection bias in EHR data for research and monitoring long-term health outcomes in the target population. Such monitoring could foster collaborations with post-acute and long-term health care services to improve recovery outcomes in patients with dementia after hip fracture surgery.