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.

Impact of Dementia on Incidence and Severity of Postoperative Pulmonary Complications Following Hip Fracture Surgery Among Older Patients.

Postoperative pulmonary complications (PPCs) are the leading cause of death following hip fracture surgery. Dementia has been identified as a PPC risk factor that complicates the clinical course. By leveraging electronic health records, this retrospective observational study evaluated the impact of dementia on the incidence and severity of PPCs, hospital length of stay, and postoperative 30-day mortality among 875 older patients (≥65 years) who underwent hip fracture surgery between October 1, 2015 and December 31, 2018 at a health system in the southeastern United States. Inverse probability of treatment weighting using propensity scores was utilized to balance confounders between patients with and without dementia to isolate the impact of dementia on PPCs. Regression analyses revealed that dementia did not have a statistically significant impact on the incidence and severity of PPCs or postoperative 30-day mortality. However, dementia significantly extended the hospital length of stay by an average of 1.37 days.

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.

Improving shared decision-making for osteoporosis pharmacologic therapy in nursing homes: a qualitative analysis.

Decisions on whether to use pharmacologic osteoporosis therapy in skilled nursing facility residents are complex and require shared decision-making. Residents, proxies, and staff desire individualized fracture risk estimates that consider advanced age, dementia, and mobility. They want options for reducing administration burden, monitoring instructions, and periodic reassessment of risk vs. benefit. PURPOSE: Decisions about pharmacologic osteoporosis treatment in nursing home (NH) residents with advanced age and multimorbidity are complex and should occur using shared decision-making. Our objective was to identify processes and tools to improve shared decision-making about pharmacologic osteoporosis treatment in NHs. METHODS: Qualitative analysis of data collected in three NHs from residents at high fracture risk, their proxies, nursing assistants, nurses, and one nurse practitioner (n = 28). Interviews explored participants' stories, attitudes, and experiences with oral osteoporosis medication management. Framework analysis was used to identify barriers to shared decision-making regarding osteoporosis treatment in this setting. RESULTS: Participants wanted individualized fracture risk estimates that consider immobility, advanced age, and comorbid dementia. Residents and proxies expected nursing staff to be involved in the decision-making; nursing staff wished to be informed on the relative risks vs. benefits of medications and given monitoring instructions. Two important competing demands to address during the shared decision-making process were burdensome administration requirements and polypharmacy. Participants wanted to reassess pharmacologic treatment appropriateness over time as clinical status or goals of care change. CONCLUSIONS: Shared decision-making using strategies and tools identified in this analysis may move osteoporosis pharmacologic treatment in NHs and for other older adults with multimorbidity from inappropriate inertia to appropriate prescribing or appropriate inaction.

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

This retrospective cohort study used electronic health records to explore the effect of race/ethnicity, insurance status, and area deprivation on post-discharge outcomes in older patients undergoing hip fracture surgery between 2015 and 2018 (N = 1,150). Inverse probability of treatment weight-adjusted regression analysis was used to identify the effects of the predictors on outcomes. White patients had higher 90- and 365-day readmission risks than Black patients and higher all-period readmissions than the Other racial/ethnic (Hispanic, Asian, American Indian, and Multicultural) group (p < .000). Black patients had a higher risk of 30- and 90-day readmission than the Other racial/ethnic group (p < .000). Readmission risk across 1-year follow-up was generally higher among patients from less deprived areas than more deprived areas (p < .05). The 90- and 365-day mortality risk was lower for patients from less deprived areas (vs. more deprived areas) and patients with Medicare Advantage (vs. Medicare), respectively (p < .05). Our findings can guide efforts to identify patients for additional post-discharge support. Nevertheless, the findings regarding readmission risks contrast with previous knowledge and thus require more validation studies.