Frequent hospital readmissions can put a significant burden on patients and their families as well as the healthcare system. This study examines the predictability of the EPIC-calculated chance of survival (ECCS) index score on hospital readmission rates. This cross-sectional study used data collected from February 2022 to November 2022 at a large Level 1 Trauma Center hospital in Virginia. ECCS was categorized as high-risk/low likelihood of survival (<53); and low risk/high likelihood of survival (≥53). Total of 3,237 adult (>18 years) patient charts were reviewed. We used logistic regression models to predict hospital readmissions within 30 days of initial hospitalizations and emergency department (ED) visits. Models were adjusted for sociodemographic variables, palliative care, and presence of advance care planning. Compared to those with an ECCS score ≥53, patients with a score <53 had a higher 30-day hospital readmission rate (52.2% vs. 39.7%). They were 59% more likely to have 30-day hospital readmissions (aOR,1.59, 95%CI:1.32 – 1.92), and 63% more at risk of having ≥3 hospital readmissions (aOR,1.63, 95%CI:1.14 – 2.33). Patients with an ECCS score <53 were 26% more likely to have ≥3 ED visits (aOR,1.26, 95%CI:0.94 – 1.68). All ratios were statistically significant, p<0.0001. ECCS score in the EPIC EMR system is a useful tool for physicians to identify patients at higher risk of hospital readmissions,allowing for early serious illness conversations and improving quality of care. This is a key element of patient-centered care that can help reduce the burden of morbidity and promote optimal use of healthcare resources.

Follow-up nonadherence can lead to suboptimal outcomes for orthopedic patients. Prior studies reveal conflicting significance of factors affecting patient follow-up adherence. We identified characteristics of patients who were lost to follow-up (LTFU) and examined the impact of the distance patients travel to the treatment center on follow-up adherence. A retrospective chart review of patients who underwent open reduction internal fixation (ORIF) from 2015-2020 at a Level-1 trauma center was performed. Demographics, comorbidities, and post-operative follow-ups within one year of surgery were recorded. Driving distance and time traveled to appointments were determined based on the distance between patients’ home zip codes and treatment center zip code using Google Map Application Programming Interface (API). Patients who did not complete their final recommended follow-up appointment were considered LTFU. Logistic regression analysis on the association of LTFU with driving distance, travel time, and other pertinent demographic and health variables was performed. 609 patients were included with a mean driving distance of 20.28 miles (SD=28.49) with 28.42 minute driving time on average (SD=29.15). 48.77% (N=297) of patients were LTFU within a year of surgery. Driving distance was not associated with the likelihood of being LTFU. Patients who were LTFU had slightly lower BMI and were more likely to use tobacco, while those who completed their final recommended follow-up were more likely to be white and women. These results can help identify patients who are at increased risk for LTFU and provide opportunities for interventions that increase follow-up adherence and decrease LTFU.

Distance to treatment center is a well-established factor that directly correlates with patient morbidity and mortality in trauma cases. The purpose of our study was to determine if distance from the patient’s home to follow-up appointments was associated with a higher rate of post-operative complications after open reduction internal fixation (ORIF) surgery.

609 adults who underwent ORIF at a Level-1 trauma center from 2015-2020 were included in this retrospective cohort study. Demographic information, comorbidities, post-operative complications, and follow-up adherence data were obtained via chart review. Driving distance and time traveled to appointments was calculated based on the distance between patients’ home zip code and treatment center zip code. Descriptive statistics, logistic regression, and multi-variate analysis were used to analyze associations within the collected data.

There was a mean driving distance of 20.28 miles (SD=28.49). 39.86% (N=228) of patients experienced at least one post-operative complication, with an average number of complications of 0.797 (SD=1.286). The number of post-operative complications was not associated with driving distance between patient’s home and the treatment center, the time at which the patient was lost to follow-up, race, gender, or age. Smokers were more likely to have post-operative complications. Patients with more completed follow-up appointments and those with longer hospital stays were more likely to have post-operative complications.

These results demonstrate that distance to treatment is not a contributing factor to post-operative complications after ORIF in our patient population, but further research should be conducted in different geographical regions with higher mean travel distances or times.

Objectives. To assess whether 30-day all-cause hospital readmissions are associated with self-reported health-related social needs (HRSNs).

Methods. A cross-sectional, retrospective study of 3896 patients who were discharged from inpatient medicine units at Flushing Hospital Medical Center between August 2022 and August 2023. Descriptive statistics and multivariate logistic regression analyses were conducted using R. All models were adjusted for race, ethnicity, age, and sex assigned at birth.

Results. We examined four HRSN domains: housing instability, food insecurity, transportation difficulties, and interpersonal safety. Based on their responses, patients were grouped into three risk categories: low (73.1%), medium (21.2%), and high (5.7%). For overall HRSN, medium-risk patients had 28% greater odds (OR 1.28, 95% CI 1.02 - 1.58, p=.028) and high-risk patients had 78% greater odds (OR 1.78, 95% CI 1.25 - 2.49, p=.001) of readmission than low-risk patients. Patients at high risk for housing instability, food insecurity, and transportation difficulties had 125% (OR 2.25, 95% CI 1.10 - 4.29, p=.018), 169% (OR 2.69, 95% CI 1.30 - 5.24, p=.005), and 177% (OR 2.77, 95% CI 1.38 - 5.26, p=.003) greater odds of readmission than low-risk patients, respectively. In comparison to low-risk respondents, patients who were medium and high risk for interpersonal safety had 42% (OR 1.42, 95% CI 1.10 - 1.80, p=.005) and 144% (OR 2.44, 95% CI 1.21 - 4.60, p=.008) greater odds of readmission, respectively.

Conclusion. This study provides insight into the relationship between HRSN diagnoses and hospital readmission. Implementing strategies that address HRSNs, such as standardized screening and streamlined referrals, may reduce preventable readmissions.