Lost in Follow-Up: Predictors of Patient No-Shows to Clinic Follow-Up After Abdominal Injury

The effect of social determinants of health on patient outcomes in acute trauma: A systematic review

INTRODUCTION

Social determinants of health (SDoH) may mediate disparities, but their effect on outcomes after trauma is not well known. The purpose of this review is to improve existing gaps of knowledge for a broad range of SDoH and trauma-related outcomes.

METHODS

This was a systematic search to identify studies that evaluated the effect of race, insurance status, socioeconomic status (SES), health literacy, and community deprivation on inpatient mortality, morbidity, and post-discharge health care utilization in diverse trauma populations ≥16 years. Data were extracted on study design, patient and injury characteristics, outcomes, and covariates. Qualitative analysis was performed and reported results were stratified by exposure. An overall assessment of the strength of evidence for key clinically relevant comparisons was conducted.

RESULTS

60 studies were included. Overall, race was not meaningfully predictive of mortality or morbidity, with evidence reporting inconsistent or small magnitude of effects. However, African American/Black race was consistently associated with decreased odds of discharge to rehabilitation. Compared to insured patients, uninsured patients may have greater mortality risk and be less likely to discharge to rehabilitation. Studies evaluating health literacy or community deprivation reported conflicting results.

CONCLUSIONS

Disparities related to race are most profound for post-discharge health care utilization, while insurance status may be a strong negative predictor of both mortality and discharge disposition. More research is needed on health literacy and community deprivation to better understand mechanisms of disparity after trauma. Interventions targeted at improving continuity of inpatient and outpatient care may be beneficial.

Risk Factors for Missed Follow-up Appointments among Facial Trauma Patients

A retrospective case-control study was performed to characterize the rate of missed follow-up appointments after facial trauma and identify associated risk factors.Follow-up appointments for facial trauma over a 3-month period at a single, safety net hospital were analyzed. Appointment-specific, sociodemographic, trauma, and management data were compared between cases (missed appointments) and controls (attended appointments). Univariate testing and multivariable logistic regression were employed.A total of 116 cases and 259 controls were identified, yielding a missed appointment rate of 30.9% (116/375). Missed appointments were significantly associated with initial clinic appointments compared to return visits (odds ratio [OR] 2.21 [1.38-3.54]), afternoon visits compared to morning (OR 3.14 [1.94-5.07]), lack of private health insurance (OR 2.91 [1.68-5.18]), and presence of midface fractures (OR 2.04 [1.28-3.27]). Missed appointments were negatively associated with mandible fractures (OR 0.56 [0.35-0.89]), surgical management (OR 0.48 [0.30-0.77]), and the presence of nonremovable hardware (OR 0.39 [0.23-0.64]). Upon multivariable logistic regression, missed appointments remained independently associated with afternoon visits (adjusted OR [aOR] 1.95 [1.12-3.4]), lack of private health insurance (aOR 2.73 [1.55-4.8]), and midface fractures (aOR 2.09 [1.21-3.59]).Nearly one-third of facial trauma patients missed follow-up appointments, with the greatest risk among those with afternoon appointments, lacking private health insurance, and with midface fractures.

A comparison of the psychometric properties of a person-administered vs. automated screening tool for posttraumatic stress disorder (PTSD) in traumatically injured patients

BACKGROUND

The American College of Surgeons Committee on Trauma (ACS-CoT) mandated that trauma centers have mental health screening and referral protocols in place by 2023. This study compares the Injured Trauma Survivor Screen (ITSS) and the Automated Electronic Medical Record (EMR) Screen to assess their performance in predicting risk for posttraumatic stress disorder (PTSD) within the same sample of trauma patients to inform trauma centers' decision when selecting a tool to best fit their current clinical practice.

METHODS

This was a secondary analysis of three prospective cohort studies of traumatically injured patients (N = 255). The ITSS and Automated EMR Screen were compared using receiver operating characteristic curves to predict risk of subsequent PTSD development. PTSD diagnosis at 6-month follow-up was assessed using the Clinician Administered PTSD Scale for DSM-5.

RESULTS

Just over half the sample screened positive on the ITSS (57.7%), while 67.8% screened positive on the Automated EMR Screen. The area under the curve (AUC) for the two screens was not significantly different (ITSS AUC = 0.745 versus Automated EMR Screen AUC = 0.694, p = 0.21), similar performance in PTSD risk predication within the same general trauma population. The ITSS and Automated EMR Screen had similar sensitivities (86.5%, 89.2%), and specificities (52.5%, 40.9%) respectively at their recommended cut-off points.

CONCLUSION

Both screens are psychometrically comparable. Therefore, trauma centers considering screening tools for PTSD risk to comply with the ACS-CoT 2023 mandate should consider their local resources and patient population. Regardless of screen selection, screening must be accompanied by a referral process to address the identified risk.