Financial toxicity after trauma and acute care surgery: From understanding to action

Financial toxicity part II: A practical guide to measuring and tracking long-term financial outcomes among acute care surgery patients

ABSTRACT

Acute care surgery (ACS) patients are frequently faced with significant long-term recovery and financial implications that extend far beyond their hospitalization. While major injury and emergency general surgery (EGS) emergencies are often viewed solely as acute moments of crisis, the impact on patients can be lifelong. Financial outcomes after major injury or emergency surgery have only begun to be understood. The Healthcare Economics Committee from the American Association for the Surgery of Trauma previously published a conceptual overview of financial toxicity in ACS, highlighting the association between financial outcomes and long-term physical recovery. The aims of second-phase financial toxicity review by the Healthcare Economics Committee of the American Association for the Surgery of Trauma are to (1) understand the unique impact of financial toxicity on ACS patients; (2) delineate the current limitations surrounding measurement domains of financial toxicity in ACS; (3) explore the "when, what and how" of optimally capturing financial outcomes in ACS; and (4) delineate next steps for integration of these financial metrics in our long-term patient outcomes. As acute care surgeons, our patients' recovery is often contingent on equal parts physical, emotional, and financial recovery. The ACS community has an opportunity to impact long-term patient outcomes and well-being far beyond clinical recovery.

Association of social determinants of health International Classification of Disease, Tenth Edition clinical modification codes with outcomes for emergency general surgery and trauma admissions

BACKGROUND

Patients with Acute Care Surgery needs (ie, emergency general surgery diagnosis or trauma admission) are at particularly high risk for nonmedical patient-related factors that can be important drivers of healthcare outcomes. These social determinants of health are typically ascertained at the geographic area level (ie, county or neighborhood) rather than at the individual patient level. Recently, the International Classification of Diseases Tenth Revision, Tenth Edition created codes to capture health hazards related to patient socioeconomic and psychosocial circumstances. We sought to characterize the impact of these social determinants of health-related codes on perioperative outcomes among patients with acute care surgery needs.

METHODS

Patients diagnosed between 2017 and 2020 with acute care surgery needs (ie, emergency general surgery diagnosis or a trauma admission) were identified in the California Department of Healthcare Access and information Patient Discharge database. Data on concomitant social determinants of health-related codes (International Classification of Diseases Tenth Revision, Tenth Edition Z55-Z65), which designated health hazards related to socioeconomic and psychosocial (socioeconomic and psychosocial, respectively) circumstances, were obtained. After controlling for patient factors, including age, sex, race, payer type, and admitting hospital, the association of socioeconomic and psychosocial codes with perioperative outcomes and hospital disposition was analyzed.

RESULTS

Among 483,280 with an acute care surgery admission (emergency general surgery: n = 289,530, 59.9%; trauma: n = 193,705, 40.1%) mean age was 56.5 years (standard deviation: 21.5) and 271,911 (56.3%) individuals were male. Overall, 16,263 (3.4%) patients had a concomitant socioeconomic and psychosocial diagnosis code. The percentage of patients with a concurrent social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis increased throughout the study period from 2.6% in 2017 to 4.4% in 2020. Patients that were male (odds ratio 1.89; 95% confidence interval 1.82, 1.96), insured by Medicaid (odds ratio 5.43; 95% confidence interval 5.15, 5.72) or self-pay (odds ratio 3.04; 95% confidence interval 2.75, 3.36) all had higher odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. Black race did not have a significant association with an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis (odds ratio 0.99; 95% confidence interval 0.94, 1.04); however, Hispanic (odds ratio 0.44; 95% confidence interval 0.43, 0.46) and Asian (odds ratio 0.40; 95% confidence interval 0.36, 0.44) race/ethnicity was associated with a lower odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. After controlling for competing risk factors on multivariable analyses, the risk-adjusted probability of hospital postoperative death was 3.1% (95% confidence interval 2.8, 3.4) among patients with a social determinants of health diagnosis versus 5.9% (95% confidence interval 5.9, 6.0) (odds ratio 0.48; 95% confidence interval 0.44, 0.54) among patients without a social determinants of health diagnosis. Risk-adjusted complications were 26.7% (95% confidence interval 26.1, 37.3) among patients with a social determinants of health diagnosis compared with 31.9% (95% confidence interval 31.7, 32.0) (odds ratio 0.74; 95% confidence interval 0.71, 0.77) among patients without a social determinants of health diagnosis.

CONCLUSION

International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code use was low, with only 3.4% of patients having documentation of a socioeconomic and psychosocial circumstance. The presence of an International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code was not associated with greater odds of complications or death; however, it was associated with longer length of stay and higher odds of being discharged to a skilled nursing facility.

Do hospital-based emergency Medicaid programs benefit trauma centers? A mixed-methods analysis

INTRODUCTION

Hospital Presumptive Eligibility (HPE) is a temporary Medicaid insurance at hospitalization, which can offset patient costs of care, increase access to postdischarge resources, and provide a path to sustain coverage through Medicaid. Less is known about the implications of HPE programs on trauma centers (TCs). We aimed to describe the association with HPE and hospital Medicaid reimbursement and characterize incentives for HPE participation among hospitals and TCs. We hypothesized that there would be financial, operational, and mission-based incentives.

METHODS

We performed a convergent mixed methods study of HPE hospitals in California (including all verified TCs). We analyzed Annual Financial Disclosure Reports from California's Department of Health Care Access and Information (2005-2021). Our primary outcome was Medicaid net revenue. We also conducted thematic analysis of semistructured interviews with hospital stakeholders to understand incentives for HPE participation (n = 8).

RESULTS

Among 367 California hospitals analyzed, 285 (77.7%) participate in HPE, 77 (21%) of which are TCs. As of early 2015, 100% of TCs had elected to enroll in HPE. There is a significant positive association between HPE participation and net Medicaid revenue. The highest Medicaid revenues are in HPE level I and level II TCs. Controlling for changes associated with the Affordable Care Act, HPE enrollment is associated with increased net patient Medicaid revenue ( b = 6.74, p < 0.001) and decreased uncompensated care costs ( b = -2.22, p < 0.05). Stakeholder interviewees' explanatory incentives for HPE participation included reduction of hospital bad debt, improved patient satisfaction, and community benefit in access to care.

CONCLUSION

Hospital Presumptive Eligibility programs not only are a promising pathway for long-term insurance coverage for trauma patients but also play a role in TC viability. Future interventions will target streamlining the HPE Medicaid enrollment process to reduce resource burden on participating hospitals and ensure ongoing patient engagement in the program.

LEVEL OF EVIDENCE

Economic And Value Based Evaluations; Level II.

Multicenter evaluation of financial toxicity and long-term health outcomes after injury

BACKGROUND

Despite the growing awareness of the negative financial impact of traumatic injury on patients' lives, the association between financial toxicity and long-term health-related quality of life (hrQoL) among trauma survivors remains poorly understood.

METHODS

Patients from nine trauma centers participating in a statewide trauma quality collaborative had responses from longitudinal survey data linked to inpatient trauma registry data. Financial toxicity was defined based on patient-reported survey responses regarding medical debt, work or income loss, nonmedical financial strain, and forgone care due to costs. A financial toxicity score ranging from 0 to 4 was calculated. Health-related quality of life was assessed using the EuroQol 5 Domain tool. Multivariable regression models evaluated the association between financial toxicity and hrQoL outcomes while adjusting for patient demographics, injury severity and inpatient treatment intensity, and health systems variables.

RESULTS

Among the 403 patients providing 510 completed surveys, rates of individual financial toxicity elements ranged from 21% to 46%, with 65% of patients experiencing at least one element of financial toxicity. Patients with any financial toxicity had worse summary measures of hrQoL and higher rates of problems in all five EuroQol 5 Domain domains ( p < 0.05 for all). Younger age, lower household income, lack of insurance, more comorbidities, discharge to a facility, and air ambulance transportation were independently associated with higher odds of financial toxicity ( p < 0.05 for all). Injury traits and inpatient treatment intensity were not independently associated with financial toxicity.

CONCLUSION

A majority of trauma survivors in this study experienced some level of financial toxicity, which was independently associated with worse risk-adjusted health outcomes across all hrQoL measures. Risk factors for financial toxicity are not related to injury severity or treatment intensity but rather to sociodemographic variables and measures of prehospital and posthospital health care resource utilization. Targeted interventions and policies are needed to address financial toxicity and ensure optimal recovery for trauma survivors.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.