Association of Rurality and Neighborhood Level Socioeconomic Deprivation with Perioperative Health Status in Total Joint Arthroplasty Patients: Analysis from a Large, Tertiary Care Hospital.

BACKGROUND: Individual socioeconomic status (SES) is associated with disparities in access to care and worse outcomes in total joint arthroplasty (TJA). Neighborhood-level SES measures are sometimes used as a proxy for individual-level SES, but the validity of this approach is unknown. We examined neighborhood level SES and rurality on perioperative health status in TJA. METHODS: The study population comprised 46,828 TJA surgeries performed at a tertiary care hospital. Community area deprivation index (ADI) was derived from the 2015 American Census Survey. Logistic regression was used to examine perioperative characteristics by ADI and rurality. RESULTS: Compared to patients from the least deprived neighborhoods, patients from the most deprived neighborhoods were likely to be female (odds ratioOR 1.46, 95% confidence interval CI: 1.33-1.61), non-white (OR 1.36, 95% CI: 1.13-1.64), with education high school or less (OR 4.85, 95% CI: 4.35-5.41), be current smokers (OR 2.20, 95% CI: 1.61-2.49), have BMI>30 kg/m2 (OR 1.43, 95% CI: 1.30-1.57), more limitation on instrumental activities of daily living (OR 1.75, 95% CI: 1.55-1.97) and American Society of Anesthesiologists (ASA) score > II (OR 2.0, 95% CI: 1.11-1.37). There was a progressive association between the degree of area level deprivation with preexisting comorbidities. Patients from rural communities were more likely to be male, white, have body mass index (BMI)>30 kg/m2 and lower education levels. However, rurality was either not associated or negatively associated with comorbidities. CONCLUSION: TJA patients from lower SES neighborhoods have worse behavioral risk factors and higher comorbidity burden than patients from higher SES neighborhoods. Patients from rural communities have worse behavioral risk factors but not comorbidities.

Disease Profile and Oncologic Outcomes After Delayed Diagnosis of Human Papillomavirus-Associated Oropharyngeal Cancer.

OBJECTIVE: Diagnostic delay in human papillomavirus-associated oropharynx squamous cell carcinoma (HPV(+)OPSCC) is common due to nonspecific symptoms. We aim to describe the disease burden and oncologic outcomes of patients with HPV(+)OPSCC diagnosed >12 months after symptom onset. STUDY DESIGN: This is a retrospective cohort study of HPV(+)OPSCC patients receiving intent-to-cure treatment (including surgery ± adjuvant therapy or primary chemoradiation). SETTING: 2006-2016, tertiary care center. METHODS: Tumor stage was compared between patients with and without delayed diagnosis using χ2 tests. Kaplan-Meier survival analysis with univariate and multivariable Cox regressions were used to determine the effect of diagnostic delay on oncologic outcomes. RESULTS: In total, 664 patients were included. Compared to patients diagnosed <12 months from symptom onset (n = 601), those diagnosed at >12 months (n = 63) were more likely to have T4 disease and higher overall American Joint Committee on Cancer (AJCC) clinical stage at presentation (P < .01 for both). At 5 years, rates of overall survival, cancer-specific survival, progression-free survival, and distant metastases-free survival in the delayed diagnosis cohort were 80%, 90%, 80%, and 89%, respectively. A >12-month delay in diagnosis did not significantly impact overall survival (adjusted hazard ratio [aHR], 1.16; 95% CI, 0.58-2.31), cancer-specific survival (aHR, 0.83; 95% CI, 0.29-2.39), progression-free survival (aHR, 1.15; 95% CI, 0.56-2.37), or distant metastases-free survival (aHR, 1.00; 95% CI, 0.42-2.40) after adjusting for age, sex, and clinical AJCC stage (P > .05 for all). CONCLUSIONS: Delayed diagnosis of HPV(+)OPSCC is associated with greater burden of disease at presentation, but oncologic outcomes remain favorable across treatment modalities. When appropriate, intent-to-cure therapy should be pursued despite diagnostic delay. LEVEL OF EVIDENCE: Level III.

Episode-based payment: evaluating the impact on chronic conditions.

BACKGROUND: Policy makers are interested in aggregating fee-for-service reimbursement into episode-based bundle payments, hoping it will lead to greater efficiency in the provision of care. The focus of bundled payment initiatives has been upon surgical or discrete procedures. Relatively little is known about calculating and implementing episode-based payments for chronic conditions. OBJECTIVE: Compare the differences in two different episode-creation algorithms for two common chronic conditions: diabetes and coronary artery disease (CAD). STUDY DESIGN: We conducted a retrospective evaluation using enrollees with continuous coverage in a self-funded plan from 2003 to 2006, meeting Healthcare Effectiveness Data and Information Set (HEDIS) criteria for diabetes or CAD. For each condition, an annual episode-based payment was assessed using two algorithms: Episode Treatment Groups (ETGs) and the Prometheus model. PRINCIPAL FINDINGS: We began with 1,580 diabetes patients with a 4-year total payment mean of $67,280. ETGs identified 1,447 (92%) as having diabetes with 4-year episode-based mean payments of $12,731; while the Prometheus model identified 1,512 (96%) as having diabetes, but included only 1,195 of them in the Prometheus model with mean diabetes payments of $23,250. Beginning with 1,644 CAD patients with a 4-year total payment mean of $65,661, ETGs identified 983 patients (60%) with a 4-year episode-based mean of $24,362. The Prometheus model identified 1,135 (69%) as CAD patients with 948 CAD patients having a mean of $26,536. CONCLUSIONS: The two episode-based methods identify different patients with these two chronic conditions. In addition, there are significant differences in the episode-based payment estimates for diabetes, but similar estimates for CAD. Implementing episode-based payments for chronic conditions is challenging, and thoughtful discussions are needed to determine appropriate payments.

Effect of multiple chronic conditions among working-age adults.

OBJECTIVE: To determine the longitudinal effect on healthcare costs of multiple chronic conditions among adults aged 18 to 64 years. STUDY DESIGN: Retrospective cohort assessment of working-age employees and their dependents with continuous coverage in a self-funded health plan from January 1, 2004, to December 31, 2007. Data were obtained from health benefit enrollment files and from medical and pharmacy claims. METHODS: Individuals were defined as having chronic conditions based on modification of a published method. The mean annual healthcare costs were estimated for individuals with 0, 1, 2, 3, 4, or 5 or more chronic conditions. The probability of persistence in high-cost categories across years was estimated for individuals in each group. RESULTS: Overall, 75.3% of working-age adult enrollees had at least 1 chronic condition, 54.3% had multiple chronic conditions, and 16.5% had 5 or more chronic conditions. The cost of healthcare was higher among individuals with more chronic conditions for all ages. The mean medical cost per year for an individual with no chronic conditions was $2137, while that for an individual with 5 or more chronic conditions was $21,183. Enrollees with more chronic conditions had higher persistence in high-cost categories between years and persisted at these high costs for more years. CONCLUSIONS: While multiple chronic conditions are common in the population 65 years and older, they are also of great concern for the working-age population. Understanding how to effectively manage individuals with multiple chronic conditions is an important challenge. Effective care management focused on managing the patient as opposed to a condition has the potential to significantly affect healthcare costs.