Who Will be the Costliest Patients? Using Recent Claims to Predict Expensive Surgical Episodes

Concentration of High-Cost Head and Neck Cancer Surgical Patients

OBJECTIVE

Health care costs are disproportionately concentrated among a small number of patients. We sought to identify variables associated with high-cost patients and high hospital concentration of high-cost patients and to examine associations with short-term outcomes in head and neck cancer (HNCA) surgery.

STUDY DESIGN

The Nationwide Inpatient Sample was used to identify 170,577 patients who underwent HNCA surgery in 2001-2011. High-cost patients were defined as patients whose costs of care were in the top decile, and high-concentration hospitals were defined as those whose percentage of high-cost patients was in the top decile.

METHODS

Multivariable regression was used to evaluate associations between cost and patient and hospital variables, postoperative complications, and in-hospital mortality.

RESULTS

Costs associated with high-cost patients were 4.47-fold greater than the remaining 90% of patients. High-concentration hospitals treated 36% of all high-cost patients. High-cost patients were more likely to be non-white (OR = 2.08 [1.45-2.97]), have oral cavity cancer (OR = 1.21 [1.05-1.39]), advanced comorbidity (OR = 1.53 [1.31-1.77]), Medicaid (OR = 1.93 [1.62-2.31]) or self-pay payor status (OR = 1.72 [1.38-2.14]), income>50th percentile (OR = 1.25 [1.05-1.51]), undergo major procedures (OR = 3.52 [3.07-4.05]) and have non-routine discharge (OR = 7.50 [6.01-9.35]). High-concentration hospitals were more likely to be teaching hospitals (OR = 3.14 [1.64-6.05]) and less likely to be urban (OR = 0.20 [0.04-0.93]). After controlling for all other variables, high-cost patients were associated with an increased odds of mortality (OR = 8.00 [5.89-10.85]) and postoperative complications (OR = 5.88 [5.18-6.68]). High-concentration hospitals were associated with an increased odds of postoperative complications (OR = 1.31 [1.08-1.61]) but were not associated with increased mortality (OR = 0.98 [0.67-1.44]).

CONCLUSIONS

High-cost HNCA surgical patients are associated with increased postoperative morbidity and mortality, and are disproportionately concentrated at teaching hospitals.

LEVEL OF EVIDENCE

4 Laryngoscope, 2024.

Surgical markup in lung cancer resection, 2015-2020

Objective

The objective of this study was to assess procedure markup (charge-to-cost ratio) across lung resection procedures and examine variability by geographic region.

Methods

Provider-level data for common lung resection operations was obtained from the 2015 to 2020 Medicare Provider Utilization and Payment Data datasets using Healthcare Common Procedure Coding System codes. Procedures studied included wedge resection; video-assisted thoracoscopic surgery; and open lobectomy, segmentectomy, and mediastinal and regional lymphadenectomy. Procedure markup ratio and coefficient of variation (CoV) was assessed and compared across procedure, region, and provider. The CoV, a measure of dispersion defined as the ratio of the SD to the mean, was likewise compared across procedure and region.

Results

Median markup ratio across all procedures was 3.56 (interquartile range, 2.87-4.59) with right skew (mean, 4.13). Median markup ratio was 3.59 for lymphadenectomy (CoV, 0.51), 3.13 for open lobectomy (CoV, 0.45), 3.55 for video-assisted thoracoscopic surgery lobectomy (CoV, 0.59), 3.77 for segmentectomy (CoV, 0.74), and 3.80 for wedge resection (CoV, 0.67). Increased beneficiaries, services, and Healthcare Common Procedure Coding System score (total) were associated with a decreased markup ratio (P < .0001). Markup ratio was highest in the Northeast at 4.14 (interquartile range, 3.09-5.56) and lowest in the South (Markup ratio 3.26; interquartile range, 2.68-4.02).

Conclusions

We observe geographic variation in surgical billing for thoracic surgery.

Low Urologist Density Predicts High-Cost Surgical Treatment of Stone Disease

Introduction and Objectives: Lack of access to urologic specialists is approaching crisis levels as the number of urologists is decreasing, while the demand for urologic care is increasing. The financial implications of this have not been explored. The objective of this study is to examine the impact of access and other patient factors on cost to treat urolithiasis. We hypothesized that markers of poor access would associate with higher costs of surgical encounters for patients presenting with urolithiasis. Methods: A retrospective review of prospectively collected data from the Registry for Stones of the Kidney and Ureter (ReSKU) from September 2015 to July 2018 was conducted to investigate characteristics of surgical patients treated for urinary stone disease. Univariate analysis was performed using the Welch two-sample t-test. Multivariate analysis was performed using logistic regression. Statistical analysis was performed in R version 3.5. Results: When taking into account age, delayed presentation, procedure type, stone size >20 mm, American Society of Anesthesiologists (ASA) code, gender, race, income, distance, urologist density, body mass index, diabetes, infection, education, language, insurance, and stone complexity, patients undergoing percutaneous nephrolithotomy procedure (p < 0.001; odds ratio [OR] 12.9, confidence interval [CI] 4.05-48.5), urologist density in the bottom quartile (p = 0.014; OR 4.66, CI 1.40-16.9), diabetes (p = 0.018; OR 4.38, CI 1.32-15.6), and infection (p = 0.007; OR 4.51, CI 1.55-14.0) were the only variables statistically significant for association with top quartile of total cost. Conclusions: Surgical encounter costs are largely dictated by patient clinical factors, but low regional urologist density appears to independently predicted for high-cost stone surgery. Increasing patients' access to a urologist may prove to be financially beneficial in the longitudinal reduction in health care costs for stone disease.