Catastrophic Health Care Expenditure Following Brachial Plexus Injury.

PURPOSE: Brachial plexus injuries (BPIs) are devastating to patients not only functionally but also financially. Like patients experiencing other traumatic injuries and unexpected medical events, patients with BPIs are at risk of catastrophic health expenditure (CHE) in which out-of-pocket health spending exceeds 40% of postsubsistence income (income remaining after food and housing expenses). The individual financial strain after BPIs has not been previously quantified. The purpose of this study was to assess the proportion of patients with BPIs who experience risk of CHE after reconstructive surgery. METHODS: Administrative databases were used from 8 states to identify patients who underwent surgery for BPIs. Demographics including age, sex, race, and insurance payer type were obtained. Inpatient billing records were used to determine the total surgical and inpatient facility costs within 90 days after the initial surgery. Due to data constraints, further analysis was only conducted for privately-insured patients. The proportion of patients with BPIs at risk of CHE was recorded. Predictors of CHE risk were determined from a multivariable regression analysis. RESULTS: Among 681 privately-insured patients undergoing surgery for BPIs, nearly one-third (216 [32%]) were at risk of CHE. Black race and patients aged between 25 and 39 years were significant risk factors associated with CHE. Sex and the number of comorbidities were not associated with risk of CHE. CONCLUSIONS: Nearly one-third of privately-insured patients met the threshold for being at risk of CHE after BPI surgery. CLINICAL RELEVANCE: Identifying those patients at risk of CHE can inform strategies to minimize long-term financial distress after BPIs, including detailed counseling regarding anticipated health care expenditures and efforts to optimize access to appropriate insurance policies for patients with BPIs.

Care Fragmentation and Mortality in Readmission after Surgery for Hepatopancreatobiliary and Gastric Cancer: A Patient-Level and Hospital-Level Analysis of the Healthcare Cost and Utilization Project Administrative Database.

BACKGROUND: Hepatopancreatobiliary (HPB) and gastric oncologic operations are frequently performed at referral centers. Postoperatively, many patients experience care fragmentation, including readmission to "outside hospitals" (OSH), which is associated with increased mortality. Little is known about patient-level and hospital-level variables associated with this mortality difference. STUDY DESIGN: Patients undergoing HPB or gastric oncologic surgery were identified from select states within the Healthcare Cost and Utilization Project database (2006-2014). Follow-up was 90 days after discharge. Analyses used Kruskal-Wallis test, Youden index, and multilevel modeling at the hospital level. RESULTS: There were 7,536 patients readmitted within 90 days of HPB or gastric oncologic surgery to 636 hospitals; 28% of readmissions (n = 2,123) were to an OSH, where 90-day readmission mortality was significantly higher: 8.0% vs 5.4% (p < 0.01). Patients readmitted to an OSH lived farther from the index surgical hospital (median 24 miles vs 10 miles; p < 0.01) and were readmitted later (median 25 days after discharge vs 12; p < 0.01). These variables were not associated with readmission mortality. Surgical complications managed at an OSH were associated with greater readmission mortality: 8.4% vs 5.7% (p < 0.01). Hospitals with <100 annual HPB and gastric operations for benign or malignant indications had higher readmission mortality (6.4% vs 4.7%, p = 0.01), although this was not significant after risk-adjustment (p = 0.226). CONCLUSIONS: For readmissions after HPB and gastric oncologic surgery, travel distance and timing are major determinants of care fragmentation. However, these variables are not associated with mortality, nor is annual hospital surgical volume after risk-adjustment. This information could be used to determine safe sites of care for readmissions after HPB and gastric surgery. Further analysis is needed to explore the relationship between complications, the site of care, and readmission mortality.

The Risks of Stone Diagnosis and Stone Removal Procedure After Different Bariatric Surgeries.

Introduction: Nephrolithiasis is common after malabsorptive bariatric surgery; however, the comparative risk of stone formation after different bariatric surgeries remains unclear. We seek to compare the risk of stone diagnosis and stone procedure after gastric banding (GB), sleeve gastrectomy (SG), short-limb Roux-en-Y (SLRY), long-limb Roux-en-Y (LLRY), and biliopancreatic diversion with duodenal switch (BPDDS). Patients and Methods: Using an administrative database, we retrospectively identified 116,304 patients in the United States, who received bariatric surgery between 2007 and 2014, did not have a known kidney stone diagnosis before surgery, and were enrolled in the database for at least 1 year before and after their bariatric surgery. We used diagnosis and procedural codes to identify comorbidities and events of interest. Our primary analysis was performed with extended Cox proportional hazards models using time to stone diagnosis and time to stone procedure as outcomes. Results: The adjusted hazard ratio of new stone diagnosis from 1 to 36 months, compared to GB, was 4.54 for BPDDS (95% confidence interval [CI] 3.66-5.62), 2.12 for LLRY (95% CI 1.74-2.58), 2.15 for SLRY (95% CI 2.02-2.29), and 1.35 for SG (95% CI 1.25-1.46). Similar results were observed for risk of stone diagnosis from 36 to 60 months, and for risk of stone removal procedure. Male sex was associated with an overall 1.63-fold increased risk of new stone diagnosis (95% CI 1.55-1.72). Conclusions: BPDDS was associated with a greater risk of stone diagnosis and stone procedures than SLRY and LLRY, which were associated with a greater risk than restrictive procedures. Nephrolithiasis is more common after more malabsorptive bariatric surgeries, with a much greater risk observed after BPDDS and for male patients.

Timing of Cleft Palate Repair in Patients With and Without Robin Sequence.

BACKGROUND: This cohort study aimed to assess how age at repair affects outcomes in nonsyndromic patients with and without Robin Sequence using a national database of commercial healthcare claims. METHODS: Children under 4 years of age undergoing palatoplasty were identified in the IBM MarketScan Commercial Database based on ICD-9-CM and CPT procedure codes. They were divided into Robin and non-Robin cleft palate groups, and further divided by time of initial cleft palate repair: Robin Sequence into 2 groups: age ≤10 months or >10 months; non-Robin cleft palate into 3 groups: age ≤10 months, >10-14 months, or >14 months age. Time to cleft palate revision within each group was assessed using Cox proportional-hazard models. RESULTS: A total of 261 patients with Robin Sequence and 3046 with non-Robin cleft palate were identified. In patients with Robin, later repair was associated with decreased risk of secondary procedures compared with early repair (Hazard Ratio (HR) 0.19, 95%CI 0.09-0.39, P < 0.001). In patients with non-Robin cleft palate, decreased risk of revision compared to early repair was associated both with repair at >10-14 months (adjusted HR 0.40, 95%CI 0.31-0.52, P < 0.001) and > 14 months (adjusted HR 0.71, 95%CI 0.57-0.88, P = 0.002). Adjusting for timing of repair, patients with non-Robin cleft palate were at significantly increased risk of secondary procedure if diagnosed with failure to thrive or anemia in the 30 days prior to palatoplasty. CONCLUSIONS: In patients with and without Robin sequence, cleft palate repair at or before 10 months of age was associated with higher risk for secondary procedures.

Postpartum diabetes screening among low income women with gestational diabetes in Missouri 2010-2015.

BACKGROUND: Gestational diabetes increases risk for type 2 diabetes seven-fold, creating a large public health burden in a young population. In the US, there are no large registries for tracking postpartum diabetes screening among women in under-resourced communities who face challenges with access to care after pregnancy. Existing data from Medicaid claims is limited as women often lose this coverage within months of delivery. In this study, we aim to leverage data from electronic health records and administrative claims to better assess postpartum diabetes screening rates among low income women. METHODS: A retrospective population of 1078 women with gestational diabetes who delivered between 1/1/2010 and 10/8/2015 was generated by linking electronic health record data from 21 Missouri Federally Qualified Health Centers (FQHCs) with Medicaid administrative claims. Screening rates for diabetes were calculated within 12 weeks and 1 year of delivery. Initial screening after the first postpartum year was also documented. RESULTS: Median age in the final population was 28 (IQR 24-33) years with over-representation of black non-Hispanic and urban women. In the final population, 9.7% of women had a recommended diabetes screening test within 12 weeks and 18.9% were screened within 1 year of delivery. An additional 125 women received recommended screening for the first time beyond 1 year postpartum. The percentage of women who had a postpartum visit (83.9%) and any glucose testing (40.6%) in the first year far exceeded the proportion of women with recommended screening tests. CONCLUSIONS: Linking electronic health record and administrative claims data provides a more complete picture of healthcare follow-up among low income women after gestational diabetes. While screening rates are higher than reported with claims data alone, there are opportunities to improve adherence to screening guidelines in this population.

Simplified risk prediction indices do not accurately predict 30-day death or readmission after discharge following colorectal surgery.

BACKGROUND: Risk-prediction indices are one category of the many tools implemented to guide efforts to decrease readmissions. However, using fied models to predict a complex process can prove challenging. In addition, no risk-prediction index has been developed for patients undergoing colorectal surgery. Therefore, we evaluated the performance of a widely utilized simplified index developed at the hospital level - LACE (length of stay, acute admission, Charlson comorbidity index score, and emergency department visits) and developed and evaluated a novel index in predicting readmissions in this patient population. METHODS: Using a retrospective split-sample cohort, patients discharged after colorectal surgery were identified within the inpatient databases of the Healthcare Cost and Utilization Project for the states of New York, California, and Florida (2006-2014). The primary outcome was death or readmission within 30 days after discharge. Multivariable logistic regression models incorporated patient comorbidities, postoperative complications, and hospitalization details, and were evaluated using the C statistic. RESULTS: A total of 440,742 patients met eligibility criteria. The rate of death or readmission within 30 days after discharge was 14.0% (n = 61,757). When applied to surgical patients, the LACE index demonstrated a poor model fit (C = 0.631). The model fit improved significantly-but remained poor (C = 0.654; P < .001)-with the addition of the following variables, which are known to be associated with readmission after colorectal surgery: age, indication for surgery, and creation of a new ostomy. A novel, simplified model also yielded a poor model fit (C = 0.660). CONCLUSION: Postdischarge death or readmission after colorectal surgery is not accurately modeled using existing, modified, or novel simplified risk prediction models. Payers and providers must ensure that quality improvement efforts applying simplified models to complex processes, such as readmissions following colorectal surgery, may not be appropriate, and that models reflect the relevant patient population.