Introduction: Many patients exhibit subsyndromal clinical findings of schizophrenia prior to diagnosis. Early treatment may mitigate schizophrenia development, yet little is known about comorbidities and healthcare resource utilization (HCRU) in these patients before diagnosis. Methods: This retrospective, longitudinal cohort study, conducted between January 1, 2007 and April 30, 2016, used claims data from the US HealthCore Integrated Research Database. Newly diagnosed patients with schizophrenia (International Classification of Diseases, Ninth Revision: 295.x or ICD 10 F20.%) were identified and matched (1:4) with non-schizophrenia comparators. Patients were 15-54 years of age with either >= 1 inpatient/emergency room claim with a primary schizophrenia diagnosis, or >= 2 claims in any setting with any schizophrenia diagnosis. Demographics, comorbidities, physician specialties, medications, and related services, and other HCRU were compared between cohorts for up to 5 years before diagnosis. Results: The schizophrenia cohort included 6732 patients (57.4% male, mean age 30.3 years for males and 36.2 years for females). All outcomes were more prevalent in the schizophrenia cohort than the comparator cohort. Substantial comorbidity, medication use, and HCRU were observed in the schizophrenia cohort even 4-5 years before diagnosis with increasing findings approaching diagnosis. From 4-5 years to 0-12 months before diagnosis, resource use increased from 205% to 533% for atypical antipsychotics, 29.3% to 48.2% for antidepressants, and 15.1% to 355% for psychiatric diagnostic examinations. Conclusions: Patients with schizophrenia extensively use healthcare resources up to 5 years before diagnosis. Our findings may help with developing predictive models to identify patients at high risk of schizophrenia. (C) 2019 Published by Elsevier B.V.

BACKGROUNDChronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality and is associated with substantial economic burden. There is a lack of data regarding COPD outcomes and costs in a real-world setting, particularly by Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity.OBJECTIVESTo (a) characterize a commercially insured U.S. population with COPD and (b) assess prevalence of exacerbations, health care resource utilization (HCRU), costs, and treatment patterns in a cohort of patients with confirmed COPD, overall and stratified by GOLD stage.METHODSThis retrospective observational cohort study used administrative claims data from the HealthCore Integrated Research Database to identify patients with ≥ 1 inpatient, emergency room (ER), or office visit claim for COPD between January 1, 2012, and November 30, 2013, and continuous enrollment for 1 year before and 2 years after the first COPD diagnosis date. Patients with a spirometry claim within 12 months were eligible for medical record abstraction to confirm COPD diagnosis (forced expiratory volume in 1 second [FEV1]/forced vital capacity ratio < 0.7) and GOLD 1-4 classification (based on postbronchodilator FEV1 percent predicted). HCRU, costs, treatment patterns, and rate of moderate/severe exacerbation were identified from diagnosis up to 24 months. Outcomes were analyzed by univariate analysis stratified by GOLD classification. Multivariable analysis was conducted to assess associations between GOLD classification and outcomes of interest.RESULTS53,484 patients newly diagnosed with COPD were identified who met initial inclusion criteria: 14,293 (27%) had a qualifying spirometry claim, and 1,505 had confirmed COPD (GOLD 1, 333 [22%]; GOLD 2, 823 [55%]; GOLD 3, 317 [21%]; GOLD 4, 32 [2%]). Patients with greater disease severity had higher rates of moderate/severe COPD exacerbations (GOLD 1 and 2, 40.4 and 48.9 per 100 person-years, respectively; GOLD 3 and 4, 83.6 and 89.1 per 100 person-years, respectively). All-cause and COPD-related inpatient admissions, COPD-related office visits, and COPD-related ER visits were more prevalent with more severe GOLD classification. Mean annual COPD-related medical costs increased with GOLD classification ($5,945 for GOLD 1 patients, $18,070 for GOLD 4). COPD maintenance medication was filled by 42%, 56%, 73%, and 75% of patients in GOLD 1-4 (57% overall), respectively; combination corticosteroid/long-acting beta2-agonist inhalers were the most commonly used medication, regardless of GOLD classification. Patients with more severe disease had greater adherence (range 44%-68% of days covered for GOLD 1-4) and persistence (range 107-209 days for GOLD 1-4).CONCLUSIONSTrends toward increases in exacerbations, HCRU, and costs were observed as airflow limitation worsened. Adherence and persistence with COPD maintenance therapy was suboptimal even with severe disease.DISCLOSURESThis study was supported by Boehringer Ingelheim Pharmaceuticals (Ridgefield, CT), which was given the opportunity to review the manuscript for medical and scientific accuracy, as well as intellectual property considerations. Willey and Singer are employees of HealthCore (parent company Anthem), which received funding from Boehringer Ingelheim to complete this study. Wallace and Shinde were employed by HealthCore at the time of this study. Wallace and Singer report stock ownership in Anthem. Napier is an employee of Anthem. Kaila, Bayer, and Shaikh are employees of Boehringer Ingelheim Pharmaceuticsls. Portions of this research were presented at the following conferences: (a) A. Wallace, S. Kaila, V. Zubek, A. Shaikh, M. Shinde, V. Willey, M. Napier, and J. Singer, Healthcare resource utilization, costs, and exacerbation rates in patients with COPD stratified by GOLD airflow limitation classification in a US commercially insured population, presented at AMCP Nexus 2017; October 16-19, 2017; Dallas, TX; and (b) A.E. Wallace, V. Zubek, S. Kaila, A. Shaikh, M. Shinde, V. Willey, M.B. Napier, and J.R. Singer, Real-world treatment patterns among newly diagnosed COPD patients according to GOLD airflow limitation severity classification in a U.S. commercially insured/Medicare Advantage population, presented at CHEST 2017 Annual Meeting; October 28-November 1, 2017; Toronto, Ontario, Canada.

BACKGROUND:The management of schizophrenia, a chronic, multifaceted mental health condition, is associated with considerable health care resource utilization (HCRU) and costs. Current evidence indicates that a high-risk and costly prodromal period, during which patients are likely symptomatic, precedes diagnosis. Better characterization and disease management during this stage could help to improve patient outcomes.OBJECTIVE:To describe and compare HCRU and costs for up to 5 years before diagnosis in a cohort with schizophrenia versus a demographically matched cohort without schizophrenia in a commercially insured U.S.POPULATION:METHODS:This retrospective study identified newly diagnosed schizophrenia patients using enrollee claims in the HealthCore Integrated Research Database between January 1, 2007, and April 30, 2016. The index date was defined as the date of the first medical claim with a schizophrenia diagnosis code. Schizophrenia patients were directly matched (1:4) by age, sex, and region to comparators without schizophrenia who were assigned the same index dates as their matched schizophrenia counterparts. Observation periods were 0-12, 13-24, 25-36, 37-48, and 49-60 months before the index date. Outcomes included HCRU and costs for inpatient admissions, emergency room visits, outpatient care (office visits and other outpatient services), and medications. Means, standard deviations, medians, and 95% confidence intervals were calculated for continuous variables; relative frequencies and percentages were calculated for categorical variables. Cohorts were compared with t-tests for continuous variables and chi-square tests for categorical variables. Differences across cohorts were estimated with individual generalized linear models for each observation period, controlling for gender, age, geographic region of residence, health plan type and subscriber status, behavioral pre-index comorbidities and chronic comorbidities during the period before diagnosis.RESULTS:6,732 schizophrenia patients were matched to 26,928 patients without schizophrenia. All-cause inpatient admissions were more prevalent among schizophrenia patients than their comparators for all time periods (49-60 months prediagnosis: 9% vs. 4%; 0-12 months prediagnosis: 33% vs. 4%). The schizophrenia cohort had higher adjusted all-cause per-patient per-month health care costs relative to comparators from the earliest period of 49-60 months prediagnosis ($557 [95% CI = 474-639] vs. $321 [95% CI = 288-355]) through 0-12 months prediagnosis ($1,058 [95% CI = 998-1,115] vs. $338 [95% CI = 320-355]). Behavioral health-related costs were different in each time period as were cost ratios (schizophrenia costs: comparator costs), which increased from 5.4 in the earliest period to 14.8 in the year before diagnosis.CONCLUSIONS:Schizophrenia patients had higher all-cause and behavioral health-related HCRU and costs before diagnosis than matched controls. Costs increased from 5 years to 1 year prediagnosis for schizophrenia patients driven primarily by inpatient hospital stays and prescription drug costs, but remained stable for comparators. Additional research is needed for the development of predictive models to aid in the identification of high-risk patients.DISCLOSURES:This study was sponsored by Boehringer Ingelheim Pharmaceuticals. Barron is an employee of HealthCore, which received funding from Boehringer Ingelheim to conduct this study. Wallace and York were employed by HealthCore at time of this study. Isenberg is an employee of Anthem. Franchino-Elder, Sidovar, and Sand are employees of Boehringer Ingelheim.

Schizophrenia is associated with considerable health care resource utilisation (HCRU) and costs, yet little is known about the patterns of care and HRCU in patients with schizophrenia prior to diagnosis. To address this knowledge gap, we examined the HCRU of patients with and without schizophrenia over a 5-year pre-diagnosis period. This US-based retrospective study used claims data from the HealthCore Integrated Research Database to identify newly diagnosed patients with schizophrenia (ICD-9: 295.x, ICD-10: F20.x) aged 15–54 years at diagnosis. Patients with schizophrenia were compared with a demographically matched (1:4) non-schizophrenia cohort during the 0–12 months, >1–2, >2–3, >3–4 and >4–5 years prior to schizophrenia diagnosis. During the pre-diagnosis periods, both all-cause and behavioural health-related HCRU were described. The schizophrenia and comparator cohorts included 6,732 and 26,928 patients, respectively. The most common types of schizophrenia were schizoaffective disorder (49%), paranoid (24%) and unspecified (19%). Patients were distributed across all major US regions (Northeast: 18%, Midwest: 27%, South: 29%, West: 27%). Average age at diagnosis was 32.8 years and most patients were male (57.4%). The percentage of patients with at least one all-cause inpatient hospitalisation in the 0–12 months prior to diagnosis was 32.7% for patients with schizophrenia versus 3.9% for comparators. Patients with schizophrenia had a greater mean number of all-cause physician office visits in all pr- diagnosis time periods versus comparators (schizophrenia: 4.5–5.5 visits, comparators: 3.1–3.2 visits). Behavioural health-related HCRU was also more substantial in patients with schizophrenia versus comparators across all time periods in terms of the mean number of visits to a psychiatrist (1.8–2.9 vs 0.1 visits, respectively) or a psychologist (1.0–1.2 vs 0.2 visits, respectively). The percentage of patients with claims for antipsychotic medication was also greater in the schizophrenia cohort vs comparators (21.8–56.6% vs 0.7–1.0% of patients, respectively). For up to 5 years prior to diagnosis, patients with schizophrenia have higher all-cause and behavioural health-related HCRU, in addition to higher use of anti-psychotic medications, compared with matched comparators. In the schizophrenia cohort, HCRU increased in frequency closer to diagnosis, compared with matched comparators, whose HCRU remained relatively stable. This study improves our understanding of the characteristics of clinically high-risk patients who go on to develop schizophrenia, who have more frequent encounters with health care providers than comparators. These results also suggest that early identification and treatment of patients prior to schizophrenia diagnosis could be optimised and is warranted. Funding: Boehringer Ingelheim (ANTHEM)

Schizophrenia is associated with considerable health care resource utilization (HCRU), yet little is known about pre-diagnosis patterns of HCRU in these patients. We examined HCRU of patients with and without schizophrenia over a 5-year pre-diagnosis period.

Objective: To determine the impact of surgical site infections (SSIs) on health care costs following common ambulatory surgical procedures throughout the cost distribution. Background: Data on costs of SSIs following ambulatory surgery are sparse, particularly variation beyond just mean costs. Methods: We performed a retrospective cohort study of persons undergoing cholecystectomy, breast-conserving surgery, anterior cruciate ligament reconstruction, and hernia repair from December 31, 2004 to December 31, 2010 using commercial insurer claims data. SSIs within 90 days post-procedure were identified; infections during a hospitalization or requiring surgery were considered serious. We used quantile regression, controlling for patient, operative, and postoperative factors to examine the impact of SSIs on 180-day health care costs throughout the cost distribution. Results: The incidence of serious and nonserious SSIs was 0.8% and 0.2%, respectively, after 21,062 anterior cruciate ligament reconstruction, 0.5% and 0.3% after 57,750 cholecystectomy, 0.6% and 0.5% after 60,681 hernia, and 0.8% and 0.8% after 42,489 breast-conserving surgery procedures. Serious SSIs were associated with significantly higher costs than nonserious SSIs for all 4 procedures throughout the cost distribution. The attributable cost of serious SSIs increased for both cholecystectomy and hernia repair as the quantile of total costs increased ($38,410 for cholecystectomy with serious SSI vs no SSI at the 70th percentile of costs, up to $89,371 at the 90th percentile). Conclusions: SSIs, particularly serious infections resulting in hospitalization or surgical treatment, were associated with significantly increased health care costs after 4 common surgical procedures. Quantile regression illustrated the differential effect of serious SSIs on health care costs at the upper end of the cost distribution.

SESSION TITLE: COPD: Lessons for the Real-World Management of Disease SESSION TYPE: Original Investigation Slide PRESENTED ON: Tuesday, October 31, 2017 at 02:45 PM - 04:15 PM PURPOSE: GOLD recommendations suggest the use of long acting β2 agonist (LABA) and/or long acting muscarinic antagonist (LAMA) for most COPD patients, reserving regimens containing inhaled corticosteroids (ICS) for a more severe subset of patients. Data on implementation of GOLD recommendations into clinical practice are limited. The purpose of this study was to characterize real-world treatment patterns among a spirometry-confirmed COPD population by GOLD airflow limitation severity classifications. METHODS: Over a study period of 1/1/2011 to 11/30/2015, a cohort of newly diagnosed COPD patients was identified using administrative claims from a large US payer. Patients were required to have ≥1 inpatient, ED or office visit claim for COPD from 1/1/2012 to 11/30/2013 and continuous health plan enrollment for 1 year prior to and 2 years after the first COPD diagnosis date. Patients with ≥1 claim for spirometry were eligible for medical record abstraction to confirm COPD diagnosis (FEV1/FVC ratio <0.7) and to determine GOLD 1-4 classification (based on post-bronchodilator FEV1 % predicted). Following COPD diagnosis, treatment patterns including COPD maintenance therapy (LAMA, LABA, ICS) observed and medication persistence (using a 60 day permissible gap) were evaluated for each GOLD classification. The rate of moderate/severe COPD exacerbation post-diagnosis was calculated. RESULTS: 85,247 newly diagnosed COPD patients were identified and 14,293 (17%) had a claim for spirometry use. Medical records containing complete spirometry results were obtained for 4,130 patients, with 1,505 (36%) having a spirometry-confirmed diagnosis. Among the 1,505 confirmed COPD patients, 333 (22%) were GOLD 1, 823 (55%) were GOLD 2, 317 (21%) were GOLD 3 and 32 (2%) were GOLD 4. Following COPD diagnosis, maintenance therapy was observed in 43% of GOLD 1, 56% of GOLD 2, 73% of GOLD 3 and 75% of GOLD 4 patients. GOLD 1 and 2 patients on maintenance therapy most frequently used ICS-LABA (48% & 45%, respectively), followed by LAMA only (29% for each) and ICS only (16% & 9%), while approximately 5% of GOLD 1 and 9% of GOLD 2 patients used triple therapy (ICS-LABA+LAMA). Similarly, a majority of GOLD 3 and 4 patients on maintenance therapy used ICS-LABA (37% & 42%), followed by LAMA only (28% & 25%) and triple therapy (20% & 17%). Overall, the observed maintenance therapy after diagnosis was an ICS-containing regimen for 67% of patients. Assessing persistence, mean (±SD) days on maintenance therapy was 143 days (±130), 188 days (±142), 215 days (±143) and 282 days (±132) for GOLD 1-4 and 191 days (±142) overall. Rates of severe/moderate COPD exacerbation per 100 person-years for GOLD 1-4 patients were 40.4, 48.9, 83.6 and 89.1, respectively. CONCLUSIONS: Large numbers of patients did not use maintenance therapy and the majority of those who did, across all GOLD classifications, used ICS-containing regimens (especially ICS-LABA), which is inconsistent with GOLD recommendations. Medication persistence was poor overall, especially in GOLD 1 patients. CLINICAL IMPLICATIONS: The observed inconsistencies with GOLD recommendations for COPD medication in this study highlight a gap between guidelines and clinical practice and the need for improved diagnosis and treatment of COPD patients. DISCLOSURE: Anna Wallace: Employee: I am an employee of HealthCore, a wholly owned subsidiary of Anthem, a health insurance company. I own Anthem stock. HealthCore received funding to conduct the work that led to this abstract. Valentina Zubek: Employee: Dr. Zubek reports she is an Employee of Boehringer Ingelheim. Shuchita Kaila: Employee: Dr. Kaila reports she is an Employee of Boehringer Ingelheim. Asif Shaikh: Employee: Dr. SHAIKH reports he is an Employee of Boehringer Ingelheim.reports other from Boehringer-Ingelheim, during the conduct of the study. Mayura Shinde: Employee: Dr. Shinde was an employee of HealthCore during the conduct of this work. HealthCore received funds from Boehrniger Ingelheim to conduct this work. Vincent Willey: Employee: Dr. Willey reports his employer, HealthCore, received funding from Boehringer Ingelheim to perform the study. Joseph Singer: Employee: Dr. Singer reports he is an employee and shareholder of HealthCore/Anthem. HealthCore received funds from Boehringer Ingelheim to conduct this work. The following authors have nothing to disclose: Mark Napier No Product/Research Disclosure Information

BACKGROUND:There are limited data on risk factors for surgical site infection (SSI) after open or laparoscopic cholecystectomy. METHODS:A retrospective cohort of commercially insured persons aged 18-64 years was assembled using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure or Current Procedural Terminology, 4th edition codes for cholecystectomy from December 31, 2004 to December 31, 2010. Complex procedures and patients (eg, cancer, end-stage renal disease) and procedures with pre-existing infection were excluded. Surgical site infections within 90 days after cholecystectomy were identified by ICD-9-CM diagnosis codes. A Cox proportional hazards model was used to identify independent risk factors for SSI. RESULTS:Surgical site infections were identified after 472 of 66566 (0.71%) cholecystectomies; incidence was higher after open (n = 51, 4.93%) versus laparoscopic procedures (n = 421, 0.64%; P < .001). Independent risk factors for SSI included male gender, preoperative chronic anemia, diabetes, drug abuse, malnutrition/weight loss, obesity, smoking-related diseases, previous Staphylococcus aureus infection, laparoscopic approach with acute cholecystitis/obstruction (hazards ratio [HR], 1.58; 95% confidence interval [CI], 1.27-1.96), open approach with (HR, 4.29; 95% CI, 2.45-7.52) or without acute cholecystitis/obstruction (HR, 4.04; 95% CI, 1.96-8.34), conversion to open approach with (HR, 4.71; 95% CI, 2.74-8.10) or without acute cholecystitis/obstruction (HR, 7.11; 95% CI, 3.87-13.08), bile duct exploration, postoperative chronic anemia, and postoperative pneumonia or urinary tract infection. CONCLUSIONS:Acute cholecystitis or obstruction was associated with significantly increased risk of SSI with laparoscopic but not open cholecystectomy. The risk of SSI was similar for planned open and converted procedures. These findings suggest that stratification by operative factors is important when comparing SSI rates between facilities.

Purpose To examine associations between board certification of psychiatrists and neurologists and quality-of-care measures, using multilevel models controlling for physician and patient characteristics, and to assess feasibility of linking physician information with patient records to construct quality measures from electronic claims data. Method The authors identified quality measures and matched claims data from 2006 to 2012 with 942 board-certified (BC) psychiatrists, 868 non-board-certified (nBC) psychiatrists, 963 BC neurologists, and 328 nBC neurologists. Using the matched data, they identified psychiatrists who treated at least one patient with a schizophrenia diagnosis, and neurologists attending patients discharged with a principal diagnosis of ischemic stroke, and analyzed claims from these patients. For patients with schizophrenia who were prescribed an atypical antipsychotic, quality measures were claims for glucose and lipid tests, duration of any antipsychotic treatment, and concurrent prescription of multiple antipsychotics. For patients with ischemic stroke, quality measures were dysphagia evaluation; speech/language evaluation; and prescription of clopidogrel, low-molecular-weight heparin, intravenous heparin, and warfarin (for patients with co-occurring atrial fibrillation). Results Overall, multilevel models (patients nested within physicians) showed no statistically significant differences in quality measures between BC and nBC psychiatrists and neurologists. Conclusions The authors demonstrated the feasibility of linking physician information with patient records to construct quality measures from electronic claims data, but there may be only minimal differences in the quality of care between BC and nBC psychiatrists and neurologists, or there may be a difference that could not be measured with the quality measures used.

Geography influences access to many specialized healthcare services. A Centers for Disease Control and Prevention report demonstrated higher mortality among rural Americans for the 5 leading cause of death.1Rural Americans at higher risk of death from five leading causes. January 12, 2017. Available at: https://www.cdc.gov/media/releases/2017/p0112-rural-death-risk.html.Google Scholar This did not include liver disease. The mechanisms for these disparities are unknown, but may include physical barriers (ie, distance traveled for specialized health care).1Rural Americans at higher risk of death from five leading causes. January 12, 2017. Available at: https://www.cdc.gov/media/releases/2017/p0112-rural-death-risk.html.Google Scholar The management of patients with chronic liver failure (CLF) encompasses a spectrum of care: (1) managing complications of portal hypertension, (2) screening and treating hepatocellular carcinoma (HCC), and (3) caring for acutely ill inpatients. Liver disease management is superior when led by an expert in liver disease at a specialized center, almost always a liver transplant (LT) center in a large urban community.2Kanwal F. Volk M. Singal A. et al.Improving quality of health care for patients with cirrhosis.Gastroenterology. 2014; 147: 1204-1207Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar, 3Kanwal F. Kramer J.R. Buchanan P. et al.The quality of care provided to patients with cirrhosis and ascites in the Department of Veterans Affairs.Gastroenterology. 2012; 143: 70-77Abstract Full Text Full Text PDF PubMed Scopus (103) Google Scholar, 4Ko C.W. Kelley K. Meyer K.E. Physician specialty and the outcomes and cost of admissions for end-stage liver disease.Am J Gastroenterol. 2001; 96: 3411-3418Crossref PubMed Google Scholar, 5Bini E.J. Weinshel E.H. Generoso R. et al.Impact of gastroenterology consultation on the outcomes of patients admitted to the hospital with decompensated cirrhosis.Hepatology. 2001; 34: 1089-1095Crossref PubMed Scopus (58) Google Scholar, 6Buchanan P.M. Kramer J.R. El-Serag H.B. et al.The quality of care provided to patients with varices in the department of Veterans Affairs.Am J Gastroenterol. 2014; 109: 934-940Crossref PubMed Scopus (32) Google Scholar For patients with CLF eligible for a LT, rural/urban status and distance to a LT center are associated with less waitlisting and transplantation.7Goldberg D.S. French B. Forde K.A. et al.Association of distance from a transplant center with access to waitlist placement, receipt of liver transplantation, and survival among US veterans.JAMA. 2014; 311: 1234-1243Crossref PubMed Scopus (99) Google Scholar, 8Goldberg D.S. French B. Sahota G. et al.Use of population-based data to demonstrate how waitlist-based metrics overestimate geographic disparities in access to liver transplant care.Am J Ttransplant. 2016; 16: 2903-2911Crossref PubMed Scopus (43) Google Scholar, 9Axelrod D.A. Guidinger M.K. Finlayson S. et al.Rates of solid-organ wait-listing, transplantation, and survival among residents of rural and urban areas.JAMA. 2008; 299: 202-207Crossref PubMed Scopus (170) Google Scholar, 10Cicalese L. Shirafkan A. Jennings K. et al.Increased risk of death for patients on the waitlist for liver transplant residing at greater distance from specialized liver transplant centers in the United States.Transplantation. 2016; 100: 2146-2152Crossref PubMed Scopus (19) Google Scholar However, no population-based studies have evaluated the association between geographic isolation and survival in patients with CLF, important because fewer than 1 in 6 are waitlisted, and fewer than 1 in 12 is transplanted.8Goldberg D.S. French B. Sahota G. et al.Use of population-based data to demonstrate how waitlist-based metrics overestimate geographic disparities in access to liver transplant care.Am J Ttransplant. 2016; 16: 2903-2911Crossref PubMed Scopus (43) Google Scholar, 11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar This was a retrospective cohort study using the HealthCore Integrated Research Database from January 1, 2006, to June 30, 2014, of patients with CLF aged 18–75 years, without exclusionary conditions for LT, as previously described.11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar CLF was defined as cirrhosis plus HCC and/or a complication of portal hypertension, and absent these, laboratory data signifying considerable synthetic dysfunction (bilirubin ≥3 mg/dL or Model for End-Stage Liver Disease score ≥15).11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar, 12Goldberg D. Lewis J. Halpern S. et al.Validation of three coding algorithms to identify patients with end-stage liver disease in an administrative database.Pharmacoepidemiol Drug Saf. 2012; 21: 765-769Crossref PubMed Scopus (101) Google Scholar, 13Goldberg D.S. Lewis J.D. Halpern S.D. et al.Validation of a coding algorithm to identify patients with hepatocellular carcinoma in an administrative database.Pharmacoepidemiol Drug Saf. 2013; 22: 103-107Crossref PubMed Scopus (40) Google Scholar We evaluated overall survival using Cox regression, with follow-up beginning on the date of CLF diagnosis. Transplant-free survival was assessed using competing-risk models (outcome: death; competing risk: transplant). The primary exposure was distance from the centroid of a patient’s zip code to the closest LT center. Based on the data’s distribution and the relationship between distance and access to LT care from prior studies, distance was modeled as a categorical variable (primary analyses), and continuous for secondary analyses.7Goldberg D.S. French B. Forde K.A. et al.Association of distance from a transplant center with access to waitlist placement, receipt of liver transplantation, and survival among US veterans.JAMA. 2014; 311: 1234-1243Crossref PubMed Scopus (99) Google Scholar, 11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar Study covariates included time-varying stage of cirrhosis and HCC, age, sex, Charlson comorbidity index, etiology of liver disease, and rural/urban status.11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar Transplant access-related variables in a local geographic area included number of LT centers, waitlisting rates, organ supply/demand, number of gastroenterologists, and zip-code level poverty.8Goldberg D.S. French B. Sahota G. et al.Use of population-based data to demonstrate how waitlist-based metrics overestimate geographic disparities in access to liver transplant care.Am J Ttransplant. 2016; 16: 2903-2911Crossref PubMed Scopus (43) Google Scholar, 11Goldberg D. French B. Newcomb C. et al.Patients with hepatocellular carcinoma have highest rates of wait-listing for liver transplantation among patients with end-stage liver disease.Clin Gastroenterol Hepatol. 2016; 14: 1638-1646Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar Among 16,824 patients with CLF, 879 (5.2%) lived >150 miles from the closest LT center. The characteristics of patients based on distance categories were balanced (Table 1). In multivariable models that included etiology of liver disease, patients living >150 miles from the closest LT center had significantly higher mortality (hazard ratio, 1.20; 95% confidence interval [CI], 1.08–1.33; P < .001) and transplant-free mortality (subhazard ratio, 1.18; 95% CI, 1.06–1.32; P = .003). Increasing distance was associated with higher overall (hazard ratio, 1.02; 95% CI, 1.003–1.04; P = .02) and transplant-free (subhazard ratio, 1.03; 95% CI, 1.01–1.04; P = .001) mortality with distance modeled as a continuous variable per unit increase in 50 miles. The association between distance and survival was evident for decompensated cirrhosis or HCC. Although patients living >150 miles from an LT center had fewer outpatient gastroenterologist visits (Table 1), this covariate did not affect the final models. Inclusion of rural/urban status did not attenuate the association between distance and survival; rural status was not associated with increased mortality after adjusting for distance. Zip-code level poverty was not associated with survival (P = .6).Table 1Clinical and Demographic Characteristics of HealthCore Patients With CLF in Study Sample (N = 16,824)VariableDistance to closest liver transplant centerP value<20.0 miles (n = 6277)20.1–40.0 miles (n = 3435)40.1–70.0 miles (n = 2881)70.1–150.0 miles (n = 3352)>150 miles (n = 879)Male gender, n (%)3962 (63.1)2129 (62.0)1831 (63.6)2056 (61.3)537 (61.1).24Age at diagnosis CLF, median (IQR)59.5 (52.4–66.5)59.1 (52.1–66.5)59.8 (52.5–67.2)59.0 (52.0–66.5)59.5 (52.5–67.5).055Etiology of liver disease< .001 HCV only1102 (17.6)532 (15.5)376 (13.1)476 (14.2)126 (14.3) HCV + alcohol963 (15.3)528 (15.4)433 (15.0)480 (14.3)129 (14.7) Alcohol only2483 (39.6)1435 (41.8)1176 (40.8)1312 (39.1)392 (44.6) Likely NASH629 (10.0)372 (10.8)260 (12.5)410 (12.2)94 (10.7) Other1100 (17.5)568 (16.5)536 (18.6)674 (20.2)138 (15.7)Charlson comorbidity index,aModified Charlson comorbidity index calculated without assigning points for liver disease. n (%).20 02641 (42.1)1439 (41.9)1159 (40.2)1416 (42.2)361 (41.1) 1640 (10.2)365 (10.6)353 (12.3)354 (10.6)103 (11.7) 2464 (7.4)266 (7.7)211 (7.3)262 (7.8)59 (6.7) 3775 (12.40439 (12.8)343 (11.9)402 (12.0)117 (13.3) 4514 (8.2)301 (8.8)253 (8.8)292 (8.7)88 (10.0) 5370 (5.9)209 (6.1)175 (6.1)218 (6.5)56 (6.4) 6273 (4.4)135 (3.9)140 (4.9)137 (4.1)30 (3.4) ≥7600 (9.6)281 (8.2)247 (8.6)271 (8.1)65 (7.4)HCC during follow-up, n (%)825 (13.1)394 (11.5)255 (8.9)302 (9.0)77 (8.8)< .001Ascites during follow-up, n (%)4546 (72.4)2499 (72.8)2152 (74.7)2436 (72.7)618 (70.3).08Variceal bleed during follow-up, n (%)897 (14.3)481 (14.0)451 (15.7)498 (14.9)151 (17.2).07Reside in a rural county23 (0.4)255 (7.4)847 (29.4)1266 (37.8)343 (39.0)< .001Follow-up time by outcome, d, median (IQR) Alive679 (264–1421)663 (246–1334)620 (236–1318)607 (223–1340)551 (217–1258).005 Died214 (52–652)246 (62–635)194 (50–570)200 (47–612)236 (49–652).15Outpatient gastroenterology visits/year of follow-up, median (IQR) Alive1.37 (0.29–3.00)1.37 (0–3.22)1.34 (0–3.34)1.23 (0–2.98)0.80 (0–2.61)< .001 Died1.58 (0–3.87)1.41 (0–4.27)1.55 (0–3.97)1.13 (0–3.52)0.61 (0–3.52)< .001HCV, hepatitis C virus; IQR, interquartile range; NASH, nonalcoholic steatohepatitis.a Modified Charlson comorbidity index calculated without assigning points for liver disease. Open table in a new tab HCV, hepatitis C virus; IQR, interquartile range; NASH, nonalcoholic steatohepatitis. For patients with CLF, transplant remains the only option for long-term survival. Yet for the 11 out of 12 who are never transplanted,8Goldberg D.S. French B. Sahota G. et al.Use of population-based data to demonstrate how waitlist-based metrics overestimate geographic disparities in access to liver transplant care.Am J Ttransplant. 2016; 16: 2903-2911Crossref PubMed Scopus (43) Google Scholar access to specialized care may still prolong life. Management of complications of cirrhosis is superior with improved survival when led by a gastroenterologist/hepatologist as part of a transplant center’s multidisciplinary team.5Bini E.J. Weinshel E.H. Generoso R. et al.Impact of gastroenterology consultation on the outcomes of patients admitted to the hospital with decompensated cirrhosis.Hepatology. 2001; 34: 1089-1095Crossref PubMed Scopus (58) Google Scholar, 9Axelrod D.A. Guidinger M.K. Finlayson S. et al.Rates of solid-organ wait-listing, transplantation, and survival among residents of rural and urban areas.JAMA. 2008; 299: 202-207Crossref PubMed Scopus (170) Google Scholar, 13Goldberg D.S. Lewis J.D. Halpern S.D. et al.Validation of a coding algorithm to identify patients with hepatocellular carcinoma in an administrative database.Pharmacoepidemiol Drug Saf. 2013; 22: 103-107Crossref PubMed Scopus (40) Google Scholar This would seem to explain the disparities in survival for geographically isolated patients with CLF (future work should include patient-level socioeconomic variables), even accounting for access to transplantation, and has important policy implications. According to Centers for Disease Control and Prevention data, age-adjusted death rates from liver disease from 2010 to 2014 are lowest in New York, where the entire population lives within 150 miles of ≥1 LT center. By contrast, New Mexico and Wyoming have the highest age-adjusted death rates, and >95% of those states’ populations live >150 miles from an LT center. The management of most patients with CLF is not centered on transplantation, but rather the spectrum of care for decompensated cirrhosis and HCC. Thus maintaining access to specialized liver care is important for patients with CLF. Although these associations do not prove cause and effect, they highlight the need for considering the broader impact of transplant-related policies that could decrease transplant volumes and threaten closures of smaller LT centers that serve geographically isolated populations in the Southeast and Midwest.

Importance Few data are available concerning surgical site infection (SSI) and noninfectious wound complications (NIWCs) after delayed (DR) and secondary reconstruction (SR) compared with immediate reconstruction (IR) procedures in the breast. Objective To compare the incidence of SSI and NIWCs after implant and autologous IR, DR, and SR breast procedures after mastectomy. Design, Setting, and Participants This retrospective cohort study included women aged 18 to 64 years undergoing mastectomy from January 1, 2004, through December 31, 2011. Data were abstracted from a commercial insurer claims database in 12 states and analyzed from January 1, 2015, through February 7, 2017. Exposures Reconstruction within 7 days of mastectomy was considered immediate. Reconstruction more than 7 days after mastectomy was considered delayed if the mastectomy did not include IR or secondary if the mastectomy included IR. Main Outcomes and Measures International Classification of Diseases, Ninth Revision, Clinical Modificationdiagnosis codes for SSI and NIWCs. Results Mastectomy was performed in 17 293 women (mean [SD] age, 50.4 [8.5] years); 61.4% of women had IR or DR. Among patients undergoing implant reconstruction, the incidence of SSI was 8.9% (685 of 7655 women) for IR, 5.7% (21 of 369) for DR, and 3.2% (167 of 5150) for SR. Similar results were found for NIWCs. In contrast, the incidence of SSI was similar after autologous IR (9.8% [177 of 1799]), DR (13.9% [19 of 137]), and SR (11.6% [11 of 95]) procedures. Compared with women without an SSI after implant IR, women with an SSI after implant IR were significantly more likely to have another SSI (47 of 412 [11.4%] vs 131 of 4791 [2.7%]) and an NIWC (24 of 412 [5.8%] vs 120 of 4791 [2.5%]) after SR. The incidence of SSI (24 of 379 [6.3%] vs 152 of 5286 [2.9%]) and NIWC (22 of 379 [5.8%] vs 129 of 5286 [2.4%]) after implant SR was higher in women who had received adjuvant radiotherapy. Wound complications after IR were associated with significantly more breast surgical procedures (mean of 1.92 procedures [range, 0-9] after implant IR and 1.11 [range, 0-6] after autologous IR) compared with women who did not have a complication (mean of 1.37 procedures [range, 0-8] after implant IR and 0.87 [range, 0-6] after autologous IR). Conclusions and Relevance The incidence of SSI and NIWCs was slightly higher for implant IR compared with delayed or secondary implant reconstruction. Women who had an SSI or NIWC after implant IR had a higher risk for subsequent complications after SR and more breast operations. The risk for complications should be carefully balanced with the psychosocial and technical benefits of IR. Select high-risk patients may benefit from consideration of delayed rather than immediate implant reconstruction to decrease breast complications after mastectomy.

Schizophrenia, often diagnosed in adolescence, is associated with substantial health care resource utilization (HCRU) and costs. Little is known about patterns of care before diagnosis. We describe clinical and demographic characteristics and HCRU of adolescent patients with and without schizophrenia over a five-year pre-diagnosis period.

OBJECTIVE Survey results suggest that prolonged administration of prophylactic antibiotics is common after mastectomy with reconstruction. We determined utilization, predictors, and outcomes of postdischarge prophylactic antibiotics after mastectomy with or without immediate breast reconstruction. DESIGN Retrospective cohort. PATIENTS Commercially insured women aged 18–64 years coded for mastectomy from January 2004 to December 2011 were included in the study. Women with a preexisting wound complication or septicemia were excluded. METHODS Predictors of prophylactic antibiotics within 5 days after discharge were identified in women with 1 year of prior insurance enrollment; relative risks (RR) were calculated using generalized estimating equations. RESULTS Overall, 12,501 mastectomy procedures were identified; immediate reconstruction was performed in 7,912 of these procedures (63.3%). Postdischarge prophylactic antibiotics were used in 4,439 procedures (56.1%) with immediate reconstruction and 1,053 procedures (22.9%) without immediate reconstruction ( P <.001). The antibiotics most commonly prescribed were cephalosporins (75.1%) and fluoroquinolones (11.1%). Independent predictors of postdischarge antibiotics were implant reconstruction (RR, 2.41; 95% confidence interval [CI], 2.23–2.60), autologous reconstruction (RR, 2.17; 95% CI, 1.93–2.45), autologous reconstruction plus implant (RR, 2.11; 95% CI, 1.92–2.31), hypertension (RR, 1.05; 95% CI, 1.00–1.10), tobacco use (RR, 1.07; 95% CI, 1.01–1.14), surgery at an academic hospital (RR, 1.14; 95% CI, 1.07–1.21), and receipt of home health care (RR, 1.11; 95% CI, 1.04–1.18). Postdischarge prophylactic antibiotics were not associated with SSI after mastectomy with or without immediate reconstruction (both P >.05). CONCLUSIONS Prophylactic postdischarge antibiotics are commonly prescribed after mastectomy; immediate reconstruction is the strongest predictor. Stewardship efforts in this population to limit continuation of prophylactic antibiotics after discharge are needed to limit antimicrobial resistance. Infect Control Hosp Epidemiol 2017;38:1048–1054

6539 Background: The proliferation of novel treatment options has placed an increased emphasis on our need to better understand the variability in treatment choice and treatment patterns in oncology. The objective of this study was to characterize the variability in cancer treatment patterns for breast, colorectal and lung cancer. Methods: Pre-authorization requests for chemotherapy and/or targeted cancer treatments were utilized to identify breast, colorectal and lung cancer patients between 6/1/2014 and 4/30/2015 within the integrated clinical oncology and administrative claims data of the HealthCore Integrated Research Environment (HIRE) - Oncology. The earliest pre-authorization date was assigned as the index date. Demographics were evaluated by cancer type. Clinical characteristics and treatment patterns were assessed by cancer type and line of treatment. Results: 3,116 breast, 1,241 colorectal and 1,200 lung cancer patients were identified with mean ages of 52.6± 9.9, 55.5±9.3 and 60.3±8.1 years, respectively. Stage IV was most prevalent among colorectal (67%) and lung (74%) cancer patients and stage II among breast cancer patients (36%). Across breast (82%), colorectal (72%) and lung (74%) cancers, 1st line therapy represented the majority of pre-authorization requests. Among breast cancer patients, the most common 1st, 2nd and +3rd line therapies were docetaxel/cyclophosphamide (17%), fulvestrant (20%) and eribulin (18%), respectively. Among colorectal cancer patients, the most prevalent 1st, 2nd, and +3rd line therapies were fluorouracil/leucovorin/oxaliplatin (35%), fluorouracil/leucovorin/irinotecan/bevacizumab (29%), and irinotecan/cetuximab (20%), respectively. In lung cancer, the most common 1st, 2nd and +3rdline therapies were pemetrexed/carboplatin (19%), docetaxel (20%) and gemcitabine (20%). Conclusions: There was extensive variation in treatment patterns among breast, colorectal and lung cancer patients, particularly within 1st line therapy which represented the majority within each cancer type. This study provides initial insight on the relative generalizability of treatments requested by physicians participating within Anthem’s CCQP.

BACKGROUND Few studies have validated ICD-9-CM diagnosis codes for surgical site infection (SSI), and none have validated coding for noninfectious wound complications after mastectomy. OBJECTIVES To determine the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes in health insurer claims data to identify SSI and noninfectious wound complications, including hematoma, seroma, fat and tissue necrosis, and dehiscence, after mastectomy. METHODS We reviewed medical records for 275 randomly selected women who were coded in the claims data for mastectomy with or without immediate breast reconstruction and had an ICD-9-CM diagnosis code for a wound complication within 180 days after surgery. We calculated the positive predictive value (PPV) to evaluate the accuracy of diagnosis codes in identifying specific wound complications and the PPV to determine the accuracy of coding for the breast surgical procedure. RESULTS The PPV for SSI was 57.5%, or 68.9% if cellulitis-alone was considered an SSI, while the PPV for cellulitis was 82.2%. The PPVs of individual noninfectious wound complications ranged from 47.8% for fat necrosis to 94.9% for seroma and 96.6% for hematoma. The PPVs for mastectomy, implant, and autologous flap reconstruction were uniformly high (97.5%–99.2%). CONCLUSIONS Our results suggest that claims data can be used to compare rates of infectious and noninfectious wound complications after mastectomy across facilities, even though PPVs vary by specific type of postoperative complication. The accuracy of coding was highest for cellulitis, hematoma, and seroma, and a composite group of noninfectious complications (fat necrosis, tissue necrosis, or dehiscence). Infect Control Hosp Epidemiol 2017;38:334–339

BACKGROUND: Noninfectious wound complications (NIWCs) after mastectomy are not routinely tracked and data are generally limited to single-center studies. Our objective was to determine the rates of NIWCs among women undergoing mastectomy and assess the impact of immediate reconstruction (IR).STUDY DESIGN: We established a retrospective cohort using commercial claims data of women aged 18 to 64 years with procedure codes for mastectomy from January 2004 through December 2011. Noninfectious wound complications within 180 days after operation were identified by ICD-9-CM diagnosis codes and rates were compared among mastectomy with and without autologous flap and/or implant IR.RESULTS: There were 18,696 procedures (10,836 [58%] with IR) among 18,085 women identified. The overall NIWC rate was 9.2% (1,714 of 18,696); 56% required surgical treatment. The NIWC rates were 5.8% (455 of 7,860) after mastectomy only, 10.3% (843 of 8,217) after mastectomy plus implant, 17.4% (337 of 1,942) after mastectomy plus flap, and 11.7% (79 of 677) after mastectomy plus flap and implant (p < 0.001). Rates of individual NIWCs varied by specific complication and procedure type, ranging from 0.5% for fat necrosis after mastectomy only, to 7.2% for dehiscence after mastectomy plus flap. The percentage of NIWCs resulting in surgical wound care varied from 50% (210 of 416) for mastectomy plus flap, to 60% (507 of 843) for mastectomy plus implant. Early implant removal within 60 days occurred after 6.2% of mastectomy plus implant; 66% of the early implant removals were due to NIWCs and/or surgical site infection.CONCLUSIONS: The rate of NIWC was approximately 2-fold higher after mastectomy with IR than after mastectomy only. Noninfectious wound complications were associated with additional surgical treatment, particularly in women with implant reconstruction, and with early implant loss. (C) 2016 by the American College of Surgeons. Published by Elsevier Inc. All rights reserved.