What drives variation in spending for breast cancer patients within geographic regions?

OBJECTIVE: To estimate and describe factors driving variation in spending for breast cancer patients within geographic region. DATA SOURCE: Surveillance, Epidemiology, and End Results (SEER)-Medicare database from 2009-2013. STUDY DESIGN: The proportion of variation in monthly medical spending within geographic region attributed to patient and physician factors was estimated using multilevel regression models with individual patient and physician random effects. Using sequential models, we estimated the contribution of differences in patient and disease characteristics or use of cancer treatment modalities to patient-level and physician-level variance in spending. Services associated with high spending physicians were estimated using linear regression. DATA EXTRACTION METHOD: A total of 20 818 women with a breast cancer diagnosis in 2010-2011. PRINCIPAL FINDINGS: We observed substantial between-patient and between-provider variation in spending following diagnosis and at the end-of-life. Immediately following diagnosis, 48% of between-patient and 31% of between-physician variation were driven by differences in delivery of cancer treatment modalities to similar patients. At the end-of-life, patients of high spending physicians had twice as many inpatient days, double the chemotherapy spending, and slightly more hospice days. CONCLUSIONS: Similar patients receive very different treatments, which yield significant differences in spending. Efforts to reduce unwanted variation may need to target treatment choices within patient-doctor discussions.

A comparison of skin cancer screening and treatment costs at a Massachusetts cancer center, 2008 versus 2013.

BACKGROUND: Temporal analyses of skin cancer costs are needed to examine how expenditure differences between diagnoses are changing. OBJECTIVE: To tabulate the costs of skin cancer-related care (SCRC), including both screening and treatment, at an academic cancer center at 2 time points. METHODS: Cost data (insurance and patient payments) at an academic cancer center from 2008 and 2013 were queried for International Classification of Diseases, Ninth Revision, codes pertaining to skin cancer. Screening costs were separated from treatment costs through associated Current Procedural Terminology codes. RESULTS: The total annual cost of SCRC increased by 64%, the number of patients receiving SCRC increased by 45%, and the mean cost per patient treated increased by 13%. Screening accounted for 17% and 16% of total annual costs in 2008 and 2013, respectively. The mean cost per patient with melanoma increased by 84%, which was the largest increase among skin cancer diagnoses. In 2013, the few patients with melanoma who were treated with ipilimumab (n = 48 [4% of patients with melanoma]) accounted for 42% of melanoma treatment costs and 20% of SCRC costs. LIMITATIONS: Prescription costs were unavailable. CONCLUSIONS: Melanoma costs have increased as a result of the introduction of ipilimumab. Ongoing studies are needed to monitor the cost-effectiveness of SCRC at a national level.

Cost and Survival Analysis Before and After Implementation of Dana-Farber Clinical Pathways for Patients With Stage IV Non-Small-Cell Lung Cancer.

PURPOSE: Increasing costs and medical complexity are significant challenges in modern oncology. We explored the use of clinical pathways to support clinical decision making and manage resources prospectively across our network. MATERIALS AND METHODS: We created customized lung cancer pathways and partnered with a commercial vendor to provide a Web-based platform for real-time decision support and post-treatment data aggregation. Dana-Farber Cancer Institute (DFCI) Pathways for non-small cell lung cancer (NSCLC) were introduced in January 2014. We identified all DFCI patients who were diagnosed and treated for stage IV NSCLC in 2012 (before pathways) and 2014 (after pathways). Costs of care were determined for 1 year from the time of diagnosis. RESULTS: Pre- and postpathway cohorts included 160 and 210 patients with stage IV NSCLC, respectively. The prepathway group had more women but was otherwise similarly matched for demographic and tumor characteristics. The total 12-month cost of care (adjusted for age, sex, race, distance to DFCI, clinical trial enrollment, and EGFR and ALK status) demonstrated a $15,013 savings after the implementation of pathways ($67,050 before pathways v $52,037 after pathways). Antineoplastics were the largest source of cost savings. Clinical outcomes were not compromised, with similar median overall survival times (10.7 months before v 11.2 months after pathways; P = .08). CONCLUSION: After introduction of a clinical pathway in metastatic NSCLC, cost of care decreased significantly, with no compromise in survival. In an era where comparative outcomes analysis and value assessment are increasingly important, the implementation of clinical pathways may provide a means to coalesce and disseminate institutional expertise and track and learn from care decisions.

Health care institutional charges associated with ambulatory bloodstream infections in pediatric oncology and stem cell transplant patients.

BACKGROUND: The impact of ambulatory bloodstream infections (Amb-BSIs) in pediatric oncology and stem cell transplant (PO/SCT) patients is poorly understood, although a large portion of their treatment increasingly occurs in this setting. This study aimed to understand the economic impact and length of stay (LOS) associated with these infections. PROCEDURE: Charges and LOS were retrospectively collected and analyzed for Amb-BSI events leading to a hospital admission between 2012 and 2013 in a tertiary, university-affiliated hospital. Events were grouped as BSI-MIXED when hospitalizations with care unrelated to the infection-extended LOS by more than 24 hr or as BSI-PURE for all others. Billing codes were used to group charges and main drivers were analyzed. RESULTS: Seventy-four BSI events were identified in 61 patients. Sixty-nine percent met definition for central line-associated BSI (CLABSI). Median total charge and LOS for an Amb-BSI were $40,852 (interquartile range [IQR] $44,091) and 7 days (IQR 6), respectively. Median charges for BSI-PURE group (N = 62) were $36,611 (IQR $34,785) and $89,935 (IQR $153,263) in the BSI-MIXED (N = 12) group. Median LOS was 6 (IQR 5) days in the BSI-PURE group and 15 (IQR 24) in the BSI-MIXED. Room, pharmacy, and procedure charges accounted for more than 70% of total charges in all groups. CONCLUSIONS: Amb-BSIs in PO/SCT patients result in significant healthcare charges and unplanned extended hospital admissions. This analysis suggests that efforts aiming at reducing rates of infections could result in substantial system savings, validating the need for increased efforts to prevent Amb-BSIs.

Characteristics Associated with In-Hospital Death among Commercially Insured Decedents with Cancer.

BACKGROUND: A majority of patients with poor-prognosis cancer express a preference for in-home death; however, in-hospital deaths are common. OBJECTIVE: We sought to identify characteristics associated with in-hospital death. DESIGN: Case series. SETTING/SUBJECTS: Commercially insured patients with cancer who died between July 2010 and December 2013 and who had at least two outpatient visits at a tertiary cancer center during the last six months of life. MEASUREMENTS: Patient characteristics, healthcare utilization, and in-hospital death (primary outcome) were ascertained from institutional records and healthcare claims. Bivariate and multivariable analyses were used to evaluate the association of in-hospital death with patient characteristics and end-of-life outcome measures. RESULTS: We identified 904 decedents, with a median age of 59 years at death. In-hospital death was observed in 254 patients (28%), including 110 (12%) who died in an intensive care unit. Hematologic malignancy was associated with a 2.57 times increased risk of in-hospital death (95% confidence interval [CI] 1.91-3.45, p < 0.001), and nonenrollment in hospice was associated with a 14.5 times increased risk of in-hospital death (95% CI 9.81-21.4, p < 0.001). Time from cancer diagnosis to death was also associated with in-hospital death (p = 0.003), with the greatest risk among patients dying within six months of cancer diagnosis. All significant associations persisted in multivariable analyses that were adjusted for baseline characteristics. CONCLUSIONS: In-hospital deaths are common among commercially insured cancer patients. Patients with hematologic malignancy and patients who die without receiving hospice services have a substantially higher incidence of in-hospital death.

Novel Data Sharing Between a Comprehensive Cancer Center and a Private Payer to Better Understand Care at the End of Life.

CONTEXT: Understanding end-of-life (EOL) care patterns is a prerequisite to improving the experience for cancer patients. EOL measures endorsed by the National Quality Forum (NQF) have been examined in older patients using Medicare claims. OBJECTIVES: To evaluate EOL care for patients treated at a comprehensive cancer center, using private payer claims data. METHODS: A retrospective cohort study was conducted of Dana-Farber Cancer Institute (DFCI) patients who died between July 2010 and December 2012, and were insured by Blue Cross Blue Shield of Massachusetts. Primary data sources included Blue Cross Blue Shield of Massachusetts claims information and DFCI administrative data. We assessed NQF-endorsed measures of EOL care related to emergency department visits, hospitalizations, and intensive care unit admissions in the last 30 days, chemotherapy in the last 14 days, hospice stay, and death in an acute care setting. Patterns of care by cancer type and service location were determined. RESULTS: Among 674 patients (mean age 58 years), event rates for NQF-endorsed EOL measures were similar to those reported using Medicare claims. Decedents with hematologic malignancies received significantly more intensive care and were less likely to have enrolled in hospice, compared to decedents with solid tumors. Thirty to 45% of EOL events occurred outside of DFCI and its affiliated hospitals. CONCLUSION: Data sharing between a private payer and a large cancer center proved feasible and informative. High rates of hospital service use outside of our sites of care were unexpected. The findings suggest opportunities to better manage care at the end of life.

Understanding Oral Chemotherapy Prescribing Patterns at the End of Life at a Comprehensive Cancer Center: Analysis of a Massachusetts Payer Claims Database.

PURPOSE: Receipt of chemotherapy in the last 14 days of life is a measure of potential overuse of care. Specific measures defining appropriate end-of-life use of oral agents have not yet been described, and little is known about prescribing patterns. METHODS: We conducted an exploratory analysis of 371 patients at Dana-Farber Cancer Institute who were covered by the Blue Cross Blue Shield of Massachusetts pharmacy benefit and died during 2012 to 2013. We analyzed processed claims as a surrogate for chemotherapy administration. We compared oral with parenteral chemotherapy claims in the last 6 months of life. RESULTS: In the last 6 months of life, 294 patients (79%) had chemotherapy claims, including 81 (22%) prescribed an oral agent; 20 patients had claims for oral chemotherapy in the last 30 days of life. For eight patients (40%), this was the initial start of that oral agent. In the last 14 days of life, only 23 patients had chemotherapy claims, including six patients prescribed an oral agent. CONCLUSION: The collection of oral chemotherapy use data through insurance claims was feasible. Processed claims for chemotherapy, including oral, sharply declined during the last 30 days of life, consistent with a shift to palliative management. These results highlight the need for a more comprehensive analysis of oral chemotherapy prescribing patterns and development of specific measures to define the appropriate use of oral chemotherapy at the end of life.

Efficacy of the combination of amlodipine and valsartan in patients with hypertension uncontrolled with previous monotherapy: the Exforge in Failure after Single Therapy (EX-FAST) study.

In this randomized, double-blind, multicenter study, patients whose blood pressure (BP) was uncontrolled by monotherapy were switched directly to amlodipine/valsartan 5/160 mg (n=443) or 10/160 mg (n=451). After 16 weeks, BP control (levels <140/90 mm Hg or <130/80 mm Hg for diabetics) was achieved in 72.7% (95% confidence interval [CI], 68.6-76.9) of patients receiving amlodipine/valsartan 5/160 mg and in 74.8% (95% CI, 70.8-78.9) receiving amlodipine/valsartan 10/160 mg. Incremental reductions from baseline in mean sitting systolic and diastolic BP were significantly greater with the higher dose (20.0+/-0.7 vs 17.5+/-0.7 mm Hg; P=.0003 and 11.6+/-0.4 vs 10.4+/-0.4 mm Hg; P=.0046). Incremental BP reductions were also achieved with both regimens irrespective of previous monotherapy, hypertension severity, diabetic status, body mass index, and age. Peripheral edema was the most frequent adverse event. These results provide support for the BP-lowering benefits of complementary antihypertensive therapy with amlodipine and valsartan in patients with hypertension uncontrolled by previous monotherapy.