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Defining a role for hospitals and health care systems in addressing cancer disparities KIM F. RHOADS, MD, MS, MPH, FACS CALIFORNIA CANCER REGISTRARS ASSOCIATION 43RD ANNUAL EDUCATION CONFERENCE NOVEMBER 3, 2016 Disclosures • NO COMMERCIAL OR FINANCIAL CONFLICTS Motivation for the work: Jeannette Barnes (1935-1993) 58 years old • Presented with a locally advanced breast mass (stage IIIB) • Breast cancer care in a safety net hospital No planned surgical intervention No breast fellowship trained surgeon No radiation therapy ?No radiation therapist ?No radiation oncologist ?No palliative care service Given antibiotics and chemotherapy Died during the hospitalization Trends in Cancer Disparities California Breast Cancer Trends 1980-2004 California Colorectal Cancer Trends 1980-2004 NCI website: http://statecancerprofiles.cancer.gov last access 7/17/12 Traditional explanations for disparities in cancer survival Patient Characteristics Chronic disease/comorbid states Late stage at diagnosis Insurance Status Lack of access to care contributes to poor outcomes Genetic/epigenetic explanations Minorities have more aggressive tumors Expanding the explanations for cancer survival disparities • • Disparities in Treatment • Lower quality treatment may drive worse outcomes Surgical Volume & Outcomes • Use of low volume hospitals results in worse outcomes • Racial Disparities in Late Survival after Rectal Cancer • African Americans more likely to be treated for rectal cancer by low volume hospitals and fail to receive adjuvant therapy. • • Morris AM, Wei Y, Birkmeyer NJ, et al. J Am Coll Surg. 2006 Race and Surgical Mortality in the United States • Black patients undergoing cancer operations in low percent black hospitals have better cancer survival. • Lucas FL, Stukel TA, Morris AM, et al. Annals of Surg 2006 Does Hospital Context and Quality Drive Disparities? • • What is known: • Racial and ethnic disparities in cancer exist • Patient characteristics are associated with poor cancer outcomes What is not well described: • What is the role of hospital characteristics on these disparities? • How are hospital characteristics associated with cancer outcomes and cancer disparities? The IOM on hospitals serving high percentages of patients with Medicaid “Because of Medicaid’s low reimbursement rates for doctors and hospitals, poor, disproportionately minority beneficiaries are subject to largely separate, often segregated systems of hospitals and neighborhood clinics. These systems often adopt their own norms of medical practice, shaped by tight resource constraints.” Unequal Treatment, Confronting Racial and Ethnic Disparities in HealthCare , IOM 2002 Quality of Colon Cancer Outcomes in Hospitals with a High Percentage of Medicaid Patients RHOADS KF, ACKERSON LK, JHA AK, DUDLEY RA. JACS 2008 Methods • Data Sources • • California Cancer Registry linked to Office of Statewide Health Planning and Development Discharge data • ICD-9CM coding of diagnosis, procedures and co-morbidities • Individual level/patient characteristics + what happens in hospitals Added hospital financial characteristics • • Defined High Medicaid hospitals based on Medicaid Utilization Rate Analytic approach • Hierarchical modeling High Medicaid Hospitals serve higher proportions of minorities and uninsured patients Patient Characteristics (n=18,000) High Medicaid Hospital (%) Non-High Medicaid Hospital (%) 38.6 12.5 24.9 24.0 76.5 6.2 9.9 7.4 Race/Ethnicity White (non-Hispanic) Black (non-Hispanic) Hispanic Asian Pacific Islander Insurance Status Private Insurance Medicaid No Insurance Medicare Unknown 25.5 16.6 10.7 37.9 9.3 49.2 2.5 1.4 45.1 1.8 Rhoads KF, Dudley RA. J Am Coll Surg 2008 High Medicaid hospitals are associated with higher colon cancer mortality 4 3.5 3 *p <0.001 2.5 High Medicaid Hospital 2 Non-High Medicaid Hospital 1.5 *p = 0.04 1 0.5 0 30days 1 year % Mortality at 30 days and 1 year for patients with colon cancer (California 1998-99) Rhoads KF, Dudley RA. J Am Coll Surg 2008 High Medicaid hospitals are associated with higher colon cancer mortality 4.5 4 3.5 3 p = 0.18 2.5 Private Insurance 2 1.5 Medicaid p = 0.07 1 0.5 0 30 day 1 year % Mortality at 30 days and 1 year for patients using High Medicaid Hospitals (Colon Cancer, California 1998-99) Rhoads KF, Dudley RA. J Am Coll Surg 2008 Understanding disparities in cancer survival: place matters Where you go for treatment…can influence survival How location of care can impact outcomes of care: Donabedian’s healthcare quality triad Structural Quality •Surgical Volume •Surgical Specialists •Med/Rad Oncologists •Rad Onc Facilities • PET/CT scanners Donabedian. Millbank Quarterly 2005 Process Quality Outcome Quality •Tumor Board Meetings •Preoperative Evaluation •Receipt of (Neo)/Adjuvant •Number of Lymph Nodes sampled Do hospitals serving a high percentage of Medicaid patients perform poorly on evidence-based care for colon cancer ? RHOADS KF, NGO JV, WELTON ML, DUDLEY RA. JHCPU, 2013 Defining evidence based care for colon cancer (NCCN guidelines) 1. Resections for colon cancer follow oncologic principles. 2. At least 12 Lymph node should be examined after resection to determine disease stage. Stage I-II – 0 positive lymph nodes Stage III – Any positive lymph nodes 3. Disease stage determines therapy Stage I-II – No chemotherapy Stage III – Chemotherapy Stage III Available at nccn.org High Medicaid hospitals lag behind others for uptake and rate of 12 LN examination Trends in Receipt of adequate LN examination Proportion of Patients 0.8000 0.7000 0.6000 0.5000 * * 0.4000 0.3000 HMH40 * Teach HVH 0.2000 0.1000 0.0000 Consensus panel recommendation Colon Cancer, California, 1996-2006; from Rhoads et al. JHCPU 2013 Patients treated in HMH settings received chemotherapy for stage III disease at lower rates Trends in Receipt of Appropriate Chemo (Stage III | Colon Cancer) 0.8500 Proportion of Patients 0.8000 0.7500 HMH40 0.7000 Teach 0.6500 HVH 0.6000 0.5500 0.5000 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 (Colon Cancer, California, 1996-2006; from Rhoads et al. JHCPU 2013 Understanding disparities in cancer survival: place matters Where you go for treatment determines the quality of care you get… and can influence survival How location of care can impact outcomes of care: Donabedian’s healthcare quality triad Structural Quality •Surgical Volume •Surgical Specialists •Med/Rad Oncologists •Rad Onc Facilities • PET/CT scanners Donabedian. Millbank Quarterly 2005 Process Quality Outcome Quality •Tumor Board Meetings •Preoperative Evaluation •Receipt of (Neo)/Adjuvant •Number of Lymph Nodes sampled Disparities in cancer mortality vary by tumor type Tumor type 5-year survival rate Absolute difference Black White Prostate 97.5% 99.9% 2.4% Pancreas 4.6% 4.7% 0.1% Liver 6.5% 9.1% 2.6% Lung 12.2% 15.2% 3% Esophagus 10.5% 16.8% 6.3% Colorectal 55.5% 65.6% 10.1% Breast 76.6% 89.8% 13.2% Bladder 64.8% 83.2% 18.4% Head & Neck 40.5% 62.1% 21.6% Uterine 61.8% 86.4% 24.6% Morris and Rhoads JACS 2010. Source: http://seer.cancer.gov/canques/survival.html last accessed 7/08 How do integrated systems address disparities in colon cancer? RHOADS KF, PATEL MI, MA Y, AND SCHMIDT L. JCO, MARCH 2015 Methods • Data Source • • Predictor Variables • • Hospital characteristics—fully integrated (Berkeley Forum definition) versus all other health care settings Outcomes • • • • CCR + OSHPD + California hospital financial data (2001-06) Delivery of evidence based care (NCCN guidelines) 5- year survival Racial/ethnic disparities Analytic Approach • Propensity Score Matching • with clinical, demographic AND social characteristics Rates of NCCN guideline compliance were higher* in Integrated versus other settings * There was no different between settings for 12 LN examination; rates ranged from 43.3% to 49.1% Rhoads KF, Patel MI, Ma Y, and Schmidt L. JCO, March 2015 Propensity score matched survival shows integrated settings associated with survival advantage Rhoads KF, Patel MI, JCO, March 2015 IHS are associated with smaller gaps in racial/ethnic survival California, Colon Cancer, 2001-2006; from: Rhoads KF, Patel MI, JCO, March 2015 Mortality disparities in integrated versus other settings; quality of care makes the difference Baseline Model Race/ethnicity White Black Hispanic API Integrated System HR (95%CI) 1.0 (referent) 0.96 (0.72-1.04) 0.92 (0.77-1.10) 0.83 (0.67-1.04) P NS NS NS All Other Systems HR (95%CI) 1.0 (referent) 1.15 (1.04-1.27) 0.90 (0.83-0.90) 0.79 (0.68-0.81) P <0.001 0.009 <0.001 -----------------------------------Baseline + Evidence Based Care----------------------------------White Black Hispanic Asian 1.0 (referent) 0.79 (0.65-0.96) 0.86 (0.72-1.02) 0.79 (0.64-1.00) 0.02 0.09 0.05 1.0 (referent) 1.09 (0.98-1.21) 0.87 (0.90-0.95) 0.73 (0.67-0.81) NS 0.001 0.001 Models adjusted for age; gender; Charlson comorbidity score; stage of disease. Abbreviations: HR-hazard ratio; 95% CI-95% confidence interval; API-Asian/Pacific Islander Interaction terms crossing race * location of care no qualitative difference (not shown) Conclusion: improving quality of care & cancer care equity can address cancer disparities • California’s largest integrated system has higher adherence to evidence based care guidelines than other systems in the state • Propensity score matched comparisons showed lower mortality after care within an integrated system • There were smaller disparity gaps in treatment in the integrated system and no detectable racial differences in survival • Most importantly, adjusting survival models for delivery of evidence based care eliminated survival disparities in all other settings • Similar findings in Acute Myeloid Leukemia • Patel MI & Rhoads KF, CEBP March 2015 Why is the role of hospitals and health care systems so important in addressing cancer disparities? How location of care can impact outcomes of care: Donabedian’s healthcare quality triad Structural Quality •Surgical Volume •Surgical Specialists •Med/Rad Oncologists •Rad Onc Facilities • PET/CT scanners Donabedian. Millbank Quarterly 2005 Process Quality Outcome Quality •Tumor Board Meetings •Preoperative Evaluation •Receipt of (Neo)/Adjuvant •Number of Lymph Nodes sampled Minorities under utilize facilities that deliver high quality cancer care HUANG LC, MA Y, NGO JV, RHOADS KF. CANCER 2014 HUANG LC, MA Y, NGO JV, RHOADS KF. DIS COL AND RECTUM 2015 Higher proportions of minorities in California live close to an NCI center 30% % of patients treated for CRC 25% 20% 15% Nearby 10% 10% 12% 14% 26% White Black Hispanic API 5% 0% Percentage of each racial group living nearby (within 5 miles of) an NCI hospital (Colorectal Cancer , California 1996-2006. (N=79,231)) Huang LC, Rhoads KF. Cancer 2014 Insurance status does not explain minority under-utilization of NCI settings Baseline Model Odds ratio P-value Insurance Model Odds ratio P-value Race White (ref) 1.0 1.0 Black 0.83 0.008 0.81 <0.001 Hispanic 0.72 <0.001 0.70 <0.001 API 1.40 <0.001 1.39 <0.001 Insurance Private (ref) 1.0 Medicaid 1.85 <0.001 Medicare 2.10 <0.001 No insurance 0.86 0.311 Missing data 1.93 <0.001 Huang LC, Rhoads KF. Cancer 2014 Neighborhood demographics are more important predictor of NCI use than travel distance Lower odds of utilization Higher odds of utilization Huang LC, Rhoads KF. Cancer 2014 Where do we go from here? Implications for increasing equity and quality in cancer care A conceptual framework for understanding disparities in cancer survival California Cancer Registry Data: Current State CCR data is collected and curated under California state law whose language focuses on reporting of cancer incidence (epidemiology); and detection of geographic high incident areas There is no language (currently) in the law to support the use of data for quality reporting or quality improvement Leveraging the CCR to measure & improve quality of care and outcomes Section 103875 of the Health and Safety Code recommended amendments: c) The director shall analyze data collected under the program to assess , measure and publicly report on the quality of cancer care in the state. In assessing and measuring the quality of cancer care, the director shall define and identify oncology providers. In publicly reporting the quality of cancer care in the state, the director shall identify oncology providers but not any cancer patients…. Section 103885 of the Health and Safety Code recommended amendments: a) “The director shall also identify and include in the statewide system cancer care quality measures for use in public reporting. Fighting cancer with data: Enabling the California cancer registry to Measure and Improve care. California Health Care Foundation, November 2014 (Available online at: http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/PDF%20F/PDF%20FightingCancerDataRegistry.pdf) Registry data can play a critical role in helping hospitals & healthcare systems address disparities • Patient Level: Increasing patient access to cancer care quality information • • • Use data to identify high and low performing health systems and hospitals Hospital level: Monitoring hospital performance • Use the data to identify high and low performing hospital (by name or characteristics) • Designing and deploying large scale interventions to improve quality (at the hospital level) Health Care System level: Inform CMS reimbursement policy for Oncology Care Model sites • NCCN guidelines define high quality care for OCM • Use registry data to document compliance with guidelines (over time) • Use long term data to rationally risk adjust reimbursement policies (Pay for Performance programs), to avoid unintended consequences of financial penalties in low resource settings Where are we trying to go: Equality versus Equity Everyone gets the same resources Everyone gets the resources they need IN CLOSING… Defining a role for hospitals and health care systems in addressing cancer disparities [email protected] THANK YOU FOR WHAT YOU DO!