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Joseph Lipscomb, PhD jlipscosph.emory Professor of Health Policy and Management Rollins School of Public Health, Emory

2. Who Is a

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Joseph Lipscomb, PhD jlipscosph.emory Professor of Health Policy and Management Rollins School of Public Health, Emory

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    1. 1 Joseph Lipscomb, PhD ( jlipsco@sph.emory.edu ) Professor of Health Policy and Management Rollins School of Public Health, Emory University Georgia Cancer Survivorship Conference Peachtree City, Sept 28, 2007

    2. 2 Who Is a “Cancer Survivor”? (Critical for Defining the Scope and Breadth of Data Required for Analysis) “An individual is considered a cancer survivor from the time of diagnosis, through the balance of his/her life. Family members, friends, and caregivers are impacted….and included in this definition.” (Office of Cancer Survivorship, National Cancer Institute; http://dccps.nci.nih.gov/ocs/) “The term cancer survivors refers to those people who have been diagnosed with cancer and the people in their lives who are affected by the diagnosis, including family members, friends, and caregivers.” (from A National Action Plan for Cancer Survivorship, issued jointly by the Centers for Disease Control and Prevention and the Lance Armstrong Foundation; http://www.cdc.gov/cancer)

    3. 3 What Are the “Outcomes” of Interest Quantity of life (survival) Quality of life - Symptom bother - Functional status (e.g., carrying out normal activities of daily living) - Health-related quality of life (HRQOL) – an integrated assessment of the impact of health-related events on the individual’s overall level of self-assessed well-being, often taking into account physical, social, and psychological functioning Economic status of the cancer survivor and his/her family

    4. 4 Improving the Outcomes of Cancer Care: National Cancer Institute Perspective

    5. 5 Major Survivorship Research and Policy Issues Requiring Ongoing Empirical Study (as reflected, for example, in the NCI research agenda) Chronic and late effects of cancer and its treatment Interventions to reduce or halt these effects Health lifestyle and behaviors (to reduce the risk of cancer recurrence and improve overall quality of life and survival) Benefit finding and posttraumatic growth following the diagnosis and treatment of cancer Family impacts Health disparities

    6. 6 What Kinds of Data Are Required to Study Such Survivorship Issues in Georgia? Specific, targeted questions can be addressed by specific data sources (e.g., expected survival can be estimated from high-quality cancer registries; HRQOL can be estimated “at a slice in time” by well-executed survey of individuals diagnosed with cancer) But to acquire the capability to address a full range of cancer survivorship issues, Georgia needs a comprehensive cancer data system that capitalizes on a range of current information sources and develops additional ones.

    7. 7 Components of a Comprehensive State-Based Cancer Data System for Survivorship Analysis Strong cancer registry system -- and the Georgia Comprehensive Cancer Registry (GCCR) is strong indeed Access to medical records/charts of cancer survivors, during primary treatment and beyond – the “more electronic” the data, the better Access to insurance claims data (Medicare, Medicaid, private indemnity plans, managed care) Information on symptoms, HRQOL, economic consequences of cancer from the survivor’s own perspective Link it all together to develop, for each individual diagnosed with cancer, a rich longitudinal picture of what it is like to “live with, through, and beyond” cancer

    8. 8 Components of a Comprehensive State-Based Cancer Data System for Survivorship Analysis Such a population-based cancer data system has been recommended by the Institute of Medicine (Enhancing Data Systems to Improve the Quality of Cancer Care, 2000; and From Cancer Patient to Cancer Survivor: Lost in Transition, 2006). Likewise, the forthcoming Georgia Comprehensive Cancer Control Plan has, as one of its Data & Metrics Goals, to “expand and enhance data collection from existing and new sources.” But can we get there from here? Do we have examples of how cancer registry data can be augmented to study the quality and outcomes of care over time? (Yes we do!)

    9. 9 Example #1, the CDC-supported study being conducted by Emory University investigators on... Determinants of Patient Dropout from Cancer Treatment and Follow-up

    10. 10 Background & Motivation Numerous patterns-of-care studies report that cancer patients frequently do not receive guideline-concordant care (Institute of Medicine, 1999). Yet, little is known about % patients not completing prescribed therapy, the factors that predict patient “dropout”, and even whether currently available data systems are adequate to support such analyses.

    11. 11 Primary Study Goals (1) Examine frequency of failure to complete prescribed treatment for breast, colorectal, lung, and prostate cancers within the 1st year of diagnosis among residents of Southwest Georgia – a 33-county region of the state.

    12. 12 Primary Study Goals (2) Investigate tumor-specific and patient-related, provider-related, and health system-related factors associated with premature treatment discontinuation in this largely rural population. (3) Determine the types of data sources and information systems required to achieve goals (1) and (2) in a population-based cancer treatment environment. Additional Study Goals (4) Identify interventions to reduce dropout (5) Propose strategies to disseminate findings (6) Recommend whether longer-term follow-on study is warranted

    13. 13 Discussion and Conclusions I In this rural population, 85% of breast cancer patients and 67% of colorectal cancer patients overall completed adjuvant chemotherapy Those cases who stopped prior to finishing treatment were much more likely to do so for toxicity and other clinical reasons than for refusal/lack of support Married CRC patients were significantly more likely to complete treatment than patients who were single, divorced or separated Among non-married breast cancer patients, older women and whites were more likely to discontinue chemotherapy for reasons other than completion

    14. 14 Discussion and Conclusions II In all analyses undertaken, white/non-white differences in chemotherapy receipt and treatment completion were either non-significant or else suggested higher completion rates for non-whites Future analyses will focus on the relationship between treatment plan and compliance, using qualitative research to investigate provider decision making

    15. 15 Example #2 funded by CDC’s National Program of Cancer Registries (NPCR) Breast and Prostate Cancer Data Quality and Patterns of Care Study

    16. 16 Background and Motivation In two influential reports, National Cancer Policy Board of the IOM (1999, 2000) emphasized both inadequacy of our present understanding of cancer care quality and important role of NPCR in monitoring and improving quality. The two most common cancers in Georgia are breast and prostate (>5,000 cases each in 2004). Georgia Comprehensive Cancer Registry is one of the nation’s best – and can become still better for patterns-of-care and quality-of-care assessment.

    17. 17 Primary Study Goals Describe patterns of care for female breast and prostate cancer among Georgia residents, based on a stratified random sample of 2,000 cases of BC and 2,000 cases of PC diagnosed in 2004 Examine the degree to which cancer care is “guideline concordant” – a frequently used approach to quality-of-care assessment Investigate factors that may influence patterns of care and guideline concordance: -- tumor-related -- patient-related (including race/ethnic, socio- economic, and geographic variables) -- provider-related -- health system-related Assess and improve the quality of the data on cancer care and outcomes

    18. 18 Examples of Specific Hypotheses (cutting across both breast and prostate cancer) Patients at higher socio-economic status more likely to receive guideline-concordant care [as defined by the National Comprehensive Cancer Network (NCCN) guidelines] Younger patients more likely to receive guideline concordant pre-treatment evaluation and care Patient’s comorbidity status will significantly influence choice of care, with strength of the effect varying by age and stage of disease Non-Hispanic whites more likely to receive guideline-concordant care than Hispanics and non-white race Patients seeking pre-treatment evaluation at high-volume facilities more likely to receive guideline concordant care

    19. 19 Organization of the Study A 7-state consortium formed by CDC in Oct 2005 following competitive selection process (“RFA” grant mechanism): GA, CA, LA, KY, MN, NC, and WI. Critically important element of study in Georgia: Collaborative relationship between GCCR, GA cancer registrars, and Emory investigators.

    20. 20 Example #3: Prostate Cancer Outcomes Study (data from multiple states, NCI-supported) OBJECTIVES Describe diagnosis and treatment patterns for prostate cancer among large (N = 3,500) diverse group of men treated in community settings and followed periodically Assess health-related quality of life among prostate cancer survivors at 5 time points over 5-year period Focus on complications associated with prostate cancer: urinary, bowel, sexual Overcome limitations of previous studies, including -- Patients from single institutions -- Quality of life evaluated by doctors, not patients -- Cross-sectional, not longitudinal

    21. 21 Some PCOS Findings The prevalence of urinary, bowel, and sexual impairments is substantially higher than some estimates from referral centers and leading academic institutions. As part of treatment planning, clinicians should consider men’s baseline function and age, since these also predict subsequent outcomes and recovery after treatment. PCOS data are increasingly being used as a treatment decision resource by patients and physicians in the community setting. Need for new therapies with lower rates of complications.

    22. 22 Example #4 CanCORS Cancer Care Outcomes Research and Surveillance Consortium: A 6-year, $40M, project supported by NCI and VA to study the impact of targeted interventions on patient-centered outcomes investigate dissemination of state-of-the-art therapies in the community examine gaps between best, evidence-based clinical practice and actual care in community analyze disparities in quality cancer care

    23. 23 CanCORS Study Design Large observational cohort study of newly identified lung and colorectal cancer patients -- For lung: 5 research teams with N = 4,700 -- For colorectal: 6 research teams with N = 5,300 Socio-economically,geographically, and race/ethnically diverse samples Public-private provider mix: large HMOs, fee-for-service, VA medical centers

    24. 24 CanCORS Study Design Rapid case ascertainment : < 3 months after diagnosis Follow-up patients 12 months after diagnosis For each patient, creates a longitudinal profile of cancer care by utilization multiple data sources Investigate structure - process - outcome links at the patient, provider, and organizational level

    25. 25 CanCORS Specific Aims 1) To determine how the characteristics & beliefs of cancer patients and providers and the characteristics of health-care organizations influence treatments and outcomes, spanning continuum of cancer care from diagnosis to recovery or death 2) To evaluate effects of select processes of care on patients’ survival, health-related quality of life, and satisfaction with care

    26. 26 Some CanCORS High-Priority Questions How and why do processes and outcomes of care vary by patient age, race, ethnicity, SES? Why do high-volume hospitals tend to have lower surgical mortality rates? How do patients and physicians go about making treatment decisions for metastatic cancer? Are symptoms (especially pain and depression) treated effectively?

    27. 27 But these and other specific studies do not produce, nor benefit from, a strong, enduring, population-based cancer care data system. How do we build such a system in Georgia to understand and improve survivor outcomes?

    28. 28 What are the Options? (1) Rely primarily on registry data - Such data crucial foundation for many survivorship studies - Sufficient to study impact of cancer on quantity of life (mortality & survival) - But does not address quality-of-life and economic consequences of cancer and its treatment

    29. 29 What are the Options? (2) Link registry data with insurance claims data -- the linkage of the NCI Surveillance, Epidemiology, and End Results (SEER) data with Medicare claims has resulted in a data base (SEER-Medicare) supporting numerous studies of patterns of care, quality of care, and economic outcomes for cancer survivors across the U.S. -- And, starting with the observation period 1999-2002, we now have “Georgia-Medicare” -- Next, we need “Georgia-Medicaid” and also the linkage of private insurance claims data to Georgia cancer registry data -- Aim: create a (near) population-representative data base linking (most) every Georgia cancer registry record with the individual’s insurance claims files [At least one significant problem: the uninsured!]

    30. 30 What are the Options? (3) Extend the follow-up period of existing patterns-of-care/quality-of-care (POC/QOC) studies For example, continue to follow the survivors now enrolled in the Breast and Prostate Cancer POC/QOC study and the SW Georgia cancer care drop-out study (4) Launch new POC/QOC studies over time, in a strategic fashion to (a) encompass a broad array of tumor types and (b) include patient-reported outcomes such as symptom bother, HRQOL, and economic consequences

    31. 31 What are the Options? (5) To augment POC/QOC studies that do not collect patient-reported outcomes, expand and intensify population-based surveys that capture symptom bother, HRQOL, economic outcomes, and other data important for interpreting the experiences of the cancer survivor, caregiver, and others touched by cancer

    32. 32 What are the Options? (6) Continue to follow patients enrolled in cancer clinical trials well beyond the “end” of the study, and expand the data collected to include patient-reported outcomes -- As the Georgia Center for Oncology Research and Education (GA CORE) works to increase the number of clinical trials across the state, this option should receive heightened attention

    33. 33 What are the Options? (7) Over the long term, seek to establish a new standard of health care data collection at the site of care, to include information on the patient’s socioeconomic status (e.g., education level), stage of cancer disease (if relevant), comorbid conditions, and patient-reported outcomes including symptom bother, HRQOL, and economic consequences of disease and treatment. -- Aim: to make such data part of the patient record that can then be abstracted in POC/QOC studies, thus reducing need for separate surveys

    34. 34 Challenges Affordability – covering the cost of an expanded Georgia cancer data system Sources: state govt, federal govt, funded research, foundations, private industry Cooperation, Coordination, Collaboration – multiple public and private entities with a strong interest in the cancer survivor and also unique perspectives, agendas, and fiscal & administrative constraints Patient Privacy and Confidentiality – the importance (and the considerable cost) of obtaining informed consent and ensuring privacy of medical records

    35. 35 But we should keep our eyes on the Prize…. A comprehensive Georgia cancer data system that enables us to understand and improve healthcare outcomes for cancer survivors across the state

    36. 36 The Opportunity and The Commitment

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