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Understanding Quality of Cancer Care in the VA Health System Nancy L. Keating, MD, MPH Department of Health Care Policy, H...
Background <ul><li>VA is largest integrated delivery system in the country </li></ul><ul><ul><li>5.5 million veterans in 2...
Background <ul><li>Some prior evaluations of quality of care in the VA </li></ul><ul><ul><li>Preventive care and chronic c...
VA Oncology Care <ul><li>Cancer 2 nd  to cardiovascular disease as cause of morbidity and mortality for veterans  </li></u...
Some Concerns About Quality of Cancer Care Remain <ul><li>At VA Hospital, a Rogue Cancer Unit  </li></ul><ul><li>--New Yor...
Objectives <ul><li>Compare the cancer care delivered to older veterans in the VA with that of older individuals in the pri...
Data Sources <ul><li>VA </li></ul><ul><ul><li>Cancer registry data </li></ul></ul><ul><ul><li>VA administrative data </li>...
VA Facilities Annu Rev Public Health 2009; 30:313-339
SEER Areas UT NM Hawaii IA Seattle/ Puget Sound Connecticut Since 1992  or earlier Metro Detroit Los Angeles San Jose/ Mon...
Cohorts <ul><li>VA </li></ul><ul><ul><li>Comparison analyses </li></ul></ul><ul><ul><ul><li>Men aged >65 years with cancer...
Measures of Cancer Care Quality <ul><li>Based on guidelines recommending various treatments for </li></ul><ul><ul><li>Colo...
Survival <ul><li>Colon cancer </li></ul><ul><li>Rectal cancer </li></ul><ul><li>Non-small cell lung cancer </li></ul><ul><...
Preference Sensitive Care <ul><li>Primary treatment for local/regional prostate cancer </li></ul><ul><li>Aggressive care a...
Control Variables <ul><li>Demographics: age, race, marital status </li></ul><ul><li>Comorbidity: Charlson score, prior can...
Patient Characteristics Colon Cancer Cohort  <ul><li>  VA SEER-Medicare   P </li></ul><ul><li>Mean age  74.9 76.4 <.001 </...
Analytic Strategy—Comparative Analyses <ul><li>Propensity score methods to account for  observed  factors </li></ul><ul><u...
Sensitivity to  Unobserved  Confounders <ul><li>Assume existence of unobserved confounder  </li></ul><ul><li>Re-estimate c...
Analytic Within-VA Analyses <ul><li>Hierarchical models including patient factors, hospital characteristics, and VISN </li...
Results—Quality of Care
Stage at Diagnosis - Colon Cancer Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson co...
Surgery for Colorectal Cancer P=.01 Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson ...
Adjuvant Therapy for Colorectal Cancer Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charls...
Non Small Cell (NSC) Lung Cancer Primary Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagn...
Non Small Cell & Small Cell Lung Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagno...
Prostate Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidit...
Lymphoma Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score...
Multiple Myeloma Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidi...
Role of Unobserved Confounders—  Incomplete Adjustment for Comorbidity Respiratory Disease
Role of Unobserved Factors:  Sensitivity Analyses <ul><li>Poor performance status </li></ul><ul><ul><li>Assume prevalence ...
Role of Unobserved Factors:  Sensitivity Analyses—Adjusted Difference in Quality   *Comparing VA with FFS-Medicare Observe...
Results—Survival
Survival for Colon Cancer Adjusted median survival VA=49 months; SEER=43 months p<0.001
Survival for Rectal Cancer Adjusted median survival VA=36 months; SEER=37 months p=0.55
Survival for NSC Lung Cancer Adjusted median survival VA=8 months; SEER=6 months p<0.001
Survival for Small Cell Lung Cancer Adjusted median survival VA=5 months; SEER=5 months p=0.64
Survival for Lymphoma Adjusted median survival VA=14 months; SEER=16 months p=0.75
Survival for Myeloma Adjusted median survival VA=19 months; SEER=17 months p=0.15
Role of Unobserved Factors:  Sensitivity Analyses—Adjusted Hazard of Death   *Comparing VA with FFS-Medicare Observed Cova...
Results— Preference Sensitive Care
Primary Prostate Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson co...
Aggressive End of Life Care Adjusted for age, race/ethnicity, marital status, cancer site, quarter-year of diagnosis, Char...
Within-VA Analyses Variation in Primary Prostate Cancer Treatment
Rates of Radiation Therapy by VAMC *Adjusted for patient, tumor, & hospital characteristics & VISN.
Rates of Radical Prostatectomy by VAMC *Adjusted for patient, tumor, & hospital characteristics & VISN.
Results—Reasons for Underuse of Effective Therapies
Rates of Treatments %
Reasons for Underuse of Therapies
Limitations <ul><li>Comparisons focused on men aged 65+; FFS Medicare only </li></ul><ul><li>VHA claims not based on payme...
Summary-Quality <ul><li>Processes of care generally comparable in VA and private sector for older men with cancer </li></u...
Summary-Survival <ul><li>Survival for colon and NSC lung cancer better in VA </li></ul><ul><ul><li>Primarily explained by ...
Summary- Preference Sensitive Care <ul><li>Higher rates of expectant management for primary treatment of prostate cancer i...
Summary-Within-VA Variation <ul><li>Large variations by facility seen in utilization and process measures </li></ul><ul><l...
Summary-Reasons for Underuse <ul><li>Recommendation against therapy was main contributor to underuse of effective therapie...
<ul><li>Relative to FFS setting, a health care delivery system with primary care focus, coordination of care and integrati...
<ul><li>VHA provides care to challenging populations; relative quality and outcomes likely even better than observed </li>...
<ul><li>Generally low rates of many measures in both settings </li></ul><ul><ul><li>Results from VHA MRA suggests that low...
Research Team <ul><li>Abt Associates  </li></ul><ul><li>Sam Bozeman  </li></ul><ul><li>Senior Project Director </li></ul><...
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LDI Research Seminar- Understanding Quality of Cancer Care in the VA Health System 10_14_11

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LDI Research Seminar- Understanding Quality of Cancer Care in the VA Health System 10_14_11

  1. 1. Understanding Quality of Cancer Care in the VA Health System Nancy L. Keating, MD, MPH Department of Health Care Policy, Harvard Medical School October 14, 2011 Funding: VA Office of Policy and Planning Contract 101-35-04
  2. 2. Background <ul><li>VA is largest integrated delivery system in the country </li></ul><ul><ul><li>5.5 million veterans in 2007 </li></ul></ul><ul><li>Major redesign of VA in late 1990s </li></ul><ul><ul><li>Implementation of integrated service networks </li></ul></ul><ul><ul><li>Eligibility reform </li></ul></ul><ul><ul><li>Global budget resource allocation </li></ul></ul><ul><ul><li>Improved access to primary care </li></ul></ul><ul><ul><li>Performance management program </li></ul></ul>
  3. 3. Background <ul><li>Some prior evaluations of quality of care in the VA </li></ul><ul><ul><li>Preventive care and chronic care better than national sample </li></ul></ul><ul><ul><li>Acute care no difference </li></ul></ul><ul><ul><ul><li>Some older evidence that cardiovascular care worse </li></ul></ul></ul><ul><li>Improvements in quality in VA outpaced that in private sector during late 1990s </li></ul><ul><li>Cited as model during health reform debate </li></ul>
  4. 4. VA Oncology Care <ul><li>Cancer 2 nd to cardiovascular disease as cause of morbidity and mortality for veterans </li></ul><ul><li>VHA established hospital-based cancer registries that report to VA Central Cancer Registry </li></ul><ul><ul><li>~100 cancer programs, most ACoS-approved </li></ul></ul>
  5. 5. Some Concerns About Quality of Cancer Care Remain <ul><li>At VA Hospital, a Rogue Cancer Unit </li></ul><ul><li>--New York Times, June 20, 2009 </li></ul>
  6. 6. Objectives <ul><li>Compare the cancer care delivered to older veterans in the VA with that of older individuals in the private sector </li></ul><ul><ul><li>Quality </li></ul></ul><ul><ul><li>Outcomes </li></ul></ul><ul><ul><li>Preference-sensitive care </li></ul></ul><ul><li>Understand cancer care delivered in the VA </li></ul><ul><ul><li>Variation </li></ul></ul><ul><ul><li>Reasons for underuse of care </li></ul></ul>
  7. 7. Data Sources <ul><li>VA </li></ul><ul><ul><li>Cancer registry data </li></ul></ul><ul><ul><li>VA administrative data </li></ul></ul><ul><ul><li>Medicare data (for eligible veterans >65) </li></ul></ul><ul><ul><li>Medical record abstraction </li></ul></ul><ul><ul><li>Survey of 138 VA medical centers </li></ul></ul><ul><li>Private sector </li></ul><ul><ul><li>SEER-Medicare data </li></ul></ul>
  8. 8. VA Facilities Annu Rev Public Health 2009; 30:313-339
  9. 9. SEER Areas UT NM Hawaii IA Seattle/ Puget Sound Connecticut Since 1992 or earlier Metro Detroit Los Angeles San Jose/ Monterey San Francisco / Oakland Atlanta 2000 SEER Expansion CA LA KY New Jersey
  10. 10. Cohorts <ul><li>VA </li></ul><ul><ul><li>Comparison analyses </li></ul></ul><ul><ul><ul><li>Men aged >65 years with cancer diagnosed or first course of treatment in VA in 2001-2004 </li></ul></ul></ul><ul><ul><li>Within-VA analyses </li></ul></ul><ul><ul><ul><li>Men and women >18 years with cancer diagnosed or first course of treatment in VA in 2001-2004 </li></ul></ul></ul><ul><li>SEER-Medicare </li></ul><ul><ul><li>Men aged >65 years with cancer diagnosed in SEER areas in 2001-2004 </li></ul></ul>
  11. 11. Measures of Cancer Care Quality <ul><li>Based on guidelines recommending various treatments for </li></ul><ul><ul><li>Colon cancer </li></ul></ul><ul><ul><li>Rectal cancer </li></ul></ul><ul><ul><li>Non-small cell lung cancer </li></ul></ul><ul><ul><li>Small cell lung cancer </li></ul></ul><ul><ul><li>Prostate cancer </li></ul></ul><ul><ul><li>Large B-cell lymphoma </li></ul></ul>
  12. 12. Survival <ul><li>Colon cancer </li></ul><ul><li>Rectal cancer </li></ul><ul><li>Non-small cell lung cancer </li></ul><ul><li>Small-cell lung cancer </li></ul><ul><li>Diffuse large-B cell lymphoma </li></ul><ul><li>Multiple myeloma </li></ul>
  13. 13. Preference Sensitive Care <ul><li>Primary treatment for local/regional prostate cancer </li></ul><ul><li>Aggressive care at the end of life </li></ul>
  14. 14. Control Variables <ul><li>Demographics: age, race, marital status </li></ul><ul><li>Comorbidity: Charlson score, prior cancer </li></ul><ul><li>Cancer: stage at diagnosis and grade </li></ul><ul><li>Zip code level indicators of SES </li></ul><ul><ul><li>% with college degree </li></ul></ul><ul><ul><li>% professionals </li></ul></ul><ul><ul><li>% over age 64 living in poverty </li></ul></ul><ul><ul><li>% African American </li></ul></ul><ul><ul><li>% Hispanic/Latino, </li></ul></ul><ul><ul><li>median household income </li></ul></ul><ul><li>Quarter of diagnosis </li></ul>
  15. 15. Patient Characteristics Colon Cancer Cohort <ul><li> VA SEER-Medicare P </li></ul><ul><li>Mean age 74.9 76.4 <.001 </li></ul><ul><li>% black 16.3 8.1 <.001 </li></ul><ul><li>% married 56.0 70.6 <.001 </li></ul><ul><li>% college grads in zip code 25.6 31.7 <.001 </li></ul><ul><li>Median income in zip code $44,772 $56,548 <.001 </li></ul><ul><li>% blacks in zip 16.1 10.1 <.001 </li></ul>
  16. 16. Analytic Strategy—Comparative Analyses <ul><li>Propensity score methods to account for observed factors </li></ul><ul><ul><li>Estimate probability to be treated in VHA based on observed control variables </li></ul></ul><ul><ul><li>Applied Standardized Mortality Ratio weights </li></ul></ul><ul><ul><ul><li>Weight = 1 for VA patients, p/(1-p) for SEER-Medicare patients </li></ul></ul></ul><ul><ul><ul><li>Gives additional weight to fee-for-service Medicare patients that most resemble VHA patients –distribution of covariates is balanced & similar to that in the original VHA cohort </li></ul></ul></ul><ul><ul><ul><li>Estimates care a typical VHA patient would get in private sector </li></ul></ul></ul>
  17. 17. Sensitivity to Unobserved Confounders <ul><li>Assume existence of unobserved confounder </li></ul><ul><li>Re-estimate causal effect under assumptions (independent estimates) of </li></ul><ul><ul><li>Relationship between confounder & treatment </li></ul></ul><ul><ul><li>Relationship between confounder & outcomes </li></ul></ul><ul><li>Information on potential unobserved confounders </li></ul><ul><ul><li>Severity of comorbidity: MRA data from subset of VHA patients </li></ul></ul><ul><ul><li>Performance status: published data on differences </li></ul></ul>
  18. 18. Analytic Within-VA Analyses <ul><li>Hierarchical models including patient factors, hospital characteristics, and VISN </li></ul>
  19. 19. Results—Quality of Care
  20. 20. Stage at Diagnosis - Colon Cancer Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P<.001 % .0
  21. 21. Surgery for Colorectal Cancer P=.01 Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P=.11
  22. 22. Adjuvant Therapy for Colorectal Cancer Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P=.35 P=.39 %
  23. 23. Non Small Cell (NSC) Lung Cancer Primary Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P=.11 P=.87 %
  24. 24. Non Small Cell & Small Cell Lung Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P=.82 P=.36 %
  25. 25. Prostate Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P=.75 P<.001 %
  26. 26. Lymphoma Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P<.001 P=.52 %
  27. 27. Multiple Myeloma Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. P<.001 %
  28. 28. Role of Unobserved Confounders— Incomplete Adjustment for Comorbidity Respiratory Disease
  29. 29. Role of Unobserved Factors: Sensitivity Analyses <ul><li>Poor performance status </li></ul><ul><ul><li>Assume prevalence differs by setting </li></ul></ul><ul><ul><ul><li>17% VA </li></ul></ul></ul><ul><ul><ul><li>9% FFS-Medicare </li></ul></ul></ul><ul><ul><li>Assume 50% decrease in likelihood of treatment </li></ul></ul><ul><li>Severe comorbid illness </li></ul><ul><ul><li>Assume prevalence differs by setting </li></ul></ul><ul><ul><ul><li>30-45% VA </li></ul></ul></ul><ul><ul><ul><li>18-28% FFS-Medicare </li></ul></ul></ul><ul><ul><li>Assume 50% decrease in likelihood of treatment </li></ul></ul>
  30. 30. Role of Unobserved Factors: Sensitivity Analyses—Adjusted Difference in Quality *Comparing VA with FFS-Medicare Observed Covariates Performance Status Severe Comorbidity Adjuvant Chemo & Radiation for Rectal Cancer 3.2 [-4.0, 10.3] 5.6 [-1.5, 12.8] 7.6 [0.4, 14.7] Curative Surgery NSC Lung Cancer -3.6 [-8.1, 0.8] -1.3 [-5.8, 3.1] 2.6 [-1.8, 7.1] Chemo & RT for Limited Stage SC Lung Cancer 2.6 [-3.0, 8.2] 4.7 [-0.9, 10.3] 8.4 [2.8, 14.0]
  31. 31. Results—Survival
  32. 32. Survival for Colon Cancer Adjusted median survival VA=49 months; SEER=43 months p<0.001
  33. 33. Survival for Rectal Cancer Adjusted median survival VA=36 months; SEER=37 months p=0.55
  34. 34. Survival for NSC Lung Cancer Adjusted median survival VA=8 months; SEER=6 months p<0.001
  35. 35. Survival for Small Cell Lung Cancer Adjusted median survival VA=5 months; SEER=5 months p=0.64
  36. 36. Survival for Lymphoma Adjusted median survival VA=14 months; SEER=16 months p=0.75
  37. 37. Survival for Myeloma Adjusted median survival VA=19 months; SEER=17 months p=0.15
  38. 38. Role of Unobserved Factors: Sensitivity Analyses—Adjusted Hazard of Death *Comparing VA with FFS-Medicare Observed Covariates Performance Status Severe Comorbidity Colon Cancer 0.87 [0.81, 0.93] 0.82 [0.76, 0.87] 0.76 [0.71, 0.82] Rectal Cancer 1.03 [0.93, 1.14] 0.97 [0.88, 1.07] 0.90 [0.82, 1.00] NSC Lung Cancer 0.91 [0.88, 0.94] 0.85 [0.82, 0.88] 0.77 [0.74, 0.80] SC Lung Cancer 0.99 [0.93, 1.05] 0.92 [0.87, 0.98] 0.84 [0.79, 0.89] Lymphoma 1.02 [0.89, 1.18] 0.96 [0.84, 1.10] 0.90 [0.78, 1.03]
  39. 39. Results— Preference Sensitive Care
  40. 40. Primary Prostate Cancer Treatment Adjusted for age, race/ethnicity, marital status, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, % with college degree in zip code, % professionals in zip code, % over 64 living in poverty in zip code, % African American in zip code, and median household income in zip code. Overall P<.001 %
  41. 41. Aggressive End of Life Care Adjusted for age, race/ethnicity, marital status, cancer site, quarter-year of diagnosis, Charlson comorbidity score, history of prior cancer, census region, percent with college degree in zip code, percent professionals in zip code, percent over 64 living in poverty in zip code, percent African American in zip code, and median household income in zip code. P<.001 P=.09 P<.001 %
  42. 42. Within-VA Analyses Variation in Primary Prostate Cancer Treatment
  43. 43. Rates of Radiation Therapy by VAMC *Adjusted for patient, tumor, & hospital characteristics & VISN.
  44. 44. Rates of Radical Prostatectomy by VAMC *Adjusted for patient, tumor, & hospital characteristics & VISN.
  45. 45. Results—Reasons for Underuse of Effective Therapies
  46. 46. Rates of Treatments %
  47. 47. Reasons for Underuse of Therapies
  48. 48. Limitations <ul><li>Comparisons focused on men aged 65+; FFS Medicare only </li></ul><ul><li>VHA claims not based on payment </li></ul><ul><ul><li>But validity of claims-based measures of chemotherapy and radiation high </li></ul></ul><ul><li>Claims based measures of comorbidity </li></ul><ul><ul><li>Medical record abstraction collected chart-based measures in subset of VA patients </li></ul></ul><ul><li>Rely on sensitivity analyses to examine role of unmeasured factors </li></ul><ul><li>Limited follow-up, cannot examine impact of treatment on long-term survival </li></ul>
  49. 49. Summary-Quality <ul><li>Processes of care generally comparable in VA and private sector for older men with cancer </li></ul><ul><ul><li>VA earlier stage at diagnosis for colorectal cancer </li></ul></ul><ul><ul><li>VA higher rates of </li></ul></ul><ul><ul><ul><li>Surgery for stage I/II/III colon cancer </li></ul></ul></ul><ul><ul><ul><li>CHOP for lymphoma </li></ul></ul></ul><ul><ul><ul><li>Bisphosphonates for myeloma </li></ul></ul></ul><ul><ul><li>VA lower rates of </li></ul></ul><ul><ul><ul><li>3D CRT/IMRT </li></ul></ul></ul>
  50. 50. Summary-Survival <ul><li>Survival for colon and NSC lung cancer better in VA </li></ul><ul><ul><li>Primarily explained by earlier stage at diagnosis </li></ul></ul><ul><li>Survival for rectal, small cell lung, and lymphoma similar in the 2 settings </li></ul>
  51. 51. Summary- Preference Sensitive Care <ul><li>Higher rates of expectant management for primary treatment of prostate cancer in VA </li></ul><ul><li>Less aggressive care at the end of life in VA </li></ul>
  52. 52. Summary-Within-VA Variation <ul><li>Large variations by facility seen in utilization and process measures </li></ul><ul><li>Suggests that the facility a patient goes to can influence care received </li></ul><ul><ul><li>And thus differences not all influenced by guideline recommendations and/or patient preferences </li></ul></ul>
  53. 53. Summary-Reasons for Underuse <ul><li>Recommendation against therapy was main contributor to underuse of effective therapies </li></ul><ul><li>Patient refusal important </li></ul><ul><ul><li>Explained some of age and racial disparities in care </li></ul></ul>
  54. 54. <ul><li>Relative to FFS setting, a health care delivery system with primary care focus, coordination of care and integration, regional cancer centers, and global-budget </li></ul><ul><ul><li>Favorable quality of care in most measures </li></ul></ul><ul><ul><li>Favorable outcomes </li></ul></ul><ul><ul><li>Less intensive care when limited evidence for use </li></ul></ul>Implications
  55. 55. <ul><li>VHA provides care to challenging populations; relative quality and outcomes likely even better than observed </li></ul><ul><li>Provision of evidence based care while limiting use of preference-sensitive care suggest VHA is providing high value care </li></ul><ul><ul><li>Observed variable adoption of new technologies, particularly those require purchase of expensive equipment (IMRT) </li></ul></ul>Implications
  56. 56. <ul><li>Generally low rates of many measures in both settings </li></ul><ul><ul><li>Results from VHA MRA suggests that low rates in VHA mostly related to patient comorbidity </li></ul></ul><ul><ul><li>Highlights need for better evidence of effectiveness in non-RCT populations </li></ul></ul><ul><ul><li>Better tools to communicate known risks and benefits of therapy to assure informed decisions </li></ul></ul>Implications
  57. 57. Research Team <ul><li>Abt Associates </li></ul><ul><li>Sam Bozeman </li></ul><ul><li>Senior Project Director </li></ul><ul><li>Rose Zummo </li></ul><ul><li>Deputy Project Director </li></ul><ul><li>Elizabeth Axelrod </li></ul><ul><li>Senior Programmer </li></ul><ul><li>David Izrael Senior Programmer </li></ul><ul><li>David Deal </li></ul><ul><li>Survey Director </li></ul><ul><li>Medical Record Abstraction </li></ul><ul><li>Angel Kolins Lead Abstractor </li></ul><ul><li>Emily Savelli </li></ul><ul><li>Programmer </li></ul><ul><li>Harvard Medical School </li></ul><ul><li>Barbara McNeil, MD, PhD PI </li></ul><ul><li>Nancy Keating, MD, MPH Co-PI </li></ul><ul><li>Mary Beth Landrum, PhD Co-PI </li></ul><ul><li>Elizabeth Lamont, MD, MS </li></ul><ul><li>Co-Investigator </li></ul><ul><li>Jeff Souza Senior Programmer </li></ul><ul><li>Stephanie Segers Programmer </li></ul><ul><li>Larry Zaborski Programmer </li></ul><ul><li>Garrett Kirk Project Support </li></ul><ul><li>Dana Farber Cancer Inst. </li></ul><ul><li>Lawrence Shulman, MD </li></ul><ul><li>All Cancers </li></ul><ul><li>William Oh, MD </li></ul><ul><li>Prostate </li></ul><ul><li>Wendy Chen, MD </li></ul><ul><li>Breast </li></ul><ul><li>Craig Earle, MD </li></ul><ul><li>Colorectal </li></ul><ul><li>Jennifer Brown, MD </li></ul><ul><li>Hematology </li></ul><ul><li>Michael Rabin, MD </li></ul><ul><li>Lung </li></ul>

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