Linking Electronic Health Records Across Institutions to Understand Why Women Seek Care at Multiple Sites for Breast Cancer Caroline A. Thompson, PhD, MPH Palo Alto Medical Foundation Research Institute Electronic Data Methods Forum Symposium June 7, 2014, San Diego, CA

COLLABORATORS Harold S. Luft, PhD Palo Alto Medical Foundation Research Institute Allison Kurian MD, MS Stanford University Medical School Oncology and Health Research and Policy 2

BREAST CANCER PATHWAYS Brest cancer treatment is a long and complex “journey” Individual “pathways” may include multiple types of treatments, physicians, facilities, and/or specialty care 3

BREAST CANCER CARE ACROSS ACADEMIC AND COMMUNITY SETTINGS 4 PAMF: Multispecialty community health care system in Greater Bay Area Stanford: Academic medical center with surgical and inpatient facilities, serving same catchment area

ACADEMIC AND COMMUNITY ELECTRONIC HEALTH RECORDS (EHR) PAMF (“Community”): Long term primary care follow-up Lack comprehensive claims data “Blind” to out-of-network care Stanford (“Academic”): Tertiary academic center “One-time” consultations; specialty care Limited long-term follow-up 5

CALIFORNIA CANCER REGISTRY (CCR) Statewide population-based cancer surveillance system Collected: –Tumor details –Diagnosis facility –Initial treatment summaries NOT collected: –Detailed treatment history –Treatment facilities –Cancer recurrences 6

BREAST CANCER CARE PATHWAYS 7 Diagnostic radiology Medical oncology Surgical oncology Breast reconstruction A Treating clinic

BREAST CANCER CARE IN A FRAGMENTED HEALTHCARE SYSTEM 8 Diagnostic radiology Medical oncology Surgical oncology Breast reconstruction Medical oncology Recurrence A C Tertiary center Community center Out of area center B Treating clinic

ONCOSHARE DATA INITIATIVE Richard & Susan Levy Family Trust Multiple data linkages: –Stanford EHR –PAMF EHR –CCR tumor details –Myriad genetics For all women treated for breast cancer at either (or both) institutions, from Weber, et al. AMIA Annu Symp Proc. 2012; 2012:

What can we learn from linking EHR? “Data linkage identified 16% of patients were treated in two health care facilities and, despite comparable prognostic factors, received far more intensive treatment.” 10

SCREENINGDIAGNOSISTREATMENTPOST-TREATMENT SURVEILLANCE -Mammography -MRI -Ultrasound -MRI -Ultrasound -Biopsy -Histology -Pathology -Surgery -Chemotherapy --Radiation -Mammography -Recurrence -Survival BREAST CANCER PATHWAYS Pt 1 Pt 2 Pt 3 Pt 5 Pt 6 ELECTRONIC HEALTH RECORDS

DEFINING THE ANALYTICAL COHORT All women with 174x ICD9 code in EMR sent to CCR for confirmation of cancer Some women just seen for consultation or screening/ surveillance Among women treated, can we identify a diagnosing procedure? 12 13,512 total patients (174x ICD9 in EMR with confirmed tumor details provided by CCR) 1,282 (9%) Physician consultation only 4,806 (36%) Screening/Diagnosis or Surveillance only 7,424 (55%) Received interventions for primary breast cancer 5353 (72%) Diagnosed and treated 2071 (28%) Treated but diagnosed elsewhere

FACILITY USE BY CARE PERIOD (N=7,424 treated patients) FacilityOverallScreeningDiagnosisTreatmentSurveillance Community3,074 (41%)1,934 (26%)3,293 (44%)3,395 (46%)3,165 (43%) Academic3,162 (43%)383 (5%)2,591 (35%)3,509 (47%)2,470 (33%) Both1,188 (16%)30 (0.4%)449 (6%)520 (7%)469 (6%) Other-5,077 (69%)1,091 (14%)-1,320 (18%) Facility Overall ScreeningDiagnosisTreatmentSurveillance Both1,188 (16%)30 (0.4%)449 (6%)520 (7%)469 (6%) 2 nd Opinion only 110 (9%)2 (6%)130 (29%)112 (22%)203 (43%) Diagnostics / Treatment 1078 (91%)28 (94%)319 (71%)408 (78%)266 (57%)

FACILITY USE BY CANCER STAGE (N=6,984 with staging data) Cancer Stage Diagnostic ProceduresTreatment Interventions Facility Switch after Diagnosis One Facility Both Facilities One Facility Both Facilities NoYes DCIS (N=1,147) 15%21%15%18%11%14% Stage I (N=2,607) 35%39%35%31%39%27% Stage II (N=2,310) 31% 37%29%40% Stage III (N=688) 9%5%9%10%8%13% Stage IV (N=232) 3% 2%4%

FACILITY USE BY TREATMENT EPISODES Episode characteristic OverallTreatment periodsSurveillance periods One Facility Both Facilities One Facility Both Facilities One Facility Both Facilities Mean number of treatment episodes % with >1 treatment episode 16%29%17%41%20%40% Average episode length in days

CONCLUSIONS Linking EHR data from multiple neighboring healthcare systems can improve understanding of cancer pathways. HOWEVER: Careful consideration of the complexity of the treatment process is necessary to make valid inferences. –How many treatment periods? –How long was the treatment period? –What about pre- and post- treatment periods? Longitudinality of the data must be preserved. WORK IN PROGRESS 16

Funding Acknowledgement: Richard & Susan Levy Family Trust Contact: Caroline A. Thompson, PhD, MPH Palo Alto Medical Foundation Research Institute 17