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Jessica Chubak, T. Onega, Weiwei Zhu, D. Buist, R. Hubbard (2017)
An Electronic Health Record-based Algorithm to Ascertain the Date of Second Breast Cancer Events.Medical care
E. Lamont, J. Herndon, J. Weeks, I. Henderson, C. Earle, R. Schilsky, N. Christakis (2006)
Measuring Disease-Free Survival and Cancer Relapse Using Medicare Claims From CALGB Breast Cancer Trial Participants (Companion to 9344)Journal of the National Cancer Institute, 98
Jessica Chubak, Onchee Yu, G. Pocobelli, L. Lamerato, Joe Webster, M. Prout, M. Yood, W. Barlow, D. Buist (2012)
Administrative data algorithms to identify second breast cancer events following early-stage invasive breast cancer.Journal of the National Cancer Institute, 104 12
K. Gooden, Daniel Howard, W. Carpenter, A. Carson, Y. Taylor, S. Peacock, P. Godley (2008)
The Effect of Hospital and Surgeon Volume on Racial Differences in Recurrence-Free Survival After Radical ProstatectomyMedical Care, 46
Tyler Ross, Daniel Ng, Jeffrey Brown, Roy Pardee, M. Hornbrook, Gene Hart, J. Steiner (2014)
The HMO Research Network Virtual Data Warehouse: A Public Data Model to Support CollaborationEGEMS, 2
P. Catalano, J. Ayanian, J. Weeks, K. Kahn, M. Landrum, A. Zaslavsky, Jeannette Lee, J. Pendergast, D. Harrington (2013)
Representativeness of Participants in the Cancer Care Outcomes Research and Surveillance Consortium Relative to the Surveillance, Epidemiology, and End Results ProgramMedical Care, 51
M. Hassett, H. Uno, A. Cronin, Nikki Carroll, M. Hornbrook, D. Ritzwoller (2017)
Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health ManagementMedical Care, 55
M. Hlatky, R. Ray, D. Burwen, K. Margolis, K. Johnson, Anna Kucharska‐Newton, J. Manson, Jennifer Robinson, M. Safford, M. Allison, T. Assimes, A. Bavry, J. Berger, R. Cooper-DeHoff, S. Heckbert, Wenjun Li, Simin Liu, L. Martin, M. Perez, H. Tindle, W. Winkelmayer, M. Stefanick (2014)
Use of Medicare Data to Identify Coronary Heart Disease Outcomes in the Women’s Health InitiativeCirculation: Cardiovascular Quality and Outcomes, 7
Schootman M, Jeffe DB, Gillanders WE
Racial disparities in the development of breast cancer metastases among older women: A multilevel study
M. Hassett, D. Ritzwoller, N. Taback, Nikki Carroll, A. Cronin, G. Ting, D. Schrag, J. Warren, M. Hornbrook, J. Weeks (2014)
Validating Billing/Encounter Codes as Indicators of Lung, Colorectal, Breast, and Prostate Cancer Recurrence Using 2 Large Contemporary CohortsMedical Care, 52
J. Fleet, S. Dixon, S. Shariff, R. Quinn, D. Nash, Z. Harel, A. Garg (2013)
Detecting chronic kidney disease in population-based administrative databases using an algorithm of hospital encounter and physician claim codesBMC Nephrology, 14
A. Deshpande, M. Schootman, A. Mayer (2015)
Development of a claims-based algorithm to identify colorectal cancer recurrence.Annals of epidemiology, 25 4
M. Klompas, E. Eggleston, J. Mcvetta, Ross Lazarus, Lingling Li, R. Platt (2013)
Automated Detection and Classification of Type 1 Versus Type 2 Diabetes Using Electronic Health Record DataDiabetes Care, 36
D. Ritzwoller, M. Hassett, H. Uno, A. Cronin, Nikki Carroll, M. Hornbrook, Lawrence Kushi (2018)
Development, Validation, and Dissemination of a Breast Cancer Recurrence Detection and Timing Informatics AlgorithmJNCI: Journal of the National Cancer Institute, 110
V. Thyagarajan, Sue Su, J. Gee, J. Duffy, Natalie McCarthy, K. Chan, Eric Weintraub, N. Lin (2013)
Identification of seizures among adults and children following influenza vaccination using health insurance claims data.Vaccine, 31 50
M. Hornbrook, Gene Hart, J. Ellis, D. Bachman, G. Ansell, Sarah Greene, E. Wagner, Roy Pardee, Mark Schmidt, A. Geiger, Amy Butani, T. Field, H. Fouayzi, Irina Miroshnik, Liyan Liu, R. Diseker, K. Wells, R. Krajenta, L. Lamerato, Christine Dudas (2005)
Building a virtual cancer research organization.Journal of the National Cancer Institute. Monographs, 35
K. Cummings, Fang Xu, L. Cummings, G. Cooper (2012)
A Comparison of Epidural Analgesia and Traditional Pain Management Effects on Survival and Cancer Recurrence after Colectomy: A Population-based StudyAnesthesiology, 116
M. Stokes, D. Thompson, E. Montoya, M. Weinstein, E. Winer, C. Earle (2005)
Ten-year survival and cost following breast cancer recurrence: estimates from SEER-medicare data.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 11 2
D. McClish, L. Penberthy, A. Pugh (2003)
Using Medicare claims to identify second primary cancers and recurrences in order to supplement a cancer registry.Journal of clinical epidemiology, 56 8
J. Saczynski, S. Andrade, L. Harrold, J. Tjia, S. Cutrona, K. Dodd, R. Goldberg, J. Gurwitz (2012)
A systematic review of validated methods for identifying heart failure using administrative dataPharmacoepidemiology and Drug Safety, 21
J. Ayanian, E. Chrischilles, R. Fletcher, M. Fouad, D. Harrington, K. Kahn, C. Kiefe, J. Lipscomb, J. Malin, A. Potosky, D. Provenzale, R. Sandler, M. Ryn, R. Wallace, J. Weeks, D. West (2004)
Understanding cancer treatment and outcomes: the Cancer Care Outcomes Research and Surveillance Consortium.Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 22 15
M. Schootman, D. Jeffe, W. Gillanders, R. Aft (2009)
Racial disparities in the development of breast cancer metastases among older womenCancer, 115
Joseph Sewell, Amrita Rao, S. Elliott (2013)
Validating a claims-based method for assessing severe rectal and urinary adverse effects of radiotherapy.Urology, 82 2
C. Earle, A. Nattinger, A. Potosky, K. Lang, R. Mallick, M. Berger, J. Warren (2002)
Identifying Cancer Relapse Using SEER-Medicare DataMedical Care, 40
Purpose: Data from claims and electronic medical records (EMRs) are frequently used to identify clinical events (eg, cancer diagnosis, stroke). However, accurately determining the time of clinical events can be challenging, and the methods used to generate time estimates are underdeveloped. We sought to develop an approach to determine the time of a clinical event-cancer recurrence-using high-dimensional longitudinal structured data. Methods: Manual chart abstraction provided information regarding the actual time of cancer recurrence. These data were linked to claims from Medicare or structured EMR data from the Cancer Research Network, which were used to determine time of recurrence for patients with lung or colorectal cancer. We analyzed the longitudinal profile of codes that could help determine the time of recurrence, adjusted for systematic differences between code dates and recurrence dates, and integrated time estimates from different codes to empirically derive an optimal algorithm. Results: We identified twelve code groups that could help determine the time of recurrence. Using claims data for patients with lung cancer, the optimal algorithm consisted of three code groups and provided an average prediction error of 4.8 months. Using EMR data or applying this approach to patients with colorectal cancer yielded similar results. Conclusion: Time estimates were improved by selecting codes not necessarily the same as those used to identify recurrence, combining time estimates from multiple code groups, and adjusting for systematic bias between code dates and recurrence dates. Improving the accuracy of time estimates for clinical events can facilitate research, quality measurement, and process improvement.
JCO Clinical Cancer Informatics – Wolters Kluwer Health
Published: May 15, 2018
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