TY - JOUR
T1 - Mind the gap
T2 - observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data
AU - North American AIDS Cohort Collaboration on Research and Design
AU - Althoff, Keri N.
AU - Wong, Cherise
AU - Hogan, Brenna
AU - Desir, Fidel
AU - You, Bin
AU - Humes, Elizabeth
AU - Zhang, Jinbing
AU - Jing, Yuezhou
AU - Modur, Sharada
AU - Lee, Jennifer S.
AU - Freeman, Aimee
AU - Kitahata, Mari
AU - Van Rompaey, Stephen
AU - Mathews, W. Christopher
AU - Horberg, Michael A.
AU - Silverberg, Michael J.
AU - Mayor, Angel M.
AU - Salters, Kate
AU - Moore, Richard D.
AU - Gange, Stephen J.
N1 - Funding Information:
The authors would like to thank the Data Managers at the individual NA-ACCORD contributing cohorts for their continued partnership and tireless efforts to collect the data. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was supported by National Institutes of Health, United States grants U01AI069918, F31AI124794, F31DA037788, G12MD007583, K01AI093197, K01AI131895, K23EY013707, K24AI065298, K24AI118591, K24DA000432, KL2TR000421, M01RR000052, N01CP01004, N02CP055504, N02CP91027, P30AI027757, P30AI027763, P30AI027767, P30AI036219, P30AI050410, P30AI094189, P30AI110527, P30MH62246, R01AA016893, R01CA165937, R01DA011602, R01DA012568, R01 AG053100, R24AI067039, U01AA013566, U01AA020790, U01AI031834, U01AI034989, U01AI034993, U01AI034994, U01AI035004, U01AI035039, U01AI035040, U01AI035041, U01AI035042, U01AI037613, U01AI037984, U01AI038855, U01AI038858, U01AI042590, U01AI068634, U01AI068636, U01AI069432, U01AI069434, U01AI103390, U01AI103397, U01AI103401, U01AI103408, U01DA03629, U01DA036935, U01HD032632, U10EY008057, U10EY008052, U10EY008067, U24AA020794,U54MD007587, UL1RR024131, UL1TR000004, UL1TR000083, UL1TR000454, UM1AI035043, Z01CP010214 and Z01CP010176; contracts CDC-200-2006-18797 and CDC-200-2015-63931 from the Centers for Disease Control and Prevention, USA; contract 90047713 from the Agency for Healthcare Research and Quality, USA; contract 90051652 from the Health Resources and Services Administration, USA; grants CBR-86906, CBR-94036, HCP-97105, and TGF-96118 from the Canadian Institutes of Health Research, Canada; Ontario Ministry of Health and Long Term Care; and the Government of Alberta, Canada. Additional support was provided by the National Cancer Institute, National Institute for Mental Health, and National Institute on Drug Abuse.
Funding Information:
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was supported by National Institutes of Health , United States grants U01AI069918 , F31AI124794 , F31DA037788 , G12MD007583 , K01AI093197 , K01AI131895 , K23EY013707 , K24AI065298 , K24AI118591 , K24DA000432 , KL2TR000421 , M01RR000052 , N01CP01004 , N02CP055504 , N02CP91027 , P30AI027757 , P30AI027763 , P30AI027767 , P30AI036219 , P30AI050410 , P30AI094189 , P30AI110527 , P30MH62246 , R01AA016893 , R01CA165937 , R01DA011602 , R01DA012568 , R01 AG053100 , R24AI067039 , U01AA013566 , U01AA020790 , U01AI031834 , U01AI034989 , U01AI034993 , U01AI034994 , U01AI035004 , U01AI035039 , U01AI035040 , U01AI035041 , U01AI035042 , U01AI037613 , U01AI037984 , U01AI038855 , U01AI038858 , U01AI042590 , U01AI068634 , U01AI068636 , U01AI069432 , U01AI069434 , U01AI103390 , U01AI103397 , U01AI103401 , U01AI103408 , U01DA03629 , U01DA036935 , U01HD032632 , U10EY008057 , U10EY008052 , U10EY008067 , U24AA020794 , U54MD007587 , UL1RR024131 , UL1TR000004 , UL1TR000083 , UL1TR000454 , UM1AI035043 , Z01CP010214 and Z01CP010176 ; contracts CDC-200-2006-18797 and CDC-200-2015-63931 from the Centers for Disease Control and Prevention , USA; contract 90047713 from the Agency for Healthcare Research and Quality , USA; contract 90051652 from the Health Resources and Services Administration , USA; grants CBR-86906 , CBR-94036 , HCP-97105 , and TGF-96118 from the Canadian Institutes of Health Research , Canada; Ontario Ministry of Health and Long Term Care; and the Government of Alberta , Canada. Additional support was provided by the National Cancer Institute, National Institute for Mental Health, and National Institute on Drug Abuse.
Funding Information:
The authors would like to thank the Data Managers at the individual NA-ACCORD contributing cohorts for their continued partnership and tireless efforts to collect the data. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was supported by National Institutes of Health, United States grants U01AI069918, F31AI124794, F31DA037788, G12MD007583, K01AI093197, K01AI131895, K23EY013707, K24AI065298, K24AI118591, K24DA000432, KL2TR000421, M01RR000052, N01CP01004, N02CP055504, N02CP91027, P30AI027757, P30AI027763, P30AI027767, P30AI036219, P30AI050410, P30AI094189, P30AI110527, P30MH62246, R01AA016893, R01CA165937, R01DA011602, R01DA012568, R01 AG053100, R24AI067039, U01AA013566, U01AA020790, U01AI031834, U01AI034989, U01AI034993, U01AI034994, U01AI035004, U01AI035039, U01AI035040, U01AI035041, U01AI035042, U01AI037613, U01AI037984, U01AI038855, U01AI038858, U01AI042590, U01AI068634, U01AI068636, U01AI069432, U01AI069434, U01AI103390, U01AI103397, U01AI103401, U01AI103408, U01DA03629, U01DA036935, U01HD032632, U10EY008057, U10EY008052, U10EY008067, U24AA020794,U54MD007587, UL1RR024131, UL1TR000004, UL1TR000083, UL1TR000454, UM1AI035043, Z01CP010214 and Z01CP010176; contracts CDC-200-2006-18797 and CDC-200-2015-63931 from the Centers for Disease Control and Prevention, USA; contract 90047713 from the Agency for Healthcare Research and Quality, USA; contract 90051652 from the Health Resources and Services Administration, USA; grants CBR-86906, CBR-94036, HCP-97105, and TGF-96118 from the Canadian Institutes of Health Research, Canada; Ontario Ministry of Health and Long Term Care; and the Government of Alberta, Canada. Additional support was provided by the National Cancer Institute, National Institute for Mental Health, and National Institute on Drug Abuse. K.N.A. serves on the Scientific Advisory Board for TrioHealth (outside the submitted work). M.J.S. received research grants to his institution from Pfizer and Merck (outside the submitted work). There are no other conflicts of interest.
Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/5
Y1 - 2019/5
N2 - Purpose: Use of electronic health records (EHRs) in health research may lead to the false assumption of complete event ascertainment. We estimated “observation windows” (OWs), defined as periods within which the assumption of complete ascertainment of events is more likely to hold, as a quality control approach to reducing the likelihood of this false assumption. We demonstrated the impact of OWs on estimating the rates of type II diabetes mellitus (diabetes) from HIV clinical cohorts. Methods: Data contributed by 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence as a case study. Procedures included (1) gathering cohort-level data; (2) visualizing and summarizing gaps in observations; (3) systematically establishing start and stop dates during which the assumption of complete ascertainment of diabetes events was reasonable; and (4) visualizing the diabetes OWs relative to the cohort open and close dates to identify immortal person-time. We estimated diabetes occurrence event rates and 95% confidence intervals in the most recent decade that data were available (January 1, 2007, to December 31, 2016). Results: The number of diabetes events decreased by 17% with the use of the diabetes OWs; immortal person-time was removed decreasing total person-years by 23%. Consequently, the diabetes rate increased from 1.23 (95% confidence interval [1.20, 1.25]) per 100 person-years to 1.32 [1.29, 1.35] per 100 person-years with the use of diabetes OWs. Conclusions: As the use of EHR-curated data for event-driven health research continues to expand, OWs have utility as a quality control approach to complete event ascertainment, helping to improve accuracy of estimates by removing immortal person-time when ascertainment is incomplete.
AB - Purpose: Use of electronic health records (EHRs) in health research may lead to the false assumption of complete event ascertainment. We estimated “observation windows” (OWs), defined as periods within which the assumption of complete ascertainment of events is more likely to hold, as a quality control approach to reducing the likelihood of this false assumption. We demonstrated the impact of OWs on estimating the rates of type II diabetes mellitus (diabetes) from HIV clinical cohorts. Methods: Data contributed by 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence as a case study. Procedures included (1) gathering cohort-level data; (2) visualizing and summarizing gaps in observations; (3) systematically establishing start and stop dates during which the assumption of complete ascertainment of diabetes events was reasonable; and (4) visualizing the diabetes OWs relative to the cohort open and close dates to identify immortal person-time. We estimated diabetes occurrence event rates and 95% confidence intervals in the most recent decade that data were available (January 1, 2007, to December 31, 2016). Results: The number of diabetes events decreased by 17% with the use of the diabetes OWs; immortal person-time was removed decreasing total person-years by 23%. Consequently, the diabetes rate increased from 1.23 (95% confidence interval [1.20, 1.25]) per 100 person-years to 1.32 [1.29, 1.35] per 100 person-years with the use of diabetes OWs. Conclusions: As the use of EHR-curated data for event-driven health research continues to expand, OWs have utility as a quality control approach to complete event ascertainment, helping to improve accuracy of estimates by removing immortal person-time when ascertainment is incomplete.
KW - Diabetes
KW - Electronic medical records
KW - HIV
KW - Health research
KW - Immortal person-time
KW - Quality control
UR - http://www.scopus.com/inward/record.url?scp=85064319599&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064319599&partnerID=8YFLogxK
U2 - 10.1016/j.annepidem.2019.01.015
DO - 10.1016/j.annepidem.2019.01.015
M3 - Article
C2 - 31005552
AN - SCOPUS:85064319599
SN - 1047-2797
VL - 33
SP - 54
EP - 63
JO - Annals of epidemiology
JF - Annals of epidemiology
ER -