scholarly journals High-dimensional propensity score adjustment in HIV research using linked administrative health data

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Taylor McLinden ◽  
Rolando Barrios ◽  
Robert Hogg
Keyword(s):  
Propensity Score ◽  
Administrative Data ◽  
Population Data ◽  
Population Based ◽  
Health Data ◽  
High Dimensional ◽  
People Living With Hiv ◽  
Administrative Health Data ◽  
Hiv Research ◽  
Linked Administrative Health Data

BackgroundDespite not being collected for research purposes, linked administrative health data are increasingly being used to conduct observational epidemiologic analyses. In the field of HIV research in British Columbia (BC), Canada, the Comparative Outcomes And Service Utilization Trends (COAST) Study is based on a linkage between HIV-related clinical data and several provincial administrative health datasets. Specifically, the BC Centre for Excellence in HIV/AIDS Drug Treatment Program, which manages antiretroviral therapy (ART) dispensation for all known people living with HIV (PLWH) in BC, is linked with several Population Data BC data holdings. Population Data BC is a repository that houses longitudinal administrative data for all BC residents. RationaleWhile the use of administrative data for research poses several challenges, bias due to confounding remains to be a key issue in this context. While randomized controlled trials of ART are common, an objective of COAST is to further examine the "real-world" impact of ART on health and clinical outcomes in a population-based sample of 13,907 PLWH in BC. Therefore, while longitudinal administrative data provide a unique opportunity to estimate the effect of ART on outcomes that are infrequently assessed in trials (e.g., chronic conditions), such data often lacks information on sociodemographic, socioeconomic, and behavioural confounders. ApproachIt has been shown that adjustment for large numbers of covariates, in the form of administrative codes (e.g., diagnostic ICD codes, procedure codes, drug identification numbers), allows for better control of confounding bias. Therefore, relying on an established methodology in pharmacoepidemiology, we will use the high-dimensional propensity score algorithm to select and prioritize covariates (codes) that collectively act as proxies for unmeasured confounders. The use of this causal inference methodology in COAST will enhance our ability to generate stronger evidence to inform strategies that may improve the health and wellbeing of PLWH in this setting.

scholarly journals Detection of adverse drug events in e-prescribing and administrative health data: a validation study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bettina Habib ◽  
Robyn Tamblyn ◽  
Nadyne Girard ◽  
Tewodros Eguale ◽  
Allen Huang
Keyword(s):  
Administrative Data ◽  
Gold Standard ◽  
Adverse Drug Events ◽  
Study Drug ◽  
Health Data ◽  
Diagnostic Code ◽  
Administrative Health Data ◽  
Potential Ades ◽  
Patient Reported

Abstract Background Administrative health data are increasingly used to detect adverse drug events (ADEs). However, the few studies evaluating diagnostic codes for ADE detection demonstrated low sensitivity, likely due to narrow code sets, physician under-recognition of ADEs, and underreporting in administrative data. The objective of this study was to determine if combining an expanded ICD code set in administrative data with e-prescribing data improves ADE detection. Methods We conducted a prospective cohort study among patients newly prescribed antidepressant or antihypertensive medication in primary care and followed for 2 months. Gold standard ADEs were defined as patient-reported symptoms adjudicated as medication-related by a clinical expert. Potential ADEs in administrative data were defined as physician, ED, or hospital visits during follow-up for known adverse effects of the study medication, as identified by ICD codes. Potential ADEs in e-prescribing data were defined as study drug discontinuations or dose changes made during follow-up for safety or effectiveness reasons. Results Of 688 study participants, 445 (64.7%) were female and mean age was 64.2 (SD 13.9). The study drug for 386 (56.1%) patients was an antihypertensive, and for 302 (43.9%) an antidepressant. Using the gold standard definition, 114 (16.6%) patients experienced an ADE, with 40 (10.4%) among antihypertensive users and 74 (24.5%) among antidepressant users. The sensitivity of the expanded ICD code set was 7.0%, of e-prescribing data 9.7%, and of the two combined 14.0%. Specificities were high (86.0–95.0%). The sensitivity of the combined approach increased to 25.8% when analysis was restricted to the 27% of patients who indicated having reported symptoms to a physician. Conclusion Combining an expanded diagnostic code set with e-prescribing data improves ADE detection. As few patients report symptoms to their physician, higher detection rates may be achieved by collecting patient-reported outcomes via emerging digital technologies such as patient portals and mHealth applications.

scholarly journals General Public Views on Uses and Users of Administrative Health Data

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
P. Alison Paprica ◽  
Michael Schull
Keyword(s):  
Private Sector ◽  
General Public ◽  
Personal Data ◽  
Health Data ◽  
General Information ◽  
Privacy And Security ◽  
Administrative Health Data ◽  
Potential Benefits ◽  
Public Views ◽  
Linked Administrative Health Data

ABSTRACTObjectivesHigh profile initiatives and reports highlight the potential benefits that could be realized by increasing access to health data, but do members of the general public share this view? The objective was to gain insight into the general public’s attitudes toward users and uses of administrative health data. ApproachIn fall 2015, four professionally-moderated focus groups with a total of 31 Ontario participants were conducted; two in Thunder Bay, two in Toronto. Participants were asked to review and comment on: general information about research based on linked administrative health data, a case study and models through which various users might use administrative health data. ResultsSupport for research based on linked administrative health data was strongest when people agreed with the purposes for which studies were conducted. The main concerns related to the security of personal data generally (e.g., Canada Revenue Agency hacking incidents were noted) and potentially inappropriate uses of health data, particularly by the private sector (e.g., strong reservations about studies done solely or primarily with a profit motive). Participants were reassured when provided with information about the process for removing or coding identifying information from health data, and about the oversight provided by the Information and Privacy Commissioner of Ontario. However, even when fully informed of privacy and security safeguards, participants still felt that risks unavoidably increase when there are more people and organizations accessing data. ConclusionsMembers of general public were generally supportive of research based on linked administrative health data but with conditions, particularly when the possibility of private sector research was discussed. Notably, and citing security concerns, focus group participants preferred models that had a limited number of individuals or organizations accessing data.

scholarly journals Multi-province epidemiological research using linked administrative data: a case study from Canada.

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Amanda Leanne Butler ◽  
Mark Smith ◽  
Wayne Jones ◽  
Carol E Adair ◽  
Simone Vigod ◽  
...  
Keyword(s):  
Information Systems ◽  
Administrative Data ◽  
Research Process ◽  
Health Data ◽  
Provincial Government ◽  
Data Systems ◽  
Administrative Health Data ◽  
Healthcare Data ◽  
Research Activities

BackgroundCanada has a publicly-funded universal healthcare system with information systems managed by 13 different provinces and territories. This context creates inconsistencies in data collection and challenges for research or surveillance conducted at the national or multi-jurisdictional level. ObjectiveUsing a recent Canadian research project as a case study, we document the strengths and challenges of using administrative health data in a multi-jurisdictional context. We discuss the implications of using different health information systems and the solutions we adopted to deal with variations. Our goal is to contribute to better understanding of these challenges and the development of a more integrated and harmonized approach to conducting multi-jurisdictional research using administrative data. Context and ModelUsing data from five separate provincial healthcare data systems, we sought to create and report on a set of provincially-comparable mental health and addiction services performance indicators. In this paper, we document the research process, challenges, and solutions. Finally, we conclude by making recommendations for investment in national infrastructure that could help cut costs, broaden scope, and increase use of administrative health data that exists in Canada. ConclusionCanada has an incredible wealth of administrative data that resides in 13 territorial and provincial government systems. Navigating access and improving comparability across these systems has been an ongoing challenge for the past 20 years, but progress is being made. We believe that with some investment, a more harmonized and integrated information network could be developed that supports a broad range of surveillance and research activities with strong policy and program implications.

scholarly journals Challenges Associated with Cross-Jurisdictional Analyses using Administrative Health Data and Primary Care Electronic Medical Records in Canada

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Alan Katz ◽  
Jennifer Enns ◽  
Sabrina T Wong ◽  
Tyler Williamson ◽  
Alexander Singer ◽  
...  
Keyword(s):  
British Columbia ◽  
Social Services ◽  
Administrative Data ◽  
Data Access ◽  
Health Data ◽  
Quality Data ◽  
Data Governance ◽  
Quality Health Care ◽  
Data Repositories ◽  
Administrative Health Data

Over the last 30 years, public investments in Canada and many other countries have created clinical and administrative health data repositories to support research on health and social services, population health and health policy. However, there is limited capacity to share and use data across jurisdictional boundaries, in part because of inefficient and cumbersome procedures to access these data and gain approval for their use in research. A lack of harmonization among variables and indicators makes it difficult to compare research among jurisdictions. These challenges affect the quality, scope, and impact of work that could be done. The purpose of this paper is to compare and contrast the data access procedures in three Canadian jurisdictions (Manitoba, Alberta and British Columbia), and to describe how we addressed the challenges presented by differences in data governance and architecture in a Canadian cross-jurisdictional research study. We characterize common stages in gaining access to administrative data among jurisdictions, including obtaining ethics approval, applying for data access from data custodians, and ensuring the extracted data is released to accredited individuals in secure data environments. We identify advantages of Manitoba’s flexible ‘stewardship’ model over the more restrictive ‘custodianship’ model in British Columbia, and highlight the importance of communication between analysts in each jurisdiction to compensate for differences in coding variables and poor quality data. Researchers and system planners must have access to and be able to make effective use of administrative health data to ensure that Canadians continue to have access to high-quality health care and benefit from effective health policies. The considerable benefits of collaborative population-based research that spans jurisdictional borders have been recognized by the Canadian Institutes for Health Research in their recent call for the creation of a National Data Platform to resolve many of the issues in harmonization and validation of administrative data elements.

scholarly journals Linkage of whole genome sequencing with administrative health, and electronic medical record data for the study of autism spectrum disorder: Feasibility, Opportunities and Challenges

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Jennifer Brooks ◽  
Evdokia Anagnostou ◽  
Farah Rahman ◽  
Karen Tu ◽  
Lavnaya Uruthiramoorthy ◽  
...  
Keyword(s):  
Health System ◽  
Whole Genome Sequencing ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Administrative Data ◽  
Genome Sequencing ◽  
Health Data ◽  
Spectrum Disorder ◽  
Whole Genome ◽  
Administrative Health Data

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) that presents with a high degree of heterogeneity (e.g., co-occurrence of other NDDs and other co-morbid conditions), contributing to differential health system needs. Genetics are known to play an important role in ASD and may be associated with different disease trajectories. Objectives and ApproachIn this proof of principle project, our objective is to link >2,200 children with a confirmed diagnosis of a NDD from the Province of Ontario Neurodevelopmental (POND) Study to administrative health data and electronic medical record (EMR) data in order to identify subgroups of ASD with unique health system trajectories. POND includes detailed phenotype and whole genome sequencing (WGS) data. Identified subgroups will be characterized based on clinical phenotype and genetics. To meet this goal, consideration of WGS-specific privacy and data issues is needed to implement processes which are above and beyond traditional requirements for analyzing individual-level administrative health data. ResultsLinkage of WGS data with administrative health data is an emerging area of research. As such it has presented a number of initial challenges for our study of ASD. Privacy concerns surrounding the use of WGS data and rare-variant analysis are of particular importance. Practical issues required the need for analysts with expertise in administrative data, EMR data and genetic analyses, and specialized software and sufficient processing power to analyze WGS data. Transdisciplinary discussions of the scope and significance of research questions addressed through this linkage were crucial. The identification of genetic determinants of phenotypes and trajectories in ASD could support targeted early interventions; EMR linkage may inform algorithms to identify ASD in broader populations. These approaches could improve both patient outcome and family experience. Conclusion/ImplicationsAs the cost of genetic sequencing decreases, WGS data will become part of the routine clinical management of patients. Linkage of WGS, EMR and administrative data has tremendous potential that has largely not been realized; including population-level ASD research to improve our ability to predict long-term outcomes associated with ASD.

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