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A population-based approach for implementing change from opt-out to opt-in research permissions.

ABSTRACT: Due to recently proposed changes in the Common Rule regarding the collection of research preferences, there is an increased need for efficient methods to document opt-in research preferences at a population level. Previously, our institution developed an opt-out paper-based workflow that could not be utilized for research in a scalable fashion. This project was designed to demonstrate the feasibility of implementing an electronic health record (EHR)-based active opt-in research preferences program. The first phase of implementation required creating and disseminating a patient questionnaire through the EHR portal to populate discreet fields within the EHR indicating patients' preferences for future research study contact (contact) and their willingness to allow anonymised use of excess tissue and fluid specimens (biobank). In the second phase, the questionnaire was presented within a clinic nurse intake workflow in an obstetrical clinic. These permissions were tabulated in registries for use by investigators for feasibility studies and recruitment. The registry was also used for research patient contact management using a new EHR encounter type to differentiate research from clinical encounters. The research permissions questionnaire was sent to 59,670 patients via the EHR portal. Within four months, 21,814 responses (75% willing to participate in biobanking, and 72% willing to be contacted for future research) were received. Each response was recorded within a patient portal encounter to enable longitudinal analysis of responses. We obtained a significantly lower positive response from the 264 females who completed the questionnaire in the obstetrical clinic (55% volunteers for biobank and 52% for contact). We demonstrate that it is possible to establish a research permissions registry using the EHR portal and clinic-based workflows. This patient-centric, population-based, opt-in approach documents preferences in the EHR, allowing linkage of these preferences to health record information.

SUBMITTER: Marshall EA

PROVIDER: S-EPMC5404843 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A population-based approach for implementing change from opt-out to opt-in research permissions.

Marshall Elizabeth A EA Oates Jim C JC Shoaibi Azza A Obeid Jihad S JS Habrat Melissa L ML Warren Robert W RW Brady Kathleen T KT Lenert Leslie A LA

PloS one 20170425 4

Due to recently proposed changes in the Common Rule regarding the collection of research preferences, there is an increased need for efficient methods to document opt-in research preferences at a population level. Previously, our institution developed an opt-out paper-based workflow that could not be utilized for research in a scalable fashion. This project was designed to demonstrate the feasibility of implementing an electronic health record (EHR)-based active opt-in research preferences progr ...[more]

PMID: 28441388

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Project description:ObjectiveTo assess the feasibility and outcomes of implementing a hospital-based "opt-out" tobacco-cessation service.MethodsIn 2014, the Medical University of South Carolina adopted a policy that all hospitalized patients who self-report using tobacco be referred to tobacco-cessation service. This is a descriptive study of a real-world effort to implement guidelines for a hospital-based cessation service consistent with Joint Commission's standards. Between February 2014 and May 2015, 42 061 adults were admitted to the Medical University of South Carolina Hospital. Eligible current cigarette smokers were referred to the tobacco-cessation service, which consisted of a bedside consult and phone follow-up 3, 14, and 30 days after hospital discharge using interactive-voice-response. The primary study outcomes evaluated the proportions of smokers reached by the bedside counselor and/or phone follow-up, smokers who opted out, and smokers who self-reported not smoking when last contacted by phone.ResultsRecords identified 8423 smokers, of whom 69.4% (n = 5843) were referred into the service. One full-time bedside counselor was able to speak with 1918 (32.8%) patients, of whom 96 (5%) denied currently smoking and 287 (14.9%) refused counselling. Reach at follow-up was achieved for 703 (55%) smokers who received bedside counselling and 1613 (49%) who did not, yielding an overall follow-up reach rate of 60%. Of those reached by phone, 36.4% reported not smoking (51% vs. 27% for those who did and did not receive bedside counselling, respectively). Intent-to-treat abstinence rate was 13.5% according to the last known smoking status.ConclusionsFindings from this study suggest that an inpatient smoking-cessation service with an "opt-out" approach can positively impact short-term cessation outcomes.Implications(1) The findings demonstrate the feasibility of implementing an automated large-scale opt-out tobacco-cessation service for hospitalized patients that is consistent with the Joint Commission recommended standards for treating tobacco dependence. (2) Receiving a bedside tobacco-cessation consult while hospitalized increased the use of stop smoking medications and abstinence from smoking after discharge from the hospital. (3) Even in those patients who did not receive a bedside consult, 5% accepted a referral to the South Carolina Tobacco Quitline to get help to stop smoking.

Project description:BackgroundParticipant recruitment is an ongoing challenge in health research. Recruitment may be especially difficult for studies of access to health care because, even among those who are in care, people using services least often also may be hardest to contact and recruit. Opt-out recruitment methods (in which potential participants are given the opportunity to decline further contact about the study (opt out) following an initial mailing, and are then contacted directly if they have not opted out within a specified period) can be used for such studies. However, there is a dearth of literature on the effort needed for effective opt-out recruitment.MethodsIn this paper we describe opt-out recruitment procedures for two studies on access to health care within the U.S. Department of Veterans Affairs. We report resource requirements for recruitment efforts (number of opt-out packets mailed and number of phone calls made). We also compare the characteristics of study participants to potential participants via t-tests, Fisher's exact tests, and chi-squared tests.ResultsRecruitment rates for our two studies were 12 and 21%, respectively. Across multiple study sites, we had to send between 4.3 and 9.2 opt-out packets to recruit one participant. The number of phone calls required to arrive at a final status for each potentially eligible Veteran (i.e. study participation or the termination of recruitment efforts) were 2.9 and 6.1 in the two studies, respectively. Study participants differed as expected from the population of potentially eligible Veterans based on planned oversampling of certain subpopulations. The final samples of participants did not differ statistically from those who were mailed opt-out packets, with one exception: in one of our two studies, participants had higher rates of mental health service use in the past year than did those mailed opt-out packets (64 vs. 47%).ConclusionsOur results emphasize the practicality of using opt-out methods for studies of access to health care. Despite the benefits of these methods, opt-out alone may be insufficient to eliminate non-response bias on key variables. Researchers will need to balance considerations of sample representativeness and feasibility when designing studies investigating access to care.

Project description:IntroductionCompliance with the recommendation that all tuberculosis (TB) patients be tested for human immunodeficiency virus (HIV) has not yet been achieved in Canada or globally.MethodsThe experience of "opt-out" HIV testing of TB patients in the Province of Alberta, Canada is described over a 10-year period, 2003-2012. Testing rates are reported before and after the introduction of the "opt-out" approach. Risk factors for HIV seropositivity are described and demographic, clinical and laboratory characteristics of TB patients who were newly diagnosed versus previously diagnosed with HIV are compared. Genotypic clusters, defined as groups of two or more cases whose isolates of Mycobacterium tuberculosis had identical DNA fingerprints over the 10-year period or within 2 years of one another, were analyzed for their ability to predict HIV co-infection.ResultsHIV testing rates were 26% before and 90% after the introduction of "opt-out" testing. During the "opt-out" testing years those <15 or >64 years of age at diagnosis were less likely to have been tested. In those tested the prevalence of HIV was 5.6%. In the age group 15-64 years, risk factors for HIV were: age (35-64 years), Canadian-born Aboriginal or foreign-born sub-Saharan African origin, and combined respiratory and non-respiratory disease. Compared to TB patients previously known to be HIV positive, TB patients newly discovered to be HIV positive had more advanced HIV disease (lower CD4 counts; higher viral loads) at diagnosis. Large cluster size was associated with Aboriginal ancestry. Cluster size predicted HIV co-infection in Aboriginal peoples when clusters included all cases reported over 10 years but not when clusters included cases reported within 2 years of one another.Conclusion"Opt-out" HIV testing of TB patients is effective and well received. Universal HIV testing of TB patients (>80% of patients tested) has immediate (patients) and longer-term (TB/HIV program planning) benefits.

Project description:Study questionWhat is the effect of default test offers--opt-in, opt-out, and active choice--on the likelihood of acceptance of an HIV test among patients receiving care in an emergency department?MethodsThis was a randomized clinical trial conducted in the emergency department of an urban teaching hospital and regional trauma center. Patients aged 13-64 years were randomized to opt-in, opt-out, and active choice HIV test offers. The primary outcome was HIV test acceptance percentage. The Denver Risk Score was used to categorize patients as being at low, intermediate, or high risk of HIV infection.Study answer and limitations38.0% (611/1607) of patients in the opt-in testing group accepted an HIV test, compared with 51.3% (815/1628) in the active choice arm (difference 13.3%, 95% confidence interval 9.8% to 16.7%) and 65.9% (1031/1565) in the opt-out arm (difference 27.9%, 24.4% to 31.3%). Compared with active choice testing, opt-out testing led to a 14.6 (11.1 to 18.1) percentage point increase in test acceptance. Patients identified as being at intermediate and high risk were more likely to accept testing than were those at low risk in all arms (difference 6.4% (3.4% to 9.3%) for intermediate and 8.3% (3.3% to 13.4%) for high risk). The opt-out effect was significantly smaller among those reporting high risk behaviors, but the active choice effect did not significantly vary by level of reported risk behavior. Patients consented to inclusion in the study after being offered an HIV test, and inclusion varied slightly by treatment assignment. The study took place at a single county hospital in a city that is somewhat unique with respect to HIV testing; although the test acceptance percentages themselves might vary, a different pattern for opt-in versus active choice versus opt-out test schemes would not be expected.What this paper addsActive choice is a distinct test regimen, with test acceptance patterns that may best approximate patients' true preferences. Opt-out regimens can substantially increase HIV testing, and opt-in schemes may reduce testing, compared with active choice testing.Funding, competing interests, data sharingThis study was supported by grant NIA 1RC4AG039078 from the National Institute on Aging. The full dataset is available from the corresponding author. Consent for data sharing was not obtained, but the data are anonymized and risk of identification is low.Trial registration Clinical trials NCT01377857.

Project description:BackgroundScientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample and the quality of the research, but these consequences are not well known.ObjectiveThis review aimed to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes.MethodsA systematic review was performed based on searches in PubMed, Embase, CINAHL, PsycINFO, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and nonconsenters. Statistical pooling was conducted, and a description of the results was provided.ResultsA total of 15 studies were included in this meta-analysis. Of the 15 studies, 13 (87%) implemented an opt-in procedure, 1 (7%) implemented an opt-out procedure, and 1 (7%) implemented both the procedures. The average weighted consent rate was 84% (60,800/72,418 among the studies that used an opt-in procedure and 96.8% (2384/2463) in the single study that used an opt-out procedure. In the single study that described both procedures, the consent rate was 21% in the opt-in group and 95.6% in the opt-out group. Opt-in procedures resulted in more consent bias compared with opt-out procedures. In studies with an opt-in procedure, consenting individuals were more likely to be males, had a higher level of education, higher income, and higher socioeconomic status.ConclusionsConsent rates are generally lower when using an opt-in procedure compared with using an opt-out procedure. Furthermore, in studies with an opt-in procedure, participants are less representative of the study population. However, both the study populations and the way in which opt-in or opt-out procedures were organized varied widely between the studies, which makes it difficult to draw general conclusions regarding the desired balance between patient control over data and learning from health data. The reuse of routinely recorded health data for scientific research purposes may be hampered by administrative burdens and the risk of bias.

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A population-based approach for implementing change from opt-out to opt-in research permissions.

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A population-based approach for implementing change from opt-out to opt-in research permissions.

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