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Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

ABSTRACT: There is an urgent need for strategies to address the US epidemic of prescription opioid, heroin and fentanyl-related overdoses, misuse, addiction, and diversion. Evidence-based treatment such as medications for opioid use disorder (MOUD) are available but lack numbers of providers offering these services to meet the demands. Availability of electronic health record (EHR) systems has greatly increased and led to innovative quality improvement initiatives but this has not yet been optimized to address the opioid epidemic or to treat opioid use disorder (OUD). This report from a clinical decision support (CDS) working group convened by the NIDA Center for the Clinical Trials Network aims to converge electronic technology in the EHR with the urgent need to improve screening, identification, and treatment of OUD in primary care settings through the development of a CDS algorithm that could be implemented as a tool in the EHR. This aim is consistent with federal, state and local government and private sector efforts to improve access and quality of MOUD treatment for OUD, existing clinical quality and HEDIS measures for OUD or drug and alcohol use disorders, and with a recent draft grade B recommendation from the US Preventative Services Task Force (USPSTF) for screening for illicit drug use in adults when appropriate diagnosis, treatment and care services can be offered or referred. Through a face-to-face expert panel meeting and multiple follow-up conference calls, the working group drafted CDS algorithms for clinical care felt to be essential for screening, diagnosis, and management of OUD in primary care. The CDS algorithm was reviewed by addiction specialists and primary care providers and revised based on their input. A clinical decision support tool for OUD screening, assessment, and treatment within primary care systems may help improve healthcare delivery to help address the current epidemic of opioid misuse and overdose that has outpaced the capacity of specialized treatment settings. A semi-structured outline of clinical decision support for OUD was developed to facilitate implementation within the EHR. Further work for adaptation at specific sites and for testing is needed.

SUBMITTER: Bart GB

PROVIDER: S-EPMC6966783 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

Bart Gavin B GB Saxon Andrew A Fiellin David A DA McNeely Jennifer J Muench John P JP Shanahan Christopher W CW Huntley Kristen K Gore-Langton Robert E RE

Addiction science & clinical practice 20200116 1

There is an urgent need for strategies to address the US epidemic of prescription opioid, heroin and fentanyl-related overdoses, misuse, addiction, and diversion. Evidence-based treatment such as medications for opioid use disorder (MOUD) are available but lack numbers of providers offering these services to meet the demands. Availability of electronic health record (EHR) systems has greatly increased and led to innovative quality improvement initiatives but this has not yet been optimized to ad ...[more]

PMID: 31948487

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Project description:IntroductionEmergency departments (ED) are incorporating Peer Support Specialists (PSSs) to help with patient care for substance use disorders (SUDs). Despite rapid growth in this area, little is published regarding workflow, expectations of the peer role, and core components of the PSS intervention. This study describes these elements in a national sample of ED-based peer support intervention programs.MethodsA survey was conducted to assess PSS site characteristics as part of site selection process for a National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) evaluating PSS effectiveness, Surveys were distributed to clinical sites affiliated with the 16 CTN nodes. Surveys were completed by a representative(s) of the site and collected data on the PSS role in the ED including details regarding funding and certification, services rendered, role in medications for opioid use disorder (MOUD) and naloxone distribution, and factors impacting implementation and maintenance of ED PSS programs. Quantitative data was summarized with descriptive statistics. Free-text fields were analyzed using qualitative content analysis.ResultsA total of 11 surveys were completed, collected from 9 different states. ED PSS funding was from grants (55%), hospital funds (46%), peer recovery organizations (27%) or other (18%). Funding was anticipated to continue for a mean of 16 months (range 12 to 36 months). The majority of programs provided "general recovery support (81%) Screening, Brief Intervention, and Referral to Treatment (SBIRT) services (55%), and assisted with naloxone distribution to ED patients (64%). A minority assisted with ED-initiated buprenorphine (EDIB) programs (27%). Most (91%) provided services to patients after they were discharged from the ED. Barriers to implementation included lack of outpatient referral sources, barriers to initiating MOUD, stigma at the clinician and system level, and lack of ongoing PSS availability due to short-term grant funding.ConclusionsThe majority of ED-based PSSs were funded through time-limited grants, and short-term grant funding was identified as a barrier for ED PSS programs. There was consistency among sites in the involvement of PSSs in facilitation of transitions of SUD care, coordination of follow-up after ED discharge, and PSS involvement in naloxone distribution.

Project description:BackgroundClinical decision support (CDS) is a valuable feature of electronic health records (EHRs) designed to improve quality and safety. However, due to the complexities of system design and inconsistent results, CDS tools may inadvertently increase alert fatigue and contribute to physician burnout. A/B testing, or rapid-cycle randomized tests, is a useful method that can be applied to the EHR in order to rapidly understand and iteratively improve design choices embedded within CDS tools.ObjectiveThis paper describes how rapid randomized controlled trials (RCTs) embedded within EHRs can be used to quickly ascertain the superiority of potential CDS design changes to improve their usability, reduce alert fatigue, and promote quality of care.MethodsA multistep process combining tools from user-centered design, A/B testing, and implementation science was used to understand, ideate, prototype, test, analyze, and improve each candidate CDS. CDS engagement metrics (alert views, acceptance rates) were used to evaluate which CDS version is superior.ResultsTo demonstrate the impact of the process, 2 experiments are highlighted. First, after multiple rounds of usability testing, a revised CDS influenza alert was tested against usual care CDS in a rapid (~6 weeks) RCT. The new alert text resulted in minimal impact on reducing firings per patients per day, but this failure triggered another round of review that identified key technical improvements (ie, removal of dismissal button and firings in procedural areas) that led to a dramatic decrease in firings per patient per day (23.1 to 7.3). In the second experiment, the process was used to test 3 versions (financial, quality, regulatory) of text supporting tobacco cessation alerts as well as 3 supporting images. Based on 3 rounds of RCTs, there was no significant difference in acceptance rates based on the framing of the messages or addition of images.ConclusionsThese experiments support the potential for this new process to rapidly develop, deploy, and rigorously evaluate CDS within an EHR. We also identified important considerations in applying these methods. This approach may be an important tool for improving the impact of and experience with CDS.Trial registrationFlu alert trial: ClinicalTrials.gov NCT03415425; https://clinicaltrials.gov/ct2/show/NCT03415425. Tobacco alert trial: ClinicalTrials.gov NCT03714191; https://clinicaltrials.gov/ct2/show/NCT03714191.

Project description:Cancer patients often do not make informed decisions regarding clinical trial participation. This study evaluated whether a web-based decision aid (DA) could support trial decisions compared with our cancer center's website.Adults diagnosed with cancer in the past 6 months who had not previously participated in a cancer clinical trial were eligible. Participants were randomized to view the DA or our cancer center's website (enhanced usual care [UC]). Controlling for whether participants had heard of cancer clinical trials and educational attainment, multivariable linear regression examined group on knowledge, self-efficacy for finding trial information, decisional conflict (values clarity and uncertainty), intent to participate, decision readiness, and trial perceptions.Two hundred patients (86%) consented between May 2014 and April 2015. One hundred were randomized to each group. Surveys were completed by 87 in the DA group and 90 in the UC group. DA group participants reported clearer values regarding trial participation than UC group participants reported (least squares [LS] mean = 15.8 vs. 32, p < .0001) and less uncertainty (LS mean = 24.3 vs. 36.4, p = .025). The DA group had higher objective knowledge than the UC group's (LS mean = 69.8 vs. 55.8, p < .0001). There were no differences between groups in intent to participate.Improvements on key decision outcomes including knowledge, self-efficacy, certainty about choice, and values clarity among participants who viewed the DA suggest web-based DAs can support informed decisions about trial participation among cancer patients facing this preference-sensitive choice. Although better informing patients before trial participation could improve retention, more work is needed to examine DA impact on enrollment and retention.This paper describes evidence regarding a decision tool to support patients' decisions about trial participation. By improving knowledge, helping patients clarify preferences for participation, and facilitating conversations about trials, decision aids could lead to decisions about participation that better match patients' preferences, promoting patient-centered care and the ethical conduct of clinical research.

Project description:ObjectiveTo report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets.DesignSystematic review and meta-analysis.Data sourcesMedline up to August 2019.Eligibility criteria for selecting studies and methodsRandomised or quasi-randomised controlled trials reporting absolute improvements in the percentage of patients receiving care recommended by clinical decision support systems. Multilevel meta-analysis accounted for within study clustering. Meta-regression was used to assess the degree to which the features of clinical decision support systems and study characteristics reduced heterogeneity in effect sizes. Where reported, clinical endpoints were also captured.ResultsIn 108 studies (94 randomised, 14 quasi-randomised), reporting 122 trials that provided analysable data from 1 203 053 patients and 10 790 providers, clinical decision support systems increased the proportion of patients receiving desired care by 5.8% (95% confidence interval 4.0% to 7.6%). This pooled effect exhibited substantial heterogeneity (I2=76%), with the top quartile of reported improvements ranging from 10% to 62%. In 30 trials reporting clinical endpoints, clinical decision support systems increased the proportion of patients achieving guideline based targets (eg, blood pressure or lipid control) by a median of 0.3% (interquartile range -0.7% to 1.9%). Two study characteristics (low baseline adherence and paediatric settings) were associated with significantly larger effects. Inclusion of these covariates in the multivariable meta-regression, however, did not reduce heterogeneity.ConclusionsMost interventions with clinical decision support systems appear to achieve small to moderate improvements in targeted processes of care, a finding confirmed by the small changes in clinical endpoints found in studies that reported them. A minority of studies achieved substantial increases in the delivery of recommended care, but predictors of these more meaningful improvements remain undefined.

Project description:Computerised clinical decision support (CDS) can potentially better inform decisions, and it can help with the management of information overload. It is perceived to be a key component of a learning health care system. Despite its increasing implementation worldwide, it remains uncertain why the effect of CDS varies and which factors make CDS more effective.To examine which factors make CDS strategies more effective on a number of outcomes, including adherence to recommended practice, patient outcome measures, economic measures, provider or patient satisfaction, and medical decision quality.We identified randomised controlled trials, non-randomised trials, and controlled before-and-after studies that directly compared CDS implementation with a given factor to CDS without that factor by searching CENTRAL, MEDLINE, EMBASE, and CINAHL and checking reference lists of relevant studies. We considered CDS with any objective for any condition in any healthcare setting. We included CDS interventions that were either displayed on screen or provided on paper and that were directed at healthcare professionals or targeted at both professionals and patients. The reviewers screened the potentially relevant studies in duplicate. They extracted data and assessed risk of bias in independent pairs or individually followed by a double check by another reviewer. We summarised results using medians and interquartile ranges and rated our certainty in the evidence using the GRADE system.We identified 66 head-to-head trials that we synthesised across 14 comparisons of CDS intervention factors. Providing CDS automatically versus on demand led to large improvements in adherence. Displaying CDS on-screen versus on paper led to moderate improvements and making CDS more versus less patient-specific improved adherence modestly. When CDS interventions were combined with professional-oriented strategies, combined with patient-oriented strategies, or combined with staff-oriented strategies, then adherence improved slightly. Providing CDS to patients slightly increased adherence versus CDS aimed at the healthcare provider only. Making CDS advice more explicit and requiring users to respond to the advice made little or no difference. The CDS intervention factors made little or no difference to patient outcomes. The results for economic outcomes and satisfaction outcomes were sparse.Multiple factors may affect the success of CDS interventions. CDS may be more effective when the advice is provided automatically and displayed on-screen and when the suggestions are more patient-specific. CDS interventions combined with other strategies probably also improves adherence. Providing CDS directly to patients may also positively affect adherence. The certainty of the evidence was low to moderate for all factors.PROSPERO, CRD42016033738.

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Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

Publications

Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

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