18 Clinical Trials for Various Conditions
The goal of this pilot clinical trial is to learn if providing a clinical decision framework for managing older adults chronic conditions during hospitalization to inpatient clinicians improves clinicians' ability to individualize chronic condition prescribing decisions for hospitalized older adults (65 and older). The main questions it aims to answer are: * Will the clinical decision framework lead to clinicians having greater confidence to individualize discharge prescribing? * Will clinicians using the framework discharge make fewer changes to hospitalized older adults with home diabetes and hypertension medications than they did prior to receiving the framework? * Will older adult patients of participating clinicians will report fewer gaps in understanding of medication changes after the clinician is exposed to the framework? Researchers will compare participating clinician survey responses and prescribing records from before and after an educational session presenting the clinical decision framework. Participants will be asked to * Attend a one-time educational session on the clinical decision framework * Complete 2 electronic surveys, one before and one following the educational session. * Agree for researchers to contact their patients, in order for patients to complete a one-time phone survey about changes made to home medications during hospitalization and quality of communication from the hospital team.
The proposed study is a quality improvement initiative designed to rigorously evaluate new variations of UCLA Health's proton pump inhibitor (PPI) order panels, building on internal quality improvement efforts to optimize prescribing workflows within the Electronic Health Record (EHR). PPIs are notoriously overprescribed, and the study team has identified that the CareConnect default prescription setting of 90 days with three refills (360 pill days) exceed standard guidelines (in most cases, 60 pill days). It is unclear whether this is the most appropriate workflow. Given that deprescribing PPIs carries minimal risk for most patients, this initiative will assess whether modifying defaulted prescription lengths influences prescribing behavior while ensuring physicians retain full decision-making authority. This evaluation of PPI order panel variations is embedded within UCLA's existing EHR system, ensuring that changes are tested pragmatically within routine workflows. The study aims to determine whether small adjustments to the order panel can better align prescribing patterns with clinical best practices while maintaining physician autonomy.
Scale-up of HIV preexposure prophylaxis (PrEP) is a key strategy of the U.S. initiative to end the HIV epidemic, but healthcare providers lack tools to support PrEP discussions and prescribing for patients likely to benefit. This research will evaluate whether integrating automated tools into electronic health records to help providers efficiently and equitably identify potential candidates for PrEP, discuss PrEP, and prescribe PrEP can improve PrEP initiation and persistence in safety-net community health centers. It will achieve this by conducting a stepped-wedge trial of a decision support tool with an embedded HIV prediction model to identify patients likely to benefit from PrEP. The intervention will be delivered to healthcare providers in 16 community health centers within the national OCHIN network.
Clinical decision support (CDS) tools can 'nudge' clinicians to make the best decisions easy. Although required by "meaningful use" regulations, more than 40% of CDS lead to no change and the remaining lead to improvements that are modest at best. This is because CDS tools often ignore contextual factors and present irrelevant information. Although many tools have undergone patient-specific optimization, 'traditional CDS' are rarely clinician-specific. For example, a traditional CDS tool for beta blockers and heart failure with reduced ejection fraction (HFrEF) addresses common prescribing misconceptions by stating asthma is not a contraindication and providing a safe threshold for blood pressure. For clinicians without these misconceptions, these statements are irrelevant and distract from key information. A 'personalized CDS' would evaluate clinician past prescribing patterns to determine whether prescribing misconceptions might exist and then conditionally present information to address those misconceptions. The objective of this research is to create personalized clinician-specific CDS that overcome shortcomings of traditional CDS. The central hypothesis is a personalized CDS that minimizes irrelevant information will lead to a higher rate of prescribing guideline-directed management and therapy (GDMT) for HFrEF compared to a traditional CDS.
The purpose of this study is to determine if an educational patient-centered presentation reduced the amount of opioid pills requested and utilized by patients compared to standard of care group.
The objective of this proposal is to compare clinical outcomes, implementation metrics (i.e., patient reach and clinician adoption), and clinician preferences of two designs (customized vs. commercial) of a clinical decision support (CDS). Beta blocker prescribing for patients with heart failure will be used as a test case. The best practices in CDS design, including the user-centered design will be incorporated into the customized CDS and compared to a commercially-available CDS in the electronic health record using a cluster randomized trial.
The goal of this study is to assess the utility of a data visualization tool for providers' understanding patients' past microbiological culture sensitivities. Providers that are ordering antibiotics for patients with previous culture data in the medical record will be asked to answer questions regarding past sensitivity results. They will be randomized to either using the visualization tool before answering the questions or using the standard medical record tools. They will then be surveyed about their decision-making, knowledge, and the usefulness of the tool.
Statins reduce cardiovascular events and mortality, but only 30% of eligible primary care patients nationally are on statins. Clinical decision support (CDS) interventions in the electronic health record (EHR) can deliver education to providers and increase adherence to guideline recommendations via many potential forms of delivery. Interruptive alerts are an effective form of CDS but disrupt clinician workflow and increase alert fatigue in an age of clinician burnout and frustration with the EHR. Non-interruptive reminders are proposed as an alternative method of delivering CDS; however, they require active pursuit by the provider, and their effectiveness compared to interruptive alerts has not been rigorously studied. The investigators propose a randomized trial comparing the effect of interruptive vs. non-interruptive reminders displayed to clinicians to increase statin prescribing in primary care clinics.
The objective of this study is to evaluate the impact of a clinical decision support (CDS) alert to facilitate the co-prescribing of naloxone, an opioid overdose reversal agent, with high-risk opioid prescriptions. Prescribing naloxone with opioids is a best practice described in the 2022 US Center for Disease Control and Prevention (CDC) guidelines on opioid prescribing. The CDS can improve quality of care delivered by improving compliance with the guideline defined best practices. The project will compare CDS alert facilitated co-prescribing of naloxone with high-risk opioid prescriptions vs usual care to evaluate the effectiveness of the CDS alert for improving naloxone prescribing. The patients are not assigned to an intervention and will be receiving any changes in care as part of their routine medical care, rather than a specific intervention that is distinct from their usual medical care. The researchers hypothesize that the CDS alert will be acceptable to providers while increasing naloxone co-prescribing which will reduce the number of opioid overdoses in subsequent 6 months.
This study aims to improve care and reduce unnecessary antibiotic prescribing for children with ear infections. The study will compare the effectiveness of a "gold standard" to a hybrid intervention combined with this gold standard, in order to identify steps to increase parent satisfaction for child ear infection care. The "gold standard" approach is a Health System Level Intervention. On its own, it involves clinician education, tools in electronic medical records, and audit and feedback reports for clinician prescribing habits. The hybrid intervention includes the elements of the health systems level intervention in addition to a Shared Decision-Making component, which allows for both an increase in the role parents play in their child's care, as well as clinician education for how to use this method. The goals of this work are to increase parent satisfaction, reduce antibiotics taken for childhood ear infections, align medical care with the current national guidelines, and evaluate differences in the two intervention groups. Both groups will be evaluated for implementation outcomes to improve dissemination and scalability for future use of these models in antibiotic prescribing for children with ear infections. This study will recruit a diverse group of patients and clinicians to complete surveys, parents to participate in focus groups, and clinicians and administrators to be interviewed in order to meet study aims and receive sufficient feedback on the interventions performed. There are two hypotheses for this research: 1. The Hybrid Intervention will have higher parent satisfaction and reduced antibiotic use compared to the Health-System Level Intervention and 2. The Hybrid Intervention will be more challenging to implement than the Health-System Level Intervention, but will be preferred by parents, clinicians, and administrators.
This will be a randomized controlled clinical trial in patients who have undergone primary unilateral total knee arthroplasty at Brigham and Women's Faulkner Hospital, Brigham and Women's Hospital and University of Chicago Medical Center. Study subjects will receive either a shared decision aid (SDA) about pain management or standard of care at the time of discharge. The impact of the SDA on the number of leftover opioid pills on postoperative day 30 and average NRS pain score on postoperative day 7 will be assessed.
This study evaluates the effects of a novel integrated clinical prediction tool on antibiotic prescription patterns of nurses for acute respiratory infections (ARIs). The intervention is an EHR-integrated risk calculator and order set to help guide appropriate, evidence-based antibiotic prescriptions for patients presenting with ARI symptoms.
The purpose of this study is to test whether physicians change their use of non-recommended tests, procedures, or medications more in response to evidence based-guidelines, price information, or an individual patient's story.
The study will measure the effect of basic clinical decision support on medical errors and adverse drug events in the ambulatory setting.
The goal of this clinical trial is to learn if electronic health record (EHR) nudges (changes to the EHR that do not restrict freedom of choice or alter incentives) can reduce Z-drug prescribing in primary care clinics for patients with insomnia. The main questions it aims to answer are: 1. Can Z-drug prescribing be reduced by setting the dispense quantity default of new Z-drug orders in the EHR to 10 pills with 0 refills? 2. Can Z-drug prescribing be reduced by an EHR alert that suggests clinicians remove a Z-drug and/or add an evidence-based behavioral treatment for insomnia, followed by a request to justify their reasoning if the suggestion is not followed? 3. Does combining these two nudges reduce Z-drug prescribing? Researchers will compare each nudge individually and in combination to an guideline education control group to see if each nudge (separately and in combination) can reduce Z-drug prescribing. Clinician-participants will: 1. Complete an introductory educational module about treating insomnia and relevant EHR changes. 2. Complete their routine patient visits. 3. Either experience EHR changes when prescribing Z-drugs, including a Z-drug dispense quantity default of 10 pills for new orders, a prompt to remove or justify Z-drug orders, both, or neither.
One mechanism to reduce potentially inappropriate medications is through deprescribing, a deimplementation-based approach to thoughtfully discontinue a medication a patient is currently prescribed. Many interventions to overcome deprescribing barriers target the provider, who is already overburdened. Although some believe providers have primary responsibility for deprescribing, patient-initiated discontinuation discussions can effectively facilitate deprescribing. In a single-site pilot study, the investigators successfully engaged VA Primary Care patients to facilitate deprescribing of select potentially inappropriate medications. The investigators now propose a multisite randomized controlled trial of engaging Veterans who may be deprescribing candidates. By study end, the investigators will have established the effectiveness of an innovative, low-tech, patient-focused intervention to promote deprescribing, thereby directly improving quality, safety, and value of VA care while also setting the stage for generalization of this approach to other potentially inappropriate medications.
Older patients using many prescription drugs (hyperpolypharmacy) may be at increased risk of adverse drug effects. This randomized controlled trial tested the effectiveness and safety of a quality intervention intended to reduce hyperpolypharmacy. The study was set at Kaiser Permanente Northern California, an integrated health system with multiple pre-existing deprescribing workflows. Eligible patients were aged ≥76 years using ≥10 prescription medications. The intervention included physician-pharmacist collaborative drug therapy management, standard-of-care practice recommendations, shared decision-making, and deprescribing protocols administered by telephone over multiple cycles for a maximum of 180 days after allocation. A priori primary effectiveness endpoints included change in the number of medications and in the prevalence of geriatric syndrome from 181-365 days after allocation. Second endpoints included utilization and adverse drug withdrawal effects. Information was obtained from the electronic health record.
This pragmatic trial examines the uptake and effects of primary care clinician commitments to follow 3 Choosing Wisely® recommendations. The investigators hypothesize that pre-encounter invitations to clinicians to commit to the recommendations will decrease ordering of: (1) imaging tests for low back pain, (2) antibiotics for acute sinusitis, and (3) imaging tests for headaches. The study is a mixed-methods, stepped wedge cluster randomized trial in which the intervention will be sequentially introduced to 6 clinics in southeastern Michigan in a randomly assigned order.