14 Clinical Trials for Various Conditions
The primary objective is to assess the effectiveness of training a clinician to be a 'value champion' within clinical settings to decrease the use of three classes of potentially inappropriate prescription medications (PIMs) among people living with dementia (PLWD). Secondary objectives include determining if the intervention is associated with a reduction in emergency department (ED) visits or hospitalizations due to a fall, and examining five implementation outcomes: appropriateness, feasibility, fidelity, penetration, and equity. This study is a pragmatic cluster-randomized trial to test the effectiveness of a primary care clinician value champion for de-implementing PIMs among patients 65 years of age and older with a diagnosis of dementia. Medicare Part D pharmacy claims data will be analyzed at the end of the 12-month intervention for the primary outcome, the medication possession rates (MPR) for three groups of potentially inappropriate medications: antipsychotic medications, benzodiazepines, and hypoglycemic medications (sulfonylureas and insulin). In a similar fashion, a hospital admission, or an emergency department visit for a fall will be assessed at the end of the intervention using Medicare claims data. Finally, the five implementation outcomes will be evaluated at the end of the intervention from notes entered by the value champions in project workbooks. Primary care clinics within each of the two participating ACOs will be randomized to either the intervention or control arms of the study. Prior to random assignment, the investigators will stratify practices based on high versus low historic prescribing rates. A primary care clinician from each clinic selected for the trial in the intervention arm (n=30 across the two ACOs) will be recruited as a clinician value champion for each intervention clinic. The clinician value champion will participate in twice monthly value champion web-based training sessions for six months and then launch a 12-month initiative within the clinician value champions' clinics to reduce PIM prescribing among PLWD. Study outcomes will be assessed 12 months after the clinician value champions launch the initiative. The hypothesis is that for each medication class, the intervention will produce clinically relevant decreases in mean possession rates of 10% of a standard deviation in patients seen in intervention clinics compared to those who are seen in control group clinics.
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.
This study tests the effectiveness of two email-based behavioral nudges, one based on peer behavior and one based on best practice guidelines, in reducing excessive opioid prescriptions after surgery. It will be conducted in three surgical specialties (general surgery, orthopedic surgery, and obstetric/gynecological surgery) at 19 hospitals within one healthcare system. These specialties will each be randomized to a control group or one of two nudge groups. Each month for one year, surgeons in the nudge groups will receive emails comparing their opioid prescribing either to their peers' prescribing or to prescribing guidelines. Both types of email-based nudges are expected to reduce opioid prescribing after surgery.
This research is being conducted to learn which implementation strategy of EQUIPPED is most effective to improve prescribing practices of ED providers toward older Veterans and determine the factors influencing implementation of this program to reduce the prescribing of PIMs to older adults upon discharge from the ED. The study has three research aims. The procedures for these research aims are described below: * Aim 1 - Examining the Impact of Passive Provider Feedback vs. Active Provider Feedback Through a Randomized Trial * Aim 2 - Determination of Factors Affecting Organizational Adoption of EQUIPPED * Aim 3 - Micro-Costing the Active and Passive Feedback Versions of the EQUIPPED Intervention
Aim 1 of the study is to identify the elements of a deprescribing intervention that address contextual factors specific to dialysis. Aim 2 of the study, described in this record, is to determine the feasibility of a deprescribing intervention tailored for older dialysis patients. Older adults receiving dialysis are often prescribed multiple medications. Some of these medications are used to treat symptoms, but they also can increase the chance of significant health problems. The purpose of this study is to identify if it is feasible to reduce the use of medications that have been identified as causing an increased risk for health problems.
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.
The purpose of the study is to determine if physician education coupled with audit and feedback of antibiotic prescribing can improve antibiotic prescribing by primary care clinicians.
Bacteria resistant to antibiotic therapy are a major public health problem. The evolution of multi-drug resistant pathogens may be encouraged by provider prescribing behavior. Inappropriate use of antibiotics for nonbacterial infections and overuse of broad spectrum antibiotics can lead to the development of resistant strains. Though providers are adequately trained to know when antibiotics are and are not comparatively effective, this has not been sufficient to affect critical provider practices. The intent of this study is to apply behavioral economic theory to reduce the rate of antibiotic prescriptions for acute respiratory diagnoses for which guidelines do not call for antibiotics. Specifically targeted are infections that are likely to be viral. The objective of this study is to improve provider decisions around treatment of acute respiratory infections. The participants are practicing attending physicians or advanced practice nurses (i.e. providers) at participating clinics who see acute respiratory infection patients. A maximum of 550 participants will be recruited for this study. Providers consenting to participate will fill out a baseline questionnaire online. Subsequent to baseline data collection and enrollment, participating clinic sites will be randomized to the study arms, as described below. There will be a control arm, with clinic sites randomized in a multifactorial design to up to three interventions that leverage the electronic medical record: Order Sets that are triggered by EHR workflow containing exclusively guideline concordant choices (SA, for Suggested Alternatives); Accountable Justification (AJ) triggered by discordant prescriptions that populate the note with provider's rationale for guideline exceptions ; and performance feedback that benchmarks providers' own performance to that of their peers (PC, for Peer Comparison). The outcomes of interest are antibiotic prescribing patterns, including prescribing rates and changes in prescribing rates over time. The intervention period will be over one year, with a one-year follow up period to measure persistence of the effect after EHR features are returned to the original state and providers no longer receive email alerts.
Bacteria resistant to antibiotic therapy are a major public health problem. The evolution of multi-drug resistant pathogens may be encouraged by provider prescribing behavior. Inappropriate use of antibiotics for nonbacterial infections and overuse of broad spectrum antibiotics can lead to the development of resistant strains. Though providers are adequately trained to know when antibiotics are and are not comparatively effective, this has not been sufficient to affect critical provider practices. The intent of this study is to apply behavioral economic theory to reduce the rate of antibiotic prescriptions for acute respiratory diagnoses for which guidelines do not call for antibiotics. Specifically targeted are infections that are likely to be viral. The objective of this study is to improve provider decisions around treatment of acute respiratory infections. The participants are practicing attending physicians or advanced practice nurses (i.e. providers) at participating clinics who see acute respiratory infection patients. A maximum of 550 participants will be recruited for this study. Providers consenting to participate will fill out a baseline questionnaire online. Subsequent to baseline data collection and enrollment, participating clinic sites will be randomized to the study arms, as described below. There will be a control arm, with clinic sites randomized in a multifactorial design to up to three interventions that leverage the electronic medical record: Order Sets that are triggered by electronic health record (EHR) workflow containing exclusively guideline concordant choices (SA, for Suggested Alternatives); Accountable Justifications triggered by discordant prescriptions that populate the note with provider's rationale for guideline exceptions (AJ); and performance feedback that benchmarks providers' own performance to that of their peers (PC, for Peer Comparisons). The outcomes of interest are antibiotic prescribing patterns, including prescribing rates and changes in prescribing rates over time. The intervention period will be over one year, with a one-year follow up period to measure persistence of the effect after EHR features are returned to the original state and providers no longer receive email alerts.
This will be an eight-week, prospective, placebo-controlled, randomized trial to evaluate a patient-centered team (pharmacist-physician) intervention to improve medication appropriateness and reduce the use of inappropriate anticholinergic medications in elderly patients enrolled in the Sanders-Brown Alzheimer's Disease Center (ADC) cohort.
Hypotheses and Specific Aims: The continued emergence of antibiotic-resistance in the outpatient setting underlines the need to responsibly manage antimicrobial prescribing. It is in this context that we seek to test an effective strategy for reducing the inappropriate use of antibiotics in primary care office practices. Our overall objective is to identify an effective and efficient strategy for decreasing the contribution of primary care clinicians to the emergence of antimicrobial-resistant bacteria in the community and to disseminate widely those strategies found to be effective and sustainable. We hypothesize that implementation of a clinician decision support system, with an active education component, will reduce the inappropriate use of antibiotics in primary care office practices. Our hypothesis is based on the premise that most inappropriate prescribing is the result of multiple factors that include difficulty in distinguishing a benign, self-limited viral infection from a more serious bacterial infection; overdiagnosis of a bacterial infection in cases where there is clinical uncertainty as to the true nature of the illness; and constraints on the time available for clinicians to explain to patients the nature of the illness and the reasons an antibiotic is not indicated. The focus of this proposal will be to compare the impact of clinical decision support and active education to no intervention for enhancing the appropriate use of antimicrobials for common outpatient infections. In this randomized control trial, primary care providers participating in the intervention arm will receive active education coupled with the implementation of a clinical decision support tool, while providers in the control arm will have no intervention. At the end of the study, providers in the control arm will receive a thorough analysis of their antibiotic prescribing patterns and suggested opportunities for improvement, as well as access to the intervention tools once the study has ended. Our interdisciplinary team will integrate novel methods in implementation science with clinical and laboratory expertise in infectious diseases, antimicrobial stewardship, primary care, information technology, performance improvement, health services research, and biostatistics. The Specific Aims are constructed to validate our hypothesis in the primary care setting by demonstrating two results of our intervention strategy: 1. Reduced use of antibiotics to treat conditions for which those drugs are known not to be effective 2. Decreased prescribing of broad-spectrum antibiotics to treat common bacterial infections. The degree of impact in terms of prescriptions per 100 visits for each targeted outpatient infection will be compared with active education and clinical decision support versus no intervention. The study will be able to measure the value of clinical decision support with active education that will inform future efforts in disseminating outpatient antibiotic stewardship interventions.
Introduction: The Beers list identifies medications that should be avoided in persons 65 years or older because they are ineffective, pose an unnecessarily high risk, or a safer alternative is available. In a recent study, we found a high rate of prescribing of Beers list medications to hospitalized patients. At Baystate, 41% of medical patients received at least one Beers list drug classified as "high severity," meaning it carried a high risk for an adverse drug reaction, while 5% received 3 or more. Some Beers drugs have been associated with delirium and falls. When compared to Baystate patients who did not receive a high severity medication, those who did had an increased risk of mortality (7.8% vs. 5.2%), longer length of stay (5.5 days vs. 3.9 days) and higher costs ($11,240 vs. 6243). Specific Aims: 1. Quantify the impact of synchronous electronic alerts on physician prescribing of high-severity Beers' list drugs to hospitalized patients over the age of 65 years. 2. Compare physician reactions to each drug-specific alert Project Description: We will develop a series of clinical alerts in CIS, Baystate's computerized provider order entry system, to reduce the use of potentially inappropriate medications among hospitalized elders. We will randomize providers to electronic alerts or usual care. Whenever a provider randomized to alerts attempts to place an order for a high-risk medication on the Beers list and the intended recipient is over 65 years of age, a synchronous alert (i.e. a "pop-up") will inform the physician about the risks associated with the medication and will propose safer alternatives. We will collect data on physician ordering and patient outcomes comparing the number of Beers list prescriptions from providers receiving electronic alerts to those not receiving alerts. Our anticipated outcome is a decrease in inappropriate prescribing during the period when the electronic alerts are activated. Other potential outcomes include decrease in length of stay and a decrease in falls.
This study will assess whether a modification in the default dose and frequency (the first option a provider sees) during electronic prescribing of a high-risk drug can impact prescribing behavior and subsequent changes in average dose for the targeted high-risk drug, when prescribed to a hospitalized patient aged ≥65 years. In this cluster randomized crossover (CRXO) trial we will randomize a non-intrusive "nudge" intervention, which involves modifying the default dose for high-risk drugs when prescribed electronically to hospitalized patients aged ≥65 years. The CRXO trial involves 10 sites in an urban health system: five sites will start the trial under the intervention/control during a first time period (T1) after which they switch intervention/control status (T2). The primary outcome is prescription rate of a lower default dose (i.e. the geriatric standard) for 8 high-risk drugs. This study will inform the effectiveness of EHR-based "nudge" interventions to reduce inappropriate prescribing of high-risk drugs for elderly patients. Analyses ongoing, expected to finalize spring 2023