58 Clinical Trials for Various Conditions
The purpose of this research study is to measure the effect on of a large language model interface on the usability, attitudes, and provider trust when using a machine learning algorithm-based clinical decision support system in the setting of bleeding from the upper gastrointestinal tract (upper GIB). Specifically, the investigators are looking to assess the optimal implementation of such machine learning algorithms in simulation scenarios to best engender trust and improve usability. Participants will be randomized to either machine learning algorithm alone or algorithm with a large language model interface and exposed to simulation cases of upper GIB.
The goal of this study is to evaluate the impact of a clinical decision support system (CDSS) in children receiving mechanical ventilation (MV) after surgery for congenital heart disease (CHD). The main question it aims to answer is: -What is the impact of a CDSS designed to facilitate weaning and discontinuation of MV on the duration of MV in post-operative congenital cardiac surgery patients? Participants will be identified as eligible to initiate weaning from mechanical ventilation. Providers will decide whether or not to initiate weaning based on recommendations provided by the CDSS. Researchers will compare patients exposed to the CDSS with a historical cohort to see if the CDSS facilitated a decrease in MV duration.
Chronic kidney disease (CKD) is a highly prevalent, poorly recognized and undertreated and increases risk of atherosclerotic cardiovascular disease (ASCVD) and mortality. ASCVD risk interventions such as statin medications are not effective if initiated when kidney disease is advanced. Thus, early recognition of CKD is important for effective ASCVD risk management. Patient centered medical homes (PCMH)s (clinics which include nurse educators, dietitians, pharmacists and social workers) were designed to address gaps in care for complex chronic diseases such as CKD by increasing availability of ancillary services for patients. However, PCMH models have not been shown to improve the recognition and treatment of CKD and its associated ASCVD risk. The E DYNAMIC CDS retrieves real-time patient data from the electronic health record (EHR) every 24 hours to help primary care providers (PCP) identify patients with CKD and assess ASCVD risk and provide appropriate treatment. E-DYNAMIC also delegates CKD care with utilization of an opt-out approach for nurse education and dietitian referral. The overall objective of this pragmatic trial is to examine whether the E-DYNAMIC CDS increases PCP recognition of CKD and use of ASCVD risk management interventions when implemented within a PCMH. This pragmatic trial will be conducted within the Hines VA Hospital and community-based outpatient clinics designed as PCMH called teamlets. Teamlets include several PCPs, a nurse educator, a dietitian, a pharmacist, and a social worker. We will randomize 51 teamlets to the E-DYNAMIC CDS or to standard care. This pragmatic trial will address the following aims: 1) Determine the difference in PCP diagnosis of CKD stage 3-5 non-dialysis dependent CKD by allocation to the E-DYNAMIC CDS; 2) Determine the difference in PCPs ASCVD risk management of patients with stage 3-5 non-dialysis dependent CKD by teamlet allocation to the E-DYNAMIC CDS; 3) Determine the difference in patient use of ASCVD risk interventions and patient activation measures by their teamlet allocation to the E-DYNAMIC CDS. The primary outcomes of the pragmatic trial will be ascertained from the EHR. The E-DYNAMIC CDS tool may be transferred into other health systems that utilize an EHR and improve the diagnosis and management of CKD.
The investigators plan to further develop a prototype, evidence-based, electronic clinical decision support system (CDSS) for pneumonia care (ePneumonia) with interoperability across Electronic Health Records in order to improve clinical outcomes and reduce healthcare resource utilization. The specific aims of this study are to evaluate the usability of ePneumonia adapted for Cerner and its impact on clinical, patient-centered and healthcare resource utilization outcomes in a stepped-wedge implementation study in 16 hospital emergency departments (EDs) across the Intermountain Healthcare integrated health system.
The investigators propose to study the feasibility, acceptability, usability and outcomes of a new clinical decision support system for clinicians of opioid therapy in the context of specialist palliative care for serious chronic illness. The system provides clinicians with patient-specific genetic information on opioid responsiveness and multi-drug interactions. This clinical decision support system should improve the clinician's ability to identify the optimal pain medication and dosage, and reduce risks associated with multi-drug treatment. Investigators will conduct clinician survey's to collection information about the clinical decision support system. Investigators will also conduct patient related questionnaires to determine any benefits or improvements in quality of life and symptom management from the clinical decision support system.
The investigators propose a three-arm, pragmatic, cluster-randomized clinical trial based in primary care. Participating Primary Care Providers (PCPs) will be randomized to usual care or one of two intervention arms. The first intervention will evaluate the efficacy of an automated CDSS that utilizes the electronic health record (EHR) to facilitate triple marker test ordering, guideline implementation and BP management, compared with usual care, among patients with previous documentation of eGFRcreat \<60 ml/min/1.73m2. The second intervention goes a step further, and will evaluate whether a CDSS plus a follow-up telephone call from a pharmacist (CDSS PLUS) can improve BP management and patient CKD and NSAID toxicity knowledge among the patients with CKD, compared with CDSS alone. The primary clinical outcome is BP level, with secondary outcomes related to processes of care and patient knowledge.
The purpose of this study is to learn what cancer patients think about IBM Watson Oncology. IBM Watson Oncology is a computer program designed to help inform oncologists about the best chemotherapy choices for their patients. The investigators will conduct focus groups with cancer patients who have received chemotherapy treatment at MSK in order to understand cancer patients' thoughts about IBM Watson Oncology.
The goal of this clinical trial is to study systemic inflammatory response syndrome (SIRS) electronic health record (EHR) alerts for sepsis in the inpatient setting. The main question it aims to answer is: do nurse alerts, prescribing clinician alerts, or both nurse and prescribing clinician alerts improve time to sepsis treatment for patients in the inpatient setting? Nurses and prescribing clinicians will receive SIRS alerts based on the group to which the patient is randomly assigned. Researchers will compare four groups: no alerts, nurse alerts only, prescribing clinician alerts only, or both nurse and prescribing clinician alerts.
The goal of this clinical trial is to study systemic inflammatory response syndrome (SIRS) electronic health record (EHR) alerts for sepsis in the emergency department (ED). The main question it aims to answer is: do nurse alerts, prescribing clinician alerts, or both nurse and prescribing clinician alerts improve time to sepsis treatment for patients in the ED? Nurses and prescribing clinicians will receive SIRS alerts based on the group to which the patient is randomly assigned. Researchers will compare four groups: no alerts, nurse alerts only, prescribing clinician alerts only, or both nurse and prescribing clinician alerts.
The goal of this study is to assess the effect of an electronic health record (EHR) clinical decision support tool, also known as a best practice alert (BPA), on healthcare provider recommendations for low dose aspirin use in a high-risk pregnant patient population. The investigators hypothesize that the implementation of the EHR BPA tool will increase the healthcare provider's recommendation for low dose aspirin compared to current standard care.
The purpose of this study is to evaluate the impact of integrating ambulatory computerized physician order entry (ACPOE) and advanced clinical decision support systems (CDSS) on safety and quality domains in the ambulatory setting, including: a) medication monitoring, b) preventive care and chronic disease management, and c) test result follow-up. In addition we will evaluate the impact on organizational efficiency, physician workflow and satisfaction, and perform a cost-benefit analysis. We hypothesize that the value of ACPOE integrated with advanced CSDSS lies in improved medication safety and guideline compliance, but also improved efficiencies for the provider and the health-care system.
The goal of this clinical trial is to learn if adding patients' goals and concerns to measurement-based collaborative care can tailor care and provide a more holistic view of treatment, thereby improving engagement in care among adult patients receiving collaborative care. The main questions it aims to answer are: * Does using a clinical decision support system (which includes an enhanced pre-visit questionnaire and patient-level dashboard) improve patient engagement in the collaborative care model? * Does using a clinical decision support system improve patient and clinician satisfaction with care? Researchers will compare the enhanced collaborative care with traditional collaborative care. Patient participants will complete pre-visit questionnaires before their collaborative care appointments. Responses will be viewed by the clinician and/or patient in a visual dashboard inside the electronic health record.
While blood clots after major cancer surgery are common and harmful to patients, the medications to decrease blood clot risk are seldom used after patients leave the hospital despite the recommendation of multiple professional medical societies. The reason why these medications are seldom prescribed is not well understood. The main questions this study aims to answer are: * Does surgeon education paired with an electronic medical record based decision support tool improve the guideline concordant prescription of pharmacologic venous thromboembolism after abdominopelvic cancer surgery? * Does dedicated patient education regarding blood clots at the time of hospital discharge after abdominopelvic cancer surgery improve understanding of the risk of venous thromboembolism and adherence to pharmacologic prophylaxis? The investigators will study these questions using a stepped-wedge randomized trial where groups of surgeons will use a tool integrated to the electronic medical record to educate them on the individualized patient risks of blood clots after major cancer surgery and inform them regarding guidelines for preventative medicines. Utilization of the medications before and after using the tool will be compared. Patients will be administered a questionnaire assessing their awareness of blood clots as a risk after cancer surgery. For those prescribed medications to reduce blood clot risk after leaving the hospital, the questionnaire will evaluate whether they took the medications as prescribed. Survey results will be evaluated before and after implementation of education on blood clot risk at the time of hospital discharge.
Hypertension (HTN) is the most prevalent modifiable risk factor for cardiovascular disease among U.S. adults. Despite a long history of established guidelines to support clinical management, only half of U.S. adults diagnosed with HTN have poorly controlled blood pressure (BP) and medication adherence to proven effective treatment remains suboptimal. Clinical decision support (CDS) has the potential to overcome barriers to delivering guideline-recommended care and improve HTN management. Practice facilitation is a well-demonstrated implementation strategy to support process changes and has the potential to facilitate CDS implementation. Our objective is to rigorously evaluate whether practice facilitation provided in concert with a HTN-focused CDS that incorporates medication adherence results is an effective strategy for scaling and implementing CDS. The investigators will update an existing CDS to incorporate alerts and tools to address medication adherence then randomize 40 small independent primary care practices in New York City to receive either practice facilitation in addition to the CDS or the CDS alone. After a twelve-month intervention period, The investigators will examine the differences in blood pressure control achieved by practices in the CDS plus practice facilitation group versus practices that received the CDS alone
This is a feasibility study for an investigational clinical decision support system ("the System") intended to optimize the management of blood pressure (BP) for patients during vasopressor infusion. The investigational outcomes are the perceptions of the nurse-subjects who are managing the BP of the patient-subjects; the operational performance of the System; and any technical failures of the software during real-time operation.
This is a pilot randomized controlled trial that will test whether a multicomponent decision support system will improve the postoperative environment for neurocognitive and clinical recovery in older, high-risk surgical patients. Decision support systems will be tested that provide targeted alerts and recommendations to the Hospital Elder Life Program and family members for delirium prevention.
This two phase study will develop and evaluate a Pediatric Emergency Department (PED) Decision Support System (DSS)-Electronic Medical Records (EMR) System to facilitate the identification of smokers and the delivery of a Second Hand Smoke (SHSe) exposure intervention to caregivers who bring their child to the PED.
The purpose of this study is to advance the science of healthcare informatics and to improve medication management through the development of a new approach to the electronic medical record called the Integrated Medication Manager (IMM).
This study will test the effectiveness of clinician-focused health IT-based decision support, family-focused health IT-based decision support, and a combination of both efforts, in increasing HPV and other adolescent vaccine rates among adolescent girls. We hypothesize that a combination of clinician-focused clinical decision support and family-focused decision support will be most effective.
To determine whether the use of educational sessions and computerized clinical reminders can improve primary care doctors' delivery of care to CKD patients compared to educational sessions alone. Hypothesis: Clinical reminders will improve the care delivered to CKD patients
Patient transfer between sites of care is regular practice during an episode of care in our current health care system. Yet inter-site transfer is associated with lapses in care quality that adversely affect patient outcomes. A common iatrogenic harm precipitated at the time of transfer is harm from drug prescribing, or adverse drug events (ADEs). In this study we will evaluate a medication reconciliation tool developed to help providers make effective prescribing decisions at the time of transfer between VA sites of care (Improved Prescribing after Transfer (IPT)). We will evaluate the quantitative effectiveness of the tool in reducing transition drug risk and ADEs. We additionally will conduct focus group discussions and cognitive task analysis among end-users to better understand how providers make drug-prescribing decisions at the time of transfer and to assess factors influencing effective use of the tool.
The Vermont Diabetes Information System (VDIS) is a registry-based decision support and reminder system based on the Chronic Care Model and targeted to primary care physicians and their patients with diabetes. It will be evaluated by a randomized, controlled study in 60 Primary Care practices in Vermont and nearby New York.
There are patients who die or have a bad outcome in the hospital and this could be prevented. Data in the nurses' notes could be used by computers to tell the rest of the care team that a patient is not doing well and that they should act more quickly. This project will build and evaluate a computer system that makes it easier for the care team to see and understand that data and act quickly to save patients. The aims of this study is to answer the questions, what is the level of provider use of the CONCERN CDS notification system (called CONCERN SMARTapp) and resulting impact on selected patient outcomes? Specifically, the study has 1) validated desired thresholds for the CONCERN CDS system and 2) integrated the CONCERN CDS system for early warning of risky patient states within CDS tools. In this portion of the study (aim 3), the investigator will implement and evaluate the CONCERN CDS system on primary outcomes of in-hospital mortality and length of stay and secondary outcomes of cardiac arrest, unanticipated transfers to the intensive care unit, and 30-day hospital readmission rates.
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.
To work best, clinical decision support tools (CDS) must be timed to provide support when healthcare decisions are made, which includes virtual visits (phone or video). Unfortunately, most CDS tools are either missing from virtual visits or not designed for the unique context of virtual visits (e.g., availability of physical assessments and labs, different workflows), which could generate new inequities for patients more likely to use virtual visits. The objective of this study is to test the reach, feasibility and acceptability of a new CDS tool for heart failure with reduced ejection fraction (HFrEF) during virtual visits. This new CDS tool was developed through an iterative design process, and will be compared to an existing HFrEF CDS tool in a randomized pilot study at outpatient cardiology clinics throughout the UCHealth system.
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 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.
This clinical trial evaluates the use of novel decision support educational materials and services using health coaches. The study includes men newly diagnosed with low-risk prostate cancer. A 160 men will be recruited. Half of the men will receive a call from a health coach before their initial consultation visit with their urologist to review their treatment concerns and questions. The other half will receive usual care provided by the urologist, such as educational materials and services provided by the urologist.
The aim of the study is to compare the effect of CirrhosisRx, a novel clinical decision support (CDS) system for inpatient cirrhosis care, versus "usual care" on adherence to national quality measures and clinical outcomes for hospitalized patients with cirrhosis.
Among patients with cognitive impairment (CI) that undergo surgery, the risk for developing postoperative delirium (POD) is high (50%) and associated with further morbidity and mortality. Yet, 30-40% of POD cases are preventable with perioperative management. This randomized pragmatic clinical trial aims to assess incidence of POD in adult surgical patients with CI, as well as provider adherence to a set of 12 perioperative best practice recommendations for perioperative management. Electronic health record (EHR) data will be used to identify patients as high risk for developing POD and clinical decision support (CDS) prompts within the EHR will display best practices. Cases will be randomized to either the control group, usual care or the intervention which includes the high-risk alert and best practice prompts.