scholarly journals Applicability of Pharmacogenomically Guided Medication Treatment during Hospitalization of At-Risk Minority Patients

2021 ◽  
Vol 11 (12) ◽  
pp. 1343
Author(s):  
Loren Saulsberry ◽  
Keith Danahey ◽  
Merisa Middlestadt ◽  
Kevin J. O’Leary ◽  
Edith A. Nutescu ◽  
...  
Keyword(s):  
At Risk ◽  
Point Of Care ◽  
Healthcare Providers ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Implementation Program ◽  
Populations At Risk ◽  
Toxicity Risk ◽  
Predominantly Female

Known disparities exist in the availability of pharmacogenomic information for minority populations, amplifying uncertainty around clinical utility for these groups. We conducted a multi-site inpatient pharmacogenomic implementation program among self-identified African-Americans (AA; n = 135) with numerous rehospitalizations (n = 341) from 2017 to 2020 (NIH-funded ACCOuNT project/clinicaltrials.gov#NCT03225820). We evaluated the point-of-care availability of patient pharmacogenomic results to healthcare providers via an electronic clinical decision support tool. Among newly added medications during hospitalizations and at discharge, we examined the most frequently utilized medications with associated pharmacogenomic results. The population was predominantly female (61%) with a mean age of 53 years (range 19–86). On average, six medications were newly prescribed during each individual hospital admission. For 48% of all hospitalizations, clinical pharmacogenomic information was applicable to at least one newly prescribed medication. Most results indicated genomic favorability, although nearly 29% of newly prescribed medications indicated increased genomic caution (increase in toxicity risk/suboptimal response). More than one of every five medications prescribed to AA patients at hospital discharge were associated with cautionary pharmacogenomic results (most commonly pantoprazole/suboptimal antacid effect). Notably, high-risk pharmacogenomic results (genomic contraindication) were exceedingly rare. We conclude that the applicability of pharmacogenomic information during hospitalizations for vulnerable populations at-risk for experiencing health disparities is substantial and warrants continued prospective investigation.

Red Book Point-of-Care Clinical Decision Support Tool

2018 ◽  
Keyword(s):  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Health Care Professionals ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Pediatric Health Care ◽  
Flip Chart

This convenient flip chart provides pediatric health care professionals with point-of-care guidance on the assessment, prevention, and treatment of childhood infectious diseases. https://shop.aap.org/red-book-pediatric-infectious-diseases-clinical-decision-support-chart/

A novel model of care in anticoagulation management

2020 ◽  
Vol 33 (6) ◽  
pp. 247-252
Author(s):  
Lisa Woodill ◽  
Allison Bodnar
Keyword(s):  
Point Of Care ◽  
Healthcare Providers ◽  
Decision Support Tool ◽  
International Normalized Ratio ◽  
Blood Collection ◽  
Management Service ◽  
Model Of Care ◽  
Anticoagulation Management ◽  
Support Tool ◽  
Care Community

For over 60 years, warfarin has been the treatment of choice in the prevention of strokes and other thromboembolic events. In recent years, a new class of Novel Oral Anticoagulant (NOAC) medication has become available, leaving clinicians and health system payors to question whether warfarin continues to have a place in therapy. This article argues that it may not be the medication that should be in question but instead the systems in place to manage anticoagulation for the patients who need it. Usual Care (UC) for warfarin management has traditionally required multiple healthcare visits, blood collection visits, and laboratory analysis of International Normalized Ratio (INR) with results to then later be relayed to the patient along with dosage adjustments. The article reviews a new model of care, Community Pharmacist-led Anticoagulation Management Service (CPAMS), in which patients receive a point-of-care INR test along with a pharmacist assessment at a pharmacy and results within minutes. Pharmacists then prescribe dosage adjustments immediately, counsel patients, and provide supporting adherence tools such as a colourful picture-based dosing calendar, created by the decision support tool, INR Online. The Nova Scotia CPAMS Demonstration Project shows that this model will result in efficiencies for healthcare providers and optimal anticoagulation with improved time in therapeutic range outcomes for patients. In addition, the CPAMS Costing Study finds the model to be a cost-effective solution for health systems when compared to UC for warfarin as well as NOAC patients.

Digitized Maternal Early Warning and Response Telehealth System

2021 ◽  
Author(s):  
Narmadha Kuppuswami ◽  
Suresh Subramanian ◽  
Karenna J. Groff ◽  
Radha Rani Ravichandran
Keyword(s):  
At Risk ◽  
Maternal Mortality ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Middle Income ◽  
Support Tool ◽  
Middle Income Countries ◽  
Resource Limited ◽  
Development Goals ◽  
Timely Treatment

Introduction: In this article, we describe a pilot telehealth project for identifying women at risk of developing serious complications early and for instituting timely, appropriate, and up-to-date management even in situations with limited resources and skilled obstetric services. Maternal mortality remains unacceptably high, with less than two-thirds of the signatories to the 2015 Millennium Development Goals achieving the outlined 75% reduction in maternal mortality ratio (MMR) from 1990 to 2015. Looking forward to 2030, the Sustainable Development Goals (SDGs) lay out a target of reducing the MMR in every country to below 70 per 100,000 live births. This will require progress in low-and-middle-income countries at a rate much greater than that seen over the past 15 years. Given that 94% of the global maternal deaths occur in low- and-middle-income countries, a solution to meet the unique challenges of these countries will be necessary to achieve the SDG. The Women’s Obstetrical Neonatal Death and Reduction (WONDER) telehealth system described here offers a potential telehealth solution to reduce mortality and morbidity rates in resource-limited environments by early identification of risk indicators and initiation of care. Materials and methods: The WONDER system consists of a cloud-based electronic health record with a Clinical Decision Support tool and a color-coded alert system. The Clinical Decision Support tool is based upon Maternal Early Warning Signs and provides real-time assistance to caregivers via relevant national treatment guidelines. This system uses inexpensive computing hardware, displays, and cell-phone technology. This system was tested in a 2-year pilot study in India. A total of 15,184 patients were monitored during labor and the postpartum period. Results: Within limitations of the study, the incidence of in-hospital eclampsia was reduced by 91.7%, and in 95% of cases, timely treatment was started within an hour of identifying the abnormality in vital signs. Maternal mortality was reduced by 50.1% over local benchmark figures. Conclusions: The WONDER system identified at-risk patients, directed skilled care to those patients at risk for complications, and helped to institute effective, timely treatment, demonstrating a potential solution for women in resource-limited locations.

scholarly journals LO22: Implementation of an electronic clinical decision support tool to improve knowledge translation and imaging appropriateness for patients with mild traumatic brain injury and suspected pulmonary embolism

CJEM ◽  
2017 ◽  
Vol 19 (S1) ◽  
pp. S34-S35
Author(s):  
J. Andruchow ◽  
D. Grigat ◽  
A. McRae ◽  
G. Innes ◽  
E. Lang
Keyword(s):  
Pulmonary Embolism ◽  
Decision Support ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Evidence Based ◽  
Support Tool ◽  
Imaging Appropriateness ◽  
Ct Head ◽  
Evidence Based Guidelines

Introduction/Innovation Concept: Utilization of CT imaging has increased dramatically over the past two decades, but has not necessarily improved patient outcomes. As healthcare spending grows unsustainably and evidence of harms from unnecessary testing accrues, there is pressure to improve imaging appropriateness. However, prior attempts to reduce unnecessary imaging using evidence-based guidelines have met with limited success, with common barriers cited including a lack of confidence in patient outcomes, medicolegal risk, and patient expectations. This project attempts to address these barriers through the development of an electronic clinical decision support (CDS) tool embedded in clinical practice. Methods: An interactive web-based point-of-care CDS tool was incorporated into computerized physician order entry software to provide real-time evidence-based guidance to emergency physicians for select clinical indications. For patients with mild traumatic brain injury (MTBI), decision support for the Canadian CT Head Rule pops up when a CT head is ordered. For patients with suspected pulmonary embolism (PE), the tool is triggered when a CT pulmonary angiogram is ordered and provides CDS for the Pulmonary Embolism Rule-out Criteria (PERC), Wells Score, age-adjusted D-dimer and CT imaging. To study the impact of the tool, all emergency physicians in the Calgary zone were randomized to receive voluntary decision support for either MTBI or PE. Curriculum, Tool, or Material: The tool uses a multifaceted approach to inform physician decision making, including visualization of risk and quantitative outcomes data and links to primary literature. The CDS tool simultaneously documents guideline compliance in the health record, generates printable patient education materials, and populates a REDCap™ database, enabling the creation of confidential physician report cards on CT utilization, appropriateness and diagnostic yield for both audit and feedback and research purposes. Preliminary data show that physicians are using the MTBI CDS approximately 30% of the time, and the PE CDS approximately 40% of the time. Evaluation of CDS impact on imaging utilization and appropriateness is ongoing. Conclusion: A voluntary web-based point-of-care decision support tool embedded in workflow has the potential to address many of the factors typically cited as barriers to use of evidence-based guidelines in practice. However, high rates of adherence to CDS will likely require physician incentives and appropriateness measures.

scholarly journals Utilization and uptake of the UpToDate clinical decision support tool at the Makerere University College of Health Sciences (MakCHS), Uganda

2021 ◽  
Vol 21 (2) ◽  
pp. 904-911
Author(s):  
Alison Annet Kinengyere ◽  
Julie Rosenberg ◽  
Olivia Pickard ◽  
Moses Kamya
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Health Sciences ◽  
Support Tool ◽  
Makerere University ◽  
Clinical Decision Support Tool

Background: The use of point-of-care, evidence-based tools is becoming increasingly popular. They can provide easy-to- use, high-quality information which is regularly updated and has been shown to improve clinical outcomes. Integrating such tools into clinical practice is an important component of improving the quality of health care. However, because such tools are rarely used in resource-limited settings, there is limited research on uptake especially among medical students. Objective: This paper explores the uptake of one such tool, Up-To-Date, when provided free of cost at a medical school in Africa. Methods: In partnership with the Better Evidence at Ariadne Labs free access to UpToDate was granted through the MakCHS IP address. On-site librarians facilitated training sessions and spread awareness of the tool. Usage data was aggre- gated, based on log ins and content views, presented and analyzed using Excel tables and graphs. Results: The data shows evidence of meaningful usage, with 43,043 log ins and 15,591 registrations between August 2019 and August 2020. The most common topics viewed were in obstetrics and gynecology, pediatrics, drug information, and infectious diseases. Access occurred mainly through the mobile phone app. Conclusion: Findings show usage by various user categories, but with inconsistent uptake and low usage. Librarians can draw upon these results to encourage institutions to support uptake of point-of-care tools in clinical practice. Keywords: UpToDate clinical decision support tool; Makerere University College of Health Sciences; Uganda.

scholarly journals Development, implementation, and evaluation of a clinical decision support tool to improve naloxone coprescription within military health system pharmacies

2021 ◽  
Author(s):  
Alexander Rittel ◽  
Krista Highland ◽  
Mark S Maneval ◽  
Archie Bockhorst ◽  
Agustin Moreno ◽  
...  
Keyword(s):  
At Risk ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Opioid Overdose ◽  
Military Health System ◽  
Military Health ◽  
Support Tool ◽  
Patients At Risk

Abstract Disclaimer In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose To describe the development, implementation, and evaluation of a pharmacy clinical decision support tool designed to increase naloxone coprescription among people at risk for opioid overdose in a large healthcare system. Summary The Military Health System Opioid Registry and underlying presentation layer were used to develop a clinical decision support capability to improve naloxone coprescription at the pharmacy point of care. Pharmacy personnel use a patient identification card barcode scanner or manually enter a patient’s identification number to quickly visualize information on a patient’s risk for opioid overdose and medical history related to pain and, when appropriate, receive a recommendation to coprescribe naloxone. The tool was made available to military treatment facility pharmacy locations. An interactive dashboard was developed to support monitoring, utilization, and impact on naloxone coprescription to patients at risk for opioid overdose. Conclusion Initial implementation of the naloxone tool was slow from a lack of end-user awareness. Efforts to increase utilization were, in part, successful owing to a number of enterprise-wide educational initiatives. In early 2020, the naloxone tool was used in 15% of all opioid prescriptions dispensed at a military pharmacy. Data indicate that the frequency of naloxone coprescription to patients at risk for opioid overdose was significantly higher when the naloxone tool was used than when the tool was not used.

scholarly journals Impact of electronic clinical decision support on adherence to guideline-recommended treatment for hyperlipidaemia, atrial fibrillation and heart failure: protocol for a cluster randomised trial

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e019087 ◽  
Author(s):  
Maya Elizabeth Kessler ◽  
Rickey E Carter ◽  
David A Cook ◽  
Daryl Jon Kor ◽  
Paul M McKie ◽  
...  
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Primary Outcome ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Clinical Decision Support Tool

IntroductionClinical practice guidelines facilitate optimal clinical practice. Point of care access, interpretation and application of such guidelines, however, is inconsistent. Informatics-based tools may help clinicians apply guidelines more consistently. We have developed a novel clinical decision support tool that presents guideline-relevant information and actionable items to clinicians at the point of care. We aim to test whether this tool improves the management of hyperlipidaemia, atrial fibrillation and heart failure by primary care clinicians.Methods/analysisClinician care teams were cluster randomised to receive access to the clinical decision support tool or passive access to institutional guidelines on 16 May 2016. The trial began on 1 June 2016 when access to the tool was granted to the intervention clinicians. The trial will be run for 6 months to ensure a sufficient number of patient encounters to achieve 80% power to detect a twofold increase in the primary outcome at the 0.05 level of significance. The primary outcome measure will be the percentage of guideline-based recommendations acted on by clinicians for hyperlipidaemia, atrial fibrillation and heart failure. We hypothesise care teams with access to the clinical decision support tool will act on recommendations at a higher rate than care teams in the standard of care arm.Ethics and disseminationThe Mayo Clinic Institutional Review Board approved all study procedures. Informed consent was obtained from clinicians. A waiver of informed consent and of Health Insurance Portability and Accountability Act (HIPAA) authorisation for patients managed by clinicians in the study was granted. In addition to publication, results will be disseminated via meetings and newsletters.Trial registration numberNCT02742545.

scholarly journals Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jamie S Hirsch ◽  
Rajdeep Brar ◽  
Christopher Forrer ◽  
Christine Sung ◽  
Richard Roycroft ◽  
...  
Keyword(s):  
Decision Support ◽  
Kidney Function ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Design Development ◽  
Order Entry ◽  
Support Tool ◽  
Maintenance Requirements ◽  
Physician Order Entry

Abstract Delivering clinical decision support (CDS) at the point of care has long been considered a major advantage of computerized physician order entry (CPOE). Despite the widespread implementation of CPOE, medication ordering errors and associated adverse events still occur at an unacceptable level. Previous attempts at indication- and kidney function-based dosing have mostly employed intrusive CDS, including interruptive alerts with poor usability. This descriptive work describes the design, development, and deployment of the Adult Dosing Methodology (ADM) module, a novel CDS tool that provides indication- and kidney-based dosing at the time of order entry. Inclusion of several antimicrobials in the initial set of medications allowed for the additional goal of optimizing therapy duration for appropriate antimicrobial stewardship. The CDS aims to decrease order entry errors and burden on providers by offering automatic dose and frequency recommendations, integration within the native electronic health record, and reasonable knowledge maintenance requirements. Following implementation, early utilization demonstrated high acceptance of automated recommendations, with up to 96% of provided automated recommendations accepted by users.

scholarly journals Towards Improving the Identification of Anterior Cruciate Ligament Tears in Primary Point-of-Care Settings

2020 ◽  
Author(s):  
Jackie L Whittaker ◽  
Michelle Chan ◽  
Bo Pan ◽  
Imran Hassan ◽  
Terry Defreitas ◽  
...  
Keyword(s):  
Point Of Care ◽  
Cruciate Ligament ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Acl Tear ◽  
Patient Reported ◽  
History Of ◽  
Clinical Decision Support Tool ◽  
Anterior Cruciate

Abstract Background: Only a small proportion of anterior cruciate ligament (ACL) tears are diagnosed on initial healthcare consultation. Current clinical guidelines do not acknowledge that primary point-of-care practitioners rely more heavily on a clinical history than special clinical tests for diagnosis of an ACL tear. This research will assess the accuracy of combinations of patient-reported variables alone, and in combination with clinician-generated variables to identify an ACL tear as a preliminary step to designing a primary point-of-care clinical decision support tool.Methods: Electronic medical records (EMRs) of individuals aged 15-45 years, with ICD-9 codes corresponding to a knee condition, and confirmed (ACL+) or denied (ACL-) first-time ACL tear seen at a University-based Clinic between 2014 and 2016 were eligible for inclusion. Demographics, relevant diagnostic indicators and ACL status based on orthopaedic surgeon assessment and/or MRI reports were manually extracted. Descriptive statistics calculated for all variables by ACL status. Univariate between group comparisons, clinician surveys (n=17), availability of data and univariable logistic regression (95%CI) were used to select variables for inclusion into multivariable logistic regression models that assessed the odds (95%CI) of an ACL-tear based on patient-reported variables alone (consistent with primary point-of-care practice), or in combination with clinician-generated variables. Model performance was assessed by accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (95%CI).Results: Of 1,512 potentially relevant EMRs, 725 were included. Participant median age was 26 years (range 15-45), 48% were female and 60% had an ACL tear. A combination of patient-reported (age, sport-related injury, immediate swelling, family history of ACL tear) and clinician-generated variables (Lachman test result) were superior for ACL tear diagnosis [accuracy; 0.95 (90,98), sensitivity; 0.97 (0.88,0.98), specificity; 0.95 (0.82,0.99)] compared to the patient-reported variables alone [accuracy; 84% (77,89), sensitivity; 0.60 (0.44,0.74), specificity; 0.95 (0.89,0.98)].Conclusions: A high proportion of individuals without an ACL tear can be accurately identified by considering patient-reported age, injury setting, immediate swelling and family history of ACL tear. These findings directly inform the development of a clinical decision support tool to facilitate timely and accurate ACL tear diagnosis in primary care settings.

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