Electronic health record with computerized decision support tools for the purposes of a pediatric cardiovascular heart disease screening program in Crete

2018 ◽  
Vol 159 ◽  
pp. 159-166 ◽  
Author(s):  
Ilias Chatzakis ◽  
Kostas Vassilakis ◽  
Christos Lionis ◽  
Ioannis Germanakis
Keyword(s):  
Heart Disease ◽  
Decision Support ◽  
Electronic Health Record ◽  
Screening Program ◽  
Disease Screening ◽  
Health Record ◽  
Decision Support Tools ◽  
Computerized Decision Support ◽  
Cardiovascular Heart Disease ◽  
Support Tools

scholarly journals Reducing Potentially Inappropriate Prescriptions for Older Patients Using Computerized Decision Support Tools: Systematic Review (Preprint)

2019 ◽  
Author(s):  
Luís Monteiro ◽  
Tiago Maricoto ◽  
Isabel Solha ◽  
Inês Ribeiro-Vaz ◽  
Carlos Martins ◽  
...  
Keyword(s):  
Decision Support ◽  
Randomized Controlled Trials ◽  
Controlled Trials ◽  
Potentially Inappropriate Medications ◽  
Decision Support Tools ◽  
Computerized Decision Support ◽  
Randomized Controlled ◽  
Support Tools ◽  
Inappropriate Medications ◽  
Inappropriate Prescriptions

BACKGROUND Older adults are more vulnerable to polypharmacy and prescriptions of potentially inappropriate medications. There are several ways to address polypharmacy to prevent its occurrence. We focused on computerized decision support tools. OBJECTIVE The available literature was reviewed to understand whether computerized decision support tools reduce potentially inappropriate prescriptions or potentially inappropriate medications in older adult patients and affect health outcomes. METHODS Our systematic review was conducted by searching the literature in the MEDLINE, CENTRAL, EMBASE, and Web of Science databases for interventional studies published through February 2018 to assess the impact of computerized decision support tools on potentially inappropriate medications and potentially inappropriate prescriptions in people aged 65 years and older. RESULTS A total of 3756 articles were identified, and 16 were included. More than half (n=10) of the studies were randomized controlled trials, one was a crossover study, and five were pre-post intervention studies. A total of 266,562 participants were included; of those, 233,144 participants were included and assessed in randomized controlled trials. Intervention designs had several different features. Computerized decision support tools consistently reduced the number of potentially inappropriate prescriptions started and mean number of potentially inappropriate prescriptions per patient. Computerized decision support tools also increased potentially inappropriate prescriptions discontinuation and drug appropriateness. However, in several studies, statistical significance was not achieved. A meta-analysis was not possible due to the significant heterogeneity among the systems used and the definitions of outcomes. CONCLUSIONS Computerized decision support tools may reduce potentially inappropriate prescriptions and potentially inappropriate medications. More randomized controlled trials assessing the impact of computerized decision support tools that could be used both in primary and secondary health care are needed to evaluate the use of medication targets defined by the Beers or STOPP (Screening Tool of Older People’s Prescriptions) criteria, adverse drug reactions, quality of life measurements, patient satisfaction, and professional satisfaction with a reasonable follow-up, which could clarify the clinical usefulness of these tools. CLINICALTRIAL International Prospective Register of Systematic Reviews (PROSPERO) CRD42017067021; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42017067021

scholarly journals Health Reform in Minnesota: An Analysis of Complementary Initiatives Implementing Electronic Health Record Technology and Care Coordination

2016 ◽  
Vol 8 (3) ◽  
Author(s):  
Karen Soderberg ◽  
Sripriya Rajamani ◽  
Douglas Wholey ◽  
Martin LaVenture
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Care Coordination ◽  
Health Reform ◽  
Clinical Decision ◽  
Health Record ◽  
Decision Support Tools ◽  
Primary Care Clinics ◽  
Support Tools ◽  
Clinical Decision Support Tools

Background: Minnesota enacted legislation in 2007 that requires all health care providers in the state to implement an interoperable electronic health record (EHR) system by 2015. 100% of hospitals and 98% of clinics had adopted EHR systems by end of 2015. Minnesota’s 2008 health reform included a health care home (HCH) program, Minnesota’s patient centered medical home. By end of 2014, 43% of HCH eligible clinics were certified with 335 certified HCHs and 430 eligible but not certified clinics.Objectives: To study the association between adoption and use of EHRs in primary care clinics and HCH certification, including use of clinical decision support tools, patient registries, electronic exchange of patient information, and availability of patient portals.Methods: Study utilized data from the 2015 Minnesota Health Information Technology Clinic Survey conducted annually by the Minnesota Department of Health. The response rate was 80% with 1,181 of 1,473 Minnesota clinics, including 662 HCH eligible primary care clinics. The comparative analysis focused on certified HCHs (311) and eligible but not certified clinics (351).Results: HCH clinics utilized the various tools of EHR technology at a higher rate than non-HCH clinics. This better utilization was noted across a range of functionalities: clinical decision support, patient disease registries, EHR to support quality improvement, electronic exchange of summary care records and availability of patient portals. HCH certification was significant for clinical decision support tools, registries and quality improvement.Conclusions: The rapid uptake in EHR technology, combined with health reform efforts focusing on accountability and care coordination, pose opportunities and challenges for providers. Opportunities are availability of tools that support decision making, quality improvement and reporting. Challenges remain for clinics to optimize health information exchange. The need to meet various care coordination requirements were likely drivers for better EHR utilization by HCH clinics. This research presents the synergy between complementary initiatives supporting EHR adoption and HCH certification.

scholarly journals Reducing Potentially Inappropriate Prescriptions for Older Patients Using Computerized Decision Support Tools: Systematic Review

10.2196/15385 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e15385 ◽  
Author(s):  
Luís Monteiro ◽  
Tiago Maricoto ◽  
Isabel Solha ◽  
Inês Ribeiro-Vaz ◽  
Carlos Martins ◽  
...  
Keyword(s):  
Decision Support ◽  
Randomized Controlled Trials ◽  
Controlled Trials ◽  
Potentially Inappropriate Medications ◽  
Decision Support Tools ◽  
Computerized Decision Support ◽  
Randomized Controlled ◽  
Support Tools ◽  
Inappropriate Medications ◽  
Inappropriate Prescriptions

Background Older adults are more vulnerable to polypharmacy and prescriptions of potentially inappropriate medications. There are several ways to address polypharmacy to prevent its occurrence. We focused on computerized decision support tools. Objective The available literature was reviewed to understand whether computerized decision support tools reduce potentially inappropriate prescriptions or potentially inappropriate medications in older adult patients and affect health outcomes. Methods Our systematic review was conducted by searching the literature in the MEDLINE, CENTRAL, EMBASE, and Web of Science databases for interventional studies published through February 2018 to assess the impact of computerized decision support tools on potentially inappropriate medications and potentially inappropriate prescriptions in people aged 65 years and older. Results A total of 3756 articles were identified, and 16 were included. More than half (n=10) of the studies were randomized controlled trials, one was a crossover study, and five were pre-post intervention studies. A total of 266,562 participants were included; of those, 233,144 participants were included and assessed in randomized controlled trials. Intervention designs had several different features. Computerized decision support tools consistently reduced the number of potentially inappropriate prescriptions started and mean number of potentially inappropriate prescriptions per patient. Computerized decision support tools also increased potentially inappropriate prescriptions discontinuation and drug appropriateness. However, in several studies, statistical significance was not achieved. A meta-analysis was not possible due to the significant heterogeneity among the systems used and the definitions of outcomes. Conclusions Computerized decision support tools may reduce potentially inappropriate prescriptions and potentially inappropriate medications. More randomized controlled trials assessing the impact of computerized decision support tools that could be used both in primary and secondary health care are needed to evaluate the use of medication targets defined by the Beers or STOPP (Screening Tool of Older People’s Prescriptions) criteria, adverse drug reactions, quality of life measurements, patient satisfaction, and professional satisfaction with a reasonable follow-up, which could clarify the clinical usefulness of these tools. Trial Registration International Prospective Register of Systematic Reviews (PROSPERO) CRD42017067021; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42017067021

scholarly journals Outcomes of Integrating Smart Phrase Interface Technology to Improve Cancer Symptom Management

2021 ◽  
Vol 5 (1) ◽  
pp. 1-11
Author(s):  
M Dufault ◽  
Keyword(s):  
Decision Support ◽  
Emotional Support ◽  
Symptom Management ◽  
Health Record ◽  
Decision Support Tools ◽  
Telephone Triage ◽  
Support Tools ◽  
Toxicity Risk ◽  
Cancer Symptom Management ◽  
Risk Predictors

ssessing cancer treatment-related symptoms is challenging for frontline telephone-triage nurses toggling multiple electronic health record (EHR) screens for information on toxicity-risk predictors while simultaneously providing over-the-phone emotional support. Decision-support tools embedded into computer-telephone interface software, called smart phrases, are not widely used nor empirically evaluated for usability and remote symptom management impact.

scholarly journals Using a configurable EMR and decision support tools to promote process integration for routine HIV screening in the emergency department

2015 ◽  
Vol 23 (2) ◽  
pp. 396-401 ◽  
Author(s):  
Robert McGuire ◽  
Eric Moore
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Hiv Testing ◽  
Screening Program ◽  
Safety Net ◽  
Hiv Screening ◽  
Decision Support Tools ◽  
Opt Out ◽  
Safety Net Hospital ◽  
Support Tools

Abstract Given the clinical and public health benefits of routine Human Immunodeficiency Virus (HIV) testing in the emergency department (ED) and Centers for Disease Control and Prevention recommendations, Maricopa Medical Center, as part of Maricopa Integrated Health System, started Test, Educate, Support, and Treat Arizona (TESTAZ) and became the first and, to-date, only hospital in Arizona to implement routine, non-targeted, opt-out, rapid HIV screening in the ED. The authors describe the implementation of a universal, routine, opt-out HIV screening program in the adult ED of an urban safety-net hospital serving under-served populations, including the uninsured and under-insured. Through a controlled and collaborative process, the authors integrated custom documentation elements specific to HIV screening into the triage/intake process, implemented and utilized clinical decision support tools to guide clinicians in each step of the process, and used electronic data collection and reporting to drive new screening protocols that led to a significant increase in overall HIV testing rates.

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