scholarly journals Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study

2018 ◽  
Vol 7 (6) ◽  
pp. e154 ◽  
Author(s):  
Stijn Van de Velde ◽  
Tiina Kortteisto ◽  
David Spitaels ◽  
Gro Jamtvedt ◽  
Pavel Roshanov ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Decision Support ◽  
Knee Osteoarthritis ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Improve Quality ◽  
Tailored Intervention

scholarly journals A Narrative Review of Clinical Decision Support for Inpatient Clinical Pharmacists

2021 ◽  
Vol 12 (02) ◽  
pp. 199-207
Author(s):  
Liang Yan ◽  
Thomas Reese ◽  
Scott D. Nelson
Keyword(s):  
Patient Safety ◽  
Quality Of Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Controlled Trials ◽  
Clinical Pharmacists ◽  
Randomized Controlled ◽  
The Impact

Abstract Objective Increasingly, pharmacists provide team-based care that impacts patient care; however, the extent of recent clinical decision support (CDS), targeted to support the evolving roles of pharmacists, is unknown. Our objective was to evaluate the literature to understand the impact of clinical pharmacists using CDS. Methods We searched MEDLINE, EMBASE, and Cochrane Central for randomized controlled trials, nonrandomized trials, and quasi-experimental studies which evaluated CDS tools that were developed for inpatient pharmacists as a target user. The primary outcome of our analysis was the impact of CDS on patient safety, quality use of medication, and quality of care. Outcomes were scored as positive, negative, or neutral. The secondary outcome was the proportion of CDS developed for tasks other than medication order verification. Study quality was assessed using the Newcastle–Ottawa Scale. Results Of 4,365 potentially relevant articles, 15 were included. Five studies were randomized controlled trials. All included studies were rated as good quality. Of the studies evaluating inpatient pharmacists using a CDS tool, four showed significantly improved quality use of medications, four showed significantly improved patient safety, and three showed significantly improved quality of care. Six studies (40%) supported expanded roles of clinical pharmacists. Conclusion These results suggest that CDS can support clinical inpatient pharmacists in preventing medication errors and optimizing pharmacotherapy. Moreover, an increasing number of CDS tools have been developed for pharmacists' roles outside of order verification, whereby further supporting and establishing pharmacists as leaders in safe and effective pharmacotherapy.

scholarly journals Repurposing Clinical Decision Support System Data to Measure Dosing Errors and Clinician-Level Quality of Care

2020 ◽  
Vol 44 (10) ◽  
Author(s):  
David L. Chin ◽  
Michelle H. Wilson ◽  
Ashley S. Trask ◽  
Victoria T. Johnson ◽  
Brittanie I. Neaves ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
System Data

Clinical decision support improves quality of care in patients with ulcerative colitis

2019 ◽  
Vol 49 (8) ◽  
pp. 1040-1051 ◽  
Author(s):  
Belinda Jackson ◽  
Jake Begun ◽  
Kathleen Gray ◽  
Leonid Churilov ◽  
Danny Liew ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Quality Of Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision

scholarly journals Application of Clinical Decision Support System to Assist Breast Cancer Patients with Lifestyle Modifications during the COVID-19 Pandemic: A Randomised Controlled Trial

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 2115
Author(s):  
Panos Papandreou ◽  
Aristea Gioxari ◽  
Frantzeska Nimee ◽  
Maria Skouroliakou
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Control Group ◽  
Healthy Weight ◽  
Lifestyle Modifications ◽  
Randomised Controlled

Clinical decision support systems (CDSS) are data aggregation tools based on computer technology that assist clinicians to promote healthy weight management and prevention of cardiovascular diseases. We carried out a randomised controlled 3-month trial to implement lifestyle modifications in breast cancer (BC) patients by means of CDSS during the COVID-19 pandemic. In total, 55 BC women at stages I-IIIA were enrolled. They were randomly assigned either to Control group, receiving general lifestyle advice (n = 28) or the CDSS group (n = 27), to whom the CDSS provided personalised dietary plans based on the Mediterranean diet (MD) together with physical activity guidelines. Food data, anthropometry, blood markers and quality of life were evaluated. At 3 months, higher adherence to MD was recorded in the CDSS group, accompanied by lower body weight (kg) and body fat mass percentage compared to control (p < 0.001). In the CDSS arm, global health/quality of life was significantly improved at the trial endpoint (p < 0.05). Fasting blood glucose and lipid levels (i.e., cholesterol, LDL, triacylglycerols) of the CDSS arm remained unchanged (p > 0.05) but were elevated in the control arm at 3 months (p < 0.05). In conclusion, CDSS could be a promising tool to assist BC patients with lifestyle modifications during the COVID-19 pandemic.

Abstract P263: Computer-Assisted Decision Support in the Treatment of Acute Coronary Syndromes and Impact on Cardiovascular Outcomes

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
Richard V Milani ◽  
Carl J Lavie ◽  
Daniel P Morin ◽  
Andres Rubiano
Keyword(s):  
Quality Of Care ◽  
Decision Support ◽  
Baseline Risk ◽  
Risk Scores ◽  
Computer Assisted ◽  
Improve Quality ◽  
Consensus Guidelines ◽  
Mortality And Morbidity ◽  
Coronary Syndrome

Background: Evidence from clinical trials and consensus guidelines suggest that in-hospital initiation of key therapeutics can reduce mortality and morbidity in patients admitted with acute coronary syndrome (ACS). As a result, the AHA and ACC have co-developed guideline-based “performance measures” for ACS patients, such that when every measure has been performed, the patient is considered to have achieved optimal or “perfect” care (PC). Computer-assisted decision support (CADS) is a tool that can improve quality of care and is well suited for complex algorithms governing treatment decisions. We sought to determine if CADS tailored to ACS would enhance the likelihood of achieving PC, and whether achievement of PC would translate into reduced mortality. Methods: 452 consecutive patients (mean age 68±13 years) admitted with ACS in 2009 were evaluated (unstable angina 29%, NSTEMI 61%, STEMI 10%). Physicians had the option of using either pre-printed ACS orders (standard orders) versus CADS generated orders. The CADS system utilized patient clinical data including risk scoring, to suggest specific therapeutics and drug dosing based on consensus guidelines. Endpoints were attainment of PC and 30-day mortality. Results: The 77 patients admitted using CADS generated orders were statistically similar (age, gender, ACS diagnosis, TIMI risk) to the 375 patients admitted with the standard order set. Attainment of PC was almost twice as likely when using CADS versus standard orders (84% vs. 44%, p<0.05). PC patients trended towards higher TIMI risk scores (3.2 ±1.7 vs 2.9 ±1.6, p = 0.09) but had half the 30-day mortality (2% vs 4%, p=0.05) compared to patients not achieving PC. Conclusions: Use of CADS in the setting of ACS is feasible and doubles the likelihood of attaining PC. Although patients achieving PC had higher baseline risk, their mortality was reduced by 50% compared to those not achieving PC. These data support the use of CADS in the setting of ACS to improve quality of care and subsequent outcomes.

scholarly journals Quality of the documentation of the Nursing process in clinical decision support systems

2021 ◽  
Vol 29 ◽  
Author(s):  
Neurilene Batista de Oliveira ◽  
Heloísa Helena Ciqueto Peres
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
P Value ◽  
Nursing Process ◽  
Post Intervention ◽  
Quasi Experimental ◽  
Process Documentation

Objective: to compare the quality of the Nursing process documentation in two versions of a clinical decision support system. Method: a quantitative and quasi-experimental study of the before-and-after type. The instrument used to measure the quality of the records was the Brazilian version of the Quality of Diagnoses, Interventions and Outcomes, which has four domains and a maximum score of 58 points. A total of 81 records were evaluated in version I (pre-intervention), as well as 58 records in version II (post-intervention), and the scores obtained in the two applications were compared. The interventions consisted of planning, pilot implementation of version II of the system, training and monitoring of users. The data were analyzed in the R software, using descriptive and inferential statistics. Results: the mean obtained at the pre-intervention moment was 38.24 and, after the intervention, 46.35 points. There was evidence of statistical difference between the means of the pre- and post-intervention groups, since the p-value was below 0.001 in the four domains evaluated. Conclusion: the quality of the documentation of the Nursing process in version II of the system was superior to version I. The efficacy of the system and the effectiveness of the interventions were verified. This study can contribute to the quality of documentation, care management, visibility of nursing actions and patient safety.

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