Navigating healthcare: a qualitative study exploring prostate cancer patients' and doctors' experience of consultations using a decision-support intervention

2014 ◽  
Vol 23 (6) ◽  
pp. 665-671 ◽  
Author(s):  
B. Hacking ◽  
S. E. Scott ◽  
L. M. Wallace ◽  
S. C. Shepherd ◽  
J. Belkora
Keyword(s):  
Prostate Cancer ◽  
Decision Support ◽  
Qualitative Study ◽  
Cancer Patients ◽  
Support Intervention ◽  
Decision Support Intervention

scholarly journals Development and pilot evaluation of a personalized decision support intervention for low risk prostate cancer patients

2019 ◽  
Vol 9 (1) ◽  
pp. 125-132 ◽  
Author(s):  
Jeffrey Belkora ◽  
June M. Chan ◽  
Matthew R. Cooperberg ◽  
John Neuhaus ◽  
Lauren Stupar ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Support ◽  
Cancer Patients ◽  
Low Risk ◽  
Support Intervention ◽  
Decision Support Intervention ◽  
Risk Prostate Cancer ◽  
Low Risk Prostate Cancer

Development and pilot testing of a decision support intervention for men with prostate cancer.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 132-132
Author(s):  
June M. Chan ◽  
Matthew R. Cooperberg ◽  
John Neuhaus ◽  
Mark Bridge ◽  
Lauren Stupar ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
Decision Support ◽  
Decision Aid ◽  
Decision Quality ◽  
Support Intervention ◽  
Decision Support Intervention ◽  
Before And After ◽  
Risk Prostate Cancer ◽  
Low Risk Prostate Cancer

132 Background: We evaluated the feasibility and efficacy of a decision support intervention designed to help men with low-risk prostate cancer consider active surveillance and standard treatments. The intervention incorporated a decision aid with coaching and question-listing. Our decision aid is the first to include data on long-term survival and side effects from men with prostate cancer undergoing active surveillance, surgery, and radiation. Methods: To develop the intervention, we conducted focus groups using the Nominal Group Technique. We used a survey instrument from the International Patient Decision Aids Standards to measure the stakeholder endorsement of our intervention. To test the intervention, we administered it to newly diagnosed men with low-risk prostate cancer (Gleason sum < = 3+4, stage < = T2N0M0, PSA < = 10 ng/ml) seen at UCSF. Before and after the intervention, we administered a survey with questions from the Decision Quality Instrument for Prostate Cancer. Our primary outcome was change in knowledge as assessed by two multiple-choice items: How many men diagnosed with early stage prostate cancer will eventually die of prostate cancer? How much would waiting 3 months to make a treatment decision affect chances of survival? Correct answers were: “Most will die of something else” and “A little or not at all.” Results: The development phase involved 6 patients, 1 family member, 2 physicians, and 5 other health care providers and four iterations of the intervention until consensus endorsement was reached. In the pilot test, 57 men consented, and 44 received the decision support intervention and completed surveys at both timepoints. Before the intervention, 30/44 (68%) got both questions right, compared to 36/44 (82%) after the intervention. 82% maintained or achieved perfect scores; 16% answered 1 or more incorrectly both before and after the intervention; and 2% answered both items correctly before, but 1 wrong after. Conclusions: This novel decision support intervention was feasible, and appeared to improve knowledge and informed decision-making. Data will guide the development of a larger scale randomized clinical trial to improve decision quality in men with prostate cancer, in the community. Clinical trial information: NCT02451345.

An Electronic Decision Support Intervention Reduces Readmissions for Patients With Cirrhosis

2022 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Jeremy Louissaint ◽  
Katie Grzyb ◽  
Linda Bashaw ◽  
Rima A. Mohammad ◽  
Neehar D. Parikh ◽  
...  
Keyword(s):  
Decision Support ◽  
Electronic Decision Support ◽  
Support Intervention ◽  
Decision Support Intervention

scholarly journals P036: A clinical decision support intervention to increase usage of probenecid in the ED

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S90-S90
Author(s):  
S. Dowling ◽  
E. Lang ◽  
D. Wang ◽  
T. Rich
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Soft Tissue ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Soft Tissue Infections ◽  
Post Intervention ◽  
Support Intervention ◽  
Intervention Phase ◽  
Decision Support Intervention

Introduction: In certain circumstances, skin and soft tissue infections are managed with intravenous (IV) antibiotics. In our center, patients initiated on outpatient IV antibiotics are followed up by a home parental therapy program the following day. A significant number of these patients require a repeat visit to the ED because of clinic hours. Probenecid is a drug that can prolong the half-life of certain antibiotics (such as cefazolin) and can therefore avoid a repeat ED visit, reducing health care costs and improve ED capacity. Our goal was to increase probenecid usage in the ED in order to optimize management of skin and soft tissue infections (SSTI) in the ED. The primary outcome was to compare the usage of probenecid in the pre and post-intervention phase. Secondary outcomes were to compare revisit rates between patients receiving cefazolin alone vs cefazolin + probenecid. Methods: Using administrative data merged with Computerized Physician Order Entry (CPOE), we extracted data 90 days pre- and 90 post-intervention (February 11, 2015 to August 11, 2015). The setting for the study is an urban center (4 adult ED’s with an annual census of over 320,000 visits per year). Our CPOE system is fully integrated into the ED patient care. The multi-faceted intervention involved modifying all relevant SSTI order sets in the CPOE system to link any cefazolin order with an order for probenecid. Physicians and nurses were provided with a 1 page summary of probenecid (indications, contra-indications, pharmacology), as well as decision support with the CPOE. Any patients who were receiving outpatient cefazolin therapy were included in the study. Results: Our analysis included 2512 patients (1148 and 1364 patients in the pre/post phases) who received cefazolin in the ED and were discharged during the 180 day period. Baseline variables (gender, age, % admitted) and ED visits were similar in both phases. In the pre-intervention phase 30.2% of patients received probenecid and in the post-intervention phase 43.0%, for a net increase of 12.8% (p=<0.0001). Patients who received probenecid had a 2.2% (11.4% vs 13.6%, p=0.014) lower re-visit rate in the following 72H. Conclusion: We have implemented a CPOE based clinical decision support intervention that demonstrated significant increase in probenecid usage by emergency physician and resulted in a decrease in ED revisits. This intervention would result in health care cost-savings.

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