Using Intelligent Tools to Support Clinical Decision Making

2020 ◽  
pp. 311-323
Author(s):  
Nilmini Wickramasinghe ◽  
Jonathan L Schaffer
Keyword(s):  
Decision Making ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Care Pathways ◽  
Detection Model ◽  
Risk Detection ◽  
Intelligent Tools ◽  
Specific Care ◽  
Decision Efficiency

Intelligent tools and collaborative systems can be used in healthcare contexts to support clinical decision making. Such an approach is concerned with identifying the way in which information is gathered and decisions are made along specific care pathways. This study develops a real-time collaborative system using an intelligent risk detection model (IRD) to improve decision efficiency in the clinical case of patients undergoing hip or knee arthroplasty. The benefits of adopting this improved clinical decision-making solution include increasing awareness, supporting communication, improving the decision making process for patients and caregivers while also improving information sharing between surgeons as key collaborative parties in the research case. This in turn leads to higher levels of patient and clinical satisfaction and better clinical outcomes.

Using Intelligent Tools to Support Clinical Decision Making

2021 ◽  
pp. 555-567
Author(s):  
Nilmini Wickramasinghe ◽  
Jonathan L Schaffer
Keyword(s):  
Decision Making ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Care Pathways ◽  
Detection Model ◽  
Risk Detection ◽  
Intelligent Tools ◽  
Specific Care ◽  
Decision Efficiency

Intelligent tools and collaborative systems can be used in healthcare contexts to support clinical decision making. Such an approach is concerned with identifying the way in which information is gathered and decisions are made along specific care pathways. This study develops a real-time collaborative system using an intelligent risk detection model (IRD) to improve decision efficiency in the clinical case of patients undergoing hip or knee arthroplasty. The benefits of adopting this improved clinical decision-making solution include increasing awareness, supporting communication, improving the decision making process for patients and caregivers while also improving information sharing between surgeons as key collaborative parties in the research case. This in turn leads to higher levels of patient and clinical satisfaction and better clinical outcomes.

Leveraging Key Aspects of Collaborative Techniques to Assist Clinical Decisions

2017 ◽  
pp. 440-456
Author(s):  
Hoda Moghimi ◽  
Jonathan L. Schaffer ◽  
Nilmini Wickramasinghe
Keyword(s):  
Decision Making ◽  
Information Technologies ◽  
Clinical Decision Making ◽  
Research Question ◽  
Clinical Decision ◽  
Detection Model ◽  
Important Approach ◽  
Hip And Knee Arthroplasty ◽  
Expected Benefits ◽  
Key Aspects

Employing collaborative systems in healthcare contexts is an important approach towards designing and developing intelligent computer solutions. The objective of this study is to develop a real-time collaborative system using the Intelligent Risk Detection Model (IRD) to improve decision efficiency for the care of patients undergoing hip and knee arthroplasty (THA, TKA). Expected benefits include increasing awareness, supporting communication, improving decision making processes and also improving information sharing between surgeons, patients, families and consultants as key collaborative parties. The research question under investigation is: How can key information technologies be designed, developed and adopted to support clinical decision making in the context of THA and TKA? This research in progress has identified the value and benefit of developing a systematic and technology supported tool to facilitate the identification of various risks associated with THA and TKA.

Reversibility of Delirium in Palliative Care (DRAFT)

2018 ◽  
Author(s):  
Tiffany Shaw ◽  
Eric Prommer
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Palliative Care ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Factors Associated ◽  
Frequent Event ◽  
Study Intervention

Delirium is a frequent event in patients with advanced cancer. Untreated delirium affects assessment of symptoms, impairs communication including participation in clinical decision-making. This study used specific diagnostic criteria for delirium and prospectively identified precipitating causes of delirium. The study identified factors associated with reversible and irreversible delirium. Impact of delirium on prognosis was evaluated. This chapter describes the basics of the study, including funding, year study began, year study was published, study location, who was studied, who was excluded, how many patients, study design, study intervention, follow-up, endpoints, results, and criticism and limitations. The chapter briefly reviews other relevant studies and information, gives a summary and discusses implications, and concludes with a relevant clinical case. Topics covered include delirium, neoplasms, palliative care, polypharmacy, risk factors, and therapeutics.

Clinical Case: Simulation-based evaluation of post-operative gait function to support clinical decision making in cerebral palsy

2017 ◽  
Vol 57 ◽  
pp. 102-103 ◽  
Author(s):  
Lorenzo Pitto ◽  
Antoine Falisse ◽  
Tessa Hoekstra ◽  
Hans Kainz ◽  
Mariska Wesseling ◽  
...  
Keyword(s):  
Decision Making ◽  
Cerebral Palsy ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Simulation Based ◽  
Case Simulation ◽  
Gait Function

A decision theory overview and case-based discussion

2021 ◽  
Vol 13 (8) ◽  
pp. 320-324
Author(s):  
David Thom
Keyword(s):  
Decision Making ◽  
Decision Theory ◽  
Reliability Analysis ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Use Of Technology ◽  
Case Based

Paramedics make decisions as part of their everyday role but often, the theory behind clinical decision-making is not discussed in depth. This article explores the theories of decision-making as they apply to a clinical case. With the increasing use of technology in healthcare, the introduction of human reliability analysis is becoming more pertinent.

scholarly journals Clinical Informatics during the COVID-19 Pandemic: Lessons Learned and Implications for Emergency Department and Inpatient Operations

2020 ◽  
Author(s):  
Hanson Hsu ◽  
Peter W Greenwald ◽  
Matthew R Laghezza ◽  
Peter Steel ◽  
Richard Trepp ◽  
...  
Keyword(s):  
Decision Making ◽  
Emergency Department ◽  
Medical Care ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Lessons Learned ◽  
Clinical Informatics ◽  
Security And Privacy ◽  
Care Pathways ◽  
Provider Education

Abstract In response to a pandemic, hospital leaders can use clinical informatics to aid clinical decision-making, virtualizing medical care, coordinating communication, and defining workflow and compliance. Clinical informatics procedures need to be implemented nimbly, with governance measures in place to properly oversee and guide novel patient care pathways, diagnostic and treatment workflows, and provider education and communication. The authors’ experience recommends: (1) creating flexible ordersets that adapt to evolving guidelines that meet needs across specialties (2) enhancing and supporting inherent telemedicine capability (3) electronically enabling novel workflows quickly and suspending non-critical administrative or billing functions in the EHR and (4) using communication platforms based on tiered urgency that do not compromise security and privacy.

scholarly journals Uncertainty and objectivity in clinical decision making: a clinical case in emergency medicine

2016 ◽  
Vol 19 (4) ◽  
pp. 595-603 ◽  
Author(s):  
Eivind Engebretsen ◽  
Kristin Heggen ◽  
Sietse Wieringa ◽  
Trisha Greenhalgh
Keyword(s):  
Decision Making ◽  
Emergency Medicine ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision

Leveraging Key Aspects of Collaborative Techniques to Assist Clinical Decisions

2017 ◽  
pp. 59-75
Author(s):  
Hoda Moghimi ◽  
Jonathan L. Schaffer ◽  
Nilmini Wickramasinghe
Keyword(s):  
Decision Making ◽  
Information Technologies ◽  
Clinical Decision Making ◽  
Research Question ◽  
Clinical Decision ◽  
Detection Model ◽  
Important Approach ◽  
Hip And Knee Arthroplasty ◽  
Expected Benefits ◽  
Key Aspects

Employing collaborative systems in healthcare contexts is an important approach towards designing and developing intelligent computer solutions. The objective of this study is to develop a real-time collaborative system using the Intelligent Risk Detection Model (IRD) to improve decision efficiency for the care of patients undergoing hip and knee arthroplasty (THA, TKA). Expected benefits include increasing awareness, supporting communication, improving decision making processes and also improving information sharing between surgeons, patients, families and consultants as key collaborative parties. The research question under investigation is: How can key information technologies be designed, developed and adopted to support clinical decision making in the context of THA and TKA? This research in progress has identified the value and benefit of developing a systematic and technology supported tool to facilitate the identification of various risks associated with THA and TKA.

Debates in Dysphagia Management: How Do You Use Evidence-Based Practice in Your Dysphagia Patient Care?

2011 ◽  
Vol 20 (4) ◽  
pp. 121-123
Author(s):  
Jeri A. Logemann
Keyword(s):  
Decision Making ◽  
Patient Care ◽  
Clinical Outcomes ◽  
Clinical Judgment ◽  
Clinical Decision Making ◽  
Evidence Based Practice ◽  
Clinical Decision ◽  
Evidence Based ◽  
Clinical Method ◽  
Do So

Evidence-based practice requires astute clinicians to blend our best clinical judgment with the best available external evidence and the patient's own values and expectations. Sometimes, we value one more than another during clinical decision-making, though it is never wise to do so, and sometimes other factors that we are unaware of produce unanticipated clinical outcomes. Sometimes, we feel very strongly about one clinical method or another, and hopefully that belief is founded in evidence. Some beliefs, however, are not founded in evidence. The sound use of evidence is the best way to navigate the debates within our field of practice.

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