scholarly journals Predicting Clinical Outcomes Using Molecular Biomarkers

2016 ◽  
Vol 8 ◽  
pp. BIC.S33380 ◽  
Author(s):  
Harry B. Burke
Keyword(s):  
Decision Making ◽  
Clinical Outcomes ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Molecular Biomarkers ◽  
The Past ◽  
Diagnosis And Prognosis ◽  
Molecular Therapies ◽  
Physician Patient

Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician–patient interaction, they will be an integral part of physician–patient-shared decision-making, and they will improve clinical care and patient outcomes.

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.

Decision-making under pressure: medical errors in uncertain and dynamic environments

2018 ◽  
Vol 42 (4) ◽  
pp. 395 ◽  
Author(s):  
Alicia M. Zavala ◽  
Gary E. Day ◽  
David Plummer ◽  
Anita Bamford-Wade
Keyword(s):  
Decision Making ◽  
Human Factors ◽  
Clinical Outcomes ◽  
Medical Errors ◽  
Thematic Analysis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Dynamic Environments ◽  
Emergency Situations ◽  
Case Complexity

Objective This paper provides a narrative overview of the literature concerning clinical decision-making processes when staff come under pressure, particularly in uncertain, dynamic and emergency situations. Methods Studies between 1980 and 2015 were analysed using a six-phase thematic analysis framework to achieve an in-depth understanding of the complex origins of medical errors that occur when people and systems are under pressure and how work pressure affects clinical performance and patient outcomes. Literature searches were conducted using a Summons Search Service platform; search criteria included a variety of methodologies, resulting in the identification of 95 papers relevant to the present review. Results Six themes emerged in the present narrative review using thematic analysis: organisational systems, workload, time pressure, teamwork, individual human factors and case complexity. This analysis highlights that clinical outcomes in emergency situations are the result of a variety of interconnecting factors. These factors may affect the ability of clinical staff in emergency situations to provide quality, safe care in a timely manner. Conclusions The challenge for researchers is to build the body of knowledge concerning the safe management of patients, particularly where clinicians are working under pressure. This understanding is important for developing pathways that optimise clinical decision making in uncertain and dynamic environments. What is known about the topic? Emergency departments (EDs) are characterised by high complexity, high throughput and greater uncertainty compared with routine hospital wards or out-patient situations, and the ED is therefore prone to unpredictable workflows and non-replicable conditions when presented with unique and complex cases. What does this paper add? Clinical decision making can be affected by pressures with complex origins, including organisational systems, workload, time constraints, teamwork, human factors and case complexity. Interactions between these factors at different levels of the decision-making process can increase the complexity of problems and the resulting decisions to be made. What are the implications for practitioners? The findings of the present study provide further evidence that consideration of medical errors should be seen primarily from a ‘whole-of-system’ perspective rather than as being primarily the responsibility of individuals. Although there are strategies in place in healthcare organisations to eliminate errors, they still occur. In order to achieve a better understanding of medical errors in clinical practice in times of uncertainty, it is necessary to identify how diverse pressures can affect clinical decisions, and how these interact to influence clinical outcomes.

scholarly journals Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign

2016 ◽  
Vol 3 (2) ◽  
pp. e26 ◽  
Author(s):  
Deborah J Cohen ◽  
Sara R Keller ◽  
Gillian R Hayes ◽  
David A Dorr ◽  
Joan S Ash ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Health Data ◽  
Lessons Learned

Clinical Decision Making in the ICU: Dysphagia Screening, Assessment, and Treatment

2019 ◽  
Vol 40 (03) ◽  
pp. 170-187 ◽  
Author(s):  
Martin B. Brodsky ◽  
Emily B. Mayfield ◽  
Roxann Diez Gross
Keyword(s):  
Intensive Care Unit ◽  
Decision Making ◽  
Intensive Care ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Level Of Care ◽  
Assessment And Treatment ◽  
Proper Training ◽  
Screening Assessment

AbstractClinicians often perceive the intensive care unit as among the most intimidating environments in patient care. With the proper training, acquisition of skill, and approach to clinical care, feelings of intimidation may be overcome with the great rewards this level of care has to offer. This review—spanning the ages of birth to senescence and covering oral/nasal endotracheal intubation and tracheostomy—presents a clinically relevant, directly applicable review of screening, assessment, and treatment of dysphagia in the patients who are critically ill for clinical speech–language pathologists and identifies gaps in the clinical peer-reviewed literature for researchers.

A comparison of patients' and physicians' expectations regarding precision oncology tests.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1568-1568
Author(s):  
Navdeep Dehar ◽  
Tasnima Abedin ◽  
Patricia A. Tang ◽  
D. Gwyn Bebb ◽  
Winson Y. Cheung
Keyword(s):  
Decision Making ◽  
Genetic Testing ◽  
Cancer Biology ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Survey Study ◽  
Precision Oncology ◽  
Diagnosis And Prognosis ◽  
Genetic Test Results ◽  
Survey Responses

1568 Background: With the increasing number and frequency of biomarker and genetic tests that are offered to patients with cancer, it is important to ensure that they fully understand the implications of these tests. In this survey study, we aimed to compare the attitudes and expectations of patients and cancer physicians about the role of biomarker and genetic testing in clinical decision-making. Methods: Two separate, complimentary, self-administered questionnaires for cancer patients and their physicians, respectively, were collected in Calgary, Alberta, Canada. Survey responses from patients were subsequently matched with those of their corresponding oncologists to form patient–oncologist dyads. We determined the concordance rates between responses of patients and those of their oncologists. Results: A total of 113 patients and 15 physicians participated in the study from July to September 2019. Patients demonstrated good understanding of general cancer biology (79%) and diagnostic processes (91%) associated with precision oncology. About 70% patients were willing to undergo minor procedures, and participate in research involving biomarker or genetic testing; however, this was over-estimated by their physicians in 82% of cases. Many patients felt that their tumor should be tested to guide treatment (70%) and were not bothered by potential delays in treatment due to testing (23%). These views from patients were largely shared by their oncologists (concordance 64%). While only 28% patients thought that they had enough knowledge to make informed decisions, majority (68%) said that they needed more information. Importantly, knowledge and expectations regarding the applications of biomarker or genetic test results on actual diagnosis and prognosis were grossly discrepant between patients and their oncologists (concordance 26% and 36%, respectively). Conclusions: Patients and cancer physicians tend to be aware of the advances in precision oncology and are willing to participate in biomarker and genetic testing and research. However, they do not consistently agree about the roles and applications of these tests, which may result in misplaced expectations. Strategies to improve education and communication are needed to align these expectations and improve the quality of clinical decision-making.

Clinical Assessment of Upper Extremity Injury Outcomes

2011 ◽  
Vol 20 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Charles Thigpen ◽  
Ellen Shanley
Keyword(s):  
Decision Making ◽  
Clinical Outcome ◽  
Outcome Assessment ◽  
Clinical Outcomes ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Assessment Tools ◽  
Bottom Line ◽  
Patient Scenario ◽  
Clinical Outcomes Assessment

Patient Scenario:The patient presented is a high school baseball pitcher who was unable to throw because of shoulder pain. He subsequently failed nonoperative management but was able to return to pitching after surgery and successful rehabilitation.Clinical Outcomes Assessment:The Disabilities of Arm, Shoulder and Hand (DASH) and the Pennsylvania Shoulder Score (PENN) were selected as clinical outcome assessment tools to quantify the patient’s perceived ability to perform common daily tasks and sport tasks and current symptoms such as pain and patient satisfaction.Clinical Decision Making:The DASH and PENN provide important information that can be used to target specific interventions, set appropriate patient goals, assess between-sessions changes in patient status, and quantify patients’ functional loss.Clinical Bottom Line:Best clinical practice involves the use of clinical outcome assessment tools to garner an objective measure of the impact of a patient’s disease process on functional expectations. This process should facilitate a patient-centered approach by clinicians while they select the optimal intervention strategies and establish prognostic timelines.

scholarly journals Centralised RECIST Assessment and Clinical Outcomes with Lenvatinib Monotherapy in Recurrent and Metastatic Adenoid Cystic Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 4336
Author(s):  
Laura Feeney ◽  
Yatin Jain ◽  
Matthew Beasley ◽  
Oliver Donnelly ◽  
Anthony Kong ◽  
...  
Keyword(s):  
Decision Making ◽  
Adenoid Cystic Carcinoma ◽  
Clinical Outcomes ◽  
Clinical Decision Making ◽  
Kinase Inhibitor ◽  
Objective Response ◽  
Response Rates ◽  
Clinical Decision ◽  
Adenoid Cystic ◽  
Phase Ii Studies

Adenoid cystic carcinoma (ACC) is a rare cancer of secretory glands. Recurrent or metastatic (R/M) ACC is generally considered resistant to cytotoxic chemotherapy. Recent phase II studies have reported improved objective response rates (ORR) with the use of the multi-kinase inhibitor lenvatinib. We sought to evaluate real-world experience of R/M ACC patients treated with lenvatinib monotherapy within the UK National Health Service (NHS) to determine the response rates by Response Evaluation Criteria of Solid Tumour (RECIST) and clinical outcomes. Twenty-three R/M ACC patients from eleven cancer centres were included. All treatment assessments for clinical decision making related to drug therapy were undertaken at the local oncology centre. Central radiology review was performed by an independent clinical trial radiologist and blinded to the clinical decision making. In contrast to previously reported ORR of 12–15%, complete or partial response was not observed in any patients. Eleven patients (52.4%) had stable disease and 5 patients (23.8%) had progression of disease as the best overall response. The median time on treatment was 4 months and the median survival from discontinuation was 1 month. The median PFS and OS from treatment initiation were 4.5 months and 12 months respectively. Multicentre collaborative studies such as this are required to evaluate rare cancers with no recommended standard of care therapy and variable disease courses.

When bright lines blur: Deconstructing distinctions between disorders of consciousness

2017 ◽  
Author(s):  
David B. Fischer ◽  
Robert D. Truog
Keyword(s):  
Decision Making ◽  
Diagnostic Criteria ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Disorders Of Consciousness ◽  
Ethical Management ◽  
The Past ◽  
Way Of Thinking

Disorders of consciousness are devastating to patients and present profound challenges to clinicians, scientists, philosophers, and ethicists alike. In the past, distinguishing between levels of these disorders has been vital to guiding important decisions. This chapter argues that these disorders are not sufficiently distinct, however, to dictate such decisions: diagnostic criteria are not discrete, nor do they reflect the conceptual definitions of these disorders. It argues that these non-distinct diagnostic boundaries reflect an inherent continuity between disorders of consciousness. In light of these points, a new way of thinking about disorders of consciousness is presented in the chapter to more effectively guide clinical decision-making. The chapter argues that these considerations bring clarity to disorders of consciousness and can improve the ethical management of patients suffering from these disorders.

Why Machine Learning Should Be Taught in Medical Schools (Preprint)

2021 ◽  
Author(s):  
Matthew Nagy ◽  
Nathan Radakovich ◽  
Aziz Nazha
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Rapid Development ◽  
Clinical Care ◽  
Clinical Decision ◽  
Medical Schools ◽  
Medical Workforce ◽  
Ethical Concerns ◽  
Clinical Tools

UNSTRUCTURED The rapid development of machine learning (ML) applications in healthcare promises to transform the landscape of healthcare. In order for ML advancements to be effectively utilized in clinical care, it is necessary for the medical workforce to be prepared to handle these changes. As physicians in training are exposed to a wide breadth of clinical tools during medical school, this offers an ideal opportunity to introduce ML concepts. A foundational understanding of ML will not only be practically useful for clinicians, but will also address ethical concerns for clinical decision making. While select medical schools have made effort to integrate ML didactics and practice into their curriculum, we argue that foundational ML principles should be taught to broadly to medical students across the country.

scholarly journals Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Andrew L. Beam ◽  
Uri Kartoun ◽  
Jennifer K. Pai ◽  
Arnaub K. Chatterjee ◽  
Timothy P. Fitzgerald ◽  
...  
Keyword(s):  
Decision Making ◽  
Predictive Modeling ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Sleep Medication ◽  
Physician Patient
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