Clinical outcome assessment in mental health

2018 ◽  
pp. 191-200
Author(s):  
Skye P. Barbic ◽  
Stefan J. Cano
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Clinical Outcome ◽  
Outcome Assessment ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Based ◽  
Measurement Issues ◽  
Health Disorders ◽  
Based Medicine

Clinical outcome assessment (COA) in mental health is essential to inform patient-centred care and clinical decision-making. In this chapter, the reader is introduced to COA as it is evolving in the field of mental health. Multiple approaches to COA are presented, but emphasis is placed on approaches that generate clinically meaningful data. Understanding COA can position clinicians and stakeholders to better evaluate their own practice and to contribute to the ongoing evolution of COA research and evidence-based medicine. This chapter begins with the definitions of assessment and measurement. Conceptual frameworks and models of COA development and testing are then presented. These are followed by a discussion of measurement in practice that reviews measurement issues related to clinical decision-making, programme evaluation, and clinical trials. Finally, this chapter highlights the contribution of metrology to improving health outcomes of individuals who experience mental health disorders.

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.

The ‘Number Needed to Treat’ and the ‘Adjusted NNT’ in Health Care Decision-Making

1998 ◽  
Vol 3 (1) ◽  
pp. 44-49 ◽  
Author(s):  
Jack Dowie
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Evidence Based Medicine ◽  
Clinical Decision Making ◽  
Treatment Options ◽  
Clinical Decision ◽  
Population Based ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Based Medicine

Within ‘evidence-based medicine and health care’ the ‘number needed to treat’ (NNT) has been promoted as the most clinically useful measure of the effectiveness of interventions as established by research. Is the NNT, in either its simple or adjusted form, ‘easily understood’, ‘intuitively meaningful’, ‘clinically useful’ and likely to bring about the substantial improvements in patient care and public health envisaged by those who recommend its use? The key evidence against the NNT is the consistent format effect revealed in studies that present respondents with mathematically-equivalent statements regarding trial results. Problems of understanding aside, trying to overcome the limitations of the simple (major adverse event) NNT by adding an equivalent measure for harm (‘number needed to harm’ NNH) means the NNT loses its key claim to be a single yardstick. Integration of the NNT and NNH, and attempts to take into account the wider consequences of treatment options, can be attempted by either a ‘clinical judgement’ or an analytical route. The former means abandoning the explicit and rigorous transparency urged in evidence-based medicine. The attempt to produce an ‘adjusted’ NNT by an analytical approach has succeeded, but the procedure involves carrying out a prior decision analysis. The calculation of an adjusted NNT from that analysis is a redundant extra step, the only action necessary being comparison of the results for each option and determination of the optimal one. The adjusted NNT has no role in clinical decision-making, defined as requiring patient utilities, because the latter are measurable only on an interval scale and cannot be transformed into a ratio measure (which the adjusted NNT is implied to be). In any case, the NNT always represents the intrusion of population-based reasoning into clinical decision-making.

Challenges to Evidence-Based Prescribing in Clinical Practice

2008 ◽  
Vol 42 (5) ◽  
pp. 704-707 ◽  
Author(s):  
Muhammad Mamdani ◽  
Andrew Ching ◽  
Brian Golden ◽  
Magda Melo ◽  
Ulrich Menzefricke
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Patient Preferences ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Based ◽  
Competing Demands ◽  
Drug Policies ◽  
Clinical Conditions ◽  
Based Medicine

Although there appears to be widespread support of evidence-based medicine as a basis for rational prescribing, the challenges to it are signilicant and often justified. A multitude of factors other than evidence drive clinical decision-making, including patient preferences and social circumstances, presence of diseasedrug and drug-drug interactions, clinical experience, competing demands from more pressing clinical conditions, marketing and promotional activity, and systemlevel drug policies.

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