scholarly journals One-Way Sensitivity Analysis for Probabilistic Cost-Effectiveness Analysis: Conditional Expected Incremental Net Benefit

2019 ◽  
Vol 38 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Christopher McCabe ◽  
Mike Paulden ◽  
Isaac Awotwe ◽  
Andrew Sutton ◽  
Peter Hall
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Cost Effectiveness Analysis ◽  
Net Benefit ◽  
Effectiveness Analysis ◽  
Incremental Net Benefit

OP34 One-Way Sensitivity Analysis For Cost Effectiveness Analysis

2019 ◽  
Vol 35 (S1) ◽  
pp. 8-8
Author(s):  
Christopher McCabe ◽  
Isaac Awotwe ◽  
Mike Paulden ◽  
Andrew Sutton ◽  
Peter Hall
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Stochastic Analysis ◽  
Cost Effectiveness Analysis ◽  
Decision Makers ◽  
Net Benefit ◽  
Effectiveness Analysis ◽  
Incremental Net Benefit ◽  
Parameter Values ◽  
The Impact

IntroductionAlthough stochastic analysis has become the accepted standard for decision analytic cost effectiveness models, deterministic one-way sensitivity analysis continues to be used to meet the needs of decision makers to understand the impact that changing the value taken by one specific parameter has on the results of the analysis. However, there are a number of problems with this approach.MethodsWe review the reasons why deterministic one-way sensitivity analysis will provide decision makers with biased and incomplete information. We then describe a new method - stochastic one-way sensitivity analysis (SOWSA), and apply this to a previously published cost effectiveness analysis, to produce a stochastic tornado diagram and conditional incremental net benefit curve. We then discuss how these outputs should be interpreted and the potential barriers to the implementation of SOWSA.ResultsThe results illustrate the shortcomings of the current approaches to deterministic one-way sensitivity analysis. For SOWSA, the expected costs and outcomes are captured, along with the sampled value of the parameter and these are linked to the probability that the parameter takes that value – which can be read off the probability distribution for the parameter used in the stochastic analysis. From these results it is possible to gain insights into probability that a parameter will take a value that will change a decision.ConclusionsAlthough a well-used technique, one-way deterministic sensitivity analysis has a number of shortcomings that may contribute to incorrect conclusions being drawn about the importance of certain parameter values on model results. By providing fuller information on uncertainty in model results, it is hoped that the methods here will lead to more informed decision making. Although, as with all developments in the presentation of analytic results to decision makers, care will be required to ensure that the decision makers understand the information provided to them.

Complementing the net benefit approach: A new framework for Bayesian cost-effectiveness analysis

2009 ◽  
Vol 25 (4) ◽  
pp. 537-545 ◽  
Author(s):  
Miguel Angel Negrín Hernández ◽  
Francisco José Vázquez-Polo ◽  
Francisco Javier Girón González-Torre ◽  
Elías Moreno Bas
Keyword(s):  
Cost Effectiveness ◽  
Real Data ◽  
Cost Effectiveness Analysis ◽  
Net Benefit ◽  
Underlying Distribution ◽  
Effectiveness Analysis ◽  
Incremental Net Benefit ◽  
The Mean ◽  
High Degree ◽  
New Framework

Objectives: The aim of cost-effectiveness analysis is to maximize health benefits from a given budget, taking a societal perspective. Consequently, the comparison of alternative treatments or technologies is solely based on their expected effectiveness and cost. However, the expectation, or mean, poses important limitations as it might be a poor summary of the underlying distribution, for instance when the effectiveness is a categorical variable, or when the distributions of either effectiveness or cost present a high degree of asymmetry. Clinical variables often present these characteristics.Methods: In this study, we present a framework for cost-effectiveness analysis based on the whole posterior distribution of effectiveness and cost.Results: An application with real data is included to illustrate the analysis. Decision-making measures such as the incremental cost-effectiveness ratio, incremental net-benefit, and cost-effectiveness acceptability curves, can also be defined under the new framework.Conclusions: This framework overcomes limitations of the mean and offers complementary information for the decision maker.

Cost-Effectiveness Analysis of Active Surveillance Screening for Methicillin-Resistant Staphylococcus aureus in an Academic Hospital Setting

2012 ◽  
Vol 33 (5) ◽  
pp. 477-486 ◽  
Author(s):  
JaHyun Kang ◽  
Paul Mandsager ◽  
Andrea K. Biddle ◽  
David J. Weber
Keyword(s):  
Staphylococcus Aureus ◽  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Active Surveillance ◽  
Hospital Setting ◽  
Cost Effective ◽  
Dominant Strategy ◽  
Cost Effectiveness Analysis ◽  
Academic Hospital ◽  
Effectiveness Analysis

Objective.To evaluate the cost-effectiveness of 3 alternative active screening strategies for methicillin-resistant Staphylococcus aureus (MRSA): universal surveillance screening for all hospital admissions, targeted surveillance screening for intensive care unit admissions, and no surveillance screening.Design.Cost-effectiveness analysis using decision modeling.Methods.Cost-effectiveness was evaluated from the perspective of an 800-bed academic hospital with 40,000 annual admissions over the time horizon of a hospitalization. All input probabilities, costs, and outcome data were obtained through a comprehensive literature review. Effectiveness outcome was MRSA healthcare-associated infections (HAIs). One-way and probabilistic sensitivity analyses were conducted.Results.In the base case, targeted surveillance screening was a dominant strategy (ie, was associated with lower costs and resulted in better outcomes) for preventing MRSA HAL Universal surveillance screening was associated with an incremental cost-effectiveness ratio of $14,955 per MRSA HAL In one-way sensitivity analysis, targeted surveillance screening was a dominant strategy across most parameter ranges. Probabilistic sensitivity analysis also demonstrated that targeted surveillance screening was the most cost-effective strategy when willingness to pay to prevent a case of MRSA HAI was less than $71,300.Conclusion.Targeted active surveillance screening for MRSA is the most cost-effective screening strategy in an academic hospital setting. Additional studies that are based on actual hospital data are needed to validate this model. However, the model supports current recommendations to use active surveillance to detect MRSA.

scholarly journals The Impact of Outliers on Net-Benefit Regression Model in Cost-Effectiveness Analysis

PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e65930 ◽  
Author(s):  
Yu-Wen Wen ◽  
Yi-Wen Tsai ◽  
David Bin-Chia Wu ◽  
Pei-Fen Chen
Keyword(s):  
Cost Effectiveness ◽  
Regression Model ◽  
Cost Effectiveness Analysis ◽  
Net Benefit ◽  
Effectiveness Analysis ◽  
The Impact

scholarly journals Correction to: Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial

2019 ◽  
Vol 37 (7) ◽  
pp. 971-971
Author(s):  
Baptiste Leurent ◽  
Manuel Gomes ◽  
Rita Faria ◽  
Stephen Morris ◽  
Richard Grieve ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Missing Data ◽  
Cost Effectiveness Analysis ◽  
Effectiveness Analysis

Cost Effectiveness Analysis of Antipsychotic Medications in the Management of Schizophrenia in Benin City

2019 ◽  
Vol 1 (1) ◽  
pp. 46-56
Author(s):  
J.W. Edefo ◽  
◽  
S.F. Usifoh ◽  
A.W. Udezi ◽  
◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Rating Scale ◽  
Response Rate ◽  
Cost Effective ◽  
Cost Effectiveness Analysis ◽  
Antipsychotic Medications ◽  
Stable Relationship ◽  
Effectiveness Analysis ◽  
The Impact

Background: Studies on cost effectiveness analysis (CEA) of typical versus atypical antipsychotics in the management of schizophrenia are still lacking in Nigeria thus the objectives of this study are to determine which of the class of antipsychotics is more cost-effective as well as the impact of socio-demographic factors on the response rate to antipsychotics. Method: The effectiveness was measured by Brief Psychiatric rating scale (BPRS) and costs were in Nigerian naira (NGN). The impact of different socio-demographics on the mean BPRScore ± Standard deviation (SD) reduction was determined. The study was conducted from patient’s perspective with decision tree analysis model using two-way sensitivity analysis. The model was used to explore incremental cost effectiveness ratios (ICER) of oral antipsychotic medications Haloperidol /Trifluoperazine versus Olanzepine /Risperidone over a 24-week study period. Results: Cost effectiveness analysis with 1st scenario sensitivity test of medications, trifluoperazine 17.81±2.51mg is more cost effective than olanzapine 10mg, while haloperidol 10mg is more cost effective than risperidone 3.5± 0.51mg. In the second scenario of sensitivity analysis, olanzapine is more cost effective than trifluoperazine only when the savings of making one person free from schizophrenia in a month is worth more than NGN537 while risperidone is more cost effective than haloperidol only when the savings of making one person free from schizophrenia in a month is worth more than NGN2524.1. The effect on response rate to antipsychotics gave p=0.0251, P=0.009, P<0.0001 for educational status, income, stable relationship respectively. Conclusion: Atypical antipsychotic medications are not more cost effective compared to the typical antipsychotics. Higher educational level, income and stable relationship positively affected the outcome of effectiveness of antipsychotics.

scholarly journals RM1 - SENSITIVITY ANALYSIS FOR NOT-AT-RANDOM MISSING DATA IN TRIAL-BASED COST-EFFECTIVENESS ANALYSIS USING MULTIPLE IMPUTATION

2018 ◽  
Vol 21 ◽  
pp. S14
Author(s):  
B. Leurent ◽  
M. Gomes ◽  
R. Faria ◽  
S. Morris ◽  
R. Grieve ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Missing Data ◽  
Multiple Imputation ◽  
Cost Effectiveness Analysis ◽  
Effectiveness Analysis
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