Estimation of the Width of Uncertainty in Care Consumption and Costs When Using Common Data Collection Tools in Economic Evaluations: A Benchmark for Sensitivity Analyses

2021 ◽  
Author(s):  
Laure Daval ◽  
Arnaud Nze Ossima ◽  
Marie-Caroline Clément ◽  
Morgane Michel ◽  
Karine Chevreul
Keyword(s):  
Data Collection ◽  
Sensitivity Analyses ◽  
Economic Evaluations

Telestroke for acute ischaemic stroke: A systematic review of economic evaluations and a de novo cost–utility analysis for a middle income country

2021 ◽  
pp. 1357633X2110324
Author(s):  
Elise Tan ◽  
Lan Gao ◽  
Huong NQ Tran ◽  
Dominique Cadilhac ◽  
Chris Bladin ◽  
...  
Keyword(s):  
Systematic Review ◽  
Ischaemic Stroke ◽  
Acute Ischaemic Stroke ◽  
Rural China ◽  
Stroke Care ◽  
Cost Utility ◽  
Cost Utility Analysis ◽  
Sensitivity Analyses ◽  
Economic Evaluations ◽  
Utility Analysis

Introduction Telemedicine can alleviate the problems faced in rural settings in providing access to specialist stroke care. The evidence of the cost-effectiveness of this model of care outside high-income countries is limited. This study aimed to conduct: (a) a systematic review of economic evaluations of telestroke and (b) a cost–utility analysis of telestroke, using China as a case study. Methods We systematically searched Embase, Medline Complete and Cochrane databases. Inclusion criteria: full economic evaluations of telemedicine/telestroke networks examining the use of thrombolysis in patients with acute ischaemic stroke, published in English. A cost–utility analysis was undertaken using a Markov model incorporating a decision tree to simulate the delivery of telestroke for acute ischaemic stroke in rural China, compared to no telestroke from a societal and healthcare perspective. One-way deterministic sensitivity analyses and probabilistic sensitivity analyses were performed to test the robustness of results. Results Of 559 publications found, eight met the eligibility criteria and were included in the systematic review (two cost-effectiveness analyses and six cost–utility analyses, all performed in high-income countries). Telestroke was a cost-saving/cost-effective intervention in five out of the eight studies. In our modelled analysis for rural China, telestroke was the dominant strategy, with estimated cost savings of Chinese yuan 4,328 (US$627) and additional 0.0925 quality-adjusted life years per patient. Sensitivity analyses confirmed the base case results. Discussion Consistent with published economic evaluations of telestroke in other jurisdictions, telestroke represents a cost-effective solution to enhance stroke care in rural China.

scholarly journals Noncompliance and Missing Data in Health Economic Evaluation

2019 ◽  
Author(s):  
Karla DiazOrdaz ◽  
Richard Grieve
Keyword(s):  
Health Economic ◽  
Economic Evaluation ◽  
Missing Data ◽  
Causal Effect ◽  
Health Economic Evaluation ◽  
Specific Treatment ◽  
Model Specification ◽  
Sensitivity Analyses ◽  
Economic Evaluations ◽  
Random Assignment

Health economic evaluations face the issues of noncompliance and missing data. Here, noncompliance is defined as non-adherence to a specific treatment, and occurs within randomized controlled trials (RCTs) when participants depart from their random assignment. Missing data arises if, for example, there is loss-to-follow-up, survey non-response, or the information available from routine data sources is incomplete. Appropriate statistical methods for handling noncompliance and missing data have been developed, but they have rarely been applied in health economics studies. Here, we illustrate the issues and outline some of the appropriate methods with which to handle these with application to health economic evaluation that uses data from an RCT. In an RCT the random assignment can be used as an instrument-for-treatment receipt, to obtain consistent estimates of the complier average causal effect, provided the underlying assumptions are met. Instrumental variable methods can accommodate essential features of the health economic context such as the correlation between individuals’ costs and outcomes in cost-effectiveness studies. Methodological guidance for handling missing data encourages approaches such as multiple imputation or inverse probability weighting, which assume the data are Missing At Random, but also sensitivity analyses that recognize the data may be missing according to the true, unobserved values, that is, Missing Not at Random. Future studies should subject the assumptions behind methods for handling noncompliance and missing data to thorough sensitivity analyses. Modern machine-learning methods can help reduce reliance on correct model specification. Further research is required to develop flexible methods for handling more complex forms of noncompliance and missing data.

Pharmacoeconomics for Dermatologists: An Introduction

1997 ◽  
Vol 1 (3) ◽  
pp. 185-189
Author(s):  
Aditya K. Gupta ◽  
Paul I. Oh ◽  
Neil H. Shear
Keyword(s):  
Health Care ◽  
Medical Literature ◽  
Treatment Options ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Economic Evaluations ◽  
Therapeutic Decision ◽  
Therapeutic Decision Making ◽  
Care Decision ◽  
Selection Of

Background: The budgets available for health care are becoming constrained and health care decision makers have increasingly begun to scrutinize cost along with efficacy, tolerability, and cost of the different treatment options for each disease state. In keeping with the above, there has been a marked increase in the number of pharmacoeconomic evaluations published in the medical literature, including dermatology journals. Methods: Comprehensive economic evaluations systematically consider the following: statement of question, defining relevant costs, perspective and time-horizon, synthesis of data on efficacy and effectiveness, and selection of the appropriate analytic type and framework. The conclusions should be tested through extensive sensitivity analyses. Conclusions: Economic evaluations are becoming more prevalent in the field of dermatology. A well-constructed analysis may be an aid to more rational therapeutic decision-making.

scholarly journals Estimating indirect costs in a pediatric trial: patient diaries and interview data collection

2019 ◽  
Author(s):  
Anaïs LE JEANNIC ◽  
Hassani Maoulida ◽  
Sophie Guilmin-Crépon ◽  
Corinne Alberti ◽  
Nadia Tubiana-Rufi ◽  
...  
Keyword(s):  
Case Report ◽  
Data Collection ◽  
Children And Adolescents ◽  
Real Time ◽  
Controlled Trial ◽  
Indirect Costs ◽  
Economic Evaluations ◽  
Case Report Form

Abstract Background: In France the pertinence of including indirect costs in economic evaluations of therapeutic strategies is left to author judgment. However productivity losses represent a significant amount of resources in particular for chronic pediatric conditions when caregivers are involved in addition to patients. In order to explore how best to collect indirect cost information, we investigated whether or not a patient diary provided additional information compared to retrospective investigator-led interviews and whether a diary filled intermittently produced more or less information than a continuous diary. The main objective of this study was to identify which type of data collection was most effective to obtain information on indirect costs over a 9-month study period. Methods : Start-In! is a randomized controlled trial comparing the efficacy of three strategies of real-time continuous glucose monitoring (CGM) for 12 months in children and adolescents with type 1 diabetes. We designed an ancillary study to compare three collection methods of indirect costs: 1) retrospectively by investigators during quarterly follow up visits and prospectively with diaries filled by children or families used 2) either continuously or 3) intermittently. Were collected the amount of information on absence from school and work, and carer time for diabetes cares, and compared to the information given to the investigator during the quarterly follow up visit in the case report form. Results: At the end of the 9-month study 42% participants had not returned their diary, less than 10% of data were collected in patients’ diaries versus 82% in investigators’ filled case report forms. Conclusions: Our study only supports the hypothesis that data collection by investigators during quarterly visits would lead to fewer missing data than a diary, that it be filled up on a trimester or every three months. Diaries might represent an important additional burden to children and their families. Trial registration: Start-In! trial registry name: Study of Insulin Therapy Augmented by Real Time Sensor IN Type 1 Children and Adolescents (START-IN!). ClinicalTrials.gov Identifier: NCT00949221. Registered on July 30, 2009.

scholarly journals A Systematic Review of the Methodological Quality of Economic Evaluations in Genetic Screening and Testing for Monogenic Disorders

2021 ◽  
Author(s):  
Karl Johnson ◽  
Kate Saylor ◽  
Isabella Guynn ◽  
Karen Hicklin ◽  
Jonathan S Berg ◽  
...  
Keyword(s):  
Systematic Review ◽  
Genetic Screening ◽  
Methodological Quality ◽  
Sensitivity Analyses ◽  
Economic Evaluations ◽  
Parameter Estimates ◽  
Alternative Interventions ◽  
Individual Level ◽  
Monogenic Disorders ◽  
Meta Analyses

Purpose: Understanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examine opportunities for improvement. Methods: We searched Pubmed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the BMJ checklist. Results: Across 47 identified studies, there was substantial variation in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulation, comparing between two and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis. Conclusion: We describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection, (2) use of uncertainty/sensitivity analyses, and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.

scholarly journals Bias from questionnaire invitation and response in COVID-19 research: an example using ALSPAC

2021 ◽  
Vol 6 ◽  
pp. 184
Author(s):  
Alba Fernández-Sanlés ◽  
Daniel Smith ◽  
Gemma L Clayton ◽  
Kate Northstone ◽  
Alice R Carter ◽  
...  
Keyword(s):  
Young Adults ◽  
Data Collection ◽  
Longitudinal Studies ◽  
Item Response ◽  
Response Rates ◽  
Sensitivity Analyses ◽  
Observational Research ◽  
Related Factors ◽  
Parents And Children ◽  
Health Related

Background: Longitudinal studies are crucial for identifying potential risk factors for infection with, and consequences of, COVID-19, but relationships can be biased if they are associated with invitation and response to data collection. We describe factors relating to questionnaire invitation and response in COVID-19 questionnaire data collection in a multigenerational birth cohort (the Avon Longitudinal Study of Parents and Children, ALSPAC). Methods: We analysed online questionnaires completed between the beginning of the pandemic and easing of the first UK lockdown by participants with valid email addresses who had not actively disengaged from the study. We assessed associations of pre-pandemic sociodemographic, behavioural, anthropometric and health-related factors with: i) being sent a questionnaire; ii) returning a questionnaire; and iii) item response (for specific questions). Analyses were conducted in three cohorts: the index children born in the early 1990s (now young adults; 41 variables assessed), their mothers (35 variables) and the mothers’ partners (27 variables). Results: Of 14,849 young adults, 41% were sent a questionnaire, of whom 57% returned one. Item response was >95%. In this cohort, 78% of factors were associated with being sent a questionnaire, 56% with returning one, and, as an example of item response, 20% with keyworker status response. For instance, children from mothers educated to degree-level had greater odds of being sent a questionnaire (OR=5.59; 95% CI=4.87-6.41), returning one (OR=1.60; 95% CI=1.31-1.95), and responding to items (e.g., keyworker status OR=1.65; 95% CI=0.88-3.04), relative to children from mothers with fewer qualifications. Invitation and response rates and associations were similar in all cohorts. Conclusions: These results highlight the importance of considering potential biases due to non-response when using longitudinal studies in COVID-19 research and interpreting results. We recommend researchers report response rates and factors associated with invitation and response in all COVID-19 observational research studies, which can inform sensitivity analyses.

scholarly journals Factors Affecting the Adoption of Electronic Data Reporting and Outcomes Among Selected Central Cancer Registries of the National Program of Cancer Registries

2021 ◽  
pp. 921-932
Author(s):  
Florence K. L. Tangka ◽  
Patrick Edwards ◽  
Paran Pordell ◽  
Reda Wilson ◽  
Wendy Blumenthal ◽  
...  
Keyword(s):  
Information Technology ◽  
Data Collection ◽  
Data Quality ◽  
Technical Assistance ◽  
Cancer Registries ◽  
Economic Evaluations ◽  
National Program ◽  
Self Perception ◽  
Factors Affecting ◽  
Electronic Reporting

PURPOSE The CDC's National Program of Cancer Registries has expanded the use of electronic reporting to collect more timely information on newly diagnosed cancers. The adoption, implementation, and use of electronic reporting vary significantly among central cancer registries. We identify factors affecting the adoption of electronic reporting among these registries. METHODS Directors and data managers of nine National Program of Cancer Registries took part in separate 1-hour telephone interviews in early 2019. Directors were asked about their registry's key data quality goals; staffing, resources, and tools used to aid processes; their definition and self-perception of electronic reporting adoption; key helpers and challenges; and cost and sustainability implications for adoption of electronic reporting. Data managers were asked about specific data collection processes, software applications, electronic reporting adoption and self-perception, information technology infrastructure, and helpers and challenges to data collection and processing, data quality, and sustainability of approach. RESULTS Larger registries identified organizational capacity and technical expertise as key aides. Other help for implementing electronic reporting processes came from partnerships, funding availability, management support, legislation, and access to an interstate data exchange. Common challenges among lower adopters included lack of capacity at both registry and data source levels, insufficient staffing, and a lack of information technology or technical support. Other challenges consisted of automation and interoperability of software, volume of cases received, state political environment, and quality of data received. CONCLUSION Feedback from the formative evaluation yielded several useful solutions that can guide implementation of electronic reporting and help refine the technical assistance provided to registries. Our findings may help guide future process and economic evaluations of electronic reporting and identify best practices to strengthen registry operations.

scholarly journals Methods to Detect Low Quality Data and Its Implication for Psychological Research

2017 ◽  
Author(s):  
Erin Michelle Buchanan ◽  
John E. Scofield
Keyword(s):  
Data Collection ◽  
Response Times ◽  
Psychological Research ◽  
Sensitivity Analyses ◽  
Detection Methods ◽  
Quality Data ◽  
Screening Methods ◽  
Data Detection ◽  
Online Data ◽  
Survey Responses

Web-based data collection methods such as Amazon's Mechanical Turk (AMT) are an appealing option to recruit participants quickly and cheaply for psychological research. While concerns regarding data quality have emerged with AMT, several studies have exhibited that data collected via AMT are as reliable as traditional college samples and are often more diverse and representative of noncollege populations. The development of methods to screen for low quality data, however, has been less explored. Omitting participants based on simple screening methods in isolation, such as response time or attention checks may not be adequate identification methods, with an inability to delineate between high or low effort participants. Additionally, problematic survey responses may arise from survey automation techniques such as survey bots or automated form fillers. The current project developed low quality data detection methods while overcoming previous screening limitations. Multiple checks were employed, such as page response times, distribution of survey responses, the number of utilized choices from a given range of scale options, click counts, and manipulation checks. This method was tested on a survey taken with an easily available plug-in survey bot, as well as compared to data collected by human participants providing both high effort and randomized, or low effort, answers. Identified cases can then be used as part of sensitivity analyses to warrant exclusion from further analyses. This algorithm can be a promising tool to identify low quality or automated data via AMT or other online data collection platforms.

scholarly journals Development and implementation of a framework for estimating the economic benefits of an accessible and inclusive society

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emile Tompa ◽  
Amirabbas Mofidi ◽  
Arif Jetha ◽  
Pamela Lahey ◽  
Alexis Buettgen
Keyword(s):  
Expert Knowledge ◽  
Economic Benefits ◽  
Sensitivity Analyses ◽  
Economic Evaluations ◽  
Persons With Disabilities ◽  
Content Type ◽  
A Value ◽  
Potential Benefits ◽  
Using Data ◽  
Inclusive Society

PurposeTo develop a framework for estimating the economic benefits of an accessible and inclusive society and implement it for the Canadian context. The framework measures the gap between the current situation in terms of accessibility and inclusiveness, and a counterfactual scenario of a fully accessible and inclusive society.Design/methodology/approachThe method consists of three steps. First, the conceptual framework was developed based on a literature review and expert knowledge. Second, the magnitudes for each domain of the framework was estimated for the reference year 2017 using data from various sources. Third, several sensitivity analyses were run using different assumptions and scenarios.FindingsIt was estimated that moving to a fully accessible and inclusive society would create a value of $337.7bn (with a range of $252.8–$422.7bn) for Canadian society in the reference year of 2017. This is a sizeable proportion of gross domestic product (17.6%, with a range of 13.1–22.0%) and is likely a conservative estimate of the potential benefits.Originality/valueUnderstanding the magnitude of the economic benefits of an accessible and inclusive society can be extremely useful for governments, disability advocates and industry leaders as it provides invaluable information on the benefits of efforts, such as legislation, policies, programs and practices, to improve accessibility and inclusion of persons with disabilities. Furthermore, the total economic benefits and the benefits per person with a disability can serve as inputs in economic evaluations and impact assessments.

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