Individual quality of life: adaptive conjoint analysis as an alternative for direct weighting?

Epidemiological Modeling of the Impact of Public Health Policies on Hepatitis C: Protocol for a Gamification Tool Targeting Microelimination

BACKGROUND

Hepatitis C is a disease with a strong social component, as its main transmission route is via blood, making it associated with lifestyle. Therefore, it is suitable to be worked on from the perspective of public health policy, which still has a lot of room to explore and improve, contrary to diagnoses and treatments, which are already very refined and effective.

OBJECTIVE

An interactive gamified policy tool, designated as Let's End HepC (LEHC), was created to understand the impact of policies related to hepatitis C on the disease's epidemiology on a yearly basis until 2030.

METHODS

To this end, an innovative epidemiological model was developed, integrating Markov chains to model the natural history of the disease and adaptive conjoint analysis to reflect the degree of application of each of the 24 public health policies included in the model. This double imputation model makes it possible to assess a set of indicators such as liver transplant, incidence, and deaths year by year until 2030 in different risk groups. Populations at a higher risk were integrated into the model to understand the specific epidemiological dynamics within the total population of each country and within segments that comprise people who have received blood products, prisoners, people who inject drugs, people infected through vertical transmission, and the remaining population.

RESULTS

The model has already been applied to a group of countries, and studies in 5 of these countries have already been concluded, showing results very close to those obtained through other forms of evaluation.

CONCLUSIONS

The LEHC model allows the simulation of different degrees of implementation of each policy and thus the verification of its epidemiological impact on each studied population. The gamification feature allows assessing the adequate fulfillment of the World Health Organization goals for the elimination of hepatitis C by 2030. LEHC supports health decision makers and people who practice patient advocacy in making decisions based on science, and because LEHC is democratically shared, it ends up contributing to the increase of citizenship in health.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/38521.

Patient preferences as human factors for health data recommender systems and shared decision making in orthopaedic practice

Background

A core set of requirements for designing AI-based Health Recommender Systems (HRS) is a thorough understanding of human factors in a decision-making process. Patient preferences regarding treatment outcomes can be one important human factor. For orthopaedic medicine, limited communication may occur between a patient and a provider during the short duration of a clinical visit, limiting the opportunity for the patient to express treatment outcome preferences (TOP). This may occur despite patient preferences having a significant impact on achieving patient satisfaction, shared decision making and treatment success. Inclusion of patient preferences during patient intake and/or during the early phases of patient contact and information gathering can lead to better treatment recommendations.

Aim

We aim to explore patient treatment outcome preferences as significant human factors in treatment decision making in orthopedics. The goal of this research is to design, build, and test an app that collects baseline TOPs across orthopaedic outcomes and reports this information to providers during a clinical visit. This data may also be used to inform the design of HRSs for orthopaedic treatment decision making.

Methods

We created a mobile app to collect TOPs using a direct weighting (DW) technique. We used a mixed methods approach to pilot test the app with 23 first-time orthopaedic visit patients presenting with joint pain and/or function deficiency by presenting the app for utilization and conducting qualitative interviews and quantitative surveys post utilization.

Results

The study validated five core TOP domains, with most users dividing their 100-point DW allocation across 1-3 domains. The tool received moderate to high usability scores. Thematic analysis of patient interviews provides insights into TOPs that are important to patients, how they can be communicated effectively, and incorporated into a clinical visit with meaningful patient-provider communication that leads to shared decision making.

Conclusion

Patient TOPs may be important human factors to consider in determining treatment options that may be helpful for automating patient treatment recommendations. We conclude that inclusion of patient TOPs to inform the design of HRSs results in creating more robust patient treatment profiles in the EHR thus enhancing opportunities for treatment recommendations and future AI applications.

Let's End HepC: Modelling Public Health Epidemiological Policies Applied to Hepatitis C in Spain

Background: The WHO has defined international targets toward the elimination of hepatitis C by 2030. Most countries cannot be on track to achieve this goal unless many challenges are surpassed. The Let's End HepC (LEHC) tool aims to contribute to the control of hepatitis C. The innovation of this tool combines the modelling of public health policies (PHP) focused on hepatitis C with epidemiological modelling of the disease, obtaining a unique result that allows to forecast the impact of policy outcomes. The model was applied to several countries, including Spain.

Methods: To address the stated objective, we applied the “Adaptive Conjoint Analysis” for PHP decision-making and Markov Chains in the LEHC modelling tool. The tool also aims to be used as an element of health literacy for patient advocacy through gamification mechanisms and country comparability. The LEHC project has been conducted in several countries, including Spain. The population segments comprised in the project are: People Who Inject Drugs (PWID), prisoners, blood products, remnant population.

Results: A total of 24 PHP related to hepatitis C were included in the LEHC project. It was identified that Spain had fully implemented 14 of those policies to control hepatitis C. According to LEHC's model forecast, the WHO's Hepatitis C elimination goal on reducing the number of patients living with Hepatitis C to 10% can be achieved in Spain by 2026 if current policies are maintained. The model estimates that the total population in Spain, by 2026, is expected to comprise 26,367 individuals living with hepatitis C. Moreover, if the 24 PHP considered for this study are fully implemented in Spain, the elimination goal may be achieved in 2024, with 29,615 individuals living with hepatitis C by that year.

Conclusion: The findings corroborate the view that Spain has set great efforts in directing PHP toward Hepatitis C Virus (HCV) elimination by 2030. However, there is still room for improvement, namely in further implementing 10 of the 24 PHP considered for the LEHC project. By maintaining the 14 PHP in force, the LEHC model estimates the HCV elimination in the country by 2026, and by 2024 if further measures are employed to control the disease.

VASMA Weighting: Survey-Based Criteria Weighting Methodology that Combines ENTROPY and WASPAS-SVNS to Reflect the Psychometric Features of the VAS Scales

Data symmetry and asymmetry might cause difficulties in various areas including criteria weighting approaches. Preference elicitation is an integral part of the multicriteria decision-making process. Weighting approaches differ in terms of accuracy, ease of use, complexity, and theoretical foundations. When the opinions of the wider audience are needed, electronic surveys with the matrix questions consisting of the visual analogue scales (VAS) might be employed as the easily understandable data collection tool. The novel criteria weighting technique VASMA weighting (VAS Matrix for the criteria weighting) is presented in this paper. It respects the psychometric features of the VAS scales and analyzes the uncertainties caused by the survey-based preference elicitation. VASMA weighting integrates WASPAS-SVNS for the determination of the subjective weights and Shannon entropy for the calculation of the objective weights. Numerical example analyzing the importance of the criteria that affect parents’ decisions regarding the choice of the kindergarten institution was performed as the practical application. Comparison of the VASMA weighting and the direct rating (DR) methodologies was done. It revealed that VASMA weighting is able to overcome the main disadvantages of the DR technique—the high biases of the collected data and the low variation of the criteria weights.

A critical review of scoring options for clinical measurement tools

BACKGROUND

The aim of this paper is twofold: (1) to describe the fundamental differences between formative and reflective measurement models, and (2) to review the options proposed in the literature to obtain overall instrument summary scores, with a particular focus on formative models.

METHODS

An extensive literature search was conducted using the following databases: MEDLINE, EMBASE, PsycINFO, CINAHL and ABI/INFORM, using "formative" and "reflective" as text words; relevant articles' reference lists were hand searched.

RESULTS

Reflective models are most frequently scored by means of simple summation, which is consistent with the theory underlying these models. However, our review suggests that formative models might be better summarized using weighted combinations of indicators, since each indicator captures unique features of the underlying construct. For this purpose, indicator weights have been obtained using choice-based, statistical, researcher-based, and combined approaches.

CONCLUSION

Whereas simple summation is a theoretically justified scoring system for reflective measurement models, formative measures likely benefit from the use of weighted scores that preserve the contribution of each of the aspects of the construct.

Discrete choice experiments in health economics: a review of the literature

BACKGROUND

Discrete choice experiments (DCEs) are increasingly used in health economics to address a wide range of health policy-related concerns.

OBJECTIVE

Broadly adopting the methodology of an earlier systematic review of health-related DCEs, which covered the period 2001-2008, we report whether earlier trends continued during 2009-2012.

METHODS

This paper systematically reviews health-related DCEs published between 2009 and 2012, using the same database as the earlier published review (PubMed) to obtain citations, and the same range of search terms.

RESULTS

A total of 179 health-related DCEs for 2009-2012 met the inclusion criteria for the review. We found a continuing trend towards conducting DCEs across a broader range of countries. However, the trend towards including fewer attributes was reversed, whilst the trend towards interview-based DCEs reversed because of increased computer administration. The trend towards using more flexible econometric models, including mixed logit and latent class, has also continued. Reporting of monetary values has fallen compared with earlier periods, but the proportion of studies estimating trade-offs between health outcomes and experience factors, or valuing outcomes in terms of utility scores, has increased, although use of odds ratios and probabilities has declined. The reassuring trend towards the use of more flexible and appropriate DCE designs and econometric methods has been reinforced by the increased use of qualitative methods to inform DCE processes and results. However, qualitative research methods are being used less often to inform attribute selection, which may make DCEs more susceptible to omitted variable bias if the decision framework is not known prior to the research project.

CONCLUSIONS

The use of DCEs in healthcare continues to grow dramatically, as does the scope of applications across an expanding range of countries. There is increasing evidence that more sophisticated approaches to DCE design and analytical techniques are improving the quality of final outputs. That said, recent evidence that the use of qualitative methods to inform attribute selection has declined is of concern.

Hearing loss in older critical care patients: participation in decision making

Older adults with hearing loss who receive care in the noisy environment of a critical care unit can be disadvantaged in their ability to understand speech, thus limiting their participation in decision making. Providing optimal outcomes for such patients can be understood through use of the American Association of Critical-Care Nurses Synergy Model. When older adults are admitted to a critical care unit, their spouses, children, and friends are in positions to participate in the patients' care. The AACN Synergy Model patient characteristic of participation in care is useful in enhancing optimal outcomes for older patients.

Methodologic evaluation of adaptive conjoint analysis to assess patient preferences: an application in oncology

BACKGROUND

Adaptive conjoint analysis (ACA) is an individually tailored preferences elicitation technique that mimics actual decision-making processes by asking participants to make trade-offs between the various dimensions that underlie decision problems. ACA is increasingly applied in patient preferences assessments but formal evaluation of its validity and reliability is lacking.

OBJECTIVE

To investigate ACA's validity and reliability in elicitation of treatment outcome preferences.

METHODS

Sixty-eight disease-free rectal cancer patients, treated with surgery with or without preoperative radiotherapy were asked to complete exercises to assess their preferences for radiotherapy [using the treatment trade-off method (TTM)] and for key outcomes associated with radiotherapy (using ACA). We assessed (i) rank ordering of ACA-derived outcome-probability utilities, (ii) compensatory decision making, (iii) ACA test-retest reliability, and (iv) concordance of ACA- and TTM-based preferences.

RESULTS

All participants completed the TTM and 66 completed the ACA questionnaire, in 15 min on average. Outcome utilities were rank ordered in agreement with probabilities from best to worst in most participants, except for sexual dysfunction. Most participants were willing to trade survival and their most important outcome. Mean importance ratings were similar at retest. ACA- and TTM-based preferences differed. TTM-based preferences were related to past treatment, ACA-based preferences were not.

CONCLUSIONS

ACA assesses group-level preferences reliably over time and captures individual preferences independently from treatment experience in treated cancer patients. ACA seems a valid treatment outcome preference elicitation method in a context in which trade-offs between cure and quality of life need to be considered.

Adaptive choice-based conjoint analysis: a new patient-centered approach to the assessment of health service preferences

Conjoint analysis (CA) has emerged as an important approach to the assessment of health service preferences. This article examines Adaptive Choice-Based Conjoint Analysis (ACBC) and reviews available evidence comparing ACBC with conventional approaches to CA. ACBC surveys more closely approximate the decision-making processes that influence real-world choices. Informants begin ACBC surveys by completing a build-your-own (BYO) task identifying the level of each attribute that they prefer. The ACBC software composes a series of attribute combinations clustering around each participant's BYO choices. During the Screener section, informants decide whether each of these concepts is a possibility or not. Probe questions determine whether attribute levels consistently included in or excluded from each informant's Screener section choices reflect 'Unacceptable' or 'Must Have' simplifying heuristics. Finally, concepts identified as possibilities during the Screener section are carried forward to a Choice Tournament. The winning concept in each Choice Tournament set advances to the next choice set until a winner is determined.A review of randomized trials and cross-over studies suggests that, although ACBC surveys require more time than conventional approaches to CA, informants find ACBC surveys more engaging. In most studies, ACBC surveys yield lower standard errors, improved prediction of hold-out task choices, and better estimates of real-world product decisions than conventional choice-based CA surveys.

Effect of adaptive abilities on utilities, direct or mediated by mental health?

Background

In cost-utility analyses gain in health can be measured using health state utilities. Health state utilities can be elicited from members of the public or from patients. Utilities given by patients tend to be higher than utilities given by members of the public. This difference is often suggested to be explained by adaptation, but this has not yet been investigated in patients. Here, we investigate if, besides health related quality of life (HRQL), persons' ability to adapt can explain health state utilities. Both the direct effect of persons' adaptive abilities on health state utilities and the indirect effect, where HRQL mediates the effect of ability to adapt, are examined.

Methods

In total 125 patients with Rheumatoid Arthritis were interviewed. Participants gave valuations of their own health on a visual analogue scale (VAS) and time trade-off (TTO). To estimate persons' ability to adapt, patients filled in questionnaires measuring Self-esteem, Mastery, and Optimism. Finally they completed the SF-36 measuring HRQL. Regression analyses were used to investigate the direct and mediated effect of ability to adapt on health state utilities.

Results

Persons' ability to adapt did not add considerably to the explanation of health state utilities above HRQL. In the TTO no additional variance was explained by adaptive abilities (Δ R² = .00, β = .02), in the VAS a minor proportion of the variance was explained by adaptive abilities (Δ R² = .05, β = .33). The effect of adaptation on health state utilities seems to be mediated by the mental health domain of quality of life.

Conclusions

Patients with stronger adaptive abilities, based on their optimism, mastery and self-esteem, may more easily enhance their mental health after being diagnosed with a chronic illness, which leads to higher health state utilities.

Preferences of diabetes patients and physicians: a feasibility study to identify the key indicators for appraisal of health care values

BACKGROUND

Evidence-based medicine, the Institute of Medicine (IOM) and the German Institute for Quality and Efficiency in Health Care (IQWiG), support the inclusion of patients' preferences in health care decisions. In fact there are not many trials which include an assessment of patient's preferences. The aim of this study is to demonstrate that preferences of physicians and of patients can be assessed and that this information may be helpful for medical decision making.

METHOD

One of the established methods for assessment of preferences is the conjoint analysis. Conjoint analysis, in combination with a computer assisted telephone interview (CATI), was used to collect data from 827 diabetes patients and 60 physicians, which describe the preferences expressed as levels of four factors in the management and outcome of the disease. The first factor described the main treatment effect (reduction of elevated HbA1c, improved well-being, absence of side effects, and no limitations of daily life). The second factor described the effect on the body weight (gain, no change, reduction). The third factor analyzed the mode of application (linked to meals or flexible application). The fourth factor addressed the type of product (original brand or generic product). Utility values were scaled and normalized in a way that the sum of utility points across all levels is equal to the number of attributes (factors) times 100.

RESULTS

The preference weights confirm that the reduction of body weight is at least as important for patients--especially obese patients--and physicians as the reduction of an elevated HbA1c. Original products were preferred by patients while general practitioners preferred generic products.

CONCLUSION

Using the example of diabetes, the difference between patients' and physicians' preferences can be assessed. The use of a conjoint analysis in combination with CATI seems to be an effective approach for generation of data which are needed for policy and medical decision making in health care.

Combining multicriteria decision analysis, ethics and health technology assessment: applying the EVIDEM decision-making framework to growth hormone for Turner syndrome patients

OBJECTIVES

To test and further develop a healthcare policy and clinical decision support framework using growth hormone (GH) for Turner syndrome (TS) as a complex case study.

METHODS

The EVIDEM framework was further developed to complement the multicriteria decision analysis (MCDA) Value Matrix, that includes 15 quantifiable components of decision clustered in four domains (quality of evidence, disease, intervention and economics), with a qualitative tool including six ethical and health system-related components of decision. An extensive review of the literature was performed to develop a health technology assessment report (HTA) tailored to each component of decision, and content was validated by experts. A panel of representative stakeholders then estimated the MCDA value of GH for TS in Canada by assigning weights and scores to each MCDA component of decision and then considered the impact of non-quantifiable components of decision.

RESULTS

Applying the framework revealed significant data gaps and the importance of aligning research questions with data needs to truly inform decision. Panelists estimated the value of GH for TS at 41% of maximum value on the MCDA scale, with good agreement at the individual level (retest value 40%; ICC: 0.687) and large variation across panelists. Main contributors to this panel specific value were "Improvement of efficacy", "Disease severity" and "Quality of evidence". Ethical considerations on utility, efficiency and fairness as well as potential misuse of GH had mixed effects on the perceived value of the treatment.

CONCLUSIONS

This framework is proposed as a pragmatic step beyond the current cost-effectiveness model, combining HTA, MCDA, values and ethics. It supports systematic consideration of all components of decision and available evidence for greater transparency. Further testing and validation is needed to build up MCDA approaches combined with pragmatic HTA in healthcare decision-making.

The experience of using the SEIQoL-DW with patients with advanced chronic obstructive pulmonary disease (COPD): issues of process and outcome

PURPOSE

To report the experience of using the SEIQoL-DW for the measurement of quality of life with patients with advanced COPD and consider its feasibility, acceptability and appropriateness for a Phase III randomised controlled trial (RCT).

METHODS

The SEIQoL-DW was administered according to its instructions within a Phase II RCT 3-5 times per patient, across 13 patients and the process audio-recorded. Quantitative and qualitative criteria were used to assess feasibility, acceptability and appropriateness. Qualitative analysis of the transcripts and fieldwork notes was conducted using Framework Analysis.

RESULTS

The SEIQoL-DW steps (of identifying five quality of life cues, rating their functioning and importance) were completed at 48/51 interviews. However, some respondents were overwhelmed by the scripted introduction, experienced difficulty with cue identification, and focused only on certain types of cues (Step 1); some had difficulty interpreting and rating the concept of Step 2; and some had difficulty interpreting 'importance' and manipulating the SEIQoL-DW disc (Step 3).

CONCLUSIONS

Patients with advanced COPD were able to complete the SEIQoL-DW but analysis of its administration identified practical and conceptual concerns which question the validity of the results obtained. Suggestions for the development of the SEIQoL-DW and future feasibility studies are given.

Somatically ill persons' self-nominated quality of life domains: review of the literature and guidelines for future studies

OBJECTIVE

To review which domains somatically ill persons nominate as constituting their QoL. Specific objective is to examine whether the method of enquiry affect these domains.

METHODS

We conducted two literature searches in the databases PubMed/Medline, CINAHL and Psychinfo for qualitative studies examining patients' self-defined QoL domains using (1) SEIQoL and (2) study-specific questions. For each database, two researchers independently assessed the eligibility of the retrieved abstracts and three researchers subsequently classified all QoL domains.

RESULTS

Thirty-six eligible papers were identified: 27 studies using the SEIQoL, and nine presenting data derived from study-specific questions. The influence of the method of enquiry on patients' self-nominated QoL domains appears limited: most domains were presented in both types of studies, albeit with different frequencies.

CONCLUSIONS

This review provides a comprehensive overview of somatically ill persons' self-nominated QoL domains. However, limitations inherent to reviewing qualitative studies (e.g., the varying level of abstraction of patients' self-defined QoL domains), limitations of the included studies and limitations inherent to the review process, hinder cross-study comparisons. Therefore, we provide guidelines to address shortcomings of qualitative reports amenable to improvement and to stimulate further improvement of conducting and reporting qualitative research aimed at exploring respondents' self-nominated QoL domains.