Choice Blindness and Health-State Choices among Adolescents and Adults

Influence of E-consultation on Intention of First-visit Patients to Select Medical Services: Based on a Scenario Survey (Preprint)

BACKGROUND

E-consultation is expected to improve the information level of patients, affect patients' subsequent judgments of medical services, and guide patients to make a reasonable medical selection in the future. Thus, it is important to understand the influence mechanism of e-consultation on patients' medical selection.

OBJECTIVE

This study aims to explore the changes in first-visit patients' understanding of disease and medical resources after e-consultation as well as the choice of follow-up medical services.

METHODS

Patients' medical selection before and after e-consultation was compared using a scenario survey. Based on the service characteristics of the e-consultation platform, representative simulation scenarios were determined, and parallel control groups were set up considering the order effect in comparison. Finally, a total of 4 scenario simulation questionnaires were designed. A total of 4164 valid questionnaires were collected through the online questionnaire collection platform. Patients' perception of disease severity, evaluation of treatment capacity of medical institutions, selection of hospitals and doctors, and other outcome indicators were tested to analyze the differences in patients' evaluation and choice of medical services before and after e-consultation. Additionally, the results' stability was tested by regression analysis.

RESULTS

In scenario 1 (mild case), before e-consultation, 14.1% (104/740) of participants considered their conditions as not serious. After e-consultation, 69.5% (539/775) of them considered their diseases as not serious. Furthermore, participants' evaluation of the disease treatment capacity of medical institutions at all levels had improved after using e-consultation. In scenario 3 (severe case), before e-consultation, 54.1% (494/913) of the participants believed their diseases were very serious. After e-consultation, 16.6% (157/945) considered their diseases were very serious. The evaluation of disease treatment capacity of medical institutions in nontertiary hospitals decreased, whereas that of tertiary hospitals improved. In both mild and severe cases, before e-consultation, all of the participants were inclined to directly visit the hospital. After e-consultation, more than 71.4% (553/775) of the patients with mild diseases chose self-treatment, whereas those with severe diseases still opted for a face-to-face consultation. After e-consultation, patients who were set on being treated in a hospital, regardless of the disease severity, preferred to select the tertiary hospitals. Of the patients with mild diseases who chose to go to a hospital, 25.7% (57/222) wanted to consult online doctors face-to-face. By contrast, 56.4% (506/897) of the severe cases wanted to consult online doctors face-to-face.

CONCLUSIONS

E-consultation can help patients accurately enhance their awareness of the disease and guide them to make a more reasonable medical selection. However, it is likely that e-consultation makes online medical services centralized. Additionally, the guiding effect of e-consultation is limited, and e-consultation needs to be combined with other supporting systems conducive to medical selection to play an improved role.

Preference Elicitation Techniques Used in Valuing Children's Health-Related Quality-of-Life: A Systematic Review

BACKGROUND AND OBJECTIVES

Valuing children's health states for use in economic evaluations is globally relevant and is of particular relevance in jurisdictions where a cost-utility analysis is the preferred form of analysis for decision making. Despite this, the challenges with valuing child health mean that there are many remaining questions for debate about the approach to elicitation of values. The aim of this paper was to identify and describe the methods used to value children's health states and the specific issues that arise in the use of these methods.

METHODS

We conducted a systematic search of electronic databases to identify studies published in English since 1990 that used preference elicitation methods to value child and adolescent (under 18 years of age) health states. Eligibility criteria comprised valuation studies concerning both child-specific patient-reported outcome measures and child health states defined in other ways, and methodological studies of valuation approaches that may or may not have yielded a value set algorithm.

RESULTS

A total of 77 eligible studies were identified from which data on country setting, aims, condition (general population or clinically specific), sample size, age of respondents, the perspective that participants were asked to adopt, source of values (respondents who completed the preference elicitation tasks) and methods questions asked were extracted. Extracted data were classified and evaluated using narrative synthesis methods. The studies were classified into three groups: (1) studies comparing elicitation methods (n = 30); (2) studies comparing perspectives (n = 23); and (3) studies where no comparisons were presented (n = 26); selected studies could fall into more than one group. Overall, the studies varied considerably both in methods used and in reporting. The preference elicitation tasks included time trade-off, standard gamble, visual analogue scaling, rating/ranking, discrete choice experiments, best-worst scaling and willingness to pay elicited through a contingent valuation. Perspectives included adults' considering the health states from their own perspective, adults taking the perspective of a child (own, other, hypothetical) and a child/adolescent taking their own or the perspective of another child. There was some evidence that children gave lower values for comparable health states than did adults that adopted their own perspective or adult/parents that adopted the perspective of children.

CONCLUSIONS

Differences in reporting limited the conclusions that can be formed about which methods are most suitable for eliciting preferences for children's health and the influence of differing perspectives and values. Difficulties encountered in drawing conclusions from the data (such as lack of consensus and poor reporting making it difficult for users to choose and interpret available values) suggest that reporting guidelines are required to improve the consistency and quality of reporting of studies that value children's health using preference-based techniques.

Incorporation of expert knowledge in the statistical detection of diagnosis related group misclassification

BACKGROUND

In activity based funding systems, the misclassification of inpatient episode Diagnostic Related Groups (DRGs) can have significant impacts on the revenue of health care providers. Weakly informative Bayesian models can be used to estimate an episode's probability of DRG misclassification.

METHODS

This study proposes a new, Hybrid prior approach which utilises guesses that are elicited from a clinical coding auditor, switching to non-informative priors where this information is inadequate. This model's ability to detect DRG revision is compared to benchmark weakly informative Bayesian models and maximum likelihood estimates.

RESULTS

Based on repeated 5-fold cross-validation, classification performance was greatest for the Hybrid prior model, which achieved best classification accuracy in 14 out of 20 trials, significantly outperforming benchmark models.

CONCLUSIONS

The incorporation of elicited expert guesses via a Hybrid prior produced a significant improvement in DRG error detection; hence, it has the ability to enhance the efficiency of clinical coding audits when put into practice at a health care provider.

The Role of Personality in Treatment-Related Outcome Preferences Among Pharmacy Students

Objective. To examine whether personality traits, particularly conscientiousness and agreeableness, were associated with systematic differences in health outcome preferences in cancer treatment scenarios among second-year Doctor of Pharmacy students. Methods. An online survey that quantified outcome preferences using profile best-worst scaling tasks was administered to pharmacy students (n=185). The Big Five personality inventory was used to categorize respondents into tertile-based levels of each trait. Treatment-related health outcomes were described using the EQ-5D-Y system and framed with hypothetical cancer treatment scenarios. Preferences were obtained using count analysis for each treatment-related outcome, and differences based on the level of trait were tested using analysis of variance. Logistic regression was used to test for significant associations between higher levels of a trait and choosing dead over a severe health state. Results. Higher conscientiousness was associated with students who had an approximately 20% more positive preference for "no problems" in the Usual Activities and Pain/Discomfort attributes, as well as a 19% more negative preference for "a lot of problems" in the Pain/Discomfort attribute. No differences in treatment preferences were observed across agreeableness tertiles. Higher levels of personality traits were not significantly associated with choosing death over being in moderate health. Conclusion. Conscientiousness appears to be a factor in treatment-related outcome preferences among pharmacy students. Individuals with higher levels of conscientiousness may be more likely to recommend treatments that are less likely to cause pain or discomfort and negatively impact a patient's usual activities.

Exclusion Criteria as Measurements I: Identifying Invalid Responses

Background. In a systematic review, Engel et al. found large variation in the exclusion criteria used to remove responses held not to represent genuine preferences in health state valuation studies. We offer an empirical approach to characterizing the similarities and differences among such criteria. Setting. Our analyses use data from an online survey that elicited preferences for health states defined by domains from the Patient-Reported Outcomes Measurement Information System (PROMIS^®), with a U.S. nationally representative sample (N = 1164). Methods. We use multidimensional scaling to investigate how 10 commonly used exclusion criteria classify participants and their responses. Results. We find that the effects of exclusion criteria do not always match the reasons advanced for applying them. For example, excluding very high and very low values has been justified as removing aberrant responses. However, people who give very high and very low values prove to be systematically different in ways suggesting that such responses may reflect different processes. Conclusions. Exclusion criteria intended to remove low-quality responses from health state valuation studies may actually remove deliberate but unusual ones. A companion article examines the effects of the exclusion criteria on societal utility estimates.