Estimating preferences for medical devices: does the number of profile in choice experiments matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with two profiles, while marketing studies routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on hearing aids. - Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys, and were randomized to choice tasks with two or three profiles. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analyses of individual-level models estimated with ordinary least squares. - Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P<0.0001). Pairs led to more variation, and were systematically biased toward the null because a third (32.2%) of respondents focused on only one attribute. This is in contrast to respondents in the triplet design who traded across all attributes. - Discussion: The number of profiles in choice tasks affects the results of conjoint analysis studies. Here triplets are preferred to pairs as they avoid non-trading and allow for more accurate estimation of preferences models

Estimating Patients' Preferences for Medical Devices: Does the Number of Profile in Choice Experiments Matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with only two profiles, while those in marketing routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on measuring patient preference for hearing aids. Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys incorporating a conjoint analysis, but were randomized to choice tasks with two or three profiles. Baseline differences between the two groups were explored using ANOVA and chi-square tests. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analysis of individual-level models estimated with ordinary least squares. Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. The only significant difference between the groups was time to complete the survey (11.5 and 21 minutes respectively). Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P

THE IMPACT OF A VALUE-BASED INSURANCE DESIGN ON THOSE WITH MULTIPLE CHRONIC CONDITIONS.

Background: Value-based insurance designs establish cost-sharing levels to promote services perceived to be high value from the health insurer or policy maker’s perspective. However, it is unclear how people with multiple chronic conditions will react to changes in insurance design because they may not be willing or able to switch to lower cost prescription drugs. These individuals are the heaviest consumers of prescription drugs and may be more susceptible to short term complications from poorly managed conditions or from drug/drug interactions. This dissertation evaluates how adults with multiple chronic conditions respond to a change in insurance benefit design. Methods: Data consists of drug and medical claims from Maryland’s high-risk pool for the years 2007-2011. High-risk pools offer insurance to those with preexisting conditions who were denied coverage on the individual market and who do not have access to employer-based insurance. An interrupted time series design with individual-level data exploits a co-pay change in 2010 that raised copayments on brand name medications while decreasing copayments on generic drugs. Outcomes include drug utilization, medical service utilization, drug and medical spending, generic substitution and whether the policy impacted medication adherence. Results: The copayment policy change had a statistically significant impact on those with increasing numbers of chronic conditions, but the magnitudes are small. The use of both brand and generic drugs increased less than one drug fill per quarter across all numbers of chronic conditions following the policy change. The financial impact was greatest for those with the most chronic conditions—an over $150 increase in quarterly out-of-pocket spending for those with 10 or more chronic conditions. The use of generics increased for antidepressant drugs and decreased for hypertensive drugs. Overall, adherence levels remained unchanged. Conclusions: This study finds little impact on the use of prescription drugs following a value-based insurance design initiative. Most of the impact is seen in those with the highest number of conditions who use more services and they experienced increased financial burden. Other insurance benefit design tools may be more effective in this population

Estimating preferences for medical devices:does the number of profile in choice experiments matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with two profiles, while marketing studies routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on hearing aids. Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys, and were randomized to choice tasks with two or three profiles. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analyses of individual-level models estimated with ordinary least squares. Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P<0.0001). Pairs led to more variation, and were systematically biased toward the null because a third (32.2%) of respondents focused on only one attribute. This is in contrast to respondents in the triplet design who traded across all attributes. Discussion: The number of profiles in choice tasks affects the results of conjoint analysis studies. Here triplets are preferred to pairs as they avoid non-trading and allow for more accurate estimation of preferences models

Economic evaluation of a task-shifting intervention for common mental disorders in India

OBJECTIVE: To carry out an economic evaluation of a task-shifting intervention for the treatment of depressive and anxiety disorders in primary-care settings in Goa, India. METHODS: Cost-utility and cost-effectiveness analyses based on generalized linear models were performed within a trial set in 24 public and private primary-care facilities. Subjects were randomly assigned to an intervention or a control arm. Eligible subjects in the intervention arm were given psycho-education, case management, interpersonal psychotherapy and/or antidepressants by lay health workers. Subjects in the control arm were treated by physicians. The use of health-care resources, the disability of each subject and degree of psychiatric morbidity, as measured by the Revised Clinical Interview Schedule, were determined at 2, 6 and 12 months. FINDINGS: Complete data, from all three follow-ups, were collected from 1243 (75.4%) and 938 (81.7%) of the subjects enrolled in the study facilities from the public and private sectors, respectively. Within the public facilities, subjects in the intervention arm showed greater improvement in all the health outcomes investigated than those in the control arm. Time costs were also significantly lower in the intervention arm than in the control arm, whereas health system costs in the two arms were similar. Within the private facilities, however, the effectiveness and costs recorded in the two arms were similar. CONCLUSION: Within public primary-care facilities in Goa, the use of lay health workers in the care of subjects with common mental disorders was not only cost-effective but also cost-saving

Task-Sharing Approaches to Improve Mental Health Care in Rural and Other Low-Resource Settings: A Systematic Review.

PURPOSE: Rural areas persistently face a shortage of mental health specialists. Task shifting, or task sharing, is an approach in global mental health that may help address unmet mental health needs in rural and other low-resource areas. This review focuses on task-shifting approaches and highlights future directions for research in this area. METHODS: Systematic review on task sharing of mental health care in rural areas of high-income countries included: (1) PubMed, (2) gray literature for innovations not yet published in peer-reviewed journals, and (3) outreach to experts for additional articles. We included English language articles published before August 31, 2013, on interventions sharing mental health care tasks across a team in rural settings. We excluded literature: (1) from low- and middle-income countries, (2) involving direct transfer of care to another provider, and (3) describing clinical guidelines and shared decision-making tools. FINDINGS: The review identified approaches to task sharing focused mainly on community health workers and primary care providers. Technology was identified as a way to leverage mental health specialists to support care across settings both within primary care and out in the community. The review also highlighted how provider education, supervision, and partnerships with local communities can support task sharing. Challenges, such as confidentiality, are often not addressed in the literature. CONCLUSIONS: Approaches to task sharing may improve reach and effectiveness of mental health care in rural and other low-resource settings, though important questions remain. We recommend promising research directions to address these questions