Using choice‐based conjoint to determine the relative importance of dental benefit plan attributes

Cunningham, Maureen; Gaeth, GJ; Juang, C. H.; Chakraborty, Goutam

doi:10.1002/j.0022-0337.1999.63.5.tb03285.x

Cited by 14 publications

(17 citation statements)

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“…35 Conjoint analysis has been used several times in order to analyze consumers decision making process in choosing health insurance as well as long term private insurance and dental insurance. [36][37][38][39][40][41][42] These research studies have demonstrated several benefits of using conjoint analysis in evaluating consumer preferences in choosing health plans. For example, these studies have demonstrated that some of the most important attributes consumers consider when choosing health care plans include premiums, freedom in choosing physicians, copayments for physicians vists, copayments for medications, freedom in choosing hospitals, and inclusion or exclusion of vision and dental coverage and strongly prefer plans which have high maximum liability.…”

Section: Overview Of Analysismentioning

confidence: 99%

“…35 Simulation procedures have been performed in several cases to simulate both current and hypothetical health plans performance in the market place. 36,42 Studies have shown that the data gathered from conjoint analysis studies is reliable in predicting the market share of different types of insurance plans which are currently on the market when used in simulations. 36,42 Subgroup analysis on secondary variables can also be performed so that differential preferences in between groups which are moderated by demographic variables may be analyzed.…”

Section: Overview Of Analysismentioning

confidence: 99%

“…36,42 Studies have shown that the data gathered from conjoint analysis studies is reliable in predicting the market share of different types of insurance plans which are currently on the market when used in simulations. 36,42 Subgroup analysis on secondary variables can also be performed so that differential preferences in between groups which are moderated by demographic variables may be analyzed. 36,37,39 The data derived from these studies also can allow decision makers to identify which specific demographic groups place more importance on certain features, so that plans may be tailored to these individuals preferences to obtain a higher yield.…”

Section: Overview Of Analysismentioning

confidence: 99%

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Evaluating Consumer Preferences for Medicare Part D Using Conjoint Analysis

Wingate¹

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The establishment of an outpatient prescription drug benefit in Medicare, Medicare Part D, was one of the more significant events in United States healthcare reform history. Many seniors have chosen to enroll in the plan as the program has an enrollment of over 27 million. One central premise of Medicare Part D was that the plan would be administered entirely through private insurance plans. Because many plans would be competing against one another for potential beneficiaries, it was expected that companies would offer seniors plans with high quality benefits at lower costs that would presumably be attractive to seniors. However, in order for this strategy to succeed, seniors must be sensitive to differences in price and the quality of benefits amongst different plans. This study sought to evaluate the relative importance seniors place on different attributes of Medicare Part D drug plans using a marketing technique called conjoint analysis. An Adaptive Choice Based Conjoint Analysis Survey was constructed and administered to 497 seniors in the Greater Memphis/Shelby County Area. Seniors were recruited from local senior centers or senior apartment homes. The survey consisted of 7 attributes: premiums, brand copayments, generic copayments, deductible amounts, doughnut hole coverage, formulary provisions, and eligibility requirements for medication therapy management services. The most important attribute in the aggregate sample was premiums with an importance score of 50.3%, followed by the formulary provisions (importance score of 12.1%), deductible (11.6%) and pharmacy access (10.1%). Seniors with higher incomes, those taking more than seven medications, and those with monthly medication costs above $80 were less sensitive to premium increases than other groups. As a group, the seniors were willing to pay approximately $20 more in monthly premiums to go from plans with the maximum allowed deductible to plans with no deductible and only $3 more to have full coverage of generics in the doughnut hole; however these values differed amongst different segments. For example, seniors with reported medication costs of at least $80 per month are willing to spend on average $20 per month for doughnut hole coverage. Adaptive Choice Based Conjoint Analysis represents a feasible way to elicit preferences for features in Medicare Part D drug plans. Seniors are sensitive to differences in cost and breadth of coverage across plans, although only a subset of seniors is sensitive to the doughnut hole. Seniors are particularly concerned with low premiums in their particular plans, although seniors with higher incomes, those taking more medications, and those with higher out of pocket medication costs are less sensitive to changes in premiums. The delivery system characteristics are also an important consideration for seniors in purchasing Medicare Part D plans, as most seniors exhibited strong preferences for being able to retain their relationship with their current pharmacy. vi TABLE OF CONTENTS CHAPTER 1.

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Section: Overview Of Analysismentioning

confidence: 99%

Section: Overview Of Analysismentioning

confidence: 99%

Section: Overview Of Analysismentioning

confidence: 99%

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Evaluating Consumer Preferences for Medicare Part D Using Conjoint Analysis

Wingate¹

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“…Conjoint analysis can better model actual decision making because it requires respondents to make trade-offs in a holistic context, as opposed to others surveys which do not impose a resource constraint; for example, respondents can rate all attributes as ''extremely important'' without having to evaluate trade-offs. 196,197,198 Conjoint analysis, which was developed originally in economic and marketing research, was based on the theory that decision options can be described by sets of attributes or factors, each made up of different levels. 199,200 The relative value that professionals attach to different factors can be estimated by constructing a series of hypothetical scenarios made up of these factors at different levels and asking professionals to rate, rank, or make choices within a set of hypothetical options.…”

Section: Introductionmentioning

confidence: 99%

“…[203][204][205][206][207][208] In spite of this, the use of conjoint analysis is still rare in dental research. [196][197][198] One of the applications where conjoint analysis was used in dental research assessed the determinants of dentists' decisions to initiate a particular restorative treatment, dental implants. This study found disagreement between what dentists say to be important (self-reported task) and the factors they actually use to judge the suitability of implant treatment (hypothetical scenarios based on a conjoint task).…”

Section: Introductionmentioning

confidence: 99%

Factors related to the use of atraumatic restorative treatment (ART) in pre and post-pediatric dentistry programs and in pediatric dentistry practices in the US

Kateeb¹

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Modelling non‐demanders in choice experiments

2003

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Discrete choice experiments have the advantage that they can study preferences in health care where revealed preference data is not readily available. However, as a substitute for actual observed market led data, the experimental set-up for hypothetical situations must mimic the circumstances under which actual choices are made. One situation that a consumer/patient might face is an opt-out option. They might not choose to accept any of the positive actions available and as such will be a non-demander of the health care on offer. This paper explores issues raised in the modelling of such data within an experiment looking at women's preferences for cervical screening services.

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Using choice‐based conjoint to determine the relative importance of dental benefit plan attributes

Cited by 14 publications

References 0 publications

Evaluating Consumer Preferences for Medicare Part D Using Conjoint Analysis

Evaluating Consumer Preferences for Medicare Part D Using Conjoint Analysis

Factors related to the use of atraumatic restorative treatment (ART) in pre and post-pediatric dentistry programs and in pediatric dentistry practices in the US

Modelling non‐demanders in choice experiments

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