Presentation on theme: "Understanding Patient Preferences in Individual Health Decisions: Conceptual and measurement considerations Sara J. Knight, PhD Interdisciplinary Program."— Presentation transcript:
1Understanding Patient Preferences in Individual Health Decisions: Conceptual and measurement considerationsSara J. Knight, PhDInterdisciplinary Program to Improve Care for Veterans with Complex Comorbid Conditions
2Goals Examine several conceptual models for understanding preferences Review approaches to the measurement of patient treatment preferencesDiscuss qualitative strategies for refining conceptual models of patient treatment preferences and health outcomesIdentify types of studies used to provide evidence for the construct validity of measures of patient values
3Characteristics of a Strong Measure of Patient Preferences Comprehensive in patient considerationsStrong in psychometric propertiesFeasible in a busy clinic settingsAppropriate for all educational backgroundsRelated to health care recommendations and outcomes
4Clarification of individual differences in decision making What are possible contributions of improved patient preference assessment?Clarification of individual differences in decision makingUnderstanding of how preferences may be constructed over timeImproved patient-centered careStrengthened patient/physician relationship
5What are preferences?Valuation of health care goods, services, and interventionsEconomic TheoryMaximize subjective expected utilityUtilities can be scaled in dollar-equivalence termsBased on assumptions of consistency and rationality with some limits
6Preferences versus Values Economic theoryUtilitiesValuesPsychological theoryAttitudes, preferences, interests, goals, needs
7Preferences versus Health Status Patient experience, well-being, functionConcurrent or retrospectivePreferencesPatient, consumer, or societal values and goalsProspective
8Economic Model Preferences Information Utility of Choice Alternatives U1 = u(Attrib11, Attrib12 , …, Attrib1n)Utility of Choice AlternativesU2 = u(Attrib21, Attrib22 , …, Attrib2n)U3 = u(Attrib31, Attrib32 , …, Attrib3n)Resources and ConstraintsStated ChoiceRevealed ChoiceDemandUtilization
9Another Economic Model: Adapted from McFadden ExperienceInformationStatedPerceptionsMemoryPerceptions/BeliefsChoice(Revealed Preferences)Motivation/AffectProcessTime and DollarConstraintsAttitudesPreferencesAttitude ScalesStated Preferences
10Individual Decision Making International Patient Decision Aid Standards (IPDAS) Collaboration Recommendations on Values MeasurementDescribe procedures and outcomes to help patients imagine what it is like to experience their physical, emotional, and social effectsAsk patients to consider which positive and negative features matter mostSuggest ways for patients to share what matters most with others
11Recognize a decision needs to be made IPDAS Effectiveness Recommendations: Does the patient decision aid ensure decision making is informed and values based?Recognize a decision needs to be madeKnow choice alternatives and their featuresUnderstand that values affect decisionsBe clear about option features that matter mostDiscuss values with their practitionerBecome involved in preferred ways
12Individual Decision Making Model Experience/AffectInformationAttributeValueAttributeValueAttributeValueAttributeValueAttributeValuePatient PreferencesPreference/ChoiceConcordancePhysician RecommendationTreatmentChoiceDecision Quality Knowledge, Satisfaction,Conflict, RegretTreatment OutcomesFunctional Status,Quality of Life, Symptoms
13Methods of Measurement Utilities ElicitationStandard GambleTime Trade-OffVisual Analog ScaleRating ScalesAttitude QuestionsConjoint AnalysisCombination Approaches
14UtilitiesValue between 0 and 1, where 0 represents the value of being dead and 1 the value of living with perfect healthRepresents patient’s subjective value for choice attribute, such as a health state or a treatment characteristic
20Example: Time Trade-Off Imagine that you have two friends, Mr. Smith and Mr. Jones.Imagine that Mr. Smith’s health fits the following description; that it will stay the same for the rest of his life; and that he will live about 10 more years.
21Time Trade-Off: The Health State Mr. Smith has mild difficulties or problems with urinating or bowel function.He is able to do most of his usual activities nearly all of the time. He is not overly tired and his energy level is pretty good.He usually has a good appetite.He has very little or no pain and it is easily controlled by medication.His ability to have sex and enjoy if has been mildly affected.He hardly ever feels tense, worried, irritable, sad, fearful or depressed.
22Time Trade-Off: The Choice Now imagine that your other friend, Mr. Jones, lives in perfect health, but will live somewhat less than ten years. If you had to be one of these 2 people, who would you rather be? Mark your answer below.10 years as Mr. Smith in health state A or 5 years as Mr. Jones in perfect health?
24Advantages of Utilities Based on economic and psychological theory; meets assumptions of normative decision makingExperimental task involving a choiceScores comparable across methodsUseful in studies of health economics and policy
25Limitations of Utilities Questionable reliabilityLogical inconsistencies within methodsLimited evidence for validityInconsistencies in scores across methodsNot well accepted by patientsDifficult for patients with low literacy and low numeracyNot related to treatment recommendationsSouchek et al., 2000
26Attitude MeasuresAttitudes are defined as a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavorUsual measurement is through ratings or rankingsEagly and Chaiken, 1996
27Example: Attitude Measure If you were forced to choose between the term “faulty gene” and “altered gene”, which would you prefer? Please circle your response on the scale below:1= I definitely prefer “altered gene”2= I prefer “altered gene”3= I am happy with either term4= I prefer “faulty gene”5= I definitely prefer “faulty gene”Wakefield et al., 2007
28Evaluation of Attitude Measures Requires few assumptions about underlying choice processesEasy for participantsHolistic approachValuation of an attribute as a wholeDoes not allow evaluation of levels or different categories of an attributeVulnerable to “halo” effectsPhillips, Johnson, Maddala, 2002
29Conjoint AnalysisAllows attributes to be evaluated in relation to each other, or “conjointly”Yields utilitiesAssumptionsEach good or service is a bundle of potential attributesEach individual has set of unique relative utilities weights for attribute levelsCombining utilities for difference attributes provides an individuals overall relative utilityPhillips, Johnson, Maddala, 2002
30Conjoint Analysis ATTRIBUTES TEST A TEST B Accuracy Privacy Cost The diagnosis is correct 80% of the time, 20% of the time it is incorrectThe diagnosis is correct almost 100% of the timePrivacyYou, your doctor, and your insurance company will receive information about your geneticsOnly you will receive information about your geneticsCost$0$500Would you choose Choice A or B?
31Evaluation of Conjoint Analysis Allows the evaluation of each attribute separatelyProvides estimation of willingness to pay; standardized approach to quantifying preferences for economic evaluationComplex and difficult for respondentsVulnerable to simplification of judgmentsPossible inconsistent responsesPhillips, Johnson, Maddala, 2002
32Integrative Approaches Bockenholt has suggested that using a nested approach to understanding value judgmentsComparative judgments are integrated with absolute judgmentsScores contain information on both relative value and scale origin
33Importance Ratings How important is… ExtremelyImportantVeryModeratelyA LittleNotAvoiding a treatment that causes problems for my relationship with my spouse/partner
34Best Worst Scaling Circle the concern that is most important to you in making your decision about yourprostate cancer treatment:Urinary FunctionResponsibilitiesSurvival
35Developing Measures of Preferences Step 1Identify a priori constructsStep 2Establish comprehensive range of constructs and exemplars for eachStep 3Develop representative content for each constructStep 4Generate items for each content area (items and subscales)Step 5Select appropriate response choicesStep 6Refine measure based on pilot testingStep 7Test measure properties
36Construct Development Ideally should be based on the purpose of the effort to understand preferencesEconomic analysis?Individual decision making?Cost analyses may require a different conceptual framework for understanding preferences and values and a different method for assessment than needed for the measurement of patient preferences in shared decision making
37Literature Review Descriptions of treatment or test alternatives Existing guidelines for carePatient education materialCase studiesOutcomes researchCost and utilization studies
39Focus Groups Used to generate broad range of constructs Often 8 to10 participants; fewer can be justifiedExperienced moderator neededStratify on key variables: treatment choice, ethnicity, genderStructured exercisesDifferences among constructsRankings among constructsCharacteristics that influence choice
40Analytic ApproachContent analysis using a priori constructs as a starting pointGrounded theory approach may be used where an a priori model does not existSoftwareNVivoEthnograph
41Cognitive Interviews Think aloud Well, it depends on what you mean by family responsibilities. Do you mean money? Helping my wife with my grandkids? My wife says she’s OK with any treatment as long as I’m still alive.
42Structured Cognitive Interviews Pretesting of measuresAdministrationItem stemsResponse scalesOrderMethodsThinkaloudsRetrospective protocolsBehavioral observations
43Psychometric measures versus utilities? Psychometric measures of attitudes yield scores interpreted from a population reference point and utility elicitation yields judgments scaled in terms of an absolute reference point (death, perfect health)Psychometric concepts of content validity and predictive validity may not be applicable to utilities where construct-irrelevant variance and construct under representation may be more relevant conceptsLenert and Kaplan, 2000
44Evaluating Measurement Properties: Accumulating Evidence ReliabilityInternal ConsistencyTest-retestValidityFaceContentCriterionConstructConstruct irrelevant varianceConstruct under-representationConsistency withinConsistency over timeCorrect conceptAdequate coverage of conceptExternal criterionConstruct being measuredMinimal spurious influenceRepresentative constructs
45Reliability: Internal Consistency InterpretationThe consistency of responses within a scale or within a subscaleStatistical MethodCronbach’s alpha (α) is the most common method. It is based on the average correlation over items weighted by variancesIt is the percent of variance that the current scale explains of the unidimensional underlying construct being measuredAcceptable valuesValues range from with higher scores reflecting more accurate measure of the underlying trait. Values below .70 suggest a need for evaluation of each item within the scale, values above .90 for use of a measure with individuals.
46Reliability: Test-Retest InterpretationThe stability in responses across assessment occasionsExperimental MethodThe same instrument is administered twice to the same sample on two occasions usually 1-2 weeks or up to one month apartStatistical MethodIntraclass reliability coefficient for continuous valued measures, kappa for discrete valued measuresAcceptable valuesValues range from with higher scores reflecting more accurate measure of the underlying trait. Values below .60 suggest low consistency and potential future difficulty in detecting differences due to real effects
47Validity: Face Interpretation Determination that the instrument is measuring the construct of interestAssessment MethodPrior to development, focus groups can inform the content. After the development of the instrument, cognitive interviews can be used to assess understanding of the content of the questionnaireStatistical MethodNo specific statistical method is associated with documenting face validityPopulation considerationsThe face validity of an instrument may vary across patient populations
48Validity: Content Interpretation Determining the adequacy of coverage of the instrumentExperimental MethodExperts in the area judge whether the instrument captures all domains of the construct of interestStatistical MethodThough rarely reported, the Content Validity Index or the Content Validity Ratio indicates the extent of expert agreement.Determination of ExpertsChoose a panel of experts that informs rather than limits your interpretation of the breadth of your construct.
49Validity: Criterion Interpretation The association between the construct and some external criterionExperimental MethodsConcurrent validity: both validation and construct tools are administered on one occasion. Predictive validity: construct is measured first; criterion is measured laterStatisticalMethodTests of association are used to assess construct validity such as a Pearson r for continuous valued scale scores, or Chi-square for categorical scale scores.Acceptable valuescoefficients of .70 or greater
50Validity: Construct Interpretation Establishes the ability of the instrument to measure the construct and to distinguish varying levels of the presence of that constructExperimental MethodsCollection of data from many subjects from the patient population of interest to determine latent trait(s) underlying the assessment instrument.Collection of data from two groups known to vary on the construct (known-groups technique).Multi-Trait Multi-Method—measure should be more strongly related to other measures of similar constructs and to measures of dissimilar constructsStatistical MethodsA statistical method to explain variability in responses (e.g. factor analysis, component analysis).A statistical method to detect differences between groups (e.g. t-test)