Supporting Health Decisions
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2005 disease management conference presentation on improving clinician/consumer decision support from a managed care perspective.
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Supporting Health Decisions
- 1. Using Heuristics to Support Optimal Health Decisions Laurie Gelb, MPH Principal Profit by Change Quality Costs Safety Decisions
- 3. SIGNS OF OUR TIME
- 19. Decision support Decision models Claims data Test results; personal, family hx Pt chart Prospective trials
- 31. Traditional presentation Underlying question What’s in a frame? What’s the best way to shorten a cold? Don’t ask for an antibiotic if all you have is a cold—it won’t help and it’s irresponsible Which of the following is the most important financial outcome for you? Consider a high-deductible plan for lower monthly premiums and more control over your expenses If I need to go to the hospital, couldn’t delaying make things worse? Don’t go to the emergency room before calling one of our nurses, who can tell you what best to do How can a blue tablet be the same as a white tablet? Pay less for prescriptions – use a generic drug—they’re just as good
- 32. [email_address] How are you framing health decisions? STAKES COMMITMENT TIME SUB-DECISIONS
Editor's Notes
- We say, play or pay But provide little support
- While untrue that people “do not know” how they make decisions, they are seldom asked this question other than in regards to product/service attributes
- We are primarily marketing decisions about use of a product after plan benefits/network affiliations/practice models/retail store have been selected So we are structuring decisions about products, as much as product purchase or selection HC is complex, so these are not binary decisions about accepting or rejecting products, and very little inclination to opt out of product lines completely, but great inclination to opt out of decision-making, whose benefits are unclear and which has significant down side Unlike even financial planning, where if a fund gains 7% in value over the year, all holders of the fund benefit—much more inter-user variability in hc outcomes Least we can do is not blur, nor let the consumer blur, the line between deciding about packaging (e.g. deductible, network) and deciding about care – the product
- How closely are we looking at decision models before we framed the decision? Are we creating a decision context where outcomes are in some ways controllable and decisions can be based on some sort of evidence or criteria? How well do we explore what the care user’s context is and will be in future? E.g. in terms of potential statin use, am I more concerned about lowering cholesterol or preventing AD? How are my expectations evolving? Who’s really evolving them – payors or the media? Apple boxes support, but don’t sell computers If CDHC implies that the plan structure is equivalent to the care – that is, the packaging is the product or the medium is the message, then how invested can I feel in the decision context? Implication that health benefits organizations must have a dividing line structurally for supporting consumers at point of care vs. point of sale that goes beyond disease management and marketing.
- Route to work – one new turn Buying lunch – the hamburger ex
- So since structuring evidence-based decisions is so important, play to heuristics Avoid recycling common sense, which has not worked well in changing behavior (people quit smoking out of self-hatred and fear of ultimate consequences, not aggregate data) and market important but feasible decisions
- We need to feel that we have control more than we need it. What inhibits decision-making is not only lacking the right structure and context, but feeling that implementation of the decision is half the battle Implementation is a loss of perceived control – if everything rests on me, then if I miss any steps, I’m toast, and there’s no way I can understand the system in its entirety from the outside
- How closely are we looking at decision models before we frame the decision? Are we creating a decision context where outcomes are in some ways controllable and decisions can be based on some sort of evidence or criteria? Younger people have lived longer in new era, are more Net-savvy and accustomed to interactive decision support for other goods How well do we explore what the care user’s context is and will be in future? E.g. in terms of potential statin use, am I more concerned about lowering cholesterol or preventing AD? How are my expectations evolving? Who’s really evolving them – payors or the media? Implication that health benefits organizations need a dividing line structurally for supporting consumers at point of care vs. point of sale that goes beyond disease management and marketing.
- Decisions are best undertaken when one is calm; illness and injury not very calming But if one has prepared in advance, that’s as good as it gets. That takes support for the understanding that bad, devastating things happen, and no plan can change that. No product can necessarily cure these things. We can, however, control how we respond to all that. To honor the rest of what life is requires that we do, to get through. “ Society and medicine are losing perspective about the uncontrollable, the unknowable, the unbearable, and the unpronounceable.” --Des Spence, GP, Glasgow, from the BMJ This is saying (and full piece worth reading) that we over-project evidence to ourselves – if everything’s a risk, we have to opt out. Then where is the health system? Driving a car is very dangerous, by any measure. Still, the roads are full. We balance the risks. Health decisions must be amenable to heuristics – we need to install some traffic lights and ramps, without closing the roads.
- Back to Donabedian Back to everyone’s a pt—you can obsessively stratify, or just communicate
- Our context not pts’ – they see as first we had everything, then 3 tier, now this…and why? Move toward “you have control over how many drugs you take” but not yet integrated with rational drug selection (burden of proof on drug and how to implement that)
- All disease is not created equal, just like anything else Do you look at your leaky faucet or your leaky car first? We can help prioritize decisions – surely the first step toward making them. Help formulate decision rules – distinguish between allergy sx that are and are not bothersome
- Encourage realism You are not going to feel good every day, all day Nor will rx or any substance change that When we let supplements take the lead, people feel worse than they did, because the benchmark is so far out there…shiny, happy people everywhere But we don’t want to feel like we are really missing the boat or worse off than others. So we need to encourage self-disease management, including learning from mistakes – you binged one day, it’s still worthwhile to have decided to diet and you still have control – no one took it from you
- Understanding the decision context requires every ingredient in the soup: The raw clinical data about the individual patient and rolled up into appropriate subgroups, e.g. Hispanic males The claims data individually and in the aggregate Heuristic market research supporting the different decision models people are using, either as professionals or laypersons Prospective trials, using these decision models’ endpoints and thresholds as part of the design
- HOR not icing on the cake – the cake (or beef) While safety and efficacy may no longer be as blithely assumed, neither can a periapproval strategy focus on them, in the limited sense of a registration trial Phase IIIb/IV research then has 2 parallel tracks, one with FDA mandated trials and one with “elective” research. Either may be drivers. From the plan perspective, reimbursement decisions will increasingly reference the “rest of the story” after FDA approval, with greater impetus to re-evaluate regularly and re-assess as significant new evidence presents All the more need to understand how decision models evolve as new evidence, expectations, pts show up (e.g. one statin pt cohort has eaten bacon every day, smoked, etc. while another runs daily, eats low fat yogurt…this must be taken into acct)
- When HOR utilizes retrospective data, there are a number of caveats Beware the easy answer, based on primary dx (meaningless), convenience sampling Recognize that compliant and persistent pts may share other traits
- Cannot presume that any two decisions are independent, nor dependent (e.g. seek care for symptom, fill rx, take rx, return for f/u) Cannot presume that presenting sx will be treated at first visit, or with first subsequent rx – more treatable/urgent problem may be surfaced Contradictory advice often received, partially based on physicians’ different knowledge levels about pt Support implementation treatment algorithms with reference to presentation/differentials, not just treatment of one feature --Meaning presenting epi on comorbidities, not just “what do you do with isolated HTN”) --If physician does not have time to present full picture to pt, how will that happen?
- Opportunity to link chart data opens many doors Not to foster a report card mentality, but that plan also wants to import best practices from physicians Retro work less meaningful if not interactive: Merely checking for adherence to published algorithm presumes it’s the best for physician’s population; given pub delays, may well be obsolete or not most refined available for practice
- If we can establish that a specific drug choice is the way to go (for now), no point in keeping it to ourselves Ensure that physicians understand why we are communicating this (not simply to minimize costs, but to benefit pts) Physicians respect evidence-based decision-making but want to know the quality of evidence is high and always under scrutiny
- Evaluate models as would any other sales support or value add: What are the caveats? What are the assumptions made? From what population was the model developed; to what population are we applying it?
- Many “market research firms” not set up to obtain IRB approval, which is necessary when mining pt level data for potential contacts Also important to consider whether pt level data is being resold (HIPAA liability), internal controls of vendor for data center, analysis, transmission
- Incents and sticks have to align with decision models (sequences of considerations, e.g. hassle factor, safety or avoid worst outcome first), e.g. for kid vs. parent for himself
- To influence decisions, need to understand, not replicate or predict them We can predict, but hardly influence the weather… Most market research forces respondent into interviewer or questionnaire’s framework – teaching to the test Decision-making is more complex, and individualized, than traditional designs permit us to believe Need to surface more than mindless parroting of labels, treatment rationales, obvious pt stratification (yes, more obese diabetics start on metformin) Medical evidence doesn’t change a decision, ipso facto – So instead of spending all our resources merely on gathering the evidence, a significant effort needs to go toward understanding what really constitutes “evidence” and how to disseminate it
- If you use the right frame for that person, it’s intuitively obvious for him, not a struggle, not a battle, not a war of words
- Summary – More important to structure decisions than products More important to support decisions than market products – clarify stakes, sub-decisions and commitment time, at a minimum Worry more about the frame than the branding on it. Decision support must be interactive and individualized to a greater extent than now – if we recycle common sense as the marketing context, and use “you may not need” as our rationale, we lose the opportunity to help consumers become more invested in their individual health, the ultimate facilitator of more informed and conscious decision-making for any product line