Custom-made versus ready-to-wear treatments: Behavioral propensities in physicians’ choices

1. Custom-made versus ready-to-wear treatments: Behavioral propensities in physicians’ choices Richard G. Frank Richard J. Zeckhauser

2. Background • Although physicians respond to financial incentives at the individual patient level, it becomes much harder for doctors to tailor care at the individual patient level. Why? The medical care system has become vastly more complex in recent years, as have its reimbursement practices • The typical American physician today holds 11 managed care contracts and serves patients from 15 health plans (NCHS, 2006). • The use of allied health professionals has expanded over time, so that today 48% of physicians use such staff compared to 30% in 1980 (CHSC, 2006).

3. Background • Evidence from behavioral economics • Individuals fall prey to behavioral decision • Also true for highly important decisions • True for professionals and individuals

4. Goal • Our goal in this paper is to assess the contemporary resolution of the forces that push toward standard treatments, i.e., norms behavior, as opposed to those that encourage customized treatments for individuals in differing situations • This paper investigates prescribing behavior for antidepressants, and whether doctors respond to the complexity of a patient’s condition when allocating their time in office visits

5. Four reasons to stick with a professional norm • Communication costs • Cognition costs • Coordination costs • Capability costs

6. Communication costs • In order to prescribe treatment outside of the norm, the physician must communicate their reasons for doing this to the patient. If patients have preconceived notions of how they want to be treated, physicians may have to expend significant effort to convince the patient that this individualized treatment is the best way to proceed.

7. Cognition costs • As every person knows, exerting mental effort is costly. Physicians can cut down on the cost of diagnosis by using heuristics. These shortcuts may not be optimal for every patient, but they generally “do a reasonable job for a broad array of cases” and also cut down on the physicians mental computing costs.

8. Coordination costs • Physicians often have to work with other physicians. The more physicians customize their treatment, the more difficult it is to communicate this alteration in care levels with specialists and thus more difficult to coordinate care.

9. Capability costs. • Physicians are trained in certain treatments. If a new, better treatment comes along, the physician has a choice • doing the old treatment • learning the new treatment poorly and performing the new treatment • learning the new treatment well and performing the new treatment. • Choice (3) may be optimal from the patient’s point of view, but for the physician it may involve significant fixed costs involved in acquiring the human capital necessary to preform the new procedure. If the physician decides not to incur the cost to learn the new technique well, it may in fact be optimal to choose option (1) over option (2) and thus old techniques will persist.

10. Example: chemotherapy treatment • Standard protocol • Fixed interval, say monthly • Dosage tradeoff between benefit and side effects • White blood count closely monitored • If low, delay treatment • Dosage not changed VERY ODD

11. Three Levels of Rationality • Hyper rationality – Doctor optimizes for each patient. • Decision cost rationality – Doctor recognizes costs of customization. Take reasonable decisions in light of the costs they face. • Heuristic behavior – Doctor simply employs ready-to-wear treatments.

13. Use of Norms Hypotheses • Therapeutic Norms Hypothesis – Doctors select treatments for a representative patient in each category. • Sensible Use of Norms (SUN) Hypothesis – Doctors use norms when they make the most sense. Thus, would customize for chronic conditions more than acute conditions. • My Way Hypothesis – For many important conditions, doctors will regularly prescribe a treatment quite different than the choice of other physicians. Thus, the choice might depend on past luck, which drug encountered first (detail men). • Note that our three behavioral hypotheses are strongly related.

14. Hypothesis: drug prescribing • Prescribing concentration by physician greater for acute conditions than chronic conditions. • Supports SUN Hypothesis • Prescribing concentration depends on physician. • Is high relative to share for top-selling drug. • Rejects SUN Hypothesis • Supports Therapeutic Norms and My Way Hypotheses

15. Hypothesis: visit time • Length of visit little affected by complexity of decisions. • Strongly affected by physician-specific factors. (Rejects SUN Hypothesis ) • Supports Therapeutic Norms and or My Way Hypotheses

16. Hypothesis: multiple drug choice • Many drugs available for same condition, and dosages vary. Alternative findings: • Drug switching and dosage driven by patient response to treatment. • Supports SUN Hypothesis • Drug switching and dosage driven by demographic, immediate clinical, or physician-specific factors. Patient response plays little role. • Supports Therapeutic Norms and/or My Way Hypotheses

17. Data • National Ambulatory Care Survey (2004) – 25,000 visits • Reason for visit, diagnosis, medication prescribed, tests, referrals, duration, demographics of patient and physician, insurance, type of practice, specialty, location. • USE TO TEST FOR TREATMENT OF CHRONIC VERSUS ACUTE CONDITIONS, AND VISIT TIMES

18. Data • Quality Improvement for Depression Study – four randomized effectiveness trials • Individuals diagnosed with major depression. Detailed clinical, treatment and demographic data. Collected four times over two years. Scores on depression scale 0-100. • Full responders had a reduction in score over 50%; partial responders reduction 25-50%; non-responders less than 25%.

22. The authors find that customization in prescribing behavior occurs most frequently for patients with chronic conditions.  This is likely because altering the “standard” treatment has more benefit for ‘repeat-visit’ patients than those with simply an acute illness.  However, race, gender, number of physician visits and insurance type do not affect prescribing behavior.

23. Overall, the evidence shows that physicians often follow norms rather than customize care. Also, it seems that the manner in which physicians are paid has no bearing on how they treat patients. However, this is likely due to the fact that 1) it is very difficult to customize visit length especially when physicians are dealing with eleven managed care contracts on average [see other evidence in "Time Allocation" post on Tai-Seale et al. (2007) or the "Doctors Behave" post on Glied and Zivin (2002)], and 2) physicians do not receive compensation for pharmaceuticals and thus have no financial incentive to tailor treatment to patients based on their individual insurance.

24. Results on concentration of prescriptions • Mean concentration for most used drug by physician for condition is greater than 60%. • Greater than market share of any drug for any of the conditions. • Concentration for chronic conditions is 13% lower. This is likely because altering the “standard” treatment has more benefit for ‘repeat-visit’ patients than those with simply an acute illness.  • However, race, gender, number of physician visits and insurance type do not affect prescribing behavior.

26. Results on concentration of prescriptions • First two findings support Therapeutic Norms and My Way Hypotheses. • Third finding gives some support to SUN Hypothesis

27. Results on visit time • 17 minutes is mean visit time. • Regarding length of the office visit, the most important factor is whether or not the patient is a new patient. • Upper respiratory problems get 2.2 minutes more. • No other characteristics of diagnosis affects visit length by as much as 2 minutes. • Complexity does not matter. • Individuals who were self-pay had shorter visits while those with had Medicare insurance had longer visits, but these results were fairly small in magnitude. • Twenty-eight percent of the differences in the length of an office visit was due to physician specific factors.

29. Results on visit time • Strongly reject SUN Hypothesis. • Support Therapeutic Norms Hypothesis.

31. Results on multiple drug choice • Changes in medications explained by schooling, age and ethnicity. • Changes in medications not related to clinical indicators. • Strongly rejects SUN Hypothesis. • Supports Therapeutic Norms and/or My Way Hypotheses. 

32. Results on dosage • Dosage increase related to schooling and age. • Dosage increase unrelated to response to treatment or level of symptoms. • Strongly rejects SUN Hypothesis. • Supports Therapeutic Norms and/or My Way Hypotheses.

33. Conclusions • Physicians rely on norms for • Selecting prescriptions • Lengths of visit • Switching medication • They tend to use ready-to-wear rather than customized treatments. • Significant evidence of My Way behavior.

34. Conclusions • It seems that the manner in which physicians are paid has no bearing on how they treat patients. • However, this is likely due to the fact that • it is very difficult to customize visit length especially when physicians are dealing with eleven managed care contracts on average [see other evidence in "Time Allocation" post on Tai-Seale et al. (2007) or the "Doctors Behave" post on Glied and Zivin (2002)] • physicians do not receive compensation for pharmaceuticals and thus have no financial incentive to tailor treatment to patients based on their individual insurance.