Rebuilding the Social Contract, Part 5

        Thus far, we have considered the traditional three A’s, but now I want to look at the fourth one—affordability. You don’t have to look very hard to find ample evidence that we have an affordability crisis in medicine. I heard a talk by Peter McGough, MD, 1 who presented some data on the question: why is US healthcare so expensive? He noted our system has the profit motive built in, has associated administrative complexity, which
accounts for 25-30% of total costs, and has enormous diagnostic and pharmaceutical costs. I recommend looking at his posts for more information, but I want to look at the issue from the standpoint of what individual physicians can do.

        Let me be clear, this is not going to be a discussion predicated on the notion that doctors are overpaid. That conversation leads to what is known as the “just wage” theory, while in a capitalist economy, the right wage is what the market will bear. I saw a recent graphic showing physician payments now amount to about 6% of total expenditures, down
from 15% some 30 years ago. To be sure, physician incomes are higher now than they were then, but other costs have been ballooning more rapidly. However, physician decisions drive a lot of additional costs, activating the spending pathway if you will.

        Consider the decision to admit a patient to the hospital. For any given principal diagnosis, there are some patients almost every physician would admit, other that none would admit, and a third group with more variability. Smulowitz and colleagues have looked at admission decisions as a function of a physician’s attitude toward risk. In the first study, they surveyed the risk tolerance of ER clinicians in Massachusetts and obtained
results on 691 providers. 2 The then examined admission decisions by those clinicians in a study sample consisting of 392,676 ED visits. Admission rates

        “…ranged from 36.3% at the 25th percentile to 48.0% at the 75th percentile (median, 42.1%). Overall, there was substantial variation in admission rates across clinicians; physicians were just as likely to over-admit or under-admit across the range of projected rates of admission. There also was weak consistency in admission rates across the most common clinical conditions, with intraclass correlations ranging from
0.09 (95%CI, 0.02-0.17) for genitourinary/syncope to 0.48 (95%CI, 0.42-0.53) for cardiac/syncope. Greater clinician risk tolerance (as measured by the Risk Tolerance Scale) was associated with a statistically significant tendency to admit less than the projected admission rate (coefficient, −0.09 [P = .04]).

        They did a second study in patients insured by Medicare. 3

        “The total study sample included 421,301 ED visits seen by 889 emergency clinicians. Patients were predominantly women (57.4%), and the average age was 72.6 years.
1 https://petermcgough.substack.com/
2 Smulowitz PB, Burke RC, Ostrovsky D, Novack V, Isbell L, Kan V, Landon BE. Clinician Risk Tolerance and
Rates of Admission from the Emergency Department. (16 February 2024.) JAMA Network Open.
2024;7(2):e2356189. doi:10.1001/jamanetworkopen.2023.56189.
3 Smulowitz PB, Ostrovsky D, Novack V, Isbell L, Kan V, Zaborski L, Landon BE. Clinician Risk Tolerance and
Rates of Admission from the Emergency Department for Medicare Patients. Ann Emerg Med 2026
Jan;87(1):29-38. doi: 10.1016/j.annemergmed.2025.06.611. Epub 2025 Jul 28.

        Mean clinician age was 46.5 years. In total, 77.1% were physicians, 59.3% were men, and 86.6% were White. We found a consistent relationship between lower risk tolerance and higher admission rates. This magnitude of the relationship was stronger for conditions with a higher rate of admissions.”

         Obviously, some variation in risk tolerance is to be expected, but I agree with these authors that thinking about ways to reduce risk in admission decisions would save money in the long run. We develop guidelines about what to do, but what about guidelines on what
not to do?

        A lower stakes example is the pressure created by ICD-based billing systems that emphasize the need for a specific “final diagnosis” to link to the diagnostic and therapeutic orders. Yet a senior clinician resulted discussed what she called the “rule of threes” in the approach to new symptoms. 4

        “It often takes more than one visit to arrive at an accurate diagnosis…Through medical school and residency, we learn the classic symptoms and diagnostic tests for conditions. In some cases, the presentation of symptoms fits a classic diagnosis… However, in many cases symptoms are vague or unclear, and a diagnosis is not immediately apparent. Testing in these situations may or may not give us the answer. As a presentation evolves, changes in symptoms and in our clinical exam can help to
identify an underlying cause. It is not until we have three data points that we can identify a trend to clue us into a diagnosis…Bayes; theorem states that the probability of an event changes as more information is available. In medicine we are practicing in a time when the amount of data is increasing and identifying the signal in the noise is an important skill. One method of applying Bayes theorem in clinical practice is to
observe trends over three visits to identify what data is important as a disease evolves…

        Another challenge in medicine is the large number of tests available to us, and a general belief that testing will give us the answer. In practice, making a diagnosis is often a process of exclusion and symptoms can occur without a diagnosis. In a fast- paced culture it can be difficult to take time to educate patients that diagnosis is a process and will require multiple visits and even testing multiple times to determine
the cause of symptoms.”

        Some physicians, and patients, want an answer “now,” which promotes the “SMA 120” approach to diagnosis—order a test even though the prior probability of the disease is low, because you don’t want to miss it, don’t have time to schedule another visit, etc. We can fix our EMR systems to reduce this pressure. In the next installment, I will consider the issue of pharmaceutical prescribing, another area where physician behavior drives costs.
13 August 2026

4 Sachdev M. The “Rule of Threes” in Ambulatory Care. I. M. Matters from ACP. July 2026.
https://www.acpjournals.org/doi/10.7326/acpi-20260714-the-rule-of-threes-in-ambulatory-
care?utm_campaign=FY26-27_NEWS_IMMATTERS_DOMESTIC_071426_EML.

Further Reading

Costs and Wasteful Care
Thinking about aggregate cost won't help doctors reduce unnecessary testing, but understanding Bayesian analysis might.

More on Variation - Part 1
Variation is not peculiar to healthcare, but is a general issue with the way the people think, and occurs whenever judgment is needed and the data are fuzzy.

Physician Decision Making
Physician decision-making is both complex and deals with uncertainty dooming current simple approaches to changing physician behavior.

Reducing Hospitalizations
A recent report by Vazquez and associates failed to show an impact of two population health processes on hospitalization rates at one year. What can we learn from this study.

Swimming Upstream
Our current cultural norms make following traditional medical advice, like eating less and exercising more, difficult for most people to do. Improving health may have more to do with modifying these forces, which is beyond the competence of health care providers and organizations.

The 1% Solution
Efforts to constrain health care costs have not been very effective. Maybe instead of grand solutions we need a series of "1% solutions."