The Medical Alignment Problem—A Primer for AI Practitioners.

Version 0.6 (Revision history at the bottom) November, 30, 2023

Much has been written about harmonizing AI with our ethical standards, a topic of great significance that still demands further exploration. Yet, an even more urgent matter looms: realigning our healthcare systems to better serve patients and society as a whole. We must confront a hard truth: the alignment of these systems with our needs has always been imperfect, and the situation is deteriorating.

My purpose is not to sway healthcare policy but to shed light on this issue for a specific audience: my peers in computer science, along with students in both medicine and computer science. They frequently pose questions to me, prompting this examination. These inquiries aren’t just academic or mercantile; they reflect a deep concern about how our healthcare systems are failing to meet their most fundamental objectives and an intense desire to bring their own expertise, energy and optimism to address these failures.

A sampling of these questions

• Which applications to clinical medicine are ripe for improvement or disruption by the application of AI?
• What do I have to demonstrate to get my AI program adopted?
• Who decides which programs are approved or paid for?
• This program we’ve developed helps patients. So why are doctors, nurses and other healthcare personnel so reluctant to use our program?
• Why can’t I just market this program directly to patients?

To avoid immediately disappointing any reader, beware, I am not going to answer those questions here although I have done so in the past and will continue to do so. Here I will focus only on the misalignment between organized/establishment healthcare and its mission to improve the health of members of our society. Understanding the misalignment is a necessary preamble to answering the questions of the sort listed above.

Basic Facts of Misalignment of Healthcare

Let’s proceed to some of the basic facts about the healthcare system and the growing misalignments. Again, many of these pertain to several developed countries but they are most applicable to the US.

Primary care is the where you go for preventive care (e.g. yearly checkups) and go first when you have a medical problem. In the US, primary care doctors are amongst the lowest paid. They also have a constantly increasing administrative burden. As a result, despite the growing needs for primary care with the graying of our citizens, the gap between the number of primacy care doctors and the need for such doctors may exceed 40,000 within the next 10 years in the US alone.

In response to the growing gap between the demand for primary care and the availability of primary care doctors, the U.S. healthcare system has seen a notable increase in the employment of nurse practitioners (NPs) and physician assistants (PAs). These professionals now constitute an estimated 25% of the primary care workforce in the United States, a figure that is expected to rise in the coming years.

You might think that the fact that U.S. doctors earn roughly double the income of doctors in Europe would result in a stable workload. Despite this higher pay, they face relentless pressure, often exerted by department heads or hospital administrators, to see more patients each day.

The thorough processes that were once the hallmark of medical training—careful patient history taking, physical examinations, crafting thoughtful diagnostic or management plans, and consulting with colleagues—are now often condensed into forms that barely resemble their original intent. This transformation of medical practice into a high-pressure, high-volume environment contributes to several profound issues: clinician burnout, patient dissatisfaction, and an increased likelihood of clinical errors. These issues highlight a growing disconnect between the healthcare system’s operational demands and the foundational principles of medical practice. This misalignment not only affects healthcare professionals but also has significant implications for patient care and safety.

The acute workforce shortage in healthcare extends well beyond the realm of primary care, touching various subspecialties that are often less lucrative and, perhaps as a result, perceived as less prestigious. Fields such as Developmental Medicine, where children are assessed for conditions like ADHD and autism, pediatric infectious disease, pediatric endocrinology, and geriatrics, consistently face the challenge of unfilled positions year after year.

This shortage is compounded by a growing trend among medical professionals seeking careers outside of clinical practice. Recent surveys indicate that about one-quarter of U.S. doctors are exploring non-clinical career paths in areas such as industry, writing, or education. Similarly, in the UK, half of the junior doctors are considering alternatives to clinical work. This shift away from patient-facing roles points to deeper issues within the healthcare system, including job dissatisfaction, the allure of less stressful or more financially rewarding careers, and perhaps a disillusionment with the current state of medical practice. This trend not only reflects the personal choices of healthcare professionals but also underscores a systemic issue that could further exacerbate the existing shortages in crucial medical specialties, ultimately impacting patient care and the overall effectiveness of the healthcare system.

Doctors have been burned by information technology: Electronic health records (EHRs). Initially introduced as a tool to enhance healthcare delivery, EHRs have increasingly been utilized primarily for documenting care for reimbursement purposes. This shift in focus has led to a significant disconnect between the potential of these systems and their actual use in clinical settings. Most of the currently widely used implementations over the last 15 years have rococo user interfaces that would offend the sensibilities of most “less is more” advocates. Many technologists will be unaware of the details of clinicians’ experience with these systems because EHR companies will have contractually imposed gag orders to prevent doctors from publishing screenshots. Yet these same EHR systems are widely understood to be major contributors to doctor burnout and general disaffection with clinical care. These same EHR’s cost millions (hundreds of millions for a large hospital) and have made many overtaxed hospital information technology leaders wary of adopting new technologies.

At least 25% of the US healthcare costs are administrative. This administrative overhead heaped atop of the provisioning of healthcare services includes the tug of war between healthcare providers and healthcare payors on how much to bill and how much to reimburse. It also includes the authorization for procedures, referrals, the multiple emails and calls to coordinate care between the members of the care team writ large (pharmacist, visiting nurse, rehabilitation hospital, social worker) and the multiple pieces of documentation entailed by each patient encounter (e.g. post-visit note to the patient, to the billing department, to a referring doctor). These non-clinical tasks don’t have the same liability as patient care and the infrastructure to execute them is more mature. As noted by David Cutler and colleagues, this makes it very likely that administrative processes will present the greatest initial opportunity for a broad foothold of AI into the processes of healthcare.

Even in centralized, nationalized healthcare systems there is a natural pressure to do something when faced with a patient who is suffering or worried. Watchful waiting, when medically prudent, requires ensuring that the patient understands that not doing anything might be the best course of action. This requires the doctor to establish trust during the first visit and in future visits, so the patient can be confident that their doctor will be vigilant and ready to change course when needed. This requires a lot more time and communication than many simple treatments or procedures. The pressure to treat is even more acute when reimbursement for healthcare is under a fee-for-service system, as is the case for at least 1/3 of US healthcare. That is, doctors get paid for delivering treatments rather than better outcome. One implication is that advice (by humans or AI) to not deliver a treatment might be in financial conflict with the interests of the clinician.

The substrate for medical decision-making is high-quality data about the patients in our care. Those data are often obtained at considerable effort, cost and risk to the patient (e.g, when involving a diagnostic procedure). Sharing those data across healthcare wherever it is provided has been an obvious and long-sought goal. Yet in many countries, patient data remains locked in propriety systems or accessible to only a few designees. Systematic and continual movement of patient data to follow them across countries is relatively rare and incomplete. EHR companies that have large marketshare therefore have outsized leverage in influencing the process of healthcare, of guiding medical leaders to market patient data (e.g for market research or training AI models). They are often also aligned with healthcare systems that would rather not share clinical data with their competitors. Fortunately, the 21st Century Cures act passed by the US congress has explicitly provided for the support of APIs such as SMART-on-FHIR to allow patients to transport their data to other systems. The infrastructure to support this transport is still in its infancy but has been accelerated by companies such as Apple which have provided customers access to their own healthcare records across hundreds of hospitals.

Finally, at the time of this writing (2023) hospitals and healthcare systems are under enormous pressure to deliver care in a more timely and safer fashion and simultaneously are financially fragile. This double jeopardy was accentuated by the consequences of the 2020 pandemic. It may also be that the pandemic merely accelerated the ongoing misalignment between medical capabilities, professional rewards, societal healthcare needs and an increasingly anachronistic and inefficient medical education and training process. The stresses caused by the misalignment may create cracks into which new models of healthcare may find a growing niche but it might also bolster powerful reactionary forces to preserve the status quo.

Did I miss an important gap relevant to AI/CS scientists, developers or entrepreneurs? Let me know by posting in this post’s comments section (which I moderate) or just reply to my X/Twitter post @zakkohane.