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Preventable Spending
In discussions of healthcare costs, it has become axiomatic that much of what is spent is wasted and that changes in the care delivery system could yield substantial savings. A new paper by Figueroa and associates[1] provides some data addressing this question. Whether it is good news or bad news depends. The authors used all Medicare claims data from 2011 and 2012, excluding those patients covered at least part of the year by Medicare advantage plans and those who died during the year, yielding a population of more than 6,100,000 persons with one year’s worth of claims. They segmented this population into six mutually exclusive groups: non-elderly disabled, (17.9%); frail elderly, (8.6%); major complex chronic illness, (18.0%); minor complex illness, (27.8%); simple chronic illness, (18.0%); and relatively healthy, (9.0%). Looking at standardized data, they identified the highest 10% of most costly patients, and found that 46.2% were in the frail elderly group, with most of the rest being in the non-elderly disabled, (14.3%), and the major complex illness group, (11.1%). Using validated algorithms, they estimated “preventable” spending in each of the six groups, and in the subpopulation of high-cost patients. For the group, 4.8% of the spending was identified as potentially preventable, but 43.9% of this was concentrated in the frail elderly group. When they looked in detail, most of the potential “savings” were inpatient care, ($3164 per person,) and in skilled nursing facilities, ($1917.) When looking at diagnoses, much of the preventable care was associated with acute care visits for heart failure, bacterial pneumonia, urinary tract infections, diabetes long-term complications, and dehydration. The authors conclude by making some observations on where spending for ambulatory care might reduce some of this avoidable spending, but, of course, would probably not result in much net savings to the system. As a practicing clinician, these observations have face validity. I find these data encouraging to the extent they suggest most of what we are currently doing is not “preventable.” From a public policy perspective, this is bad news, in that it suggests there are no simple solutions to the problem of Medicare spending. The latter point was addressed in an accompanying editorial by Leff and Milstein.[2] They note that many of the health care systems at financial risk are currently able to reduce spending more than 5%, primarily by reducing hospitalization, thereby confirming the analysis of Figueroa and associates. But they note that other programs, such as palliative care, are not consistently offered to patients with limited life-expectancy, perhaps because most of the persons in the current system lack financial incentive to do so. They also note social determinants of health care matter, such as lack of transportation. They conclude: “New payment and patient assignment models are also needed, and their creation will not be easy.” Both these articles are describing population-based analyses in which patients are assigned to a group. In fact, patients tend to have their own trajectory, and may move from one class to another relatively quickly. The bottom line, though, is that the frail elderly are the group where the most opportunity lies to reduce expenses, and they are not going to get younger and spryer, no matter what we do. I recall a conversation with one of my more observant dialysis patients following the death of another patient. She said: “I saw it coming. When I went back on dialysis, she was walking in, then she was coming in with a walker, then a wheelchair, and here at the end on a stretcher.” This echoes the data in the geriatric literature that walking speed is one of the best measures of frailty. We can do a great job measuring hemoglobin A1c, an okay job with weight and blood pressure, but in routine practice we don’t measure walking speed, mental acuity, or memory with any standardized “lab tests.” Even if we do try to capture these elements, there is no ICD 10 modifier code captured in the electronic record to either track these data or to communicate this information to the ED or in-patient hospitalist, neither of whom can accurate assess baseline function during an acute illness or decompensation. The best we can do now is talk to family members to try and gain some sense of how they were doing before getting sick. In the “olden days,” when the same physician followed the patient in different care settings, his or her individual memory, knowledge, and attitudes, combined with rapport led to informal, non-standardized decision-making. But today’s situation is different. Care in different locations is provided by different physicians, and in the office setting, there is probably an advanced practice nurse rather than a physician. Hence, all decision-making is done in crisis mode. I really don’t think physicians avoid palliative care because of financial considerations. It reflects the challenge of having difficult conversations with patients and families that you don’t know, and when you don’t have good longitudinal data to show them the patient has been declining steadily and will not, under any circumstance, be returned to “health” at the end of the current episode. Changing coding systems and professional practices to include assessments of frailty and cognitive impairment on some sort of regular basis are not simple, but don’t require anywhere near the number of steps required to change payment systems. What is required is for all of us to start defining what can be reasonably expected from the interventions we offer adjusted for the patient’s physical and mental function. EMR systems can be modified to display this information as prominently as any other data. This is personalized care at its best—we should settle for no less, regardless of financial incentives. 27 November 2017 [1] Figueroa JF, Joynt Maddox KE, Beaulieu N, Wild RC, Jha AK. Concentration of Potentially Preventable Spending Among High-Cost Medicare Subpopulations: An Observational Study. Ann Intern Med 2017;167:706-713. doi. 10.7326/M17-0767. [2] Leff B, Milstein A. Possibilities Beyond Analyses of a Fee-for-Service Database and Clinician Mindset. Ann Intern Med 2017;167:746-747. doi.10.7326/M17-2627. |
Further Reading
Changing Physician Behavior Population Health Population health is a phrase that disguises some hard realities as illustrated by two recent reports. Recovering Professionalism A recent flurry of articles show the challenges to medical practice have reached critical mass. The Hospitalist Dilemma Is the hospital medicine model a boon, a bane, or a response to an unresolved underlying problem? Thoughts on Clinical Realities |