When you live in a small town that is at least a half hour away from “big box stores” and other commercial outlets you begin to develop some shopping efficiencies. Recently, before driving the one hundred miles south to Boston for me to attend a meeting, my wife and I asked ourselves was what tasks should we accomplish along the way. There are many options right on the way in Manchester and Nashua. I was a little surprised when my wife said that we needed to stop in Concord to buy a refrigerator before stopping at Costco in Nashua to restock our supply of ibuprofen.
It may seem that her answer was a little impulsive but after a second’s thought I realized it really wasn’t. She is working through her “punch list”. We have just renovated our home and there are still some holes to be filled before her vision is complete. It may be an extravagance but we would like to have a new overflow refrigerator-freezer in the garage to replace an old one that is a very tired twenty year old veteran. She had purchased all of our other new appliances at a store in Concord and had liked their service.
As is usually the case, the item we decided that was best for us was a little more expensive than we had expected, but we bought it anyway. As we left the store we were asking ourselves why we had made the purchase. Had we been rational? We were headed to Costco to buy ibuprofen to save a couple of bucks? We might have saved a couple of hundred dollars if we had gone to a discount store. We could have gone online and looked for a bargain. We knew that we would pass several other places to buy appliances like BestBuy and Sears between the store in Concord and Costco in Nashua; but we chose to pay more.
Classical economic theoretical considerations would have predicted that we would have made the purchase that was in our best financial interest but we did not. Our decision to buy is usually weighted heavily toward price, but economists have a hard time predicting behavior in the market. There are factors other than price that drive our behavior.
Our defense to ourselves for paying more was that we trusted the store. We knew our new refrigerator would be delivered efficiently and they would take away the old fridge. We were coming off a very positive sales and service experience with them. We knew them by their reputation for service if problems were to rise in the future. If need be, they were willing to come to us which is a positive if you live in an out of the way place. In that context our economic behavior was understandable and rather easy to defend, despite the fact that most of the advantage that we were buying was based on trust that was derivative of only one previous direct interaction but also a reputation earned over many years with other people we knew and trusted.
The conference that I was attending in Boston was called ATLAS which stands for the Annual Thought Leadership on Access Symposium and is presented by Kyruus, as a disclosure, I have been affiliated with Kyruus as a member of its clinical advisory board for about a year and a half. This was to be my second ATLAS conference and I new if it was as good as the first one, I was in for a treat. The agenda of individual presentations and the panel discussions that were planned was exciting to anticipate and was noteworthy for its blend of subjects that ranged from social media to healthcare economics, with a clearly demonstrated awareness of the importance of judging everything from the point of view of creating value for patients.
Among many great presentations, the one that struck me as containing the most useful piece of new information to consider as we try to understand an uncertain future was a conversation presented under the title of “Dr. Right: The Clinical Imperative of Patient-Provider Matching”. It was actually a conversation with Professor Amitabh Chandra who is an economist and Director of Health Policy Research at the Harvard University Kennedy School. If you are a regular reader of these notes you have seen Professor Chandra’s name before. Most recently I reported his thoughtful presentation at the 2015 Massachusetts Cost Trend Hearings.
In the opening minutes of the conversation Professor Chandra was asked to discuss a paper that he had recently published in the economics literature. What he described was what we would call in healthcare a “natural experiment”, something like the moment in time back in 1969 when the entire Holy Cross Football team was simultaneously exposed to hepatitis A via a contaminated water source dispensed during a mid-practice water break during their preseason workouts. If you want that story from a lay perspective, click on the link.
The “natural experiment” that Professor Chandra studied was the impact on the purchase of healthcare by the employees of a large company that decided to put every employee and their dependents on a high deductible health plan coupled with a health spending account of about $3500 and a cap on maximum out of pocket expenses of about $6500. There was total equity. The CEO got the same benefit as the receptionist at the front door. The sample size was large enough to give statistically significant sample sizes at all income levels and the medical status of employees was known. Here was an opportunity to see how personal income, disease status and coverage interacted in “the wild”.
The paper is a robust 78 pages long. Here is the abstract. The bolding is mine. The message is scary because people avoided the expense of care they needed.
Measuring consumer responsiveness to medical care prices is a central issue in health economics and a key ingredient in the optimal design and regulation of health insurance markets. We study consumer responsiveness to medical care prices, leveraging a natural experiment that occurred at a large self-insured firm which forced all of its employees to switch from an insurance plan that provided free health care to a non-linear, high deductible plan. The switch caused a spending reduction between 11.79%-13.80% of total firm-wide health spending ($100 million lower spending per year). We decompose this spending reduction into the components of (i) consumer price shopping (ii) quantity reductions (iii) quantity substitutions, finding that spending reductions are entirely due to outright reductions in quantity. We find no evidence of consumers learning to price shop after two years in high-deductible coverage. Consumers reduce quantities across the spectrum of health care services, including potentially valuable care (e.g. preventive services) and potentially wasteful care (e.g. imaging services). We then leverage the unique data environment to study how consumers respond to the complex structure of the high-deductible contract. We find that consumers respond heavily to spot prices at the time of care, and reduce their spending by 42% when under the deductible, conditional on their true expected end-of-year shadow price and their prior year end-of-year marginal price. In the first-year post plan change, 90% of all spending reductions occur in months that consumers began under the deductible, with 49% of all reductions coming for the ex ante sickest half of consumers under the deductible, despite the fact that these consumers have quite low shadow prices. There is no evidence of learning to respond to the true shadow price in the second year post-switch.
Professor Chandra’s discussion suggested that decision aids and price transparency were in place. When patients did purchase care many of them reacted like my wife and I did at the appliance store. They made choices that were not always explicable in purely economic terms. The message to me was that a future that is significantly determined by the economic choices of patients may be quite chaotic. We must consider ways to reach populations under these plans with tools that help them make better decisions and not avoid the care they need. It has been clear for some time that even the most superficial discussions of the barriers to the Triple Aim usually quickly become a discussion of economics and resource utilization.
This train of thought brought me into rethinking much of what I hold to be axiomatic. So far my conclusion is that everything I believe to be true is generally true but there are barriers to success in the details and complexity that will force us to be better than we are and develop tools and attitudes that are in very short supply or still evolving at this time. The destination or the BHAG (big hairy audacious goal) has not changed. It is still the Triple Aim. What is clear is that we have a lot more work to do on medical markets, understanding the mind of the consumer, managing evolving workforce challenges, optimizing insurance plans and benefits, and improving our ability to price care as a function of outcomes rather than current cost. Universal coverage and improved primary care and behavioral health are goals that are vulnerable to pricing and costs and the outcome we desire needs to consider the variations in behavior that arise from the way that individuals seek to pursue what is valuable to them.
