For all the advances in both medicine and technology, patients still face a bewildering array of advice and information when trying to weigh the possible consequences of certain medical treatments. But a hands-on, data-driven tool I have developed with some colleagues can now help patients obtain personalized predictions for their recovery from surgery. This tool can help patients better manage their expectations about their speed of recovery and long-term effects of the procedure.
People need to be able to fully understand the possible effects of a medical procedure in a realistic and clear way. Seeking to develop a model for recovery curves, we developed a Bayesian modeling approach to recovery curve prediction in order to forecast sexual function levels after prostatectomy, based on the experiences of 300 UCLA clinic patients both before radical prostatectomy surgery and during the four years immediately following surgery. The resulting interactive tool is designed to be used before the patient has a prostatectomy in order to help the patient manage expectations. A central predicted recovery curve shows the patient’s average sexual function over time after the surgery. The tool also displays a range of lighter-colored curves illustrating the broader range of possible outcomes.
This talk was given at a local TEDx event, produced independently of the TED Conferences. Ayesha Khalid, surgeon at Harvard Medical School and recent MBA from the MIT Sloan Fellows Program, is at the intersection of disruptive innovation in healthcare and the digital health experience. Ayesha previously pioneered groundbreaking research in sinus disease including muco-ciliary clearance and outcomes following surgery. She is now a passionate believer that disruptive innovation in healthcare requires collaboration, not competition. Using a systems thinking approach, Ayesha wants us to suspend our belief that adding more process to our healthcare system will add back “health” and “care” to a broken system. Instead, this compelling talk provides an imaginative way to approach the redesign of our health care system to one that promotes “health” and works “systematically” for the patient.
A sinus surgeon at Harvard Medical School and recent MBA graduate from MIT, Ayesha Khalid is a healthcare innovation enthusiast involved with entrepreneurial ventures at the intersection of healthcare innovation and digital technologies. She has pioneered groundbreaking research techniques in inflammation and sinus disease and is working to create different funding paradigms to accelerate clinical research.
For more information, see this op-ed about Dr. Khalid’s approach to reshaping the healthcare system in Huffington Post UK.
Ayesha Khalid is a surgeon at Harvard Medical School and recent MBA graduate from the MIT Sloan Fellows Program.
The days of the passive patient and omnipotent Marcus Welby-like physician are long gone. Since the 1990s, consumer empowerment in health care has been increasing, most notably with the advent of direct-to-consumer advertising for prescription medicines. Then, the rise of digital media allowed consumers to search symptoms and create communities around common disease experiences. More recently, the ability to shop for health insurance through health care exchanges and obtain treatment at drug store clinics has led to a new age of consumer empowerment.
We’ve gone from a B-to-B model to a B-to-C model in health care. This shift in power to consumers has many implications when it comes to how we make decisions about our health care. Here are six ways that a behavioral lens can help us understand the implications of empowering consumers in health care:
Heuristics are very important. These mental shortcuts or “rules of thumb” allow us to make decisions efficiently. However, these judgments are subject to non-rational (or biased) influences in the marketplace. For example, a retail promotion like a drug store coupon can affect the price on which patients “anchor” their judgments about the appropriate cost of health care. And a retail clinic can affect the appeal of non-healthy alternatives with their location, like in the candy aisle. While this may not have been a big deal before, it is an important consideration in a B2C retail environment.
Picture yourself going to the doctor. You arrive by car, park nearby, and when you enter a receptionist greets you and checks your information on a computer. You’re led into a comfortable, well-lit office; the cabinets are fully stocked. Your records are on hand. The nurses and doctors are well educated and knowledgeable, their equipment at the ready. If they can’t help you, they refer you to someone who can.
Now try to picture the same scene in sub-Saharan Africa. If you’re wealthy, your experience may be similar. But if you’re not, it’s altogether different. The roads are unpaved and riddled with potholes; it might take all day to get to the clinic by public transport. The queue to see the doctor is long–an eight-hour wait is not unusual–and there’s nowhere to sit. You might have to bribe someone to be seen. The electricity is unreliable; the clinic’s supplies are running low. Your medical records are incomplete, perhaps even non-existent. The doctors and nurses, while trained and dedicated, are not up-to-date on current treatments, and lack access to the tools they need.
As our healthcare system moves from compensating providers on the basis of quantity of care to quality of care, it’s very important to measure hospital performance. But a key limitation for that measurement is patient selection.
A large body of research suggests that it doesn’t matter where patients go for treatment. Teaching hospitals, for example, have been found to achieve modestly better health outcomes. Unfortunately, patients in worse health tend to choose or are referred to hospitals based on the facilities’ capabilities. So hospitals with higher levels of treatment intensity – meaning teaching hospitals or hospitals that perform the latest procedures – could appear to have poorer grades on healthcare report cards because they are treating the sickest patients.