In order to grapple with spending increases, the U.S. healthcare industry is transforming the way physicians are compensated to provide care to patients from the current fee-for-service (FFS) model to one in which medical providers are paid a flat fee for servicing a defined group of patients.
This pivot in reimbursement is often discussed as far off. A survey by Numerof & Associates, a St. Louis, Missouri-based healthcare strategy consultancy, finds that most health organizations have been slow to make the shift: 54% receive less than 10% of their revenue from risk-based agreements.
However, as consumers become more sophisticated, and payers and health systems become more emboldened to wring out costs, we expect to see the shift in reimbursement models take off in the coming years. Provider groups that embrace this shift now have an opportunity to gain meaningful first-mover advantages.
Policy changes will further enhance the transition. Annual FFS pricing increases are set by the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA), and physicians treating Medicare patients will receive FFS raises of 0.5% this year and next. Then, from 2020 through 2024, there will be no automatic payment increases.
That’s not a recipe for growing revenues. But instead of fearing the transition to a value-based compensation model, physician groups that have the foresight and inclination to harness analytic tools, patient data, and standardized processes will have a leg up on other practices, positioning them to win new contracts with payers and systems, and capture more patient volumes.
A key to a profitable shift away from the traditional FFS reimbursement model is a practice’s ability to effectively price a procedure based on their understanding of the patient’s medical history and other risk factors, as well as an understanding of what it costs to perform the procedure, including consumables, implants, and the time the physician spends with the patient. Automated or programmatic data analysis can help.
A good place to begin is an analysis of the top procedures the group performs. Using data from the practice’s electronic medical records system to answer the following questions can help providers determine a competitive price for these procedures.
As an example, an orthopedic group analyzing the pricing for a knee replacement might evaluate:
What is being spent on implants? Are there commonalities or preferences on implants across the group? If a standard implant system could be selected, the group could standardize procedures or timing, allowing it to negotiate for better prices with vendors and better price the time associated with the procedure.
What are the common complications associated with knee replacements? Are there recommendations that can be given to patients to reduce complications and hospital readmissions and improve outcomes?
What are the facility charges?
With this level of data in hand, a group can develop a series of costs for procedures and an appropriate target profit per patient before negotiating a capitated rate with a health system or insurance company.
Physician practices that are making the move to this model now by partnering with or serving a healthcare system or insurance provider are significantly growing their businesses. In doing so, they exchange the potential upside of being able to charge for extra services for the ability to gain market share by treating significantly more patients.
Groups that do not have this level of sophistication or understanding of their data or how to deliver care in a cost-effective manner will be at a profound disadvantage and will likely miss the opportunity to participate in ACOs or narrow provider networks.
All this requires significant analysis of data that the practice can draw from its electronic health records system. Some practices will be able to undertake this analysis with the leadership and guidance of a controller and a billing team, while others may need assistance from a consultant. Currently, numerous data-focused healthcare information service businesses are helping physician groups sift through their patient data, procedure outcomes, and expenses to effectively price their services.
This approach can deliver better healthcare to patients at a lower price while helping efficient practices grow significantly. By using data and analytics in this way, healthcare providers and insurers have the same incentive to lower healthcare costs. We’re already seeing this approach work.
Kaiser Permanente, for example, owns both its own insurance and health systems, in which 95% of its 12.2 million members are covered on a capitated basis. All manner of practices can benefit from this approach, from dermatologists, orthopedic surgeons, gastroenterologists and ophthalmologists, to name just a few.
The Harvard Business Review writes that the value-based approach can trim waste from U.S. healthcare spending while also making physicians’ practices significantly more profitable: “Better products at lower costs generate higher value, which helps organizations achieve better market positions. Strategies based on that thinking have transformed other industries. We believe that they will do the same in healthcare. Population-based payment will play a critical role in helping care delivery groups make that leap.”
Whether physicians’ practices like it or not, this transition is taking place. It may take the next 15 to 20 years to get there, but it’s always good to be ahead of the curve.
The All of Us Research Program, part of the National Institutes of Health (NIH), has launched the Fitbit Bring-Your-Own-Device (BYOD) project. Now, in addition to providing health information through surveys, electronic health records, and bio-samples, participants can choose to share data from their Fitbit accounts to help researchers make discoveries.
According to All of Us research program officials, the project is a key step for the program in integrating digital health technologies for data collection.
The All of Us Research Program, established by the White House in 2015, aims to advance precision medicine by studying the health data of 1 million diverse Americans over the next five years. One aim of the project is to include groups that have been historically underrepresented in research. As of September 2018, more than 110,000 people have registered with the program to begin the participant journey, and more than 60,000 have completed all elements of the core protocol.
The participants are sharing different types of information, including through surveys, access to their electronic health records and blood and urine samples. These data, stripped of obvious identifiers, will be accessible to researchers, whose findings may lead to more tailored treatments and prevention strategies in the future, according to program officials.
Digital health technologies, like mobile apps and wearable devices, can gather data outside of a hospital or clinic. This data includes information about physical activity, sleep, weight, heart rate, nutrition, and water intake, which can give researchers a more complete picture of participants’ health.” The All of Us Research Program is now gathering this data in addition to surveys, electronic health record information, physical measurements, and blood and urine samples, working to make the All of Usresource one of the largest and most diverse data sets of its kind for health research,” NIH officials said.
“Collecting real-world, real-time data through digital technologies will become a fundamental part of the program,” Eric Dishman, director of the All of Us Research Program, said in a statement. “This information, in combination with many other data types, will give us an unprecedented ability to better understand the impact of lifestyle and environment on health outcomes and, ultimately, develop better strategies for keeping people healthy in a very precise, individualized way.”
All of Us participants with any Fitbit device who wish to share Fitbit data with the program may log on to the All of Us participant portal at https://participant.joinallofus.organd visit the Sync Apps & Devices tab. Participants without Fitbit devices may also take part if they choose, by creating a free Fitbit account online and manually adding information to share with the program.
All of Us is developing additional plans to incorporate digital health technologies. A second project with Fitbit is expected to launch later in the year, NIH officials said, and this project will include providing devices to a limited number of All of Us participants who will be randomly invited to take part, to enable them to share wearable data with the program.
The All of Us research program plans to add connections to other devices and apps in the future to further expand data collection efforts and engage participants in new ways.
The University of Chicago Medicine was able to adjust hospital EHR use and educate doctors and nurses on how to reduce in-hospital sleep deprivation, thereby improving sleep for patients staying at the hospital.
The changes were part of a study designed by UChicago Medicine researchers called Sleep for Inpatients: Empowering Staff to Act (SIESTA), which examined the effects of nighttime sleep interruptions on patients in the hospital environment and how to improve patient sleep.
For the study, SIESTA employed electronic “nudges” using the patients EHR to urge doctors and nurses to avoid sleep disruptions that have minimal value, such as waking patients at night to take vital signs or administering nonurgent medications.
“Efforts to improve patients’ sleep are not new, but they do not often stick because they rely on staff to remember to implement the changes,” said Dr Vineet Arora, a professor of medicine at the University of Chicago and the study’s lead author.
For the study, the researchers interviewed patients about sleep barriers. During the interviews, the researchers found that major barriers to sleep were taking vital signs, administering medications, and drawing blood during sleep hours.
The researchers also found out that doctors did not know how to change the default vital signs order for every four hours or how to batch-order morning blood draws at a time other than 4 am.
Based on the interviews, the researchers developed and integrated electronic nudges into the EHR and taught doctors and nurses about the sleep friendly tools in the system. Taken together, these changes reduced the number of unnecessary sleep interruptions.
The researchers published the results of the study in the January 2019 issue of the Journal of Hospital Medicine.
The one-year study focused on two 18-bed general medicine units at UChicago Medicine. Between March 2015 and March 2016, 1,083 patients were admitted either to the SIESTA-enhanced unit or to a standard hospital unit nearby.
Both units had doctors who were trained in the use of nighttime orders, but only the SIESTA unit had nurses who were trained to advocate for patients with the doctors.
For the SIESTA unit, decisions by doctors and nurses not to take vital signs every four hours increased from 4 percent to 34 percent and sleep friendly timing of medication administration rose from 15 percent to 42 percent. Nighttime room entry decreased by 44 percent.
For the standard unit, decisions not to take vital signs every four hours increased from 3 percent to 22 percent, sleep friendly timing of medication administration increased from 12 percent to 28 percent.
As a result, patients in the SIESTA unit had six fewer nighttime room entries, four times fewer sleep disruptions for medication administration, and three times fewer sleep disruptions for vital signs.
The researchers concluded that adjustments to the EHR system along with doctor and nursing education significantly reduced the number of nighttime vital sign orders and led to better timing of nighttime administration of medications in both units.
However, the study found that having the nurses as patient champions helped to sustain the benefits of a sleep friendly environment in the SIESTA unit over time.
Sara Ringer, a patient in the SIESTA unit, said that the changes enabled her to sleep more soundly. “As a frequently hospitalized patient, I am used to being woken up as often as every 1 to 2 hours. It never feels like your body has a chance to rest and heal. My last hospitalization at University of Chicago was one of the easiest I've had because the hospital staff made it possible for me to sleep.”
“This illustrates the importance of engaging both nurses and physicians to create sleep-friendly environments in hospitals,” concluded Arora.
The research was funded by the National Institute on Aging and the National Heart, Lung and Blood Institute.