U.S. healthcare has a $40 billion problem — and it’s one that we must treat immediately.
This problem is unplanned hospital readmission from patients whose conditions deteriorate soon after treatment, which is an enormous and expensive burden on the system that will only grow if not properly addressed. In 2011, there were about 3.3 million 30-day hospital readmissions in the U.S., a figure that is associated with approximately $41.3 billion in healthcare costs. According to more recent statistics, 15 percent of Medicare patients — who generally require the most care and consume the most healthcare resources — are readmitted to hospitals for unplanned treatment within 30 days of leaving, which costs Medicare about $17 billion a year.
A perfect way to illustrate the readmission challenge is sepsis, one of the leading causes of hospital readmission, which is estimated to cause between one-third and one-half of all in-hospital deaths. Due to hospitals' increased efforts at reducing sepsis and sepsis-related deaths, more patients are surviving sepsis. This had a knock-on and unforeseen impact - their readmission risk increased by nearly three times for 2010 to 2015.
A research letter by Prescott et al published in JAMA examined the causes of sepsis readmission and found that 41.6 percent of cases were sensitive to ambulatory care. Lead author Hallie Prescott wrote, "Getting on the right medications and diet, receiving counseling on infection risks and signs, and having kidney function tested more often, could be examples of post-hospital interventions that sepsis survivors could benefit more from." However, these options are only available if we are able to identify those who require treatment — at a point that ambulatory care is still appropriate.
The economic and clinical burden of readmissions are accompanied by emotional and financial strain on patients and their families, and also poorer patient outcomes. As a result, payers, government and healthcare providers are now focused on reducing readmissions.
Payers, through value-based contracting and metric assessment have begun heavily incentivizing providers to reduce readmissions. Under the Affordable Care Act (ACA), CMS is required to financially penalize providers if their level of readmissions is higher than the national average. In 2017, these penalties amounted to a $528 million reduction in Medicare payments. However, these penalties, under the Hospital Readmissions Reduction Program, are only one part of the total cost to health systems of readmissions. Those with private health insurance, those who can’t pay and state Medicaid plans, all are penalising health systems for high readmissions. As health systems move to more capitated and accountable healthcare models, the financial risks exponentially increase.
These costs are set against a constellation of ever growing economic and operational challenges faced by healthcare providers. As more care shifts to an outpatient environment, it has caused reductions in inpatient volume, reducing reimbursements.
At the same time, providers face increasing labor costs and an absence of primary care for the uninsured population, turning the emergency department (ED) into a de-facto primary care center for this population. For example, Cleveland Clinic saw its Q2 2018 operating income drop by 80 percent as a result of this.
Strategy 1 - Improve risk stratification at index hospitalization
The first strategy is to better understand who is high risk as they are hospitalized. Much work has been done on readmission risk scores, such as those at Intermountain Healthcare. However, evidence for these scores is weak. As one recent systematic review published in JAMA showed, most of these scores perform poorly.
We believe that an important reason for the poor quality of these scores is the absence of deep data and understanding at the individual level. Scores are built at a population level and rely on data solely from the EMR, such as prescriptions, procedures and demographics. This data is often erroneous or missing. Remote patient monitoring provides us with real-time data and far deeper understanding of an individual patient’s health. By combining this data with existing data sets and extrapolating insights through machine learning, there is the potential to greatly increase the sensitivity and specificity of scores.
Remote health monitoring offers one further benefit in this regard. For elective admissions--for example, a hip replacement--it also allows pre-admission monitoring to better stratify who is high risk before they are even admitted. This then allows far earlier changes in treatment plan.
Strategy 2 - Improve care transitions
The 48 hour period after a patient leaves the hospital is one of the highest risk periods. It's a time of vulnerability and anxiety for the patient. The jump between hospital and home is significant, there is dramatically less (sometimes zero) support once the patient gets home. Even the jump between hospital and a nursing facility or care facility sees a significant reduction in support and monitoring.
Understanding that health and care does not end once the patient leaves the hospital, is critical to reducing readmissions. Optimizing this transition period, and ensuring the patient is surrounded by support and services can and has been shown to reduce readmissions and improve outcomes. For example, a study published in JAMA in 2006 showed that by providing the patient with communication tools, coaching and by encouraging patients to take more of an active role in their health and care reduced readmissions at 30 days and 90 days.
A particular challenge in transitional care management is providing coaches and care managers with more insight into patient health at home. Remote health monitoring has potential to greatly change this, by providing care managers and coaches with objective information on the patients health trajectory once they leave hospital. By linking patient educational content to the objective insights generated on their health, we also believe it's possible to increase patient empowerment.
Strategy 3 - Improve post-discharge monitoring and treatment
As identified in Prescott’s letter, just under half of sepsis readmissions may be treatable through ambulatory care. However, delivering treatment is only part of the problem. First, you must identify the patients who actually require treatment. After the patient leaves the hospital, they enter a black box where physicians and healthcare professionals have little idea of the patient’s health trajectory. Patients don’t always know when they need to call their doctor.
Advances in technology can relegate this problem to a thing of the past. Wearable, passive remote health monitoring has the ability to continuously measure patient health at home while advances in AI allow actionable insights and early warnings to be generated from this data. Platforms, like that developed at Current, are likely to become the norm in future.
The move toward predictive medicine is a huge market opportunity, which is why more and more established tech companies are entering the remote patient monitoring technology (RPM) space.
Current's platform is one solution to this problem, delivering passive, wireless monitoring of patients at home combined with predictive analytics to deliver a patient-specific early warning.
Our wearable is the most sophisticated and accurate all-in-one wireless device available, providing continuous ICU-level monitoring in any setting. Acting as a hub, it seamlessly integrates with a range of peripherals, such as for weight or peak flow. There’s no time consuming manual entry - for the patient or for healthcare staff. Our patient app allows patients to report symptoms, receive medication reminders, review educational content and undertake video visits with their doctors.
Our platform continuously analyzes the data being collected to deliver sensitive and specific early warnings to physicians and healthcare staff. We’ve already seen this reduce readmissions, empower patients and free staff from manual tasks.
This amassing and instant analysis of all kinds of patient data will enable medical professionals to detect the deterioration of a patient’s condition at an earlier, proactive point, reducing the strain on the healthcare system and improving the patient’s outcomes.