Veta Health | October 2018
Care redesign is essential to an organization’s success in shifting from Fee-for-Service to Value-Based Care models – but where should an organization begin for success?
Depending on who you’re talking to, we hear conflicting predictions from various healthcare stakeholders on whether or not we’re going to continue the momentum to achieve a successful shift to value-based payment models across healthcare, and whether or not a complete shift will realistically happen. These predictions are usually supported with case studies from organizations who have successfully implemented strategies of care redesign to support value-based care, as well as case studies from organizations that have yet to experience success in shifting from fee-for-service to value-based payments. For any organization, degrees of success have a lot to do with the resource allocation of a given organization to strategically redesign care delivery models.
As organizations develop and refine strategies to support the shift to value-based care, it’s important to identify what changes will have the lowest barriers to entry, with the greatest yield – or the low hanging fruit. Transforming care by implementing digital solutions to automate resource intensive processes in the care delivery lifecycle, is how organizations can achieve efficiency while reducing costs.
Value-Based Payments, By The Numbers
By the end of 2017, 34% of healthcare payments were tied to value, up from 23% in 2015, based on a new report from the Health Care Payment Learning and Action Network, a part of the U.S. Department of Health and Human Services. This 34% of payments came from two main categories: alternative payment models, grafted onto a fee-for-service framework and population-based payment. It encompassed about 226 million patients in the US, coming to roughly 80% of the insured population in the US.
In 2017 the percentage of APMs across markets for commercial business lines was 28.3%, 49.5% for Medicare Advantage, 38.3% for Medicare fee-for-service and 25% for Medicaid. This marks an upswing in payments tied to APMs, which was detailed in a report from the Health Care Learning and Action Network, in 2017. The report looks at 2016 data and the analysis found 29% of healthcare payments tied to APMs at that time – proving a natural progression from then to now.
Earlier in 2018, the Centers for Medicare and Medicaid Services (CMS) announced changes with the goal of further aligning quality reporting measures for both physicians and hospitals, and driving more eligible clinicians toward the APM track.
It’s clear that value-based models are here to stay, but redesigning care is a significant lift for many organizations, especially those without the existing resources. For any healthcare organization it’s best to start with the low-hanging fruit, by identifying the processes that could be improved with automation.
When we say automation, we’re talking about using technology to help increase efficiency and scale existing processes & workforce. There are a number of areas where automation can play a huge role in workflow optimization and efficiency, but there are a few we highlight as high-impact:
Data: Collection & Analytics
There’s an apparent need across the healthcare industry to effectively collect, digitize and analyze all of the existing data on patients. Data on even just a single patient likely lives across different health systems and repositories, with little to no communication or tracking mechanism. To date, we haven’t seen enough efficiency in running data centers, largely a product of the manual data collection methods, incomplete data sets on patients, and the time spent tracking down patients for follow-up, sometimes years later. Automation in data collection and analyzation is a huge opportunity to increase efficiency and reduce waste – and with the rise in digital data collection methods that extend outside the care facility, we’re seeing patient-generated health data (PGHD) become more meaningful and standardized, enabling the advancement of predictive analytics, and evidence-based medicine.
Patients: Appointments & Billing
Two significant opportunities for optimization through automation lie on each end of the patient visit – their experience getting in the door, for the first time or for unique visits/procedures, as well as after a visit, through the billing process. The impact of digitally onboarding a patient with automatic feedback loops to administrative & clinical teams ahead of a visit ensures patients are optimized before walking in the door, decreasing costs for practices by optimizing appointment wait times, alignment of covered & received services, and increases patient retention, which can be a challenge in today’s healthcare landscape.
Additionally, billing departments have seen a high volume of claims that sit in accounts receivable. At times organizations end up eating costs, or continuously bill patients to no avail. Which translates to unplanned costs. An analysis conducted by the Advisory Board on over 400,000 patient claims found that a patient’s propensity to pay, significantly decreases as deductibles increase, irrespective of income level. We see a number of digital health companies successfully innovating on the automation of payment collection and tracking both at the point of service and following patient visits, showing ROI almost immediately to healthcare organizations by reducing the number of unpaid claims, without additional effort from the care teams and staff.
Clinicians: Workflow & Decision Support
As we shift to value-based care models within hospitals and practices, automation at various points in clinician workflows is high value both financially and clinically. The ROI is tangible and measurable, and care team satisfaction increases, at a time when clinician burnout is at an all time high. Clinicians are tasked with tracking patient outcomes longitudinally, assuming direct responsibility for their care journeys up to 90 days after they’ve left the facility. The follow-up in this time period has traditionally been manual, leaving clinicians spending more time on patient outreach and documentation and less time directly caring for patients. Care coordination efforts can only be scaled by care management teams to a certain patient volume before needing additional FTEs. With automation, nurses and care coordination teams are able to more effective scale their efforts. The time traditionally spent manually contacting patients is decreased, and clinicians are connected to patients at risk of an adverse health event in real-time, and with clinical decision support tools, ensure patients receive the most effective clinical pathways and interventions, decreasing chance of human error in documentation, patients falling through the cracks, or be readmitted to the hospital.
As health systems develop and further refine their care delivery redesign strategies to support value-based models, it’s beneficial to evaluate digital health partners who specialize in targeted areas of care automation. As subject matter experts, these companies have been built on the pillars to support each healthcare organization, deliver ROI, and implement standardized metric tracking for continued success that show reduce costs, and increase efficiency increasingly over time.
What is your organization’s low-hanging fruit?