Skilled nursing facilities face many challenges today, among them being the outflux of patient transports to the hospital.
Every year, approximately 1.3 million patients are transferred from a skilled nursing facility (SNF) to an Emergency Department (ED) in the United States.
Given the patient population they care for, nursing home staff are typically hired for—and are experts in—chronic care. Market dynamics make it difficult to staff nursing homes with enough personnel to attend to both chronic and acute needs; thus, patients who experience acute changes of condition are transferred to the ED in the vast majority of cases. With a multitude of pre-existing comorbidities, these transferred patients are almost invariably admitted to the hospital, where it costs the healthcare system an average of $15,000 per patient for every transfer. Patients suffering from conditions as simple as early-onset urinary tract infections often spend multiple days in a hospital, away from their home, leaving them feeling isolated and uncomfortable.
Many of these patients could be treated in the comfort of their beds within the nursing facility, if our healthcare system provided the tools and incentives that enabled facilities to do so. Nursing home operators and administrators face significant challenges, including tight operational margins & corresponding staffing difficulties with which to care for a resource-intensive patient population. Moreover, the current payer reimbursement model typically limits the options available to them.
By gaining more visibility into their operations, administrators have an opportunity to make changes within their organization that can help optimize operations, improve care and reduce ED transports, and ultimately drive further revenue into the nursing home where it can be used for even more meaningful improvement for the patients they serve.
Visibility through Data and Predictive Analytics
Gaining greater visibility into the day-to-day facility operations can provide SNF administrators with a wealth of information which they can then leverage to reduce the volume of transfers to the ED, improve the quality of care and reduce costs.
First and foremost, operational data can enable administrators to track the volume of transfer rates, the percentage of transfers that were avoidable, and when and why transports are taking place.
It is also important to look at the factors contributing to transfer rates so they can be systematically addressed. Facilities can start by tracking which indicators suggest patients will be transferred to the ED most often, using underrecognized data points that identify certain patients are at the highest risk of transfers. By understanding which patients are at highest risk for transfer, facilities can essentially predict emergency calls before they happen, and then take steps to reduce transfer rates by creating more tailored care plans for those patients, engaging their families and PCPs early and often, and frequently monitoring those patients’ vital signs.
Another contributing factor facilities can track is whether patients are consistently being transferred at a significantly higher volume during certain staff shifts or days of the week. If data shows that this is the case, facilities can dig deeper as to the underlying causes; there may be a need for additional training or support for staff members, or for certain staff to be placed on particular units in order to care for the needs of higher risk patients – for example, a facility may choose to place RNs on high acuity units and place LPNs on other floors.
If patients are being transferred more often during certain times or days of the week – such as in the evenings or on weekends – facilities may choose to make an adjustment in staff allocation in order to support those staff members in caring for patients, such as shifting some daytime staff over to a weekend shift. Another option they may consider is leveraging third-party technology and services solutions that can support the facility with treating patients in their beds. Technology, coupled with informed and integrated services, can facilitate quality care and drastically reduce transports.
Finally, having access to operational data enables facilities to better visualize the financial impact of the cost of transfers and hospitalizations over time. Reviewing data points such as the cost of lost patient days and revenue for each avoidable transfer allows administrators to see how the changes they’re making are impacting the organization financially.
Uncovering the Data
Some of this operational data is available within electronic health records currently utilized by many SNFs; in order to obtain the most useful insights, however, it’s helpful to compare information a facility is seeing in their own EHR with nursing home patient trends both locally and nationally. The most important step in approaching predictive analytics is not gathering the data, but determining which points are most valuable and then analyzing the data in a meaningful way so it can be used to create change. There are also technology platforms that can support skilled nursing facilities with extracting and analyzing their data to make the process seamless.
The shift toward value-based care provides an opportunity to transform the experience for nursing home patients and staff. The evolution of technology now provides resources that deliver superior care to patients, while reducing costs --the goal for all providers and payers. As part of this transition, gaining deeper insights is critical for facility administrators. Having access to deeper analytics will enable administrators to make more data-informed operational and medical decisions in order to reduce the volume of transfer rates, address any needs within their current infrastructure, provide the best quality of care while operating more efficiently, and measure how these changes are impacting their organization over time.
Author: Timothy C. Peck, MD, Cofounder and CEO, Call9
Timothy Peck, MD, is the Cofounder and CEO of Call9. He previously held a faculty position at Harvard Medical School and was the Chief Resident in the Emergency Department at Beth Israel Deaconess/Harvard.
While at Beth Israel Deaconess, Peck repeatedly encountered the challenge of treating patients who would have had superior outcomes had he and his team been able to treat them earlier. After investigating this problem, Peck learned that 1) Skilled Nursing Facility (SNF) patients make up nearly 20% of ambulance transfers to the ED, and 2) the average time it takes for a SNF patient to see an Emergency Physician is over 60 minutes. Shortly after learning the scope of the problem, Peck conceived of Call9, applied to the startup incubator Y Combinator and set out to solve it via a combination of on-site care coupled with technology.
Prior to his time in Boston—where Peck also studied entrepreneurship, learning and technology at Harvard’s Graduate School of Education—Peck earned his MD from NYU.