Caring for patients in skilled nursing facilities is one of the most challenging and noble callings in medicine. Unfortunately nursing home operators and administrators face several challenges today, including a rising population combined with staffing shortages and tight margins under which to operate.

One of the most significant challenges they face is that 19% of all transports to the Emergency Department (ED) come from nursing homes. Nursing home staff tends to be well trained in chronic care given the patient population they’re usually caring for; thus, patients who experience acute changes of condition are often transferred to the ED. Because of the multitude of comorbidities this patient population often lives with, once they are transferred to the ED they are almost invariably admitted to the hospital where the cost to the healthcare system skyrockets – averaging over $15,000 per patient for every patient transferred. Patients suffering from conditions as simple as a urinary tract infection often spend multiple days in a hospital. Not only is the patient removed from their home, which can be isolating and uncomfortable, but this costs the healthcare system tens of thousands of dollars.

Many of these patients could actually be treated in the comfort of their beds, if our healthcare system provided nursing facilities the tools and incentives to do so. Yet, the current economics of nursing home care often prevents the expansion of facility staff, and the payer reimbursement model typically limits the options available to nursing home operators. However, by gaining more visibility into facility operations, operators and administrators can make changes within the organization that can help improve care, reduce ED transports and costs, and ultimately drive further revenue to the home where it can be used for even more meaningful improvement for patients.

The Importance of Data & Visibility

The first step to reducing avoidable transfers is obtaining greater visibility via big data. Having access to data and analytics on day-to-day operations can empower operators with information on when and why transports are taking place, which they can then leverage in order to reduce them.

For example, by examining operational data, facilities can glean the following types of insights:

  • Transfer Rates: Identify the volume of patient transports to the hospital versus how many were avoidable. From there, drill down on contributing factors that increase transfer rates so they can be addressed.
  • Contributing Factors: Many factors contribute to a patient being transferred to the ED. Data points could include:
    • Identify which patients are being transferred most often, and thus who is at the highest risk for future transfers. In essence, this enables operators to predict emergencies before they even happen, and address them by creating more tailored care plans, engaging families early and often, and frequent vital sign monitoring for those patients.
    • Identify whether patients are consistently being transferred at a significantly higher volume during certain staff shifts. If so, a next step may be to understand why those staff members are transferring so often, and if they could use additional training or support; need to be moved to a different unit (for example, RNs placed on high acuity units and LPNs placed on other floors); or if a different hire needs to be made to meet the needs of the facility.
    • Identify if patients are being transferred more often during certain days of the week, and if so, whether an adjustment in staff allocation may be needed; for example, if transfers happen more often on weekends, a next step may be to add or shift staff to the weekend in order to reduce transfers.
  • Financial Impact: Analyze the cost of transfers and hospitalizations over time. Reviewing data such as the cost of lost patient days and revenue for each avoidable transfer – month over month and quarter over quarter – as the facility is making changes is helpful to see how these decisions impact the organization financially.

Much, if not all of this data is available by combining information from a facility’s electronic health records with a broader understanding of nursing home patient trends both locally and nationally. It’s a matter of coupling that data, teasing out the relevant information and analyzing it in a useful way. There are technology platforms that can support skilled nursing facilities with data extraction and analysis to make the task quick and seamless.

Once armed with the knowledge around why patients are being transferred and which transfers are avoidable, another option is to leverage a telehealth platform that can support the facility with treating patients at home in their beds. Technology, leveraged by the facility’s care staff, can help address staffing shortages, facilitate quality care and reduce transports.

As we move toward value-based care, there is an opportunity to transform the experience for both patients and the staff caring for them in the nursing home. With deeper insights, nursing home operators and administrators can make more data-informed operational and medical decisions – ultimately enabling them to provide the best possible care while operating more efficiently.

Timothy C. Peck, M.D.,  is the co-founder 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.