The healthcare industry has experienced an explosion in data volume in recent years, leaving some providers wondering how to realize the full value of this information to improve clinical, operational, and financial outcomes.
Healthcare data holds the ability to drive a transformation of healthcare, improving everything from the accuracy of diagnoses to the effectiveness of treatments, but all that data adds up. For example, approximately 30% of the world’s data volume is being generated by the healthcare industry today, according to RBC Capital Markets. By 2025, the compound annual growth rate of data for healthcare will reach 36%, which is 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media and entertainment.
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Despite all this data – or perhaps because of its overwhelming volume – health systems have struggled to harness their power to improve performance. Too often, executives look to data retrospectively to understand what has happened, rather than using data prescriptively to understand what is likely to happen and, in turn, how to best respond.
Harnessing data insights to optimize care orchestration and patient flow
As hospitals continue to contend with staff shortages, rising labor costs, and thin margins, they must reimagine patient flow and improve care orchestration, but to do so, they must be able to harness the rich data to yield significant clinical, operational, and financial benefits.
Following are four common scenarios of how care orchestration enables hospitals to capture and leverage data to generate insights that improve the “last mile” of care delivery.
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- Streamline transfer patient flow & reduce transfer times
As a result of staffing shortages and multiple layers of communication requiring numerous phone calls, hospitals often experience elongated transfer times, resulting in delays to patient care and suboptimal capacity. Overly onerous transfer acceptance processes are often to blame.
In the traditional acceptance model, a referral source calls a hospital’s transfer coordinator, who records the patient’s demographics and history. The coordinator then assigns the patient to a physician at the accepting hospital, and the physician must then conduct conversations with specialists and referring physicians before deciding whether to accept the patient. This approach is inefficient, and often leads to frustration for physicians who are required to devote significant time to phone calls.
In contrast, under a single provider acceptance (SPA) model, the referral source has a discussion with a representative of the admitting hospital’s transfer center who assigns the patient to a physician, as in the traditional approach. However, in contrast, the physician is empowered to decide regarding acceptance of the transfer, removing layers of communication and resulting in a faster process.
A third alternative, called the auto-accept model, empowers the transfer center coordinator to make the decision regarding patient acceptance, streamlining the process even further.
To evolve their acceptance processes, hospitals should analyze which service lines have high acceptance rates, making them ideal candidates for the SPA or auto-accept models. Simply start with one service line and grow the capabilities from there where appropriate based on service line acceptance rates. Potential benefits of SPA and auto-accept include fewer administrative steps, a reduction in phone calls and transfer times, increased patient volume and provider satisfaction, and service line growth.
- Transfer center performance analysis
As demand for patient care rises, hospitals sometime have difficulty achieving the capacity to accommodate that demand. When they struggle to meet demand, they may experience an increase in lost and canceled transfers as well as longer transfer cycle times.
To understand when and where lost cases are occurring, hospitals should compare three factors: accepted cases, cases that were lost and were actively being worked, and cases that were lost with no action. Armed with this data, administrators can set target response times that vary by providers and bed management teams based on service lines.
The goal is to get to “yes” as quickly and as safely as possible when accepting appropriate transfers, and ultimately increase the capture rate of transfers while also measuring performance related to times associated with transfer cycle, provider procurement, and bed procurement.
- Transfer center and service line optimization
Emerging from the pandemic, some hospitals have faced challenges in ramping up service line activities to previous levels. In other cases, hospitals have cut service lines entirely, leaving competitors to accommodate local patient demand for those services.
In either case, there is an opportunity to expand service lines to serve more patients. To evaluate service line expansion, examine lost transfer trends to identify potential areas for improvement. (Frequently, for example, transfers are lost for service lines with only part-time coverage.) Then, weigh the benefit of the increased contribution margin of that expansion with the cost of providing services.
By expanding service lines to accommodate demand, hospitals can increase patient volumes and build stronger relationships with referring providers.
- Post-acute discharge and demand planning
Often, the timing of daily discharges at hospitals is not well-planned or coordinated, resulting in surges that can cause capacity issues and may lead to excessive waitlisting and lost patients. The problem has been particularly prevalent as hospitals look to return to post-pandemic levels of activity.
Discharges often lag demand, beginning too late in the day and causing delays for patients seeking to be admitted to the hospital. It is important for hospitals to stay ahead of demand for admission to not only ensure they have beds available for new patients, but also to lessen burdens on associated service providers, such as transportation partners, enabling them to more evenly allocate work throughout the day to operate more efficiently.
To overcome this issue, hospitals can analyze their data to identify patterns of demand to help pinpoint the optimal times of day for discharges, creating the needed capacity for new patients. Additionally, it is essential to ensure all stakeholders are aware of these optimal times and are committed to removing roadblocks.
By optimizing discharge timing, hospitals can achieve a measurable increase in available beds at times of high demand, as well as a reduction in the use of waitlisting and lost transfers. With improved patient flow and care orchestration, health systems can serve more patients.
Although the amount of data floating around in the healthcare industry can be overwhelming, healthcare is full of opportunities for data-driven improvements. Through care orchestration and better management of patient flow, hospitals can ensure they deliver the right care to the right patient at the right time as well as evolve and improve healthcare operations with real-time, actionable data and insights.
Photo: FS Productions, Getty Images
Jonathan Shoemaker joined ABOUT in 2023 as Chief Executive Officer, bringing more than 25 years of health system and information systems experience with a proven track record of transforming and delivering initiatives and solutions that improve healthcare delivery, operations, and growth.
Before joining ABOUT, Jonathan most recently was senior vice president of operations and chief integration officer as well as a member of the senior executive team leading Allina Health’s Performance Transformation Office. Before his most recent role at Allina, Shoemaker spent six years as Allina Health’s chief information officer and chief improvement officer. Prior to Jonathan’s tenure at Allina, he held leadership positions at prominent IT & healthcare firms, including NorthPoint Health and Wellness Center, BORN Consulting, and Hennepin County Medical Center.
