To meet current challenges, hospitals and health systems are increasingly exploring innovative, and potentially transformative, approaches that involve making unprecedented real-time use of data and redefining traditional relationships.
Healthcare organizations have pursued innovative strategies to improve the health of their populations, deliver high-quality care, and ensure financial sustainability in recent years. For most, this effort has involved expanding beyond acute care to offer a continuum of services and growing into new communities, regions, and states to gain both efficiencies and market presence.
Although undertaken in pursuit of laudable goals—to better manage population health, quality, and resource utilization and engage in risk-sharing, for example—these efforts also have too often resulted in an accumulation of businesses rather than an integrated delivery system. Thus, many health systems today operate as holding companies rather than unified systems.
This outcome is understandable, given the significant challenges involved with integrating disparate, autonomous entities into a system that operates consistently across all aspects of care, from patient safety and clinical standards to talent management and the patient experience.
Acutely aware of the gap between their goals and this reality, health leaders are investing in digital health, unified strategic and operating plans, and innovative governance models. In addition to focusing on those measures, finance leaders and their teams should consider investing intellectual capital immediately in two areas they may find surprising where they can further their organizations’ strategic goals.
Data Analytics for Real-Time and Predictive Application
Tertiary and quaternary hospitals must invest deeply in productivity to survive the next two to five years. Although the conventional wisdom is that inpatient volumes are declining, occupancy at these hub hospitals has in fact steadily increased as community hospitals have invested in lower acuity services and pushed their complex patients “downtown.” This dynamic, combined with a graying population, is pushing occupancy to record levels, with a new normal of greater than 90 percent occupancy emerging for many, according to GE Healthcare data. Under such conditions, it becomes increasingly difficult to deliver safe, high-quality care and a positive patient experience.
Legacy investments in electronic health record (EHR) technology, IT systems, and human capital, while useful for many things, are not well-suited to this challenge. EHRs are used to manage data on a patient-by-patient basis, and collective IT systems create islands of disconnected data. Meanwhile, the workforce is left to figure it all out. Facing massive operational pressure to improve performance, hospitals require actionable information that these disconnected data cannot give them—a reliable way to spot and resolve bottlenecks, delays, and missed handoffs as they occur.
Many health systems are attempting to resolve this problem by investing in patient “navigators” or care managers to assist patients in navigating the operational hurdles they are likely to encounter. Often, however, this approach simply layers on an additional cost while only putting a band-aid on the true systemic issues.
One viable solution is to invest in new approaches for real-time, ongoing optimization of facility operations. Until recently, hospital leaders had little choice but to assess operational effectiveness in hindsight, based on monthly or quarterly metrics such as average length of stay (ALOS), emergency department (ED) wait times, and ambulance diversions. Executives had access to plenty of data, but the data were mostly historical—useful for spotting problem areas and formulating potential solutions, but useless for preventing a specific patient on a particular day from having to wait four hours for a bed.
In contrast, advances in software and analytics now enable decision making in response to situations as they occur. By monitoring a continuous stream of data from relevant sources across the organization—such as beds, operating room (OR) and ED information systems (ORIS and EDIS), orders, admission-discharge-transfer (ADT), transport, code events, and even machine data—and applying analytics in real time, organizations can help staff manage patient care activity on a minute-by-minute basis, setting priorities, synchronizing care efforts, and mitigating risk.
This thinking has informed the development of hospital command centers—healthcare “traffic control” systems that follow the lead of aerospace and aviation industries in their quest to ensure consistency of mission-critical operations. Hospital command centers combine systems engineering, predictive analytics, and problemsolving to manage patient flow in and through the hospital and other operations. The purpose of these centers is to enable staff, in the moment, to optimize utilization of limited resources and coordinate care while preserving clinical quality, safety, and the patient experience. The targeted intelligence provided by a hospital command center seeks to solve many of the issues that keep healthcare leaders up at night—readmissions, ALOS, patient risk, protocol compliance, and long wait times, for instance.
Notably, the information in a hospital command center is not a new IT system. Instead, it represents a new ability to “listen” for risk that’s already being captured in multiple IT systems. As such, it provides a means for an organization to make the best possible use, in real time, of its existing digital information and IT systems.
At one command center, the system receives about 500 messages per minute from 14 different IT systems or modules generating real-time data. The information, which is refreshed every 30 seconds, provides a continuous “read-out” of everything from bed availability and OR efficiency to patient status and staffing. In the event of major accident, for example, the system would alert center personnel to a sudden influx of patients and the likely services needed, enabling immediate action on staffing adjustments and bed assignments to prevent bottlenecks and long wait times.
Here is another, more-specific scenario that illustrates how a command center functions: Imagine that a hospital is full. An ED patient needs an ICU bed, and there are 10 pending discharges. Command-center analytics spot that one of those discharges would open the bed type needed for a patient to step down from an ICU bed to a floor bed. In response to the analytic, command-center staff notify care management and home health teams of the pressing need for an open floor bed, the discharge is expedited, and it becomes possible to quickly transfer the ICU patient, thereby opening up an ICU bed to deliver the much-needed care to the ED patient.
From a forecasting standpoint, the system’s predictive analytics enable the command center to forecast future demand for patient beds on every floor two days in advance. And center staff can see the specific expected number of patients being admitted and discharged on a daily basis looking three days ahead.
Healthcare leaders who are contemplating the creation of a hospital command center must address two key considerations:
- Updating their organization’s data governance and analytic framework to ensure data are converted to information to drive clinical and operational decisions
- Investigating the specific tools required to equip a command center, so it can empower care team members with the predictive information they need to optimize resource utilization within facilities and across the system
The good news is that most hospitals already have made the foundational investments in healthcare IT technology required for a command center to work. Command-center analytics create information by applying logic to data that are being entered into existing source systems, such as EHRs and bed management systems, every second of every day.
The important thing is to design each facet of the command center based on the specific problems it is meant to address. For example, it is necessary to determine which critical functions the command center is intended to enhance—whether it is patient scheduling, staff scheduling, risk surveillance, or operations management, for example. It also is necessary to determine which data should be shared on the center’s “big board” to create situational awareness and drive action, and what actions staff should take in response to alerts, among other considerations.
It is in this stage where the investment of time and planning is most needed. The key for senior finance leaders is to educate themselves on command-center implementation so they can evaluate requests for capital and help guide strategies for next-level performance. They also should ensure that all senior-level stakeholders have a shared understanding of the command center and, as with any new trend, be certain to evaluate potential vendor partners on their results rather than their intentions.
The Value of Super-Partners
Major healthcare technology companies and major health systems need one another. These relationships create a safe space within which to develop and nurture innovation. The health system provides a “lab” and intellectual property. The company provides technology, consulting, and product development muscle. What’s new is that health systems are beginning to focus on pursuing a few limited super partnerships, in which vendor and provider align around outcomes and seek innovation together.
Such deep relationships are necessary to foster the innovation required to overcome health care’s challenges around managing complex caseloads, reducing risk, improving outcomes, and ensuring positive patient experiences. There is no such thing as “drive-by” innovation: It requires intimacy, trust, and massive amounts of work. The two organizations must invest energy together over time—not just in a few meetings—to develop ventures that will have a meaningful impact on performance.
There are many advantages for health systems to engage in super-partnerships, including access to cutting-edge innovation early in the process, the ability to influence vendor investments and shape its developmental road map, and the potential to participate in royalties or downstream benefits of co-invention.
The largest potential pitfall for a super-partner relationship is unrealistic expectations. While super partners are eager to come together to innovate, the work required is not easy to accomplish. It takes real commitment and a sustained effort from both sides. Although it is possible to become more efficient, improve outcomes, and achieve other desirable goals, successful execution requires engagement from many staff members across the hospital organization.
This challenge is somewhat mitigated by the nature of the super-partner model, where both parties have decided to focus on a few special partners, rather than spreading and diluting their efforts across many initiatives. This selective, focused approach makes it easier to mobilize the resources necessary to deliver the desired impact, because staff members are more likely to recognize and respond to such a significant and far-reaching commitment.
Senior finance leaders who understand the potential of super-partnerships are in a strong position to help guide the organization in seeking the right partner and crafting a mutually beneficial relationship. Organizations that get on this pathway early will gain the advantage of experience in shaping these relationships to address the growing complexities of managing integrated health systems. The key is to enter well-designed relationships with only a few well-chosen super-partners, vetted for their capability of driving innovation and transformation in line with the organization’s vision.
The following steps can help health systems lay the groundwork for such relationships:
- Conduct a portfolio analysis of all business units and service lines to identify those critical to accomplishing the organization’s strategic and financial goals.
- Shed assets or services that may no longer fit with the organization’s future focus, while prioritizing resource allocation to those that are crucial for success.
- Identify areas where unique capabilities are required to succeed or where the organization needs greater depth.
- Reevaluate existing vendor relationships to identify “enabling” organizations willing to align with the organization’s desired outcomes and share risk and rewards for accomplishing its goals.
From Affiliated to Integrated to Successful
Hospital and health system consolidation is transforming the nation’s care delivery landscape. Healthcare organizations are coming together for many reasons, including the following:
- To create seamless care continuums that attract and retain consumers across the life cycle
- To gain clinical and operational efficiencies through economies of scale
- To improve population health management for the benefit of patients, payers, and providers
- To drive sustainability through broader geographic coverage
How an organization chooses to invest time and capital in the coming months and years will be critical to achieving those outcomes.
Clearly, real-time data analytics offer considerable potential as a tool to drive systemwide cohesion and functionality, while delivering direct benefits in care delivery quality, access, and efficiency. Data and predictive analytics also can help organizations gain visibility into capacity utilization so they can reduce the “waste” of unused capacity.
Finally, establishing alliances with interested super-partners that are capable of entering into risk-sharing relationships at a strategic level can provide a strong basis for pursuing innovative approaches that enable better care delivery moving forward.
Laurent Dubois, MSAE, is CEO, GE Healthcare Partners, Chicago.
Jeff Terry, MBA, FACHE, is managing principal, GE Healthcare Partners, Chicago.
Laura P. Jacobs, MPH, is president, GE Healthcare Camden Group, Los Angeles.