By Sanjeev Agrawal, president, LeanTaaS.
There is tremendous pressure on health systems to serve more patients, particularly as the need for services rises and insurance disbursements decrease. Adding new facilities to accommodate demand is often not a feasible option due to budgetary/capital constraints nor is adding more doctors with nowhere to put them. As a result, healthcare leaders consistently ask whether they are getting all that they can out of existing resources.
Operating rooms are a prime example. They serve as the economic backbone for health systems, and organizations need to maximize the use of OR capacity if they want to achieve their fiscal and patient access goals. Yet effectively managing OR blocks and scheduling in the face of volatile weekly demand patterns can feel like trying to squeeze blood from a stone.
If a significant portion of OR time has been reserved as dedicated blocks for surgeons or service lines, unless time not needed is released efficiently, ORs end up both not being used during business hours and yet working late into the night. Patients wait longer than necessary for scheduling procedures and organizations lose revenue.
Additionally, poor OR utilization makes it extremely difficult to accommodate the new surgeons that health systems want to attract. Current providers have a lock on ORs far in advance, regardless of whether they may need the time or not and/or later release these blocks. Such practices leave few opportunities for new surgeons to secure time when needed.
To remedy the situation, health systems are turning to data to look for insights into what can be done to improve OR utilization. After all, small changes in utilization translate to big differences in patient access, revenue and profitability.
The Role of EHRs
As data insights move to the forefront in organizational decision-making, there is some confusion about what EHR systems do and the role that they play. In a nutshell, EHRs tell you what’s already happened. They are vital systems, absolutely necessary for describing problems within organizations and supplying the data to back up assessments.
Breaking this down further, the purpose of implementing an EHR is threefold:
- Reservation system: EHRs provide health systems a way to reserve resources, whether it be rooms, infusion chairs, or clinic time. EHRs do this as well as enable scheduling of specific equipment or providers.
- Single source of truth for patient encounters: Organizations need a way to maintain records for every patient encounter — a single instance for each enterprise deployment — and EHRs provide this.
- Descriptive reporting: Health systems require reporting. EHRs generate reports based on what was done, sort of like how Charles Schwab tells you how your portfolio performed.
While these functions are all essential to running a successful health system, there are several things EHRs are NOT designed to do no matter how much teams may wish they could. For example:
- EHRs don’t try to optimize anything. They just report what has already happened. If an organization is considering collectible time — and wants to know which provider is not going to use their time well — it requires something more sophisticated. Given this, EHRs can’t allocate an appropriate amount of operating time by surgeon or optimize staffing levels based on OR nurse preferences.
- Not predictive: Similarly, EHRs can’t predict the volume and mix factoring into case-mixes, seasonality and/or other features. They can’t predict who isn’t going to use their block well in an attempt to get them to release it.
- Not proactive or prescriptive. They are not designed to spot potentially underutilized blocks — instead people have to analyze the data themselves, reactively, in order to make it worthwhile.
- Unavailable on the go: Currently, EHRs do not offer compelling mobile solutions that enable schedulers to send out messages or reminders to ask “Dr. Jones, are you going to use the OR block you have reserved? If not, will you please release it?”
- Lack a learning mechanism: And thinking back to an EHR’s reporting capabilities, while it can let you know how you did, it will not teach you why or how to do better. Continuing the Charles Schwab comparison from above, Schwab might offer me a powerful platform for trading, but it doesn’t teach me how to trade because it’s just not meant for that.
So, while EHRs are excellent at specific functions, they can’t do it all. To make EHRs more valuable, many health systems are layering in predictive analytics solutions as well.
Predictive Analytics Offer Next-Level Insights
Predictive analytics can take data generated by the EHR system and use it to let you know what will likely happen and how you can take actions to improve results. Predictive analytics solutions offset the things EHRs don’t do to create a comprehensive system. The technologies — EHR platforms and predictive analytics — work together to inform decisions that are highly surgeon-centric, and the predictive analytics layer specifically helps organizations do more with less through vastly improved OR access, transparency, visibility and fairer block utilization.
Predictive analytics offer a powerful, granular look at data to allow health systems to streamline operations and maximize efficiencies in really novel ways. But the best way to understand how predictive analytics can influence OR management and utilization is to think about what they offer from a practical standpoint.
An Example of the Power of Living in a Predictive World
Imagine a world in which any clinic can find any OR across any of its locations for a specific time with the resources available to do the case required. Surgeons could request any available time and submit any special requests (such as a robotics room). They could also establish a wish list for dates, times or rooms that they’d like, even if not currently available. Surgeons could also release times with a click of a button on a mobile app.
This may sound like a fantasy, but some predictive analytics solutions make all of these capabilities and more possible today. These products move OR scheduling away from an arduous, more manual process to something akin to OpenTable, where open time appears — and they are based on highly personalized data. With systems like this, surgeons and schedulers can see and select the times that work best. There is full visibility into what is happening currently, which gives teams the ability to manage their own destiny through a more streamlined process.
Requests for rooms go into a portal, for example, which can be approved or denied based not only on data but also any extraneous factors that a human scheduler might need to consider. The effect is that health systems never lose time on the margin, and surgeons can find time when they need it. Additionally, these systems help new surgeons find open slots and build business.
Simply put, predictive analytics help health systems get the most out of all of their existing resources and investments, including their EHR systems. By leveraging data in novel ways, organizations and providers can thrive, while increasing patient access and offering better options. Predictive analytics take health systems into the future so that they can offer unparalleled care with precision.