Due to healthcare reform, an aging population and a higher incidence of chronic disease, the demand for healthcare services continues to spiral upward. At the same time, pressure from payers to reduce costs by eliminating waste requires that providers do more with less to meet more of the demand with the available resources — especially expensive, constrained resources like operating rooms, infusion centers, pharmacies, and diagnostic imaging— in which they have already invested.
The easy way out — investing billions of dollars to expand facilities, extend operating hours and add staff — seems out of reach for most healthcare providers and looks more like a bandage than a cure. In the past few years, we have worked with a number of large healthcare organizations to address this problem. Drawing upon our decades-long experience helping Fortune 500 companies make operational improvements, and by employing lean principles and predictive analytics, we set out to find the root cause of this operational paradox: Vital resources are often both overbooked and underutilized on the same day.
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Here are five practical approaches to improving patient access, decrease wait times and reduce healthcare delivery costs without embarking on multi-year, budget-stretching mega projects.
Increase velocity
A hospital visit can be divided into value-added time — the time the patient spends receiving treatment or undergoing a surgical procedure — and non-value-added time spent waiting for something to happen. In general, 70-80 percent of a patient’s time in the hospital is spent waiting. To improve patient satisfaction, focus your efforts on decreasing wait times. There are added benefits to such streamlining; the provider can treat more patients in the same time without sacrificing quality or safety.
Shape the demand curve
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The first step to changing the demand curve is to understand that it is not something that just “is” but rather something that can be shaped and optimized to great effect. Every asset in a hospital (labs, pharmacy, operating rooms, infusion center, diagnostic imaging center, etc.) has a pronounced peak period (“rush hour”) and long periods of underutilization on the same day, leading to a triangular utilization profile. Establishing a 75 percent utilization target is useless if it is achieved by a 50 percent utilization level for half the day and a 100 percent gridlock for the other half of the day. The optimal approach is to use data to continuously monitor capacity, forecast volume and then use those insights to nudge the day’s appointments forward or backward by a small amount (15-20 minutes) to flatten the midday peak. By flattening the demand curve, a provider can greatly reduce the gridlock they experience every day and open up more opportunities for more patients to receive care while leveling the workload for nurses and staff.
Start small
Former U.S. Army General Creighton Williams Abrams Jr. famously said, “When eating an elephant, take one bite at a time.” Complex, interconnected systems such as supply chains and network routers are best optimized by ensuring that the nodes are performing at capacity before focusing on the velocity of the edges that connect the nodes. Hence, optimizing the demand-supply balance for individual departments on a near-continuous basis in 15-minute chunks throughout the day is the correct first step. Only then does it make sense to improve the interconnectedness, which can be represented as visiting several nodes by traveling across the various edges in a specific sequence. Unfortunately, many health systems attempt to “coordinate” their way out of the problem by assigning navigators to help patients complete each step of the journey. As with expediting (if you expedite everything, the result is that nothing will get expedited), health systems discover that the navigators work harder and harder against the impossible task of consistently delivering an on-time experience spanning multiple nodes for a growing number of patients each day. To ensure the success of the whole network of hospital operations, the capacity and performance of each individual resource must first be optimized to deliver a consistent, on-time experience for patients despite a high level of variability inherent in the system.
Unfortunately, many health systems attempt to “coordinate” their way out of the problem by assigning navigators to help patients complete each step of the journey. But if you expedite everything, the result is that nothing will get expedited. Health systems discover that the navigators work harder and harder against the impossible task of consistently delivering an on-time experience spanning multiple nodes for a growing number of patients each day. To ensure the success of the whole network of hospital operations, the capacity and performance of each individual resource must first be optimized to deliver a consistent, on-time experience for patients despite a high level of variability inherent in the system.
Invest in data science
Data science has the power to significantly improve operational excellence through predictive analytics and machine learning. If hospitals are able to predict how a certain day will look — or even a certain week or month — based on data provided by their electronic health record (EHR) systems, then they will be able to plan better, schedule better and provide a superior patient experience. There are dozens of unforeseen events that cause delays at every stage of care. Eventually, all of these factors manifest in one of two ways: patient punctuality and whether the actual duration of a visit was shorter or longer than expected. Advanced simulation algorithms can help ensure that the appointment schedule is resilient to such “shocks,” therefore offering confidence to the health system or pointing to specific areas needing additional staff or equipment. Applying lean principles and predictive analytics can ensure resource utilization is increased, capacity is optimized but not taxed, and patient flow is smoother throughout the day.
Co-exist with EHRs
With the passage of the HITECH Act in 2009, all public and private healthcare providers were required to begin using EHRs, sometimes also referred to as electronic medical records (EMRs). By any name, such data collection, storage, and retrieval systems are here to stay; in fact, Centers for Medicare and Medicaid Services have offered $18 billion in incentives for EMR rollouts. While some healthcare professionals have decried the mandate, arguing that time spent entering data into the EHR system adds to the patient’s non-value-added time, the opportunity to use that data to shape the demand curve far outweighs this perceived burden. Some EHRs offer predictive analytics ability but lack the speed and agility needed to keep pace with hospital operations. For this reason, the biggest gains will come from extracting data, optimizing it outside of the EHR and then applying that knowledge to build optimized schedules that benefit the hospital (by allowing more patients to be seen), the staff (by reducing chaos and overtime) and patients (by smoothly guiding them through their treatment journey).
By employing software capabilities that marry lean principles with sophisticated predictive analytics, over 40 healthcare organizations — such as Stanford Health Care, UCHealth, University of California San Francisco, Wake Forest Baptist, New York-Presbyterian and others — have increased patient access by as much as 20 percent, decreased wait times by as much as 55 percent and reduced healthcare delivery costs by eliminating 50 percent of overtime hours.
If they focus on reducing the non-value-added time patients spend seeking treatment, flattening the resource demand curve, starting with smaller projects for quick wins, harnessing the power of data science, and fully leveraging their EHR systems, healthcare providers can transform chaos into order to benefit both patients and themselves without spending billions of dollars unnecessarily.
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