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How Hospitals Can Manage Supply Shortages as Demand Surges


An article from Harvard Business Review
pdf How Hospitals Can Manage Supply Shortages as Demand Surges (.pdf)

An effective strategy must tackle both sides of the problem.
by Richard M. J. Bohmer, Gary P. Pisano, Raffaella Sadun, and Thomas C. Tsai
April 03, 2020

559KB

Harvard Business Review

As everyone has become painfully aware, acute shortages of materials like masks, ventilators, intensive care unit (ICU) capacity, and staff are hamstringing the heroic efforts of health care professionals around the world to address the pandemic.

Now, more than ever, the right supply-chain strategies and management practices are urgently needed to optimize scarce resources, alleviate shortages, and expand capacity quickly. While good management can never be a substitute for dedicated and skilled medical practitioners, improving the management of supply chains is crucially needed to ensure that these professionals have the resources to do their jobs.

This article, which draws from the best practices in supply chain and operations management, can help struggling hospitals and other care providers increase the odds they will have those resources. It is based on a central reality: Tackling shortages and supply constraints requires a comprehensive strategy aimed at both the demand- and supply-side roots of the problem.

Managing Demand

A pandemic generates an enormous demand shock for health care systems already running at close to full capacity. While social-distancing measures, travel restrictions, and shelter-in-place orders are effective in dampening demand, they are only part of the solution. It is still necessary to manage the way patients enter and proceed through the various nodes of the health care delivery system.

Managing flow means proactively shaping how, when, and where among these nodes patients (both infected and uninfected) receive care. During the Covid-19 outbreak, hospitals have been forced to redesign patient flow in real time, grappling with such issues as: Which care can be moved from a hospital to an alternative setting (even the home)? Which procedures for which patients can be safely postponed? What policies do we put in place to determine how long patients (those with and those without Covid-19) need to stay in the hospital or utilize an ICU?

To help alleviate system congestion, health care managers should follow two principles:

1. Be aware of systems interdependencies and unintended consequences.

Health care systems are composed of many interconnected points of care, and the demands across them are not independent. For example, demand for baby delivery rooms spurs demand for postpartum and neonatal care. System interdependencies mean that changes in one part of the system can generate unintended consequences.

For instance, a study of ICU care by Diwas Singh KC and Christian Terwiesch found that as ICUs reached full capacity utilization, physicians responded by shortening lengths of stay for patients. This “early” discharge strategy indeed worked to open capacity in the short term, but there was an unintended consequence: It increased the “bounce-back” (re-admission) rate to the ICU, thus increasing demand for the ICU (and effectively reducing peak ICU capacity). The general implication of this study is to be careful not to inadvertently make a bad capacity situation worse by diverting patients from specific points of care. Postponing broad swaths of routine care — a strategy being pursued by many hospitals today — could create similar false economies if some patients will then require more intensive care later as a result of the postponement.

The lesson here is to carefully stratify patients by the risk of postponement to manage not only their current health, but also their future demand for the scarcest health resources. In the context of the Covid-19 pandemic, for instance, we should be very careful about postponing care that increases the risks a patient will require ICU or ventilator capacity a few weeks down the road. The acute shortages of ICU capacity and ventilators due to Covid-19-relared demand is a big enough problem; we should not make it worse by making poor choices about how to treat patients who aren’t infected by Covid-19.

Taking a system perspective also means that providers should consider available resources, bottlenecks, and capabilities outside their own walls. Hospitals under stress quite naturally focus their attention on hospital resources (like beds and medical staff). But in doing so, they risk neglecting the constraints faced by providers of community and home health care whose personnel and infrastructure capacity is already stretched. Yes, diverting non-critical patients from hospital settings to home care helps free up hospital capacity for the critically ill and reduces the incidence of contagion. But this strategy needs to be complemented with the appropriate infrastructure and technology (e.g., mobile care units and telemedicine capabilities) to monitor and coordinate such care. If it isn’t, more home-bound patients may end up requiring hospitalization or intensive care later on than otherwise would be the case.

2. Forecast short-term demand.

When demand is exploding and systems are overwhelmed, it may seem futile to make the effort to forecast demand a week or two out. After all, what difference does it make if a system is overutilized by 25% or 50%? Both seem dire. But when systems are overloaded, small week-to-week differences in caseloads can have a big impact on a hospital’s utilization of its resources. Therefore, while no forecast is perfect, having some visibility into short-term future demand provides hospitals and other care sites the opportunity to plan patient flows proactively (e.g., pursue preemptive diversionary strategies).

There is now enough data from around the world on Covid-19 infection rates and their impact on care providers for local providers to make perhaps rough but sufficiently useful short-term forecasts, taking into account population density, social distancing policies, the daily testing rates that can be achieved, the time it takes to process the tests, and so on.

As we discuss below, good forecasting also becomes critical for managing supply shortages and bottlenecks.

Managing Supply Problems and Shifting Bottlenecks

Managing demand needs to be complemented with effective strategies for managing the supply of resources needed to care for patients — obviously, not an easy task when dealing with a highly contagious disease like Covid-19. But it’s crucial since not doing so can trigger vicious cycles, as we’re already seeing.

Covid-19 cases increase demand for tests and for staff. The increase in demand for tests initially results in test shortages (and thus testing backlogs). Staff need protective gear both to perform tests and to treat patients. So, not surprisingly, increases in patient flows creates shortages of masks and other protective equipment.

Shortages of both testing and protective equipment leave staff vulnerable to infection. In Italy, health care practitioners constitute 9% of all Covid-19 cases. In Spain, the figure is 14%. And there is now a significant infection rate among health care workers in the United States, according to reports in The New York Times and The Boston Globe. High rates of infection among health care workers not only make already bad staffing shortages worse, they also can increase demand if infected staff become a vector for transmission to patients who don’t have Covid-19.  The key challenge in dealing with supply shortage is to break these vicious circles.  There is no one way to do this, but applying some of the principles below should be helpful.

Engage in systematic de-bottlenecking. This means not just focusing on existing bottlenecks, but also identifying future potential bottlenecks (in other words, forecasting them) and addressing them before they materialize or become acute.

Dealing with acute shortages means identifying the root source of the shortage and focusing efforts there to expand or leverage available supply (which we discuss later). Because staff is a critical resource of almost every phase of health care delivery, protecting their health should be the number one priority. Increasing ventilator production or creating new ICU beds is helpful only to the extent that there are staff available to operate that new equipment and care for the patients.

In highly interdependent supply chains, bottlenecks will shift. For instance, if testing capacity is limited by the availability of cotton swabs, it does little good to increase the availability of testing kits or to increase laboratory capacity to process tests. Getting ahead of supply shortages requires forecasting the next bottleneck in the system, which requires excellent information about the inventory available in the entire supply chain (not just one’s own inventory), the capacity of suppliers, demand patterns, and rates of consumption.

Like demand forecasting, supply forecasting is not a precise science. But supply forecasts provide important visibility into the future state of the supply chain and enable organizations to proactively identify potential shortages in advance — when there is time to resolve the issue. In health care organizations right now, it is natural to focus on the shortage of ventilators, masks, protective gear, and swabs — those shortages must be addressed urgently. However, hospital managers should be aware that future shortages in other commodities and resources are lurking. The sooner they are identified, the better the chance to resolve them before they become acute.

Pool and coordinate resources across organizations. It is a well-known principle in supply-chain management that the amount of inventory required to meet a given level of demand decreases as the number of places holding inventory shrinks. Centralization reduces inventory requirements because of the beneficial effects of pooling uncorrelated demand from different locations (that is, while some places might be experiencing higher-than-expected demand and requiring more inventory, this would be balanced out by places experiencing lower-than-expected demand, which require less inventory). This is an area where territorial behavior concerning supplies by states, hospitals within states, or even departments within a hospital may significantly exacerbate shortages.

A critical part of pooling is not just sharing physical inventory but also sharing information about inventory: What is available, in which quantities, and where it is located? Good information cannot magically make shortages of physical materials go away, but bad information can certainly make shortages worse. Lack of information creates uncertainty, and uncertainty can lead to “just in case” hoarding.

As a first step, it is absolutely essential to break down departmental barriers and to optimize inventory within a hospital. However, during a time of crisis, hospitals should think about going one step further: pooling and managing inventory (including sharing information) within their health care system and even across health systems within the same region. This means sharing inventory across hospitals that may compete for patients in normal times. But if hospitals try to preemptively procure materials to gain an advantage over their rivals, it simply makes shortages worse.

Pooling of resources does not just apply to materials inventory. It should be used for equipment that can be easily moved from hospital to hospital. Staff could potentially be pooled across hospitals. In the Netherlands, ICU bed availability is managed nationally, and in other services, such as obstetrics, as many as 10 hospitals that are competitors in normal times now report their bed availability regionally, so that beds can be managed as a single resource and allocated through one call center.

Technically, none of this is particularly difficult. A ventilator or ICU nurse employed in Hospital X presumably would be just as effective in Hospital Y across town. The difficulty is getting hospital leadership to change their thinking. There is a time for competition and a time for cooperation. A pandemic is a really good time for cooperation.

Innovating and learning in real time. Attacking a shortage requires creative technical and organizational solutions. In response to the short supply of masks (especially N95 masks), many hospitals have been developing and producing alternative designs that may be suitable for interacting with non-Covid-19 patients. Repurposing post-anesthesia care units (PACUs) into ICUs is another example of innovation occurring in some hospitals.

Human assets can also be repurposed. In the United Kingdom, for instance, generalist nurses are being trained to manage a ventilator under the supervision of a specialist critical care nurse, thus effectively increasing the number of ventilated patients each specialist nurse can care for.

Some of the challenges of repurposing are more institutional or organizational than technical. For instance, most countries or professional societies require certification for health care specialists to perform certain tasks. Relaxing these requirements can help alleviate staff shortages.

Any kind of innovation involves risks. Are the makeshift masks really safe? Are repurposed PACUs really as effective as regular ICUs? Is the quality of care harmed by having generalist nurses operate ventilators under the supervision of specialists? Under intense pressure, hospitals simply do not have time to wait for definitive answers to these questions or to follow the traditional approach to implementing new practices (e.g., long clinical trials). What is needed is data — collected, analyzed, and shared in real time — to provide insights about what is working, what is safe, and what is not.

Hospitals and providers need to experiment with new approaches, but they also need to share information candidly so that others can learn and that everyone can make the right mid-course corrections. Good information and fast feedback loops can accelerate the learning needed to identify, implement, and diffuse innovative approaches.

Focus on Information, Fast Decision-Making, and Learning

The Covid-19 crisis is testing the both the medical and managerial competencies of health care systems throughout the world. Dealing with the operational strains created by this crisis requires coherent, comprehensive, systematic efforts that span both demand and supply forces.  To implement these efforts, health care managers need to focus on information, fast decision-making, and learning.

Information is everything. Every practice we’ve recommended above hinges on having high-quality and high-velocity information. You cannot forecast patient flows without excellent information on things like how many tests have been conducted, how many people are infected, where are they, where have they been, with whom have they been in contact, and so forth. You cannot predict the consequence of new approaches to patient flow without good information about current demand and supply in different parts of the system. You cannot predict the next bottleneck without information on future demand, usage rates, and current stock levels. Testing capacity and turnaround matters not only for the clinical reasons, but because it provides information needed to proactively make and adapt operating plans.

Fast decision-making. Covid-19 attacks at a pace determined by nature, not by government regulations, bureaucratic rhythms, political machinations, management systems, or institutional rules. Having high quality and timely information does little good if managers running health care systems are unwilling and unable to respond quickly to that information.

The challenge facing health care managers is balancing the value of centralized coordination and information-sharing with the need for flexibility and responsiveness by clinicians and nursing staff working on the front lines. Hierarchical structures, which tend to be slow under the best of times, are totally inadequate during a fast-moving crisis. Good leadership in a crisis focuses on providing those on the front lines the resources and decision rights they need to solve problems quickly and learn.

Focus on learning. Almost by definition, a crisis brings an organization into uncharted territory. The existing playbooks have to be rewritten on the fly and under enormous strain.  Everything we discussed above requires grappling with questions for which answers are not fully know or for which the answers are changing by the day. Waiting for perfect information is not an option.

Under these situations, execution is a series of experiments and failures. Failures (or “mistakes”) are an inevitable consequence of doing something new, not a sign of incompetence. Learning from experiments, including what hasn’t worked, is critical, but that can only happen if the leadership of the organization creates a psychologically safe and transparent environment. The health care organizations that will battle best against Covid-19 are not necessarily the ones with the right answers, but those that can learn fastest.

Richard M.J. Bohmer
Richard M.J. Bohmer is a physician and a senior visiting fellow at the Nuffield Trust in London and advises health care organizations around the world. He previously was a professor of management practice at Harvard Business School. He is the author of Designing Care: Aligning the Nature and Management of Health Care.

Gary P. Pisano
Gary P. Pisano is the Harry E. Figgie Jr. Professor of Business Administration and the senior associate dean of faculty development at Harvard Business School. He is the author of Creative Construction: The DNA of Sustained Innovation.

Raffaella Sadun
Raffaella Sadun is a professor of business administration at Harvard Business School. Her research focuses on the economics of productivity, management and organizational change in the private and public sectors. She is a faculty research fellow at the National Bureau of Economic Research and a research associate in the Ariadne Labs Program at Harvard T.H. Chan School of Public Health.

Thomas C. Tsai, MD
Thomas C. Tsai, MD, is an assistant professor in the Department of Health Policy and Management at the Harvard T.H. Chan School of Public Health and a member of the faculties of the Department of Surgery at Brigham and Women’s Hospital and Harvard Medical School.

This article originally appeared on HBR.org and is being brought to you by Medtronic.

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