- Michael J. Alkire, President and CEO, Premier Inc.
- David A. Hargraves, Senior Vice President of Supply Chain, Premier Inc.
- Soumi Saha, Vice President of Advocacy, Premier Inc
Our response to the COVID-19 pandemic left no doubt that U.S. health care heroes provide world-class care. But the job was much harder than it needed to be. Each day, there were new stories about product shortages (for example, personal protective equipment) and other supply chain challenges that compromised or created obstacles to our national response.
In this post, we reflect on supply chain lessons learned from the pandemic and outline key capabilities required to build an interconnected digital supply network for greater resiliency, risk management, and preparedness.
A Supply Chain Guessing Game
During the pandemic, one major barrier to an effective response was that no one had downstream visibility into the exact quantities of critical medical supplies and drugs on US soil at any given time. Parts of the nation had a surplus of products while other communities were operating in crisis mode, leveraging household products such as garbage bags to protect frontline workers.
Alongside this lack of understanding on product availability risks, the US saw wave after wave of supply chain challenges including a rampant gray market, panic buying, and hoarding that created shortages for others. At the same time, government leaders had difficulty understanding where COVID-19 disease was spreading, what supplies and therapeutics were available, and how long it would take to replenish stockpiles.
Because of this knowledge gap, a proactive response to conserve existing supplies, secure safety stock, or ramp up manufacturing in other locations was not possible. Our nation’s limited information on the location, production process, and inventory status for medical products and drugs amounted to a guessing game to find products in the supply chain and earmark them based on patient need.
To better understand product availability and risks, the federal government stood up a health information collection process to determine these factors across the supply chain. Unfortunately, this process involved asking hospitals to manually report on-hand inventory via Excel files. This antiquated approach created substantial additional work for health care providers already stressed during the COVID-19 public health emergency. Worse still, it proved to be of little use, as inconsistent data nomenclature meant hospitals were reporting “boxes” and “units” differently from one another. In some cases, hospitals opted to cease reporting inventory levels due to both administrative burden and fear that available products would be confiscated by the government.
COVID-19 was a wakeup call that real change is necessary across the supply chain information technology (IT) ecosystem—beginning with access to robust and timely data.
A Data Infrastructure For The 21st Century
A vital component to end-to-end supply chain visibility is an on-call data infrastructure that the nation can summon at any point in time to manage a large-scale emergency.
Rather than standing up another inadequate and duplicative process, as experienced during the pandemic, the nation needs a system that can comprehensively track critical product availability—from the raw materials, to manufacturer, to distribution, to state and national stockpiles, to hospital inventory.
This will enable accurate inventory management, dynamic allocation—the delivery of existing products to areas in greatest need—and a data-driven approach to ramping up supply via mechanisms such as the Defense Production Act. Not only will this help providers anticipate demand for key products, but it will also allow the nation to better manage supplies during a crisis.
For greatest effectiveness, this interconnected data network requires three key capabilities.
1. Public-Private Coordination
All supply chain stakeholders—including the federal government, group purchasing organizations, distributors, and manufacturers—must work together to promote harmonization and interoperability within a national supply chain data infrastructure.
This includes creating a standardized data nomenclature to reduce misinterpretation and ambiguity, as well as the acquisition of data across the Strategic National Stockpile (SNS), manufacturers, distributors, and within health care systems, all tied to real-time demand. The Department of Health and Human Services (HHS) began this work in March 2020 with the pilot launch of the since-stood-down “Supply Chain Control Tower,” a data initiative to monitor the availability and supply of critical medical products in conjunction with the SNS and Federal Emergency Management Agency. HHS should build on this progress and leverage existing supply chain data and technology capabilities to develop and deploy an electronic, ready-to-go system.
For example, early in the pandemic, Premier, Inc., created a near real-time technology system to gain visibility into hospital inventory, including stockpiles, providing visibility to the SKU level. Overlaying clinical and supply chain data can help entities in both the public and private sectors see where products, such as N95 masks and gloves, are stocked as well as gaps in resources. This progressive monitoring approach needs to extend across the supply chain, providing advanced alerts of demand signaling and inventory levels, and enabling rapid movement of product to points of care.
To accomplish this, policy changes are needed to provide data rights to create predictive algorithms and to acquire and use data for surveillance. Congress should enact legislation to provide specific criteria, supportive funding, and incentives to encourage reporting, such as requiring reporting as a condition of eligibility for receiving supplies from the SNS during times of crisis.
2. Automated Collection Techniques
Building an on-call IT infrastructure requires an automated data collection and reporting approach—one consistent with the internal operations and processes of reporting organizations to help alleviate provider burden and improve efficiency.
Automating data collection and reporting will help address data reliability, quality, and consistency issues—improving trust in the data. This process and system would exist behind the scenes, ready to be “turned on” in a moment’s notice and could be pressure-tested annually to ensure it remains in place and operational. Automating and expanding the scope of data collected will enable HHS to understand stress signals and predict usage, demand, and burn rates at a localized level—and to leverage inventory data to inform and justify dynamic allocation strategies.
For ease of collection and appropriate granularity, HHS should start with a focus on detailed information that can be captured via clinical surveillance and enterprise resource planning systems. The system would live under HHS, but partnerships with private-sector organizations to leverage existing technology and automation capabilities will enable a more seamless process.
Future efforts may focus on artificial intelligence technology such as machine learning that uses algorithms to break down data, learn from it, and then make a determination or prediction.
Syndromic surveillance powered by machine learning is increasingly being used to solve a variety of health care industry problems, including accurate predictions of disease surge to better manage public health and the associated need for supplies and resources.
3. Strong Feedback Mechanisms
The movement toward value-based care and alternative payment models has created an even greater imperative for health information exchange and interoperability. Aggregating insights and trends from national, regional, and local data will enable providers to:
- Monitor treatment responses and inform mitigation strategies
- Determine institution and local community spread and impact
- Leverage predictive modeling to make actionable forecasts
- Forecast surges, disease rates, and subsequent clinical and supply/logistics needs
The lack of access to complete and timely data across the supply chain and care continuum adds inefficiencies and costs to the health care system—and hampers population health efforts, public health surveillance, and reporting. Public reporting data can dramatically improve facilities’ patient management, provision of quality of care, and the elimination of waste.
Equally vital is that we leave no provider behind within this data infrastructure, particularly those in rural and remote communities who may lack the existing capabilities needed for accurate data reporting and management. Improving technology access for small, rural, independent, and critical access hospitals—and meaningfully engaging them as part of the process—will help ensure both equitable distribution of products as well as improved outcomes for patients in these communities.
If there’s one thing COVID-19 laid bare, it’s the antiquated nature of our public health data systems and technologies. While much of our lives can be orchestrated with a simple click, the health care industry still largely relies on inefficient, manual processes where very little is wired—let alone technology enabled.
In the 1950s, President Dwight D. Eisenhower began the transformative work of building the highway system to connect the country; for the same reason, today we must develop our health care supply chain IT ecosystem. This is imperative—not only to help limit risk and ensure greater resiliency for the next pandemic—but also to drive cost, quality, and outcome transformation for the health care industry of the future.
This article ran in the Health Affairs Blog on September 30, 2020.