Seismic Shift

How the COVID-19 pandemic can prepare health care systems for the next ‘big one’

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This article is part of Harvard Medical School’s continuing coverage of medicine, biomedical research, medical education and policy related to the SARS-CoV-2 pandemic and the disease COVID-19.

The COVID-19 pandemic has fundamentally disrupted U.S. health care organizations. Hospitals have faced drug and device shortages and created new intensive care units overnight. Care plans have evolved out of necessity, and hospitals’ carefully constructed patient flow systems were upended.

In a commentary published in NEJM Catalyst Innovations in Care Delivery, leaders and clinical researchers from Harvard Medical School and Beth Israel Lahey Health propose using complexity science to identify strategies that health care organizations can use to respond better to the ongoing pandemic and to anticipate future challenges to health care delivery. Complexity science is concerned with understanding dynamic, unpredictable systems, such as the human brain, economies or climates.

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“COVID-19 has been a painful reminder that health care, both as an industry and as a series of complex organizations, has evolved slowly over time, as have the metrics and models we use to assess quality, safety and accommodate future needs,” said lead author Jennifer P. Stevens, HMS assistant professor of medicine and director of the Center for Healthcare Delivery Science at Beth Israel Deaconess Medical Center.

“The principles of complexity science offer three strategies health care leaders can employ to manage operations during the COVID-19 pandemic: engaging diverse perspectives in leadership teams, staying open to new metrics and creating forecasting tools that reflect complex health care systems,” she said.

Engage diverse thinkers

Noting that individuals are often unable to see the big picture from within a complex system like health care, Stevens and colleagues recommend bringing additional, perhaps unexpected voices to leadership teams.

For example, while epidemiologists naturally guided health care leadership teams in the context of COVID-19, Stevens and colleagues suggest including patient or community representatives, physicians from disciplines that may be more tangentially related to the current crisis, or clinical and operations staff from the communities disproportionately affected by the pandemic to crisis-response teams.

“Voices from these various perspectives can expand the vantage point, allowing health care leaders see more of the complex system and implement strategies that anticipate future needs,” said Stevens.

Identify metrics

Identifying a broader range of relevant metrics can also expand leadership’s view of the complex system. For example, patient demographics were a largely unreported variable early on in the pandemic so physicians didn’t have a clear picture of how tightly race, ethnicity and other socioeconomic factors were linked to the risk of contracting and dying of COVID-19.

“Having a better understanding about the disparate impact of COVID-19 on communities of color could have helped health care leaders better anticipate the flow of patients coming into clinics, as well as the implications for clinical staff and personal protective equipment needs,” said Stevens, adding that “Health care leaders must be open to new metrics and watchful for undervalued variables, or we may find ourselves so focused on one set of metrics that we miss the significance of more meaningful data.” 

 As an example of a metric with shifting value, Stevens and colleagues described how the significance of the number of patients with COVID-19 in Beth Israel Deaconess’ ICU changed from spring to summer. In the spring, patients with COVID-19 arrived at the hospital with severe respiratory symptoms and required immediate critical care services. The rising number of patients admitted with COVID-19 meant that the hospital would need additional ICU beds and ventilators, personal protective equipment and other resources.

However, once the state of Massachusetts and the hospital deemed it safe to reinstate urgent and elective procedures, all patients were tested for COVID-19 upon admission. The universal testing yielded infected but asymptomatic patients who had come to the hospital for reasons unrelated to COVID-19.

“Suddenly, we were admitting asymptomatic patients with COVID-19 who wouldn’t require the same resources and care as the patients critically ill with the novel coronavirus,” said Stevens. “So the meaning behind the number of COVID-19 patients at BIDMC really shifted over the early months of the pandemic.”

Create forecasting tools

The team also suggests that forecasting tools must truly reflect the complex realities of the COVID-19 pandemic. To build such a model, the team used machine learning to pull relevant data from each of the 13 hospitals and three business units that make up the Beth Israel Lahey Health system. Next, they added publicly available local cell phone data to the model, revealing how much people were moving around and interacting with other people. Taken together, these data sources, reflecting both shifting local public health policies as well as the shifting social norms of behavior, contributed to a model capable of providing timely and locally relevant predictions.

“Our model leverages the principles of complexity to guide hospital leadership, providing weekly updates to a group of health care leaders about how and when a new surge of infections may arrive,” Stevens said. “Models need to reflect the shifting health and policy landscape to allow for the complexity of the pandemic itself for any health care organization to make meaningful use of them.”

“Health care is facing one of its greatest challenges, in part because our comfortably familiar metrics and dashboards, which were designed to handle the problems of a complex system, couldn’t see the ‘big one’ coming,” said Kevin Tabb, president and CEO of Beth Israel Lahey Health and HMS professor of medicine. “Adapting to new realities that COVID-19 brought to the fore requires that health care leaders build new models that reflect the true complexity we are facing, engage new voices and remain flexible and curious about our metrics. We are still squarely in the middle of this earthquake, and we have many aftershocks ahead.”

Additional authors include Ashley O’Donoghue, Steven Horng and Manu Tandon.

Stevens is supported by the Agency for Healthcare Research and Quality (grant no. K08HS024288). Horng discloses support from Philips Healthcare. The other authors report no conflicts of interest or disclosures relevant to this work.

Adapted from a Beth Israel Deaconess news release.