A hybrid Shewhart chart for visualizing and learning from epidemic data.

OBJECTIVE: As the globe endures the coronavirus disease 2019 (COVID-19) pandemic, we developed a hybrid Shewhart chart to visualize and learn from day-to-day variation in a variety of epidemic measures over time. CONTEXT: Countries and localities have reported daily data representing the progression of COVID-19 conditions and measures, with trajectories mapping along the classic epidemiological curve. Settings have experienced different patterns over time within the epidemic: pre-exponential growth, exponential growth, plateau or descent and/ or low counts after descent. Decision-makers need a reliable method for rapidly detecting transitions in epidemic measures, informing curtailment strategies and learning from actions taken. METHODS: We designed a hybrid Shewhart chart describing four 'epochs' ((i) pre-exponential growth, (ii) exponential growth, (iii) plateau or descent and (iv) stability after descent) of the COVID-19 epidemic that emerged by incorporating a C-chart and I-chart with a log-regression slope. We developed and tested the hybrid chart using international data at the country, regional and local levels with measures including cases, hospitalizations and deaths with guidance from local subject-matter experts. RESULTS: The hybrid chart effectively and rapidly signaled the occurrence of each of the four epochs. In the UK, a signal that COVID-19 deaths moved into exponential growth occurred on 17 September, 44 days prior to the announcement of a large-scale lockdown. In California, USA, signals detecting increases in COVID-19 cases at the county level were detected in December 2020 prior to statewide stay-at-home orders, with declines detected in the weeks following. In Ireland, in December 2020, the hybrid chart detected increases in COVID-19 cases, followed by hospitalizations, intensive care unit admissions and deaths. Following national restrictions in late December, a similar sequence of reductions in the measures was detected in January and February 2021. CONCLUSIONS: The Shewhart hybrid chart is a valuable tool for rapidly generating learning from data in close to real time. When used by subject-matter experts, the chart can guide actionable policy and local decision-making earlier than when action is likely to be taken without it.

Understanding variation in reported covid-19 deaths with a novel Shewhart chart application.

OBJECTIVE: Motivated by the coronavirus disease 2019 (covid-19) pandemic, we developed a novel Shewhart chart to visualize and learn from variation in reported deaths in an epidemic. CONTEXT: Without a method to understand if a day-to-day variation in outcomes may be attributed to meaningful signals of change-rather than variability we would expect-care providers, improvement leaders, policy-makers, and the public will struggle to recognize if epidemic conditions are improving. METHODS: We developed a novel hybrid C-chart and I-chart to detect within a geographic area the start and end of exponential growth in reported deaths. Reported deaths were the unit of analysis owing to erratic reporting of cases from variability in local testing strategies. We used simulation and case studies to assess chart performance and define technical parameters. This approach also applies to other critical measures related to a pandemic when high-quality data are available. CONCLUSIONS: The hybrid chart detected the start of exponential growth and identified early signals that the growth phase was ending. During a pandemic, timely reliable signals that an epidemic is waxing or waning may have mortal implications. This novel chart offers a practical tool, accessible to system leaders and frontline teams, to visualize and learn from daily reported deaths during an epidemic. Without Shewhart charts and, more broadly, a theory of variation in our epidemiological arsenal, we lack a scientific method for a real-time assessment of local conditions. Shewhart charts should become a standard method for learning from data in the context of a pandemic or epidemic.

Health care huddles: managing complexity to achieve high reliability.

BACKGROUND: Health care huddles are increasingly employed in a range of formats but theoretical mechanisms underlying huddles remain relatively uncharted. PURPOSE: A complexity science view implies that essential managerial strategies for high-performing health care organizations include meaningful conversations, enhanced relationships, and a learning culture. These three dimensions informed our approach to studying huddles. We explore new theories for how and why huddles have been useful in health care organizations. METHODS: We used a study design incorporating literature review, direct observation, and semistructured interviews. A complexity science framework guided data collection in three health care settings; we also incorporated theories on high-reliability organizations to analyze our observations and interpret huddle participants' perspectives. FINDINGS: We identify theoretical paths that could link huddles to improvement in patient safety outcomes. Huddles create time and space for conversations, enhance relationships, and strengthen a culture of safety. Huddles can be of particular value to health care organizations seeking or sustaining high reliability. PRACTICE IMPLICATIONS: Achieving high reliability, the organizational capacity to deliver what is intended to be delivered every time is difficult in complex systems. Managers have potential to create conditions from which huddle outcomes that support high reliability are more likely to emerge. Huddles support efforts to improve patient safety when they afford opportunities for heedful interactions to take place among individuals caring for patients and embed mindfulness into the organization.

It Is Time to Reconsider Factorial Designs: How Bradford Hill and R. A. Fisher Shaped the Standard of Clinical Evidence.

OBJECTIVES: Could medical research and quality improvement studies be more productive with greater use of multifactor study designs? METHODS: Drawing on new primary sources and the literature, we examine the roles of A. Bradford Hill and Ronald A. Fisher in introducing the design of experiments in medicine. RESULTS: Hill did not create the randomized controlled trial, but he popularized the idea. His choice to set aside Fisher's advanced study designs shaped the development of clinical research and helped the single-treatment trial to become a methodological standard. CONCLUSIONS: Multifactor designs are not widely used in medicine despite their potential to make improvement initiatives and health services research more efficient and effective. Quality managers, health system leaders, and directors of research institutes could increase productivity and gain important insights by promoting a broader use of factorial designs to study multiple interventions simultaneously and to learn from interactions.

Improving outcomes of hospitalized patients: the Physician Relationships, Improvising, and Sensemaking intervention protocol.

BACKGROUND: Our goal is to improve the safety and effectiveness of inpatient care. Rather than focus on improving process of care, we focus on the social structure within physician teams. We have developed the Physician Relationships, Improvising, and Sensemaking (PRISm) intervention to improve the way physician teams round, enabling them to better relate, make sense of their patients' conditions, and improvise in uncertain clinical situations. We are currently studying the impact of PRISm on adverse events and complications in hospitalized patients. This manuscript describes the PRISm intervention. METHODS/DESIGN: PRISm is a structured communication tool consisting of three components: daily briefings before rounds; use of the Situation, Task, Intent, Concern, and Calibrate (STICC) framework during rounds as part of the discussion of individual patients; and debriefings after rounds. We are implementing the PRISm intervention on eight inpatient medical and surgical physician teams in the South Texas Veterans Health Care System. We are assessing PRISm impact on the way team members relate to each other, round, and discuss patients through pre- and post-implementation observations and surveys. We are also assessing PRISm impact on complications and adverse events. Finally, we are interviewing physicians regarding their experience using the intervention. DISCUSSION: Our results will allow us to begin to understand the potential impact of interventions designed to improve how providers relate to each other, improvise, and make sense of what is happening as a strategy for improving inpatient care. Our in-depth data collection will enable us to assess how relationships, improvising, and sensemaking influence patient outcomes, potentially through creating shared mental models or enhancing distributed cognition during clinical reasoning. Finally, our results will lay the groundwork for larger implementation studies to improve clinical outcomes through improving how providers, and providers, patients, and caregivers, relate.