This session includes two presentations about how communities have been engaged in data collection and display efforts.
- Presentation 1: Introducing Health Equity Objectives to Community Partners: Data to Action
(Dionisia de la Cerda, Ashley Sherrill; CU Anschutz) - Presentation 2: Assessing Syndromic Surveillance Data Quality During the Pandemic Uncovers Lessons in Health Equity and Access to Care (Jennifer Kret, Yushiuan Chen; Tri-County Health Department)
---------------------------
Full presentation descriptions:Introducing Health Equity Objectives to Community Partners: Data to Action This lecture presentation will describe to attendees a process for working with a large research team to identify methods to embed inclusivity and health equity (I&E) objectives into existing practice improvement work. In Colorado, the Practice Innovation Program at the University of Colorado (PIPCO) convenes and staffs the Colorado Health Extension System, a multi-stakeholder cooperative partnership that includes over twenty Practice Transformation Organizations, which include health systems, professional associations, and other groups that provide transformation and quality improvement support for practices and healthcare delivery organizations. PIPCO leads projects with ongoing quality improvement efforts in clinical practices and communities.
Practice facilitators work directly with practice staff and clinicians to identify and agree on specific and achievable milestones and action steps that aim to address inclusivity and health equity. The milestone activities present a guide for practice facilitators to provide objective steps to build I&E into leadership, data driven quality improvement, team-based care, patient and family engagement, and access to care. The revised milestones guide practice-level activities that translate I&E aims into routine practice actions. This innovative approach supports gathering data and metrics to monitor and measure improvements and identify and address health inequities in clinical practice populations across Colorado.
Working with PIPCO leadership and health equity experts, we implemented this new I&E component into our existing milestone assessment tool. This talk aims to discuss the lessons learned in the early design and implementation process, and what we are learning from the data thus far.
Assessing Syndromic Surveillance Data Quality During the Pandemic Uncovers Lessons in Health Equity and Access to CareColorado Local Syndromic Surveillance collects near-real time data for residents of Adams, Arapahoe, and Douglas counties who visited a participating hospital. These data improve situational awareness and enhance responsiveness to hazardous events and disease outbreaks.
Complete data are essential for identifying disease trends in a pandemic. Missing information can adversely affect downstream meaningful and actionable uses of data for public health monitoring or policy decisions. During the pandemic, total emergency department (ED) visits sharply declined from 8,835 the week of March 8, 2020 to 4,493 the week of April 12, 2020, and then steadily rebounded. During 2021, percentages of missing discharge diagnoses increased from 2.3% (low) to 4.6% (high). Meanwhile, percentages of patients whose discharge disposition indicated leaving against medical advice or discontinued care increased from 1.2% (low) to 4.0% (high). Our hypothesis is that increases in COVID-19 patients overwhelmed EDs and health care systems, causing patients to forgo receiving care for other reasons (e.g., abdominal pain, chest pain, alcohol withdrawal), when experiencing long wait times in EDs.
The presentation will describe trends in ED visits, from October 2019 to December 2021, overall, with missing discharge diagnoses, and those where patients left without receiving care. During 2021, counts of COVID-19-related visits correlated with percentages of missing diagnoses (Correlation=0.710, p<.0001) and numbers of patients leaving the ED (Correlation=0.706, p<.0001). We will also describe characteristics of patients who left without receiving care, including age, sex, race, ethnicity, zip code, and insurance, during 2021 and highlight disparities.
These analyses offer insights to patient healthcare-seeking behaviors during the pandemic and a proxy indicator for access to care. These observations in Syndromic Surveillance will likely appear in hospital discharge data. Looking through a data quality lens is a novel way to identify disparities and health equity trends, as we transition towards recovery and new beginnings.