Catalyzing System Change: 100 Quality Improvement Projects in 1000 Days.

BACKGROUND: Health system change requires quality improvement (QI) infrastructure that supports frontline staff implementing sustainable innovations. We created an 8-week rapid-cycle QI training program, Stanford Primary Care-Project Engagement Platform (PC-PEP), open to patient-facing primary care clinicians and staff. OBJECTIVE: Examine the feasibility and outcomes of a scalable QI program for busy practicing providers and staff in an academic medical center. DESIGN: Program evaluation. PARTICIPANTS: A total of 172 PCPH team members: providers (n = 55), staff (n = 99), and medical learners (n = 18) in the Stanford Division of Primary Care and Population Health (PCPH) clinics, 2018-2021. MAIN MEASURES: We categorized projects by the Institute for Healthcare Improvement's (IHI) Quintuple Aim (QA): better health, better patient experience, lower cost of care, better care team experience, and improved equity/inclusion. We assessed project progress with a modified version of The Ottawa Hospital Innovation Framework: step 1 (identified root causes), step 2 (designed/tested interventions), step 3 (assessed project outcome), step 4 (met project goal with target group), step 5A (intervention(s) spread within clinic), step 5B (intervention(s) spread to different setting). Participants rated post-participation QI self-efficacy. KEY RESULTS: Within 1000 days, 172 unique participants completed 104 PC-PEP projects. Most projects aimed to improve patient health (55%) or care team experience (23%). Among projects, 9% reached step 1, 8% step 2, 16% step 3, 26% step 4, 21% step 5A, and 20% step 5B. Learner involvement increased likelihood of scholarly products (47% vs 10%). Forty-six of 47 (98%) survey respondents reported improved QI self-efficacy. Medical assistants, more so than physicians, reported feeling acknowledged by the health system for their QI efforts (100% vs 61%). CONCLUSIONS: With appropriate QI infrastructure, scalable QI training models like Stanford PC-PEP can empower frontline workers to create meaningful changes across the IHI QA.

Disparities in COVID-19 testing and outcomes among Asian American and Pacific Islanders: an observational study in a large health care system.

BACKGROUND: The COVID-19 pandemic has disproportionately impacted racial and ethnic minorities in the United States, including Asian Americans, Native Hawaiians and Pacific Islanders (Asian Americans and NH/PIs). However, few studies have highlighted nor disaggregated these disparities by Asian Americans and NH/PIs ethnic subgroups. METHODS: This retrospective, cross-sectional observational study aimed to assess variation of Asian Americans and NH/PIs COVID-19 testing and outcomes compared to non-Hispanic Whites (NHW). The study utilized data from the electronic health records (EHR) and the COVID-19 Universal Registry for Vital Evaluations (CURVE) from all patients tested for SARS-CoV-2 (n = 556,690) at a large, health system in Northern and Central California between February 20, 2020 and March 31, 2021. Chi-square tests were used for testing differences in the severity of COVID-19 (hospitalization, ICU admission, death) and patient demographic and clinical characteristics across the Asian Americans and NH/PIs subgroups and NHW. Unadjusted and adjusted Odds Ratios (ORs) were estimated for measuring effect of race ethnicity on severity of COVID-19 using multivariable logistic regression. RESULTS: Of the entire tested population, 70,564/556,690 (12.7%) tested positive for SARS-CoV-2. SARS-CoV-2 positivity of Asian subgroups varied from 4% in the Chinese and Korean populations, to 11.2%, 13.5%, and 12.5% for Asian Indian, Filipino, and "other Asian" populations respectively. Pacific Islanders had the greatest subgroup test positivity at 20.1%. Among Asian Americans and NH/PIs patients with COVID-19 disease, Vietnamese (OR = 2.06, 95% CI = 1.30-3.25), "Other Asian" (OR = 2.13, 95% CI = 1.79-2.54), Filipino (OR = 1.78, 95% CI = 1.34-2.23), Japanese (OR = 1.78, 95% CI = 1.10-2.88), and Chinese (OR = 1.73, 95% CI = 1.34-2.23) subgroups had almost double the odds of hospitalization compared to NHW. Pacific Islander (OR = 1.58, 95% CI = 1.19-2.10) and mixed race subgroups (OR = 1.55, 95% CI = 1.10-2.20) had more than one and a half times odds of hospitalization compared to NHW. Adjusted odds of ICU admission or death among hospitalized patients by different Asian subgroups varied but were not statistically significant. CONCLUSIONS: Variation of COVID-19 testing and hospitalization by Asian subgroups was striking in our study. A focus on the Asian Americans and NH/PIs population with disaggregation of subgroups is crucial to understand nuances of health access, utilization, and outcomes among subgroups to create health equity for these underrepresented populations.