Events

June 4, 2024

SPRING CONFERENCE ROUNDUP

Emily Godfrey, MD, MPH

Professor of Family Medicine
and of Obstetrics and Gynecology

M. Ashworth Dirac, MD, PhD

Assistant Professor of Health Metrics Sciences
and of Family Medicine

TITLE

Using a community and academic partnership to assess family medicine’s contribution to maternal and infant health

ABSTRACT

Worse rates of pregnancy-related mortality and morbidity exist in the United States than any other high-income country in the world. This may be due in part to many pregnant individuals residing in locations without local access to obstetric care providers. To track access, the March of Dimes reports on Maternity Care Deserts (MCDs), defined as counties without practicing obstetrician-gynecologists or certified nurse midwives. Family medicine physicians who provide OB (FM OB) are not included among the obstetrical providers in these reports. In fact, there are FM OB providers in 16% of MCD counties. This presentation will present how we engaged a community partner, the Robert Graham Center in Washington DC, to conduct an analysis comparing county-level, log-transformed maternal mortality ratio (MRR) and infant low birth weight (LBW) rates using data from the National Vital Statistics System, National Center for Health Statistics between 943 “true” MCD counties (without FM OB) and 181 MCD counties with FM OB. Although data analysis is still underway, we will discuss the process we use to accurately determine differences between “true” MCD and FM OB MCD counties, and how we work with our community partner to plan for dissemination of the study findings.

LEARNING OBJECTIVES

1. How to assess maternal mortality ratios and infant low birth weight rates using national vital statistics data
2. Understand the importance of engaging partners as equal members of the research team

M. Ashworth Dirac, MD, PhD

Assistant Professor of Health Metrics Sciences
and of Family Medicine

Mei Wang, MPH

Researcher,
Institute for Health Metrics and Evaluation,

Reproductive, Genitourinary, and Digestive Diseases (RGUD) Team

TITLE

Estimating Mortality in Gallbladder and Biliary Diseases Using the CODEm Method: Insights from the Global Burden of Disease Study

ABSTRACT

Introduction: GBD (Global Burden of Disease Study) is a global scientific effort to quantify the burden of over 360 diseases and injuries by age, sex, and location from 1990 to present.

Methods: To estimate age, sex, year and location-specific death rates of gallbladder and biliary disease, we utilized Cause of Death (COD) data and applied Cause of Death Ensemble modeling (CODEm) tool. COD data for gallbladder and biliary disease was extracted from vital registration systems and verbal autopsies from 3701 sources covering 126 countries. Raw COD data were standardized to account for different coding practices and age-sex aggregations. Processed COD data were used as an input to CODEm—a highly systemized Bayesian, geo-temporal ensemble model—to analyze death rates of disease. CODEm tested a wide variety of submodels using different sets of predictive covariates and model types. Each submodel was weighted based on its out-of-sample predictively validity. The submodels with the highest predictive validity were combined to make the final ensemble model, ensuring accuracy and robustness in estimating cause-specific mortality rates across diverse populations and regions.

Results: Global deaths were estimated at 131,100 (113,600 to 161,800) in 2021. This was a 71.7% increase from 76,400 (60,900 to 85,300) deaths in 1990. The global age-standardized mortality rate was 1.62 (1.4 to 2) per 100,000 in 2021, which was a 28% decrease from 2.25 (1.83 to 2.51) per 100,000 in 1990.

Conclusion: Although a significant global increase in gallbladder and biliary diseases death between 1990 and 2021 was noticed, there has been a notable decrease in the age-standardized mortality rate over the same period, suggesting potential advancements in healthcare and management strategies. The application of the CODEm method not only enhances the accuracy of mortality assessments but also facilitates informed decision-making and targeted strategies for addressing different challenges in different parts of the world.

LEARNING OBJECTIVES

1. Describe the benefits of meta-regression and predictive modeling for understanding epidemiological trends when and where data are scarce
2. Distinguish between trends in real burden versus age-standardized rates and how each provide useful information for healthcare planning and population health

Paula Kett, PhD, MPH, RN

Research Scientist,
Department of Family Medicine

TITLE

Factors associated with public health workforce competencies to advance health equity

ABSTRACT

Background: We examined individual and local health department (LHD) characteristics associated with health equity concepts.

Methods: Using the 2021 Public Health Workforce Interest and Needs Survey (PH WINS), a national dataset (N=29751), logistic regression assessed associations between key factors and staff-reported “knowledge of” and “confidence in addressing” structural racism, health equity, social determinants of equity (SDoE), social determinants of health (SDOH), and environmental justice; also, agreement that addressing racism should be part of their work and whether they are involved in that work. Key factors included staff education, tenure, race/ethnicity, and skills (e.g. cross-sector collaboration, policy advocacy), LHD characteristics (e.g. clinician-led), and county demographics.

Results: Staff with a master’s degree or higher compared with less education reported greater odds of confidence in addressing structural racism (adjusted odds ratio [AOR]=1.23) and health equity (AOR=1.56), agreeing that addressing racism should be a part of their work (AOR=2.45) and being involved in such efforts (AOR=1.57). Black staff compared with White staff reported greater odds of confidence in addressing all concepts: structural racism (AOR=1.98), health equity (AOR=1.34), SDoE (AOR=1.53), SDOH (AOR=1.21), environmental justice (AOR=1.72), and agreeing that addressing racism should be a part of their work (AOR=2.11). Patterns were similar among other staff of color, however, black (AOR=0.68) and Hispanic/Latino (AOR=0.83) staff reported lower odds of involvement in efforts to address racism. Staff skills like cross-sector collaboration and policy advocacy, as well as clinician-led LHDs, were positively associated with most outcomes.

Conclusions: Findings suggest the need for more targeted workforce development, including designing training which involves explicitly naming structural racism’s effects, application of health equity concepts, skill development in policy advocacy, and measurements to evaluate success. Future research should explore ways to effectively motivate White staff to accept responsibility as public health practitioners to address racism as well as how to support staff of color in health equity work.

LEARNING OBJECTIVES

1. Describe two to three factors associated with greater knowledge of and confidence in addressing health equity among governmental public health staff
2. Identify at least two characteristics associated with staff-reported involvement in work to address racism as a public health crisis
3. Discuss recommendations to improve workforce development and training focused on advancing health equity

Samantha Pollack, MHS

Research Scientist,
Department of Family Medicine

TITLE

Medical Assistants’ Telehealth Roles and Skills in Primary Care During the COVID-19 Pandemic

ABSTRACT

Research Objective: This study identifies the skills and roles of medical assistants (MAs) that best supported the transition to greater use of telehealth in primary care in response to the COVID-19 pandemic; the policies and practices supporting MAs’ expanded roles and transfer of skills to virtual care; and longer-term needs to improve and maintain telehealth skills and competencies in the MA workforce.

Study Design: Qualitative interview study and literature review. We reviewed published (gray and peer-reviewed) literature on the influence of telehealth implementation on MAs’ roles in primary care and conducted interviews with ten key informants knowledgeable about the workforce providing telehealth in primary care.

Population Studied: Key informants represented MA and telehealth education programs, MA and/or telehealth professional organizations, as well as individuals involved in the implementation of telehealth in primary care practice. Informants were selected across a range of national and state-levels, government and private-sectors, and different system sizes and geographic distribution.

Principal Findings: Pandemic emergency rules expanding telehealth payment and preserving primary care services enabled many of MAs’ roles to transfer from in-person to virtual and provided MAs with opportunities to rapidly take on new roles and increased responsibility in support of telehealth primary care teams. How and the extent to which MAs’ telehealth roles were implemented during the pandemic depended on the size and location of the clinic facilities, and the variety and consistency of staffing at the clinics. MAs were generally not well-prepared by their education programs in specific telehealth skills. Most of their telehealth training took place on-the-job, and they were able to adapt the skills and roles in which they were already trained for use in virtual settings.

Conclusions: MAs will continue to be integral to both in-person and virtual health care teams and more opportunities may emerge for MAs to expand their roles in telehealth. When MAs were available to support telehealth teams during the pandemic, their roles in promoting clinic efficiency and care quality were recognized.

2024 research seminars

January 2

Sebastian Tong, MD, MPH

Kris Pui Kwan Ma, PhD

Topic: Addressing Loneliness in Young Adults
February 6

Randl Dent, PhD & Candice Chen, MD, MPH

Topic: Addressing Health Worker Burnout
March 5

Xiaochu Hu, PhD

Topic: Drs. Barbie and Ken – Gender Inequality in the Physician Workforce
April 2

Monica Zigman Suchsland, MPH

Topic: Evaluation of pre- and post- sport related concussion symptom presentation through concussion sub-type classification using machine learning methods
May 7

Jeongyoung Park, PhD

Topic: Factors Associated with Documenting Social Determinants of Health in Electronic Health Records by Family Physicians
June 4

Spring Conference Roundup

 
September 3

Ashley Johnson, MPH

Topic: TBD
October 1

Mae Dirac, MD, PhD

Topic: TBD
November 5

Kate Comtois, PhD, MPH

Topic: TBD
December 3

Conference Round Up

 

To join a seminar or to be added to the Research Seminar mailing list, please e-mail Azelea Sayavong: azeleagn@uw.edu.