DNP Informatics Projects

Technology and informatics tools are projected to be key to improving health outcomes for populations as well as decreasing health care costs. Critical questions that need answers include how to best use information tools or data to identify health care needs, change health behaviors, manage chronic health conditions, improve health in communities, and increase access to care. Currently, a gap exists between public and population health, social determinants of health (SDOH), and informatics concepts. To address this gap, AACN created the Doctor of Nursing Practice Informatics Project awards to support students in their final projects focused on the use of data, data tools, and the public and population health/SDOH to improve health outcomes.  

Funded Projects

The Evaluation of Rapid Cycle Development Clinical Decision Support in Infectious Disease Processes
Dr. Dwayne Hoelscher (Texas Tech University Sciences Center)

Project Title: The Evaluation of Rapid Cycle Development Clinical Decision Support in Infectious Disease Processes

Student: Dwayne Hoelscher is graduate prepared nurse with 22 years of nursing experience including emergency nursing, critical care nursing, case management, risk management, and the last five years in clinical informatics. Hoelscher is the primary clinical decision support staff member at his current place of employment. He is the co-chair with CMIO of local rules and alerts committee. Hoelscher has given multiple presentations focusing on clinical decision support including a podium presentation at HIMSS 2017 (co-presenter) and two poster presentations, one at Texas Tech University Health Sciences Center (co-presenter) and one at ANIA 2016 annual conference (co-presenter). Evaluating usability, reducing alert fatigue, and evaluating documentation burden has been the main foci of this project.

Project Summary: The purpose of this project is to develop a modular approach to rapid deployment of CDS for infectious diseases and evaluate the usability of the design. The project will also develop a governance model including interdisciplinary infectious disease experts to guide the process. The main objective will be a well-designed CDS strategy for infectious disease within the clinician’s workflow with minimal interruption. Evaluation will include usability, monitoring functionality, and reporting outcomes.

Implementing a Social Determinants of Health Screening Tool at a Community Health Clinic
Dr. Erin Floyd (University of Kansas)

Project Title: Implementing a Social Determinants of Health Screening Tool at a Community Health Clinic

Student: Dr. Erin Floyd is a graduate of the Doctor of Nursing Practice Program for Family Practice at the University of Kansas.  Her career in nursing has spanned almost 7 years. She is currently working with the Cardiothoracic Surgery Intensive Care group at the University of Kansas Health System.  Her previous nursing experience was in Medical-Surgical Intensive and Progressive care.

While pursuing her educational goals, Dr. Floyd worked as a Graduate Teaching Assistant in several graduate courses and taught Bachelor of Nursing Students in the Clinical Learning Lab at the University of Kansas School of Nursing. While in school, Dr. Floyd spent a semester of clinical practicum with underserved populations, which sparked her interest and led her to pursue research in social determinants for underserved populations. As a student, she was an Advanced Nursing Education Workforce Grant recipient, which allowed her to gain clinical exposure to rural healthcare in Kansas.  In her personal time, Dr. Floyd enjoys exercising, painting, traveling with friends, and relaxing at home with her two cats.

Project Summary: The aim of this project is to implement a social determinants of health (SDOH) screening tool to increase provider referral rates to community services for patients cared for at a safety-net clinic in Kansas City, Kansas. While referral rates to community services are the primary objective, the desired purpose is to implement a sustainable informatics process to screen for SDOH.

Digitalizing Infectious Disease Clinical Guidelines for Improved Clinician Satisfaction
Dr. Stephanie Hoelscher (Texas Tech University Sciences Center)

Project Title: Digitalizing Infectious Disease Clinical Guidelines for Improved Clinician Satisfaction

Student: Steph Hoelscher MSN, RN-BC, CPHIMS, CHISP is the Chief Clinical Analyst for the Office of Clinical Transformation at Texas Tech University Health Sciences Center’s School of Medicine in Lubbock, Texas. She is a nurse with more than 20 years of experience in trauma, acute care, and ambulatory settings. In 2010, she moved to informatics and assisted in the implementation of an electronic health record (EHR) for a large academic center. To date, she continues to aid in the design and build of EHR applications for two ambulatory systems as well as a large medical center. She has served as a member of the implementation team for development of an EHR within a high-fidelity simulation center, concentrating specifically on obfuscation and de-identification of patient data. Steph is currently a member of the CDC’s Adapting Clinical Guidelines for the Digital Age project. She works with the local SAFER Guides leadership group to improve the safety of the institutional EHR. She is currently serving her second year as the Lubbock HIMSS chapter Vice President of Finance. Recent highlights include testifying at the Public Health Task Force in Washington, DC, regarding Zika and its impact on clinical decision support systems and presenting at the Public Health Informatics conference regarding care of the transgender patient in EHRs.

Project Summary: The purpose of this project is to design a CDS rapid-deployment model to use in the event of future infectious diseases such as Zika or Ebola. These types of outbreaks require rapid deployment with flexibility given the swiftly changing components such as travel history exposure. The project strategy will focus on developing a base model EHR documentation template, and alert algorithms that can be modified and turned on quickly for execution. Use of the PDSA model coupled with the quadruple aim1 will aid in enhancing the patient experience, improving population health, reducing cost, and improving provider satisfaction.