: Health care delivery systems are poised to change the paradigm of care delivery by using Health Information Technology (HIT) to bring population-based data to clinicians in support of population-based clinical practice. This information can potentially affect the quality, efficiency, and safety of health care delivery by engendering principles of population-based clinical practice. The overall project objective is to develop and evaluate novel methods for improving the care of patients presenting with acute respiratory infections (ARI). Annual outbreaks of ARI (bacterial and viral) are responsible for the majority of outpatient health care visits, and a large portion of hospitalizations in the US. The overuse of antibiotics for viral respiratory conditions has been linked to antibiotic resistance and represents a critical problem for our nation's public health. The problem of antibiotic overuse has been well documented, yet solutions to this problem have been only moderately successful, difficult to sustain, underdeveloped, and understudied. New approaches are urgently needed. The proposed project will focus on the population-based clinical practice and clinician management of ARI. A major problem is the inappropriate or ineffective use of antibiotics. For infectious diseases with person- to-person spread, the individual's likelihood of infection depends on the local incidence of disease. A clinician's understanding of local disease incidence is dependent upon observed trends that can be highly dynamic. A clinician with a poor understanding of local disease incidence has difficulty in differentiating bacterial from viral infections and in making effective decisions about antibiotics use and symptom-relieving therapies. Clinicians with knowledge of local disease activity and effective therapies may have difficulty implementing their decisions if the care delivery system in which they work is not designed to effectively manage patient expectations and health literacy that preclude them from exercising good judgment. The hypothesis we propose to test is that by providing physicians and their patients with timely and easily accessible information about the local incidence of common respiratory viruses, we will improve their ability to distinguish viral infections from bacterial infections, leading to more effective antibiotic prescribing in the context of ARI. We believe that evolving information technologies can support novel and sustainable approaches to delivering timely, population-health information about ARI to front line clinicians at the point-of- care in support of clinical decision.
Specific aims i nclude the following:
Aim 1 : Assess primary care clinician use of current population-based ARI health information resources and decision support tools using focus groups and structured observation.
Aim 2 : Refine decision support tools to improve clinical information system workflow integration and patient communication.
Aim 3 : Implement decision support tools in primary and urgent care settings.
Aim 4 : Measure the effects of decision support tools on population-based clinical practice and patient/parent compliance. My career development aims are designed to increase my expertise in the following areas: 1. Information visualization and geographical information display. 2. Visual perception, human cognition, and medical decision making. 3. Knowledge integration in clinical information systems. 4. Design, execution, and evaluation of health information technology intervention studies in clinical settings. These career development aims will facilitate my overarching career goal to become a nationally recognized, independent, physician scientist who will use information technology and clinical information systems to study and optimize the management of common diseases that greatly affect the health of adults and children. Acute respiratory infections (ARI) represent a major burden to the heath care delivery system and the public's health. The imprudent use of antibiotics for viral infections has contributed to the rapid emergence of antimicrobial resistance and a substantial number of adverse drug events. As a result, preventing the overuse of antibiotics is a National priority area for research. This proposal directly addresses this priority area and leverages federally funded public health surveillance infrastructure to generate and disseminate population- health information to front line clinicians.

Public Health Relevance

Acute respiratory infections (ARI) represent a major burden to the heath care delivery system and the public's health. The imprudent use of antibiotics for viral infections has contributed to the rapid emergence of antimicrobial resistance and a substantial number of adverse drug events. As a result, preventing the overuse of antibiotics is a National priority area for research. This proposal directly addresses this priority area and leverages federally funded public health surveillance infrastructure to generate and disseminate population- health information to front line clinicians.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Clinical Investigator Award (CIA) (K08)
Project #
5K08HS018538-03
Application #
8107596
Study Section
HSR Health Care Research Training SS (HCRT)
Program Officer
Anderson, Kay
Project Start
2009-09-30
Project End
2014-07-31
Budget Start
2011-09-01
Budget End
2012-07-31
Support Year
3
Fiscal Year
2011
Total Cost
Indirect Cost
Name
University of Utah
Department
Pediatrics
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
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Neill, Daniel B; Soetebier, Karl A (2011) International society for disease surveillance conference 2011: building the future of public health surveillance. Emerg Health Threats J 4:11702
Staes, Catherine J; Wuthrich, Amyanne; Gesteland, Per et al. (2011) Public health communication with frontline clinicians during the first wave of the 2009 influenza pandemic. J Public Health Manag Pract 17:36-44
Walton, Nephi A; Poynton, Mollie R; Gesteland, Per H et al. (2010) Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables. BMC Med Inform Decis Mak 10:68