This Career Development Application provides targeted coursework and mentored research necessary for progression to independent research in the interdisciplinary area of health information quality. Data and information in health records are used in decision making in the clinical setting, for billing, and for important secondary uses such as quality improvement and research. Inaccurate, incomplete, or inaccessible information may jeopardize clinical decisions, and may deter clinicians from using health information systems, thus undermining the gains in healthcare safety and quality that we seek through Health Informatics and Health IT. Our ability to improve human health through informatics relies on acceptable information quality. Thus, it is imperative that information quality methodology in healthcare keep pace with advances in other areas of health informatics. Therefore, the specific aims of the mentored (M) and independent (R) research phases are:
Aim M1: Identify and characterize factors in clinician willingness to use information provided by others in decision making, e.g., information in EHRs, or information from Health Information Exchanges (HIEs).
Aim M2: Develop and validate indicators of information quality, e.g., a quality score that will increase clinician willingness to use appropriate quality information provided by others.
Aim M3: Evaluate methodology to test the impact of poor information quality on clinical decisions in hypertension and colorectal cancer screening patients.
Aim R1: Extend the work in aim M1 to other clinical facilities to achieve greater generalizability.
Aim R2: Test whether knowledge information quality impacts information use in clinical guideline-based decisions in hypertension and colorectal cancer screening patients.
Aim R3: Test the impact of improving information quality on blood pressure control in hypertensive patients in the primary care setting using a randomized, controlled clinical trial. This significant work initiates a formal program of research in an uncharted area. The applicant, Meredith Nahm, PhD has completed doctoral study in Health Informatics and has considerable career and early research experience characterizing and assessing clinical data quality.
These aims probe the need for information quality research in healthcare, and pilot methodology to assess the impact of information quality and knowledge of information quality on clinical decisions. Positive results from this research will provide methodology for information quality improvement that targets clinically important information.

Public Health Relevance

Public Narrative Poor information quality causes problems across all industries, and decisions are often only as good as the information on which they were based. Healthcare providers, professionals, and patients rely on information for decision making. Further, society depends on the quality of information generated in the healthcare setting through secondary data uses like disease surveillance, quality improvement, and clinical research. This pioneering research directly impacts public health by supporting the development of an independent researcher devoted to health information quality, and by laying the foundation for program of research in healthcare information quality.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Career Transition Award (K99)
Project #
1K99LM011128-01A1
Application #
8300533
Study Section
Special Emphasis Panel (ZLM1-ZH-C (01))
Program Officer
Sim, Hua-Chuan
Project Start
2012-04-01
Project End
2014-03-31
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
1
Fiscal Year
2012
Total Cost
$88,770
Indirect Cost
$6,105
Name
Duke University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Zozus, Meredith N; Pieper, Carl; Johnson, Constance M et al. (2015) Factors Affecting Accuracy of Data Abstracted from Medical Records. PLoS One 10:e0138649
Nahm, Meredith; Hammond, W Ed (2013) Data standard ? data quality. Stud Health Technol Inform 192:1208