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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 4 of 4 Research Studies DisplayedLi M, Morey DA, Rayo MF
Symbiotic design application in healthcare: preventing hospital acquired infections.
The purpose of this study was to describe the researchers’ experience with the early development stages of an AI-enabled clinical decision support (CDS) tool for hospital-acquired infection (HAI) prevention. The study focuses on three central principles of a symbiotic design process that the researchers have determined to be vital for aligning goals, priorities, mental models, and techniques among a multidisciplinary team: 1) recurrent bottom-up feedback, 2) continual model alignment, and 3) openness to co-direction. The study explores the successes and challenges encountered by the team during the process and discusses how those experiences can impact the design of human-machine teams.
AHRQ-funded; HS027200.
Citation: Li M, Morey DA, Rayo MF .
Symbiotic design application in healthcare: preventing hospital acquired infections.
Proc Int Symp Hum Factors Ergon Healthc 2021 Jun;10(1):211-16. doi: 10.1177/2327857921101138..
Keywords: Research Methodologies, Clinical Decision Support (CDS), Health Information Technology (HIT)
Rodriguez PJ, Ward ZJ, Long MW
Applied methods for estimating transition probabilities from electronic health record data.
This study examined the usefulness of electronic health records (EHRs) in estimating transition probabilities for state-transition models. No guidelines exist on appropriate methods. The authors used 3 potential methods to estimate transition probabilities for EHR data, using pediatric eating disorders (EDs) as a case study. They mapped diagnoses to 3 ED health states: anorexia nervous, bulimia nervosa, and other specified feeding or eating disorder using data from PEDsnet, which includes 8 US children’s hospitals. They used 3 approaches: simple first-last proportions, a multistate Markov (MSM) model, and independent survival models. The first-last proportion approach estimated higher probabilities of remaining the same health state, while the other two approaches estimated higher probabilities of transitioning to a different health state. Published literature differed substantially from these estimates. Further research is needed to improve methods for using EHR data to inform transition probabilities.
AHRQ-funded; HS013853.
Citation: Rodriguez PJ, Ward ZJ, Long MW .
Applied methods for estimating transition probabilities from electronic health record data.
Med Decis Making 2021 Feb;41(2):143-52. doi: 10.1177/0272989x20985752..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR), Research Methodologies
Valdez RS, Guterbock TM, Thompson MJ
Beyond traditional advertisements: leveraging Facebook's social structures for research recruitment.
This study aimed to develop and assess the feasibility, benefits, and challenges of recruiting for research studies related to consumer health information technology (IT) by leveraging the social structures embedded in the social networking platform, Facebook. It demonstrated that leveraging the social structures of Facebook for health-related research was feasible for obtaining small samples appropriate for qualitative research but not for obtaining large samples needed for quantitative research.
AHRQ-funded; HS022930.
Citation: Valdez RS, Guterbock TM, Thompson MJ .
Beyond traditional advertisements: leveraging Facebook's social structures for research recruitment.
J Med Internet Res 2014 Oct 27;16(10):e243. doi: 10.2196/jmir.3786..
Keywords: Health Information Technology (HIT), Social Media, Research Methodologies
Keenan GM, Wilkie DJ
Integration of NNN into EHRS: how are we doing?: IJNK virtual issue.
This commentary introduces a virtual edition of IJNK, hosted on the Journal’s website. It includes six articles published in the last 20 years that provide a snapshot of efforts to integrate one or more of the standardized terminologies, NANDA-I, NOC, NIC (NNN), into electronic health records (EHRs).
AHRQ-funded; HS015054.
Citation: Keenan GM, Wilkie DJ .
Integration of NNN into EHRS: how are we doing?: IJNK virtual issue.
Int J Nurs Knowl 2014 Jun;25(2):68-9. doi: 10.1111/2047-3095.12039..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Research Methodologies