Research on health informatics at Kaiser Permanente Washington focuses on developing and using health information technology (IT) to transform health care delivery. By testing new paradigms of care that provide more opportunities to engage patients, this research is supplying valuable evidence that is helping shape federal policy and guiding innovative redesign of health care.
“We’re working to understand how to make health IT practical so patients and care teams find it useful and engaging,” explained Kaiser Permanente Washington Health Research Institute (KPWHRI) Senior Investigator James Ralston, MD, MPH. “We want to find ways to use information technologies to support patients and providers together, both inside and outside the office.”
Integral to this support is designing technologies that are user-friendly and meet the needs of both patients and providers. By applying human-centered methods that focus on needs, use, and usability, KPWHRI researchers inform the design of health IT with direct participation from users.
Groundbreaking methodological work by KPWHRI health informatics researchers includes developing natural language processing (NLP) to analyze text such as notes and written reports in electronic health records (EHRs). Assistant Investigator David Carrell, PhD, leads in the area of using NLP and machine learning to identify patient phenotypes, or specific health characteristics such as possible heart disease, risk of opioid overdose, or suggestion of colon cancer. This information can assist researchers in studying how genetics and other factors influence disease.
Other examples of KPWHRI health informatics research include projects using EHRs and secure electronic communications such as:
Examples of KPWHRI research in mobile health (mHealth) and user-centered design include:
“Our studies on using health IT to improve care are showing that we can achieve better outcomes when we shift care from the doctor’s office to where people live: in their homes—and online,” said Senior Investigator Beverly B. Green, MD, MPH.
Eicher JD, Chami N, Kacprowski T, Nomura A, Chen MH, Yanek LR, Tajuddin SM, Schick UM, Slater AJ, Pankratz N, Polfus L, Schurmann C, Giri A, Brody JA, Lange LA, Manichaikul A, Hill WD, Pazoki R, Elliot P, Evangelou E, Tzoulaki I, Gao H, Vergnaud AC, Mathias RA, Becker DM, Becker LC, Burt A, Crosslin DR, Lyytikäinen LP, Nikus K, Hernesniemi J, Kähönen M, Raitoharju E, Mononen N, Raitakari OT, Lehtimäki T, Cushman M, Zakai NA, Nickerson DA, Raffield LM, Quarells R, Willer CJ, Peloso GM, Abecasis GR, Liu DJ; Global Lipids Genetics Consortium, Deloukas P, Samani NJ, Schunkert H, Erdmann J; CARDIoGRAM Exome Consortium; Myocardial Infarction Genetics Consortium, Fornage M, Richard M, Tardif JC, Rioux JD, Dube MP, de Denus S, Lu Y, Bottinger EP, Loos RJ, Smith AV, Harris TB, Launer LJ, Gudnason V, Velez Edwards DR, Torstenson ES, Liu Y, Tracy RP, Rotter JI, Rich SS, Highland HM, Boerwinkle E, Li J, Lange E, Wilson JG, Mihailov E, Mägi R, Hirschhorn J, Metspalu A, Esko T, Vacchi-Suzzi C, Nalls MA, Zonderman AB, Evans MK, Engström G, Orho-Melander M, Melander O, O'Donoghue ML, Waterworth DM, Wallentin L, White HD, Floyd JS, Bartz TM, Rice KM, Psaty BM, Starr JM, Liewald DC, Hayward C, Deary IJ, Greinacher A, Völker U, Thiele T, Völzke H, van Rooij FJ, Uitterlinden AG, Franco OH, Dehghan A, Edwards TL, Ganesh SK, Kathiresan S, Faraday N, Auer PL, Reiner AP, Lettre G, Johnson AD. Platelet-related variants identified by exomechip meta-analysis in 157,293 individuals. Am J Hum Genet. 2016 Jul 7;99(1):40-55. doi: 10.1016/j.ajhg.2016.05.005. Epub 2016 Jun 23. PubMed
Bayliss EA, McQuillan DB, Ellis JL, Maciejewski ML, Zeng C, Barton MB, Boyd CM, Fortin M, Ling SM, Tai-Seale M, Ralston JD, Ritchie CS, Zulman DM. Using electronic health record data to measure care quality for individuals with multiple chronic medical conditions. J Am Geriatr Soc. 2016 Jul 7. doi: 10.1111/jgs.14248. [Epub ahead of print]. PubMed
Glass JE, Bohnert K, Brown RL. Alcohol screening and intervention among United States adults who attend ambulatory healthcare. J Gen Intern Med. 2016 Jul;31(7):739-45. doi: 10.1007/s11606-016-3614-5. Epub 2016 Feb 9. PubMed
Hubbard RA, Johnson E, Chubak J, Wernli K, Kamineni A, Bogart A, Rutter CM. Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models. Health Serv Outcomes Res Methodol. 2017 Jun;17(2):101-112. doi: 10.1007/s10742-016-0149-5. Epub 2016 Jun 3. PubMed
Bradley CJ, Grossman DC, Hubbard RA, Ortega AN, Curry SJ. Integrated interventions for improving total worker health: a panel report from the National Institutes of Health Pathways to Prevention Workshop: total worker health—what's work got to do with it? Ann Intern Med. 2016 May 31. doi: 10.7326/M16-0740. [Epub ahead of print]. PubMed
James D. Ralston, MD, MPHSenior Investigator |
Jennifer B. McClure, PhDDirector, Investigative Science |
Beverly B. Green, MD, MPHSenior Investigator |
Katharine A. Bradley, MD, MPHSenior Investigator |
Paula Lozano, MD, MPHSenior Investigator; Director, ACT Center |
Yates Coley, PhDAssociate Biostatistics Investigator |
Brian D. Williamson, PhDAssistant Biostatistics Investigator |
Annie Hoopes, MD, MPHActing Assistant Investigator |
Claire Allen, MPHManager, Collaborative Science |
Annie Piccorelli, PhDSenior Collaborative Biostatistician |