Machine Learning | Digital Healthcare Research

Harnessing Health Information Technology to Promote Equitable Care for Patients with Limited English Proficiency and Complex Care Needs

Description

This research will test and validate a machine learning predictive analytic intervention to optimize the timely and appropriate use of interpreters for hospitalized patients with language barriers and complex care needs.

Grant Number

R21 HS028475

Principal Investigator(s)

Barwise, Amelia K.

Improving Health Data Quality by Assessing and Enhancing Semantic Integrity

Description

This research will develop and validate advanced statistical and machine learning methods to assess and improve representational semantic integrity of terminologies in large clinical databases.

Grant Number

R01 HS028450

Principal Investigator(s)

Zeng, Qing

Nelson, Stuart James

Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol.

Citation

Lin E, Uhler LM, Finley EP, Jayakumar P, Rathouz PJ, Bozic KJ, Tsevat J. Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol. BMJ Open. 2022 Feb 21;12(2):e055933. doi: 10.1136/bmjopen-2021-055933. PMID: 35190439; PMCID: PMC8860037.

Principal Investigator

Bozic, Kevin John

Project Name

Incorporating Patient-Reported Outcomes into Shared Decision Making with Patients with Osteoarthritis of the Knee

Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events.

Citation

Fong A, Harriott N, Walters DM, Foley H, Morrissey R, Ratwani RR. Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events. Int J Med Inform. 2017 Aug;104:120-125. doi: 10.1016/j.ijmedinf.2017.05.005. Epub 2017 May 11. PMID: 28529113.

Principal Investigator

Ratwani, Raj M.

Project Name

Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability

Responding to health information technology reported safety events: Insights from patient safety event reports.

Citation

Adams K.T., Kim T.C., Fong A., Howe J.L., Kellogg K.M., Ratwani R.M. (2019) Responding to health IT reported safety events: Insights from patient safety event reports. Journal of Patient Safety and Risk Management. https://doi.org/10.1177/2516043519847330

Principal Investigator

Ratwani, Raj M.

Project Name

Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability

A machine learning approach to reclassifying miscellaneous patient safety event reports.

Citation

Fong A, Behzad S, Pruitt Z, Ratwani RM. A machine learning approach to reclassifying miscellaneous patient safety event reports. J Patient Saf. 2021 Dec 1;17(8):e829-e833. doi: 10.1097/PTS.0000000000000731. PMID: 32555052.

Principal Investigator

Ratwani, Raj M.

Project Name

Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability

Advancing motivational interviewing training with artificial intelligence: ReadMI.

Citation

Hershberger PJ, Pei Y, Bricker DA, Crawford TN, Shivakumar A, Vasoya M, Medaramitta R, Rechtin M, Bositty A, Wilson JF. Advancing motivational interviewing training with artificial intelligence: ReadMI. Adv Med Educ Pract. 2021 Jun 4;12:613-618. doi: 10.2147/AMEP.S312373. PMID: 34113205; PMCID: PMC8186935.

Principal Investigator

Hershberger, Paul J.

Project Name

Real-time Assessment of Dialogue in Motivational Interviewing Training (ReadMI)

Predicting self-intercepted medication ordering errors using machine learning.

Citation

King CR, Abraham J, Fritz BA, Cui Z, Galanter W, Chen Y, Kannampallil T. Predicting self-intercepted medication ordering errors using machine learning. PLoS One. 2021 Jul 14;16(7):e0254358. doi: 10.1371/journal.pone.0254358. PMID: 34260662; PMCID: PMC8279397.

Principal Investigator

Abraham, Joanna

Project Name

An Etiology for Medication Ordering Errors in Computerized Provider Order Entry Systems

Early identification of epilepsy surgery candidates: A multicenter, machine learning study.

Citation

Wissel BD, Greiner HM, Glauser TA, Pestian JP, Kemme AJ, Santel D, Ficker DM, Mangano FT, Szczesniak RD, Dexheimer JW. Early identification of epilepsy surgery candidates: A multicenter, machine learning study. Acta Neurol Scand. 2021 Jul;144(1):41-50. doi: 10.1111/ane.13418. Epub 2021 Mar 26. PMID: 33769560; PMCID: PMC8178229.

Principal Investigator

Dexheimer, Judith W.

Project Name

Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications.

Citation

Xue B, Li D, Lu C, King CR, Wildes T, Avidan MS, Kannampallil T, Abraham J. Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications. JAMA Netw Open. 2021 Mar 1;4(3):e212240. doi: 10.1001/jamanetworkopen.2021.2240. PMID: 33783520; PMCID: PMC8010590.

Principal Investigator

Avidan, Michael

Project Name

Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)