Decision Making in Biosurveillance

Funding Agency: 
NIH
Grant/Contract No.: 
R01 LM009132
Project Dates: 
09/30/2008 to 09/29/2013

The objective of this research is to advance the use of decision analysis in biosurveillance. The specific aims of the research were to (1) construct decision analyses of representative biosurveillance decision problems using standard decision analytic techniques, and (2) deploy the underlying decision models in a decision-support system for analysts and epidemiologists.

Home care: more than just a visiting nurse

Romagnoli KM, Handler SM, Hochheiser H.  Home care: more than just a visiting nurse.  BMJ Quality & Safety. doi:10.1136/bmjqs-2013-002339.  Aug. 2013 PMID: 23940375 [PubMed in process]

When patients leave the hospital and return home with home nursing care, they go from highly supportive medical environments with potentially many physicians, nurses, aides and other professionals, to non-medical environments with formal and informal caregiver support frequently supplemented by visits from home care nurses. Patients and caregivers must struggle to absorb confusing and potentially contradictory information imparted both by multiple clinicians prior to discharge from the hospital and by home care nurses. Providers, for their part, often have incomplete understandings of home environments and patient and caregiver capabilities. Despite these difficulties, patients are largely left to themselves, expected to be engaged in their care sufficiently to own and manage their medical conditions. It is a daunting task.

Patient safety at home is as important as patient safety in hospitals. Unsafe conditions in the home can lead to unnecessary or avoidable hospitalisations.1 Home care decreases costs, improves health outcomes, and reduces hospital stays.2–8 Despite these benefits, problems exist. Around 13% of patients enrolled in home care experience an adverse event.9 ,10 The largest proportion of adverse events that occur among home care patients are related to medications, with 20–33% experiencing a medication problem or adverse drug event.11 ,12 Research has found that home care personnel and informal caregivers may play a role in a substantial subset of adverse events that result in hospitalisation,13 although further investigation is needed to understand the nature of the interaction. Insufficient attention to effective communication during transitional care from hospital to home may be one of the factors contributing to these patterns.1 ,14

Relatively little attention has been paid to the underlying causes of these adverse events and how they might be prevented. Our literature search revealed a limited number of published manuscripts in this domain compared to other settings. To prevent hospital readmissions, improve patient outcomes and save money, more attention must be paid to home care safety.

Publication Year: 
2013

Jonathan Young, MD, MS

Directory Listing Information
Young, Jonathan
518a BAUM

Doctoral Student, Intelligent Systems Program

BA (2002, Biology) University of Virginia

MS (2005, Physiology and Biophysics) Georgetown University

MD (2010, Medicine) Eastern Virginia Medical School

MS (2015, Biomedical Informatics) University of Pittsburgh

 

Clinical integration of next-generation sequencing technology

Gullapalli RR, Lyons-Weiler M, Petrosko P, Dhir R, Becich MJ, LaFramboise WA. Clinical integration of next-generation sequencing technology. Clin Lab Med. 2012 Dec;32(4):585-99. doi: 10.1016/j.cll.2012.07.005. Review. PMID: 23078661

Publication Year: 
2012

Pathology informatics fellowship retreats: The use of interactive scenarios and case studies as pathology informatics teaching tools

Lee RE, McClintock DS, Balis UJ, Baron JM, Becich MJ, Beckwith BA, Brodsky VB, Carter AB, Dighe AS, Haghighi M, Hipp JD, Henricks WH, Kim JY, Klepseis VE, Kuo FC, Lane WJ, Levy BP, Onozato ML, Park SL, Sinard JH, Tuthill MJ, Gilbertson JR. Pathology informatics fellowship retreats: The use of interactive scenarios and case studies as pathology informatics teaching tools. J Pathol Inform. 2012;3:41. doi: 10.4103/2153-3539.103995. Epub 2012 Nov 28. PMID: 23248762

Publication Year: 
2012

UWM-TRIADS: Classifying Drug-Drug Interactions with Two-Stage SVM and Post-Processing

Rasteger-Mojarad, M., Boyce RD., Prasad, R. UWM-TRIADS: Classifying Drug-Drug Interactions with Two-Stage SVM and Post-Processing. Proceedings of the 2013 International Workshop on Semantic Evaluation (SemEval), Task 9 - Extraction of Drug-drug Interactions from BioMedical Texts. Atlanta Georgia, June 2013.

Publication Year: 
2013
Faculty Author: 

Anish Bhaswanth Chakka

Directory Listing Information
Chakka, Anish Bhaswanth
5607 Baum Blvd
(412) 624-8150

Software Design/Development

^