NURSING RESEARCH SEMINAR SERIES Using CTSA Resources for

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NURSING RESEARCH SEMINAR SERIES Using CTSA Resources for Big Data Research, Scholarship, and Teaching

NURSING RESEARCH SEMINAR SERIES Using CTSA Resources for Big Data Research, Scholarship, and Teaching Presented by Connie White Delaney, Ph. D, RN, FAAN, FACMI Bonnie L. Westra, Ph. D, RN, FAAN, FACMI Monday, February 2, 2015 Noon to 1: 00 pm ♦ 4 -130 WDH (Benson Center)

Objectives • Connect Clinical and Translational Science Award (CTSA) resources to facilitate your teaching

Objectives • Connect Clinical and Translational Science Award (CTSA) resources to facilitate your teaching and scholarship • Explore a powerful emerging nursing and other health data set for research and teaching Clinical and Translational Science Institute http: //www. ctsi. umn. edu/

Rank order the top 3 words Estimate how many times were words repeated in

Rank order the top 3 words Estimate how many times were words repeated in the CTSA RFA? • • • Stakeholder Innovation Collaboration Engage/Engagement Enterprise Integrate/Integration

… Answer … • • • Stakeholder - 10 Innovation - 40 Collaboration -

… Answer … • • • Stakeholder - 10 Innovation - 40 Collaboration - 14 Engage/Engagement - 43 Enterprise - 9 Integrate/Integration - 35

Intro/Exposu re to Research Foundational Training in Research Training Award Preparedness Career Development in

Intro/Exposu re to Research Foundational Training in Research Training Award Preparedness Career Development in Research URP ARP Pre-K ARP TRDP TL 1 KL 2 Pathways to Independence Career Establishme nt K to R 01 SUCCESS The CTSI Research Supported Pipeline

Informatics meeting your needs for data, resources, and collaborators Services Tools • • •

Informatics meeting your needs for data, resources, and collaborators Services Tools • • • CTMS [email protected] Research. Match Redcap Analytical tools Natural Language Processing MN Supercomputer Institute (MSI) Tunnel In process: • Genotype/phenotype mapping • • Informatics Consulting Service AHC IS CTSI Portal Front Door Data • AHC IE Clinical Data Repository • i 2 b 2 cohort-discovery tool • MN Death Index In process: • Dental EHR • Imaging; Center for Magnetic Resonance Research (CMRR); clinical images • UMN Biospecimen Enterprise Storage initiative & data: Enterprise storage initiative, Bio. Medical Genomics Center Community • Greater Plains Collaborative (PCORI) • Hennepin County Medical Center (NSF grant) • CTSA Collaborations Education Researchers & Users • Generalist • Specialist Informaticians • IHI – MHI, MS and Ph. D • SON – DNP-NI, Ph. D-NI • SPH – MPH-Informatics • UMII Biomedical Informatics & Computational Biology Graduate degrees

Informatics meeting your needs for data, resources, and collaborators Services Tools • • •

Informatics meeting your needs for data, resources, and collaborators Services Tools • • • CTMS [email protected] Research. Match Redcap Analytical tools Natural Language Processing MN Supercomputer Institute (MSI) Tunnel In process: • Genotype/phenotype mapping • • Informatics Consulting Service AHC IS CTSI Portal Front Door Data • AHC IE Clinical Data Repository • i 2 b 2 cohort-discovery tool • MN Death Index In process: • Dental EHR • Imaging; Center for Magnetic Resonance Research (CMRR); clinical images • UMN Biospecimen Enterprise Storage initiative & data: Enterprise storage initiative, Bio. Medical Genomics Center Community • Greater Plains Collaborative (PCORI) • Hennepin County Medical Center (NSF grant) • CTSA Collaborations Education Researchers & Users • Generalist • Specialist Informaticians • IHI – MHI, MS and Ph. D • SON – DNP-NI, Ph. D-NI • SPH – MPH-Informatics • UMII Biomedical Informatics & Computational Biology Graduate degrees

Our Infrastructure capacity for big data • Minnesota Super Computer Institute (MSI) • Access

Our Infrastructure capacity for big data • Minnesota Super Computer Institute (MSI) • Access to supercomputers that meet high-performance computing needs for advanced computation and scientific visualization • Minnesota Population Center • • Access to U. S. census data back to 1790 for the U. S. , as well as data from 75 other countries Technical expertise to support strong empirical orientation for large-scale data analysis, geospatial analysis, and policy-relevant research • Optum Labs partnership

Inter-CTSA collaborations • Greater Plains Collaborative (10 sites) for the Patient-Centered Outcomes Research Institute

Inter-CTSA collaborations • Greater Plains Collaborative (10 sites) for the Patient-Centered Outcomes Research Institute (PCORI) award – Leader in applying and sharing LOINC mappings for Labs – Developed a common data model for demographic data – First site to get Pop. Med. Net client installed and functioning; the tool allows multiple sites to submit and receive queries • NCATS Accrual to Clinical Trials – NCATS ACT leverages i 2 b 2 across 13 CTSA sites – Our governance model is driving the ACT model

Inter-CTSA collaborations • Midwest Area Research Consortium for Health (MARCH) – Established multi-site IRB

Inter-CTSA collaborations • Midwest Area Research Consortium for Health (MARCH) – Established multi-site IRB agreement – MARCH leverages i 2 b 2 • UMN/Mayo CTSA – UMN is a national leader on extended clinical data space – Sharing experience and expertise in SHRINE and i 2 b 2 with Mayo

Our partnerships • Minnesota Department of Health • • E-Health: Public-private collaborative that aims

Our partnerships • Minnesota Department of Health • • E-Health: Public-private collaborative that aims to accelerate the adoption and use of health information technology Death Index: Key researcher resource that offers improved data quality, and is updated weekly • National Center for Interprofessional Practice and Education • Data from the nation’s only coordinating center is part of the Academic Health Center Information Exchange

Providing support throughout the research tools & process Front Door Experts@ Minnesota Research. Match

Providing support throughout the research tools & process Front Door [email protected] Minnesota Research. Match i 2 b 2 cohort- REDcap Clinical Data Repository Biospecimen repository NLP discovery tool Define question Analytical Tools (JMP, R, SAS, SPSS) Participants & logistics Collect data Findings On. Core Clinical Trials Management System Informatics Consulting Service Standards Knowledge representation Data cleaning Share and output Translate

How BMI adds value and meets researchers needs for data, resources, and collaborators Services

How BMI adds value and meets researchers needs for data, resources, and collaborators Services Tools • • • CTMS [email protected] Research. Match Redcap Analytical tools Natural Language Processing MN Supercomputer Institute (MSI) Tunnel In process: • Genotype/phenotype mapping • • Informatics Consulting Service AHC IS CTSI Portal Front Door Data • AHC IE Clinical Data Repository • i 2 b 2 cohort-discovery tool • MN Death Index In process: • Dental EHR • Imaging; Center for Magnetic Resonance Research (CMRR); clinical images • UMN Biospecimen Enterprise Storage initiative & data: Enterprise storage initiative, Bio. Medical Genomics Center Community • Greater Plains Collaborative (PCORI) • Hennepin County Medical Center (NSF grant) • CTSA Collaborations Education Researchers & Users • Generalist • Specialist Informaticians • IHI – MHI, MS and Ph. D • SON – DNP-NI, Ph. D-NI • SPH – MPH-Informatics • UMII Biomedical Informatics & Computational Biology Graduate degrees

IMPORTANCE AND AVAILABILITY OF DATA FOR RESEARCH AND TEACHING Bonnie L. Westra, Ph. D,

IMPORTANCE AND AVAILABILITY OF DATA FOR RESEARCH AND TEACHING Bonnie L. Westra, Ph. D, RN, FAAN, FACMI

Use of Clinical Data Sets • Facilitate cross-study comparison of results • Enable aggregation

Use of Clinical Data Sets • Facilitate cross-study comparison of results • Enable aggregation of data from multiple studies / sources – greater statistical power, detect weaker signals • Speed study start up by selecting from existing data • Improve replication and reproducibility • Find patients for recruitment into studies

U of Minnesota AHC Information Exchange (AHC IE) cwd 2012

U of Minnesota AHC Information Exchange (AHC IE) cwd 2012

University of Minnesota AHC IE Platform 2. 3 M Patients UMN CDR - Rows

University of Minnesota AHC IE Platform 2. 3 M Patients UMN CDR - Rows of data 2, 263, 847 26, 068, 675 18, 478, 842 5. 6 Billion lines of 65, 597, 327 46, 367, 516 data 439, 081, 234 8 hospitals and 40+ 785, 879, 618 clinical settings 368, 473, 934 Reference Accounts / Coverage Medications Procedures and Labs 397, 546, 666 Diagnosis Flowsheets 88, 364, 370 Encounter Chart Patient Chart Flowsheets 1, 939, 232, 775 Episodes Notes 1, 402, 423, 830 Patient Interventions 59, 924, 418

Flowsheet Example - Falls

Flowsheet Example - Falls

Flowsheet Data • Nursing and interprofessional – OT, PT, ST, Nutrition, SW • Collected

Flowsheet Data • Nursing and interprofessional – OT, PT, ST, Nutrition, SW • Collected across settings – varies in use – ED, Clinic, Hospital, Rehab – Hospital – ICU, Peds, NICU, OB, Adult (generic)

Initial Framework Flowsheet Data

Initial Framework Flowsheet Data

Example Respiratory Data

Example Respiratory Data

Example Skin/ Pressure Ulcers

Example Skin/ Pressure Ulcers

EXAMPLES RESEARCH QUESTIONS TEACHING STRATEGIES

EXAMPLES RESEARCH QUESTIONS TEACHING STRATEGIES

AHC-IE Services/ Resources • • • Access to data – identified/ deidentified Linking AHC-IE

AHC-IE Services/ Resources • • • Access to data – identified/ deidentified Linking AHC-IE data to other data sets De-identification of data Data storage Access to data analytic tools • SAS, SPSS, Stata, R and Rstudio, Mat. Lab, Microsoft Office, JMP Pro, Epi. Info

Sepsis & Diabetes • Evaluate whether use of EBP guidelines make a difference in

Sepsis & Diabetes • Evaluate whether use of EBP guidelines make a difference in development of complications • Discover new interventions which lead to improvement in outcomes and add to EBP guidelines • Determine if there are differences in use of EBP guidelines and outcomes for health disparities • HCMC Epic data – mapping data based on FHS data in AHC-IE • Data storage/ analytic tools • Interprofessional team – Faculty & Students • Computer Science - Michael Steinbach, Vipin Kumar, Pranjul Yadav, Andrew Hangsleben, Sanjoy Dey, Katherine Hauwiller, Kevin Schiroo – School of Nursing - Bonnie L. Westra, Connie W. Delaney, Lisiane Pruinelli – Institute for Health Informatics - György J. Simon

Predictive Models for CAUTI • Jung In Park, Ph. D-C • Requesting AHC-IE services

Predictive Models for CAUTI • Jung In Park, Ph. D-C • Requesting AHC-IE services – EHR data from the UMN-TIDE and add in UMMC’s NDNQI Data – De-identify MRN after matching CAUTI to hospitalizations – Link unit level nurse staff characteristics to patients with CAUTI i. e. education, experience – Data storage and use analytic tools

Predictors Liver Transplant Survival • Lisiane Pruinelli, Ph. D Student • Transplant Information System

Predictors Liver Transplant Survival • Lisiane Pruinelli, Ph. D Student • Transplant Information System • Requesting AHC-IE services – Use of secure workbench - assures data remain secure – Potentially de-identify dates (date shifting) – Access to analytic tools

Unanticipated ICU Admissions After Surgery • Jessica Peterson, Ph. D Student • Examine anesthesia

Unanticipated ICU Admissions After Surgery • Jessica Peterson, Ph. D Student • Examine anesthesia variables and patient characteristics that predict unanticipated admission to ICUs • AHC-IE Services – Exploring availability of data from UMN TIDE – Data storage – Use of analytic tools in secure workbench

Teaching Preparation of EHR Data for Research • Participating in a CTSA pilot project

Teaching Preparation of EHR Data for Research • Participating in a CTSA pilot project (Lisa Pulkrabek, DNP Student) • Assisting with mapping flowsheets to concepts in a clinical data model • Learning how to apply national data standards for comparing data across CTSA sites

Discussion – Your Use of CTSI Resources • Potential courses – Evidence-based practice –

Discussion – Your Use of CTSI Resources • Potential courses – Evidence-based practice – Quality improvement – Research – Specialty courses – data projects i. e. gero, psych, etc. • Your research topic and potential use of data and other CTSI resources

Find Information on Data Access z. umn. edu/clinicaldata

Find Information on Data Access z. umn. edu/clinicaldata

Data Set Access

Data Set Access

NURSING RESEARCH SEMINAR SERIES Using CTSA Resources for Big Data Research, Scholarship, and Teaching

NURSING RESEARCH SEMINAR SERIES Using CTSA Resources for Big Data Research, Scholarship, and Teaching Presented by Connie White Delaney, Ph. D, RN, FAAN, FACMI Bonnie L. Westra, Ph. D, RN, FAAN, FACMI Thank you