Creative Partnerships between PhD Programs and Industry · NIH Research Evaluation and...
Transcript of Creative Partnerships between PhD Programs and Industry · NIH Research Evaluation and...
Creative Partnerships between
PhD Programs and Industry Thomas R. Clancy, PhD, MBA, RN, FAAN
Clinical Professor and Associate Dean, Faculty Practices, Partnerships and Professional Development
School of Nursing, The University of Minnesota
Minneapolis, MN
Objectives
• Define types of academic/industry partnerships.
• Review faculty roles in industry partnerships.
• Identify key considerations in working with industry partners.
• Discuss examples of industry sponsored research and scholarship.
Associate Dean for Practice, Partnerships and
Professional Development
• Health Systems • Hospitals, clinics, sub-acute
• Corporate • Medical Device
• Technology (EHR)
• Commercial Insurance
• Community • Religious (Charities)
• Federal/State/County (HRSA)
• Private
• Foundations • Private
• Corporate
Academic/Industry Partnership
Roles:
• Expert Consultation
• Joint Research
• Continuing Education and Professional Development
• Product/Service Development
Key Considerations
• Research
• Pre-disclosure • IP Disclosure form
• Intellectual Property • Non-disclosure
agreement
• Copyright
• Provisional patent
• Utility patent
• Institutional agreements
• Academic freedom
• Licensing
• Commercialization
Trends in National Institutes
of Health Appropriations
http://faseb.org/Science-Policy-and-Advocacy/Federal-Funding-Data/NIH-Research-Funding-Trends.aspx
NIH Research Evaluation and
Commercialization Hubs (REACH)
• Nine million in funding to develop best practices in translating academic innovations into products to improve health.
• Provides education in industry-style project management to commercialize technologies that are poised to launch.
NIH
REACH
Hubs
University
of
Minnesota
Long Island
Bioscience
Hub
University of
Louisville, Kentucky
Boston
Biomed.
Hub
Cleveland
Clinic Innovation
Accelerator
University of CA
BRAID Center
Academic vs Industry Lenses
Grant Application
• Project Narrative
• Specific Aims
• Need
• Methodological Approach
• Work Plan
• Logic Model
• Evaluation Plan
• Outcome Measures
• Sustainability, Replicability
• Dissemination
Business Plan
• Executive Summary
• Opportunity (product
solution)
• Market Analysis
• Company and
Management (SWOT)
• Strategy and
Implementation Plan
• Financial Plan
Expert Consultation
• Application of domain expertise to a product or service. • Determine ROI of a
hands free communication device
• Integration of new technology into nurses workflow
• Design, pilot and evaluate product or service
• Publish and present
Table 4 Comparison of Event Data
Type of Event
Percent of
Total
Events
Average
Delay
(seconds)
Events per
Surgical
Case
Percent of
Total Events
Average
Delay
(seconds)
Events per
Surgical
Case
Percent Difference
in Average Delay
Pre and Post
Percent Difference in
Events per Surgical
Case Pre and Post
Call placed and answered 42.47% 100 2.28 53.87% 65 1.063 -35.0% -53.38%
Call received and answered 23.49% 100 1.21 13.60% 65 0.268 -35.0% -77.85%
Call placed and message left 8.43% 66 0.5 9.07% 46 0.178 -30.3% -64.40%
Call placed, put on hold or transferred 6.13% 231 0.39 4.80% 108 0.094 -53.2% -75.90%Walked to a phone to answer a call 6.13% 173 0.32 1.33% 89 0.026 -48.6% -91.88%
Physically searched for someone 4.77% 207 0.26 0.27% 135 0.005 -34.8% -98.08%
Checked phone mail 4.51% 100 0.26 4.80% 65 0.0947 -35.0% -63.58%
Call placed, put on hold and left a message 2.55% 197 0.15 8.00% 89 0.157 -54.8% 4.67%
Sent a text message 1.02% 183 0.06 0.80% 53 0.0157 -71.0% -73.83%
Sent broadcast page to multiple staff 0.51% 228 0.03 3.47% 75 0.068 -67.1% 126.67%
Average1
118.71 5.46 68.02 1.97 -46.5% -46.8%
1 The difference in the Average Delay per Surgical Case, pre and post Vocera, are significant at a p< .01.
Sample Size
Pre HFMD 189 cases observed
Post HFMD 190 cases observed
PRE-VOCERA POST-VOCERA
Table 3 Comparison of Cycle Time by Area
Surgical Area
Average Minutes per
Surgical Case
Standard
Deviation
Average Minutes
per Surgical Case
Standard
Deviation
Percent
Difference
t test p
value
Pre-operative 121.81 67.4 112.32 44.88 -7.8% 0.0079
Intra-operative 85.4 81.2 83.9 64.8 -1.8% 0.643
Phase 1 recovery 91.82 46 78.69 30.93 -14.3% 0.00012
Phase 2 recovery 96.33 71.6 95.19 72.95 -1.2% 0.728
Total cycle time (Pre, Intra & Post-operative)1
308.6 162.6 293.0 129.0 -5.0% 0.0001091
1 Total cycle time is a weighted average
Sample size:
Pre HFMD - 2784
Post HFMD - 828
PRE-VOCERA POST VOCERA
1 Place call
6 Receive call
2 Leave phone
3 On hold or transfer
7 Walk to a phone
8 Search
5 Check voice mail
4 Placed on hold
11 Text
9 Broadcast page
SURGERY Pt
Pre-operative AreaOperating Room Phase 1 Recovery
Phase 2 Recovery
message
room to room
0
0
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0
0
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07:00:00
February 1, 2012
Joint Research
Database
UM Nursing Sandbox
Data
Explore
Research Views
• Unified (claims/EHR)
• Death Index
• SES (social/economic)
Team
• Project Mgt
• Domain Ex
• Machine Learn
• Data Dic. Analyst
Data Warehouse
• Project Mgr
• Data Engineer
• Data Dic. Analyst
AHC
• Medicine
• Pharmacy
• Public Health
• Joint academic/corporate partnership to conduct research
• Academic/Industry National Research Collaborative.
• Facilitate ongoing big data research between faculty, industry and grantees
Partners Academic/ Industry Partnership
Sample of Research Studies
Funding
Source
Otolaryngology
Prediction model: causal factors in patients presenting
with dizziness
NIH
Nursing Prediction model: Patients experiencing adverse
effects of statin therapy
UM Internal
Prediction model: Cardiovascular disease risk
prediction using EHR/claims data
UM Internal
AHC Seed
Symptom management of liver transplant patients NIH
Prevention of urinary tract infections in young women NIH
Public Health Prediction model: Diffusion of knowledge from
clinical trials to practice.
NIH
Comparative effectiveness of extended oral
anticoagulant use
PCORI
Contemporary Venous Thromboembolism Treatment -
NIH
NIH
Neurosurgery Comparative effectiveness between surgical and non-
surgical intervention of low back pain.
NIH
Continuing Education and
Professional Development • Advance knowledge
surrounding a specific domain.
• Create continuing education to inform market of new products and services.
• Study on incontinence associated skin damage (IASD)
• Funded study to inform public on the scope of the problem and outcomes of previous research.
License this Technology IASD - Patient Care License $500.00 IASD - Trial License $25.00 IASD - Non-profit Research License $0.00
Product/Service Development
• Collaborate with an industry partner to develop a new product or service. • Faculty/student/industry
collaboration on reducing infections from IV tubing in pediatric oncology patients.
• Validation through research
• Publications and presentations
• Office of Technology Commercialization
• New patent