This document discusses occupational health and safety management systems and high-performance work systems. It defines biomedical and health informatics, public health informatics, visual analytics, and geovisualization. It presents the University of Illinois Health system's current paper-based occupational health workflow and its proposed electronic, data-driven workflow using Qualtrics, ESRI, IBM SPSS, and Cerner software. It demonstrates predictive analytics on employee health reports to provide real-time metrics and optimize decisions using geographic information systems.

1. Advancing
Occupational Safety &
Health Management
System
High-Performance
Work Systems in
Occupational Health
Management

2. Arash Jalali, MPH, MSHI
Christopher M Bell,
MSHI, CAPM, CHTS-IM

3. UI Health Introduction
Define Biomedical and Health
Informatics & Geovisualization
UHS Current System Workflow
UHS Proposed System Workflow
UHS Predictive Analytics Demo

4. – 495-bed hospital
– Outpatient Care Clinic
– Numerous Specialty Clinics
– Seven Health Science
Colleges

5. University of Illinois Mission
• Deliver personalized health in pursuit of
the elimination of racial and ethnic
health disparities
• Train professionals in a wide range of
public service disciplines serving Illinois
as the principal educator of health-
science professionals and as a major
health-care provider to the underserved

6. “Develop an information technology and
informatics capability to enable real-time
situational awareness regarding progress toward
Workforce Health Protection Strategy
Development. That includes improved
communication and information sharing among
health, safety, and medical activities, fostering a
more cohesive environment for workforce health
protection to support mission readiness” (IOM,
2014)
IOM (Institute of Medicine). 2014. Advancing workforce health at the Department of Homeland Security:
Protecting those who protect us. Washington, DC: The National Academies Press.

7. Fundamental Theorem of Biomedical Informatics

8. Friedman, C. P. (2009). A “fundamental theorem” of biomedical informatics. Journal of the American Medical Informatics Association, 16(2), 169-170.
Friedman, C. P. (2012). What informatics is and isn't. Journal of the American Medical Informatics Association, amiajnl-2012.
Hunter, J. S. (2010). Letters: Enhancing Friedman's “Fundamental Theorem of Biomedical Informatics”. Journal of the American Medical Informatics Association:
JAMIA, 17(1), 112.
Fundamental Theorem of Biomedical Informatics
1. Informatics is more about people than
technology
2. In order for the theorem to hold, the
resource must offer something that the
person does not already know
3. Whether the theorem holds depends on
an interaction between person and
resource, the results of which cannot be
predicted in advance
“Fundamental Theorem is accompanied
by three corollaries:
Scientific method: the cycle of conjecture or hypothesis, experiment, data, analysis,
and thence to new conjecture persists within fundamental theorem.”

9. Friedman, C. P. (2012). What informatics is and isn't. Journal of the American Medical Informatics Association, amiajnl-2012.
Informatics isn't:
“Scientists or clinicians tinkering with computers: ‘Tinkerers’ are wonderful and
the world needs them. They have terrific ideas, but typically, because ‘tinkerers’
lack formal training in the basic informational sciences, what they develop is not
scalable or usable by anyone other than the developer him/herself.
Analysis of large datasets per se: It has been said that all epidemiologists are
informaticians because they carry out statistical analyses using information
technology. Epidemiologists and others who perform large-scale analytics do
vital research essential to public health, but they use information technology
strictly as a tool.”
(Friedman, 2012)

10. Friedman, C. P. (2012). What informatics is and isn't. Journal of the American Medical Informatics Association, amiajnl-2012.
Informatics isn't:
“Circumscribed roles related to deployment and configuration of electronic
health records in pursuit of meaningful use: The workforce education program
developed through the Office of the National Coordinator for Health IT
envisioned 12 health IT workforce roles. Most of these roles—for example,
configuration or technical support specialists—operate exclusively at one level
of the ‘tower of achievement’ and, as such, do not meet the criteria advanced
here to allow the label informatics to be attached to them.” (Friedman, 2012)

11. Friedman, C. P. (2012). What informatics is and isn't. Journal of the American Medical Informatics Association, amiajnl-2012.
Informatics isn't:
“The profession of health information management: This important profession
evolved from the profession of medical records management. It is a profession,
in and of itself, with its own culture. Rank and file health information
management professionals are informed users of technology but not
scientifically-trained developers or explorers of its consequences. It follows that
educational programs preparing students for careers as health information
management professionals are not educational programs in informatics.
Anything done using a computer: This increasingly frequent misuse of
informatics almost requires no elaboration. It reflects the same fundamental
confusion between a tool and a field of human endeavor.” (Friedman, 2012)

12. Biomedical and health informatics (BMHI)

13. "Biomedical and health informatics
(BMHI) is the science of using data and
information, often aided by technology, to
improve individual health, health care,
public health, and biomedical research."
(Hersh, 2009)
Hersh, W. (2009). A stimulus to define informatics and health information technology. BMC Medical
Informatics and Decision Making, 9(1), 24.

14. Hersh, W. (2009). A stimulus to define informatics and health information technology. BMC Medical
Informatics and Decision Making, 9(1), 24.

15. Public Health Informatics

16. “Public health informatics differs from other informatics specialties in
that it involves:
1. The focus of public health informatics is on applications of
information science and technology that promote the health of
populations as opposed to the health of specific individuals.
2. A focus on disease prevention, rather than treatment;
• Public health informatics is on applications of informatics
science and technology that prevent disease and injury by
altering the conditions or the environment that put
populations of individuals at risk.”
(Magnuson & O’Carroll, 2014)
Source: Magnuson, J. A., & Fu, P. C. (2014). Public Health Informatics and Information Systems. Springer London. URL:
http://link.springer.com/book/10.1007/978-1-4471-4237-9

17. 3. “A focus on preventive intervention at all vulnerable points
in the causal chains leading to disease, injury, or disability.
• Public health informatics applications explore the
potential for prevention at all vulnerable points in the
causal chains leading to disease, injury, or disability;
applications are not restricted to particular social,
behavioral, or environmental contexts.”
(Magnuson & O’Carroll, 2014)
Source: Magnuson, J. A., & Fu, P. C. (2014). Public Health Informatics and Information Systems. Springer London. URL:
http://link.springer.com/book/10.1007/978-1-4471-4237-9

18. 4. “Operation typically within a governmental, rather than a
private, context.
• As a discipline, public health informatics reflects the
governmental context in which public health is
practiced. Much of public health operates through
government agencies that require direct responsiveness
to legislative, regulatory, and policy directives; careful
balancing of competing priorities; and open disclosure
of all activities.”
(Magnuson & O’Carroll, 2014)
Source: Magnuson, J. A., & Fu, P. C. (2014). Public Health Informatics and Information Systems. Springer London. URL:
http://link.springer.com/book/10.1007/978-1-4471-4237-9

19. Visual Analytics & Geovisualization

20. Visual analytics
“Visual analytics is the science of analytical reasoning facilitated by
interactive visual interfaces. People use visual analytics tools and
techniques to synthesize information and derive insight from
massive, dynamic, ambiguous, and often conflicting data; detect
the expected and discover the unexpected; provide timely,
defensible, and understandable assessments; and communicate
assessment effectively for action.”
(James & Cook, 2005)
Source: Thomas, James J., and Kristin A. Cook, eds. Illuminating the path: The research and development agenda for visual analytics.
IEEE Computer Society Press, 2005. http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf

21. Visual analytics
“Visual analytics is a multidisciplinary field that includes the following focus areas:
• Analytical reasoning techniques that enable users to obtain deep insights that
directly support assessment, planning, and decision making
• Visual representations and interaction techniques that take advantage of the
human eye’s broad bandwidth pathway into the mind to allow users to see,
explore, and understand large amounts of information at once.”
(James & Cook, 2005)
Source: Thomas, James J., and Kristin A. Cook, eds. Illuminating the path: The research and development agenda for visual analytics.
IEEE Computer Society Press, 2005. http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf

22. Visual analytics
• “Data representations and transformations that convert all types of conflicting
and dynamic data in ways that support visualization and analysis
• Techniques to support production, presentation, and dissemination of the results
of an analysis to communicate information in the appropriate context to a variety
of audiences.”
(James & Cook, 2005)
Source: Thomas, James J., and Kristin A. Cook, eds. Illuminating the path: The research and development agenda for visual analytics.
IEEE Computer Society Press, 2005. http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf

23. Geovisualization
“Geovisualization, or geographic visualization, is an approach and a process through
which maps and graphics are used to gain insight from geographic information. An
emerging field within geographic information science, it focuses on using dynamic
and interactive graphics to generate ideas from digital data sets but is loosely
bounded due to the multitude of disciplines that contribute to this aim and uses to
which such activity can be put. Geovisualization embraces a whole range of exciting,
impressive, novel, and sometimes bizarre graphics to try and help those involved in
data analysis “see into” their data.”
(Kemp, 2008)
Source: Kemp, K. (Ed.). (2008). Encyclopedia of geographic information science. Sage.

24. Public Health
Geovisualization

25. Health Data Geovisualization
Source: NorthShore University HealthSystem (2014). Syndromic Surveillance Across the NorthShore Population.
URL: http://fad.northshore.org/wga/WGAPublic.aspx

26. Health Data Geovisualization
Source: NorthShore University HealthSystem (2014). Syndromic Surveillance Across the NorthShore Population.
URL: http://fad.northshore.org/wga/WGAPublic.aspx

27. Health Data Geovisualization
Source: Chicago Health Atlas (2014). Browse by neighborhood. URL: http://www.chicagohealthatlas.org/

28. Health Data Geovisualization
Source: Chicago Health Atlas (2014). Browse by neighborhood. URL: http://www.chicagohealthatlas.org/

29. Epi Info™

30. “Epi Info™ is a data collection, management, analysis, visualization, and
reporting software for public health professionals. It is used worldwide
for the rapid assessment of disease outbreaks; for the development of
small to mid-sized disease surveillance systems; as ad hoc components
integrated with other large scale or enterprise-wide public health
information systems; and in the continuous education of public health
professionals learning the science of epidemiology, tools, and
techniques.
Epi Info™ is a trademark of the Centers for Disease Control and
Prevention (CDC). The software is in the public domain and freely
available for use, copying translation and distribution.”
(CDC, 2014)
Source: CDC (2014). What is Epi Info URL: http://wwwn.cdc.gov/epiinfo/

33. Smarter Public Health
Prevention System (SPHPS)

34. Source: Chen, B. (2014). Simplifying the Bull: How Picasso Helps to Teach Apple’s Style: Inside Apple’s Internal Training Program.
URL: http://www.nytimes.com/2014/08/11/technology/-inside-apples-internal-training-program-.html

35. Create
Forms
• Data
CollectionEnter Data
• Data Analysis &
Spatial Analytics
Analyze
Data
• Geo-Visualization: Dynamic
Mapping & Visualization
Create
Maps

36. • Mobile Survey
(Qualtrics)
Create Forms
/ Enter Data
• Data Analysis & Spatial Analytics
(IBM SPSS & ESRI ArcGIS)
Analyze Data
• Geo-Visualization: Dynamic
Mapping & Visualization (ESRI
ArcGIS)
Create Maps

37. Jalali, A., Olabode, O. A., & Bell, C. M. (2012). Leveraging Cloud Computing to Address Public Health Disparities: An Analysis of the SPHPS. Online journal of
public health informatics, 4(3).
The Smarter Public Health
Prevention System (SPHPS) will
securely incorporate population
centric view and patient centric
view to form a cloud-knowledge
discovery environment to drive
knowledge based decisions.

38. Jalali, A., Olabode, O. A., & Bell, C. M. (2012). Leveraging Cloud Computing to Address Public Health Disparities: An Analysis of the SPHPS. Online journal of
public health informatics, 4(3).
The Smarter Public Health
Prevention System (SPHPS) theory
proposes that the gravitational
force between two objects,
Population Health and Patient-
Centered Care, is Workforce
Health Protection or Occupational
Health.

39. Integrated Employee Health System:
“An infrastructure that would support all health system
employee health activities; provide a way to link
information about all aspects of the health of
employees; and make this information available to
leadership at all levels for the purposes of decision
making, accountability, continuous improvement,
surveillance, and other questions related to health.”
(IOM, 2014)
IOM (Institute of Medicine). 2014. Advancing workforce health at the Department of Homeland Security:
Protecting those who protect us. Washington, DC: The National Academies Press.

40. UHS Current System Workflow
UHS Proposed System Workflow
UHS Predictive Analytics Demo

41. Current System
Workflow:
“Paper
Persistence”
Harrison, M. I., Koppel, R., & Bar-Lev, S. (2007). Unintended
consequences of information technologies in health care—
an interactive sociotechnical analysis. Journal of the
American Medical Informatics Association, 14(5), 542-549.

42. Last updated in 2011
Report submission
is unsecure via email
Need to print,
complete, sign, scan . .
Data captured through first report of
injury/illness form is via a paper-based
sources.

43. Proposed System
Workflow:
Data-Driven Decision-
Making

44. Centers for Disease Control and Prevention. CDC’s Vision for Public Health Surveillance in the 21st
Century. MMWR 2012;61(Suppl; July 27, 2012): 1-42
Public Health Surveillance in The Larger Context of Health Knowledge

45. Tolentino, H. (2012). Problem Solving Framework for Public Health Informatics. American Medical
Informatics Association Annual Symposium, Panel Discussion, Date of Presentation: November 7, 201
Plan
Capture
Manage
Analyze
Use
Evaluate
• Storage/Retrieval
• Transformation
• Exchange
• Protection
• Integration
• Visualization
• Classification
• Aggregation, linkage
• Knowledge representation
• Organizational context
• Information needs
• Change management issues
• Resources (financing, workforce)
• Information systems architecture
• Capture Methods
• Data Types & Formats
• Data Standards
• Data Quality
• Process
• Outputs
• Outcomes
• Impact
Information
Value Cycle
DATA
INFORMATIONKNOWLEDGE
ACTION
Adapted from Taylor, R. S. (1982). Value-added
processes in the information life cycle. Journal of
the American Society for Information Science, 33,
341-346.

46. Improving our informatics capabilities "enables evidence-based decision making,
surveillance, accountability, and continuous quality improvement" (IOM, 2014)
IOM (Institute of Medicine). 2014. Advancing workforce health at the Department of Homeland Security: Protecting
those who protect us. Washington, DC: The National Academies Press.
Qualtrics "is high risk
data, such as HIPAA,
compliant, thus the
data is secure."
Electronic data capture
For first report of
injury/illness report
via Qualtrics
Perform predictive analytics
on UIC hosted servers
Operational Dashboard
Provide real-time health
performance metrics to
leadership via visual analytics

47. Electronic data capture
For first report of
injury/illness report
via Qualtrics
Performing predictive analytics
ESRI Operational Dashboard
Provide real-time health
performance metrics to
leadership via visual analytics
IBM SPSS Modeler
Cerner PowerInsight
Enterprise Data Warehouse
Enterprise Data Delivery
Information Environment (EDDIE)
Cerner - Integrated Employee Health System

48. Predictive Analytics (Text
Analytics) Demo:
Improved Employee
Health Outcomes &
Optimize Decisions
Making with GIS
(Geographic Information
Systems)

49. Mapping Total Reported Injury
Without Data Preparation

50. IBM SPSS Modeler Text Analytics 16 Data
Preparation (Example Stream)

51. IBM SPSS Modeler Text Analytics 16
(Key Concepts for Injury Into Five
Categories)

52. 2013- Measuring Geographic
Distribution (Mean Center)

53. 2013- Mapping Clusters (Optimized Hot
Spot Analysis)

54. Mapping Total Reported Injury Counts -
2013

57. “mere collection of data is not enough; the
data must be aggregated, analyzed, and
used to monitor the effects of
the program and enable continuous
improvement” (IOM, 2014)
IOM (Institute of Medicine). 2014. Advancing workforce health at the Department of Homeland Security: Protecting
those who protect us. Washington, DC: The National Academies Press.

58. Garman, A. N., McAlearney, A. S., Harrison, M. I., Song, P. H., & McHugh, M. (2011). High-performance work systems in health care management,
Part 1: Development of an evidence-informed model. Health care management review,36(3), 201-213.
Empowering The Frontline
“The effect of team outcomes has
also been documented in several
health care–specific studies. One
study found a significant
association between the level of
team participation and safety
outcome including whether
respondents reported seeing
harmful errors or near-misses or
experienced work-related injuries,
occupational stress.”
(Garman et al., 2011)