Building a Comprehensive Health History Build a health history for a 55-year-old Asian female living in a high-density public housing complex – Introduction of the paper, then explain 1. How would your communication and interview techniques for building a health history differ with each patient? 2. How might you target your questions for building a health history based on the patient’s social determinants of health? 3. What risk assessment instruments would be appropriate to use with the patient, or what questions would you ask the patient to assess his or her health risks? 4. Identify any potential health-related risks based upon the patient’s age, gender, ethnicity, or environmental setting that should be taken into consideration. 5. Select one of the risk assessment instruments presented in Chapter 1 or Chapter 5 of the Seidel's Guide to Physical Examination text, or another tool with which you are familiar, related to your selected patient. 6. Develop at least eight targeted questions you would ask the selected patient to assess his or her health risks and begin building a health history. Resources Ball, J. W., Dains, J. E., Flynn, J. A., Solomon, B. S., & Stewart, R. W. (2019). Seidel's guide to physical examination: An interprofessional approach (9th ed.). St. Louis, MO: Elsevier Mosby. · Chapter 1, “The History and Interviewing Process”  · Chapter 5, “Recording Information” provides methods for maintaining clear and accurate records, also explore the legal aspects of patient records. Sullivan, D. D. (2019). Guide to clinical documentation (3rd ed.). Philadelphia, PA: F. A. Davis. · Chapter 2, "The Comprehensive History and Physical Exam" (pp. 19–29) R Ryanne, W., & Lori A, O. (2015). Implementation of health risk assessments with family health history: barriers and benefits. Postgraduate Medical Journal, 1079, 508. Lushniak, B. D. (2015). Surgeon general’s perspectives: family health history: using the past to improve future health. Public Health Reports, 1, 3. Jardim, T. V., Sousa, A. L. L., Povoa, T. I. R., Barroso, W. K. S., Chinem, B., Jardim, L., Bernardes, R., Coca, A., & Jardim, P. C. B. V. (2015). The natural history of cardiovascular risk factors in health professionals: 20-year follow-up. BMC Public Health, 15, 1111.  ITS 832 Chapter 5 From Building a Model to Adaptive Robust Decision Making Using Systems Modeling InformationTechnology in a Global Economy Professor Miguel Buleje Introduction • Modeling & Simulation • Fields that develops and applies computational methods to address complex system • Addresses problems related to complex issues • Focus on decision making abilities • Opportunities to leverage interdisciplinary approach, and learn across fields to understand complex systems. • Legacy System Dynamics (SD) modeling and others methods are presented • Recent innovations • What the future holds • Examples Systems Modeling • Dynamic complexity • Behavior evolves over time • Mode.

1. Building a Comprehensive Health History
Build a health history for a 55-year-old Asian female living in a
high-density public housing complex –
Introduction of the paper, then explain
1. How would your communication and interview techniques for
building a health history differ with each patient?
2. How might you target your questions for building a health
history based on the patient’s social determinants of health?
3. What risk assessment instruments would be appropriate to use
with the patient, or what questions would you ask the patient to
assess his or her health risks?
4. Identify any potential health-related risks based upon the
patient’s age, gender, ethnicity, or environmental setting that
should be taken into consideration.
5. Select one of the risk assessment instruments presented in
Chapter 1 or Chapter 5 of the Seidel's Guide to Physical
Examination text, or another tool with which you are familiar,
related to your selected patient.
6. Develop at least eight targeted questions you would ask the
selected patient to assess his or her health risks and begin
building a health history.
Resources
Ball, J. W., Dains, J. E., Flynn, J. A., Solomon, B. S., &
Stewart, R. W. (2019). Seidel's guide to physical examination:
An interprofessional approach (9th ed.). St. Louis, MO: Elsevier
Mosby.

2. · Chapter 1, “The History and Interviewing Process”
· Chapter 5, “Recording Information” provides methods for
maintaining clear and accurate records, also explore the legal
aspects of patient records.
Sullivan, D. D. (2019). Guide to clinical documentation (3rd
ed.). Philadelphia, PA: F. A. Davis.
· Chapter 2, "The Comprehensive History and Physical Exam"
(pp. 19–29)
R Ryanne, W., & Lori A, O. (2015). Implementation of health
risk assessments with family health history: barriers and
benefits. Postgraduate Medical Journal, 1079, 508.
Lushniak, B. D. (2015). Surgeon general’s perspectives: family
health history: using the past to improve future health. Public
Health Reports, 1, 3.
Jardim, T. V., Sousa, A. L. L., Povoa, T. I. R., Barroso, W. K.
S., Chinem, B., Jardim, L., Bernardes, R., Coca, A., & Jardim,
P. C. B. V. (2015). The natural history of cardiovascular risk
factors in health professionals: 20-year follow-up. BMC Public
Health, 15, 1111.
ITS 832
Chapter 5
From Building a Model to Adaptive Robust
Decision Making Using Systems Modeling
InformationTechnology in a Global Economy
Professor Miguel Buleje
Introduction
• Modeling & Simulation

3. • Fields that develops and applies computational methods to
address complex system
• Addresses problems related to complex issues
• Focus on decision making abilities
• Opportunities to leverage interdisciplinary approach, and learn
across fields to understand complex systems.
• Legacy System Dynamics (SD) modeling and others
methods are presented
• Recent innovations
• What the future holds
• Examples
Systems Modeling
• Dynamic complexity
• Behavior evolves over time
• Modeling Methods
• System Dynamics (CD)
• Discrete Event Simulation (DES)
• Multi-actor Systems Modeling (MAS)
• Agent-based Modeling (ABM)
• Complex Adaptive Systems Modeling (CAS)
• Enhanced computing supports model based decision making
• Modeling and simulation has become interdisciplinary

4. • Operation research, policy analysis, data analytics, machine
learning,
computer science
Legacy System Dynamics Modeling
• 1950’s – Jay W. Forrester
• Primary characteristics
• Method to model complex systems or issues
• Feedback effects – dependent on their own past
• Accumulation effects – building up intangibles/ mental or
other
states for a complete model.
• Behavior of a system is explained
• Casual theory – model generates dynamic behavior
• Works well when:
• Complex system responds to feedback and accumulation
Recent Innovations
• Detailed list of individual innovations
• Deep uncertainty
• Analysts do not know or cannot agree on
• Model

5. • Probability distributions of key features
• Value of alternative outcomes
• Two primary evolutions:
• Smarter methods (Data Science)
• Usability/accessibility advances
What the Future Holds
• Better models, as a result of technology innovation
• More data (“Big Data”)
• Social media
• Advanced capabilities for:
• Hybrid Modeling: mixing and matching models.
• Simultaneous Modeling
• Modeling multiple models or uncertainty
• Adopting all recent innovations and opportunities would bring
the
future state in Modeling and Simulation, as presented in Fig. 5.1
Modeling and Simulation

6. Examples
• Assessing the Risk, and Monitoring, of New Infectious
Diseases
• Simple systems model with deep uncertainty
• Integrated Risk-Capability Analysis Under Deep
Uncertainty
• System-of-systems approach
• Policing Under Deep Uncertainty
• Smart model-based decision support system
Summary
• Modeling has long been used with complex systems
and issues / simulation.
• Recent evolutions have advanced modeling
• Increase computing power
• Social media and Big data
• Sophisticated analytics
• Multi-method and hybrid approaches are now feasible
• Continued move into interdisciplinary study
• Advanced modeling for complex systems
• Operation research, policy analysis, data analytics, machine

7. learning, computer science