SlideShare a Scribd company logo
1 of 20
The Culture of Health Care
Health Care Processes and Decision Making
Lecture a
This material (Comp 2 Unit 4) was developed by Oregon Health & Science University, funded by the Department
of Health and Human Services, Office of the National Coordinator for Health Information Technology under
Award Number IU24OC000015. This material was updated in 2016 by Bellevue College under Award
Number 90WT0002.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.
Health Care Processes and
Decision Making
Learning Objectives
• Describe the elements of the “classic paradigm” of the clinical process. (Lecture a)
• List the types of information used by clinicians when they care for patients. (Lecture a)
• Describe the steps required to manage information during the patient-clinician
interaction. (Lectures a, b, c)
• List the different information structures or formats used to organize clinical information.
(Lecture b)
• Describe different paradigms and elements of clinical decision making. (Lectures a, b)
• Explain the differences among observations, findings, syndromes, and diseases.
(Lectures a, b, c)
• Describe techniques or approaches used by clinicians to reach a diagnosis. (Lectures
a, b, c, d, e)
• List the major types of factors that clinicians consider when devising a management
plan for a patient’s condition in addition to the diagnosis and recommended treatment.
(Lecture e)
• Describe the role of EHRs and technology in the clinical decision-making process.
(Lectures a, b, c, d, e)
3
The Classic Paradigm
• Classic paradigm assumes a single patient
interacts with a single clinician
• Patient has a single problem
• Care is provided during a single episode
• Various tools mediate this process
– Medical records
– Computers supporting clinical information systems
– Medical devices and medical diagnostic equipment
– Electronic communication: email, portals
4
Classic Paradigm
Evolution of Tools That Support the Task
• Central theorem of health informatics
– human + computer > human alone
• Classic paradigm in health informatics
– One patient
– One problem
– One clinician
– One visit
• Technology supports this 1:1:1:1 paradigm
5
Attributes of Clinician
• Possesses specialized knowledge
• Received experiential training
• Has direct relationship with patient, directly
involved in the care of the patient and
makes decisions about patient care
• Acts in patient’s best interest
• Integrates diverse types of information
• Functions within time & resource
constraints 6
Types of Information
Information Type
Information
Characteristics
Sources
Patient data Refers to one person
Patient, family, records,
observation
Population statistics
Aggregated patient
data
Colleagues, public health
department, EHR
Medical knowledge
Generalizable to
many persons
Textbooks, journal
articles, MEDLINE
Logistic information
How to get things
done
People, policy,
procedure, and insurance
companies
Social influence
How others get the
job done
Observe and discuss
with colleagues
4.1 Table: Types of information that clinicians utilize when making decisions
7
Organization:
How Clinicians Organize Information
• Narrative structure
• Rearranged into a history and physical
format
• Further rearranged into a hierarchy
• Reformulated into a computable structure
for utilization by clinical information
systems
8
Disease
“Disease often tells its secrets in a
casual parenthesis.”
—Wilfred Trotter
9
How Stories Fit into Health System
Part 1
• Communication between patient and
clinician
– Facts embedded in story (meaning to
clinician)
– Meaning of the illness to the patient
– Communication and relationship building
– Therapeutic value
– Important aspect of quality of care
10
How Stories Fit into Health System
Part 2
• Among clinicians
– Efficient communication among experts
– Values and ethics are communicated through
stories
• How do modern healthcare systems (and
health IT) affect stories?
– Eliminate or alter them
– Lose context
11
Interpretation:
How Clinicians Understand Clinical Data
• Disciplinary differences
• Different approaches to clinical data
interpretation
• Development of social construction
• Contextual interpretation of data
12
Beyond the Classic Paradigm:
Collaboration in Surgery
Medical
Situations
Patients Problems Clinicians Visits
Classic
paradigm
1 1 1 1
Operating room 1 1 Many 1
4.2 Table: Comparison of classic paradigm with operating room
• Multiple disciplines with different roles and
tasks
• Short time horizon
• Requires advance planning, resource rich
13
Beyond the Classic Paradigm:
Uncertain, Complex, High Stakes
Medical
Situations
Patients Problems Clinicians Visits
Classic
paradigm
1 1 1 1
Operating room 1 1 Many 1
Acute complex
illness
1 Many Many 1 or more
4.3 Table: Comparison of classic paradigm with operating room and acute complex illness
• Complex acute illness—multiple disciplines,
roles, tasks
• Short time horizon, unplanned events,
uncertain data
14
Beyond the Classic Paradigm:
Uncertain, Complex, High Stakes Continued
Medical
Situations
Patients Problems Clinicians Visits
Classic
paradigm
1 1 1 1
Operating room 1 1 Many 1
Acute complex
illness
1 Many Many 1 or more
Emergency dept Many Many Many 1
4.4 Table: Comparison of classic paradigm with operating room, acute complex illness, and emergency department
• Simultaneous care of multiple acute and non-
acute—very short time horizon
• Planning for the unexpected, resources are often
constrained
• Coordination, cooperation, collaboration 15
Steps in the Classic Process
• What is the
matter?
– Diagnosis
• What can be
done?
– Treatment
• What will happen?
– Prognosis
• Gathering data
• Analyzing findings
• Making a diagnosis
• Choosing
treatment
• Communicating the
plan
16
Health Care Processes and
Decision Making
Summary – Lecture a
• Looked at types of information that
clinicians use in the course of managing
patients
• Defined the role and nature of a clinician
• Examined the classic paradigm of the
clinical process and also looked at some
alternate paradigms
• Correlated patient questions with
diagnostic process 17
Health Care Processes and
Decision Making
References – Lecture a
References
Alfaso-LeFevre, R. (2017). Critical thinking, clinical reasoning and clinical judgment: A practical
approach. 6th ed. Philadelphia, PA: Elsevier.
Evans, D. A., & Gadd, C. S. (1989). Managing coherence and context in medical problem-solving
discourse. In Evans D. A., & Patel V. L. (Eds.), Cognitive science in medicine: Biomedical
modeling. Cambridge, MA: MIT Press, 211–255.
Friedman, C. P. (2009). A Fundamental theorem of biomedical informatics. NCBI Resources. Journal
of the American Medical Informatics. Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2649317/
Hunter, K. M. (1991). Doctors' stories: The narrative structure of medical knowledge. Princeton
University Press.
Kassirer, J., Wong, J. & Kopelman, R. (2009). Learning clinical reasoning (2nd ed). Lippincott,
Williams & Wilkins, 332.
Trotter, W. (n.d.) Quotation. “Disease often tells its secrets in a casual parenthesis.”
Van Roy K., Vanheule S. & Deveugele M. (2013) What makes up good consultations? A qualitative
study on GP’s discourses. BMC Family Practice, May 16;14:62. Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662575/
18
Health Care Processes and
Decision Making
References – Lecture a Continued
Charts, Tables, Figures
4.1 Table: Types of information that clinicians utilize when making decisions (Slide 6)
4.2 Table: Comparison of classic paradigm with operating room (Slide 12)
4.3 Table: Comparison of classic paradigm with operating room and acute complex illness (Slide 13)
4.4 Table: Comparison of classic paradigm with operating room, acute complex illness, and emergency
department (Slide 14)
19
The Culture of Health Care
Health Care Processes and
Decision Making
Lecture a
This material was developed by Oregon Health &
Science University, funded by the Department of
Health and Human Services, Office of the National
Coordinator for Health Information Technology
under Award Number IU24OC000015. This
material was updated in 2016 by Bellevue College
under Award Number 90WT0002.
20

More Related Content

What's hot

Health Care Processes and Decision Making_Lecture 3_ slides
Health Care Processes and Decision Making_Lecture 3_ slidesHealth Care Processes and Decision Making_Lecture 3_ slides
Health Care Processes and Decision Making_Lecture 3_ slidesCMDLearning
 
Evidence-Based Practice_lecture 1_slides
Evidence-Based Practice_lecture 1_slidesEvidence-Based Practice_lecture 1_slides
Evidence-Based Practice_lecture 1_slidesCMDLearning
 
MHA 690 UCLA Prominent Patients Training
MHA 690 UCLA Prominent Patients TrainingMHA 690 UCLA Prominent Patients Training
MHA 690 UCLA Prominent Patients Traininginmompoint
 
Evidence-based medicine databases
Evidence-based medicine databasesEvidence-based medicine databases
Evidence-based medicine databasesnabot
 
Final_Presentation_of_the_Project
Final_Presentation_of_the_ProjectFinal_Presentation_of_the_Project
Final_Presentation_of_the_ProjectHussam Albugami
 
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau Tran
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau TranPatient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau Tran
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau TranBao Chau Tran
 
Biostatistics
BiostatisticsBiostatistics
BiostatisticsPRIYAG63
 
Cross sectional studies
Cross sectional studiesCross sectional studies
Cross sectional studiessoudfaiza
 
vias venosas difíciles en emergencias.
vias venosas difíciles en emergencias.vias venosas difíciles en emergencias.
vias venosas difíciles en emergencias.Marco Darby
 
2016_The exchangeability of self-reports and administrative health care resou...
2016_The exchangeability of self-reports and administrative health care resou...2016_The exchangeability of self-reports and administrative health care resou...
2016_The exchangeability of self-reports and administrative health care resou...Cindy Noben
 
Niko Prado revised resume
Niko Prado revised resumeNiko Prado revised resume
Niko Prado revised resumeNikolas Prado
 
Careers in epidemiology
Careers in epidemiologyCareers in epidemiology
Careers in epidemiologyentranzz123
 
Careers in epidemiology
Careers in epidemiologyCareers in epidemiology
Careers in epidemiologyentranzz123
 
Difference between cohort, cross sectional and case control study - Scientifi...
Difference between cohort, cross sectional and case control study - Scientifi...Difference between cohort, cross sectional and case control study - Scientifi...
Difference between cohort, cross sectional and case control study - Scientifi...Pubrica
 
Application of Biostatistics
Application of BiostatisticsApplication of Biostatistics
Application of BiostatisticsJippy Jack
 

What's hot (20)

Health Care Processes and Decision Making_Lecture 3_ slides
Health Care Processes and Decision Making_Lecture 3_ slidesHealth Care Processes and Decision Making_Lecture 3_ slides
Health Care Processes and Decision Making_Lecture 3_ slides
 
Evidence-Based Practice_lecture 1_slides
Evidence-Based Practice_lecture 1_slidesEvidence-Based Practice_lecture 1_slides
Evidence-Based Practice_lecture 1_slides
 
MHA 690 UCLA Prominent Patients Training
MHA 690 UCLA Prominent Patients TrainingMHA 690 UCLA Prominent Patients Training
MHA 690 UCLA Prominent Patients Training
 
Evidence-based medicine databases
Evidence-based medicine databasesEvidence-based medicine databases
Evidence-based medicine databases
 
Evidence based medicine
Evidence based medicineEvidence based medicine
Evidence based medicine
 
83341 ch12 jacobsen
83341 ch12 jacobsen83341 ch12 jacobsen
83341 ch12 jacobsen
 
Final_Presentation_of_the_Project
Final_Presentation_of_the_ProjectFinal_Presentation_of_the_Project
Final_Presentation_of_the_Project
 
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau Tran
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau TranPatient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau Tran
Patient-Oriented Summer Insitutes_5.4.16_SR_Bao Chau Tran
 
Biostatistics
BiostatisticsBiostatistics
Biostatistics
 
Cross sectional studies
Cross sectional studiesCross sectional studies
Cross sectional studies
 
vias venosas difíciles en emergencias.
vias venosas difíciles en emergencias.vias venosas difíciles en emergencias.
vias venosas difíciles en emergencias.
 
2016_The exchangeability of self-reports and administrative health care resou...
2016_The exchangeability of self-reports and administrative health care resou...2016_The exchangeability of self-reports and administrative health care resou...
2016_The exchangeability of self-reports and administrative health care resou...
 
Case Report Writing
Case Report WritingCase Report Writing
Case Report Writing
 
Case history
Case historyCase history
Case history
 
Niko Prado revised resume
Niko Prado revised resumeNiko Prado revised resume
Niko Prado revised resume
 
Careers in epidemiology
Careers in epidemiologyCareers in epidemiology
Careers in epidemiology
 
Careers in epidemiology
Careers in epidemiologyCareers in epidemiology
Careers in epidemiology
 
Research, Policy and Advocacy: Reflections of an Academician by Lynne D. Rich...
Research, Policy and Advocacy: Reflections of an Academician by Lynne D. Rich...Research, Policy and Advocacy: Reflections of an Academician by Lynne D. Rich...
Research, Policy and Advocacy: Reflections of an Academician by Lynne D. Rich...
 
Difference between cohort, cross sectional and case control study - Scientifi...
Difference between cohort, cross sectional and case control study - Scientifi...Difference between cohort, cross sectional and case control study - Scientifi...
Difference between cohort, cross sectional and case control study - Scientifi...
 
Application of Biostatistics
Application of BiostatisticsApplication of Biostatistics
Application of Biostatistics
 

Similar to Health Care Processes and Decision Making_lecture 1_slides

Health Care Processes and Decision Making_Lecture 4_slides
Health Care Processes and Decision Making_Lecture 4_slidesHealth Care Processes and Decision Making_Lecture 4_slides
Health Care Processes and Decision Making_Lecture 4_slidesCMDLearning
 
Evidence-Based Practice: An introduction for new librarians
Evidence-Based Practice: An introduction for new librariansEvidence-Based Practice: An introduction for new librarians
Evidence-Based Practice: An introduction for new librariansPamela Harrison
 
Informatics for librarians: the core of the onion
Informatics for librarians: the core of the onionInformatics for librarians: the core of the onion
Informatics for librarians: the core of the onionJacqueline Leskovec
 
Evidence-Based Practice Lecture 2_slides
Evidence-Based Practice Lecture 2_slidesEvidence-Based Practice Lecture 2_slides
Evidence-Based Practice Lecture 2_slidesCMDLearning
 
The Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesThe Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesPhilip Payne
 
Assured Clinical Insight - Health In4matics 2012
Assured Clinical Insight  - Health In4matics 2012Assured Clinical Insight  - Health In4matics 2012
Assured Clinical Insight - Health In4matics 2012BredaCorish
 
Delivering Healthcare (Part 2) Lecture A
Delivering Healthcare (Part 2) Lecture ADelivering Healthcare (Part 2) Lecture A
Delivering Healthcare (Part 2) Lecture ACMDLearning
 
6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril6-005-1430-Keeppanasseril
6-005-1430-Keeppanasserilmed20su
 
Incorporating EBM in Residency Training
Incorporating EBM in Residency TrainingIncorporating EBM in Residency Training
Incorporating EBM in Residency TrainingImad Hassan
 
Health IT: The Big Picture (October 4, 2018)
Health IT: The Big Picture (October 4, 2018)Health IT: The Big Picture (October 4, 2018)
Health IT: The Big Picture (October 4, 2018)Nawanan Theera-Ampornpunt
 
Introduction to Health Informatics and Health Information Technology (Part 2)...
Introduction to Health Informatics and Health Information Technology (Part 2)...Introduction to Health Informatics and Health Information Technology (Part 2)...
Introduction to Health Informatics and Health Information Technology (Part 2)...Nawanan Theera-Ampornpunt
 
Electronic health records
Electronic health recordsElectronic health records
Electronic health recordsChan Chan
 

Similar to Health Care Processes and Decision Making_lecture 1_slides (20)

Health Care Processes and Decision Making_Lecture 4_slides
Health Care Processes and Decision Making_Lecture 4_slidesHealth Care Processes and Decision Making_Lecture 4_slides
Health Care Processes and Decision Making_Lecture 4_slides
 
Evidence-Based Practice: An introduction for new librarians
Evidence-Based Practice: An introduction for new librariansEvidence-Based Practice: An introduction for new librarians
Evidence-Based Practice: An introduction for new librarians
 
EVIDENCE BASED NURSING PRACTICE
EVIDENCE BASED NURSING PRACTICE EVIDENCE BASED NURSING PRACTICE
EVIDENCE BASED NURSING PRACTICE
 
Clinical informatics I: Roles of Health IT
Clinical informatics I: Roles of Health ITClinical informatics I: Roles of Health IT
Clinical informatics I: Roles of Health IT
 
Informatics for librarians: the core of the onion
Informatics for librarians: the core of the onionInformatics for librarians: the core of the onion
Informatics for librarians: the core of the onion
 
Evidence-Based Practice Lecture 2_slides
Evidence-Based Practice Lecture 2_slidesEvidence-Based Practice Lecture 2_slides
Evidence-Based Practice Lecture 2_slides
 
The Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesThe Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across Scales
 
Overview of Health IT
Overview of Health ITOverview of Health IT
Overview of Health IT
 
Health IT: The Big Picture (July 2, 2015)
Health IT: The Big Picture (July 2, 2015)Health IT: The Big Picture (July 2, 2015)
Health IT: The Big Picture (July 2, 2015)
 
Overview of Health IT (October 2, 2016)
Overview of Health IT (October 2, 2016)Overview of Health IT (October 2, 2016)
Overview of Health IT (October 2, 2016)
 
Assured Clinical Insight - Health In4matics 2012
Assured Clinical Insight  - Health In4matics 2012Assured Clinical Insight  - Health In4matics 2012
Assured Clinical Insight - Health In4matics 2012
 
Delivering Healthcare (Part 2) Lecture A
Delivering Healthcare (Part 2) Lecture ADelivering Healthcare (Part 2) Lecture A
Delivering Healthcare (Part 2) Lecture A
 
Patient Reported Outcomes to Accelerate Change
Patient Reported Outcomes to Accelerate ChangePatient Reported Outcomes to Accelerate Change
Patient Reported Outcomes to Accelerate Change
 
6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril
 
Incorporating EBM in Residency Training
Incorporating EBM in Residency TrainingIncorporating EBM in Residency Training
Incorporating EBM in Residency Training
 
Watson – from Jeopardy to healthcare
Watson – from Jeopardy to healthcareWatson – from Jeopardy to healthcare
Watson – from Jeopardy to healthcare
 
Transitional Care Workgroup
Transitional Care WorkgroupTransitional Care Workgroup
Transitional Care Workgroup
 
Health IT: The Big Picture (October 4, 2018)
Health IT: The Big Picture (October 4, 2018)Health IT: The Big Picture (October 4, 2018)
Health IT: The Big Picture (October 4, 2018)
 
Introduction to Health Informatics and Health Information Technology (Part 2)...
Introduction to Health Informatics and Health Information Technology (Part 2)...Introduction to Health Informatics and Health Information Technology (Part 2)...
Introduction to Health Informatics and Health Information Technology (Part 2)...
 
Electronic health records
Electronic health recordsElectronic health records
Electronic health records
 

More from CMDLearning

What is Health Informatics - Lecture B
What is Health Informatics - Lecture BWhat is Health Informatics - Lecture B
What is Health Informatics - Lecture BCMDLearning
 
Evolution of and Trends in Health Care - Lecture D
Evolution of and Trends in Health Care - Lecture DEvolution of and Trends in Health Care - Lecture D
Evolution of and Trends in Health Care - Lecture DCMDLearning
 
Evolution of and Trends in Health Care - Lecture C
Evolution of and Trends in Health Care - Lecture CEvolution of and Trends in Health Care - Lecture C
Evolution of and Trends in Health Care - Lecture CCMDLearning
 
Evolution of and Trends in Health Care - Lecture B
Evolution of and Trends in Health Care - Lecture BEvolution of and Trends in Health Care - Lecture B
Evolution of and Trends in Health Care - Lecture BCMDLearning
 
Public Healthcare (Part 2) Lecture C
Public Healthcare (Part 2) Lecture CPublic Healthcare (Part 2) Lecture C
Public Healthcare (Part 2) Lecture CCMDLearning
 
Public Healthcare (Part 2) Lecture B
Public Healthcare (Part 2) Lecture BPublic Healthcare (Part 2) Lecture B
Public Healthcare (Part 2) Lecture BCMDLearning
 
Public Healthcare (Part 2) Lecture A
Public Healthcare (Part 2) Lecture APublic Healthcare (Part 2) Lecture A
Public Healthcare (Part 2) Lecture ACMDLearning
 
Public Health (Part 1) Lecture C
Public Health (Part 1) Lecture CPublic Health (Part 1) Lecture C
Public Health (Part 1) Lecture CCMDLearning
 
Public Health (Part 1) Lecture B
Public Health (Part 1) Lecture BPublic Health (Part 1) Lecture B
Public Health (Part 1) Lecture BCMDLearning
 
Public Health (Part 1) Lecture A
Public Health (Part 1) Lecture APublic Health (Part 1) Lecture A
Public Health (Part 1) Lecture ACMDLearning
 
Regulating Healthcare - Lecture E
Regulating Healthcare - Lecture ERegulating Healthcare - Lecture E
Regulating Healthcare - Lecture ECMDLearning
 
Regulating Healthcare - Lecture D
Regulating Healthcare - Lecture DRegulating Healthcare - Lecture D
Regulating Healthcare - Lecture DCMDLearning
 
Regulating Healthcare - Lecture C
Regulating Healthcare - Lecture CRegulating Healthcare - Lecture C
Regulating Healthcare - Lecture CCMDLearning
 
Regulating Healthcare - Lecture A
Regulating Healthcare - Lecture ARegulating Healthcare - Lecture A
Regulating Healthcare - Lecture ACMDLearning
 
Regulating Healthcare - Lecture B
Regulating Healthcare - Lecture BRegulating Healthcare - Lecture B
Regulating Healthcare - Lecture BCMDLearning
 
Financing Healthcare (Part 2) Lecture C
Financing Healthcare (Part 2) Lecture CFinancing Healthcare (Part 2) Lecture C
Financing Healthcare (Part 2) Lecture CCMDLearning
 
Financing Healthcare (Part 2) Lecture B
Financing Healthcare (Part 2) Lecture BFinancing Healthcare (Part 2) Lecture B
Financing Healthcare (Part 2) Lecture BCMDLearning
 
Financing Healthcare (Part 2) Lecture A
Financing Healthcare (Part 2) Lecture AFinancing Healthcare (Part 2) Lecture A
Financing Healthcare (Part 2) Lecture ACMDLearning
 
Financing Healthcare (Part 2) Lecture D
Financing Healthcare (Part 2) Lecture DFinancing Healthcare (Part 2) Lecture D
Financing Healthcare (Part 2) Lecture DCMDLearning
 
Financing Healthcare (Part 1) Lecture D
Financing Healthcare (Part 1) Lecture DFinancing Healthcare (Part 1) Lecture D
Financing Healthcare (Part 1) Lecture DCMDLearning
 

More from CMDLearning (20)

What is Health Informatics - Lecture B
What is Health Informatics - Lecture BWhat is Health Informatics - Lecture B
What is Health Informatics - Lecture B
 
Evolution of and Trends in Health Care - Lecture D
Evolution of and Trends in Health Care - Lecture DEvolution of and Trends in Health Care - Lecture D
Evolution of and Trends in Health Care - Lecture D
 
Evolution of and Trends in Health Care - Lecture C
Evolution of and Trends in Health Care - Lecture CEvolution of and Trends in Health Care - Lecture C
Evolution of and Trends in Health Care - Lecture C
 
Evolution of and Trends in Health Care - Lecture B
Evolution of and Trends in Health Care - Lecture BEvolution of and Trends in Health Care - Lecture B
Evolution of and Trends in Health Care - Lecture B
 
Public Healthcare (Part 2) Lecture C
Public Healthcare (Part 2) Lecture CPublic Healthcare (Part 2) Lecture C
Public Healthcare (Part 2) Lecture C
 
Public Healthcare (Part 2) Lecture B
Public Healthcare (Part 2) Lecture BPublic Healthcare (Part 2) Lecture B
Public Healthcare (Part 2) Lecture B
 
Public Healthcare (Part 2) Lecture A
Public Healthcare (Part 2) Lecture APublic Healthcare (Part 2) Lecture A
Public Healthcare (Part 2) Lecture A
 
Public Health (Part 1) Lecture C
Public Health (Part 1) Lecture CPublic Health (Part 1) Lecture C
Public Health (Part 1) Lecture C
 
Public Health (Part 1) Lecture B
Public Health (Part 1) Lecture BPublic Health (Part 1) Lecture B
Public Health (Part 1) Lecture B
 
Public Health (Part 1) Lecture A
Public Health (Part 1) Lecture APublic Health (Part 1) Lecture A
Public Health (Part 1) Lecture A
 
Regulating Healthcare - Lecture E
Regulating Healthcare - Lecture ERegulating Healthcare - Lecture E
Regulating Healthcare - Lecture E
 
Regulating Healthcare - Lecture D
Regulating Healthcare - Lecture DRegulating Healthcare - Lecture D
Regulating Healthcare - Lecture D
 
Regulating Healthcare - Lecture C
Regulating Healthcare - Lecture CRegulating Healthcare - Lecture C
Regulating Healthcare - Lecture C
 
Regulating Healthcare - Lecture A
Regulating Healthcare - Lecture ARegulating Healthcare - Lecture A
Regulating Healthcare - Lecture A
 
Regulating Healthcare - Lecture B
Regulating Healthcare - Lecture BRegulating Healthcare - Lecture B
Regulating Healthcare - Lecture B
 
Financing Healthcare (Part 2) Lecture C
Financing Healthcare (Part 2) Lecture CFinancing Healthcare (Part 2) Lecture C
Financing Healthcare (Part 2) Lecture C
 
Financing Healthcare (Part 2) Lecture B
Financing Healthcare (Part 2) Lecture BFinancing Healthcare (Part 2) Lecture B
Financing Healthcare (Part 2) Lecture B
 
Financing Healthcare (Part 2) Lecture A
Financing Healthcare (Part 2) Lecture AFinancing Healthcare (Part 2) Lecture A
Financing Healthcare (Part 2) Lecture A
 
Financing Healthcare (Part 2) Lecture D
Financing Healthcare (Part 2) Lecture DFinancing Healthcare (Part 2) Lecture D
Financing Healthcare (Part 2) Lecture D
 
Financing Healthcare (Part 1) Lecture D
Financing Healthcare (Part 1) Lecture DFinancing Healthcare (Part 1) Lecture D
Financing Healthcare (Part 1) Lecture D
 

Recently uploaded

💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋
💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋
💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋Sheetaleventcompany
 
Hot Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In Ludhiana
Hot  Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In LudhianaHot  Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In Ludhiana
Hot Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In LudhianaRussian Call Girls in Ludhiana
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...Gfnyt.com
 
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...Niamh verma
 
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...High Profile Call Girls Chandigarh Aarushi
 
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service Gurgaon
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service GurgaonCall Girl Gurgaon Saloni 9711199012 Independent Escort Service Gurgaon
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service GurgaonCall Girls Service Gurgaon
 
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...High Profile Call Girls Chandigarh Aarushi
 
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591adityaroy0215
 
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012Call Girls Service Gurgaon
 
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsi
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsiindian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsi
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana TulsiHigh Profile Call Girls Chandigarh Aarushi
 
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...Sheetaleventcompany
 
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real MeetCall Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meetpriyashah722354
 
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591adityaroy0215
 
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service Dehradun
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service DehradunDehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service Dehradun
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service DehradunNiamh verma
 
Leading transformational change: inner and outer skills
Leading transformational change: inner and outer skillsLeading transformational change: inner and outer skills
Leading transformational change: inner and outer skillsHelenBevan4
 
Basics of Anatomy- Language of Anatomy.pptx
Basics of Anatomy- Language of Anatomy.pptxBasics of Anatomy- Language of Anatomy.pptx
Basics of Anatomy- Language of Anatomy.pptxAyush Gupta
 

Recently uploaded (20)

Call Girl Lucknow Gauri 🔝 8923113531 🔝 🎶 Independent Escort Service Lucknow
Call Girl Lucknow Gauri 🔝 8923113531  🔝 🎶 Independent Escort Service LucknowCall Girl Lucknow Gauri 🔝 8923113531  🔝 🎶 Independent Escort Service Lucknow
Call Girl Lucknow Gauri 🔝 8923113531 🔝 🎶 Independent Escort Service Lucknow
 
💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋
💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋
💚😋Chandigarh Escort Service Call Girls, ₹5000 To 25K With AC💚😋
 
Hot Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In Ludhiana
Hot  Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In LudhianaHot  Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In Ludhiana
Hot Call Girl In Ludhiana 👅🥵 9053'900678 Call Girls Service In Ludhiana
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
 
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...
Call Girls Service Chandigarh Gori WhatsApp ❤7710465962 VIP Call Girls Chandi...
 
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...
Call Girls Service Chandigarh Grishma ❤️🍑 9907093804 👄🫦 Independent Escort Se...
 
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service Gurgaon
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service GurgaonCall Girl Gurgaon Saloni 9711199012 Independent Escort Service Gurgaon
Call Girl Gurgaon Saloni 9711199012 Independent Escort Service Gurgaon
 
Russian Call Girls in Dehradun Komal 🔝 7001305949 🔝 📍 Independent Escort Serv...
Russian Call Girls in Dehradun Komal 🔝 7001305949 🔝 📍 Independent Escort Serv...Russian Call Girls in Dehradun Komal 🔝 7001305949 🔝 📍 Independent Escort Serv...
Russian Call Girls in Dehradun Komal 🔝 7001305949 🔝 📍 Independent Escort Serv...
 
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...
Russian Call Girls in Chandigarh Ojaswi ❤️🍑 9907093804 👄🫦 Independent Escort ...
 
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591
VIP Call Girl Sector 88 Gurgaon Delhi Just Call Me 9899900591
 
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012
VIP Call Girls Sector 67 Gurgaon Just Call Me 9711199012
 
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsi
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsiindian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsi
indian Call Girl Panchkula ❤️🍑 9907093804 Low Rate Call Girls Ludhiana Tulsi
 
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...
Call Girl In Zirakpur ❤️♀️@ 9988299661 Zirakpur Call Girls Near Me ❤️♀️@ Sexy...
 
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real MeetCall Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
 
VIP Call Girls Lucknow Isha 🔝 9719455033 🔝 🎶 Independent Escort Service Lucknow
VIP Call Girls Lucknow Isha 🔝 9719455033 🔝 🎶 Independent Escort Service LucknowVIP Call Girls Lucknow Isha 🔝 9719455033 🔝 🎶 Independent Escort Service Lucknow
VIP Call Girls Lucknow Isha 🔝 9719455033 🔝 🎶 Independent Escort Service Lucknow
 
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591
VIP Call Girl Sector 25 Gurgaon Just Call Me 9899900591
 
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service Dehradun
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service DehradunDehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service Dehradun
Dehradun Call Girls Service ❤️🍑 8854095900 👄🫦Independent Escort Service Dehradun
 
Leading transformational change: inner and outer skills
Leading transformational change: inner and outer skillsLeading transformational change: inner and outer skills
Leading transformational change: inner and outer skills
 
Call Girls in Lucknow Esha 🔝 8923113531 🔝 🎶 Independent Escort Service Lucknow
Call Girls in Lucknow Esha 🔝 8923113531  🔝 🎶 Independent Escort Service LucknowCall Girls in Lucknow Esha 🔝 8923113531  🔝 🎶 Independent Escort Service Lucknow
Call Girls in Lucknow Esha 🔝 8923113531 🔝 🎶 Independent Escort Service Lucknow
 
Basics of Anatomy- Language of Anatomy.pptx
Basics of Anatomy- Language of Anatomy.pptxBasics of Anatomy- Language of Anatomy.pptx
Basics of Anatomy- Language of Anatomy.pptx
 

Health Care Processes and Decision Making_lecture 1_slides

  • 1.
  • 2. The Culture of Health Care Health Care Processes and Decision Making Lecture a This material (Comp 2 Unit 4) was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number IU24OC000015. This material was updated in 2016 by Bellevue College under Award Number 90WT0002. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.
  • 3. Health Care Processes and Decision Making Learning Objectives • Describe the elements of the “classic paradigm” of the clinical process. (Lecture a) • List the types of information used by clinicians when they care for patients. (Lecture a) • Describe the steps required to manage information during the patient-clinician interaction. (Lectures a, b, c) • List the different information structures or formats used to organize clinical information. (Lecture b) • Describe different paradigms and elements of clinical decision making. (Lectures a, b) • Explain the differences among observations, findings, syndromes, and diseases. (Lectures a, b, c) • Describe techniques or approaches used by clinicians to reach a diagnosis. (Lectures a, b, c, d, e) • List the major types of factors that clinicians consider when devising a management plan for a patient’s condition in addition to the diagnosis and recommended treatment. (Lecture e) • Describe the role of EHRs and technology in the clinical decision-making process. (Lectures a, b, c, d, e) 3
  • 4. The Classic Paradigm • Classic paradigm assumes a single patient interacts with a single clinician • Patient has a single problem • Care is provided during a single episode • Various tools mediate this process – Medical records – Computers supporting clinical information systems – Medical devices and medical diagnostic equipment – Electronic communication: email, portals 4
  • 5. Classic Paradigm Evolution of Tools That Support the Task • Central theorem of health informatics – human + computer > human alone • Classic paradigm in health informatics – One patient – One problem – One clinician – One visit • Technology supports this 1:1:1:1 paradigm 5
  • 6. Attributes of Clinician • Possesses specialized knowledge • Received experiential training • Has direct relationship with patient, directly involved in the care of the patient and makes decisions about patient care • Acts in patient’s best interest • Integrates diverse types of information • Functions within time & resource constraints 6
  • 7. Types of Information Information Type Information Characteristics Sources Patient data Refers to one person Patient, family, records, observation Population statistics Aggregated patient data Colleagues, public health department, EHR Medical knowledge Generalizable to many persons Textbooks, journal articles, MEDLINE Logistic information How to get things done People, policy, procedure, and insurance companies Social influence How others get the job done Observe and discuss with colleagues 4.1 Table: Types of information that clinicians utilize when making decisions 7
  • 8. Organization: How Clinicians Organize Information • Narrative structure • Rearranged into a history and physical format • Further rearranged into a hierarchy • Reformulated into a computable structure for utilization by clinical information systems 8
  • 9. Disease “Disease often tells its secrets in a casual parenthesis.” —Wilfred Trotter 9
  • 10. How Stories Fit into Health System Part 1 • Communication between patient and clinician – Facts embedded in story (meaning to clinician) – Meaning of the illness to the patient – Communication and relationship building – Therapeutic value – Important aspect of quality of care 10
  • 11. How Stories Fit into Health System Part 2 • Among clinicians – Efficient communication among experts – Values and ethics are communicated through stories • How do modern healthcare systems (and health IT) affect stories? – Eliminate or alter them – Lose context 11
  • 12. Interpretation: How Clinicians Understand Clinical Data • Disciplinary differences • Different approaches to clinical data interpretation • Development of social construction • Contextual interpretation of data 12
  • 13. Beyond the Classic Paradigm: Collaboration in Surgery Medical Situations Patients Problems Clinicians Visits Classic paradigm 1 1 1 1 Operating room 1 1 Many 1 4.2 Table: Comparison of classic paradigm with operating room • Multiple disciplines with different roles and tasks • Short time horizon • Requires advance planning, resource rich 13
  • 14. Beyond the Classic Paradigm: Uncertain, Complex, High Stakes Medical Situations Patients Problems Clinicians Visits Classic paradigm 1 1 1 1 Operating room 1 1 Many 1 Acute complex illness 1 Many Many 1 or more 4.3 Table: Comparison of classic paradigm with operating room and acute complex illness • Complex acute illness—multiple disciplines, roles, tasks • Short time horizon, unplanned events, uncertain data 14
  • 15. Beyond the Classic Paradigm: Uncertain, Complex, High Stakes Continued Medical Situations Patients Problems Clinicians Visits Classic paradigm 1 1 1 1 Operating room 1 1 Many 1 Acute complex illness 1 Many Many 1 or more Emergency dept Many Many Many 1 4.4 Table: Comparison of classic paradigm with operating room, acute complex illness, and emergency department • Simultaneous care of multiple acute and non- acute—very short time horizon • Planning for the unexpected, resources are often constrained • Coordination, cooperation, collaboration 15
  • 16. Steps in the Classic Process • What is the matter? – Diagnosis • What can be done? – Treatment • What will happen? – Prognosis • Gathering data • Analyzing findings • Making a diagnosis • Choosing treatment • Communicating the plan 16
  • 17. Health Care Processes and Decision Making Summary – Lecture a • Looked at types of information that clinicians use in the course of managing patients • Defined the role and nature of a clinician • Examined the classic paradigm of the clinical process and also looked at some alternate paradigms • Correlated patient questions with diagnostic process 17
  • 18. Health Care Processes and Decision Making References – Lecture a References Alfaso-LeFevre, R. (2017). Critical thinking, clinical reasoning and clinical judgment: A practical approach. 6th ed. Philadelphia, PA: Elsevier. Evans, D. A., & Gadd, C. S. (1989). Managing coherence and context in medical problem-solving discourse. In Evans D. A., & Patel V. L. (Eds.), Cognitive science in medicine: Biomedical modeling. Cambridge, MA: MIT Press, 211–255. Friedman, C. P. (2009). A Fundamental theorem of biomedical informatics. NCBI Resources. Journal of the American Medical Informatics. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2649317/ Hunter, K. M. (1991). Doctors' stories: The narrative structure of medical knowledge. Princeton University Press. Kassirer, J., Wong, J. & Kopelman, R. (2009). Learning clinical reasoning (2nd ed). Lippincott, Williams & Wilkins, 332. Trotter, W. (n.d.) Quotation. “Disease often tells its secrets in a casual parenthesis.” Van Roy K., Vanheule S. & Deveugele M. (2013) What makes up good consultations? A qualitative study on GP’s discourses. BMC Family Practice, May 16;14:62. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662575/ 18
  • 19. Health Care Processes and Decision Making References – Lecture a Continued Charts, Tables, Figures 4.1 Table: Types of information that clinicians utilize when making decisions (Slide 6) 4.2 Table: Comparison of classic paradigm with operating room (Slide 12) 4.3 Table: Comparison of classic paradigm with operating room and acute complex illness (Slide 13) 4.4 Table: Comparison of classic paradigm with operating room, acute complex illness, and emergency department (Slide 14) 19
  • 20. The Culture of Health Care Health Care Processes and Decision Making Lecture a This material was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number IU24OC000015. This material was updated in 2016 by Bellevue College under Award Number 90WT0002. 20

Editor's Notes

  1. No audio. Recording preparation.
  2. Welcome to The Culture of Health Care: Health Care Processes and Decision Making. This is Lecture a. The component, The Culture of Health Care, addresses job expectations in health care settings. It discusses how care is organized in a practice setting, privacy laws, and professional and ethical issues encountered in the workplace.
  3. The objectives for Health Care Processes and Decision Making are to: Describe the elements of the “classic paradigm” of the clinical process. List the types of information used by clinicians when they care for patients. Describe the steps required to manage information during the patient-clinician interaction. List the different information structures or formats used to organize clinical information. Describe different paradigms and elements of clinical decision making. Explain the differences among observations, findings, syndromes, and diseases. Describe techniques or approaches used by clinicians to reach a diagnosis. List the major types of factors that clinicians consider when devising a management plan for a patient’s condition in addition to the diagnosis and recommended treatment. Describe the role of EHRs and technology in the clinical decision-making process.
  4. This lecture is concerned with health care processes and decision making. In this paradigm, the basic assumption is that a single patient is interacting with a single clinician about a single problem during a single episode of care. Various tools may be used to mediate the interaction, including medical records, computers, medical devices, medical diagnostic equipment, and clinical information systems such as the electronic health record, or EHR [E-H-R], and clinical decision support systems. Electronic communication tools such as email and patient portals play a key role in supporting the patient and clinician interaction. This discussion focuses on the one-patient, one-problem, one-clinician, one-episode of care scenario, in part because it’s realistic in many situations and also because it helps to bound the problem. Note, however, that it’s not uncommon for a single patient to have multiple problems and diagnoses that require multiple clinicians and visits to achieve problem resolution.
  5. This classic paradigm is somewhat analogous to what’s been called the “central theorem [theer-uhm] of health informatics [in-fer-mat-iks].” The central theorem was articulated by Chuck Friedman [freed-muhn], and his assumption in this theorem is that a human being working in the health care field will perform better when assisted by properly designed computer tools than when working alone. Most people working in biomedical informatics carry this assumption as the foundation of their work even when it’s unstated. Similarly, the classic paradigm is operative in many discussions, even when it’s unstated. The paradigm is often assumed not only during the clinical process, such as when making diagnostic or treatment decisions, but also during the interaction between clinicians and technology—for example, the interaction between the physician and the EHR. Because a common scenario involves a single patient with a single problem being addressed by a single clinician during a single visit, technologies have been developed that support this one-to-one-to-one-to-one arrangement. This lecture also discusses health care configurations in which computer tools need to be designed to serve other purposes, but for now, the focus is on this classic concept of the patient-clinician relationship.
  6. This unit frequently uses the word clinician [kli-nish-uh n] to refer to the individual who is providing care. It’ll be helpful to define this term more precisely. Here, clinician does not refer to a person who has any particular degree or educational background. After all, a person with a degree in nursing may be in a senior administrative position, serving as the CEO, for instance. Most people wouldn’t call that work clinical. Similarly, a person with a doctorate in medicine may be developing computer systems or running a health insurance plan, and these forms of work aren’t clinical either. However, the work of patient care is performed by people with a variety of educational and training backgrounds who may be considered clinicians. For the purposes of this lecture, the clinician is a person who possesses the following attributes. First, a clinician is someone who possesses specialized knowledge, typically obtained through formal education, such as in a medical, nursing, or pharmacy school. Second, a clinician is someone who has received extensive experiential training. For example, fields such as nursing and medicine require post-classroom learning, substantial training, and practice under supervision so that the clinician learns how to apply formal knowledge in practice. In addition, state licensure is typically required for these clinicians to practice at their full capacity. Third, a clinician is a person who has a relationship with the patient and is directly involved in the care of the patient. Regardless of a person’s training, indirect activities such as setting policy about patient care don’t constitute clinical work, whereas direct interactions with the patient are considered clinical activities. Fourth, a clinician is someone who combines his or her knowledge, training, and experience to make decisions about patient care, such as assessment or management of the patient. Fifth, a clinician is a person who is expected to act in the best interest of the patient. This duty is called a fiduciary responsibility, similar to that of a trustee for a trust or a board member for an organization. Clinicians are expected to make choices and perform actions that aren’t in their own best interest but instead are best for the patient. Sixth, the clinician integrates diverse types of information, including not only individual knowledge of the patient and medical knowledge acquired in training but also information about local resources and constraints, as discussed later. Seventh, clinicians are almost always functioning within significant time and resource constraints. A clinician, then, is a person—whether a neurosurgeon, a nurse, a clinical pharmacist, or a physical therapist—who possesses these attributes.
  7. Clinicians use many different types of information while assessing and managing patients. The table lists five types of information that clinicians commonly use. The first type of information is patient data, or information that’s specific to an individual person, such as whether he or she has allergies, a history of diabetes, or a heart murmur. This information can be obtained from various sources: the patient, the patient’s family or friends, medical records, the patient’s personal health record, and/or the clinician’s own observations while conducting the history and physical examination. Relevant patient information also may be electronically obtained through access to another health system provider or a health information exchange. The second type of information is population statistics, which is data that has been aggregated [ag-ri-geyt-ed] from individual patients. One version of population statistics is a clinician’s informal knowledge of recent local history, such as recent flu outbreaks or a resurgence of whooping [hoo-ping] cough, which may be relevant to the findings in a particular case. A more formal version of population statistics might be a public health department publication about the frequency of diseases in a particular locale or a population-based report obtained from a clinic’s or hospital’s EHR system. The third type of information is medical knowledge—the rules or conclusions about health and health care that are relevant not just to the individual patient but are generalizable to many persons. This information may be obtained from textbooks, whether electronic or in print form; from reviews in journal articles; or from the medical literature. The fourth type of information, which is surprisingly useful for clinicians, is called logistic information. It focuses on how to get things done rather than on what to do. For example, the question isn’t whether a particular medication is indicated for a particular patient, but how to obtain that medication or how to get it paid for; it isn’t whether a particular type of surgery is indicated for a patient, but which surgeon is available to perform it and how he or she may be reached. This type of information may be available from informal sources, such as the organizational knowledge of staff in the clinic or hospital, or formal sources, such as policy and procedure manuals, directories, and other institutional documents. The insurance companies play a key role in care logistics, for example, by identifying preferred physicians and health care providers, covered and non-covered services, and other non-clinically based community services. The fifth type of information that physicians often use is called social influence, or the impact of others’ job performance on the clinician’s decisions. Clinicians may not always conform exactly to the practices of others, but in general they like to know how other clinicians are managing particular problems and whether their own practices align relatively well with those of others. In studying clinicians and their reasoning and decision-making processes, it’s helpful to remember that all of these types of information may be brought to bear at various stages of the process.
  8. In addition to using many different types of information, clinicians organize and reorganize information in several ways as they manage a patient. Information typically begins in a narrative structure, becomes rearranged into a highly structured history and physical format, and then is rearranged again into meaningful groupings in a hierarchy, as described by Evans and Gadd [gad]. The manner of recording information, such as the SOAP [soap] (subjective, objective, assessment, and plan) note, can be helpful in supporting the clinician’s thinking, and other ad hoc structures are used as needed. With the use of clinical information systems, much of the diagnostic information, such as lab results, radiology results, and data from medical devices, is provided to the clinician in electronic format. Each clinician typically enters his or her patient assessment, notes, and treatment plan directly into the EHR or clinical information system. This system provides a central location where all clinicians engaged in the patient’s care can access patient information and document their own clinical actions in a single electronic patient record, presenting a complete picture of the patient’s care and progress. Also, patient information may be aggregated or reformulated in an electronic manner that supports reporting capabilities, such as clinical decision support, quality improvement activities, and research, based on patient populations.
  9. Although a great deal of effort is devoted to giving structure to clinical data, the narrative structure is pervasive throughout the clinical process. This slide contains an old saying in health care, attributed to Wilfred Trotter, that says, [quote] “Disease often tells its secrets in a casual parenthesis.” [end quote] This means that despite the clinician’s attempt to elicit useful information about the patient’s problem by asking pointed and directed questions, critical clues may emerge only when the patient is simply allowed to tell his or her story. In fact, the clinical process almost always begins and very often ends with a narrative.
  10. Kathryn Montgomery Hunter has examined some of the many ways that stories are used and why they’re important to the health care system. First, stories are the principal communication between patient and clinician. Before asking direct and pointed questions, clinicians are taught to ask open-ended questions that allow the patient to tell his or her story in its native form. The patient’s narrative enables the clinician not only to find facts embedded in the stories that are meaningful for generating a diagnosis but also to understand the meaning of the illness for the patient. Listening to the story is an important part of relationship building and may have therapeutic value on its own. The clinician’s attentive listening can be a very important aspect of the quality of care as perceived by the patient.
  11. Stories or structured narratives are also a form of efficient communication among clinicians when discussing the patient. Storytelling in health care settings is an important part of the hidden curriculum through which values and ethics are communicated, often informally. Unfortunately, our modern and often fragmented health care system doesn’t always deal well with stories because of the constraints of time, the multidisciplinary process, and other factors. As a result, clinicians may eliminate or alter stories, reduce opportunities to hear them, or extract information from them incorrectly, losing important context or details.
  12. As clinicians gather information and decide what to do for each patient, their interpretation of the data depends on many factors. First, there are professional and disciplinary differences. A neurologist and a psychiatrist examining the same patient may elicit and focus on very different information and make different sense of it. Clinicians may also use differing approaches to interpreting clinical data as they attempt to reach a diagnosis. When observing clinicians working in groups, it becomes apparent that an important part of interpretation, especially in interdisciplinary care, is social construction, or the meaning that arises as clinicians discuss a patient. Social construction can be observed in settings such as the intensive care unit. During ICU rounds, the conversation among the participants often allows insight and consensus to emerge. Perhaps most important, clinicians’ interpretation of data depends on context—the patient’s context, the clinician’s context, the setting, and other factors. A single piece of information may have very different implications depending on these contexts.
  13. This slide depicts the classic paradigm with one patient, one problem, one clinician, and one visit, and compares it to an alternate situation, the operating room. Surgical procedures usually involve one visit and are concerned with one problem in a single patient. During surgical procedures, however, many clinicians from many disciplines may participate in the process and share information and collaborate in a synchronous fashion. The setting is also characterized by a relatively short time horizon and a fairly narrow clinical focus as well as substantial advance planning and rich resource availability. These differences may have implications for the kinds of health information technologies that will be helpful to the clinicians involved.
  14. Another setting that differs from the classic paradigm is complex acute illness. In this setting, one patient may be cared for in one or more visits by multiple clinicians dealing with multiple health problems. For example, the patient may have lung disease, kidney disease, joint disease, an infection, or preexisting chronic conditions such as diabetes and hypertension. In this scenario, multiple clinicians may perform multiple tasks over one or several patient visits. There’s often a short time horizon as well as unplanned events. Additionally, there’s almost always a great deal of uncertainty about some of the data, especially in critical care settings that tend to be focused on immediate goals. Because of unanticipated events and uncertain data, clinicians must remain flexible to allow dynamic re-planning as necessary. Clinical information systems designed for such a context might have different requirements than those designed for simple one-to-one settings.
  15. Yet another example in which health care goes beyond the classic paradigm is the emergency department. Here there are many patients with many different clinical problems being treated simultaneously by many different clinicians, usually involving a single visit, although in some cases there may have been previous episodes of care. Both acute and non-acute conditions must be treated. The very short time horizon in emergency departments is captured in the expression “treat ’em and street ’em,” because of the need to constantly keep things moving. Clinicians must be prepared for the unexpected, even in the face of significant resource constraints. Also mandatory are effective coordination, cooperation, and collaboration among the many individuals participating in the care. This is especially critical when the patient is admitted directly from the emergency department to an inpatient or critical care hospital setting. Once again, these factors may have a significant influence on the kinds of information technology and clinical information systems used in this setting.
  16. Having considered several health care scenarios, this slide returns to the classic paradigm. People who consult with a clinician are, in general, looking for the answers to three questions: What’s the matter? What can be done about it? What will happen to me? These questions correspond to the classic steps that clinicians take to make a diagnosis, recommend treatment, and make a prognosis. The remainder of this unit examines how clinicians gather data from the patient, analyze findings within that data, make sense from it to reach a diagnosis, consider that diagnosis along with many other contextual factors to recommend a treatment or management plan, and finally communicate their results to a variety of interested parties.
  17. This concludes Lecture a of Health Care Processes and Decision Making. In summary, this lecture looked at the central theorem of health informatics and at the types of information that clinicians use while managing patients. The role and nature of a clinician were defined, the classic paradigm of the clinical process was outlined, and some alternative paradigms were discussed. The typical questions that patients ask were correlated with the classic steps that clinicians use to make a diagnosis and devise a treatment plan.
  18. No audio.
  19. No audio.
  20. No audio.