Learning Public Health Informatics Nuts and Bolts Competencybased
Learning Public Health Informatics Nuts and Bolts: Competency-based Informatics Training at CDC Herman Tolentino, MD Lead, Public Health Informatics Fellowship Program 2014 Ae. HIN Hour Office of Surveillance, Epidemiology, and Laboratory Services Public Health Informatics Fellowship Program
Outline • • Informatics overview Nuts and Bolts: Cycles and Layers Public Health Informatics Applied Definition Dissected Informatics Competencies Training Programs Q&A 2
Informatics involves the study of the information dimensions of systems at different levels of organization, from molecules to populations Adapted by Tolentino from Ted Shortliffe’s presentation for Biomedical Informatics http: //sci. asu. edu/news/bmi_symposium/downloads/Edward. Shortliffe_presentation. pdf 3
System Nuts and Bolts Mental Models: Cycles and Layers TRANSFORMATIONS CREATION OF VALUE UNFOLDS OVER TIME LAYERS OF COMPLEX SYSTEMS INTERACTING COMPONENTS 4
What is Public Health Informatics? Definition 1 2 3 4 to improve population health capture, manage, analyze, use information knowledge about systems (that) Systematic application (of) PHIFP definition 5
What is Public Health Informatics? Definition 1 2 3 4 to improve population health capture, manage, analyze, use information knowledge about systems (that) Systematic application (of) PHIFP definition END MEANS 6
4 Improving Population Health Population health is defined as the health outcomes of a group of individuals, including the distribution of such outcomes within the group Kindig, DA, Stoddart G. (2003). What is population health? American Journal of Public Health, 93, 366 -369. Kindig DA. (2007). Understanding Population Health Terminology. Milbank Quarterly, 85(1), 139 -161. 7
Improving Population Health Stakeholders Within a Complex Health System Community Government agencies other than public health Clinical care delivery system Governmental public health infrastructure Education sector Employers and businesses The media Institute of Medicine, For the Public's Health: The Role of Measurement in Action and Accountability (2011) 8
Measuring Population Health We cannot improve what we do not measure. – Lord Kelvin DISTAL FACTORS Cultural context Political context Education Poverty Social connections Workplace Environment PROXIMAL FACTORS Diet Activity level Alcohol Smoking Self-identity PHYSIOLOGIC FACTORS Cholesterol Blood glucose Blood pressure Immunity DISEASES/INJURIES Diabetes Cardiovascular disease Infection Violence Adapted from Parrish G. Measuring Population Health Outcomes. Prev Chronic Dis 2010; 7(4): A 71. URL: http: //www. cdc. gov/pcd/issues/2010/jul/10_0005. htm. HEALTH OUTCOMES Function/disability Sense of well-being Death 9
Measuring Population Health The Health System Feedback Loop – A Complicated Business Causal Web of Health Status and Determinants Information Systems capture, manage, analyze, use Data, information, knowledge Health system performance Policies Programs Health System Decisions Interventions Collective action Public health is an information-driven enterprise. Information systems enable feedback loops that drive public health programs and policies. Adapted by H Tolentino from Sterman, John D. "Learning from evidence in a complex world. " American Journal of Public Health 96. 3 (2006); and Parrish G. Measuring Population Health Outcomes. Prev Chronic Dis 2010; 7(4): A 71. URL: http: //www. cdc. gov/pcd/issues/2010/jul/10_0005. htm. 10
Classification of Population Health Measurements Measures of current health status Health services research Process and outcome measures Descriptive Evaluative Evidence-based medicine Evidencebased policy Predictive Explanatory Projections and risk estimation Epidemiology Etiology and determinants Mc. Dowell, Ian, Robert A. Spasoff, and Betsy Kristjansson. "On the classification of population health measurements. " Am J of Public Health 94. 3 (2004). 11
Measuring Population Health The Health System Feedback Loop Public health is an information-driven enterprise. Information systems enable feedback loops that drive public health programs and policies. Adapted by H Tolentino from Sterman, John D. "Learning from evidence in a complex world. " American Journal of Public Health 96. 3 (2006); and Parrish G. Measuring Population Health Outcomes. Prev Chronic Dis 2010; 7(4): A 71. URL: http: //www. cdc. gov/pcd/issues/2010/jul/10_0005. htm. 12
Modern Measurement Challenges (Big) Data Issues – 5 Vs Variety Sources Formats Types Structures Transmission Velocity Creation/generation Transmission Computation Consumption Volume Storage Retrieval Computation Consumption Veracity Source (trust) Content integrity Voids Completeness Comprehensiveness Fragments Representativeness 13
Measuring Population Health The Health System Feedback Loop – Simplified Health Determinants and Outcomes Measurements Using Information Systems Collective Action The Health System Adapted by H Tolentino from Sterman, John D. "Learning from evidence in a complex world. " American Journal of Public Health 96. 3 (2006); and Parrish G. Measuring Population Health Outcomes. Prev Chronic Dis 2010; 7(4): A 71. URL: http: //www. cdc. gov/pcd/issues/2010/jul/10_0005. htm. 14
3 • • • Information Value Cycle • • • Organizational context Information needs Change management issues Resources (financing, workforce) Information systems architecture Inputs Process Outputs Outcomes Impact Improve population health • Decision support • Situation awareness • Disseminate health information Adapted from (1) Taylor, R. S. (1982). Value-added processes in the information life cycle. Journal of the American Society for Information Science, 33, 341 -346; (2) SB Thacker, et al. (2012). Public health surveillance in the US: Evolution and challenges. MMWR Supplement, July 27, 2012, 61: 3 -9. Capture Methods Data Types & Formats Data Standards Data Quality • • • • Visualization Classification Aggregation, linkage Knowledge representation Storage/Retrieval Transformation Exchange Protection (security) Integration 15
Information Value Cycle Information systems must generate value in each step. WISDOM DATA ACTION KNOWLEDGE Adapted from (1) Taylor, R. S. (1982). Value-added processes in the information life cycle. Journal of the American Society for Information Science, 33, 341 -346; (2) SB Thacker, et al. (2012). Public health surveillance in the US: Evolution and challenges. MMWR Supplement, July 27, 2012, 61: 3 -9; (3) M Laventure, B Brandt. , Minnesota Department of Health, Karen Zeleznak Bloomington Division of Public Health, 2005. INFORMATION 16
2 What is a System? • It is a whole with a purpose and has interacting, interdependent parts. Car = technological feat Traffic jam = nuisance of urban life Air pollution = large scale disaster – Parts cannot provide system function, examples: Wheels alone cannot carry passengers from points A to B, but the whole car does. • Implementing solutions with a limited understanding of a system and its interactions with larger systems can lead to unintended consequences with time delays – Examples: Traffic congestion, air pollution, siloed information systems, siloed professional practice 17
An Information System People, Process and Technology § The system that captures, manages, analyzes and uses information is made up of people, process and technology. § Alignment of all three enables smooth functioning of the IS. § Alignment with organizational context enables IS to deliver impact to organization bottom line. 18
DISC: Data, the Information System and its Context Knowledge about systems comes from various disciplines. § Environment: Technology trends and advancements, socio-cultural factors, health system factors, legislation, other information systems, other systems Information system components (structure): § People: End users, system administrators, decision makers § Organization: Mission, structure, resources information culture, values, informatics capacity, programs and policies § Process: Business activities supported by information system § Technology: Paper, computing and communication devices, communication networks, software applications that support information management System interactions: Data: § Data § Information § Knowledge Context components: Information System Context § Both environmental and organizational contexts affect how information systems are designed, developed, implemented and used. § Organizational performance can be a cause or a consequence of information generation and use, and vice versa (reinforcing loops). Adapted from (1) Heeks R, Bathnagar S. Understanding success and failure in information age reform. Reinventing Government in the Information Age, Heeks, Richard (Ed), Routledge, London, 1999, pp 49 -74. (2) Avgerou C. (2008). The significance of context in information systems and organizational change. Information Systems Journal, 11 (1): 43 -63. 19 (3) Ramaprasad, A. , and A. Rai. "Envisioning management of information. " Omega 24. 2 (1996): 179 -193.
1 Looking for Informatics Problems Gaps in value creation Context problems Data problems IS problems 20
IVC – Application The solutions of today may be the problems of tomorrow. Design/Development Phase Opportunities for prevention of downstream problems Implementation/Maintenance Phase Opportunities for improvement – rethinking or reframing existing problems 21
Continuous Quality Improvement By the time you have improved it, it’s already obsolete! Iteration 1 Iteration 2 Iteration 3 Iteration X Improving a surveillance system through an iterative approach. 22
Information Systems in the Enterprise System of Systems: Potential Interfaces Law Enforcement Foodborne Illness Environmental Health Department of Labor Occupational Safety Injury Prevention Health Care 23
Systems Interoperability in the Enterprise Importance of standards Eisenhower Interstate System Plug n’ Play Information Super Highway 24
Layers of Interoperability Alignment challenges § Human-to-human interoperability as important if not more than machineto-machine interoperability. § Corresponding layers may be asymmetrically developed 25
Informatics Problem Solving A Systematic Approach to Apply Knowledge to Real World Issues • A problem is defined as a recognized gap between a current state and a future state. Problem solving is a systematic approach to get to the future state. • From a living systems perspective, an informatics problem is like a “disease” or disorder within an information system that prevents creation of value. • There may be organizational or environmental determinants that lead to development of informatics problems. 26
Information “Pathologies” § Preventable gaps in distributed information processing § When Information that can be applied to a decision-making process is: § Producible and not produced § Procurable and not procured § Transmissible and not (accurately) transmitted § Applicable and not (accurately) applied Scholl W. Restrictive control and information pathologies in organizations. Journal of Social Issues, 1999. 27
Diagnosing and Treating Informatics Problems The Systematic Application Problem Determinants Collect data Analyze Diagnose Prognose Recommend or provide informatics solutions Follow up Track outcomes 28
Diagnosing and Treating Informatics Problems With living systems… Problem Determinants Collect data Analyze Diagnose Prognose Recommend or provide treatment or intervention Follow up Track outcomes 29
How do we become experts in informatics problem solving? Systematic Application – PHIFP Problem Solving Framework A. PROBLEM SOLVING INPUTS B. PROBLEM MANAGEMENT C. PERFORMANCE IMPROVEMENT Tolentino H, Papagari S, Kuruchittham V, Reese P, Franzke L, Koo D (2011). Development of a problem-solving framework for public health informatics. Poster session presented at: 2011 Public Health Informatics Network (PHIN) Conference; 22 August 2011; Atlanta, GA. 30
PHIFP Problem Solving Framework Simplified Version – Three Components A B Problem Solving Inputs Problem Management C Performance Improvement Tolentino H, Papagari S, Kuruchittham V, Reese P, Franzke L, Koo D (2011). Development of a problem-solving framework for public health informatics. Poster session presented at: 2011 Public Health Informatics Network (PHIN) Conference; 22 August 2011; Atlanta, GA. 31
To be competent, you have to feel bad. – Hubert Dreyfus INFORMATICS COMPETENCIES
Expert Performance Ericsson, K. Anders, Ralf T. Krampe, and Clemens Tesch-Römer. "The role of deliberate practice in the acquisition of expert performance. " Psychological review 100. 3 (1993): 363.
Informatics Competencies (Domains) Supporting Public Health Practice Community Dimensions of Practice Cultural Competence Communication Public Health Sciences Leadership and Systems Thinking PHIFP Competencies, 2009 Analysis, Assessment and Evaluation UNLEARNING Informatics Practice
CDC INFORMATICS FELLOWSHIPS
CDC Informatics Fellowships Different folks, different strokes • Public Health Informatics Fellowship Program (PHIFP): 2 year assignment to a CDC center, institute or office in Atlanta, GA; masters/doctoral; 4 -6/year, begins summer; accepts international fellows • Applied Public Health Informatics Fellowship Program (APHIF): 1 -year assignment to a state or local health department; masters/doctoral; 8 -10/year, begins summer • Informatics Training in Place Program (I-TIPP): 1 -year fellowship for existing employees of state or local health departments; bachelors; 8 -10/year, begins summer
Informatics Workforce Pipeline PHIFP, APHIF Preentry Planning TIPP Entry Exist Exit Preparing Workforce Managing Workforce Retiring Workforce Short term training: • • Internships Faculty development Capacity building Info. Aids PHI introductory course Pipeline adapted from Ramesh Krishnamurthy, WHO
You in 2015
Contact: htolentino@cdc. gov http: //www. cdc. gov/PHIFP QUESTIONS? Public health informatics is the systematic application of knowledge about systems that capture, manage, analyze and use information to improve population health.
- Slides: 39