MODULE 1: DECREASE ADMINISTRATIVE BURDEN
Assessment, Measurement, and Foundation Building
Module Learning Objectives
The Administrative Crisis
18.5 million hours annually
Canadian physicians spend on unnecessary administrative tasks
44% of physicians
Experience clear symptoms of burnout in 2024
Chapter 1: The Administrative Crisis in Canadian Healthcare
Understanding the Scope and Impact of Administrative Burden
1.1 The Statistical Reality
Physician Administrative Burden
The scope of administrative burden affecting Canadian physicians is both quantifiable and alarming. According to data from the Canadian Medical Association and provincial medical associations, Canadian physicians collectively spend 18.5 million hours annually on administrative tasks that are considered unnecessary or could be delegated to other personnel (Canadian Medical Association, 2024).
Key Statistics:
- 38% of physician administrative tasks could be delegated or eliminated entirely
- Equivalent of 9,250 full-time positions diverted from direct patient care
- 15-20 hours per week spent on administrative duties by Alberta physicians
- 40% of Alberta physician administrative tasks deemed unnecessary or delegable
Provincial data from Alberta provides particularly detailed insights. Healthcare professionals in this province report spending an average of 15 to 20 hours per week on administrative duties, with an estimated 40% of these tasks considered unnecessary or suitable for delegation (Alberta College of Family Physicians & Alberta Medical Association, 2023). This translates to an annual loss of approximately 3,458,000 physician-hours in Alberta alone, with 1,383,200 of those hours spent on tasks that offer little direct value to patient care.
Nursing Administrative Burden
While comprehensive Canadian time-motion studies for nurses focusing specifically on administrative tasks are less prevalent in available literature, existing data and international studies provide valuable insights into the nursing documentation burden that likely reflects Canadian experiences.
International time-motion studies indicate that documentation can account for up to 35% of nursing practice time (Hendrich et al., 2008). More recent studies show nurses spending significant portions of their shifts on EMR-related activities, with one study finding nurses spent an average of 31.63 minutes per 4-hour observation period on charting in electronic health records (Poissant et al., 2005).
Canadian-Specific Evidence
A 2022 survey of Infection Prevention and Control (IPC) nurses in Montreal revealed that 70% of respondents believed that administrative tasks such as process surveillance, data entry, and statistical analysis could be reassigned to other roles (Canadian Journal of Infection Control, 2022).
Health Canada’s Nursing Retention Toolkit explicitly acknowledges that nurses are frequently burdened with administrative tasks and other duties that fall outside the typical scope of nursing practice, including notifying patients of appointments, transporting charts, cleaning examination rooms, and restocking supplies (Health Canada, 2023).
Allied Health Professional Impact
Allied health professionals—including pharmacists, physiotherapists, occupational therapists, speech-language pathologists, and medical technologists—face unique administrative challenges that often differ from those experienced by physicians and nurses.
Pharmacy Practice
Pharmacists experience particular challenges with prior authorization processes, insurance coverage verification, and drug utilization reviews that can delay critical patient therapies.
Therapy Services
Physical and occupational therapists report substantial time requirements for treatment justification documentation and insurance verification processes.
1.2 The Burnout Connection: Evidence-Based Analysis
2024 National Survey Findings
The 2024 National Survey of Canadian Physicians provides compelling evidence of the relationship between administrative burden and professional burnout. The survey revealed that 44% of Canadian physicians are experiencing clear symptoms of burnout, with the breakdown as follows (Canadian Medical Association, 2024):
28% – “Definitely burning out”
11% – Persistent burnout symptoms
5% – “Completely burned out”
The “completely burned out” category represents physicians considering practice closure or requiring professional assistance.
The 2021 Canadian Medical Association National Physician Health Survey found that nearly 60% of responding physicians identified administrative issues as direct contributors to declining mental health (CMA, 2021). This establishes a clear causal relationship between administrative burden and healthcare professional well-being.
The “Pajama Time” Phenomenon
One of the most concerning aspects of administrative burden is the extension of work into personal time. The 2024 survey revealed that a substantial proportion of physicians dedicate considerable after-hours time to EMR work:
After-Hours EMR Work Distribution:
- 23% spend less than 1 hour
- 25% spend 1-2 hours
- 28% spend 2-3 hours
- 23% spend 3+ hours
This means 51% of physicians spend 2 or more hours on EMR work at home after their regular workday.
The perception of this after-hours EMR use is overwhelmingly negative, with 33% of physicians deeming it “Excessive” and 32% rating it as “Moderately high,” meaning nearly two-thirds find this additional workload problematic (Canadian Medical Association, 2024).
Direct Impact on Patient Care
The connection between administrative burden and patient care quality is both direct and measurable. Research demonstrates that 75% of Canadian doctors report that their administrative workload serves as an impediment to providing adequate care to their patients (CMA, 2024).
Alberta-Specific Impact Data
The Alberta College of Family Physicians and Alberta Medical Association study found particularly concerning impacts on patient access:
- 96% of physicians report administrative tasks negatively affect work-life balance
- 97% find administrative tasks limit their enjoyment of work
- 80.8% are contemplating retirement or leaving longitudinal care
- 59% report limitations in time with existing patients
- 65% have reduced patient appointment slots
(ACFP & AMA, 2023)
1.3 Financial Impact and Opportunity Costs
Direct Healthcare System Costs
While precise, current national figures for the specific financial cost of administrative burden distinct from general healthcare administration costs are not readily itemized in major Canadian Institute for Health Information expenditure reports, available data provides concerning context about the scale of healthcare administrative spending.
A 2017 comparative study found that Canada spent $551 per capita on health administration, representing 17.0% of national health expenditures (Woolhandler et al., 2023). While this was considerably lower than United States expenditures (34.2%), it still represented significant spending within the context of total healthcare costs.
2024 Healthcare Spending Context
Total healthcare spending in Canada is projected to reach $372 billion in 2024, equivalent to 12.4% of the nation’s GDP (CIHI, 2024).
Even modest improvements in administrative efficiency could yield substantial savings given this scale of spending.
Opportunity Cost Analysis
The true economic impact of administrative burden lies in opportunity costs—the value of clinical activities that could be performed if administrative time were reduced. When healthcare professionals spend time on administrative tasks, the cost includes not just their salary for those hours, but the potential health outcomes that could be achieved through direct patient care activities.
Quantifying Lost Opportunity
If even 20% of the unnecessary administrative time physicians currently spend could be reclaimed, this would translate to:
- 3.7 million additional physician-hours annually
- Hundreds of thousands of additional patient visits
- More thorough consultations for existing patients
- Improved access to care across the healthcare system
Recruitment and Retention Costs
Administrative burden contributes significantly to healthcare professional turnover and early retirement. When 80.8% of Alberta physicians report contemplating retirement or leaving longitudinal care due to administrative burden, the potential recruitment and retention costs become substantial.
The costs associated with replacing experienced healthcare professionals include recruitment expenses, onboarding time, training requirements, lost institutional knowledge, and productivity gaps during transition periods. Each experienced healthcare professional who leaves the field represents not just replacement costs, but the loss of years of accumulated expertise and patient relationships.
Chapter 2: The Canadian Regulatory Landscape for Healthcare AI
Navigating Federal and Provincial Requirements
2.1 Health Canada’s Comprehensive Approach
Software as a Medical Device (SaMD) Framework
Health Canada has developed a sophisticated, risk-based approach to regulating artificial intelligence in healthcare that balances innovation with patient safety. The cornerstone of this approach is the Software as a Medical Device (SaMD) framework, which classifies software based on its intended medical purpose and the healthcare situation and decision it informs (Health Canada, 2022).
SaMD Classification Criteria
SaMD classification considers two primary factors:
- Healthcare situation: Critical, serious, or non-serious
- Healthcare decision: Treat/diagnose, drive clinical management, or inform clinical management
Administrative AI tools may fall into various classification categories depending on their specific functions and impacts on patient care.
A license is generally required for the import or sale of SaMD in Canada, which can include software downloaded from an app store. Health Canada’s guidance document on SaMD, first adopted in 2019 and updated in 2022, provides examples to aid in the classification of these technologies (Health Canada, 2022).
Good Machine Learning Practice (GMLP) Principles
In collaboration with the U.S. Food and Drug Administration and the UK’s Medicines and Healthcare products Regulatory Agency, Health Canada has established ten foundational principles for Good Machine Learning Practice (Health Canada, FDA, MHRA, 2021):
1. Multi-disciplinary Expertise
Leverage diverse expertise throughout the product lifecycle
2. Software Engineering & Security
Implement robust software engineering and security practices
3. Representative Data Sets
Ensure training data represents intended patient populations
4. Independent Data Sets
Maintain independence between training and test datasets
5. Best Available Methods
Base reference datasets on highest quality available methods
6. Tailored Model Design
Design models for available data and intended use
7. Human-AI Team Performance
Focus on collaborative human-AI performance
8. Real-World Testing
Test performance during clinically relevant conditions
9. Clear User Information
Provide essential, understandable information to users
10. Performance Monitoring
Monitor deployed models and manage retraining risks
2.2 Provincial Privacy Legislation
Ontario’s Personal Health Information Protection Act (PHIPA)
PHIPA establishes comprehensive requirements for health information custodians, including specific provisions that directly impact AI implementation in healthcare settings. The Act defines health information custodians as doctors, hospitals, and other healthcare providers, establishing their obligations for the collection, use, and disclosure of personal health information (Government of Ontario, 2004).
Key PHIPA Requirements for AI Implementation:
- Consent: AI systems must operate within established consent frameworks
- Security Safeguards: Administrative, technical, and physical protection required
- Use Limitations: AI must only access information necessary for specific functions
- Individual Rights: Patients maintain access and correction rights
Alberta’s Personal Information Protection Act (PIPA)
PIPA serves as Alberta’s private-sector privacy law, applying to provincially regulated private sector organizations, businesses, and non-profit organizations that collect, use, or disclose personal information within the province (Government of Alberta, 2003).
Organizations subject to PIPA must develop and adhere to reasonable policies and practices to meet their obligations under the Act. The emphasis is on reasonable purposes for AI use—administrative efficiency improvements generally qualify as reasonable purposes—and obtaining appropriate consent with clear explanation of AI processing.
Saskatchewan’s Health Information Protection Act (HIPA)
HIPA governs the collection, use, disclosure of, and access to personal health information in Saskatchewan. The Act establishes specific requirements for “trustees” of health information, including health authorities and healthcare professionals (Government of Saskatchewan, 1999).
The “Need-to-Know” Principle
HIPA explicitly states the “need-to-know” principle, which has particular relevance for AI implementation. Access to personal health information is generally restricted to a “need-to-know” basis, determined by the requirements of an individual’s job duties.
This principle directly impacts how AI systems are designed and what data they can access for administrative pattern recognition.
2.3 Federal Guidance on AI Decision-Making
Privacy Commissioner Principles for Generative AI
In December 2023, the Office of the Privacy Commissioner of Canada, in collaboration with provincial and territorial counterparts, released “Principles for responsible, trustworthy and privacy-protective generative AI technologies” (Office of the Privacy Commissioner of Canada, 2023).
Core Principles Include:
- • Legal Authority and Consent
- • Appropriate Purposes
- • Necessity and Proportionality
- • Openness and Transparency
- • Accountability
Additional Requirements:
- • Individual Access
- • Limiting Collection and Use
- • Accuracy Standards
- • Appropriate Safeguards
- • Impact on Vulnerable Groups
Pan-Canadian AI for Health Guiding Principles
The Pan-Canadian AI for Health (AI4H) Guiding Principles, endorsed by Federal, Provincial, and Territorial Health Ministers (with the exception of Quebec), provide overarching direction for AI adoption across Canada’s health systems (Health Canada, 2023).
AI4H Guiding Principles:
- Person-centricity
- Equity, Diversity, and Inclusion
- Privacy and Security
- Safety and Oversight
- Accountability and Responsibility
- Transparency and Understandability
- AI Literacy
- Robust Data and Data Practices
- Indigenous-led Governance and Data Sovereignty
Chapter 3: Measuring Administrative Burden
Evidence-Based Assessment and Baseline Establishment
3.1 Validated Assessment Methodologies
Time-Motion Study Principles
Accurate measurement of administrative burden requires systematic application of validated time-motion study methodologies. These approaches, originally developed in industrial engineering and adapted for healthcare settings, provide objective data on how healthcare professionals actually spend their time (Zheng et al., 2011).
Core Measurement Dimensions
Effective administrative burden assessment captures five critical dimensions:
- Time Allocation: Actual time spent on different categories of administrative tasks
- Task Complexity: Cognitive load and skill requirements for different activities
- Delegation Potential: Tasks that could be handled by other staff or automated
- Regulatory Necessity: Requirements mandated by professional or legal standards
- Professional Impact: Effect on job satisfaction and professional fulfillment
Research in healthcare time allocation demonstrates that traditional estimations of time use are often inaccurate. Healthcare professionals frequently underestimate time spent on administrative tasks and overestimate time spent on direct patient care (Ammenwerth et al., 2009). This makes objective measurement essential for accurate baseline establishment.
Administrative Task Categorization
Effective measurement requires systematic categorization of administrative activities. Research-based taxonomies provide standardized frameworks for consistent data collection across different healthcare disciplines and settings.
High-Value Administrative Tasks
- • Clinical documentation with direct patient care relevance
- • Care coordination and team communication
- • Quality improvement and safety reporting
- • Patient education documentation
Low-Value Administrative Tasks
- • Redundant data entry across multiple systems
- • Insurance authorization for routine procedures
- • Scheduling and appointment management
- • Supply ordering and inventory management
3.2 Professional Burnout Assessment
Maslach Burnout Inventory Adaptation
The relationship between administrative burden and professional burnout can be measured using validated instruments adapted for healthcare settings. The Maslach Burnout Inventory, widely used in healthcare burnout research, assesses three dimensions: emotional exhaustion, depersonalization, and reduced personal accomplishment (Maslach & Jackson, 1981).
Administrative Burden-Specific Indicators
- Emotional Exhaustion: Feeling drained by paperwork rather than patient care
- Depersonalization: Reduced time for meaningful patient interaction
- Reduced Accomplishment: Administrative tasks overshadowing clinical work
- “Pajama Time”: Administrative work done at home after hours
Canadian research demonstrates strong correlations between administrative burden and burnout symptoms. A study in a Canadian mental health organization found that 61% of physicians experiencing burnout attributed it directly to EHR use (Canadian Medical Association, 2023).
Work-Life Integration Assessment
The impact of administrative burden extends beyond workplace burnout to affect overall work-life integration. Assessment tools must capture both professional and personal dimensions of administrative burden impact.
Research from Alberta demonstrates that 96% of physicians report administrative tasks negatively affect their work-life balance, while 97% find that these tasks limit their enjoyment of work (ACFP & AMA, 2023). These findings suggest that administrative burden assessment must include work-life integration measures.
3.3 Baseline Establishment and Progress Tracking
Comprehensive Baseline Metrics
Effective AI implementation requires comprehensive baseline measurement that enables accurate assessment of improvement over time. Research in healthcare quality improvement demonstrates the importance of multi-dimensional baseline assessment (Pronovost et al., 2006).
Essential Baseline Measurements
Quantitative Measures
- • Weekly hours on administrative tasks
- • Percentage of work time on administration
- • After-hours administrative work time
- • Number of administrative systems accessed daily
Qualitative Measures
- • Job satisfaction scores
- • Work-life balance ratings
- • Professional fulfillment assessment
- • Burnout risk evaluation
Progress Monitoring Framework
Successful AI implementation requires ongoing monitoring and adjustment based on measured outcomes. Implementation science research emphasizes the importance of continuous measurement and feedback loops for sustained improvement (Damschroder et al., 2009).
Evidence from Canadian healthcare AI implementations suggests that benefits often take 3-6 months to fully manifest as staff adapt to new workflows and tools become integrated into daily practice. Regular measurement during this period enables timely adjustments and optimization.
Module 1 Assignments
Assignment 1: Personal Administrative Burden Audit
Conduct a comprehensive 7-day time audit using validated time-motion study principles to establish your personal administrative burden baseline.
Assignment 2: Regulatory Compliance Assessment
Complete a comprehensive assessment of your current understanding and preparedness for AI implementation within Canadian healthcare regulatory requirements.
Assignment 3: Professional Well-being Baseline
Establish comprehensive baseline measurements for professional satisfaction, burnout risk, and work-life integration to track improvement throughout the course.
Module 1 Completion Time: 6-8 hours
Complete all assignments before proceeding to Module 2
References and Citations
Alberta College of Family Physicians & Alberta Medical Association. (2023). Decreasing Administrative Burden Report. Alberta College of Family Physicians.
Ammenwerth, E., Spötl, H. P., & Bürkle, T. (2009). Evaluation of health information systems—problems and challenges. International Journal of Medical Informatics, 78(4), 271-280.
Canadian Institute for Health Information. (2024). National Health Expenditure Trends, 2024. CIHI.
Canadian Medical Association. (2021). CMA National Physician Health Survey. Canadian Medical Association.
Canadian Medical Association. (2024). 2024 National Survey of Canadian Physicians. Canadian Medical Association.
Damschroder, L. J., Aron, D. C., Keith, R. E., Kirsh, S. R., Alexander, J. A., & Lowery, J. C. (2009). Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science, 4(1), 50.
Government of Alberta. (2003). Personal Information Protection Act. Queen’s Printer.
Government of Ontario. (2004). Personal Health Information Protection Act. Queen’s Printer for Ontario.
Government of Saskatchewan. (1999). The Health Information Protection Act. Queen’s Printer.
Health Canada. (2022). Guidance Document: Software as a Medical Device (SaMD): Classification Examples. Health Canada.
Health Canada. (2023). Pan-Canadian AI for Health (AI4H) Guiding Principles. Health Canada.
Health Canada. (2023). Reduced Administrative Burden: Nursing Retention Toolkit. Health Canada.
Health Canada, FDA, MHRA. (2021). Good Machine Learning Practice for Medical Device Development: Guiding Principles. International Medical Device Regulators Forum.
Hendrich, A., Chow, M., Skierczynski, B. A., & Lu, Z. (2008). A 36-hospital time and motion study: how do medical-surgical nurses spend their time? The Permanente Journal, 12(3), 25-34.
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99-113.
Office of the Privacy Commissioner of Canada. (2023). Principles for responsible, trustworthy and privacy-protective generative AI technologies. Office of the Privacy Commissioner of Canada.
Poissant, L., Pereira, J., Tamblyn, R., & Kawasumi, Y. (2005). The impact of electronic health records on time efficiency of physicians and nurses: a systematic review. Journal of the American Medical Informatics Association, 12(5), 505-516.
Pronovost, P., Needham, D., Berenholtz, S., Sinopoli, D., Chu, H., Cosgrove, S., … & Goeschel, C. (2006). An intervention to decrease catheter-related bloodstream infections in the ICU. New England Journal of Medicine, 355(26), 2725-2732.
Woolhandler, S., Campbell, T., & Himmelstein, D. U. (2023). Costs of health care administration in the United States and Canada. New England Journal of Medicine, 388(11), 978-980.
Zheng, K., Guo, M. H., & Hanauer, D. A. (2011). Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research. Journal of the American Medical Informatics Association, 18(5), 704-710.
Module 1 Complete
You have established a comprehensive foundation for AI implementation in healthcare
Next: Module 2 – Reclaim Professional Purpose
Learn how to optimize workflows and align AI implementation with professional values