Health Policy Exam Review PDF

Week 9 The Bite of Blood Safety: Environmental Health II 1. Overview West Nile Virus Outbreak (2002): Epidemic in Ontario and Quebec raised concerns about mosquito bites and transmission through the blood supply. Policy Responses: o Introduction of nucleic acid amplific...

Week 9 The Bite of Blood Safety: Environmental Health II 1. Overview West Nile Virus Outbreak (2002): Epidemic in Ontario and Quebec raised concerns about mosquito bites and transmission through the blood supply. Policy Responses: o Introduction of nucleic acid amplification testing (NAT) for screening. o Focused on evidence, ethics (precautionary principle), cost-effectiveness, and federal-provincial roles. 2. Environmental Health Definition (WHO): Assessing and controlling environmental factors affecting current and future generations. Approaches: Systems-based, ecological, focusing on hazards and promoting health- supportive environments. 3. Emerging Infectious Diseases (Naylor Report, 2003) Examples: Ebola (1977), West Nile Virus (2002), COVID-19. Importance of preparedness for new and spreading diseases. 4. Vector-Borne Diseases (VBDs) Transmitted by infected arthropods (e.g., mosquitoes, ticks). Examples: o Mosquitoes: West Nile Virus, Zika. o Ticks: Lyme disease. Key Principles and Frameworks Precautionary Principle Act to prevent harm despite scientific uncertainty (Rio Declaration, 1992). Emphasizes proportionality, non-discrimination, and consistent measures based on evolving science. Risk Management Framework 1. Risk Assessment: Identifies hazards, toxicity, and exposure levels to characterize risks. 2. Risk Management: Involves evaluating regulatory options and deciding on actions like remediation, communication, or policy changes. Failure Modes and Effects Analysis (FMEA) Steps: Identify failure modes, causes, and consequences. Criticality Matrix categorizes risk levels based on severity and likelihood. Economic Evaluation in Policy 1. Comparative Analysis: Compares costs and consequences of interventions. 2. Types of Evaluations: o Cost-Minimization: Focuses on cost differences when efficacy is the same. o Cost-Effectiveness: Natural units like life-years gained or cases prevented. o Cost-Utility: Uses QALY to compare diverse health outcomes. o Cost-Benefit: Includes tangible and intangible costs and benefits. Case Studies  Krever Commission (1997): Reform of Canada’s blood system post-HIV/Hepatitis C crisis. Naylor Report: Highlighted gaps in public health coordination during SARS, emphasizing federal-provincial collaboration. Public Health Renewal Focus: Population-based systems for surveillance, prevention, and health promotion. Federal/provincial roles: Federal funds vs. provincial responsibilities. Economic and Ethical Trade-Offs Balancing resources against public safety and opportunity costs. Examples: o Health system costs vs. patient outcomes. o Ethics: Balancing utilitarian goals with precautionary actions. Week 10 Overview: What to Do With the Queue? Case Study: Princess Margaret Hospital (PMH), Toronto, faced radiotherapy wait list issues. Key Challenges: o Shortages of specialists (therapists, oncologists, physicists). o 20% of patients treated within 4 weeks (CARO recommendation); nearly 50% waited over 8 weeks. Policy Issues: o Managing wait lists. o Ethics of rationing care. o Payment mechanisms and human resource planning. Framing the Problem 1. Distribution: o Send patients to less-demanded centers, raising ethical concerns (e.g., being away from family). 2. Human Resources (HHR): o Address staffing shortages. o Improve wages and work conditions. o Extend machine operation hours. 3. Management: o Establish oversight bodies to coordinate and manage wait times. Key Concepts: Queue Theory and Management Definition: Managing lines or sequences of patients waiting for treatment. Types of Queues: o Single line (first-in, first-out). o Multiple lines. o Prioritized queues (e.g., moving critical patients ahead). Key Metrics: o 𝞺 (rho): Resource utilization ratio. ! Formula: 𝜌 = " ∙ %  Where: § 𝜆 (lambda) = rate at which patients arrive. § s = number of healthcare providers (servers). § 𝜇 (mu) = rate at which patients are treated per provider. § 𝞺 must remain 1 indicate backlog reduction;