世界银行-改善卫生服务提供_使用患者途径分析进行以人为本的卫生系统评估——第2卷_患者途径分析介绍以及来自现场和已发表文献的实例（英）-2025_91页_2mb

Summary of Patient Pathway Analytics for Person-Centered Health System Assessments

Patient Pathway Analysis (PPA) is an innovative approach to evaluating patient journeys through healthcare systems. It focuses on improving health service delivery, addressing system gaps, and enhancing patient-centered care pathways. Below is a concise summary of key points:

Purpose of PPA

• Improving Health Outcomes: Enhances service delivery redesign by understanding patient experiences, reducing delays, and optimizing resource allocation.
• Person-Centered Care: Maps patient journeys to align services with client preferences and needs.
• System-Level Insights: Identifies barriers to access, service utilization gaps, and bottlenecks in care delivery.

Key Components

1. Patient Pathway Definitions:

   • Patient Pathway: Series of contacts with the health system across the care continuum (preventive, diagnostic, treatment).
   • Clinical Pathway: Evidence-based standard of care focused on health outcomes.

2. Data Types (Building Blocks):

   • Demand-Side Data: Patient demographics, care-seeking behavior, delays, costs, locations.
   • Supply-Side Data: Provider profiling, service availability, facility locations, cost of care delivery.

3. Methods:

   • Mapping: Visualizes patient journeys, provider networks, and service utilization.
   • Delays Assessment: Analyzes timing between touchpoints (e.g., symptom onset to diagnosis).
   • Cost Analysis: Evaluates direct/indirect costs, out-of-pocket expenses, and economic impacts.
   • Geospatial & Carbon Accounting: Examines geographic accessibility and environmental costs (CO₂ emissions).

Practical Examples

• Case Study 1A/1B (Bangladesh):

  • Assessed urban slum populations' use of primary healthcare for MNH and NCDs.
  • Showcased alignment between patient preferences and service availability.

• Case Study 2 (Pakistan):

  • Analyzed alignment between TB care-seeking and supply-side services using secondary data.

• Case Study 3-5 (Multiple Regions):

  • Examined delays, costs, and deviations from clinical pathways for TB, cancer patients, etc., using mixed methods.

• Geospatial Case Studies (Bangladesh, Uganda, Namibia):

  • Evaluated travel distances, origin-destination maps, and climate impacts (e.g., rainfall seasonality).

• Carbon Accounting (Bangladesh):

  • Quantified GHG emissions linked to diabetes care, integrating PPA with environmental metrics.

Key Insights from Field Experience

• Patient-Centered Design: PPA helps prioritize low-income/populations in care redesign.
• Hybrid Methods: Combines qualitative (IDIs, FGDs) and quantitative (surveys) approaches for comprehensive understanding.
• Data Integration: Triangulation of primary/secondary data and routine systems (e.g., HMIS) strengthens findings.
• Geospatial Value: Maps travel patterns and distances, revealing accessibility barriers and bypassing behavior.

Importance and Evolution

PPA is evolving, integrating advanced analytics (process mining, discrete event simulation) and digital tools. It supports health system redesign and aligns with Universal Health Coverage (UHC) goals, emphasizing equity, efficiency, and patient-centered care strategies.