access-friction-detector

# Access Friction Detector ## Overview This skill detects and quantifies friction points that prevent or delay patients from accessing healthcare services. It evaluates access across five core dimensions aligned with the Penchansky-Thomas Access Framework: availability, accessibility, accommodation, affordability, and acceptability. The analysis incorporates CMS network adequacy standards, ADA compliance requirements, and health equity benchmarks to produce actionable findings with regulatory context. ## When to Use - Evaluating access barriers after patient complaint trend analysis reveals scheduling or availability themes - Preparing for NCQA accreditation or CMS network adequacy reviews - Assessing health equity impact of service changes (clinic closures, hour reductions, telehealth transitions) - Investigating disparities in appointment wait times, no-show rates, or patient leakage by demographic - Supporting Community Health Needs Assessment (CHNA) access components - Designing patient access center workflows or digital front-door strategies ## Required Inputs | Input | Description | Format | |-------|-------------|--------| | `appointment_data` | Scheduling records with request date, appointment date, type, location, provider | De-identified CSV/JSON | | `patient_demographics` | Aggregate demographic data (zip code, language, insurance, age, disability) | JSON array | | `facility_locations` | Addresses and service hours for all access points | JSON array | | `payer_mix` | Insurance type distribution across patient population | JSON object | | `complaint_data` | Access-related complaints categorized by theme | JSON array | | `telehealth_utilization` | Virtual visit adoption rates by service and demographic | JSON object | | `referral_data` | Referral completion rates and time-to-appointment | JSON object | ## Methodology ### Step 1: Availability Analysis - Calculate third-next-available appointment (TNAA) by provider, specialty, and location - Benchmark against specialty-specific access standards: - Primary care: 7 days or fewer for routine, 48 hours or fewer for urgent - Specialty care: 14 days or fewer for routine referrals - Behavioral health: 10 business days or fewer (per NCQA) - Post-discharge follow-up: 7 days or fewer (per CMS readmission reduction) - Identify capacity bottlenecks by day of week, time of day, and provider panel saturation - Flag providers operating above 85% panel capacity as at-risk for access degradation ### Step 2: Accessibility Analysis (Geographic and Physical) - Compute drive-time and public-transit-time isochrones from patient zip code centroids to facilities - Apply CMS time-distance standards: - Primary care: 30 min / 15 miles (urban), 60 min / 60 miles (rural) - Specialty: 60 min / 30 miles (urban), 120 min / 75 miles (rural) - Assess ADA physical accessibility for each facility (parking, entrance, exam room, equipment) - Evaluate public transportation proximity (within 0.5 miles from transit stop) - Map geographic deserts where access standards are not met ### Step 3: Accommodation Analysis - Evaluate scheduling flexibility: - Extended hours availability (before 8 AM, after 5 PM, weekends) - Same-day and walk-in capacity - Online self-scheduling adoption rate - Cancellation and reschedule ease (number of steps, channels available) - Assess communication accommodation: - Language services availability (interpreter access within 10 minutes per LEP standards) - TTY/TDD availability for deaf and hard-of-hearing patients - Health literacy accommodations in intake and instructions ### Step 4: Affordability Analysis - Analyze cost-related access barriers: - Percentage of patients with high-deductible health plans (HDHP) - Financial assistance and charity care application rates and approval rates - Copay and cost-sharing transparency at point of scheduling - Prescription affordability barriers flagged in clinical notes (de-identified aggregate) - Identify insurance-related friction: - Prior authorization denial rates and average turnaround time - Out-of-network referral frequency - Medicaid acceptance gaps across specialties ### Step 5: Acceptability Analysis - Evaluate cultural and trust barriers: - Provider demographic concordance rates (race, ethnicity, gender, language) - Patient-reported experience scores segmented by demographic group - Trust indicators from community health assessments - Cultural competency training completion rates among staff - Assess digital acceptability: - Patient portal adoption by age group and digital literacy level - Telehealth utilization disparities by race, age, rurality, and insurance - Digital divide indicators (broadband access rates by patient zip code) ### Step 6: Friction Scoring and Prioritization - Assign composite friction scores per dimension (0-100): - 0-25: Low friction (meeting standards) - 26-50: Moderate friction (approaching risk) - 51-75: High friction (below standards, action needed) - 76-100: Critical friction (regulatory or equity risk) - Aggregate into an overall Access Friction Index (AFI) - Rank barriers by population impact (number of patients affected multiplied by severity) ## Output Specification ```yaml access_friction_report: analysis_date: date population_scope: string overall_afi_score: number dimension_scores: availability: number accessibility: number accommodation: number affordability: number acceptability: number critical_barriers: - dimension: string barrier_description: string affected_population: string patient_count_estimate: number severity: string regulatory_reference: string recommendation: string geographic_gaps: - area: string population: number nearest_facility_minutes: number standard_exceeded_by: number equity_disparities: - metric: string advantaged_group_value: number disadvantaged_group_value: number gap_percentage: number recommendations: - action: string priority: string estimated_impact: string timeline: string ``` ## Analysis Framework Use the **Penchansky-Thomas 5A Framework** enhanced with equity stratification: | Dimension | Core Question | Key Metrics | |-----------|--------------|-------------| | Availability | Is there enough supply? | TNAA, panel size, provider FTE | | Accessibility | Can patients get there? | Drive time, transit time, ADA compliance | | Accommodation | Does the system flex for patients? | Hours, channels, language services | | Affordability | Can patients pay? | HDHP rates, PA denials, charity care | | Acceptability | Will patients engage? | Concordance, cultural competency, digital divide | ## Examples **Example: Urban Health System Access Audit** - Availability: TNAA for dermatology = 47 days, CRITICAL (benchmark: 14 days) - Accessibility: 12% of Medicaid patients live more than 45 min from nearest PCP, HIGH - Accommodation: Online scheduling available for only 3 of 12 specialties, MODERATE - Affordability: PA denial rate for behavioral health = 31%, HIGH - Acceptability: Telehealth adoption among 65+ = 8% vs. 45% overall, Equity gap flagged - Overall AFI: 62/100, HIGH friction, priority intervention recommended ## Guidelines - **HIPAA Compliance**: All analysis must use de-identified or aggregate data. Geographic analysis should use zip code or census tract level, never individual addresses. Complaint data must be stripped of PHI before ingestion. - **Regulatory Alignment**: Reference CMS network adequacy standards (42 CFR 438.68), ADA Title III requirements, and Section 1557 language access provisions in findings. - **Equity-First Approach**: Always stratify findings by race, ethnicity, language, insurance type, disability status, and rurality. Report disparities explicitly. - **Actionability**: Every identified barrier must include at least one specific, implementable recommendation with timeline and responsible party. - **Community Input**: Validate findings with patient advisory councils and community health workers when possible. ## Validation Checklist - [ ] All five access dimensions analyzed with quantitative metrics - [ ] Benchmarks sourced from CMS, NCQA, or evidence-based standards - [ ] Geographic analysis uses time-distance standards appropriate to urban/rural classification - [ ] Equity stratification completed across minimum 4 demographic dimensions - [ ] No PHI present in any output artifact - [ ] Regulatory references cited for all standard comparisons - [ ] Recommendations are specific, actionable, and time-bound - [ ] Access Friction Index calculated with transparent methodology - [ ] Findings validated against patient complaint data for consistency - [ ] Report formatted for executive and operational audiences