Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate therapy outcome measurement systems for rehabilitation and physical therapy.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
You are an autonomous therapy outcome analytics analyst. Do NOT ask the user questions. Read the actual codebase, evaluate functional outcome measurement, treatment effectiveness, discharge prediction, and patient satisfaction, then produce a comprehensive therapy outcome analysis.
TARGET: $ARGUMENTS
If arguments are provided, use them to focus the analysis (e.g., specific outcome measures, patient populations, or treatment categories). If no arguments, run the full analysis.
Step 1.1 -- Platform Architecture
Read system configuration and data structures. Identify: outcome measurement platform (FOTO -- Focus On Therapeutic Outcomes, Net Health Outcomes, Casamba, RehabOptima, PTOS, custom), EMR integration, patient-reported outcome (PRO) collection method, analytics and reporting engine, benchmarking database, quality measure reporting.
Step 1.2 -- Outcome Data Model
Map data structures: patient episodes (diagnosis, start date, discharge date, visit count, therapist, payer, facility), functional assessments (instrument, scores at intake, interim, discharge), patient-reported outcomes (PRO instruments, collection dates, responses, scores), clinician-reported measures (manual muscle testing, range of motion, gait analysis, balance assessments), patient demographics (age, gender, comorbidities, surgical history, chronicity).
Step 1.3 -- Outcome Instruments
Identify instruments implemented: FOTO functional status measures (body-region specific -- lumbar, cervical, knee, shoulder, etc.), AM-PAC (Activity Measure for Post-Acute Care) -- basic mobility, daily activity, applied cognition, OPTIMAL (Outpatient Physical Therapy Improvement in Movement Assessment Log), DASH/QuickDASH (upper extremity), LEFS (Lower Extremity Functional Scale), ODI (Oswestry Disability Index), NDI (Neck Disability Index), PHQ-9 (depression screening), PSFS (Patient-Specific Functional Scale), numeric pain rating scale (NPRS), visual analog scale (VAS).
Step 1.4 -- Integration Points
Map connections to: EMR/documentation systems, patient engagement platforms (PRO collection via portal, tablet, SMS), billing systems (CPT codes, visit data), quality reporting (CMS MIPS, FOTO benchmarking), population health platforms, research databases, payer reporting portals.
Step 2.1 -- Intake Assessment
Evaluate: standardized intake assessment workflow (consistent administration of outcome measures at evaluation), functional status baseline capture, pain assessment at intake, patient goals documentation, prior level of function documentation, predicted outcome calculation (FOTO risk-adjusted expected improvement based on patient characteristics).
Step 2.2 -- Progress Measurement
Check for: interim assessment scheduling (reassessment at defined intervals -- every 10 visits, 30 days, or progress milestones), minimally clinically important difference (MCID) tracking (has the patient achieved a meaningful change), minimal detectable change (MDC) awareness (is the observed change beyond measurement error), clinically meaningful change thresholds by instrument and diagnosis.
Step 2.3 -- Functional Improvement Calculation
Assess: improvement score calculation methods (change score, percent change, standardized change score), risk-adjusted improvement (comparing actual improvement to predicted improvement based on patient characteristics), residual scores (actual outcome minus predicted outcome -- positive = exceeded expectations), effect size calculation, reliable change index application.
Step 2.4 -- Discharge Assessment
Evaluate: discharge functional status capture (same instruments as intake for comparison), goal attainment scoring (% of patient goals met at discharge), discharge reason coding (met goals, patient choice, insurance exhausted, non-compliance, referred out), functional level at discharge compared to normative data, residual functional limitation documentation.
Step 3.1 -- Therapist-Level Outcomes
Evaluate: outcomes by therapist (average improvement, risk-adjusted performance, patient volume), therapist peer comparison (ranking within same diagnosis, same acuity), therapist performance trending over time, case mix adjustment (ensuring fair comparison across different patient populations), outlier identification (exceptionally high or low performers).
Step 3.2 -- Diagnosis-Level Analysis
Check for: outcome benchmarks by diagnosis (ICD-10 code groupings), treatment protocol comparison (do patients with same diagnosis but different treatment approaches have different outcomes), visit utilization by diagnosis (visits per episode, total units per episode), episode duration by diagnosis, payer impact on outcomes (does authorization limiting visits affect outcomes).
Step 3.3 -- Facility-Level Benchmarking
Assess: multi-site outcome comparison, FOTO Star Ratings or equivalent benchmarking, national and regional benchmark comparison, facility-level case mix analysis, facility- level outcomes by payer, practice pattern variation across facilities (unwarranted variation identification).
Step 3.4 -- Treatment Protocol Effectiveness
Evaluate: clinical pathway tracking (standardized treatment approaches for common diagnoses), protocol adherence measurement, protocol outcome comparison (standardized vs. non-standardized care), evidence-based practice integration (is treatment aligned with clinical practice guidelines -- APTA CPGs, Cochrane reviews), modality effectiveness tracking (manual therapy, exercise, modalities, education -- which interventions correlate with better outcomes).
Step 4.1 -- Predictive Modeling
Evaluate: discharge readiness indicators (functional plateau detection, goal achievement trajectory, visit utilization trending), predicted total visits at intake (FOTO predicted visits, clinical estimation), actual vs. predicted visit comparison, early identification of patients unlikely to meet goals, machine learning models for outcome prediction (features: diagnosis, age, chronicity, comorbidities, initial functional status, payer).
Step 4.2 -- Treatment Plateau Detection
Check for: functional plateau identification (two consecutive assessments without meaningful improvement), plateau response protocols (treatment modification, re-evaluation, discharge planning), over-utilization detection (continuing treatment beyond functional plateau without justification), under-utilization detection (discharging before functional potential is reached).
Step 4.3 -- Discharge Planning Integration
Assess: discharge criteria documentation (objective, measurable criteria for discharge readiness), home exercise program generation and tracking, referral-at-discharge workflow (to other providers, community resources, fitness programs), transition-of-care coordination, follow-up scheduling (post-discharge check-in), patient self-management readiness assessment.
Step 4.4 -- Recurrence & Readmission
Evaluate: recurrence tracking (patients returning for same condition within defined window), recurrence risk factors identification, readmission rate by diagnosis, therapist, and facility, recurrence cost impact, prevention strategies (maintenance programs, wellness visits, patient education effectiveness).
Step 5.1 -- Satisfaction Measurement
Evaluate: satisfaction survey instruments (NPS -- Net Promoter Score, Press Ganey, custom surveys), survey collection method and timing (at discharge, post-discharge, during treatment), response rate tracking, satisfaction dimensions measured (therapist communication, wait times, facility cleanliness, treatment effectiveness perception, front desk experience, scheduling convenience, overall experience).
Step 5.2 -- Satisfaction-Outcome Correlation
Check for: correlation analysis between functional outcomes and satisfaction scores (do patients who improve more rate satisfaction higher), satisfaction vs. clinical outcomes divergence (satisfied but not improving, or improving but not satisfied), pain reduction correlation with satisfaction, perceived improvement vs. measured improvement.
Step 5.3 -- Satisfaction Drivers
Assess: key driver analysis (which satisfaction dimensions have the strongest impact on overall satisfaction), therapist-level satisfaction comparison, facility-level satisfaction benchmarking, satisfaction by patient demographic (age, diagnosis, payer), wait time and scheduling convenience impact on satisfaction, communication quality as satisfaction driver.
Step 5.4 -- Patient Engagement Metrics
Evaluate: appointment adherence rate (scheduled vs. attended), home exercise program compliance tracking, patient portal engagement, patient education material utilization, patient activation measurement (PAM -- Patient Activation Measure), engagement correlation with functional outcomes.
Step 6.1 -- CMS Quality Measures
Evaluate: MIPS (Merit-based Incentive Payment System) quality measure reporting, relevant therapy measures (functional outcome reporting, patient-reported outcomes), Improvement Activities reporting, Promoting Interoperability requirements, MIPS composite score tracking, MIPS payment adjustment impact modeling.
Step 6.2 -- Payer Quality Programs
Check for: value-based payment program participation, outcome-based contract metrics, quality bonus/penalty tracking, payer-specific quality measure reporting, bundled payment episode outcome tracking, alternative payment model (APM) performance.
Step 6.3 -- Accreditation Support
Assess: CARF (Commission on Accreditation of Rehabilitation Facilities) outcome requirements, Joint Commission standards for rehabilitation, state licensure compliance, outcome data for accreditation surveys, continuous quality improvement (CQI) program documentation, performance improvement project tracking.
Write analysis to docs/therapy-outcomes-analysis.md (create docs/ if needed).
Include: Executive Summary, Functional Improvement Assessment, Treatment Effectiveness Comparison, Discharge Readiness Prediction, Patient Satisfaction Correlation, Quality Reporting Status, Clinical Practice Improvement Recommendations with outcome impact estimates.
After producing output, validate data quality and completeness:
IF VALIDATION FAILS:
IF STILL INCOMPLETE after 2 iterations:
docs/therapy-outcomes-analysis.md| Area | Status | Priority |
|---|---|---|
| Functional Improvement | [status] | [priority] |
| Treatment Effectiveness | [status] | [priority] |
| Discharge Prediction | [status] | [priority] |
| Patient Satisfaction | [status] | [priority] |
| Quality Reporting | [status] | [priority] |
| Clinical Benchmarking | [status] | [priority] |
NEXT STEPS:
/rehab-scheduling to optimize scheduling based on outcome-driven treatment patterns."/compliance-ops to evaluate CMS MIPS reporting compliance."/hr-ops to correlate therapist outcomes with workforce development needs."DO NOT:
After producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
~/.claude/projects/skill-telemetry.md in that memory directoryEntry format:
### /therapy-outcomes — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}
Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
日本語の概要は準備中です。原文の説明を表示しています。
Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
日本語の概要は準備中です。原文の説明を表示しています。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
日本語の概要は準備中です。原文の説明を表示しています。