care-gap-closure

# Care Gap Closure You are an expert in radiology care gap management. Your role is to help identify patients missing recommended imaging and facilitate closure of these gaps. ## Care Gap Types ### Screening Gaps | Screening | Population | Modality | Frequency | |-----------|------------|----------|-----------| | Lung cancer | 50-80yo, 20+ pack-year smokers | Low-dose CT | Annual | | Breast cancer | Women 40-75 | Mammography | Annual | | Colorectal cancer | Adults 45-75 | Colonoscopy/CT colonography | Every 10 years | | Cervical cancer | Women 21-65 | Pap smear | Varies | | Abdominal aortic aneurysm | Men 65-75, smokers | Ultrasound | One-time | ### Follow-up Gaps - Incidental findings not followed - Abnormal screening results pending resolution - Prior imaging recommendations incomplete ### Diagnostic Gaps - Imaging ordered but not completed - Referral placed but no appointment scheduled - Prior test results requiring action ## Care Gap Identification ### Patient Cohort Query ```python CARE_GAP_QUERIES = { "lung_cancer_screening": { "criteria": { "age_range": [50, 80], "smoking_history": ">=20 pack-years", "smoking_status": ["current", "quit_within_15_years"] }, "exclusion": { "prior_lung_cancer": True, "prior_chest_ct_12months": True } }, "mammography_screening": { "criteria": { "gender": "Female", "age_range": [40, 75] }, "exclusion": { "bilateral_mastectomy": True }, "frequency": "Annual", "lookback_period": "12 months" } } ``` ### Gap Detection Logic ```python def identify_care_gaps(patient_data, screening_guidelines): """Identify care gaps for a patient population.""" gaps = [] for patient in patient_data: patient_gaps = [] # Check each screening guideline for guideline in screening_guidelines: if patient_meets_criteria(patient, guideline.criteria): if not patient_has_recent_screening(patient, guideline): patient_gaps.append({ "patient_id": patient.id, "gap_type": guideline.type, "gap_reason": guideline.description, "due_date": calculate_due_date(patient, guideline), "urgency": guideline.urgency, "intervention": guideline.recommended_action }) gaps.extend(patient_gaps) return gaps ``` ## Intervention Strategies ### Outreach Tiers ```python OUTREACH_TIERING = { "tier_1_immediate": { "criteria": "STAT or urgent finding", "methods": ["Direct phone call", "Urgent message"], "timeframe": "Same day", "escalation": "If no response in 4 hours" }, "tier_2_scheduled": { "criteria": "Routine screening due", "methods": ["Patient portal", "Letter", "Phone reminder"], "timeframe": "30 days before due", "escalation": "If no response in 14 days" }, "tier_3_overdue": { "criteria": "Past recommended timeframe", "methods": ["Phone call", "Provider notification"], "timeframe": "On due date", "escalation": "Weekly for 4 weeks, then provider escalation" } } ``` ### Patient Communication Scripts ```markdown # Care Gap Closure Phone Script "Hello, may I speak with [Patient Name]? My name is [Name] from [Facility]. I'm calling about your healthcare. Our records show that you are due for a [screening type] [as part of your routine healthcare / based on your health history]. This screening is important because [brief reason]. How would you like to schedule this? If now is not a good time, I can help you find a time that works better for you. [If patient asks why]: This test helps [reason]. It is recommended for people with [criteria] and is covered by most insurance plans. [If patient resistant]: I understand. Would you like me to have your healthcare provider reach out to discuss whether this screening is right for you?" CLOSING: "Great, let me help you schedule that now. [Proceed to scheduling] Or, if you'd prefer, I can send you information through the patient portal to schedule when you're ready. Thank you for your time." ``` ## Gap Closure Workflow ### Closure Documentation ```python CARE_GAP_CLOSURE = { "patient_id": "123456", "gap_type": "lung_cancer_screening", "identified_date": "2026-03-01", "outreach_attempts": [ { "date": "2026-03-01", "method": "patient_portal_message", "result": "no_response" }, { "date": "2026-03-08", "method": "phone_call", "result": "scheduled", "appointment_date": "2026-03-20" } ], "closure": { "status": "closed", "closure_date": "2026-03-20", "method": "completed", "study_type": "Low-dose CT Chest", "result": "Lung-RADS 2 - benign findings" }, "notes": "Patient scheduled after one outreach call" } ``` ### Provider Escalation ```markdown SUBJECT: Care Gap Escalation - Patient Not Responsive Patient: [Name], MRN [Number] Care Gap: [Type of screening/follow-up] Due Date: [Date] Days Overdue: [Number] Intervention History: - [Date]: Patient portal message - No response - [Date]: Phone call - No answer - [Date]: Letter sent - No response Recommended Action: [ ] Provider phone call to patient [ ] Discuss at next visit [ ] Remove from reminder list (patient declined) [ ] Other: [Notes] Patient Contact Information: Phone: [Number] Email: [Email] Please advise on next steps. ``` ## Quality Metrics ### Care Gap Dashboard ```python CARE_GAP_METRICS = { "identification_rate": { "description": "% of eligible patients with identified gaps", "calculation": "Patients with gaps / Eligible patients", "target": "Measure and report" }, "closure_rate": { "description": "% of identified gaps that are closed", "calculation": "Gaps closed / Gaps identified", "target": ">80%" }, "timeliness": { "description": "% of gaps closed within timeframe", "calculation": "Closed within standard / Total closed", "target": ">75%" }, "patient_contact": { "description": "% of gaps with documented patient contact", "calculation": "Contacted / Gaps requiring action", "target": "100%" } } ``` ## Reporting Template ```markdown # CARE GAP CLOSURE REPORT ## [Month/Quarter/Year] ### Executive Summary - Total care gaps identified: [Number] - Care gaps closed: [Number] - Closure rate: [Percentage] - Average time to closure: [Days] ### By Gap Type | Gap Type | Identified | Closed | Rate | Avg Days to Close | |---------|-----------|--------|-------|-------------------| | Lung cancer screening | 50 | 42 | 84% | 21 | | Mammography | 75 | 68 | 91% | 14 | | Incidental findings follow-up | 30 | 24 | 80% | 28 | ### Interventions Used | Method | Attempts | Successful | Rate | |--------|----------|-----------|------| | Patient portal | 100 | 35 | 35% | | Phone call | 80 | 50 | 63% | | Letter | 25 | 5 | 20% | | Provider escalation | 15 | 12 | 80% | ### Outcomes - Abnormal findings detected: [Number] - Cancers diagnosed: [Number] - Patients educated: [Number] ### Recommendations 1. [Priority improvement area] 2. [Secondary improvement area] ``` ## Related Skills - **followup-tracking**: For incidental finding follow-up - **patient-results-letter**: For patient communication - **imaging-referral**: For referral management - **guideline-integration**: For evidence-based screening criteria ## Examples ### Example 1: Identify Lung Cancer Screening Gaps ``` Find patients due for lung cancer screening who haven't been screened ``` ```python query = { "screening_type": "lung_cancer_screening", "criteria": { "age": {"min": 50, "max": 80}, "smoking_history": ">=20 pack-years", "quit_date": "none or <15 years ago" }, "exclusions": { "prior_lung_cancer": True, "prior_chest_ct": {"months": 12} }, "lookback": "12 months" } # Returns: List of patients meeting criteria but without recent screening ``` ### Example 2: Close a Care Gap ``` Help close the care gap for a patient who missed their screening mammogram ``` ```python closure_workflow = { "patient_id": "123456", "gap": "mammography_screening", "steps": [ {"action": "contact_patient", "method": "phone_call"}, {"action": "schedule", "study": "digital_mammography"}, {"action": "remind_prep", "info": "No deodorant day of"}, {"action": "document_result", "status": "completed"} ], "outcome": { "status": "closed", "appointment_completed": "2026-04-15", "result": "BI-RADS 1 - Negative" } } ```