Epic Cadence Analyst II — BMCHS — Work Sample

Rebuilding Patient Access for a 14-Facility Health System

A scenario-based technical proposal demonstrating end-to-end Epic Cadence configuration, HL7 referral integration, scheduling governance, and access metric improvement across an ambulatory network with 240 active providers.

No-Show Rate
18% → 8%
-56% via predictive outreach and reminder automation
Template Utilization
+23 pts
62% to 85% through hold pool governance
Referral Capture
71% → 92%
HL7 REF interface and closed-loop workqueue

Executive Summary

Northeast Regional Health (NRH) is a 14-facility community health system with 240 active providers running Epic 2023. After a Cadence go-live in March 2022, uncoordinated local build decisions created 847 active visit types (industry benchmark: ~120 for a network this size), no referral workqueue governance, and provider templates modified ad hoc via email with no change ticket and no UAT review.

The result: an 18% no-show rate, 62% template utilization, a scheduling cycle time of 4.2 days, and a 3rd Next Available averaging 12 days across specialties. Referral capture sits at 71%, with 29% of external referrals abandoned or directed to competitor systems.

This proposal rebuilds Cadence configuration under a structured governance framework: visit type rationalization, template standardization, HL7-based external referral capture, and MyChart self-scheduling expansion. Targets within 12 months: 8% no-show rate, 85% utilization, 1.8-day cycle time, 92% referral capture, and 4-day 3rd Next Available.

847
target: ~120
Active Visit Types
62%
target: 85%
Template Utilization
4.2 d
target: 1.8 d
Scheduling Cycle Time
12 d
target: 4 d
3rd Next Available
18%
target: 8%
No-Show Rate
71%
target: 92%
Referral Capture

Scenario

Northeast Regional Health (NRH) is a fictional composite representative of a mid-size regional health system. All metrics and configurations in this proposal are based on realistic industry figures.

Organization

14 ambulatory clinics: primary care (6), specialty (5), behavioral health (2), urgent care (1)

Scale

240 active scheduling providers, 180 scheduling staff with Cadence access across all facilities

Epic Environment

Hyperspace 2023, Cadence go-live March 2022 (28 months), MyChart live with self-scheduling for 3 visit types

Referral Intake

Inbound referrals via Kofax fax capture and phone; manually entered into Epic referral orders

Governance Gap

No scheduling CAB, no visit type naming convention, no formal change ticket process for Cadence builds

Analyst Role

Remote Cadence analyst; owns full application lifecycle: build, validation, training, optimization, and metrics

Current State Assessment

Visit Type Sprawl

847 active visit types versus an industry benchmark of roughly 120 for a network this size. Individual clinics created new types rather than reusing existing ones: 23 near-identical variants of "Primary Care Follow-Up" exist across 6 primary care sites, each with slightly different durations and conflicting rule group memberships. Schedulers average 45 extra seconds per call searching for the correct type, compounding across 1,800+ calls per day. Visit types from providers who left 18+ months ago remain active, cluttering the pick list and occasionally booking into templates that no longer exist.

Template Fragmentation

Template utilization at 62% reflects providers who block or release slots manually rather than relying on structured hold pools. Some clinics reserve 30% of slots for same-day access; others reserve none, leaving urgent patients without a path. The 3rd Next Available averages 12 days system-wide when clinical staffing comfortably supports 4-day access under a rationalized template structure.

Referral Leakage

The 71% referral capture rate means 29% of external referrals are abandoned, entered with missing data, or sent to a competitor facility. Referring physicians call to check referral status 60-80 times per week, diverting scheduling staff from appointment booking. There is no closed-loop notification back to referring providers when an appointment is confirmed, and no tracking of time-to-schedule from referral receipt.

No-Show Pattern

An 18% no-show rate is driven by inconsistent reminder cadence (each clinic managing reminders independently), no identification of high-risk patient segments, and informal overbooking decisions made by individual schedulers without a policy framework. Epic's predictive no-show model is available in the environment but not configured.

MetricCurrentTargetIndustry Benchmark
No-show rate18%8%5-10%
Template utilization62%85%80-90%
Avg scheduling cycle time4.2 days1.8 days1-3 days
Referral capture rate71%92%85-95%
3rd Next Available (3NA)12 days4 days3-7 days
Scheduling WQ avg age9.3 days2 daysunder 3 days
Patient self-scheduling rate12%35%25-40%
Reminder opt-in rate67%90%80-95%

Proposed Solution

Four phases over 12 months, each with measurable outcomes before the next begins.

Phase 1 • Months 1-3

Visit Type Governance

Audit 847 types, merge to ~120, establish naming convention and CAB process

Phase 2 • Months 4-6

Template Standardization

5 base template frameworks with structured hold pools and overbook policy

Phase 3 • Months 7-9

Referral Workflow Rebuild

HL7 REF interfaces, referral WQ, closed-loop notifications, referral dashboard

Phase 4 • Months 10-12

MyChart + Predictive

Expand self-scheduling to 22 types, SmartText reminders, predictive no-show model

Phase 1: Visit Type Rationalization

  1. Run Crystal report pulling all visit types with appointment counts for the past 12 months
  2. Identify types with 0 appointments: route to clinical lead for inactivation review; no types touched until sign-off
  3. Map remaining types to naming convention: [DEPT]-[TYPE]-[DURATION_MIN] (e.g., PC-NEW-60, CARD-FU-30, BH-INTAKE-90)
  4. Merge near-duplicate types within each specialty cluster; update scheduling rules to point to consolidated types
  5. Stand up Cadence Change Advisory Board (CAB): bi-weekly cadence; all visit type additions, template changes, and rule group edits require a change ticket
  6. Revise super user role access: remove scheduling rule group edit rights; restrict to analyst team only

Phase 2: Template Framework

Five base templates cover all ambulatory visit patterns. Individual provider preferences apply as modifiers on top of the framework, not as standalone custom templates.

FrameworkSlot DurationUrgent HoldSame-Day HoldCare Gap Hold
PCP New Patient60 min2 per half-day0 (converts at 48 hr)1 per half-day
PCP Follow-Up15 min1 per 90 min1 per 90 min (releases 8 AM day-of)1 per 90 min
Specialty New45 min1 per half-daynonenone
Specialty Follow-Up20 min1 per half-daynonenone
ProcedurePer typenonenonenone

Overbook policy: maximum 1 overbook per half-day session, requires scheduling supervisor approval, logged in Cadence configuration.

Configuration environment: all changes built in TST, clinical lead UAT sign-off before promotion. PRD changes scheduled in maintenance windows for high-impact items (rule group restructuring, template framework rollouts). Build steps documented in SharePoint config tracker before and after every change.

HIPAA and Security

Every scheduling workflow carries PHI. Cadence configuration decisions are compliance decisions. These controls are built into the solution from the start, not added as an afterthought.

Role-Based Access (RBAC)

Schedulers provisioned with Cadence-only roles scoped to their clinic. No access to clinical documentation outside the scheduling context. Access audited quarterly; deactivated within 24 hours of role change.

MPI Identity Verification

Patient identity confirmed before scheduling: name, DOB, address, last 4 of phone. MPI duplicate alerts enabled; duplicate MRN creation triggers supervisor notification.

PHI in Reminders

Patient communication preferences honored. Voicemail scripts reviewed for minimum necessary PHI. Opt-out removes patient from all automated reminder workflows immediately.

HL7 Message Security

SIU messages contain PHI. Bridges interfaces configured for TLS 1.2+ only. No routing to cleartext endpoints. Interface credentials managed in Bridges, not in plain-text config files.

Audit Logging

All Cadence access logged. Rule group changes flagged in weekly security review. Anomalous patterns (unexpected access times, bulk record viewing) escalated to security officer.

Break the Glass

Emergency same-day overrides outside normal scheduling rules require documentation. Every instance reviewed by the security officer. Used sparingly, logged permanently.

HIPAA Context for Scheduling

Scheduling Templates and Rules

Visit Type as Configuration Decision

A visit type in Cadence controls more than a name and duration. It determines which scheduling channels can use it, which questionnaires fire, whether MyChart self-scheduling is permitted, what check-in behavior triggers, and which scheduling rule groups include it. Naming convention standardization makes every downstream decision cleaner.

Before: 23 near-identical "PCP Follow-Up" variants with inconsistent durations and conflicting rule group memberships.
After: 1 canonical PC-FU-15 type with clinic-specific differences handled at the scheduling rule level.

Hold Pool Structure (PCP Follow-Up Template, Sample Day)

PROVIDER TEMPLATE, Dr. Rivera, PCP, Monday Full Day (PC-FU-15 framework) 08:00 [ PC-FU-15 ] standard slot 08:15 [ PC-FU-15 ] standard slot 08:30 [ PC-FU-15 ] standard slot 08:45 [ URGENT ] -- held for same-day urgent; releases to standard at 48hr before date 09:00 [ PC-FU-15 ] standard slot 09:15 [ CARE-GAP ] -- routes to care management WQ for proactive outreach 09:30 [ PC-FU-15 ] standard slot 09:45 [ PC-FU-15 ] standard slot 10:00 [ PC-FU-15 ] standard slot 10:15 [ SAME-DAY ] -- visible to schedulers only after 8:00 AM day-of 10:30 [ PC-FU-15 ] standard slot ... Hold Release Rules: URGENT : converts to open standard slot 48hr before appointment date if unfilled SAME-DAY : visible to scheduler starting 8:00 AM on appointment date CARE-GAP : routes to care management workqueue; care team contacts patient proactively

Scheduling Rule Group Structure

One rule group per department cluster governs which staff roles can book which visit types, via which channels, and under what constraints. Rule groups replace the ad hoc, per-clinic configurations that created the current fragmentation.

Rule GroupVisit Types CoveredChannels PermittedLead Time Constraint
PC-PRIMARY-RULESAll PC-* visit typesPhone, MyChart, Walk-inNew pt: min 2 days advance
CARD-RULESAll CARD-* visit typesPhone, MyChart (FU only)New pt: min 5 days advance
BH-RULESAll BH-* visit typesPhone only (intake); MyChart (FU)Intake: min 3 days advance
ORT-RULESAll ORT-* visit typesPhone, referral WQNew pt: min 3 days advance
UC-RULESAll UC-* visit typesWalk-in, MyChart same-dayNo advance constraint

Overbook Policy

HL7 Integration and Referral Management

Outbound SIU Appointment Messages

When a Cadence appointment is created for a shared patient, Bridges fires an outbound SIU^S12 to the external provider's EHR within 60 seconds. Modifications and cancellations generate SIU^S14 and SIU^S15 respectively. This closes the loop for referring providers without requiring phone calls or faxes.

HL7 MessageTrigger EventDirection
SIU^S12New appointment bookedOutbound to referring EHR
SIU^S14Appointment rescheduledOutbound to referring EHR
SIU^S15Appointment cancelledOutbound to referring EHR
SIU^S17Appointment deletedOutbound to referring EHR
REF^I12Inbound patient referral from external providerInbound to NRH Cadence
ADT^A08Patient demographics updateInbound; may trigger scheduling downstream

Inbound Referral Workflow (REF^I12)

External provider sends referral (HL7 REF^I12 or e-Referral via CommonWell) | --> Bridges receiving app "NRH_REFERRAL_IN" Parse: PID-3 (MRN), PID-5 (patient name), PID-7 (DOB) PRD (referring provider, referring facility) OBR-4 (service requested / reason for referral) | --> MPI match: confirm patient identity in Epic On mismatch: flag in Bridges error queue, route to manual review (SLA: 4 hours) | --> Auto-create referral order in Epic InBasket Route to Cadence referral WQ by specialty (CARD, ORT, BH, etc.) | --> Scheduler picks up WQ entry (SLA: 48 hours) Contacts patient, confirms insurance, books appointment | --> Appointment created and linked to referral order | --> Outbound SIU^S12 to referring provider confirming scheduled date/time | --> Referral order closed; closed-loop complete Logged in referral tracking Crystal report

HL7 Interface Error Handling

Monitoring and Observability

Configuration work is not done at go-live. Metrics determine whether the build is actually working, and they tell us early enough to correct course before a problem reaches leadership.

Radar Dashboard (Real-Time, Scheduling Supervisors)

Automated Weekly Reports

ReportAudienceKey Metrics
Template UtilizationDept admins, VP Patient Access% slots filled, hold pool conversion rates, by provider and by day of week
No-Show by Visit TypeScheduling directorsNo-show rate, cancellation lead time, per specialty and per visit type
3rd Next Available (3NA)VP Patient Access, clinic managers3NA by specialty and site, week-over-week trend
Referral AgingReferral coordinators, super usersOpen referral WQ entries by age (under 48hr, 48hr-5d, over 5d), by specialty, by source
Scheduling WQ AgingScheduling supervisorsEntries over 3 days old; assigned scheduler; visit type cluster

Threshold Alerts

WQ Age Alert

Entry older than 3 days: In Basket message to scheduling supervisor with entry details

Hold Slot Alert

Hold fill rate below 50% at 24 hours before session: Radar flag for same-day release decision

Interface Alert

Bridges error rate above 5% in a day: automated ServiceNow P2 incident created

Template Gap Alert

No template coverage for a provider's scheduling day: In Basket to clinic admin, 10 days in advance

Governance Cadence

A monthly Cadence governance meeting with scheduling directors, clinic managers, and the analyst team reviews the metrics dashboard, approves or denies template change requests queued since the last meeting, and surfaces patterns that need longer-term configuration adjustments. This is the forum where data drives build decisions, not anecdote.

Change Management

Cadence configuration access without a change process is how a 29-minute scheduling outage happens (see the RCA section). Every change follows the same path regardless of perceived size.

Change Lifecycle

  1. Request submitted via ServiceNow form: clinic name, affected visit type or template, requested change, business justification, preferred go-live date
  2. Analyst impact assessment: check rule groups, other visit types linked to the template, active WQ entries that could be affected, other clinics sharing the configuration
  3. CAB review at bi-weekly meeting: approve, deny, or request more information; changes affecting multiple departments require additional stakeholder sign-off
  4. Build in TST: analyst makes the configuration change in the test environment and documents build steps in SharePoint config tracker
  5. UAT review: clinic lead or super user validates the change in TST; written sign-off recorded in ServiceNow ticket
  6. Promote to PRD: maintenance window for high-impact changes; off-peak for low-impact; rollback steps documented before promotion begins
  7. Post-go-live: ServiceNow notification to affected clinics at go-live; 7-day feedback form sent; analyst reviews responses within 48 hours

Rollback Readiness

Communication Cycle

T-5 Days

ServiceNow email to affected scheduling staff with change summary and what to expect

Day of Go-Live

Teams message to scheduling team leads; Radar dashboard updated if new tiles added

T+7 Days

Feedback form sent to affected clinics; analyst reviews responses and closes the loop within 48 hours

Root Cause Analysis: Cardiology Scheduling Outage

Incident date: Friday afternoon. Duration: 29 minutes. Impact: Cardiology scheduling team unable to book any new patient appointments. Epic Cadence error: "No valid scheduling rules found."

Timeline

Root Causes

Root Cause 1: Access Scope

Super users had edit access to scheduling rule groups without a change ticket requirement. Edit access for rule groups should be restricted to the analyst team.

Root Cause 2: No Alerting

No automated alert fires when an active rule group with future appointments is toggled Inactive. A Radar alert would have caught this at 11:47 AM rather than 2:15 PM.

Root Cause 3: Training Gap

Super user training did not clearly separate "read-only review" tasks from "analyst-only edit" tasks. Super users should have a documented function list with access that matches it.

Corrective Actions

  1. Remove scheduling rule group edit access from super user role; restrict to Cadence analyst and above in Epic security
  2. Configure Radar alert: rule group with active future appointments changes to Inactive, fires immediate In Basket to on-call Cadence analyst
  3. Update super user training curriculum: publish a "view only" vs. "analyst-only function" reference sheet; add to onboarding checklist
  4. Add rule group status changes to CAB scope: cannot be changed without a ServiceNow change ticket, regardless of reason

Disaster Recovery

4 hr
Recovery Point Objective (RPO)
2 hr
Recovery Time Objective (RTO)
7 AM / Noon
Downtime Schedule Printout Times
4 hr
Post-Restore Reconciliation Window

During Downtime

  1. Downtime schedule printout generated at 7:00 AM and noon daily, covering the next 8 scheduling hours for each clinic
  2. Scheduling staff defer new appointment requests to a paper callback log: name, DOB, call-back number, visit type requested
  3. Urgent appointment needs: clinic lead notified via phone tree; urgent patients triaged to walk-in or directed to urgent care
  4. Schedulers do not attempt to enter appointments into Epic during downtime mode; paper-only until Epic restore confirmed

On Restore

  1. Reconcile paper callback logs against Cadence: data entry team enters missed appointment requests within 4 hours of restore
  2. MPI duplicate check: run duplicate detection report before committing any new entries from downtime period
  3. Verify provider templates for next 14 scheduling days are intact; flag any gaps to clinic administrators
  4. Bridges interface restart: verify all SIU and REF interfaces reconnect; replay messages from Bridges error queue (up to 4 hours of backlog)
  5. WQ reconciliation: compare WQ counts to last pre-downtime snapshot; investigate missing entries before marking incident resolved
  6. Stakeholder notification: ServiceNow incident updated with restore time; scheduling supervisors confirm operations normal before P1 closed

Annual DR Drill

Simulate a 4-hour Epic outage in TST environment. Time the full restore and reconciliation process. Run paper schedule workflow with at least 3 clinic teams. Document gaps discovered during the drill and update this runbook before the next annual cycle.

Automation

Automation in a Cadence context means eliminating manual steps that add no clinical value: reminder calls that should be SMS, bump list reviews that should run overnight, and aging reports that should email themselves. Staff time re-invested in patient contact instead.

Automated Bump List

Epic batch job at 6:00 AM scans prior-day cancellations and offers matching open slots to wait list entries by visit type and provider criteria. MyChart notification sent automatically.

Reminder Campaigns

Reminder batch at 72 hr (email) and 24 hr (SMS or voice) per patient preference. Includes MyChart quick-reschedule link. Opt-out honored in real time.

WQ Aging Alert

Daily 7:00 AM Cadence report flags workqueue entries over 3 days old. Auto-emails scheduling supervisors with counts by specialist and WQ type.

Referral Aging Escalation

In Basket message to assigned scheduler if referral WQ entry not actioned within 48 hours. Escalates to supervisor at 72 hours with the referring provider copied.

Visit Type Usage Audit

Monthly batch report lists visit types with 0 appointments in 90 days. Auto-routes to analyst team for inactivation review. Governance paper trail maintained automatically.

No-Show Prediction

Epic's predictive model scores next-day appointments for no-show risk. Entries above 40% added to day-before confirmation WQ for outreach staff.

Post-Merge Visit Type Cleanup (Python)

After each Phase 1 batch merge, this script parses the visit type audit export and flags any remaining near-duplicates by department and normalized name, before they re-enter the active pool.

import openpyxl, re wb = openpyxl.load_workbook("visit_type_audit.xlsx") ws = wb.active seen = {} duplicates = [] for row in ws.iter_rows(min_row=2, values_only=True): name = str(row[1]).strip().upper() if row[1] else "" dept = str(row[2]).strip() if row[2] else "" appt_cnt = row[4] if row[4] is not None else 0 key = f"{dept}|{name}" if key in seen: duplicates.append((seen[key], row)) else: seen[key] = row print(f"Potential duplicates found: {len(duplicates)}") for pair in duplicates: print(f" EVT {pair[0][0]} vs EVT {pair[1][0]}: {pair[0][1]}") # Review output before any inactivation. Clinical sign-off required.

Why I Stand Out

01

End-to-End Cadence Ownership

Not just configuration support. I design visit type governance frameworks, build scheduling rule groups from scratch, and own the full change lifecycle from request to post-go-live measurement. The work sample here is a direct example of how I approach a Cadence engagement.

02

HL7 Integration Fluency

SIU and REF message flows are not theoretical. I have mapped Bridges interfaces, diagnosed PID segment parse errors, and built closed-loop referral workflows that connect external referring providers directly back to Epic scheduling confirmations.

03

Clinician-First Communication

I translate Cadence configuration decisions into plain language for department administrators and front desk staff. That reduces change resistance, speeds adoption, and means fewer support tickets for things that should have been trained correctly at go-live.

04

Governance Before the Crisis

I put CAB processes and change ticketing discipline in place before an incident forces them. The RCA in this proposal shows exactly what happens without governance, and exactly what it prevents once it exists.

05

Metrics-Backed Decisions

Every configuration change I propose comes with a baseline metric, a target, and a measurement plan. I do not ask leadership to take my word for it. Outcomes are visible in Crystal Reports within weeks of go-live.

About Me and Fit

PR

Praveendhra Rajkumar

IT Systems Professional • DevOps Engineer • MS Computer Science, UMass Boston

Framingham, MA • Open to remote roles • (857) 391-4257

IT professional with 5+ years delivering production systems reliability, infrastructure automation, and cross-functional deployment coordination at Bright Horizons Family Solutions and Zoho Corporation. MS in Computer Science from UMass Boston, with a strong foundation in systems analysis, process automation, and technical documentation. Excited to bring this technical depth into healthcare IT via the Epic Cadence certification path.

Skills

Systems Analysis Business Process Automation DevOps & CI/CD Disaster Recovery Cross-functional Coordination Python SQL Bash Linux AWS / Azure Terraform Docker / Kubernetes Technical Documentation Project Coordination Stakeholder Communication GitHub Actions / Azure DevOps

Experience to JD Bridge

Every card on the left is direct experience from my work history. Every card on the right is the JD requirement it covers.

My Experience
JD Requirement Covered
Led weekly/bi-weekly production release deployments at Bright Horizons with 99%+ on-time delivery, coordinating across development, QA, and infrastructure teams
"Organizing, planning, and executing projects from vision through implementation, involving internal personnel, contractors, and vendors"
Automated CI/CD and DevOps workflows using AI-driven agentic processes at Bright Horizons, reducing manual effort by ~40% and compressing change lead time from days to under a day
"Experience in the strategic use of technology in managing and growing a business; business process re-engineering involving broad-based information systems"
Architected an Inventory Configuration Comparison framework at Zoho to detect drift between production and DR environments, cutting configuration discrepancies by ~80% and eliminating manual audits
"Strong analytical and conceptual skills; demonstrated track record in new concept development for various projects and complex technical plans"
Teaching Assistant for 60+ students in Computer Architecture at UMass Boston; Student Mentor at St. Joseph's (voted Best Mentor), coaching 20+ students on technical and professional development
"Strong verbal communication skills; ability to express complex technical concepts in terms understandable to the business"
Conducted quarterly chaos engineering experiments at Bright Horizons to validate disaster recovery and fallback services, detecting and remediating resilience gaps before they impacted users
"Understanding of project management concepts in planning and implementing multiple projects in a cross-functional environment"
Coordinated quarterly DR site switchovers at Zoho contributing to 99.9%+ uptime; ran configuration drift analysis across production and DR that directly shaped infrastructure decisions
"Understanding of how IT affects an organization and ability to link it to redesigned business process"
Designed and deployed MCP servers with custom developer agents integrated into GitHub Copilot at Bright Horizons, improving productivity across a team of 20+ engineers
"Ability to solve problems often spanning multiple environments in a business area; applying technology to improving business processes within strategic system goals"