Use CasesHealthcare
Healthcare

Claims exceptions. Critical lab alerts. Patient follow-ups. All auto-classified.

Patient records, insurance claims, appointment logs, lab results — healthcare organisations generate enormous volumes of structured data that lives in spreadsheets. MISBuddy classifies, tracks, and exports that data with full auditability — without touching your core EMR or HMS.

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4
Core Workflows
Minutes
Daily Claims Exception Report
0
Missed Critical Lab Alerts
DPDP
Compliant Self-Hosted Option
The Problem

Healthcare data that never connects

Hospitals, clinics, and health insurers maintain dozens of operational spreadsheets alongside their core systems. A typical mid-size hospital has:

  • A daily OPD/IPD register maintained by billing staff
  • An insurance claims tracker owned by the TPA coordinator
  • A lab results log updated by the pathology team
  • A patient follow-up list managed by the front desk

None of these talk to each other. Reporting to management means someone spending half a day copying data across files. Insurance rejections are tracked in a notebook.

MISBuddy connects these data streams, classifies every record, and enables instant operational reporting.
Core Workflows

Four workflows, full hospital coverage

1
Patient Appointment & Visit Tracking
Configuration: Patient Visits
visit_id string mobile_number unique_id visit_date date visit_type choice department choice doctor_name string payment_type choice total_bill float balance_due float follow_up_date date visit_status choice diagnosis_code string
Disposition Logic: Patient Follow-Up Priority
P1
OUTSTANDING_DUES
balance_due > 0 AND visit_status = Discharged
P2
OVERDUE_FOLLOW_UP
follow_up_date is set AND visit_status = Completed
P3
ADMITTED
visit_status = Admitted
P4
NO_SHOW
visit_status = No Show
P5
CHRONIC_CONDITION
diagnosis_code contains E11 (diabetes) or I10 (hypertension)
2
Insurance Claims Management
Configuration: Insurance Claims

The highest-impact use case for hospital billing teams. Insurance claims are tracked in Excel because the HMS rarely provides a usable claims pipeline view.

claim_id string tpa_name string insurance_company string claimed_amount float approved_amount float rejected_amount float deduction_reason choice claim_status choice days_pending integer query_raised choice settlement_date date
Disposition Logic: Claims Exception Management
P1
FRAUD_FLAG
deduction_reason = Fraud Suspect
P2
REJECTED_ESCALATION
claim_status = Rejected AND rejected_amount > ₹50,000
P3
QUERY_PENDING
query_raised = Yes AND settlement_date is empty
P4
LONG_PENDING
days_pending > 30 AND claim_status in [Submitted, Under Process]
P5
PARTIAL_APPROVAL
claim_status = Partially Approved AND rejected_amount > 0
P6
READY_FOR_SETTLEMENT
claim_status = Approved AND settlement_date is empty
Weekly billing review: Export REJECTED_ESCALATION and LONG_PENDING packets → share with TPA coordinator for resolution meetings. Previously this took an afternoon of manual filtering.
3
Lab Results & Diagnostic Tracking
Configuration: Lab Orders
order_id string test_name string test_category choice order_date date expected_report_date date actual_report_date date result_status choice critical_flag choice report_delivered choice doctor_notified choice
Disposition Logic: Lab Alert Priority
P1
CRITICAL_UNNOTIFIED
critical_flag = Yes AND doctor_notified = No
P2
CRITICAL_NOTIFIED
critical_flag = Yes AND doctor_notified = Yes
P3
ABNORMAL_PENDING_DELIVERY
result_status = Abnormal AND report_delivered = No
P4
OVERDUE_REPORT
actual_report_date is empty AND expected_report_date is set
P5
NORMAL_DELIVERED
result_status = Normal AND report_delivered = Yes
4
Chronic Disease Patient Monitoring
Configuration: Chronic Patient Register

For hospitals running DM, HTN, or oncology follow-up programmes.

patient_id string condition choice last_visit_date date next_due_date date hba1c_last float bp_systolic integer medication_adherence choice hospitalisation_last_6m integer risk_score integer programme_status choice
Disposition Logic: High-Risk Patient Flag
P1
CRITICAL_RISK
risk_score > 7 OR hospitalisation_last_6m > 2
P2
OVERDUE_VISIT
next_due_date is set AND programme_status = Active
P3
POOR_ADHERENCE
medication_adherence = Poor
P4
LAPSED
programme_status = Lapsed
P5
WELL_CONTROLLED
medication_adherence = Good AND risk_score < 4
Integrations

Connects to your existing stack

🏥
HMS / EMR (Practo, Meddbase, Insta)
Daily discharge summary CSV export → upload
📋
TPA Portal (MDIndia, Vipul, Paramount)
Claims status Excel download → upload for classification
🔬
LIS (Lab Information System)
Daily report CSV → upload to lab orders config
🏛️
Government Schemes (Ayushman Bharat)
Claim status CSV → dedicated configuration
Compliance & Audit

MISBuddy maintains a full record of every upload, every classification run, and every export:

  • ✓ Who uploaded the data and when
  • ✓ Which disposition logic version was applied
  • ✓ Who exported which packets and when
  • ✓ Self-hosted plan for full data sovereignty (DPDP Act compliant)
Business Outcomes

What changes for your team

Billing Team
Produces the daily pending claims list in minutes, not hours. Exception packets route to the right people automatically.
TPA Coordinator
Has a live exception view for rejections and queries. No more end-of-week reconciliation exercises.
Medical Director
Gets weekly chronic disease programme reports automatically. High-risk patients surfaced without manual analysis.
Finance
Reconciles insurance receivables against settlements without manual matching across multiple spreadsheets.
Lab Manager
Never misses a critical result notification. CRITICAL_UNNOTIFIED packet ensures every urgent result reaches the doctor.

Ready to connect your healthcare data streams?

Book a 30-minute demo. We'll map your HMS export format to a MISBuddy configuration and show a live claims classification.

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