Methods/ Best Practices Fraud prevention and detection Group 2

1. Methods/ Best PracticesFraud prevention and detectionGroup 2 Insurance Institute of India, Mumbai 24th February 2012

2. Interplay between Policy and Care • More defined Terms and Conditions of Insurance Policy: ailment exclusions/ wait period, procedure caps, waiting period, deductibles • Rising sensitivities to: • care delivered and rate plans followed by providers • Variations between planned care and delivered care • Episodic transaction during loss incidence i.e. hospitlisation

3. Active Participation…..

4. Factors in fraud managementLeaks, Misrepresentation, Inflation, Fabricated cases • Detectability: • Wrong information, pattern, trend, adverse event • Severity: Loss amount • Frequency: number of cases • Remedial action • Impact of remedial action

5. Detectibility • Welcome call before issuing policy. • Risk Scoring against weighted criteria (Tolerence levels and concurrent audit) • Organised data (template) to prompt detection of gaps/ deviation from routine • Std Treatment Guidelines (Routine elements of diagnosis, care and prognosis): • Train claims assessors to detect non routine elements and confirm rationale with provider • Medical Audits, Infrastructure Audit of Providers • Triggers: Age, Gender, ICD group, lockin period, Locn (provider; Locn (member); Cashless/MR; Claimed amt; • Investigators: • Training Modules to build competency • Establish and communicate Code of Conduct for investigation function • Data Sharing: • ICD 10 coding • Common shared folder between common interest groups • Trends and Patterns: Agent, Cashless, MR

6. Severity Tele Follow Ups for suspicious cases on events during care process. • Case Management for high value claim or catastrophic treatment (eg Multiple injuries) • Second opinion by qualified doctor in similar speciality preferably in same region • Checklist to insured member to track hospitalisation events for planned care (eg Diagnostic tests, Decision of admission, informed consent, preauth request, approval terms and conditions, assessment, care, prognosis, discharge)

7. Frequency • Shared Data and Joint assessment of experiences against trends and patterns • Red alerting suspicious providers vis-à-vis ICD groups and black listing fraudulant providers • Shared knowledge on status of suspicious hospitals across TPAs, Ins Companies • Learnings (Improving) and Unlearnings (simplifying)

8. Corrective Actions • Remedial action (control): • isolate cause/ environment of cause: Deny cashless while hospitalisation; suspend cashless facility to provider pending investigations. • reduce loss: mediation, negotiation, arbitration (sensitivities with legal action) • Recover loss: To establish mechanism and process of recovery post- retrospection • Impact of remedial action: • Amount recovered • Leak stopped (potential loss avoided) • Sustenance of control measures (detection, compliance, deterministic)

9. Preventive MeasuresSustenance of effective actions • Committee for knowledge creation from current experiences, patterns and trends. • Committee to approve best practices and propagation • CME for Medical staff in Insurance segment • Newsletters for member groups • Newsletters for provider groups • Thoughts! • Automation of consistent processes • Algorithm (statistical) based decision prompt

10. Possible methods • Assess care Vis-à-vis hospital infrastructure and specialties included (A scale to measure hospital compliance available) especially for Non NW Hospital with high volume of cases and/ or high claim value. • Insurance specific ‘Informed consent’ to capture member behaviour Vs provider behavior • Credentialing and performance tracking of investigators • Regional committees to resolve disputes between parties and close the open cases. • Change in accreditation status with NABH, Licencing authority may benefit by avoiding potential fraud • Published fraud hospital list has legal implications and not suggested • Reporting to Police, MCI, Statutory Licencing authority, IMA has not yielded positive responses

11. Thank You