Speak to the Hand

Using Biometrics in Patient Identification

2013

Mollie Drake MBA, CPAM

Senior Director, Corporate Access Management

2

Today’s Agenda

About Scripps

Set Up for Failure

Measures Tried or Considered

Product Selected

Implementation

Outcomes

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About Scripps

5 Hospitals on 4 Campuses located in San Diego

Not for Profit

More than 2600 Affiliated Physicians

Two Level I Trauma Centers

Extensive Ambulatory Care Network

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Set Up For Failure

Most Affluent to Homeless

Large Hispanic Population

Close to Border with Mexico

High Number of Tourists

Multiple Points of Entry

No EMPI

Manual Merges

Averaged 10 MRN errors a day!

Name Search on Maria Lopez:

868 hits

128 with common dates of birth

40% without Social Security Number

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Patient Data Base History

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Group Acquisitions

Need to rapidly add

new medical groups

required merging of

patient records into

database to be cleaned

up later.

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Fragmented Resources

Central MRN Analyst for

hospitals

Number control

department for ambulatory

Site specific staff

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Measures Tried

Accountability

Job descriptions

Monitoring and reporting

Lack of consequences

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Measures Tried

Identification

Policy to require identification

Name in system = name on

ID

Conflicts with insurance

Conflicts with orders

Poor customer service

Poor enforcement

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Measures Considered

Patient Photos

Expense equipment

Patient objections

Continual updating

Failure rate 1in 500

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Measures Considered

Fingerprints

CSI connotations

Ridge detail can

change

Lower accuracy rate

No longer unique

Failure rate 1 in 500

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Measures Considered

Retinal Scans

Expense equipment

Considered

invasive

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Product Selected

Patient Secure

Noninvasive

Accurate to 1 in 5 million

Not impacted by cuts or dirt

Low maintenance

Minimal IT data storage

Interfaces with registration system

Streamlines registration

Useful even if patient unconscious

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Implementation

Created 4 fields in system to document scanning

Started at one site

21 scanners

All points of registration

Drop in training week before

On site for 3 days

Returned 2 weeks later

Rolled out to 18 more sites in 11 months

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Start Up Tips

Provide marketing material

Provide hand sanitizer and wipes

Monitor enrollment

Share patient reactions and responses

Don’t present as an option

Central contact to modify data base

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Decisions

ID to enroll?

Age to scan children?

Placement in kiosks?

Marketing campaign?

Enroll non-patients?

Which hand to scan?

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Outcomes

High level of patient acceptance

Rapid adoption by staff

Prevents identity theft

Community standard for HIE

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Outcomes

Speeds up registration

Eliminates need for ID

Discourages frequent

flyers

MRN error rate down 65%

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Last Thoughts

1.49 million Americans were affected by

medical identity theft in 2011

Most people (46%) first learn they were a

victim of identity theft by receiving a

collection letter

Ponemon Institute’s Second Annual Survey on Medical Identity Theft

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Questions