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The Need for a Nationwide Patient Matching Strategy

Session #400, March 6, 2017

Dr. John Halamka, Chief Information Officer, Beth Israel Deaconess Medical Center

Ben Moscovitch, Manager, Health Information Technology, The Pew Charitable

Trusts

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John Halamka, MD

Ben Moscovitch

Has no real or apparent conflicts of interest to report.

Conflict of Interest

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Agenda• Causes and implications of inadequate patient matching

• Methods used for matching domestically

• Various options to advance patient matching

• A nationwide approach attempted abroad

• Moderated discussion

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Learning Objectives• Differentiate between the various ways hospitals currently match

patients, and why they are insufficient

• Evaluate the existing alternatives to matching patients and identify the strengths and weaknesses of each

• Explain the need for a single, nationwide strategy for patient matching and how it could promote patient safety

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Matching: Current RatesPatient Matching: The ability to link an individual with his or her medical records, and connect different records that refer to the same person

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Matching: Implications

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Matching: Common Problems

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What Does a Patient Index Do?

When looking at two records, it calculates an “Agreement Weight” for

each field, based on how similar they are (e.g. Is the Date of Birth the

same or close to the same?)

Then it adds all of those “weights” together to form the overall similarity

for that pair

Based on the configuration of the system, it either decides that weight

represents the same patient, different patients or puts the pair on a

worklist for manual review

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Weight Example

Total Calculated Weight for this pair = 26.5

This is compared to the Thresholds to determine if the pair is automatically linked.

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Thresholds

Autolink

Threshold

Links

?

Validate

Threshold

Validate

Review

Threshold

Non-Link

?

Review

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Potential Opportunities1. Have unique patient identifier that could be used for matching

a. Perennially discussed in healthcare

b. At this time, would need to be private-sector led

2. Patient-focused approach

3. Enhanced demographic standards

a. Agreement on data elements

b. Use of novel data elements

4. Use of third party data

a. Questions on costs; pediatric populations

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Nationwide Strategy Needed

Convened experts on a nationwide strategy

• Matching occurs cross-organizations with different policies

• Many different technologies in play

Some key characteristics discussed:

• Government can’t be the driver—should be private-sector led

• Trusted organization could help coordinate & identify standards

• Standards-based

• Flexibility for different technologies and capabilities

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The Gates Foundation South Africa Project

The 90/90/90 national policy goal

• 90% of patients with HIV know they are HIV positive

• 90% of patients who know they are positive are treated with anti-virals

• 90% of patients who are treated have laboratory evidence of viral

suppression

The challenge

• Low sensitivity and positive predictive value from demographic matching

approaches

• A highly mobile population

• Unstable infrastructure - electrical power, bandwidth, compute/storage

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The Approach • Biometric matching using low cost mobile “kits”

• A decentralized data storage infrastructure leveraging blockchain for data integrity

• A medical wallet that runs on basic phones

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Biometric linking kit … configured to have an iris biometric device, a touchscreen, a label printer and a bar code scanner…

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Patient

Poly-unique patient code, AA code, clinical record scan

Poly-unique patient code on clinical patient folder

Poly-unique patient code on ticket given to patient at reception as they move from station to station

GUI on small screen for clerk and clinician to scan patient, QR codes or bar codes during an “event”, and to look at prior linked “events”

Linking the patient within and between clinics and to clinical and laboratory records, and enabling independent and incremental

deployment at clinics over time … Linking events at a clinic (e.g. arrival, phlebotomy, doctor assessment) for a patient over time .…

Bar code and Document scanner

BiometricDevices

Label Printer

Event not yet linked

Events linked

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Metrics for Success• Matching sensitivity and positive predictive value

• Provider satisfaction (90/90/90 data easily available)

• Patient satisfaction (excess testing avoided)

• Reduction in redundant/unnecessary care

• Stability/reliability/security of data exchange

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Questions

John Halamka, MD

Chief Information Officer

Beth Israel Deaconess Medical Center

e: jhalamka@bidmc.harvard.edu

Ben Moscovitch

Manager, Health Information Technology

The Pew Charitable Trusts

e: bmoscovitch@pewtrusts.or

t: @benmoscovitch