SlideShare uma empresa Scribd logo
1 de 20
Paul Brian Contino
Corporate Chief Technology Officer
New York City Health & Hospitals Corporation
DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.
CLOSING KEYNOTE:
Best Practices – Panel of End Users
February 23 2014 3:00-4:15
Privacy and Security: Challenges and
Opportunities in Healthcare Identity
My Interest in Identity Management:
A Personal Vignette
© 2014 HIMSS
Paul Brian Contino
New York City Health & Hospitals Corporation
• Largest municipal healthcare organization in the U.S.
• $6.7 billion integrated healthcare delivery system
• Serving 1.4 million New Yorkers every year, including 475,000 uninsured
Facilities:
• 11 acute care hospitals, 4 skilled nursing facilities,
6 large diagnostic and treatment centers
• Health and Home Care (in-home services)
• More than 80 community health clinics
• 420,000 member health plan (MetroPlus)
Care statistics (2012)
• Staffed Beds: 7,554 (4500 acute, 3000 LTC)
• Clinic Visits: 4,876,259 ER Visits: 1,190,413
• Discharges: 221,372 Births: 20,744
.
New York City Health & Hospitals Corporation
Healthcare : Where Are We Going?
Identity Management
EHR PHR
NHIN
RHIO HIE
eHealth Exchange
HISP
HIO
Direct
ACO
PCMH
Health
Home
MU 1- 2
Circa 2009 2014
Healthcare
Exchanges
Patient
Portals
Blue Button
Islands of Information
$2.5 Trillion Dollars
2009 U.S Healthcare Expenditure
EMR 1
EMR 2
EMR 3
EMR 4
$3.1 Trillion Dollars
2014 U.S Healthcare Expenditure (Est)
HIE 1
HIE 2
HIE 3
HIE 4
Importance of Patient Identity
Is the patient in front of us who they say?
• Patient safety & appropriate medical care
• Avoid potential medical errors
Linking patient to existing medical records
• Continuity of Care
• Complete and accurate clinical data to our providers
Medical Billing and Claims Processing
• Reduce Medical Identity Theft
• Reduce Fraud and Abuse
Data Sharing with our Partners
• RHIOs, Medical/Health Home, ACO
.
The Challenges of Patient Identification
The Challenge of Patient Identification
The Demographic Profile
A very limited set of information is
used to identify patients
• Last Name
• First Name
• Date of Birth
• Address
• Full or Partial SSN
(often prohibited)
.
Patient
Demographic
Changes
Changing Demographics of Patients
Number of Marriages each
year
Number of Divorces each year
Number of job changes
over the lifetime of an
average worker
Number of US citizens that
moved between 2012 and
2013
(11.7% of population)
Our Patients are in Motion
Year 2010
610,000 migrations
Healthcare Utilization
Number of different
doctors the average
patient will see in their
lifetime
Healthcare Billing and Payment
transactions each year
ER Visits per year
Physician
Office visits per
year
The Longitudinal Patient Record
High School College
Post
Grad
Professional Retirement
Alejandra Ortiz
DOB: 02/23/1949
540 W 2nd Ave
San Bernardino, CA
92410
Family Home
✚
Alejandra Ortiz
DOB: 02/23/1949
3231 Walnut St.
Philadelphia, PA
19104
U. Penn

Alejandra Ortiz
DOB: 02/23/1949
602 West 139th St.
New York, NY
10031
Columbia U.
✚
Alejandra Ortiz
DOB: 02/23/1949
5041 East Vista St.
Long Beach, CA
90803
Family Home

Alexa Thomas
DOB: 02/23/1949
3927 Glenwood St.
Little Neck, NY
11363
✚✚
Alexa Ortiz
DOB: 02/23/1949
1018 Paper Mill Ct
NW Washington,DC
20007
Washington Post

Alexa Ortiz
DOB: 02/23/1949
88 Bleecker St.
New York, NY
10012
New York Times

Alexa Ortiz-Thomas
DOB: 02/23/1949
565 Broadway #5P
New York, NY
10012
Marriage

2 Kids, 1 Dog
New Home
Alexa & John Thomas
2882 Banyan
Boulevard Circle Nw
Boca Raton, FL
33431
Snow Birds
✚
= Unique Physicians

✚ = Emergency Visits
21 Physicians
5 Different States
4 Name Variations
The Challenge of Matching Patient Records
Name: Alejandra Ortiz Alexa Thomas
Address: 540 W 2nd Ave 3927 Glenwood St.
San Bernardino, CA Little Neck, NY
92410 11363
DOB: 02/23/1949 02/23/1949
Age: 65 65
Gender: F F
Tel: (909) 883-3386 (917) 245-6565
SSN4: 8696 8669
Are these the same individual?
YES – But Patient Records are
Continually Developing Collections of Changeable
Data
National Patient Matching Initiative
December 16, 2013 - ONC Stakeholder meeting to address patient identification and matching.
Patient
Registration
Medical
Record
Payor
PBMAncillary
Systems
(Lab, Rad)
RHIO
HIE
RHIO - RHIO
Nation eHealth Exchange
Cascading Error
“We don’t have an algorithm issue,
we have a data quality issue.”
- Dr Scott Schumacher, chief scientist for MDM at IBM
Major Transformation of Healthcare
Rapid Adoption of Electronic Health Records
• 44% (2009) to 73% (2012) have electronic records
Health Information Exchanges (HIE)
• Over 280 across the US with more than 50% of hospitals
participating in HIE organizations, Meaningful Use
New Delivery and Payment Models
Health and Medical Homes (HMH, PCMH)
• Managing patients across continuum of care and
reimbursement based on outcomes (volume to value)
Accountable Care Organizations (ACOs) –
• Over 370 ACOs across the US, 150 more in development
Retail Clinics –
• CVS, Walgreens & Target operate 70% of retail clinics in US.
Virtual Care – Remote Patient Monitoring, eVisits, Telemedicine
.
The Engaged and Empowered Patients
• Embracing New Technologies
• Educated consumer of healthcare services
• Patients are making use of retail clinics and urgent care centers
(convenience and lower costs)
• mHealth (Mobile Health and Wellness applications) are
exploding
• Patient Self Monitoring (wearable sensor technology)
• Patients have the ability to stream continuous health data on
dozens of physiological measures and vital signs
(blood pressure, weight, pulse oximetry)
• Social Networks
Challenge : Connecting the Dots
Plenty of Technology in Place
Identity Assurance
Bar Codes
ID Cards Smart Cards Biometrics
Sensors
Point of Care Longitudinal Record
Patient identification is foundational for the
Interoperability of Electronic Health Records
and for Health Information Exchange
• Go-forward strategy: Patient Identification not Matching
• Policy has hampered progress on crucial research and
development (lost time and funding)
• Put patients at the center of this process
• Patient safety and satisfaction can be greatly enhanced
• Universal Patient Identifier
Questions?
Paul Brian Contino
Corporate Chief Technology Officer
Enterprise Information Technology Services
NYC Health and Hospitals Corporation (HHC)
160 Water Street, Office 1312
New York, NY 10038
Tel: 646-458-3888
Fax: 212-788-3446
Cell: 917-279-4760
paul.contino@nychhc.org

Mais conteúdo relacionado

Mais procurados

Mais procurados (20)

Evolution of Accountable Care Organization (ACO) Initiatives at CMS - Public ...
Evolution of Accountable Care Organization (ACO) Initiatives at CMS - Public ...Evolution of Accountable Care Organization (ACO) Initiatives at CMS - Public ...
Evolution of Accountable Care Organization (ACO) Initiatives at CMS - Public ...
 
Webinar: Health Care Innovation Awards Round Two - Overview of Categories Thr...
Webinar: Health Care Innovation Awards Round Two - Overview of Categories Thr...Webinar: Health Care Innovation Awards Round Two - Overview of Categories Thr...
Webinar: Health Care Innovation Awards Round Two - Overview of Categories Thr...
 
Webinar: Community Health Access and Rural Transformation (CHART) Model – Ove...
Webinar: Community Health Access and Rural Transformation (CHART) Model – Ove...Webinar: Community Health Access and Rural Transformation (CHART) Model – Ove...
Webinar: Community Health Access and Rural Transformation (CHART) Model – Ove...
 
Webinar: Strong Start for Mothers and Newborns Amended FOA - How to Generate ...
Webinar: Strong Start for Mothers and Newborns Amended FOA - How to Generate ...Webinar: Strong Start for Mothers and Newborns Amended FOA - How to Generate ...
Webinar: Strong Start for Mothers and Newborns Amended FOA - How to Generate ...
 
Conference Call: Strong Start for Mothers and Newborns
Conference Call: Strong Start for Mothers and NewbornsConference Call: Strong Start for Mothers and Newborns
Conference Call: Strong Start for Mothers and Newborns
 
Webinar: Strong Start - Partnerships Between States and Applicants
Webinar: Strong Start - Partnerships Between States and ApplicantsWebinar: Strong Start - Partnerships Between States and Applicants
Webinar: Strong Start - Partnerships Between States and Applicants
 
Webinar: Comprehensive Kidney Care Contracting (CKCC) Model Options - Introdu...
Webinar: Comprehensive Kidney Care Contracting (CKCC) Model Options - Introdu...Webinar: Comprehensive Kidney Care Contracting (CKCC) Model Options - Introdu...
Webinar: Comprehensive Kidney Care Contracting (CKCC) Model Options - Introdu...
 
Webinar: Value-Based Insurance Design, Opportunities to Improve Medication Ad...
Webinar: Value-Based Insurance Design, Opportunities to Improve Medication Ad...Webinar: Value-Based Insurance Design, Opportunities to Improve Medication Ad...
Webinar: Value-Based Insurance Design, Opportunities to Improve Medication Ad...
 
Webinar: Strong Start Delivering Enhanced Prenatal Care
Webinar: Strong Start Delivering Enhanced Prenatal CareWebinar: Strong Start Delivering Enhanced Prenatal Care
Webinar: Strong Start Delivering Enhanced Prenatal Care
 
State Innovation Models Initiative for State Officials - Model Testing
State Innovation Models Initiative for State Officials - Model TestingState Innovation Models Initiative for State Officials - Model Testing
State Innovation Models Initiative for State Officials - Model Testing
 
Webinar: Maternal Opioid Misuse (MOM) Model - Notice of Funding Opportunity a...
Webinar: Maternal Opioid Misuse (MOM) Model - Notice of Funding Opportunity a...Webinar: Maternal Opioid Misuse (MOM) Model - Notice of Funding Opportunity a...
Webinar: Maternal Opioid Misuse (MOM) Model - Notice of Funding Opportunity a...
 
Office Hours: Medicare Advantage Value-Based Insurance Design Model - 2022 Ho...
Office Hours: Medicare Advantage Value-Based Insurance Design Model - 2022 Ho...Office Hours: Medicare Advantage Value-Based Insurance Design Model - 2022 Ho...
Office Hours: Medicare Advantage Value-Based Insurance Design Model - 2022 Ho...
 
Webinar: Comprehensive Primary Care Plus - Interested Payer Overview
Webinar: Comprehensive Primary Care Plus - Interested Payer OverviewWebinar: Comprehensive Primary Care Plus - Interested Payer Overview
Webinar: Comprehensive Primary Care Plus - Interested Payer Overview
 
Webinar: Comprehensive Primary Care Initiative - For Primary Care Physicians
Webinar: Comprehensive Primary Care Initiative -  For Primary Care PhysiciansWebinar: Comprehensive Primary Care Initiative -  For Primary Care Physicians
Webinar: Comprehensive Primary Care Initiative - For Primary Care Physicians
 
Webinar: Accountable Health Comunities Model - Overview & Application Require...
Webinar: Accountable Health Comunities Model - Overview & Application Require...Webinar: Accountable Health Comunities Model - Overview & Application Require...
Webinar: Accountable Health Comunities Model - Overview & Application Require...
 
Webinar: Bundled Payments - Distinguishing Between Applicant Roles
Webinar: Bundled Payments - Distinguishing Between Applicant RolesWebinar: Bundled Payments - Distinguishing Between Applicant Roles
Webinar: Bundled Payments - Distinguishing Between Applicant Roles
 
Webinar: Accountable Health Communities Model - State Medicaid Agency Roles
Webinar: Accountable Health Communities Model - State Medicaid Agency RolesWebinar: Accountable Health Communities Model - State Medicaid Agency Roles
Webinar: Accountable Health Communities Model - State Medicaid Agency Roles
 
Webinar: Direct Contracting Model Options - Payment Part One
Webinar: Direct Contracting Model Options - Payment Part OneWebinar: Direct Contracting Model Options - Payment Part One
Webinar: Direct Contracting Model Options - Payment Part One
 
Webinar: Medicare Advantage Value-Based Insurance Design Model - CY2020 Desig...
Webinar: Medicare Advantage Value-Based Insurance Design Model - CY2020 Desig...Webinar: Medicare Advantage Value-Based Insurance Design Model - CY2020 Desig...
Webinar: Medicare Advantage Value-Based Insurance Design Model - CY2020 Desig...
 
Webinar: Medicare Advantage Value-Based Insurance Design Model and Part D Pay...
Webinar: Medicare Advantage Value-Based Insurance Design Model and Part D Pay...Webinar: Medicare Advantage Value-Based Insurance Design Model and Part D Pay...
Webinar: Medicare Advantage Value-Based Insurance Design Model and Part D Pay...
 

Destaque

Laurent licht (ongewild) tipje sluier erfenis Boudewijn op
Laurent licht (ongewild) tipje sluier erfenis Boudewijn opLaurent licht (ongewild) tipje sluier erfenis Boudewijn op
Laurent licht (ongewild) tipje sluier erfenis Boudewijn op
Thierry Debels
 
CVLAURA 2016 INGLES
CVLAURA 2016 INGLESCVLAURA 2016 INGLES
CVLAURA 2016 INGLES
Laura Vidal
 
Studying the Link Between Volume of Media Coverage and Business Outcomes. 
Studying the Link Between Volume of Media Coverage and Business Outcomes.  Studying the Link Between Volume of Media Coverage and Business Outcomes. 
Studying the Link Between Volume of Media Coverage and Business Outcomes. 
Udit Joshi
 
Eerste grote fout van koning in de maak
Eerste grote fout van koning in de maakEerste grote fout van koning in de maak
Eerste grote fout van koning in de maak
Thierry Debels
 

Destaque (16)

Just how broken is football's financial model?
Just how broken is football's financial model?Just how broken is football's financial model?
Just how broken is football's financial model?
 
Don't Be A F'in Wantrepreneur - Silicon Valley Comes to the Baltics
Don't Be A F'in Wantrepreneur - Silicon Valley Comes to the BalticsDon't Be A F'in Wantrepreneur - Silicon Valley Comes to the Baltics
Don't Be A F'in Wantrepreneur - Silicon Valley Comes to the Baltics
 
Subscriber Engagement Presentation
Subscriber Engagement PresentationSubscriber Engagement Presentation
Subscriber Engagement Presentation
 
Laurent licht (ongewild) tipje sluier erfenis Boudewijn op
Laurent licht (ongewild) tipje sluier erfenis Boudewijn opLaurent licht (ongewild) tipje sluier erfenis Boudewijn op
Laurent licht (ongewild) tipje sluier erfenis Boudewijn op
 
CVLAURA 2016 INGLES
CVLAURA 2016 INGLESCVLAURA 2016 INGLES
CVLAURA 2016 INGLES
 
Studying the Link Between Volume of Media Coverage and Business Outcomes. 
Studying the Link Between Volume of Media Coverage and Business Outcomes.  Studying the Link Between Volume of Media Coverage and Business Outcomes. 
Studying the Link Between Volume of Media Coverage and Business Outcomes. 
 
Текст и контекст: античные мотивы в литературе XIX-XX в.
Текст и контекст: античные мотивы в литературе XIX-XX в.Текст и контекст: античные мотивы в литературе XIX-XX в.
Текст и контекст: античные мотивы в литературе XIX-XX в.
 
Games as Logic Machines: Learning the Humanities through the Logic and Parate...
Games as Logic Machines: Learning the Humanities through the Logic and Parate...Games as Logic Machines: Learning the Humanities through the Logic and Parate...
Games as Logic Machines: Learning the Humanities through the Logic and Parate...
 
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand RoundsBuilding capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
 
SharePoint - The hybrid story and beyond
SharePoint - The hybrid story and beyondSharePoint - The hybrid story and beyond
SharePoint - The hybrid story and beyond
 
Banking
BankingBanking
Banking
 
Eerste grote fout van koning in de maak
Eerste grote fout van koning in de maakEerste grote fout van koning in de maak
Eerste grote fout van koning in de maak
 
Hoe kom ik in de Office365 cloud?
Hoe kom ik in de Office365 cloud?Hoe kom ik in de Office365 cloud?
Hoe kom ik in de Office365 cloud?
 
Schoonbroer koningin Mathilde verdient geld aan asielcrisis
Schoonbroer koningin Mathilde verdient geld aan asielcrisisSchoonbroer koningin Mathilde verdient geld aan asielcrisis
Schoonbroer koningin Mathilde verdient geld aan asielcrisis
 
Future of Asia
Future of AsiaFuture of Asia
Future of Asia
 
Postal services
Postal servicesPostal services
Postal services
 

Semelhante a Privacy and Security: Challenges and Opportunities in Healthcare Identity

Leadership austin presentation chenven april 24 2015_pdf
Leadership austin presentation chenven  april 24 2015_pdfLeadership austin presentation chenven  april 24 2015_pdf
Leadership austin presentation chenven april 24 2015_pdf
AnnieAustin
 
Leadership austin presentation chenven april 24 2015_pp
Leadership austin presentation chenven  april 24 2015_ppLeadership austin presentation chenven  april 24 2015_pp
Leadership austin presentation chenven april 24 2015_pp
AnnieAustin
 

Semelhante a Privacy and Security: Challenges and Opportunities in Healthcare Identity (20)

18ohca-hie-overview-8-29-09.ppt
18ohca-hie-overview-8-29-09.ppt18ohca-hie-overview-8-29-09.ppt
18ohca-hie-overview-8-29-09.ppt
 
1416 Join the Revolution
1416 Join the Revolution 1416 Join the Revolution
1416 Join the Revolution
 
Gw unity feb_09
Gw unity feb_09Gw unity feb_09
Gw unity feb_09
 
The Future of the American Healthcare Delivery System in an Era of Change
The Future of the American Healthcare Delivery System in an Era of ChangeThe Future of the American Healthcare Delivery System in an Era of Change
The Future of the American Healthcare Delivery System in an Era of Change
 
Homeless Navigator Feb. Issue
Homeless Navigator Feb. IssueHomeless Navigator Feb. Issue
Homeless Navigator Feb. Issue
 
Leadership austin presentation chenven april 24 2015_pdf
Leadership austin presentation chenven  april 24 2015_pdfLeadership austin presentation chenven  april 24 2015_pdf
Leadership austin presentation chenven april 24 2015_pdf
 
NRHA
NRHANRHA
NRHA
 
Palliative Care vs. Curative Care
Palliative Care vs. Curative CarePalliative Care vs. Curative Care
Palliative Care vs. Curative Care
 
Reducing Readmissions and Length of Stay | VITAS Healthcare
Reducing Readmissions and Length of Stay | VITAS HealthcareReducing Readmissions and Length of Stay | VITAS Healthcare
Reducing Readmissions and Length of Stay | VITAS Healthcare
 
Reducing Readmissions and Length of Stay
Reducing Readmissions and Length of StayReducing Readmissions and Length of Stay
Reducing Readmissions and Length of Stay
 
Delivering Care Across the Continuum
Delivering Care Across the ContinuumDelivering Care Across the Continuum
Delivering Care Across the Continuum
 
Leadership austin presentation chenven april 24 2015_pp
Leadership austin presentation chenven  april 24 2015_ppLeadership austin presentation chenven  april 24 2015_pp
Leadership austin presentation chenven april 24 2015_pp
 
Writing Sample J. Burnaska Hospital Final Presentation
Writing Sample J. Burnaska   Hospital Final PresentationWriting Sample J. Burnaska   Hospital Final Presentation
Writing Sample J. Burnaska Hospital Final Presentation
 
Innovations of virginias aaa bay aging 2016 governors conference on aging
Innovations of virginias aaa bay aging 2016 governors conference on agingInnovations of virginias aaa bay aging 2016 governors conference on aging
Innovations of virginias aaa bay aging 2016 governors conference on aging
 
Investment in Primary Care, Michael Fine, MD - SLC 2015
Investment in Primary Care, Michael Fine, MD - SLC 2015Investment in Primary Care, Michael Fine, MD - SLC 2015
Investment in Primary Care, Michael Fine, MD - SLC 2015
 
Reducing Readmissions and Length of Stay
Reducing Readmissions and Length of StayReducing Readmissions and Length of Stay
Reducing Readmissions and Length of Stay
 
Reducing Readmissions and Length of Stay
Reducing Readmissions and Length of StayReducing Readmissions and Length of Stay
Reducing Readmissions and Length of Stay
 
Reducing Readmissions and Lengths of Stay
Reducing Readmissions and Lengths of StayReducing Readmissions and Lengths of Stay
Reducing Readmissions and Lengths of Stay
 
Health Insurance Exchanges Summit
Health Insurance Exchanges SummitHealth Insurance Exchanges Summit
Health Insurance Exchanges Summit
 
Health 3.0 Leadership Conference: Population Health in Detroit with David Law
Health 3.0 Leadership Conference: Population Health in Detroit with David LawHealth 3.0 Leadership Conference: Population Health in Detroit with David Law
Health 3.0 Leadership Conference: Population Health in Detroit with David Law
 

Mais de Paul Brian Contino

Mais de Paul Brian Contino (6)

CB-Insights_Big-Tech-In-Healthcare-2022.pdf
CB-Insights_Big-Tech-In-Healthcare-2022.pdfCB-Insights_Big-Tech-In-Healthcare-2022.pdf
CB-Insights_Big-Tech-In-Healthcare-2022.pdf
 
Data, Analytics, and AI - A Discussion on the Promise and Pitfalls
Data, Analytics, and AI - A Discussion on the Promise and PitfallsData, Analytics, and AI - A Discussion on the Promise and Pitfalls
Data, Analytics, and AI - A Discussion on the Promise and Pitfalls
 
arcsight_scmag_hcspecial
arcsight_scmag_hcspecialarcsight_scmag_hcspecial
arcsight_scmag_hcspecial
 
HFMA - IT and DSRIP Technology Enabled Healthcare - Paul Contino
HFMA - IT and DSRIP Technology Enabled Healthcare - Paul ContinoHFMA - IT and DSRIP Technology Enabled Healthcare - Paul Contino
HFMA - IT and DSRIP Technology Enabled Healthcare - Paul Contino
 
Transforming Healthcare with Big Data, Social and Mobile
Transforming Healthcare with Big Data, Social and MobileTransforming Healthcare with Big Data, Social and Mobile
Transforming Healthcare with Big Data, Social and Mobile
 
Improving Care Coordination with Big Data, Analytics and Technology - Paul Co...
Improving Care Coordination with Big Data, Analytics and Technology - Paul Co...Improving Care Coordination with Big Data, Analytics and Technology - Paul Co...
Improving Care Coordination with Big Data, Analytics and Technology - Paul Co...
 

Último

Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
chetankumar9855
 
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
Sheetaleventcompany
 
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
adilkhan87451
 
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
Sheetaleventcompany
 

Último (20)

Andheri East ^ (Genuine) Escort Service Mumbai ₹7.5k Pick Up & Drop With Cash...
Andheri East ^ (Genuine) Escort Service Mumbai ₹7.5k Pick Up & Drop With Cash...Andheri East ^ (Genuine) Escort Service Mumbai ₹7.5k Pick Up & Drop With Cash...
Andheri East ^ (Genuine) Escort Service Mumbai ₹7.5k Pick Up & Drop With Cash...
 
Saket * Call Girls in Delhi - Phone 9711199012 Escorts Service at 6k to 50k a...
Saket * Call Girls in Delhi - Phone 9711199012 Escorts Service at 6k to 50k a...Saket * Call Girls in Delhi - Phone 9711199012 Escorts Service at 6k to 50k a...
Saket * Call Girls in Delhi - Phone 9711199012 Escorts Service at 6k to 50k a...
 
Top Rated Call Girls Kerala ☎ 8250092165👄 Delivery in 20 Mins Near Me
Top Rated Call Girls Kerala ☎ 8250092165👄 Delivery in 20 Mins Near MeTop Rated Call Girls Kerala ☎ 8250092165👄 Delivery in 20 Mins Near Me
Top Rated Call Girls Kerala ☎ 8250092165👄 Delivery in 20 Mins Near Me
 
Call Girls Jaipur Just Call 9521753030 Top Class Call Girl Service Available
Call Girls Jaipur Just Call 9521753030 Top Class Call Girl Service AvailableCall Girls Jaipur Just Call 9521753030 Top Class Call Girl Service Available
Call Girls Jaipur Just Call 9521753030 Top Class Call Girl Service Available
 
Independent Call Girls In Jaipur { 8445551418 } ✔ ANIKA MEHTA ✔ Get High Prof...
Independent Call Girls In Jaipur { 8445551418 } ✔ ANIKA MEHTA ✔ Get High Prof...Independent Call Girls In Jaipur { 8445551418 } ✔ ANIKA MEHTA ✔ Get High Prof...
Independent Call Girls In Jaipur { 8445551418 } ✔ ANIKA MEHTA ✔ Get High Prof...
 
Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
Call Girl In Pune 👉 Just CALL ME: 9352988975 💋 Call Out Call Both With High p...
 
Call Girls Coimbatore Just Call 8250077686 Top Class Call Girl Service Available
Call Girls Coimbatore Just Call 8250077686 Top Class Call Girl Service AvailableCall Girls Coimbatore Just Call 8250077686 Top Class Call Girl Service Available
Call Girls Coimbatore Just Call 8250077686 Top Class Call Girl Service Available
 
Top Rated Hyderabad Call Girls Chintal ⟟ 9332606886 ⟟ Call Me For Genuine Se...
Top Rated  Hyderabad Call Girls Chintal ⟟ 9332606886 ⟟ Call Me For Genuine Se...Top Rated  Hyderabad Call Girls Chintal ⟟ 9332606886 ⟟ Call Me For Genuine Se...
Top Rated Hyderabad Call Girls Chintal ⟟ 9332606886 ⟟ Call Me For Genuine Se...
 
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
 
Top Quality Call Girl Service Kalyanpur 6378878445 Available Call Girls Any Time
Top Quality Call Girl Service Kalyanpur 6378878445 Available Call Girls Any TimeTop Quality Call Girl Service Kalyanpur 6378878445 Available Call Girls Any Time
Top Quality Call Girl Service Kalyanpur 6378878445 Available Call Girls Any Time
 
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
💚Call Girls In Amritsar 💯Anvi 📲🔝8725944379🔝Amritsar Call Girl No💰Advance Cash...
 
Call Girls Service Jaipur {9521753030} ❤️VVIP RIDDHI Call Girl in Jaipur Raja...
Call Girls Service Jaipur {9521753030} ❤️VVIP RIDDHI Call Girl in Jaipur Raja...Call Girls Service Jaipur {9521753030} ❤️VVIP RIDDHI Call Girl in Jaipur Raja...
Call Girls Service Jaipur {9521753030} ❤️VVIP RIDDHI Call Girl in Jaipur Raja...
 
9630942363 Genuine Call Girls In Ahmedabad Gujarat Call Girls Service
9630942363 Genuine Call Girls In Ahmedabad Gujarat Call Girls Service9630942363 Genuine Call Girls In Ahmedabad Gujarat Call Girls Service
9630942363 Genuine Call Girls In Ahmedabad Gujarat Call Girls Service
 
Low Rate Call Girls Bangalore {7304373326} ❤️VVIP NISHA Call Girls in Bangalo...
Low Rate Call Girls Bangalore {7304373326} ❤️VVIP NISHA Call Girls in Bangalo...Low Rate Call Girls Bangalore {7304373326} ❤️VVIP NISHA Call Girls in Bangalo...
Low Rate Call Girls Bangalore {7304373326} ❤️VVIP NISHA Call Girls in Bangalo...
 
Call Girls Ahmedabad Just Call 9630942363 Top Class Call Girl Service Available
Call Girls Ahmedabad Just Call 9630942363 Top Class Call Girl Service AvailableCall Girls Ahmedabad Just Call 9630942363 Top Class Call Girl Service Available
Call Girls Ahmedabad Just Call 9630942363 Top Class Call Girl Service Available
 
Call Girls Amritsar Just Call 8250077686 Top Class Call Girl Service Available
Call Girls Amritsar Just Call 8250077686 Top Class Call Girl Service AvailableCall Girls Amritsar Just Call 8250077686 Top Class Call Girl Service Available
Call Girls Amritsar Just Call 8250077686 Top Class Call Girl Service Available
 
Top Rated Pune Call Girls (DIPAL) ⟟ 8250077686 ⟟ Call Me For Genuine Sex Serv...
Top Rated Pune Call Girls (DIPAL) ⟟ 8250077686 ⟟ Call Me For Genuine Sex Serv...Top Rated Pune Call Girls (DIPAL) ⟟ 8250077686 ⟟ Call Me For Genuine Sex Serv...
Top Rated Pune Call Girls (DIPAL) ⟟ 8250077686 ⟟ Call Me For Genuine Sex Serv...
 
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
Russian Call Girls Lucknow Just Call 👉👉7877925207 Top Class Call Girl Service...
 
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
Dehradun Call Girls Service {8854095900} ❤️VVIP ROCKY Call Girl in Dehradun U...
 
Mumbai ] (Call Girls) in Mumbai 10k @ I'm VIP Independent Escorts Girls 98333...
Mumbai ] (Call Girls) in Mumbai 10k @ I'm VIP Independent Escorts Girls 98333...Mumbai ] (Call Girls) in Mumbai 10k @ I'm VIP Independent Escorts Girls 98333...
Mumbai ] (Call Girls) in Mumbai 10k @ I'm VIP Independent Escorts Girls 98333...
 

Privacy and Security: Challenges and Opportunities in Healthcare Identity

  • 1. Paul Brian Contino Corporate Chief Technology Officer New York City Health & Hospitals Corporation DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS. CLOSING KEYNOTE: Best Practices – Panel of End Users February 23 2014 3:00-4:15 Privacy and Security: Challenges and Opportunities in Healthcare Identity
  • 2. My Interest in Identity Management: A Personal Vignette © 2014 HIMSS Paul Brian Contino
  • 3. New York City Health & Hospitals Corporation • Largest municipal healthcare organization in the U.S. • $6.7 billion integrated healthcare delivery system • Serving 1.4 million New Yorkers every year, including 475,000 uninsured Facilities: • 11 acute care hospitals, 4 skilled nursing facilities, 6 large diagnostic and treatment centers • Health and Home Care (in-home services) • More than 80 community health clinics • 420,000 member health plan (MetroPlus) Care statistics (2012) • Staffed Beds: 7,554 (4500 acute, 3000 LTC) • Clinic Visits: 4,876,259 ER Visits: 1,190,413 • Discharges: 221,372 Births: 20,744 .
  • 4. New York City Health & Hospitals Corporation
  • 5. Healthcare : Where Are We Going? Identity Management EHR PHR NHIN RHIO HIE eHealth Exchange HISP HIO Direct ACO PCMH Health Home MU 1- 2 Circa 2009 2014 Healthcare Exchanges Patient Portals Blue Button
  • 6. Islands of Information $2.5 Trillion Dollars 2009 U.S Healthcare Expenditure EMR 1 EMR 2 EMR 3 EMR 4 $3.1 Trillion Dollars 2014 U.S Healthcare Expenditure (Est) HIE 1 HIE 2 HIE 3 HIE 4
  • 7. Importance of Patient Identity Is the patient in front of us who they say? • Patient safety & appropriate medical care • Avoid potential medical errors Linking patient to existing medical records • Continuity of Care • Complete and accurate clinical data to our providers Medical Billing and Claims Processing • Reduce Medical Identity Theft • Reduce Fraud and Abuse Data Sharing with our Partners • RHIOs, Medical/Health Home, ACO .
  • 8. The Challenges of Patient Identification
  • 9. The Challenge of Patient Identification The Demographic Profile A very limited set of information is used to identify patients • Last Name • First Name • Date of Birth • Address • Full or Partial SSN (often prohibited) .
  • 10. Patient Demographic Changes Changing Demographics of Patients Number of Marriages each year Number of Divorces each year Number of job changes over the lifetime of an average worker Number of US citizens that moved between 2012 and 2013 (11.7% of population)
  • 11. Our Patients are in Motion Year 2010 610,000 migrations
  • 12. Healthcare Utilization Number of different doctors the average patient will see in their lifetime Healthcare Billing and Payment transactions each year ER Visits per year Physician Office visits per year
  • 13. The Longitudinal Patient Record High School College Post Grad Professional Retirement Alejandra Ortiz DOB: 02/23/1949 540 W 2nd Ave San Bernardino, CA 92410 Family Home ✚ Alejandra Ortiz DOB: 02/23/1949 3231 Walnut St. Philadelphia, PA 19104 U. Penn  Alejandra Ortiz DOB: 02/23/1949 602 West 139th St. New York, NY 10031 Columbia U. ✚ Alejandra Ortiz DOB: 02/23/1949 5041 East Vista St. Long Beach, CA 90803 Family Home  Alexa Thomas DOB: 02/23/1949 3927 Glenwood St. Little Neck, NY 11363 ✚✚ Alexa Ortiz DOB: 02/23/1949 1018 Paper Mill Ct NW Washington,DC 20007 Washington Post  Alexa Ortiz DOB: 02/23/1949 88 Bleecker St. New York, NY 10012 New York Times  Alexa Ortiz-Thomas DOB: 02/23/1949 565 Broadway #5P New York, NY 10012 Marriage  2 Kids, 1 Dog New Home Alexa & John Thomas 2882 Banyan Boulevard Circle Nw Boca Raton, FL 33431 Snow Birds ✚ = Unique Physicians  ✚ = Emergency Visits 21 Physicians 5 Different States 4 Name Variations
  • 14. The Challenge of Matching Patient Records Name: Alejandra Ortiz Alexa Thomas Address: 540 W 2nd Ave 3927 Glenwood St. San Bernardino, CA Little Neck, NY 92410 11363 DOB: 02/23/1949 02/23/1949 Age: 65 65 Gender: F F Tel: (909) 883-3386 (917) 245-6565 SSN4: 8696 8669 Are these the same individual? YES – But Patient Records are Continually Developing Collections of Changeable Data
  • 15. National Patient Matching Initiative December 16, 2013 - ONC Stakeholder meeting to address patient identification and matching. Patient Registration Medical Record Payor PBMAncillary Systems (Lab, Rad) RHIO HIE RHIO - RHIO Nation eHealth Exchange Cascading Error “We don’t have an algorithm issue, we have a data quality issue.” - Dr Scott Schumacher, chief scientist for MDM at IBM
  • 16. Major Transformation of Healthcare Rapid Adoption of Electronic Health Records • 44% (2009) to 73% (2012) have electronic records Health Information Exchanges (HIE) • Over 280 across the US with more than 50% of hospitals participating in HIE organizations, Meaningful Use New Delivery and Payment Models Health and Medical Homes (HMH, PCMH) • Managing patients across continuum of care and reimbursement based on outcomes (volume to value) Accountable Care Organizations (ACOs) – • Over 370 ACOs across the US, 150 more in development Retail Clinics – • CVS, Walgreens & Target operate 70% of retail clinics in US. Virtual Care – Remote Patient Monitoring, eVisits, Telemedicine .
  • 17. The Engaged and Empowered Patients • Embracing New Technologies • Educated consumer of healthcare services • Patients are making use of retail clinics and urgent care centers (convenience and lower costs) • mHealth (Mobile Health and Wellness applications) are exploding • Patient Self Monitoring (wearable sensor technology) • Patients have the ability to stream continuous health data on dozens of physiological measures and vital signs (blood pressure, weight, pulse oximetry) • Social Networks Challenge : Connecting the Dots
  • 18. Plenty of Technology in Place Identity Assurance Bar Codes ID Cards Smart Cards Biometrics Sensors Point of Care Longitudinal Record
  • 19. Patient identification is foundational for the Interoperability of Electronic Health Records and for Health Information Exchange • Go-forward strategy: Patient Identification not Matching • Policy has hampered progress on crucial research and development (lost time and funding) • Put patients at the center of this process • Patient safety and satisfaction can be greatly enhanced • Universal Patient Identifier
  • 20. Questions? Paul Brian Contino Corporate Chief Technology Officer Enterprise Information Technology Services NYC Health and Hospitals Corporation (HHC) 160 Water Street, Office 1312 New York, NY 10038 Tel: 646-458-3888 Fax: 212-788-3446 Cell: 917-279-4760 paul.contino@nychhc.org

Notas do Editor

  1. Ortiz 94th most common to 14th with Thomas Patient records are continually developing collections of changeable data
  2. Continuing de facto endorsement of statistical matching as the only practicable approach to linking patients to their electronic health records will inhibit the effective development of the national health information network. http://www.himss.org/files/HIMSSorg/policy/d/2012_Ask1_PatientDataMatchingStrategy.pdf Enterprise Master Patient Indexes (EMPI) algorithms are at best 90-95% accurate.4 But most important factor is the quality of the data.
  3. Continuing de facto endorsement of statistical matching as the only practicable approach to linking patients to their electronic health records will inhibit the effective development of the national health information network. http://www.himss.org/files/HIMSSorg/policy/d/2012_Ask1_PatientDataMatchingStrategy.pdf