Capturing Clinical Data to Monitor, Evaluate, & Improve .../media/Files/Activity Files/HealthServices...Capturing Clinical Data to Monitor, Evaluate, & Improve Health Care Delivery

Indiana UniversitySchool of Medicine

Capturing Clinical Data to Monitor, Evaluate, & Improve

Health Care Delivery & Outcomes for Persons Living with HIV/AIDS

Capturing Clinical Data to Monitor, Evaluate, & Improve

Health Care Delivery & Outcomes for Persons Living with HIV/AIDS

William M. Tierney, MDPresident and CEO

Regenstrief Institute, Inc.Associate Dean for Clinical Effectiveness Research

Indiana University School of Medicine

William M. Tierney, MDPresident and CEO

Regenstrief Institute, Inc.Associate Dean for Clinical Effectiveness Research

Indiana University School of Medicine


Points to be discussedPoints to be discussed

● Capturing the requisite clinical data– registries vs. electronic health records– defining the core dataset

● Models for capturing & integrating clinical data– key components of effective models– collecting from healthcare providers vs. patients – policies, incentives, and adherence

● Recommendations


RegistriesRegistries

Funding Agency

Funding Agency


Electronic health records Electronic health records

Funding AgencyFunding Agency

HIV ClinicHIV Clinic

Funding Agency

Funding Agency

DISCORDANT COUPLES

70%

0%2%

12%

5%

4%

1% 3% 3%

MTRH Mosoriot Turbo Burnt Forest AmukuraChulaimboWebuyeNaitiriTeso

DISCORDANT COUPLES

70%

0%2%

12%

5%

4%

1% 3% 3%

MTRH Mosoriot Turbo Burnt Forest AmukuraChulaimboWebuyeNaitiriTeso


Defining core data → who needs it?Defining core data → who needs it?

● Clinicians managing patients’ care● Health care system managers● Quality improvement programs● Ancillary upport programs● Patients and their families● Regulatory and funding agencies● Payers


Example: HIV/AIDS in Africa Example: HIV/AIDS in Africa






AMPATH: Academic Model Providing Access to Healthcare AMPATH: Academic Model Providing Access to Healthcare



AMPATH patient enrollmentAMPATH patient enrollment

0

20,000

40,000

60,000

80,000

100,000

120,000

140,0002001NOV

DEC

2001JAN FEB

MAR APR

MAY

JUN

2002JUL AUG SEP

OCT

NOV DEC

2003JAN FEB

MAR APR

MAY

JUN

2003JUL AUG SEP

OCT

NOV DEC

2004JAN FEB

MAR APR

MAY

JUN

2004JUL AUG SEP

OCT

NOV DEC

2005JAN FEB

MAR APR

MAY

JUN

2005JUL AUG SEP

OCT

NOV DEC

2006JAN

2/1/2006

3/1/2006

4/1/2006

5/1/2006

6/1/2006

7/1/2006

8/1/2006

9/1/2006

10/1/2006

11/1/2006

12/1/2006

1/1/2007

2/1/2007

3/1/2007

4/1/2007

5/1/2007

6/1/2007

7/1/2007

8/1/2007

9/1/2007

10/1/2007

11/1/2007

12/1/2007

1/1/2008

2/1/2008

3/1/2008

4/1/2008

5/1/2008

6/1/2008

7/1/2008

8/1/2008

9/1/2008

10/1/2008

11/1/2008

12/1/2008

1/1/2009

2/1/2009

3/1/2009

4/1/2009

5/1/2009

6/1/2009

7/1/2009

8/1/2009

9/1/2009

10/1/2009

11/1/2009

12/1/2009

1/1/2010

2/1/2010

3/1/2010

4/1/2010

5/1/2010

6/1/2010

7/1/2010

8/1/2010

9/1/2010

10/1/2010

11/1/2010

12/1/2010

1/1/2011

2/1/2011

3/1/2011

Cumulative HIV+ Patients Enrolled: Nov ’01 – Mar ‘11


AMPATH patient visitsAMPATH patient visits

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000Nov-01

Dec-01

Jan-02

Feb-02

Mar-02

Apr-0

2May-02

Jun-02

Jul-02

Aug-02

Sep-02

Oct-0

2

Nov-02

Dec-02

Jan-03

Feb-03

Mar-03

Apr-0

3May-03

Jun-03

Jul-03

Aug-03

Sep-03

Oct-0

3Nov-03

Dec-03

Jan-04

Feb-04

Mar-04

Apr-0

4May-04

Jun-04

Jul-04

Aug-04

Sep-04

Oct-0

4Nov-04

Dec-04

Jan-05

Feb-05

Mar-05

Apr-0

5

May-05

Jun-05

Jul-05

Aug-05

Sep-05

Oct-0

5Nov-05

Dec-05

Jan-06

Feb-06

Mar-06

Apr-0

6May-06

Jun-06

Jul-06

Aug-06

Sep-06

Oct-0

6Nov-06

Dec-06

Jan-07

Feb-07

Mar-07

Apr-0

7

May-07

Jun-07

Jul-07

Aug-07

Sep-07

Oct-0

7Nov-07

Dec-07

Jan-08

Feb-08

Mar-08

Apr-0

8May-08

Jun-08

Jul-08

Aug-08

Sep-08

Oct-0

8Nov-08

Dec-08

Jan-09

Feb-09

Mar-09

Apr-0

9May-09

Jun-09

Jul-09

Aug-09

Sep-09

Oct-0

9

Nov-09

Dec-09

Jan-10

Feb-10

Mar-10

Apr-1

0May-10

Jun-10

Jul-10

Aug-10

Sep-10

Oct-1

0Nov-10

Dec-10

Jan-11

Feb-11

Mar-11

Cumulative HIV+ Patient Visits: Nov ’01 – Mar ‘11


AMPATH encounter forms AMPATH encounter forms

We got it wrongWe got it wrong
























AMPATH performance measuresAMPATH performance measures

● OBJECTIVE 1.1: Continue ART without interruption and increase enrolment● OBJECTIVE 1.2: Conduct home-based counseling and testing● OBJECTIVE 1.3: Improve and expand control of TB in the community and in HIV-TB co-infected patients ● OBJECTIVE 1.4: Provide support for social services, nutrition, economic, and psychosocial needs● OBJECTIVE 1.5: Strengthen clinic-based prevention programs● OBJECTIVE 1.6: Strengthen and expand community-based ART● OBJECTIVE 1.7: Enhance care coordination between AMPATH care sites● OBJECTIVE 2.1: Expand and strengthen community and workplace prevention programs● OBJECTIVE 2.2: Expand prevention and care programs for hazardous alcohol drinking● OBJECTIVE 2.3: Expand prevention and care programs for HIV-discordant couples● OBJECTIVE 2.4: Expand prevention and care programs for commercial sex workers and truckers.● OBJECTIVE 2.5: Expand prevention and care programs for patients at risk for STIs or who have STIs● OBJECTIVE 2.6: Expand prevention and care programs for children and adults with disabilities● OBJECTIVE 3.1: Assist communities and families to meet needs of orphans and vulnerable children● OBJECTIVE 3.2: Enhance economic security for AMPATH patients and their households● OBJECTIVE 3.3: Empower PLWHA to access legal services


Capturing clinical dataCapturing clinical data

● Key components of effective models– standard minimum core dataset – only coded or numeric data– add items not usually captured– entered by the person collecting the dataØ clerksØ cliniciansØ ancillary support persons (e.g. social workers)

– take little if any extra time than normal duties

W.O.R.M.write once, read many times

W.O.R.M.write once, read many times●Health-related quality of life●Functional status●Severity of illness●Comorbid problems ●Socioeconomic issues

●Health-related quality of life●Functional status●Severity of illness●Comorbid problems ●Socioeconomic issues


Combining data from multiple sourcesCombining data from multiple sources

● Interfaces between systems – different systems– different data– different coding– different output formats

● Requires standardizing data, coding, formats– requires custom programming in almost all cases– requires mapping of terms

● Push vs. pull

TOUGH!


One solution → HIEs One solution → HIEs

● Upload data routinely from providers● Establish and maintain interfaces● Provide term mapping → interoperability


Example: Indiana Network for Patient Care

Example: Indiana Network for Patient Care


>60 hosps → >2M ED visits/yr All laboratoriesAll radiology centersIN Dept. of Public Health5 large payors→>600M claims19,000 physicians≈ 1,500 interfaces≈ 12 million individuals≈ 5 billion structured results

A Regenstrief Institute study indicated that nearly 60% of Indianapolis-area patients visit more than one area hospital system over a period of several years.

A Regenstrief Institute study indicated that nearly 60% of Indianapolis-area patients visit more than one area hospital system over a period of several years.

INPC


Data captured in the INPC Data captured in the INPC

● Registration records → demographics● Text reports

– admission, discharge, outpatient visit notes– imaging, operative, and pathology reports

● Lab tests (numeric, coded)● Inpatient medications and immunizations● Outpatient medications (several PBMs)● Insurance claims


Policies, incentives, & adherence Policies, incentives, & adherence

● Voluntary reporting● Required reporting

– by statute– to obtain funds for HIV/AIDS treatment

● Data extraction from EHRs – from individual systems – from health information exchanges

● Registries● Sentinel care systems

●Biased●Spotty adherence ●Not representative

●Biased●Spotty adherence ●Not representative

●Requires sanctions●Carrot and stick? ●Requires sanctions●Carrot and stick? ●Draconian●Most effective●Requires funding!

●Draconian●Most effective●Requires funding!

●Requires one or few national EHR systems → not in U.S.!

●Won’t have some key measures

●Requires one or few national EHR systems → not in U.S.!

●Won’t have some key measures

●HIEs are not sustainable●Won’t have some key measures ●HIEs are not sustainable●Won’t have some key measures ●Voluntary

●Biased ●Voluntary●Biased

●Most cost-effective●Selection process is

key to generalizability

●Most cost-effective●Selection process is

key to generalizability


RecommendationsRecommendations

● For patients with frank AIDS or meeting CD4 criteria for anti-retroviral therapy– pay for care (already being done for most)– require minimum dataset for paymentØ core data → correct coding schemesØ standard transmission format

● For other HIV-infected patients – registry– consider prospectively selected sentinels


Recommendations (2)Recommendations (2)

● Decide on the core (minimum) clinical data● Add key clinical data not typically in an EHR

– HIV risk factors, symptoms– severity of illness, HRQoL

● Include non-clinical measures– socioeconomic, psychosocial factors

● Obtain some key data directly from patients– direct queries (mail, e-mail)– online personal health records


Thank you! Thank you!

Documents

Capturing Clinical Data to Monitor, Evaluate, & Improve .../media/Files/Activity Files/HealthServices...Capturing Clinical Data to Monitor, Evaluate, & Improve Health Care Delivery