Automated Use of Clinical Laboratory Results in Adults

Benjamin Littenberg, MDUniversity of Vermont

andVermont Clinical Decision Support, LLC

Disclosure

I have an equity position in Vermont Clinical Decision Support, LLC, (Vermedx) along with The University of Vermont and other

faculty inventors.

www.Vermedx.com

Agenda

• Two problems in diabetes– Quality of individual care– Public health impact

• A novel strategy for using information

• Clinical and public health impacts

• Economic impact

Problem Characteristics

• Lab results are central to diabetes management– Good consensus on at least some aspects of care

• Keeping track of results is difficult– Doctors love flow sheets – but hate to keep them up!– Patients use many different laboratories

• Interpreting results is difficult– Diabetes is among the most complex problems a primary care

provider faces• Patients get “lost to follow-up”

– No reminder systems• Doctors and nurses care for individual patients

– Nobody has a “population view”

Guidelines• Hemoglobin A1C measures average blood sugar over last 6-8 weeks

– Low: <7.0%; Medium 7-9%; High: >9%– Frequency: 3 months if high or medium; 6 months if low

• LDL-Cholesterol measures “bad cholesterol” and vascular disease risk– Low: <100 mg/dl; Medium: 100-130; High >130– Frequency: 3 months if high; 6 months if medium; 12 months if low

• Creatinine measures current kidney function– High depends on age and sex (and race and size and....)– Frequency: annual

• Urine protein ratio measures risk for future kidney failure– Low: <30; Medium: 30-300; High: >300– Frequency: 12 months if low; never again if high or 2 mediums or if on

certain medications

And that’s just (some) of the lab tests!

Registry Approach

• Integrate data from multiple sources– Multiple laboratories

• Feedback to providers about individual patients with “value-added reports”

• Feedback to patients• Aggregate to population level

It works for infections. Why not diabetes?

Design Criteria

• Low cost per case• Low technology investment at the practice

– With or without electronic medical record

• Little change in practice flow• Little disruption of patient-provider

relationship• Accommodate multiple data sources• High face validity (accuracy)

Vermedx Diabetes Information System (VDIS)

• Automatic reports to providers and patients

• Based on clinical laboratory results

• Daily feeds from clinical labs

• Electronic messages or faxes to providers (doctors, nurses, physician assistants)

• Letters to patients

VDIS Architecture

VDIS Computer

Primary Care

Provider

Patient

ClinicalLab

ClinicalLab

Electronic medical record

or fax

MailSecure Network

Public HealthSurveillance

VDIS Clinical Outreach

• Flow sheet updates after every lab result

• Reminders to providers

• Reminder letters to patients

• Clinical alert letters to patients

• Quarterly population reports to providers

All products based on national guidelines

Flow sheet

• A flow sheet of pertinent labs, with decision support recommendations

– sent to provider whenever a pertinent test is done

– use in the visit to decide what to do

– follow trends– decide when to re-test– remember odd testing

intervals– possible handout for the

patient

Patient Reminder

• Letter from provider with practice address and telephone

– Explains which tests are due and when

– Asks patient to call office to set up testing

– Motivates patients to stay involved

– Reminds them that the practice cares about their long-term health

– Sent 30 days after the test is overdue (grace period)

Provider Reminder

• A reminder to the practice when patient is overdue

– Use this to keep patients from getting lost to follow up

– Sent 30 days after the test is overdue (grace period)

Patient Alert

• Letter from provider alerting patient to abnormal results

– Sent only for high results (A1C>8 or LDL>130)

– Asks patient to call provider’s office to set up further care (if they haven’t already)

Population Report

– Lists provider’s roster of diabetes patients, their most recent result and overdue status

• Makes it easy to find lost or out-of-control patients for quality improvement

– Provides “report card” for the practice, compared to all other providers and the top 10% performance

– Delivered every 3 months by mail

– Confidential – not shared with anyone else!

• VDIS is not recommended as a “Pay for Performance” system

Clinical Impact: The VDIS Trial

• Randomized by practice• Active practices get all 5 products• Control practices get none• 32 months• Outcomes:

– On-time testing– Blood sugar (A1C), Cholesterol– Costs

• Supported by NIH (R01 DK61167)

Participants

• 64 General Internal Medicine or Family Practices

• 128 Primary Care Providers– MD, DO, NP, PA

• 7,412 adults with diabetes confirmed by provider

• 1,006 randomly selected for home survey

1.17

1.39 1.40

1.74

11.

52

2.5

3O

dds

Ra

tio a

nd

95%

CI

A1C Cholesterol Creatinine Urine Protein

Adjusted for baseline testing and clustering n = 7,412On time testing

Other patient outcomes

• No change in– A1C levels– Cholesterol levels– Renal function– Blood pressure– Functional status– Body mass index

• Improvement in self-care (exercise)

Health Care UtilizationOutcome Control Intervention

AdjustedEffect* P

Hospital days/y 1.89 1.18 -1.01 0.047

Emergency room visits/y

0.72 0.55 -0.23 0.020

Primary care visits/y 2.86 2.04 -0.81 0.010

Specialty visits/y 0.23 0.15 -0.08 0.044

Costs $/y $4937 $3202 -$2426 0.033

*Linear regression adjusted for age, sex, marital status, education, health literacy, race, insulin use, comorbidity, hospital, and clustering within practices.

Health Care UtilizationOutcome Control Intervention

AdjustedEffect* P

Hospital days/y 1.89 1.18 -1.01 0.047

Emergency room visits/y

0.72 0.55 -0.23 0.020

Primary care visits/y 2.86 2.04 -0.81 0.010

Specialty visits/y 0.23 0.15 -0.08 0.044

Costs $/y $4937 $3202 -$2426 0.033

*Linear regression adjusted for age, sex, marital status, education, health literacy, race, insulin use, comorbidity, hospital, and clustering within practices.

The VDIS registry with patient outreach saves over $2,400 per patient per year.

Study Conclusions

• A registry-based clinical outreach program in primary care:– is feasible– improves diabetes care– saves money

What about using it for Public Health?

Registries in Public Health

• Inexpensive surveillance data

• Population view

• Analytic uses

• Clinical outreach (sometimes)

Laboratory results fit the bill.

What can a registry do for public health surveillance?

• Current overall status • Outcomes in subgroups

– Age, sex, geography, provider

• Trends over time• Maps• Combination with other data sources

– Census, surveys, hospital discharges, claims

Data for policy, persuasion and programs

80

10

01

20

14

0M

ea

n L

DL

-Ch

ole

ste

rol (

mg

/dl)

0 20 40 60 80 100Percent of Practices

71 practices 7,512 patients 105.8 patients/practice

Cholesterol by Practice

46

81

0A

1C (

%)

A B C D E F G H I J K LHospital Service Area

Blood Sugar Control by Hospital Service Area

6.50

6.75

7.00

7.25

7.50

7.75

Mea

n A

1C

2001 2002 2003 2004 2005 2006 2007

Monthly Averages

Linear Fit

A1C is falling by 0.036% per year (P<0.001)A1C over Time

6.50

6.75

7.00

7.25

7.50

7.75

Mea

n A

1C (

%)

2001 2002 2003 2004 2005 2006 2007

Vermont

New York

VT: -0.068 per year NY: +0.003 per year (P<0.05)Population Trend: A1C over Time

Clinton, NY

Franklin, NYSt. Lawrence, NY

Grafton, NH

CaledoniaChittenden

EssexFranklin

Gra

nd I

sle

Lamoille

Orange

Orleans

Rutland

Washington

Windham

Addison

Ben

ning

ton

Windsor

Red = High (P<0.05)

Blue = Low (P<0.05)

Grey = Non-outlier

White = No data

Glycemic Control by County

Clinton, NY

Franklin, NYSt. Lawrence, NY

Grafton, NH

CaledoniaChittenden

EssexFranklin

Gra

nd I

sle

Lamoille

Orange

Orleans

Rutland

Washington

Windham

Addison

Ben

ning

ton

Windsor

Red = High (P<0.05)

Blue = Low (P<0.05)

Grey = Non-outlier

White = No data

Glycemic Control by County

Current Vermedx RegistriesVermont New York City San Antonio

Started 2002 2006 May 2008

Sponsor Integrated provider group, insurer

Health Department

Health Department

Patients ~3,000 ~600,000 ~210,000?

Scope A1C, lipids, renal A1C only A1C only

Outreach Yes Pilot phase No

Surveillance No Yes Yes

Patient consent Opt-out None None

Benefits of Population-Based Decision Support

• Improved clinical outcomes for patients

• Help with management of chronic illness for physicians

• Cost savings for the health care system

• Improvement in Public Health

Thanks!

Benjamin Littenberg, MD

Benjamin.Littenberg@vtmednet.org

802-847-8268

www.Vermedx.com