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Use of Information Technology for Precision Performance Measurement and Focused Quality Improvement David W. Baker, MD MPH Chief, General Internal Medicine Feinberg School of Medicine, Northwestern University AHRQ Annual Conference September 9 th , 2008

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Use of Information Technology for Precision Performance Measurement and Focused Quality Improvement

Use of Information Technology for Precision Performance Measurement and Focused Quality Improvement

David W. Baker, MD MPHChief, General Internal Medicine

Feinberg School of Medicine, Northwestern University

David W. Baker, MD MPHChief, General Internal Medicine

Feinberg School of Medicine, Northwestern University

AHRQ Annual Conference September 9th, 2008

The Problem The Problem We want to routinely measure quality of care

for dozens of measures in outpatient practice and use this information to improve care

Cost of chart abstraction problematic

Administrative (claims) data inaccurate

– Need to capture medical and patient reasons for not achieving a quality measure

We want to routinely measure quality of care for dozens of measures in outpatient practice and use this information to improve care

Cost of chart abstraction problematic

Administrative (claims) data inaccurate

– Need to capture medical and patient reasons for not achieving a quality measure

The Solution?The Solution? EHR systems have the potential to routinely

measure quality with a high accuracy

– Denominator (if diagnoses entered…)

– Numerator (e.g., satisfied measure): meds, screening tests, blood pressure, etc

– Exceptions: diagnoses, allergies, lab abnormalities

• But most EHRS do not have adequate tools to routinely capture medical and patient reasons

EHR systems have the potential to routinely measure quality with a high accuracy

– Denominator (if diagnoses entered…)

– Numerator (e.g., satisfied measure): meds, screening tests, blood pressure, etc

– Exceptions: diagnoses, allergies, lab abnormalities

• But most EHRS do not have adequate tools to routinely capture medical and patient reasons

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pap mam crc pvx hba1c bp ldl asp

bp ldl asp antilipid mibeta afibwarf

Preventive Services Diabetes

Cardiovascular Disease 1 Cardiovascular Disease 2

Q1 2006 Q2 2006 GIM Q2 2006

Pe

rcen

tDenise AuEHR Facilitates Quality MeasurementEHR Facilitates Quality Measurement

Accuracy of Quality Measurement Using Only EHRS Data

Compared to Physician Review

Accuracy of Quality Measurement Using Only EHRS Data

Compared to Physician Review

Persell SD, et al, Arch Intern Med 2006

Baker DW et al, Ann Intern Med 2007

Quality measure Automated

%

After MD review %

Percent change

1. Antiplatelet drug 82 96 + 14

2. Lipid lowering drug 93 97 + 4

3. Beta blocker 83 90 + 7

4. BP measured 97 99 + 2

5. Lipid measurement 82 88 + 6

6. LDL control 85 87 + 2

7. ACE inhibitor 85 89 + 4

Automated Measurement vs. Hybrid Measurement

Automated Measurement vs. Hybrid Measurement

ConclusionsConclusions

Overall, good agreement between quality measured by EHR data compared to MD notes

Several factors limit accuracy of EHR measures

– Many pts did not actually have HF, CAD

– Medications were not always documented, but especially problematic for aspirin

– Exclusion criteria less well captured

Overall, good agreement between quality measured by EHR data compared to MD notes

Several factors limit accuracy of EHR measures

– Many pts did not actually have HF, CAD

– Medications were not always documented, but especially problematic for aspirin

– Exclusion criteria less well captured

Implications for QIImplications for QI

• As quality of care improves and specificity of “failure to comply” declines:

– Differences in performance more likely due to differences in documentation than to true differences in quality of care

– Point-of-care alerts for individual patients are usually incorrect: MDs ignore alerts

– List of patients need outreach are mostly wrong: outreach expensive, inefficient

• As quality of care improves and specificity of “failure to comply” declines:

– Differences in performance more likely due to differences in documentation than to true differences in quality of care

– Point-of-care alerts for individual patients are usually incorrect: MDs ignore alerts

– List of patients need outreach are mostly wrong: outreach expensive, inefficient

UPQUALUtilizing Precision Performance Measurement to Improve Quality

Funded by the Agency for Healthcare Research and Quality: 1R18HS017163

UPQUALUtilizing Precision Performance Measurement to Improve Quality

Funded by the Agency for Healthcare Research and Quality: 1R18HS017163

Implement multi-component quality improvement intervention

Aim to achieve ultra-high level of performance through more accurate performance measurement

Use quality measurement system to drive focused quality improvement

Implement multi-component quality improvement intervention

Aim to achieve ultra-high level of performance through more accurate performance measurement

Use quality measurement system to drive focused quality improvement

UPQUAL Study TeamUPQUAL Study Team Dave Baker, Steve Persell, Janu Khandekar,

Russell Robertson, Tom Gavagan, Nancy Dolan

Darren Kaiser, Dale Sanders, Tom Smith, Steve Smith, Sue Levi, et al from ENH IT

Jason Thompson

Elisha Friesema

Dave Baker, Steve Persell, Janu Khandekar, Russell Robertson, Tom Gavagan, Nancy Dolan

Darren Kaiser, Dale Sanders, Tom Smith, Steve Smith, Sue Levi, et al from ENH IT

Jason Thompson

Elisha Friesema

UPQUAL—ComponentsUPQUAL—Components Audit and feedback to physicians

Point of care alerts for quality measures which are not satisfied– Allows easy review and ordering– Allows documentation of medical and

patient reasons for not ordering

Medical and patient reasons sent to care manager and member of quality committee

Monthly feedback on individual patients not receiving essential medications

Audit and feedback to physicians

Point of care alerts for quality measures which are not satisfied– Allows easy review and ordering– Allows documentation of medical and

patient reasons for not ordering

Medical and patient reasons sent to care manager and member of quality committee

Monthly feedback on individual patients not receiving essential medications

Quality Measures (18)Quality Measures (18) CHD

– Antiplatelet therapy– Lipid lowering– Beta blocker-MI– ACE/ARB-CHD+DM

Heart failure– Beta blocker-LVSD– ACE/ARB-LVSD– Anticoagulation-AFIB

Hypertension control

CHD– Antiplatelet therapy– Lipid lowering– Beta blocker-MI– ACE/ARB-CHD+DM

Heart failure– Beta blocker-LVSD– ACE/ARB-LVSD– Anticoagulation-AFIB

Hypertension control

Diabetes– HbA1c control– LDL control– Blood pressure control– Nephropathy screen/treat– Aspirin primary prevention

Preventive care– Mammography– Cervical cancer screen– Colon cancer screen– Pneumonia vaccine ≥65 y– Osteoporosis screen/treat

Diabetes– HbA1c control– LDL control– Blood pressure control– Nephropathy screen/treat– Aspirin primary prevention

Preventive care– Mammography– Cervical cancer screen– Colon cancer screen– Pneumonia vaccine ≥65 y– Osteoporosis screen/treat

Best Practice AlertBest Practice Alert

Physician Sees Patient Who Needs Testing or TreatmentPhysician Sees Patient Who Needs Testing or Treatment

Physician Sees Patient Who Cannot Afford Medication

Physician Sees Patient Who Cannot Afford Medication

Each week, care manager receives list of patients who refuse or cannot afford a recommended test or procedure → outreach

Each week, care manager receives list of patients who refuse or cannot afford a recommended test or procedure → outreach

Physician Sees Patient Who S/he Thinks Has

Contraindication to Medication

Physician Sees Patient Who S/he Thinks Has

Contraindication to Medication

Each week, physician reviewer receives list of patients who had a medical exception entered and reviews the chart

Each week, physician reviewer receives list of patients who had a medical exception entered and reviews the chart

Display of Medical and Patient Reasons for Not Meeting Goals

for Chronic Conditions

Display of Medical and Patient Reasons for Not Meeting Goals

for Chronic Conditions

Preserving Physician Judgment:

Removing Patients from QI Registries with “Global Exeptions”

Preserving Physician Judgment:

Removing Patients from QI Registries with “Global Exeptions”

Improving Quality for the Unseen Patient

Improving Quality for the Unseen Patient

Monthly List of Patients Sent to MDMonthly List of Patients Sent to MD

Provider: Marcus Welby, M. D.Name MRN DOB

DOE, JANE 123919 2/1/54

Consider antiplatelet drug for CHD

JUAN, DON 999660 4/4/37

Consider beta blocker for prior MI

Consider ACE/ARB for CHD with DM

SMITH, ZORRO 139784 7/3/24

Consider antiplatelet drug for CHD

Provider: Marcus Welby, M. D.Name MRN DOB

DOE, JANE 123919 2/1/54

Consider antiplatelet drug for CHD

JUAN, DON 999660 4/4/37

Consider beta blocker for prior MI

Consider ACE/ARB for CHD with DM

SMITH, ZORRO 139784 7/3/24

Consider antiplatelet drug for CHD

Preliminary Results from First Three Months of UPQUAL

Preliminary Results from First Three Months of UPQUAL

Aspirin for Primary Prevention in Diabetes

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Satisfied Exceptions Deficiencies

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Time (mo.)Month

%

Anticoagulation in Heart Failure and Atrial Fibrillation

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Satisfied Exceptions Deficiencies

MonthTime (mo.)

%

Month

%

Summary Summary

Advanced quality measurement can be built into physician work flow

Exceptions to quality measures can be used to drive focused QI activities

Accurate quality measurement can inform the care of an entire panel of patients (both seen and unseen)

Advanced quality measurement can be built into physician work flow

Exceptions to quality measures can be used to drive focused QI activities

Accurate quality measurement can inform the care of an entire panel of patients (both seen and unseen)