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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. The Problem. - PowerPoint PPT Presentation
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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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70
80
90
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Satisfied Exceptions Deficiencies
%
Time (mo.)Month
%
Anticoagulation in Heart Failure and Atrial Fibrillation
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80
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)