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 David W. Baker, MD MPH Chief, General Internal Medicine Feinberg School of Medicine, Northwestern University AHRQ Annual Conference September 9 th, 2008

The Problem l We want to routinely measure quality of care for dozens of measures in outpatient practice and use this information to improve care l Cost of chart abstraction problematic l Administrative (claims) data inaccurate –Need to capture medical and patient reasons for not achieving a quality measure l We want to routinely measure quality of care for dozens of measures in outpatient practice and use this information to improve care l Cost of chart abstraction problematic l Administrative (claims) data inaccurate –Need to capture medical and patient reasons for not achieving a quality measure

The Solution? l 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 l 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 Facilitates Quality Measurement

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 measureAutomated % After MD review % Percent change 1. Antiplatelet drug Lipid lowering drug Beta blocker BP measured Lipid measurement LDL control ACE inhibitor Automated Measurement vs. Hybrid Measurement Automated Measurement vs. Hybrid Measurement

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

UPQUAL Utilizing Precision Performance Measurement to Improve Quality Funded by the Agency for Healthcare Research and Quality: 1R18HS l Implement multi-component quality improvement intervention l Aim to achieve ultra-high level of performance through more accurate performance measurement l Use quality measurement system to drive focused quality improvement l Implement multi-component quality improvement intervention l Aim to achieve ultra-high level of performance through more accurate performance measurement l Use quality measurement system to drive focused quality improvement

UPQUAL Study Team l Dave Baker, Steve Persell, Janu Khandekar, Russell Robertson, Tom Gavagan, Nancy Dolan l Darren Kaiser, Dale Sanders, Tom Smith, Steve Smith, Sue Levi, et al from ENH IT l Jason Thompson l Elisha Friesema l Dave Baker, Steve Persell, Janu Khandekar, Russell Robertson, Tom Gavagan, Nancy Dolan l Darren Kaiser, Dale Sanders, Tom Smith, Steve Smith, Sue Levi, et al from ENH IT l Jason Thompson l Elisha Friesema

UPQUAL—Components l Audit and feedback to physicians l 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 l Medical and patient reasons sent to care manager and member of quality committee l Monthly feedback on individual patients not receiving essential medications l Audit and feedback to physicians l 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 l Medical and patient reasons sent to care manager and member of quality committee l Monthly feedback on individual patients not receiving essential medications

Quality Measures (18) l CHD –Antiplatelet therapy –Lipid lowering –Beta blocker-MI –ACE/ARB-CHD+DM l Heart failure –Beta blocker-LVSD –ACE/ARB-LVSD –Anticoagulation-AFIB l Hypertension control l CHD –Antiplatelet therapy –Lipid lowering –Beta blocker-MI –ACE/ARB-CHD+DM l Heart failure –Beta blocker-LVSD –ACE/ARB-LVSD –Anticoagulation-AFIB l Hypertension control l Diabetes –HbA1c control –LDL control –Blood pressure control –Nephropathy screen/treat –Aspirin primary prevention l Preventive care –Mammography –Cervical cancer screen –Colon cancer screen –Pneumonia vaccine ≥65 y –Osteoporosis screen/treat l Diabetes –HbA1c control –LDL control –Blood pressure control –Nephropathy screen/treat –Aspirin primary prevention l Preventive care –Mammography –Cervical cancer screen –Colon cancer screen –Pneumonia vaccine ≥65 y –Osteoporosis screen/treat

Best Practice Alert

Physician Sees Patient Who Needs Testing or Treatment

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

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

Display of Medical and Patient Reasons for Not Meeting Goals for Chronic Conditions

Preserving Physician Judgment: Removing Patients from QI Registries with “Global Exeptions”

Improving Quality for the Unseen Patient

Monthly List of Patients Sent to MD Provider: Marcus Welby, M. D. Name MRN DOB DOE, JANE /1/54 Consider antiplatelet drug for CHD JUAN, DON /4/37 Consider beta blocker for prior MI Consider ACE/ARB for CHD with DM SMITH, ZORRO /3/24 Consider antiplatelet drug for CHD Provider: Marcus Welby, M. D. Name MRN DOB DOE, JANE /1/54 Consider antiplatelet drug for CHD JUAN, DON /4/37 Consider beta blocker for prior MI Consider ACE/ARB for CHD with DM SMITH, ZORRO /3/24 Consider antiplatelet drug for CHD

Preliminary Results from First Three Months of UPQUAL

% Time (mo.) Month %

Time (mo.) % Month %

Summary l Advanced quality measurement can be built into physician work flow l Exceptions to quality measures can be used to drive focused QI activities l Accurate quality measurement can inform the care of an entire panel of patients (both seen and unseen) l Advanced quality measurement can be built into physician work flow l Exceptions to quality measures can be used to drive focused QI activities l Accurate quality measurement can inform the care of an entire panel of patients (both seen and unseen)