How can Meaningful Use lead to Meaningful Improvements in Hypertension Care? Peter J. Greco, M.D. The MetroHealth System







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How can “Meaningful Use”

lead to “Meaningful



Hypertension Care?

Peter J. Greco, M.D.

The MetroHealth System



z Who you are and what you hope to learn z Who I am and what I know

z What is “Meaningful Use”

z What works for improving hypertension care z Examples from a “real” EMR (Electronic

Medical Record; also known as an Electronic Health Record [EHR]).


Who am I?

z Primary Care Internist

z ABIM Certified 1990, Recertified 2000,

Re-recertified 2010

z Extensive experience building tools for

documentation and decision support in the EpicCare Electronic Medical Record


Stages of Electronic Medical

Record (EMR) Adoption

Source: Health Information and Management Systems Society


Key Points

z “Getting the data into the computer” is a

means to an end, not an end in itself

z The value comes in what you do with those


z Most EMR implementations today are


z The Government’s Meaningful Use incentives


Meaningful Use Roadmap

z There are 3 Stages of Meaningful Use

z Stage 1 (final rule released 2010) z Stage 2 (2013 ?)

z Stage 3 (2015 ?)

z We know a few things about Stage 2 and 3

z Incentives for use become Penalties for non-use z “Optional” will likely become “Mandatory”

z “Capable of X” will likely become “Actually doing X”


How might Meaningful Use help in the

care of your patients?

z We’ll review the Stage 1 MU Goals z We’ll look at some of the barriers to

improving hypertension control

z We’ll review what the literature tells us about

successful EMR-based intervention


Goals for Meaningful Use of the

Electronic Health Record (Stage 1)

z Improve quality, safety, efficiency, and reduce

health disparities

z Engage patients and families in their healthcare z Improve care coordination

z Improve population and public health

z Ensure adequate privacy and security protections

for personal health information

(note: I will only mention the incentives which are relevant to “Eligible Professionals”, not Hospitals)


Improve quality, safety, efficiency,

and reduce health disparities

z Use physician order entry for medications z Perform drug-drug and drug-allergy

interaction checks

z Implement drug-formulary checks z Transmit prescriptions electronically z Maintain up-to-date list of problems,


Improve quality, safety, efficiency,

and reduce health disparities

z Record & chart vital signs (Ht, Wt, BP, BMI, growth


z Record smoking status for patients 13+ years old z Record demographics (language, race, gender,


z Implement a clinical decision support rule and

track compliance with it


Improve quality, safety, efficiency,

and reduce health disparities

z Incorporate lab results as structured data

z Generate lists of patients by condition for quality

improvement, reduction of disparities, research or outreach

z Send reminders to patients for


Engage patients/families

in their health care

z Provide patients with an electronic copy of their

health information

z Provide clinical summaries for each office visit z Provide patients with timely electronic access to

their health informationwithin 4 business days of its availability

z Identify patient-specific education resources and


Improve care coordination

z Exchange key clinical information electronically z Perform medication reconciliation when

receiving a patient from another setting of care or provider of care

z Provide a summary of care record for each


Improve public health

z Submit electronic data to immunization registries z Submit electronic syndromic surveillance data to


It’s not Rocket Science

z The objectives are straightforward z You may already be doing a lot of it

z BUT you may have to change how you do it

z Has to be understood by the computer z Can’t be buried in your note


Quality Measures

z Similar in many ways to the Medicare Physician

Quality Reporting Initiative (PQRI)

z Based on “who you saw”, not “your patients”

z Potentially an issue for group practices z Accept the measures as being imperfect


Quality Measures in Stage 1:


z 3 “Core” Measures

z Hypertension: Blood Pressure Measurement (NQF 0013)

z Tobacco:

z a) Use Assessment (NQF 0028a)

z b) Cessation Counseling (NQF 0028b)

z Screening Adults for abnormal BMI & follow-up if abnormal (NQF


z 3 “Alternate” Core Measures may be substituted

z Weight Assessment and Counseling for Children and

Adolescents (NQF 0024)

z Influenza Immunization for Patients 50+ years old (NQF 0041)

z Childhood Immunization Status (NQF 0038)

z 12 individual measures rolled into one 0Final%20Rule.pdf for more details


Quality Measures in Stage 1:


z 3 “Optional” Measures must be reported

z Chosen from a menu of 38

z Considerable overlap with PQRI

z Examples relevant to hypertension:

z Last BP < 140/90 in people with hypertension

(NQF 0018)

z Last BP < 140/90 in people with diabetes


Trends in Hypertension, 1976-2000

Sources: NHANES II/III; Unpublished data for 1999–2000 computed by M. Wolz, National Heart, Lung, and Blood Institute; JNC 6


Barriers to improving

hypertension care


You see a patient later today with hypertension and diabetes. Blood pressure is 142/90. Patient has missed “a few” pills and is currently on Lisinopril 10mg daily.

You decide NOT to change the treatment regimen, and to have the patient return for follow-up.

When will you have the patient return?

z Within 2 weeks z In 3 to 4 weeks z In 6 weeks


Reference: 48/10/717.full.pdf+html

(accessed 9/29/2010)


Reasons we don’t adjust the medications when the visit BP is ≥140/90

z Home BP is “OK”: 18% (vs. 52%)*

z Repeat BP is < 140/90: 13% (vs. 61%)

z Provider is willing to permit a longer follow-up interval in

a hypothetical scenario

z “Follow up in ≤2 weeks”: 58% z “Follow up in 3-4 weeks”: 52% z “Follow up in > 4 weeks”: 41%

z Treatment goal is > 130: 33% (vs. 55% if goal is ≤ 130) z Discussed adherence at visit: 23% (vs. 52%)

*% of encounters in which the medication regimen was changed.  Patients had 

diabetes and hypertension, and had a lowest triage blood pressure of ≥ 140 mm Hg 


We think we’re doing better than we


z Percentage of patients on guideline-concordant


z Physician Perception: 75% z Reality: 67%

z Percentage of patients whose last BP was < 140/90:

z Physician Perception: 68% z Reality: 43%‐9343(04)00390‐0/abstract; accessed 


Protocol-Based Computer Reminders, the Quality of Care and the Non-Perfectibility of Man 19% 22% 22% 45% 61% 52% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Seek symptom or exam finding

Order a test Prescribe a treatment Type of Recommendation C o m p lia n ce No Reminder Reminder N Engl J Med 1976; 295:1351-1355


A Recent Meta-Analysis of

computerized reminders and alerts

z Care processes improved by reminders/alerts

z By a median of 4.2%

z Trend toward greater improvement when a

response to the reminder is required

z 12.9% vs. 2.7% [p=0.09]

z Brigham & Women’s (homegrown system)

outperformed the rest

z 16.8% vs. 3.0% [p=0.04]; accessed 9/29/2010


Provider Education, Provider Alerts,

and Patient Education

z Study of 1341 Hypertensive Veterans in the TN


z BP 140/90 or higher on 2 or more occasions

z On only one antihypertensive agent

z Providers were randomly assigned to:

z Provider education only

z Provider Education plus Clinical Alert

z Provider Education plus Alert plus Patient Education

z Outcomes:

z BP



no change in prescribing, but

big changes in systolic blood pressure

Group SBP: Change SBP: Mean SBP 140 DBP 90 Provider Education -12 145 42% 68% Provider Education + Alert -11 146 41% 59% Provider Education + Alert + Patient Education -16 138 60% 68%


Effects of lifestyle changes on

SBP (per JNC 7)

z Weight loss of 10kg: 5-20 mm Hg z DASH diet: 8-14 mm Hg z Sodium restriction: 2-8 mm Hg z Physical activity: 4-9 mm Hg


Effective Clinical Decision Support

has 4 features

Odds Ratio

95% C.I. P value

Automatic (part of clinician workflow) 112.1 12.9 to ∞ <0.00001

Provided at time and location of decision making

15.4 1.3 to 300.6 0.0263

Recommendation (rather than just an assessment)

7.1 1.3 to 45.6 0.0187

Computer based (vs. paper) 6.3 1.2 to 45.0 0.0294


Computerized Order Entry

Reduces Medication Errors


Hypertension-Specific Quality

Improvement Efforts

z Review of 44 studies

z 34 randomized controlled trials z 5 quasi-randomized trials

z 5 before-after studies

z Most studies involved multiple simultaneous



Systolic BP:

4.5 mm Hg



Diastolic BP:

2.1 mm Hg



What is “Team Change”?

z “assigning some patient care responsibilities

to someone other than the patient’s doctor”

z Pharmacist

z Nurse

z Physician assistant

z various models

z Complete “Outsourcing” of hypertension management to the


z Shared responsibility

z Physician-focused


VA Experience

z Re-engineering z Decision Support


VA Re-engineering

z In 1995 the VA launched a re-engineering

program including:

z Better use of information technology

z Measurement and reporting of performance z Integration of services

z Realigned payment policies


Substantial improvement in control

of hypertension (& other conditions)


0 10 20 30 40 50 60 70 80 90 100 % of m easur es ach ieved Chr onic Depr ess ion Diabe tes Lipid s Hype rten sion Preve ntiv e Scre enin g Diagn osis

VA performance is better than the rest for Chronic & Preventive Measures

VA National Sample



z Decision support system for hypertension

care developed at the VA

z Utilizes technology developed at Stanford

Medical Informatics

z Provides specific computerized point-of-care

recommendations when BP is not at target:

z Add a recommended medication

z Substitute a recommended medication (stop X, start Y)


Lessons from ATHENA

z All technology introduces new errors z Many potential sources of error

z Bugs

z Missing data

z Not checking drug interactions

z False expectations

z Rearrangement of clinical priorities

z Rare but serious problems may not be

recognized in initial testing

z As with drugs & devices &blobtype=pdf; accessed 9/30/2010


Sample EMR Tools

z From the EpicCare Ambulatory Electronic

Medical Record

z All Screen Shots Copyright 2010, Epic


Four EMR Views of BP (same patient)

Mean (std. dev.) blood pressure for the last 10 readings (09/02/2009 to 09/28/2010):

Systolic: 149.7 (17.6); coefficient of variation = 11.8% Diastolic: 81.6 (10.0); coefficient of variation = 12.3%


Another view: BP and medications

(same patient)


How information is displayed

can make a difference


Home Blood Pressure


z Randomized trial of standard vs. graphical

home BP monitor

z Standard monitor:

z Review individual readings

z Graphical monitor:

z Blood pressure trend vs. goal (135/85) z Average over the past week


Graphical display

resulted in faster

achievement of

target BP


Graphical displays should:

z Show the data

z Induce viewer to think about substance (rather than

methodology, graphic design, … or something else)

z Avoid distorting what the data have to say

z Present many small numbers in a small space

z Encourage the eye to compare different pieces of data z Reveal the data at several levels of detail, from a broad

overview to the fine structure


Prototype produced using Eastwood Charts (similar to Google Charts API);


Patient Lists/Reports

z Generated automatically from the structured

data in the EMR

z i.e. it’s a byproduct of Meaningful Use

z Provides a view of the entire panel of patients

with hypertension

z Not just who’s here today

z Can be used to identify patients who are:

z overdue for follow up


Criteria: Last SBP ≥150 AND Average SBP ≥150 AND no appointment scheduled


Criteria: Last SBP ≥150 AND Average SBP ≥150 AND no appointment scheduled AND last visit 14-365 days ago (21 patients found)


Issues with patient lists

z It has to be somebody’s job to work the list z PCP has to be correct

z You can spend a lot of time chasing phantom


z Currently we have no method to document “what


Patient Portals

z Patients love them

z Doctors tend to be afraid they will be deluged z Test results can be communicated quickly

and without the cost of postage

z Portals meet a number of Meaningful Use

Requirements, while avoiding the



z We don’t know a lot about what works in

EMR technology

z Or why it works (or doesn’t work) z It’s not anywhere near maturity

z Simply digitizing our old models of care and

documentation won’t accomplish much

z Alerts can help


Thank You



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