How can “Meaningful Use”
lead to “Meaningful
Improvements”
in
Hypertension Care?
Peter J. Greco, M.D.
The MetroHealth System
Agenda
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
dadta
z Most EMR implementations today are
incomplete
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)
https://www.cms.gov/EHRIncentivePrograms/Downloads/MU_Stage1_ReqSummary.pdf
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
charts)
z Record smoking status for patients 13+ years old z Record demographics (language, race, gender,
etc.)
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:
Required
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
0421)
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
http://www.ihs.gov/recovery/mu_documents/Summary_MU%20Stage%201_CMS%2 0Final%20Rule.pdf for more details
Quality Measures in Stage 1:
Optional
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:
http://www.annals.org/content/1 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
are
z Percentage of patients on guideline-concordant
medications:
z Physician Perception: 75% z Reality: 67%
z Percentage of patients whose last BP was < 140/90:
z Physician Perception: 68% z Reality: 43%
http://www.amjmed.com/article/S0002‐9343(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]
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2842864/pdf/182e216.pdf; accessed 9/29/2010
Provider Education, Provider Alerts,
and Patient Education
z Study of 1341 Hypertensive Veterans in the TN
Valley:
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
Results:
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 HgEffective 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
interventions
Systolic BP:
↓
4.5 mm Hg
(median)
Diastolic BP:
↓
2.1 mm Hg
(median)
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
non-physician
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
ATHENA-HTN
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
http://www.ncbi.nlm.nih.gov/bookshelf/picrender.fcgi?book=aps&part=A1140 &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
Monitoring
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
patients
z Currently we have no method to document “what
Patient Portals
z Patients love themz 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
Conclusions
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