Utilizing the Electronic Medical Record to
Reduce Inappropriate Medication Use
Alan White, PhD – Abt Associates
Valerie Weber, MD – Geisinger
Health System
Background
• Falls are a common problem threatening the
independence of older individuals.
– Falls have serious health and economic consequences
– One of every three adults over the age of 65 in the United States
suffers one or more falls each year, as do almost 50 percent of
elders more than 80 years old
– 1.8 million fall-related ER visits among over 65 population
(34.7 million persons) – cost $16.4 billion (Lewin 2000)
• Previous studies have shown that medications (number
and use of psychotropic medications) is a risk factor for
falls.
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Study Questions
• Computerized reminder systems have improved the
performance of cancer screening, and other preventive
services.
• Can they work to influence polypharmacy, and perhaps
decrease falls, in the elderly at risk population?
– Would physicians read and respond to the messages they
received as part of the intervention?
– Would the intervention lead to changes in the use of
medications, particularly psychotropic medications?
– How would the intervention affect falls and medical costs?
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Population Studied and Design
• Patients for study were identified based on age and
medications
– Patients of Geisinger Health System, which serves predominantly
an aging and elderly rural population spread across 31 counties
in central Pennsylvania.
– Age over 70
– 4+ active medications; at least one psychotropic medication
• Patients were assigned to intervention or comparison
group by clinic.
– Stratified by location to ensure that physicians receiving
intervention were not caring for comparison group patients.
– 15 intervention sites (n=413); 3 comparison sites (n=207)
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The intervention
• Pharmacist review of medications
– Primary care physician was advised of the results of a review of
the patient’s medications by a pharmacist, using a messaging
function on the EMR.
– The message informs the physician that the patient has been
identified as being at risk of falls because of their age and
medication history.
– Made individualized suggestions regarding medications, often
focused on the use of psychoactive medications
– Sent through the EMR
• Message to physician included a link to best practice
guidelines based on material from the American Geriatrics
Society/American Academy of Orthopedic Surgery
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The Message:
As part of a research study on patient safety in the elderly being
conducted by the Department of General Internal medicine, your
patient (name) has been identified as being at risk for falls based
on age and medication history. Falls are a major cause of morbidity
in the elderly and account for 6% of all medical expenditures in
this population. Decreasing polypharmacy in the elderly, and in
particular certain medications such as benzodiazepines, has been
shown to reduce the risk of falls in this population.
(Patient’s name) has had a medication review conducted via EPICcare
by a GHS pharmacist.
The following medications should be reviewed/changed as you deem
appropriate:
(Specific recommendations inserted here)
An evidence-based guideline for fall prevention in the elderly is
found under the Pathways button on EPICcare for your review. This
guideline contains simple, practical ways to reduce the risk of
falls in your patients.
Thank you,
Elderly Falls Study Team
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Data Sources
• Survey of participating physicians
• GHS Electronic Medical records (hospitalizations,
physician encounters, prescription medications); no
nursing home data
• Fall-related encounters identified based on diagnosis and
procedure codes. Chart review was used to determine
whether some encounters were fall-related.
• Patient telephone survey: Self-reported information on
number of falls (collected quarterly by a GHS nurse)
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Almost All Physicians Read the Messages They
Received and Many Responded In Some Way
 78% reported having read “all” of the message
 47% reported having reviewed the fall guideline
 26% reported having altered their patient management in
some way, including:
 asked more about falls (62%)
 Increased awareness about falls (50%)
 More attention to polypharmacy in the elderly (100%)
 Changed medications (63%)
 Stopped medications (25%)
 High response may be due to personal nature of message
from pharmacist-- not an automated reminder.
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Intervention Had No Apparent Impact on
Number of Medications Started
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Number of Psychotropic Medications Decreased
for Intervention Group (Months 1-6)
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Number of Psychotropic Medications Started:
No Significant Impact
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Impact Was Significant for Subset of Patients
with Two or More Psychotropic Meds at Baseline
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Results – Falls
• Two measures of falls– medical records (EpicCare)
and patient survey
– Fall rates over the 12-month study period:
• Medical Records: 20% intervention group, 23% for
comparison group (insignificant difference)
• Self-Reported: 36% for intervention group, 40% for
comparison group (significant difference only in quarter
2)
• Multivariate results:
– Medical Records: Intervention associated with significantly
fewer fall-related diagnoses (p < .01)
– Self-Reported: Insignificant difference
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Medical Costs
• No statistically significant difference seen in total health
care costs between the intervention and control groups
• Lack of data on nursing home costs limits our ability to
conduct cost-effectiveness analysis
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Conclusions
• The current study supports the use of the EMR to drive
best practice.
• We believe that using a pharmacy driven EMR protocol
can reduce the use of psychotropic medications in the
elderly and therefore falls.
• Pharmacist-physician partnerships hold great promise
and are underutilized.
• The intervention is not costly and could be replicated in
health care systems without an EMR.
• One factor limiting adoption may be that the savings in
terms of avoided medical costs are not captured by the
organization that pays for the intervention.
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