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Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry H. Gurwitz, M.D. Executive Director Meyers Primary Care Institute Chief, Division of Geriatric Medicine University of Massachusetts Medical School Worcester, Massachusetts
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Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Dec 25, 2015

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Page 1: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Using Clinical Decision Support Systems to Measure and Improve Quality of Care for

Special Populations:The Elderly in the Long-term Care Setting

Jerry H. Gurwitz, M.D.Executive Director

Meyers Primary Care InstituteChief, Division of Geriatric Medicine

University of Massachusetts Medical SchoolWorcester, Massachusetts

Page 2: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

It is much easier to write upon a disease than upon a remedy. The former is in the hands of nature and a faithful observer

with an eye of tolerable judgement cannot fail to delineate a likeness. The latter will ever be subject to the whim,

the inaccuracies and the blunder of mankind.

William Withering (1741-1799)

Page 3: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study

E.G. is an 85 year-old female nursing home resident with a history of atrial fibrillation, stroke, dementia, and hypertension, who is receiving chronic therapy with warfarin. Her primary care provider has been dosing her warfarin to maintain her at an INR of 2.0.

Page 4: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study

One evening, a covering physician is called with a report that the patient has developed a fever. The patient is initiated on empiric antibiotic therapy with cephalexin (500 mg po TID for 7 days) to treat a presumed urinary tract infection.

Page 5: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study

The next morning the primary care physician is called with the previous day’s INR, 1.75. He increases the daily warfarin dose from 4 mg to 5 mg per day. He is not notified of the cephalexin ordered the previous evening by the covering physician.

Page 6: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study

One week later, the INR comes back at 13.8 and a covering physician is notified. That evening’s warfarin dose is held. The INR the following day is 16.1. The warfarin continues to be held. No vitamin K is administered.

Page 7: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study

The very next day the patient develops congestion and shortness of breath. A chest x-ray reveals an infiltrate and the covering physician orders Augmentin 875 mg po q12 hours for 10 days. The next day the patient passes tarry stool and omeprazole is initiated.

Page 8: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case Study The following morning the patient’s

hematocrit is 25 and her INR is 11.3. The primary care physician is notified, and vitamin K 10 mg sc is administered for 3 days with a decrease in the INR to 0.9. The physician writes that warfarin will not be reinitiated because anticoagulation has been difficult to control for unclear reasons.

Page 9: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Casade

B.F. is an 80 year-old female nursing home resident with a history of Parkinson’s Disease treated with long-term Sinemet therapy (25-100 TID). She has suffered occasional hallucinations attributed to the Sinemet therapy, which have recently increased in frequency. The hallucinations sometimes involve large animals and can be quite terrifying.

Page 10: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

The resident is initiated on olanzapine 2.5 mg at bedtime. Due to agitation and continued hallucinations, the olanzapine dose is increased to 5 mg and lorazepam 0.5 mg po q4 hours prn is added to the medication regimen. The hallucinations continue and the evening dose of olanzapine is increased to 7.5 mg.

Page 11: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

The resident is noted by the nursing staff to be shaky and stiff, but no change is made in the olanzapine dose. She becomes increasingly lethargic. She is described as rigid and stooped over with ambulation and begins to have more difficulty with activities of daily living including bathing, dressing, toileting, and tranferring. She begins to require a wheelchair.

Page 12: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

The resident’s functional decline is attributed to Parkinson’s Disease...

Page 13: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Measuring the quality of prescribing to the elderly?

• The Beers list

• List of 33 drugs– Drugs that should always be avoided

– Drugs that are rarely appropriate

– Drugs with some indications, but that are often misused

Page 14: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

11 drugs that should always be avoided in the elderly:

• Barbiturates

• Chlorpropamide

• Flurazepam

• Meperidine

• Meprobamate

• Pentazocine

• Belladonna alkaloids

• Dicyclomine

• Hyoscyamine

• Propantheline

• Trimethobenzamide

Zhan et al. JAMA 2001

Page 15: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Use of “Always Avoid” Drugs

2.6% 2.9%5.1%

0

2

4

6

8

10

1996 U.S. 1996Ontario

2000-2001US HMOs

Per

cen

t

Page 16: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Incidence and Preventability of Adverse Drug Events in Two

Large Academic Long-term Care Facilities

Funded by AHRQ

Page 17: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Adverse Drug Events

Medication Errors

ADEs

Preventable

Page 18: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Methods

• Study conducted in two large academic long-term care facilities

• Total of 1229 beds

• Time period: 2000-2001

Page 19: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Methods

Drug-related incidents were detected using multiple methods:

• Review of nursing home records in monthly segments

• Computer-generated signals

Page 20: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Computer Generated Signals

• Abnormal laboratory results• Elevated INRs, high potassium levels

• Medications (antidotes)• Vitamin K, sodium polystyrene sulfonate

• Abnormal drug levels• Phenytoin• Digoxin

Page 21: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Methods

• Chart reviews were performed by trained clinical pharmacist investigators

• Incidents were classified by two independent physician reviewers:

– adverse drug event

– severity

– preventability

Page 22: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Results - Event Rates

• Adverse drug events

– Events: 815

– Rate: 9.8 per 100 resident-months

• Preventable adverse drug events

– Events: 338– Rate: 4.1 per 100 resident-months

Page 23: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Adverse Drug Events (n=815)Preventable vs Non-Preventable

58%42% Preventable

Non-Preventable

Page 24: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Adverse Drug Events by Severity(n=815)

Category Number Percentage

Fatal 4 <1%

Life-threatening

33 4%

Serious 188 23%

Less serious 590 72%

Page 25: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Preventability of Adverse Drug Events

Of fatal, life-threatening & serious events

Of less serious events

Preventable61% Preventable

34%

Page 26: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Error Stage for Preventable ADEs(n=338 preventable ADEs)

Category Number Percentage

Ordering 198 59%

Dispensing 16 5%

Administration 43 13%

Monitoring 271 80%

Page 27: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Drug Categories

Warfarin 12%

Atypical antipsych 12%

Loop diuretics 10%

Benzos (intermediate) 9%

Opioids 8%

ACE inhibitors 8%

Other antidepressants 7%

Antiplatelets 7%

Insulin 5%

Laxatives 5%

Preventable events

Page 28: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Event Categories - Preventable

Neuropsychiatric 29%

Hemorrhagic 16%

Gastrointestinal 16%

Renal/electrolytes 12%

Fall with injury 5%

Cardiovascular 4%

Fall without injury 3%

EPS 2%

Syncope/dizziness 2%

Page 29: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Guiding Principles for Quality Measures

• Compelling importance

• Clear relevance to improving care

• Parsimony

• Reasonable administrative burden

Page 30: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Guiding Principles for Development of Quality Measures

Is it possible to arrive at a set of measures that are of compelling importance and which have clear relevance to care, and that are also scientifically valid, usable, and feasible?

Page 31: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Translating Quality Measures into Clinical Decision Support

Co

mp

lexi

ty

Validity

DrugData

Drugs & Dx’s

Drugs, Dx’s& Labs

Drugs, Dx’s, Labs& Clinical Info

Page 32: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

CPOE with Clinical Decision Support at Baycrest Centre for Geriatric Care in

Toronto, Ontario

Page 33: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.
Page 34: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.
Page 35: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Big Question

Can the types of errors and events that I shared with you be captured with a set of quality measures that can guide the development of computerized clinical decision support systems in the long-term care setting?

Page 36: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.
Page 37: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Quality Indicators for Appropriate Medication Use in Older Adults

Assessing Care of Vulnerable Elders (ACOVE)

• Warfarin: INR should be monitored using standardized protocols

• Loop diuretics: Check electrolytes within 1 week and at least annually

• Avoid chlorpropamide• Avoid drugs with strong anticholinergic

properties• Avoid barbiturates• Avoid meperidine• ACE inhibitors: Monitor renal function and

potassium in patients on ACE inhibitors

Page 38: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Quality Indicators for Appropriate Medication Use in Older Adults

Assessing Care of Vulnerable Elders (ACOVE)

• Document the indication for a new drug therapy

• Educate patients on the benefits and risks

• Maintain a current medication list• Document response to therapy• Periodically review ongoing need for

therapy

Page 39: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

Drug 1

ADE

Drug 2

Page 40: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

DRUG 2 == PROXY FOR ADE

Page 41: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case-Control Study Design

Drug Exposure:Yes or No?

Drug Exposure:Yes or No?

BEGIN

Cases(ADE)

Controls

CLASSIFY/COMPARE

Page 42: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

Metoclopramide

Extrapyramidal Effects

Levodopa Rx

Page 43: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Case-Control Study Design

Metoclopramide:Yes or No?

Metoclopramide:Yes or No?

BEGIN

L-dopaRx

Controls

CLASSIFY/COMPARE

Page 44: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Results

Metoclopramide users were over three times more likely to begin

use of L-dopa therapy compared with non-users

(OR=3.09; 95% CI 2.25 to 4.26).

Page 45: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Likelihood of L-dopa Treatment by Metoclopramide Dose

1.2

3.3

5.3

0

1

2

3

4

5

6

>0-10 >10-20 >20

DAILY DOSE (mg/day)

OD

DS

RA

TIO

Page 46: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

Conclusion

Metoclopramide confers an increased risk for the initiation of treatment generally reserved

for the managment of idiopathic Parkinson’s disease.

Page 47: Using Clinical Decision Support Systems to Measure and Improve Quality of Care for Special Populations: The Elderly in the Long-term Care Setting Jerry.

The Prescribing Cascade

Drug 1

ADE

Drug 2