Fall Related Injury Risk Clinical Trial
Official title:
Reducing Injuries From Medication-Related Falls by Generating Targeted Computerized Alerts for High Risk Patients Within an Electronic Prescribing System
Drug-related illness accounts for 5% to 23% of hospital admissions, and is now claimed to be
the sixth leading cause of mortality. Older adults are at higher risk of adverse drug-related
events, and medication-related fall injuries are the most common adverse event that could be
potentially prevented. There are 1.2 million falls per year among Canadian elderly, at a cost
of $2.4 billion in health care services, and substantial risk of loss of independence.
The overall purpose of this research program is to reduce medication-related fall injuries by
using computerized electronic prescribing and drug management systems to identify high risk
patients and provide physicians with patient-specific recommendations for modifying
psychotropic medication use to reduce this risk.
Background: Fall-related injuries account for significant morbidity and mortality,
particularly in the elderly where multiple comorbidities and age-related changes in bone
density increase the risk of fall-related fractures Indeed use of psychotropic medications in
elderly persons is associated with a 2 to 29 fold increase in the risk of falls and a 2 to 5
fold increase in the risk of hip fracture. At particular risk are individuals over the age of
70, those with a prior history of falls, cognitive impairment, stroke, Parkinson's disease,
or other conditions that would impair balance or gait. In our particular study population,
67.5% of persons with a psychotropic drug prescribing problem had at least one additional
risk factor for fall-related injuries. This was particularly true for women who not only were
more likely to have a psychotropic drug prescribing alerts than men but were also more likely
to have other risk factors. 70.3% of women who had a psychotropic prescribing alert had other
risk factors in comparison to 62.1% of men, particularly as it related to older age and a
history of a fall-related fracture or soft-tissue injury in the past 12 months. A recent
in-hospital study showed that providing physicians with patient-specific recommendations for
changes in high risk psychotropic therapy through a computerized order-entry system reduced
the prescription of non-recommended drugs and doses by 10%, which in turn was associated with
a significant two-fold reduction in the in-hospital fall rate{5007}. If even a 5% reduction
(annual prevalence 16.1% to 11.1%) could be achieved in primary care through targeted
recommendations for high risk patients with psychotropic drug prescribing alerts, we would
expect that it could conservatively reduce the number of falls among Canadian elderly
(assuming the lowest risk of RR=1.66) from 116,064 to 82,212 and the number of fall-related
injuries from 11,606 to 8,221. Based on the average costs of treating fall-related injuries
of $20,000/injury{5006}, a reduction in adverse events of this magnitude would be associated
with an annual savings of $67,708,000 in direct care costs. The research question is the
following: Can medication-related fall injuries be reduced by using computerized electronic
prescribing and drug management systems to identify high risk patients and provide physicians
with patient-specific recommendations for modifying psychotropic medication use to reduce
this risk?
Objective: To determine the extent to which a targeted psychotropic drug alert and
recommendation system will reduce
a) the rate of potentially inappropriate psychotropic medication for patients at risk of
fall-related injuries, and b) fall-related injury risk, fall-related injuries and
hospitalizations.
Research Plan : A single blind, cluster randomized controlled trial will be conducted to test
the hypothesized benefits of the targeted psychotropic drug alert and recommendation system
versus the standard automated generic drug alert system within a fixed cohort of primary care
physicians and an open cohort of patients seen by study physicians in the 16 month follow-up
period for the assessment of reductions in potentially inappropriate psychotropic
prescriptions and fall-related injuries. A single blind trial was planned because
intervention status cannot be blinded for physicians in the study. However, study
participants are blinded to the outcomes assessed, because the data required to assess these
outcomes can be predominantly collected and assessed using data sources that are independent
of the intervention status. Patients, clustered within physicians, is the unit of analysis
because patient level information provides the most precise, non-ecological, method of the
study outcomes as well as potential confounders, and because hierarchical multivariate
analytic methods are now available to model clustering in the assessment of treatment
effect{Chuang, 2000 4339 /id}. The benefit of the intervention will be assessed by comparing
patients of physicians who received the psychotropic drug alert and recommendation system and
patients of physicians who received automated drug decision support. This approach minimizes
Hawthorne effects, arising from the intensive nature of practice intervention required to
support computer-based systems in primary care that would likely result in over-estimation of
benefit if computer-based decision support for drug management were compared to physicians
with no computerized intervention. Further, it provides a means by which information on
prescriptions, drug and disease profile can be assessed in an equivalent way between patients
of physicians with automated control or targeted alert experimental decision-support,
reducing biases related to differences in measurement sources.
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