Patricia Quigley

Effects of Telerehabilitation on Physical Function and Disability for Stroke Patients: A Randomized, Controlled Trial

Background and Purpose— To determine the effect of a multifaceted stroke telerehabilitation (STeleR) intervention on physical function, and secondarily on disability, in veterans poststroke. Methods— We conducted a prospective, randomized, multisite, single-blinded trial in 52 veterans with stroke from 3 Veterans Affairs medical centers. Veterans with a stroke in the preceding 24 months were randomized to the STeleR intervention or usual care. The STeleR intervention consisted of 3 home visits, 5 telephone calls, and an in-home messaging device provided over 3 months to instruct patients in functionally based exercises and adaptive strategies. Usual care participants received routine rehabilitation care as prescribed by their physicians. The primary outcome measures were improvement in function at 6 months, measured by both the motor subscale of the Telephone Version of Functional Independence Measure and by the function scales of the Late-Life Function and Disability Instrument. Results— The 2 complementary primary outcomes (Late-Life Function and Disability Instrument Function and Telephone Version of Functional Independence Measure) improved at 6 months for the STeleR group and declined for the usual care group, but the differences were not statistically significant (P=0.25, Late-Life Function and Disability Instrument; P=0.316). Several of secondary outcomes were statistically significant. At 6 months, compared with the usual care group, the STeleR group showed statistically significant improvements in 4 of the 5 Late-Life Function and Disability Instrument disability component subscales (P<0.05), and approached significance in 1 of the 3 Function component subscales (P=0.06). Conclusions— The STeleR intervention significantly improved physical function, with improvements persisting up to 3 months after completing the intervention. STeleR could be a useful supplement to traditional poststroke rehabilitation given the limited resources available for in-home rehabilitation for stroke survivors. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00384748.

Fall prevention and injury protection for nursing home residents.

Recognizing that risk factors for falls are multifactorial and interacting, providers require guidance on the components, intensity, dose, and duration for an effective fall and fall injury prevention program. Administrators of health care facilities require guidance on resources needed for these programs. Clear guidance does not exist for specifying the right combination of interventions to adequately protect specific at-risk populations, such as nursing home residents with dementia or osteoporosis. Staff education about fall prevention and resident fall risk assessment and reassessments has become part of standards of practice; however, the selection, specificity, and combination of fall prevention and injury protection interventions are not standardized. To address these gaps, this team of researchers conducted a critical examination of selected intervention studies relevant to nursing home populations. The objectives of this literature review were to (1) examine the selection and specificity of fall prevention and injury protection interventions described in the literature since 1990; (2) evaluate the strength of evidence for interventions that both prevent falls and protect residents from fall-related injury; and, (3) provide clinical and policy guidance to integrate specific interventions into practice.

Study protocol: home-based telehealth stroke care: a randomized trial for veterans

BackgroundStroke is one of the most disabling and costly impairments of adulthood in the United States. Stroke patients clearly benefit from intensive inpatient care, but due to the high cost, there is considerable interest in implementing interventions to reduce hospital lengths of stay. Early discharge rehabilitation programs require coordinated, well-organized home-based rehabilitation, yet lack of sufficient information about the home setting impedes successful rehabilitation. This trial examines a multifaceted telerehabilitation (TR) intervention that uses telehealth technology to simultaneously evaluate the home environment, assess the patients mobility skills, initiate rehabilitative treatment, prescribe exercises tailored for stroke patients and provide periodic goal oriented reassessment, feedback and encouragement.MethodsWe describe an ongoing Phase II, 2-arm, 3-site randomized controlled trial (RCT) that determines primarily the effect of TR on physical function and secondarily the effect on disability, falls-related self-efficacy, and patient satisfaction. Fifty participants with a diagnosis of ischemic or hemorrhagic stroke will be randomly assigned to one of two groups: (a) TR; or (b) Usual Care. The TR intervention uses a combination of three videotaped visits and five telephone calls, an in-home messaging device, and additional telephonic contact as needed over a 3-month study period, to provide a progressive rehabilitative intervention with a treatment goal of safe functional mobility of the individual within an accessible home environment. Dependent variables will be measured at baseline, 3-, and 6-months and analyzed with a linear mixed-effects model across all time points.DiscussionFor patients recovering from stroke, the use of TR to provide home assessments and follow-up training in prescribed equipment has the potential to effectively supplement existing home health services, assist transition to home and increase efficiency. This may be particularly relevant when patients live in remote locations, as is the case for many veterans.Trial RegistrationClinical Trials.gov Identifier: NCT00384748

Incidence and Cost of Serious Fall-Related Injuries in Nursing Homes

Background: Fall-related injuries (FRIs) result in morbidity and mortality for patients, as well as unnecessary expense to health care institutions. Objectives: (a) Estimate the incidence of falls and FRIs with a nursing home as the source of admission in Veterans Administration (VA) and non-VA facilities. (b) Estimate the cost of hospitalizations for each level of FRI severity. Research Design: Retrospective analysis of falls and FRI resulting in a hospitalization whose source of admission was a VA nursing home. Data: Falls and FRIs were obtained from Minimum Data Set (MDS) reports (January 2007-June 2009). Costs were obtained from the VA Decision Support System reports and Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) reports (2000-2006). Measures: Incidence of falls, fracture incidence, number of hospitalizations for FRIs, and costs associated with hospitalization for by level of FRI severity. Results: Fall incidence was 10.6% in VA and 13.1% in CMS facilities. Fracture incidence was 0.9% in VHA and 1.65% in CMS facilities. Over a 3-year period, there were 2,400 admissions to VHA hospitals for FRI, with 55.4% hip fractures and10.1% intracranial injuries, with an average cost of US

Central Nervous System Medication Changes and Falls in Nursing Home Residents

23,723 per admission. Over a 9-year period, there were 141,308 admissions from nursing homes to non-VA hospitals for FRIs, with 38.8% hip fractures, 35.7% other fractures, and 11.1% intracranial injuries, with an average cost of US

Clinical practice algorithms: Medication management to reduce fall risk in the elderly—Part 4, Anticoagulants, anticonvulsants, anticholinergics/bladder relaxants, and antipsychotics

31,507 per admission. Conclusions: Prevention program emphasis should shift away from a focus on preventing falls as a measure of quality care to decreasing FRIs. These findings support implementation of injury prevention programs for the elderly that reduces risk for injury as the primary outcome.

Clinical practice algorithms: medication management to reduce fall risk in the elderly--part 2, summary algorithm.

We investigated the role of changes in 6 mutually exclusive medication categories on the risk of falling in nursing home residents. The 6 categories were: gastrointestinal, hypoglycemics, antibiotics, central nervous system (CNS) acting, cardiovascular disease agents, and analgesics. A change was defined as a new start, a dose change, an as-needed dose, or a discontinuation. Incident reports were used to determine the fall date and time. Medication records were abstracted to identify the date of changes before the date of each fall. The 158 residents who fell had 419 recorded falls during 2002 and 2003; they were on average 80.5 years old (SD 8.1; range 65-103), and 67% were men. Within 1-3 days of a change in any CNS medication (antipsychotic, sedative, antidepressant, or antiseizure), the fall risk (odds ratio) increased 3.4-fold (95% confidence interval 1.2-9.5) using 7-9 days prior as comparable control days. No changes in other medication categories had a significant effect on fall risk. These data suggest that the risk of falls among nursing home residents is significantly elevated within 3 days of a CNS medication change.

Clinical practice algorithms: Medication management to reduce fall risk in the elderly—Part 3, benzodiazepines, cardiovascular agents, and antidepressants

This article, the final in a series of evidence-based medication algorithms to reduce medication-related risks for elderly at risk for falls, presents subalgorithms for specific medication classes associated with increased risk of falling or fall-related injuries. The medication classes reviewed here are anticoagulants, anticonvulsants, anticholinergics/bladder relaxants, and antipsychotics. We presented the process of development of the algorithms in our first article (Quigley, 2007) and the summary algorithms (algorithms 1 and 2) in our second article (Bulat, Castle, Rutledge, & Quigley, 2008a) in this series. In the third one (Bulat, Castle, Rutledge, & Quigley, 2008b), we presented specific algorithms for benzodiazepines, cardiovascular agents, and antidepressants (algorithms 3–5). This fourth article in the series reviews the development of specific subalgorithms for algorithms 6–9 for management of anticoagulants, anticonvulsants, anticholinergics/bladder relaxants, and antipsychotics. There are a number of ways in which drugs might increase the riskof anelderlyperson falling, themost common being sedation, impaired balance and reaction time, orthostatic hypotension, and drug-induced parkinsonism (Campbell, 1991). Medications are a potentially modifiable factor, which can reduce fall risk (Campbell, Robertson, Gardner, Norton, & Buchner, 1999; Close et al., 1999; Tinetti, 2003). There are associations between the falls and the use of sedatives, psychotropics, cardiovascular agents, antidepressants, and polypharmacy (Fick et al., 2003; Neutel, Perry, & Maxwell, 2002; Schwab et al., 2000; Smith, 2003). Both medication use and falls increase with advancing age. The frailest patients (those most likely to fall) are often receiving the greatest number of medications, and improving their drug regimen is an effective way of reducing fall risk (Haumschild, Karfonta, Haumschild, & Phillips, 2003). The guideline for the prevention of falls in older persons (American Geriatrics Society, British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Falls Prevention, 2001) states that ‘‘patients who have fallen should have their medications reviewed and altered or stopped, as appropriate, in light of their risk of future falls. Particular attention to medication reduction should be given to older persons taking four or more medications and those taking psychotropic medications (grade C)’’ (p. 668). The panel also reminds us that ‘‘For all

A randomized controlled trial on Stroke telerehabilitation: The effects on falls self-efficacy and satisfaction with care

In the previous issue, we reported the process used in the development of the clinical practice algorithms to reduce fall risk in the elderly. In this issue, we present the summary algorithms,whichwill be followedbyadescriptionof individual algorithms for a specific drug class in the subsequent issues of the journal. Falls are common in older adults. It is estimated that about 30% of community-living people over 65 years of age fall at least once a year. The fall rate increases in acutely ill elderly admitted to a hospital and is even higher in frail, elderly nursing home residents (Rubenstein et al., 2002). Many of these falls lead to fractures,most serious being the hip fractures. Falls are the leading cause of accidental death among people age 75 years or older and are responsible for appreciable morbidity and admission to long-term care facilities (Tinetti & Williams, 1997). Both medication use and falls increase with advancing age. The frailest patients (those most likely to fall) are often receiving the greatest number of medications, and improving their drug regimen is an effective way of reducing fall risk (Haumschild, Karfonta, Haumschield, & Phillips, 2003). There are a number of ways in which drugs might increase the risk of an elderly person falling, most common being sedation, impaired balance and reaction time, orthostatic hypotension, and drug-induced parkinsonism (Campbell, 1991). Associations exist between falls and the use of sedatives, psychotropics, cardiovascular agents, antidepressants, and polypharmacy (Leipzig, Cumming, & Tinetti, 1999a,b; Neutel, Perry, & Maxwell, 2002; Smith, 2003). Medications are a potentially modifiable factor, which can reduce fall risk (Campbell, Robertson, Gardner, Norton, & Buchner, 1999; Tinetti, 2003). Thus, primary care providers are in a pivotal position to assess patients for underlying risk factors for falls and to intervene to decrease medicationrelated risk for falls. Methods

Exercise interventions, gait, and balance in older subjects with distal symmetric polyneuropathy: a three-group randomized clinical trial.

There are associations between falls and the use of sedatives, psychotropics, cardiovascular agents, antidepressants, and polypharmacy (Leipzig, Cumming, & Tinetti, 1999a,b; Neutel, Perry, & Maxwell, 2002; Smith, 2003; French et al., 2006). Our third article in the series will review the development of specific subalgorithms for benzodiazepines (BZDs), cardiovascular agents, and antidepressants (algorithms 3–5). We presented the process of development in our first article and the summary algorithm (algorithms 1 and 2) in our second article in this series. There are a number of ways in which drugs might increase the risk of an elderly person falling,most common being sedation, impaired balance and reaction time, orthostatic hypotension, and drug-induced parkinsonism (Campbell, 1991; Fick et al., 2003; Seymour & Routledge, 1998). Medications are a potentially modifiable factor which can reduce fall risk (Campbell, Robertson, Gardner, Norton, & Buchner, 1999; Tinetti, 2003; Williams, 2002). The Guideline for the prevention of falls in older persons (American Geriatrics Society, British Geriatrics Society and American Academy of Orthopaedic Surgeons Panel of Falls Prevention, 2001) states that patients who have fallen should have their medications reviewed and altered or stopped as appropriate in light of their risk of future falls.