ContextEffective multifactorial interventions reduce the frequent falling rate of older patients by 30% to 40%. However, clinical consensus suggests reserving these interventions for high-risk patients. Limiting fall prevention programs to high-risk patients implies that clinicians must recognize features that predict future falls.ObjectiveTo identify the prognostic value of risk factors for future falls among older patients.Data Sources and Study SelectionSearch of MEDLINE (1966-September 2004), CINAHL (1982-September 2004), and authors' own files to identify prospective cohort studies of risk factors for falls that performed a multivariate analysis of such factors.Data ExtractionTwo reviewers independently determined inclusion of articles and assessed study quality. Disagreements were resolved by consensus. Included studies were those identifying the prognostic value of risk factors for future falls among community-dwelling persons 65 years and older. Clinically identifiable risk factors were identified across 6 domains: orthostatic hypotension, visual impairment, impairment of gait or balance, medication use, limitations in basic or instrumental activities of daily living, and cognitive impairment.Data SynthesisEighteen studies met inclusion criteria and provided a multivariate analysis including at least 1 of the risk factor domains. The estimated pretest probability of falling at least once in any given year for individuals 65 years and older was 27% (95% confidence interval, 19%-36%). Patients who have fallen in the past year are more likely to fall again [likelihood ratio range, 2.3-2.8]. The most consistent predictors of future falls are clinically detected abnormalities of gait or balance (likelihood ratio range, 1.7-2.4). Visual impairment, medication variables, decreased activities of daily living, and impaired cognition did not consistently predict falls across studies. Orthostatic hypotension did not predict falls after controlling for other factors.ConclusionsScreening for risk of falling during the clinical examination begins with determining if the patient has fallen in the past year. For patients who have not previously fallen, screening consists of an assessment of gait and balance. Patients who have fallen or who have a gait or balance problem are at higher risk of future falls.

Introduction: One third of older adults fall each year, and falls are costly to both the patient in terms ofmorbidity and mortality and to the health system. Given that falls are a preventable cause of injury, ourobjective was to understand the characteristics and trends of emergency department (ED) fall-relatedvisits among older adults. We hypothesize that falls among older adults are increasing and examinepotential factors associated with this rise, such as race, ethnicity, gender, insurance and geography.Methods: We conducted a secondary analysis of data from the National Hospital AmbulatoryMedical Care Survey (NHAMCS) to determine fall trends over time by examining changes in EDvisit rates for falls in the United States between 2003 and 2010, detailing differences by gender,sociodemographic characteristics and geographic region.Results: Between 2003 and 2010, the visit rate for falls and fall-related injuries among people age≥ 65 increased from 60.4 (95% confidence interval [CI][51.9-68.8]) to 68.8 (95% CI [57.8-79.8]) per1,000 population (p=0.03 for annual trend). Among subgroups, visits by patients aged 75-84 yearsincreased from 56.2 to 82.1 per 1,000 (P <.01), visits by women increased from 67.4 to 81.3 (p =0.04), visits by non-Hispanic Whites increased from 63.1 to 73.4 (p < 0.01), and visits in the Southincreased from 54.4 to 71.1 (p=0.03).Conclusion: ED visit rates for falls are increasing over time. There is a national movement toincrease falls awareness and prevention. EDs are in a unique position to engage patients on futurefall prevention and should consider ways they can also partake in such initiatives in a manner that isfeasible and appropriate for the ED setting. [West J Emerg Med. 2017;18(5)785-793.]

Objective: To describe the quality of osteoarthritis care provided to community‐dwelling elderly patients and to characterize arthritis‐related function in these patients.Methods: Two medical groups in the western United States participated in a practice‐redesign intervention targeted at falls and mobility disorders, incontinence, and cognitive impairment, but not osteoarthritis. From 339 individuals reporting a diagnosis of arthritis, we collected information on demographics, functional status, and quality of care via patient interviews and mailed questionnaires. Eight quality indicators measured osteoarthritis care: 4 indicators measuring the provision of effective osteoarthritis care (osteoarthritis treatment indicators) and 4 measuring the provision of safe osteoarthritis care (medication safety indicators).Results: The mean ± SD Short Form 12 physical component summary score was 35 ± 11 points, indicating a physically frail population. The overall indicator pass rate was 57.0% (95% confidence interval [95% CI] 53.9–60.2). Pass rates were higher for indicators of osteoarthritis treatment (63.5%, 95% CI 59.8–67.2) than for indicators of medication safety (43.8%, 95% CI 38.2–49.4). Patients with hip or knee pain had mean ± SD Western Ontario and McMaster Universities Osteoarthritis Index pain, stiffness, and function scores of 6.0 ± 4.0, 3.1 ± 1.7, and 25 ± 12 points, respectively.Conclusion: Quality of osteoarthritis care for older adults is suboptimal, particularly with regard to medication safety. Given the high prevalence of osteoarthritis in older age groups, the population impact of any improvement in quality would be substantial. Quality improvement efforts for osteoarthritis should target appropriate use of and counseling regarding medications, as well as underuse of efficacious therapy for osteoarthritis.

Recurrent strokes are preventable through awareness and control of risk factors such as hypertension, and through lifestyle changes such as healthier diets, greater physical activity, and smoking cessation. However, vascular risk factor control is frequently poor among stroke survivors, particularly among socio-economically disadvantaged blacks, Latinos and other people of color. The Chronic Care Model (CCM) is an effective framework for multi-component interventions aimed at improving care processes and outcomes for individuals with chronic disease. In addition, community health workers (CHWs) have played an integral role in reducing health disparities; however, their effectiveness in reducing vascular risk among stroke survivors remains unknown. Our objectives are to develop, test, and assess the economic value of a CCM-based intervention using an Advanced Practice Clinician (APC)-CHW team to improve risk factor control after stroke in an under-resourced, racially/ethnically diverse population. In this single-blind randomized controlled trial, 516 adults (≥40 years) with an ischemic stroke, transient ischemic attack or intracerebral hemorrhage within the prior 90 days are being enrolled at five sites within the Los Angeles County safety-net setting and randomized 1:1 to intervention vs usual care. Participants are excluded if they do not speak English, Spanish, Cantonese, Mandarin, or Korean or if they are unable to consent. The intervention includes a minimum of three clinic visits in the healthcare setting, three home visits, and Chronic Disease Self-Management Program group workshops in community venues. The primary outcome is blood pressure (BP) control (systolic BP <130 mmHg) at 1 year. Secondary outcomes include: (1) mean change in systolic BP; (2) control of other vascular risk factors including lipids and hemoglobin A1c, (3) inflammation (C reactive protein [CRP]), (4) medication adherence, (5) lifestyle factors (smoking, diet, and physical activity), (6) estimated relative reduction in risk for recurrent stroke or myocardial infarction (MI), and (7) cost-effectiveness of the intervention versus usual care. If this multi-component interdisciplinary intervention is shown to be effective in improving risk factor control after stroke, it may serve as a model that can be used internationally to reduce race/ethnic and socioeconomic disparities in stroke in resource-constrained settings. ClinicalTrials.gov Identifier NCT01763203 .

Identifying fall-related injuries and costs using healthcare claims data is cost-effective and easier to implement than using medical records or patient self-report to track falls. We developed a comprehensive four-step algorithm for identifying episodes of care for fall-related injuries and associated costs, using fee-for-service Medicare and Medicare Advantage health plan claims data for 2,011 patients from 5 medical groups between 2005 and 2009. First, as a preparatory step, we identified care received in acute inpatient and skilled nursing facility settings, in addition to emergency department visits. Second, based on diagnosis and procedure codes, we identified all fall-related claim records. Third, with these records, we identified six types of encounters for fall-related injuries, with different levels of injury and care. In the final step, we used these encounters to identify episodes of care for fall-related injuries. To illustrate the algorithm, we present a representative example of a fall episode and examine descriptive statistics of injuries and costs for such episodes. Altogether, we found that the results support the use of our algorithm for identifying episodes of care for fall-related injuries. When we decomposed an episode, we found that the details present a realistic and coherent story of fall-related injuries and healthcare services. Variation of episode characteristics across medical groups supported the use of a complex algorithm approach, and descriptive statistics on the proportion, duration, and cost of episodes by healthcare services and injuries verified that our results are consistent with other studies. This algorithm can be used to identify and analyze various types of fall-related outcomes including episodes of care, injuries, and associated costs. Furthermore, the algorithm can be applied and adopted in other fall-related studies with relative ease.