Leo M. Cooney

A Multicomponent Intervention to Prevent Delirium in Hospitalized Older Patients

BACKGROUND Since in hospitalized older patients delirium is associated with poor outcomes, we evaluated the effectiveness of a multicomponent strategy for the prevention of delirium. METHODS We studied 852 patients 70 years of age or older who had been admitted to the general-medicine service at a teaching hospital. Patients from one intervention unit and two usual-care units were enrolled by means of a prospective matching strategy. The intervention consisted of standardized protocols for the management of six risk factors for delirium: cognitive impairment, sleep deprivation, immobility, visual impairment, hearing impairment, and dehydration. Delirium, the primary outcome, was assessed daily until discharge. RESULTS Delirium developed in 9.9 percent of the intervention group as compared with 15.0 percent of the usual-care group, (matched odds ratio, 0.60; 95 percent confidence interval, 0.39 to 0.92). The total number of days with delirium (105 vs. 161, P=0.02) and the total number of episodes (62 vs. 90, P=0.03) were significantly lower in the intervention group. However, the severity of delirium and recurrence rates were not significantly different. The overall rate of adherence to the intervention was 87 percent, and the total number of targeted risk factors per patient was significantly reduced. Intervention was associated with significant improvement in the degree of cognitive impairment among patients with cognitive impairment at admission and a reduction in the rate of use of sleep medications among all patients. Among the other risk factors per patient there were trends toward improvement in immobility, visual impairment, and hearing impairment. CONCLUSIONS The risk-factor intervention strategy that we studied resulted in significant reductions in the number and duration of episodes of delirium in hospitalized older patients. The intervention had no significant effect on the severity of delirium or on recurrence rates; this finding suggests that primary prevention of delirium is probably the most effective treatment strategy.

Driving Cessation and Increased Depressive Symptoms: Prospective Evidence from the New Haven EPESE

OBJECTIVES: The purpose of this study was to determine the association between driving cessation and depressive symptoms among older drivers. Previous efforts in this area have focused on the factors associated with cessation, not the consequences of having stopped.

Decline in physical function following hip fracture.

The main objective of the study was to determine the change in physical function following hip fractures in a community‐living elderly population. A secondary objective was the determination of baseline factors predictive of altered function following hip fracture.

MODELS OF GERIATRICS PRACTICE; The Hospital Elder Life Program: A Model of Care to Prevent Cognitive and Functional Decline in Older Hospitalized Patients

OBJECTIVES: To describe the Hospital Elder Life Program, a new model of care designed to prevent functional and cognitive decline of older persons during hospitalization.OBJECTIVES To describe the Hospital Elder Life Program, a new model of care designed to prevent functional and cognitive decline of older persons during hospitalization. PROGRAM STRUCTURE AND PROCESS: All patients aged > or =70 years on specified units are screened on admission for six risk factors (cognitive impairment, sleep deprivation, immobility, dehydration, vision or hearing impairment). Targeted interventions for these risk factors are implemented by an interdisciplinary team-including a geriatric nurse specialist, Elder Life Specialists, trained volunteers, and geriatricians--who work closely with primary nurses. Other experts provide consultation at twice-weekly interdisciplinary rounds. INTERVENTION Adherence is carefully tracked. Quality assurance procedures and performance reviews are an integral part of the program. PROGRAM OUTCOMES To date, 1,507 patients have been enrolled during 1,716 hospital admissions. The overall intervention adherence rate was 89% for at least partial adherence with all interventions during 37,131 patient-days. Our results indicate that only 8% of admissions involved patients who declined by 2 or more points on MMSE and only 14% involved patients who declined by 2 or more points on ADL score. Comparative results for the control group from the clinical trial were 26% and 33%, and from previous studies 14 to 56% and 34 to 50% for cognitive and functional decline, respectively. Effectiveness of the program for delirium prevention and of the programs nonpharmacologic sleep protocol have been demonstrated previously. CONCLUSIONS These results suggest that the Hospital Elder Life Program successfully prevents cognitive and functional decline in at-risk older patients. The program is unique in its hospital-wide focus; in providing skilled staff and volunteers to implement interventions; and in targeting practical interventions toward evidence-based risk factors. Future studies are needed to evaluate cost-effectiveness and longterm outcomes of the program as well as its effectiveness in non-hospital settings.

A Simple Procedure for General Screening for Functional Disability in Elderly Patients

We propose a short, simple approach that can be used by general internists to routinely screen the functional status of elderly patients in office practice. The approach relies on checking a limited number of targets that are commonly dysfunctional but often unappreciated when conventional histories and physical examinations are done for elderly patients. The new focus is on carefully selected tests of vision, hearing, arm and leg function, urinary incontinence, mental status, instrumental and basic activities of daily living, environmental hazards, and social support systems. Brief questions and easily observed tasks are used to obtain the information needed for a suitable, effective screening while minimizing the time for administration. The approach can be incorporated into routine practice if certain relatively unproductive procedures are eliminated from the routine clinical examination, and particularly if internists are suitably compensated for the additional time.

A predictive index for functional decline in hospitalized elderly medical patients

Objective: To prospectively develop and validate a predictive index to identify on admission elderly hospitalized medical patients at risk for functional decline.Design: Two prospective cohort studies, in tandem. The predictive model developed in the initial cohort was subsequently validated in a separate cohort.Setting: General medical wards of a university teaching hospital.Patients: For the development cohort, 188 hospitalized general medical patients aged ≥70 years. For the validation cohort, 142 comparable patients.Measurement and main results: The subjects and their nurses were interviewed twice weekly using standardized, validated instruments. Functional decline occurred among 51/188 (27%) patients in the development cohort. Four independent baseline risk factors (RFs) for functional decline were identified: decubitus ulcer (adjusted relative risk [RR] 2.7; 95% confidence interval [CI] 1.4, 5.2); cognitive impairment (RR 1.7; CI 0.9, 3.1); functional impairment (RR 1.8; CI 1.0, 3.3); and low social activity level (RR2.4; CI 1.2, 5.1). A risk-stratification system was developed by adding the numbers of RFs. Rates of functional decline for the low- (0 RF), intermediate- (1–2 RFs), and high- (3–4 RFs) risk groups were 8%, 28%, and 63%, respectively (p<0.0001).The corresponding rates in the validation cohort, of whom 34/142 (24%) developed functional decline, were 6%, 29%, and 83% (p<0.0001). The rates of death or nursing home placement, clinical outcomes associated with functional decline in the hospital, were 6%, 19%, and 41% (p<0.002) in the development cohort and 10%, 32%, and 67% (p<0.001) in the validation cohort, respectively, for the three risk groups.Conclusions: Functional decline among hospitalized elderly patients is common, and a simple predictive model based on four risk factors can be used on admission to identify elderly persons at greatest risk.

Predictors of Automobile Crashes and Moving Violations among Elderly Drivers

Although the absolute number of automobile crashes involving older drivers is low, these drivers have a high incidence of crashes per mile driven [1, 2]. Moreover, crashes among older persons are more likely to cause injury, hospitalization, and death [3-6]. For example, national estimates described by Cerelli [7] for 1986 showed that 16- to 19-year-old drivers had 28.6 crashes per million miles and 5.6 fatalities per 100 million miles, 45- to 49-year-old drivers had 3.7 crashes and 0.9 fatalities, and drivers aged 85 years and older had 38.8 crashes and 30.7 fatalities. Consequently, factors that contribute to driving ability and safety among older drivers have been sought, with visual and cognitive ability and medical conditions receiving the most attention. Previous studies have evaluated the effect of specific impairments or diseases on driving ability or crashes. Several studies found associations between visual acuity, visual field loss, or visual attention and motor vehicle crashes [8-14]. Other studies found increased crash rates in persons with dementia [15, 16]. Medical conditions that have been linked to driving ability or crashes include cardiac disease, diabetes, seizure disorders, Parkinson disease, and stroke [17-24]. Despite these studies, few investigators have analyzed how multiple domains of risk factors in a general population of older drivers might affect the incidence of motor vehicle crashes. Consensus has not yet been reached on which driver-related factors increase the crash rate or on how to identify drivers at greatest risk for crashes. We determined the occurrence of adverse driving events, such as automobile crashes, moving violations, and being stopped by police, among older drivers in a representative community-living cohort and identified factors associated with these occurrences. Identifying persons at high risk for such events is the first step in determining if and why driving ability is impaired. This information will ultimately help family members, clinicians, and public safety officials develop recommendations about driving restrictions or cessation and develop targeted interventions to decrease the risk for adverse events. Methods Participants We selected study participants from the Project Safety cohort, a probability sample of noninstitutionalized persons aged 72 years and older living in New Haven, Connecticut, in 1989. Project Safety studied the risk factors for falls and fall-related injuries in an older community-living population. The sampling technique for this cohort was similar to that used to establish the New Haven Established Populations for Epidemiologic Studies of the Elderly (EPESE) cohort. Both sampling techniques have been described in detail elsewhere [25-27]. A census was taken of all 2483 age-restricted elderly housing units not occupied by persons enrolled in the EPESE cohort. We identified nonage-restricted community houses and apartment buildings through utilities listings. Every 62d nonage-restricted unit was sampled, and the next 12 units were identified as a cluster included in the study. Eligibility criteria included the ability to speak English, Spanish, or Italian; to follow simple commands; and to walk across a room without human assistance. Of 1392 eligible persons, 1103 (79%) agreed to participate and were enrolled in the cohort. All cohort members had a baseline interview and a 1-year follow-up interview. There were 1103 respondents to the baseline interview and 915 respondents to the first-year follow-up interview. Of the remaining baseline respondents, 111 (10%) refused to participate further, 59 (5%) died, and 18 (2%) were proxy respondents. Study participants included all respondents who reported driving (n = 283) in the period between the baseline and follow-up interviews. Data Collection All participants had a baseline interview and physical performance assessment in their homes by a trained research nurse. Independent variables in this study included items potentially related to driving from the following five domains: demographic, health, psychosocial, activity, and physical performance. Demographic features included age, sex, number of years of education, race, marital status, and type of housing. Data in the health domain were obtained on self-rated health, alcohol use, several chronic conditions, dizziness, loss of consciousness, and urinary incontinence. We used a Rosenbaum card [28, 29] to measure corrected static near visual acuity and used the Whisper test [30] to assess hearing. Medication use was determined by asking patients about prescription and over-the-counter medications and by examining pill bottles. Assessed medications potentially related to driving ability included opioid analgesics, tricyclic and tetracyclic antidepressants, antipsychotic agents, benzodiazepines, insulin, and oral hypoglycemic agents. The psychosocial domain included cognitive impairment assessed by the Folstein Mini-Mental State Examination [31], depressive symptoms assessed by the Center for Epidemiologic Studies-Depression scale (CES-D) [32], and availability of help with chores. The activity domain consisted of self-reported independence in basic and instrumental activities of daily living derived from Katz and colleagues [33], Branch and colleagues [34], and the Older Americans Resource Services Instrument [35]. We also ascertained the number of flights of stairs and blocks walked on an average day. We assessed higher-level physical activity using a modification of the Yale Physical Activity Survey [36], in which participation in several activities was converted into a scale based on the estimated kilocalorie expenditure for each activity and the frequency of participation. A battery of physical performance items included balance (side-to-side stand, tandem stand, single-leg stand, and withstanding a sternal nudge) and was scored on a 4-point scale, with 1 point given for each item done without instability [37, 38]. We determined strength and range of motion using manual muscle testing of shoulder abduction, grasp, hip flexion, knee flexion, and knee extension and categorized them as good (full resistance and full range of motion) versus fair or poor (less than full resistance or range of motion) [39]. We assessed ability to stand on toes and heels and the number of foot abnormalities presenttoenail irregularities, calluses, bunions, and toe deformities such as hammer toes. Timed performance measures included hand signature, three chair stands, usual-pace walk (10 feet each up and back, including a turn, at usual pace), rapid-pace walk (10 feet each up and back as fast as the participant felt safe and comfortable), and foot tap (10 taps alternating between two circles on a mat). Outcomes At the follow-up interview, participants were asked if and how often they had driven in the past year (daily, every other day, once or twice a week, or less often), and if they had been stopped by the police or been cited for a moving violation. They were also asked if they had been involved in an accident while driving and, if so, if they had been injured or hospitalized as a result. The term accident was chosen because it is familiar to older drivers and because alternatives such as crash may connote a more severe event so that persons might not report minor incidents. Statistical Analysis We initially compared potential predictors of adverse events from the five domains of independent variables in bivariate analysis using chi-square tests for categorical variables (the Pearson chi-square for dichotomous variables and the Mantel-Haenszel chi-square for ordinal variables) [40]. For infrequently occurring factors with expected cell counts of 5 or less, we used the Fisher exact test instead of the chi-square test. We also grouped continuous variables by quartiles or at the median unless accepted cut-off scores were available (for example, 16 for the Center for Epidemiologic Studies-Depression scale) and analyzed them using chi-square tests. If no gradient was apparent for quartiles, the quartiles were collapsed into two levels. We entered variables significantly associated (P < 0.05) with the occurrence of adverse events in bivariate analysis into relative-risk binomial regression models using Generalized Linear Interactive Modeling [41] and adjusted for driving frequency to account for exposure and type of housing (the original sampling variable). Results The mean age of the 283 participants was 77.8 years (range, 72 to 92 years); 57% of participants were male. Forty-eight percent of participants lived in community dwellings, 45% lived in private age-restricted housing complexes, and 6% lived in public age- and income-restricted housing complexes. Fifty-five percent of participants reported driving daily, 24% every other day, and 21% 2 times a week or less. Thirty-eight of the 283 drivers (13%) reported an adverse event in the first year of follow-up. Thirty-one of these persons reported a crash, 4 of whom were also cited for a moving violation; 4 participants were only cited for moving violations, and 3 participants were only stopped by the police. Of the 31 persons reporting a crash, 6 sustained an injury, and 1 was hospitalized. The factors associated with adverse events in bivariate analysis are shown in Table 1. The only factor in the health and demographic domains that was significantly associated with adverse events was the number of chronic conditions, although this was based on the five participants with four conditions. The only types of medication marginally associated with adverse events were antidepressant agents, although only five persons were receiving them, and the association was not statistically significant. The occurrence of adverse events did not substantially differ between persons with better than or those with worse than 20/40 near static visual acuity; most states require 20/40 acuity for an unrestricted license [13]. Alcohol con

Development of a Test Battery to Identify Older Drivers at Risk for Self‐Reported Adverse Driving Events

OBJECTIVES: The purposes of this study were (1) to develop a battery of tests that assessed a wide range of functional abilities relevant to driving yet could be performed in a clinicians office and (2) to determine which of these tests were most closely associated with self‐reported adverse driving events.

Predictors of mortality and institutionalization after hip fracture: the New Haven EPESE cohort. Established Populations for Epidemiologic Studies of the Elderly.

OBJECTIVES Hip fractures can have devastating effects on the lives of older individuals. We determined the frequency of occurrence of hip fracture and the baseline factors predicting death and institutionalization at 6 months after hip fracture. METHODS A representative cohort of 2812 individuals aged 65 years and older was followed prospectively for 6 years. Hip fractures were identified, and the occurrence of death and institutionalization within 6 months of the fracture was determined. Prefracture information on physical and mental function, social support, and demographic features and in-hospital data on comorbid diagnoses, fracture site, and complications were analyzed to determine predictors of death and institutionalization after hip fracture. RESULTS Of 120 individuals suffering a hip fracture, 22 (18%) died within 6 months and 35 (29%) were institutionalized at 6 months. The predictors of death in multiple logistic regression included fracture site, a high number of comorbid conditions, a high number of complications, and poor baseline mental status. The primary predictor of institutionalization was poor baseline mental status. CONCLUSIONS The frequency of death, institutionalization, and loss of function after hip fracture should prompt a reevaluation of the current approach to this problem.

Resource utilization groups: A patient classification system for long-term care

The ability to understand, control, manage, regulate, and reimburse nursing home care has been hampered by the inavailability of a classification system of long-term care patients. A study of 1,469 patients in Connecticut nursing homes has resulted in such a classification system that clusters patients with similar relative needs for resources, in particular, for nursing time. The nine groups formed can be used to develop a case-mix profile of the relative care needs of these patients, and their development demonstrates that only a few measures of the functional status of patients, rather than diagnosis or psychosocial/behavioral problems, are sufficient to form such a system.