Predicting the risk of hospital admission in older persons--validation of a brief self-administered questionnaire in three European countries

The role of geriatric syndromes in predicting unplanned hospitalizations: a population-based study using Minimum Data Set for Home Care

BACKGROUND

The predictive accuracies of screening instruments for identifying home-dwelling old people at risk of hospitalization have ranged from poor to moderate, particularly among the oldest persons. This study aimed to identify variables that could improve the accuracy of a Minimum Data Set for Home Care (MDS-HC) based algorithm, the Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) Scale, in classifying home care clients' risk for unplanned hospitalization.

METHODS

In this register-based retrospective study, factors associated with hospitalization among home care clients aged ≥ 80 years in the City of Tampere, Finland, were analyzed by linking MDS-HC assessments with hospital discharge records. MDS-HC determinants associated with hospitalization within 180 days after the assessment were analyzed for clients at low (DIVERT 1), moderate (DIVERT 2-3) and high (DIVERT 4-6) risk of hospitalization. Then, two new variables were selected to supplement the DIVERT algorithm. Finally, area under curve (AUC) values of the original and modified DIVERT scales were determined using the data of MDS-HC assessments of all home care clients in the City of Tampere to examine if addition of the variables related to the oldest age groups improved the accuracy of DIVERT.

RESULTS

Of home care clients aged ≥ 80 years, 1,291 (65.4%) were hospitalized at least once during the two-year study period. Unplanned hospitalization occurred following 15.9%, 22.8%, and 33.9% MDS-HC assessments with DIVERT group 1, 2-3 and 4-6, respectively. Infectious diseases were the most common diagnosis within each DIVERT groups. Many MDS-HC variables not included in the DIVERT algorithm were associated with hospitalization, including e.g. poor self-rated health and old fracture (other than hip fracture) (p 0.001) in DIVERT 1; impaired cognition and decision-making, urinary incontinence, unstable walking and fear of falling (p < 0.001) in DIVERT 2-3; and urinary incontinence, poor self-rated health (p < 0.001), and decreased social interaction (p 0.001) in DIVERT 4-6. Adding impaired cognition and urinary incontinence to the DIVERT algorithm improved sensitivity but not accuracy (AUC 0.64 (95% CI 0.62-0.65) vs. 0.62 (0.60-0.64) of the original DIVERT). More admissions occurred among the clients with higher scores in the modified than in the original DIVERT scale.

CONCLUSIONS

Certain geriatric syndromes and diagnosis groups were associated with unplanned hospitalization among home care clients at low or moderate risk level of hospitalization. However, the predictive accuracy of the DIVERT could not be improved. In a complex clinical context of home care clients, more important than existence of a set of risk factors related to an algorithm may be the various individual combinations of risk factors.

A hybrid machine learning framework to improve prediction of all-cause rehospitalization among elderly patients in Hong Kong

BACKGROUND

Accurately estimating elderly patients' rehospitalisation risk benefits clinical decisions and service planning. However, research in rehospitalisation and repeated hospitalisation yielded only models with modest performance, and the model performance deteriorates rapidly as the prediction timeframe expands beyond 28 days and for older participants.

METHODS

A temporal zero-inflated Poisson (tZIP) regression model was developed and validated retrospectively and prospectively. The data of the electronic health records (EHRs) contain cohorts (aged 60+) in a major public hospital in Hong Kong. Two temporal offset functions accounted for the associations between exposure time and parameters corresponding to the zero-inflated logistic component and the Poisson distribution's expected count. tZIP was externally validated with a retrospective cohort's rehospitalisation events up to 12 months after the discharge date. Subsequently, tZIP was validated prospectively after piloting its implementation at the study hospital. Patients discharged within the pilot period were tagged, and the proposed model's prediction of their rehospitalisation was verified monthly. Using a hybrid machine learning (ML) approach, the tZIP-based risk estimator's marginal effect on 28-day rehospitalisation was further validated, competing with other factors representing different post-acute and clinical statuses.

RESULTS

The tZIP prediction of rehospitalisation from 28 days to 365 days was achieved at above 80% discrimination accuracy retrospectively and prospectively in two out-of-sample cohorts. With a large margin, it outperformed the Cox proportional and linear models built with the same predictors. The hybrid ML revealed that the risk estimator's contribution to 28-day rehospitalisation outweighed other features relevant to service utilisation and clinical status.

CONCLUSIONS

A novel rehospitalisation risk model was introduced, and its risk estimators, whose importance outweighed all other factors of diverse post-acute care and clinical conditions, were derived. The proposed approach relies on four easily accessible variables easily extracted from EHR. Thus, clinicians could visualise patients' rehospitalisation risk from 28 days to 365 days after discharge and screen high-risk older patients for follow-up care at the proper time.

Classifying home care clients' risk of unplanned hospitalization with the resident assessment instrument

Aim

The aim was to identify tools for classifying the risk of unplanned hospitalization among home care clients utilizing the Resident Assessment Instrument-Home Care (RAI-HC).

Findings

The Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) Scale predicts unplanned hospitalizations in home care clients. In the oldest age groups, however, it works poorly.

Message

DIVERT Scale can be used for identifying high-risk home care clients needing urgent care planning to prevent unplanned hospital admissions and their potential adverse consequences. Clients scoring high in the scale and experiencing the outcome earlier than others, should be the primary group for more detailed assessment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41999-022-00665-x.

Purpose

To identify predictive case finding tools for classifying the risk of unplanned hospitalization among home care clients utilizing the Resident Assessment Instrument-Home Care (RAI-HC), with special interest in the Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) Scale.

Methods

A register-based, retrospective study based on the RAI-HC assessments of 3,091 home care clients (mean age 80.9 years) in the City of Tampere, Finland, linked with hospital discharge records. The outcome was an unplanned hospitalization within 180 days after RAI-HC assessment. The Area Under the Curve (AUC) and the sensitivity and specificity were determined for the RAI-HC scales: DIVERT, Activities of Daily Living Hierarchy (ADLh), Cognitive Performance Scale (CPS), Changes in Health, End-Stage Diseases, Signs, and Symptoms Scale (CHESS), and Method for Assigning Priority Levels (MAPLe).

Results

Altogether 3091 home care clients had a total of 7744 RAI-HC assessments, of which 1658 (21.4%) were followed by an unplanned hospitalization. The DIVERT Scale had an AUC of 0.62 (95% confidence interval 0.61–0.64) when all assessments were taken into account, but its value was poorer in the older age groups (< 70 years: 0.71 (0.65–0.77), 70–79 years: 0.66 (0.62–0.69), 80–89 years: 0.60 (0.58–0.62), ≥ 90 years: 0.59 (0.56–0.63)). AUCs for the other scales were poorer than those of DIVERT, with CHESS nearest to DIVERT. Time to hospitalization after assessment was shorter in higher DIVERT classes.

Conclusion

The DIVERT Scale offers an approach to predicting unplanned hospitalization, especially among younger home care clients. Clients scoring high in the DIVERT algorithm were at the greatest risk of unplanned hospitalization and more likely to experience the outcome earlier than others.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41999-022-00665-x.

Psychometric Properties, Feasibility, and Acceptability of the Self-Reported interRAI Check-Up Assessment

OBJECTIVES

To assess the feasibility, acceptability, and psychometric properties of the self-report version of the interRAI Check-Up (CUSR).

DESIGN

Cross-sectional study of participant ratings of item content and difficulty completing the CUSR. Participants were also randomly assigned to complete the assessment by themselves or with help from a lay interviewer.

SETTINGS AND PARTICIPANTS

A total of 184 older adults from diverse backgrounds, served by 6 Canadian organizations in Ontario and Nova Scotia were recruited. Settings ranged from retirement communities for healthy older adults to assisted living facilities.

MEASURES/METHODS

Time to complete the interRAI CUSR was tracked automatically. Participants self-reported on what items they wanted to have modified, added, or deleted. The also rated whether items were embarrassing or difficult to complete. Psychometric properties were examined between the 2 approaches to completion and were benchmarked against existing reports on psychometric properties of clinician-led home care assessments.

RESULTS

The interRAI CUSR takes about 28 minutes to complete with both self-administered and lay interviewer approaches. The convergent validity and reliability of CUSR is comparable to those of clinician-based assessments like the Resident Assessment Instrument-Home Care. Most participants had no difficulty completing the assessment, and none rated the task as very difficult. Poor self-rated health and difficulty with phone use were predictive of any difficult in completing the assessment in a multivariate logistic regression. Most participants reported that CUSR adequately described their health needs, but arthritis, hypertension, and mental health issues were identified as items to be added by participants.

CONCLUSIONS AND IMPLICATIONS

The CUSR is an appropriate, feasible assessment system with good psychometric properties for use with general populations, including primary care, community services, and patient-reported outcome measurement studies. Interoperability with other interRAI assessments makes it an ideal system to use to obtain a longitudinal view of the person's needs over time.

Factors Associated With Hospitalization Before the Start of Long-Term Care Among Elderly Disabled People

The growing number of elderly people with functional limitations, cognitive impairment, and disability is an organizational challenge for the health care sector. This study investigated the factors associated with hospitalization in the period between evaluation and the start of a long-term care (LTC) program for patients on the waiting list. A population-based historical cohort study was performed using data extracted from different administrative databases. The cohort included disabled individuals 65 years and older who were evaluated for entrance into an LTC program between January 1, 2012, and December 31, 2013, in Tuscany, Italy. The sample consisted of 11,429 subjects. The characteristics positively associated with hospital admission were residence zone {urban incidence rate ratio (IRR) = 0.83 (95% confidence interval [CI] 0.74-0.94)}, number of prescribed drugs IRR = 1.01 (95% CI 1.00-1.02), a Charlson Comorbidity Index of 2 IRR = 1.44 (95% CI 1.26-1.64), and lower social conditions IRR = 0.99 (95% CI 0.98-1.00). The rate of hospitalization for patients with heart failure, chronic obstructive pulmonary disease, and dementia was higher than for patients without these diseases. Our results indicate that it may be possible to predict factors that can lead to hospitalization before the start of an LTC program.

Screening for vulnerable older people: Is the Probability of Repeated Admission scale an accurate tool?

AIM

To evaluate the Probability of Repeated Admission (Pra) scale performance in predicting healthcare utilization and death in a community sample of Rio de Janeiro city, Brazil.

METHODS

This was a prospective longitudinal study. The sample was composed of community-dwelling older people who participated in the research network Frailty in Brazilian Older People Study, Rio de Janeiro section. It analyzed data from the baseline and the follow up. At the baseline, 764 older adults were stratified by the Pra, and, 3 years later, data on health services utilization and survival status were collected. The Pra accuracy, obtained by the area under the curve, the sensitivity and the specificity to predict hospitalization in 3 years; visits to the emergency department; and death were determined. Cox regression estimated the survival curves, according to the risk strata.

RESULTS

The accuracy, the sensitivity and the specificity of Pra were 62% (95% CI 57-68%), 8.8% and 95.4% for hospitalization in 3 years; 59% (95% CI 53-64%), 8.3% and 94.8% for emergency room visits; 66% (95% CI 59-74%) and 68% (95% CI 63-73%), 15.0% and 96.0% for death. Survival curves showed that high-risk individuals were more likely to die compared with the low-risk individuals, adjusted to covariables (P < 0.001).

CONCLUSIONS

The Pra presented low accuracy, low sensitivity and high specificity for all outcomes observed, indicating a poor performance to screen vulnerable older adults in Brazil. Therefore, this tool should not be used alone, as a case-finding instrument. Geriatr Gerontol Int 2020; 20: 360-365.

Identifying Older Patients at High Risk for Emergency Department Visits and Hospitalization

Hospitalizations are costly, potentially hazardous for older patients, and sometimes preventable. With Medicare's implementation of hospital penalties for 30-day readmissions on certain index conditions, health care organizations have prioritized addressing those issues that lead to avoidable hospitalizations. Little is known about the utility and feasibility of using standardized tools to identify adults at risk for hospitalizations in primary care. In this study, the goal was to determine, from a sample of 60 adults aged 65 and older, whether the Probability of Repeat Admission (PRA), the Vulnerable Elders Survey (VES-13), or a provider estimate of likelihood of hospitalization could identify patients at high risk for emergency department (ED) visits or hospitalization at 6 and 12 months, while being feasible to administer in a primary care setting. PRA, VES-13, and provider estimate were administered in an outpatient practice. Number of ED visits and hospitalizations at 6 and 12 months were assessed through follow-up phone calls and chart review. PRA and provider estimate were not significant predictors of hospitalizations at 6 months (PRA odds ratio [OR] 1.95; P = 0.39; physician estimate OR 4.33, P = 0.08), but were at 12 months (PRA OR 6.00; P < 0.001; physician estimate OR 2.3; P < 0.05). Additionally, a hospitalization during the prior year was not a significant predictor of hospitalization at 6 months (OR 2.97; P = 0.15) but was at 12 months (OR 3.89, P < 0.05). No tool was a significant predictor of ED visits at either time. PRA and the physician estimate were easy to administer and feasible to implement in a primary care setting.

Screening tools to identify patients with complex health needs at risk of high use of health care services: A scoping review

Background

Many people with chronic conditions have complex health needs often due to multiple chronic conditions, psychiatric comorbidities, psychosocial issues, or a combination of these factors. They are at high risk of frequent use of healthcare services. To offer these patients interventions adapted to their needs, it is crucial to be able to identify them early.

Objective

The aim of this study was to find all existing screening tools that identify patients with complex health needs at risk of frequent use of healthcare services, and to highlight their principal characteristics. Our purpose was to find a short, valid screening tool to identify adult patients of all ages.

Methods

A scoping review was performed on articles published between 1985 and July 2016, retrieved through a comprehensive search of the Scopus and CINAHL databases, following the methodological framework developed by Arksey and O’Malley (2005), and completed by Levac et al. (2010).

Results

Of the 3,818 articles identified, 30 were included, presenting 14 different screening tools. Seven tools were self-reported. Five targeted adult patients, and nine geriatric patients. Two tools were designed for specific populations. Four can be completed in 15 minutes or less. Most screening tools target elderly persons. The INTERMED self-assessment (IM-SA) targets adults of all ages and can be completed in less than 15 minutes.

Conclusion

Future research could evaluate its usefulness as a screening tool for identifying patients with complex needs at risk of becoming high users of healthcare services.

Health Promotion and Preventive Care Intervention for Older Community-Dwelling People: Long-Term Effects of a Randomised Controlled Trial (RCT) within the LUCAS Cohort

OBJECTIVES

An RCT of a health promotion and preventive care intervention was done in 2001-2002. Here, long-term analyses based on 12 years of follow-up of survival and of change in functional competence between intervention and control group are presented. Positive 1-year results (significantly higher use of preventive services and better health behaviour) were presented earlier.

DESIGN

Parallel group randomised controlled trial (RCT) with 878 participants in the intervention and 1,702 participants in the control group.

SETTING

The study took place in Hamburg, Germany and made use of health care structures and professionals of a geriatrics centre.

PARTICIPANTS

Study participants were initially community-dwelling, aged 60 years and older and without B-ADL-restrictions, cognitive impairment, or need of nursing care, with sufficient command of the German language.

INTERVENTIONS

Health promotion and preventive care interventions relied on an extensive health questionnaire and the subsequent offer to participate in multi-topic personal reinforcement performed in small group sessions or at preventive home visits.

MEASUREMENTS

Primary outcome: Survival time; in some analyses, adjustments were made for gender, age and self-perceived health. Secondary outcome: Functional competence (LUCAS Functional Ability Index) based on responses to self-administered questionnaires at 1-year follow-up and 12 years after 1-year follow-up (2013/2014).

RESULTS

Mean time under observation was 10.3 years. 38.3% (987/2,580) of the participants died; intervention group (IG): 35.7% (313/878), control group (CG): 39.6% (674/1,702); HR=0.89; p=0.09. Functional competence at 1-year follow-up: IG: ROBUST 67.4% (391/580), FRAIL 11.9% (69/580) vs. CG: ROBUST 62.9% (861/1,368), FRAIL 14.8% (203/1,368); p=0.12. 12-years after 1-year follow-up: IG: ROBUST 50.0% (160/320), FRAIL 30.9% (99/320) vs. CG: ROBUST 48.9% (307/628), FRAIL 34.1% (214/628); p=0.56.

CONCLUSIONS

Insignificant but consistent effects on survival and the dynamics of functional competence suggest effectivity of the complex intervention. We plan to take a closer look at the effect of each reinforcement separately.

External validation of the Probability of repeated admission (Pra) risk prediction tool in older community-dwelling people attending general practice: a prospective cohort study

OBJECTIVES

Emergency admission is associated with the potential for adverse events in older people and risk prediction models are available to identify those at highest risk of admission. The aim of this study was to externally validate and compare the performance of the Probability of repeated admission (Pra) risk model and a modified version (incorporating a multimorbidity measure) in predicting emergency admission in older community-dwelling people.

SETTING

15 general practices (GPs) in the Republic of Ireland.

PARTICIPANTS

n=862, ≥70 years, community-dwelling people prospectively followed up for 2 years (2010-2012).

EXPOSURE

Pra risk model (original and modified) calculated for baseline year where ≥0.5 denoted high risk (patient questionnaire, GP medical record review) of future emergency admission.

PRIMARY OUTCOME

Emergency admission over 1 year (GP medical record review).

STATISTICAL ANALYSIS

descriptive statistics, model discrimination (c-statistic) and calibration (Hosmer-Lemeshow statistic).

RESULTS

Of 862 patients, a total of 154 (18%) had ≥1 emergency admission(s) in the follow-up year. 63 patients (7%) were classified as high risk by the original Pra and of these 26 (41%) were admitted. The modified Pra classified 391 (45%) patients as high risk and 103 (26%) were subsequently admitted. Both models demonstrated only poor discrimination (original Pra: c-statistic 0.65 (95% CI 0.61 to 0.70); modified Pra: c-statistic 0.67 (95% CI 0.62 to 0.72)). When categorised according to risk-category model, specificity was highest for the original Pra at cut-point of ≥0.5 denoting high risk (95%), and for the modified Pra at cut-point of ≥0.7 (95%). Both models overestimated the number of admissions across all risk strata.

CONCLUSIONS

While the original Pra model demonstrated poor discrimination, model specificity was high and a small number of patients identified as high risk. Future validation studies should examine higher cut-points denoting high risk for the modified Pra, which has practical advantages in terms of application in GP. The original Pra tool may have a role in identifying higher-risk community-dwelling older people for inclusion in future trials aiming to reduce emergency admissions.

Developing a postal screening tool for frailty in primary care: a secondary data analysis

The purpose of this secondary data analysis (SDA) was to review a subset of quantitative and qualitative paired data sets from a returned postal screening tool (PST) completed by patients and compare them to the clinical letters composed by elderly care community nurses (ECCN) following patient assessment to ascertain the tool's reliability and validity. The aim was to understand to what extent the problems identified by patients in PSTs aligned with actual or potential problems identified by the ECCNs. The researcher examined this connection to establish whether the PST was a valid, reliable approach to proactive care. The findings of this SDA indicated that patients did understand the PST. Many appropriate referrals were made as a result of the ECCN visit that would not have occurred if the PST had not been sent. This article focuses specifically upon the physiotherapy section as this was the area where the most red flags were identified.

Unexpected readmission after lung cancer surgery: A benign event?

OBJECTIVE

The study objective was to study the incidence, predictors, and implications of unanticipated early postoperative readmission after lung resection for non-small cell lung cancer.

METHODS

Patients undergoing surgery for clinical stage I to III non-small cell lung cancer were abstracted from the National Cancer Database. Regression models were fitted to identify predictors of 30-day readmission and to study the association of unplanned readmission with 30-day and long-term survival.

RESULTS

Between 1998 and 2010, 129,893 patients underwent resection for stage I to III non-small cell lung cancer. Of these, 5624 (4.3%) were unexpectedly readmitted within 30 days. In a multivariate regression model, increasing age, male gender, preoperative radiation, and pneumonectomy (odds ratio, 1.77; 95% confidence interval, 1.56-2.00) were associated with unexpected readmissions. Longer index hospitalization and higher Charlson comorbidity score were also predictive of readmission. The 30-day mortality for readmitted patients was higher (3.9% vs 2.8%), as was the 90-day mortality (7.0% vs 3.3%, both P < .001). In a multivariate Cox proportional hazards model of long-term survival, increasing age, higher Charlson comorbidity score, and higher pathologic stage (hazard ratio, for stage III 1.81; 95% confidence interval, 1.42-2.29) were associated with greater risk of mortality. Unplanned readmission was independently associated with a higher risk of long-term mortality (hazard ratio, 1.40; 95% confidence interval, 1.34-1.47). The median survival for readmitted patients was significantly shorter (38.7 vs 58.5 months, P < .001).

CONCLUSIONS

Unplanned readmissions are not rare after resection for non-small cell lung cancer. Such events are associated with a greater risk of short- and long-term mortality. With the renewed national focus on readmissions and potential financial disincentives, greater resource allocation is needed to identify patients at risk and develop measures to avoid the associated adverse outcomes.

Which Part of a Short, Global Risk Assessment, the Risk Instrument for Screening in the Community, Predicts Adverse Healthcare Outcomes?

The Risk Instrument for Screening in the Community (RISC) is a short, global risk assessment to identify community-dwelling older adults' one-year risk of institutionalisation, hospitalisation, and death. We investigated the contribution that the three components of the RISC (concern, its severity, and the ability of the caregiver network to manage concern) make to the accuracy of the instrument, across its three domains (mental state, activities of daily living (ADL), and medical state), by comparing their accuracy to other assessment instruments in the prospective Community Assessment of Risk and Treatment Strategies study. RISC scores were available for 782 patients. Across all three domains each subtest more accurately predicted institutionalisation compared to hospitalisation or death. The caregiver network's ability to manage ADL more accurately predicted institutionalisation (AUC 0.68) compared to hospitalisation (AUC 0.57, P = 0.01) or death (AUC 0.59, P = 0.046), comparing favourably with the Barthel Index (AUC 0.67). The severity of ADL (AUC 0.63), medical state (AUC 0.62), Clinical Frailty Scale (AUC 0.67), and Charlson Comorbidity Index (AUC 0.66) scores had similar accuracy in predicting mortality. Risk of hospitalisation was difficult to predict. Thus, each component, and particularly the caregiver network, had reasonable accuracy in predicting institutionalisation. No subtest or assessment instrument accurately predicted risk of hospitalisation.

Patient-reported geriatric symptoms as risk factors for hospitalization and emergency department visits

There is an urgent need to identify predictors of adverse outcomes and increased health care utilization in the elderly. The Mayo Ambulatory Geriatric Evaluation (MAGE) is a symptom questionnaire that was completed by patients aged 65 years and older during office visits to Primary Care Internal Medicine at Mayo Clinic in Rochester, MN. It was introduced to improve screening for geriatric conditions. We conducted this study to explore the relationship between self-reported geriatric symptoms and hospitalization and emergency department (ED) visits within 1 year of completing the survey. This was a retrospective cohort study of patients who completed the MAGE from April 2008 to December 2010. The primary outcome was an ED visit or hospitalization within 1 year. Predictors included responses to individual questions in the MAGE. Data were obtained from the electronic medical record and administrative records. Logistic regression analyses were performed from significant univariate factors to determine predictors in a multivariable setting. A weighted scoring system was created based upon the odds ratios derived from a bootstrap process. The sensitivity, specificity, and AUC were calculated using this scoring system. The MAGE survey was completed by 7738 patients. The average age was 76.2 ± 7.68 years and 57% were women. Advanced age, a self-report of worse health, history of 2 or more falls, weight loss, and depressed mood were significantly associated with hospitalization or ED visits within 1 year. A score equal to or greater than 2 had a sensitivity of 0.74 and specificity of 0.45. The calculated AUC was 0.60. The MAGE questionnaire, which was completed by patients at an outpatient visit to screen for common geriatric issues, could also be used to assess risk for ED visits and hospitalization within 1 year.

[Screening the risk for functional loss: a basic strategy for organizing the elderly health care network]

From a critical analysis of experiments in the use of screening tools for functional loss in the elderly, it was observed that the main motivation to develop and implement a screening instrument is to improve health care for the frail elderly or those at risk of functional loss and repeated hospital admissions. The instruments are preferably short questionnaires with no more than 16 self-reported questions. The main intervention performed after screening was monitoring the elderly by a specialized nursing service that, when necessary, referring them to the medical service. The results of this approach included the reduction of functional loss, hospital admissions, deaths, lower health expenses and greater consumer satisfaction.

Integration and continuity of Care in health care network models for frail older adults

A detailed review was conducted of the literature on models evaluating the effectiveness of integrated and coordinated care networks for the older population. The search made use of the following bibliographic databases: Pubmed, The Cochrane Library, LILACS, Web of Science, Scopus and SciELO. Twelve articles on five different models were included for discussion. Analysis of the literature showed that the services provided were based on primary care, including services within the home. Service users relied on the integration of primary and hospital care, day centers and in-home and social services. Care plans and case management were key elements in care continuity. This approach was shown to be effective in the studies, reducing the need for hospital care, which resulted in savings for the system. There was reduced prevalence of functional loss and improved satisfaction and quality of life on the part of service users and their families. The analysis reinforced the need for change in the approach to health care for older adults and the integration and coordination of services is an efficient way of initiating this change.

Predicting risk of hospital and emergency department use for home care elderly persons through a secondary analysis of cross-national data

BACKGROUND

Older adults remain the highest utilization group with unplanned visits to emergency departments and hospital admissions. Many have considered what leads to this high utilization and the answers provided have depended upon the independent measures available in the datasets used. This project was designed to further understanding of the reasons for older adult ED visits and admissions to acute care hospitals.

METHODS

A secondary analysis of data from a cross-national sample of community residing elderly, 60 years of age or older, and most of whom received services from a local home-care program was conducted. The assessment instrument used in this study is the interRAI HC (home care), designed for use in assessing elderly home care recipients. The model specification stage of the study identified the baseline independent variables that do and do not predict the follow-up measure of hospitalization and ED use. Stepwise logistic regression was used next to identify characteristics that best identified elders who subsequently entered a hospital or visited an ED. The items generated from the final multivariate logistic equation using the interRAI home care measures comprise the interRAI Hospital-ED Risk Index.

RESULTS

Independent measures in three key domains of clinical complications, disease diagnoses and specialized treatments were related to subsequent hospitalization or ED use. Among the eighteen clinical complication measures with higher, meaningful odds ratios are pneumonia, urinary tract infection, fever, chest pain, diarrhea, unintended weight loss, a variety of skin conditions, and subject self-reported poor health. Disease diagnoses with a meaningful relationship with hospital/ED use include coronary artery disease, congestive heart failure, cancer, emphysema and renal failure. Specialized treatments with the highest odds ratios were blood transfusion, IV infusion, wound treatment, radiation and dialysis. Two measures, Alzheimer's disease and day care appear to have a protective effect for hospitalization/ED use with lower odds ratios.

CONCLUSIONS

Examination into "preventable" hospitalizations and re-hospitalizations for older adults who have the highest rates of utilization are occurring beneath an umbrella of assuring the highest quality of care and controlling costs. The interRAI Hospitalization-ED Risk Index offers an effective approach to predicting hospitalization utilization among community dwelling older adults.

Activating patients with chronic disease for self-management: comparison of self-managing patients with those managing by frequent readmissions to hospital

Understanding the factors that activate people to self-manage chronic disease is important in improving uptake levels. If the many frequent hospital users who present with acute exacerbations of chronic disease were to self-manage at home, some hospital admissions would be avoided. Patient interview and demographic, psychological, clinical and service utilisation data were compared for two groups of patients with chronic disease: those attending self-management services and those who managed by using hospital services. Data were analysed to see whether there were differences that might explain the two different approaches to managing their conditions. The two groups were similar in terms of comorbidity, age, sex, home services, home support and educational level. Self-managing patients were activated by their clinician, accepted their disease, changed their identity, confronted emotions and learnt the skills to self-manage and avoid hospital. Patients who frequently used hospital services to manage their chronic disease were often in denial about their chronic disease, hung on to their identity and expressed little emotional response. However, they reported a stronger sense of coherence and rated their health more highly than self-managing patients. This study shed light on the process of patient activation for self-management. A better understanding of the process of patient activation would encourage clinicians who come into contact with frequently readmitted chronic disease patients to be more proactive in supporting self-management.

Risk factors for depressed mood amongst a community dwelling older age population in England: cross-sectional survey data from the PRO-AGE study

BACKGROUND

The Quality and Outcomes Framework in the United Kingdom (UK) National Health Service previously highlighted case finding of depression amongst patients with diabetes or coronary heart disease. However, depression in older people remains under-recognized. Comprehensive data for analyses of the association of depression in older age with other health and functional measures, and demographic factors from community populations within England, are lacking.

METHODS

Secondary analyses of cross-sectional baseline survey data from the England arm of a randomised controlled trial of health risk appraisal for older people in Europe; PRO-AGE study. Data from 1085 community-dwelling non-disabled people aged 65 years or more from three group practices in suburban London contributed to this study. Depressed mood was ascertained from the 5-item Mental Health Inventory Screening test. Exploratory multivariable logistic regression was used to identify the strongest associations of depressed mood with a previous diagnosis of a specified physical/mental health condition, health and functional measures, and demographic factors.

RESULTS

Depressed mood occurred in 14% (155/1085) of participants. A previous diagnoses of depression (OR 3.39; P < 0.001) and poor vision as determined from a Visual Function Questionnaire (OR 2.37; P = 0.001) were amongst the strongest factors associated with depressed mood that were independent of functional impairment, other co-morbidities, and demographic factors. A subgroup analyses on those without a previous diagnosis of depression also indicated that within this group, poor vision (OR 2.51; P = 0.002) was amongst the strongest independent factors associated with depressed mood.

CONCLUSIONS

Previous case-finding strategies in primary care focussed on heart disease and diabetes but health-related conditions other than coronary heart disease and diabetes are also associated with an increased risk for depression. Complex issues of multi-morbidity occur within aging populations. 'Risk' factors that appeared stronger than those, such as, diabetes and coronary heart disease that until recently prompted for screening in the UK due to the QOF, were identified, and independent of other morbidities associated with depressed mood. From the health and functional factors investigated, amongst the strongest factors associated with depressed mood was poor vision. Consideration to case finding for depressed mood among older people with visual impairment might be justified.

Rede FIBRA-RJ: fragilidade e risco de hospitalização em idosos da cidade do Rio de Janeiro, Brasil

O objetivo do estudo foi determinar o perfil de risco e fatores associados à fragilidade em idosos da comunidade. A população-fonte constituiu-se de indivíduos com 65 anos ou mais, residentes nos bairros da zona norte da cidade do Rio de Janeiro, Brasil, e clientes de uma operadora de saúde. O estudo foi transversal, na linha de base de uma coorte, com amostra estratificada por sexo e idade, composta por 764 indivíduos. Para a estratificação de risco, utilizou-se o instrumento de rastreio probabilidade de internações repetidas (PIR). A análise de regressão logística foi realizada para estudar a associação entre a PIR e um conjunto de variáveis sociodemográficas, de estado de saúde, funcionais e cognitivas, após a análise bivariada. Encontraram-se 6,7% de idosos com alto risco de internação. Associaram-se ao risco de internação câncer, quedas, doença pulmonar obstrutiva crônica e medicamentos usados, bem como as seguintes condições: receber visita de profissional da saúde, ter estado acamado no domicílio, morar só e praticar as atividades de vida diária. O instrumento parece ser útil na estratificação de risco dos idosos.

The Longitudinal Urban Cohort Ageing Study (LUCAS): study protocol and participation in the first decade

Background

We present concept, study protocol and selected baseline data of the Longitudinal Urban Cohort Ageing Study (LUCAS) in Germany. LUCAS is a long-running cohort study of community-dwelling seniors complemented by specific studies of geriatric patients or diseases. Aims were to (1) Describe individual ageing trajectories in a metropolitan setting, documenting changes in functional status, the onset of frailty, disability and need of care; (2) Find determinants of healthy ageing; (3) Assess long-term effects of specific health promotion interventions; (4) Produce results for health care planning for fit, pre-frail, frail and disabled elderly persons; (5) Set up a framework for embedded studies to investigate various hypotheses in specific subgroups of elderly.

Methods/Design

In 2000, twenty-one general practitioners (GPs) were recruited in the Hamburg metropolitan area; they generated lists of all their patients 60 years and older. Persons not terminally ill, without daily need of assistance or professional care were eligible. Of these, n = 3,326 (48 %) agreed to participate and completed a small (baseline) and an extensive health questionnaire (wave 1). In 2007/2008, a re-recruitment took place including 2,012 participants: 743 men, 1,269 women (647 deaths, 197 losses, 470 declined further participation). In 2009/2010 n = 1,627 returned the questionnaire (90 deaths, 47 losses, 248 declined further participation) resulting in a good participation rate over ten years with limited and quantified dropouts. Presently, follow-up data from 2007/2008 (wave 2) and 2009/2010 (wave 3) are available. Data wave 4 is due in 2011/2012, and the project will be continued until 2013. Information on survival and need of nursing care was collected continuously and cross-checked against official records. We used Fisher’s exact test and t-tests. The study served repeatedly to evaluate health promotion interventions and concepts.

Discussion

LUCAS shows that a cohort study of older persons is feasible and can maintain a good participation rate over ten years, even when extensive self-reported health data are collected repeatedly through self-filled questionnaires. Evidently individual health developments of elderly persons can be tracked quantifying simultaneously behaviour, co-morbidity, functional competence and their changes. In future, we expect to generate results of significance about the five study aims listed above.

A randomized trial of effects of health risk appraisal combined with group sessions or home visits on preventive behaviors in older adults

BACKGROUND

To explore effects of a health risk appraisal for older people (HRA-O) program with reinforcement, we conducted a randomized controlled trial in 21 general practices in Hamburg, Germany.

METHODS

Overall, 2,580 older patients of 14 general practitioners trained in reinforcing recommendations related to HRA-O-identified risk factors were randomized into intervention (n = 878) and control (n = 1,702) groups. Patients (n = 746) of seven additional matched general practitioners who did not receive this training served as a comparison group. Patients allocated to the intervention group, and their general practitioners, received computer-tailored written recommendations, and patients were offered the choice between interdisciplinary group sessions (geriatrician, physiotherapist, social worker, and nutritionist) and home visits (nurse).

RESULTS

Among the intervention group, 580 (66%) persons made use of personal reinforcement (group sessions: 503 [87%], home visits: 77 [13%]). At 1-year follow-up, persons in the intervention group had higher use of preventive services (eg, influenza vaccinations, adjusted odds ratio 1.7; 95% confidence interval 1.4-2.1) and more favorable health behavior (eg, high fruit/fiber intake, odds ratio 2.0; 95% confidence interval 1.6-2.6), as compared with controls. Comparisons between intervention and comparison group data revealed similar effects, suggesting that physician training alone had no effect. Subgroup analyses indicated favorable effects for HRA-O with personal reinforcement, but not for HRA-O without reinforcement.

CONCLUSIONS

HRA-O combined with physician training and personal reinforcement had favorable effects on preventive care use and health behavior.

Validade preditiva de instrumento para identificação do idoso em risco de hospitalização

OBJETIVO: Avaliar a validade de predição do Instrumento de Predição de Risco de Admissão Hospitalar Repetida da hospitalização de idosos. MÉTODOS: Estudo de coorte de base populacional com seguimento de seis meses com 515 idosos (> 60 anos de idade) não-institucionalizados, atendidos pela Estratégia Saúde da Família na cidade de Progresso, RS, em 2005. Os idosos responderam a oito perguntas objetivas, que foram reunidas em modelo de regressão logística para estimar seu risco de admissão hospitalar futura, por estratos de risco. Análise de sobrevida e a curva Receiver Operating Characteristics foram empregadas para aferir a validade do instrumento. RESULTADOS: Dos entrevistados, 56,1% eram mulheres e 10,1% foram hospitalizados. O grupo de risco alto teve freqüência de internação hospitalar 6,5 vezes superior em relação ao grupo de risco baixo. CONCLUSÕES: O instrumento é efetivo ao predizer o risco de hospitalização dos idosos atendidos pela Estratégia Saúde da Família do Sistema Único de Saúde.

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: the elders risk assessment index

BACKGROUND

The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.

METHODS

We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.

RESULTS

The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.

CONCLUSIONS

It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: the elders risk assessment index

BACKGROUND

The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.

METHODS

We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.

RESULTS

The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.

CONCLUSIONS

It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

Predicting hospital admission and returns to the emergency department for elderly patients

OBJECTIVES

Methods to accurately identify elderly patients with a high likelihood of hospital admission or subsequent return to the emergency department (ED) might facilitate the development of interventions to expedite the admission process, improve patient care, and reduce overcrowding. This study sought to identify variables found among elderly ED patients that could predict either hospital admission or return to the ED.

METHODS

All visits by patients 75 years of age or older during 2007 at an academic ED serving a large community of elderly were reviewed. Clinical and demographic data were used to construct regression models to predict admission or ED return. These models were then validated in a second group of patients 75 and older who presented during two 1-month periods in 2008.

RESULTS

Of 4,873 visits, 3,188 resulted in admission (65.4%). Regression modeling identified five variables statistically related to the probability of admission: age, triage score, heart rate, diastolic blood pressure, and chief complaint. Upon validation, the c-statistic of the receiver operating characteristic (ROC) curve was 0.73, moderately predictive of admission. We were unable to produce models that predicted ED return for these elderly patients.

CONCLUSIONS

A derived and validated triage-based model is presented that provides a moderately accurate probability of hospital admission of elderly patients. If validated experimentally, this model might expedite the admission process for elderly ED patients. Our models failed, as have others, to accurately predict ED return among elderly patients, underscoring the challenge of identifying those individuals at risk for early ED returns.

Risk factors for hospitalization among community-dwelling primary care older patients: development and validation of a predictive model

BACKGROUND

Unplanned hospitalization often represents a costly and hazardous event for the older population.

OBJECTIVES

To develop and validate a predictive model for unplanned medical hospitalization from administrative data.

RESEARCH DESIGN

Model development and validation.

SUBJECTS

A total of 3919 patients aged > or =70 years who were followed for at least 1 year in primary care clinics of an academic medical center.

MEASURES

Risk factor data and the primary outcome of unplanned medical hospitalization were obtained from administrative data.

RESULTS

Of 1932 patients in the development cohort, 299 (15%) were hospitalized during 1 year follow up. Five independent risk factors were identified in the preceding year: Deyo-Charlson comorbidity score > or =2 [adjusted relative risk (RR) = 1.8; 95% confidence interval (CI): 1.4-2.2], any prior hospitalization (RR = 1.8; 95% CI: 1.5-2.3), 6 or more primary care visits (RR = 1.6; 95% CI: 1.3-2.0), age > or =85 years (RR = 1.4; 95% CI: 1.1-1.7), and unmarried status (RR = 1.4; 95% CI: 1.1-1.7). A risk stratification system was created by adding 1 point for each factor present. Rates of hospitalization for the low- (0 factor), intermediate- (1-2 factors), and high-risk (> or =3 factors) groups were 5%, 15%, and 34% (P < 0.0001). The corresponding rates in the validation cohort, where 328/1987 (17%) were hospitalized, were 6%, 16%, and 36% (P < 0.0001).

CONCLUSIONS

A predictive model based on administrative data has been successfully validated for prediction of unplanned hospitalization. This model will identify patients at high risk for hospitalization who may be candidates for preventive interventions.

Preventive home visits to home-dwelling older people and hospital admissions: a municipality-randomised intervention trial

Preventive home visits to older home-dwelling people have been part of national policy in Denmark since 1996. The aim was to evaluate whether education of home visitors and GPs was associated with hospital admission rates. In a population-based prospective controlled intervention trial in 34 municipalities, intervention municipality visitors received regular education during 3 years and GPs were introduced to a short assessment programme. Participation totalled 4,034 75- and 80-year-old home-dwelling persons, of which 3,132 (78%) had no mobility disability at baseline. Complete data on hospital services were obtained for all participants. No difference was observed in time to first admission between older people living in the intervention municipalities compared with people living in the control municipalities, HR 0.93 (95%CI: 0.85, 1.02, P = 0.17). Duration of first hospital stay was the same in the two groups (7.3 days). The mean number of admissions was not associated with intervention. Accepting and receiving home visits was associated with a reduced risk of hospital admission, HR 0.84 (95%CI: 0.76, 0.92), especially among the initially disabled. Hospital admission rates were associated with functional decline patterns. Persons experiencing catastrophic and progressive decline had the highest risk. Persons experiencing reversible functional decline were more often hospitalised in the intervention municipalities, and fewer persons living in the intervention municipalities experienced progressive decline. Education of primary care professionals was not associated with risk for first hospital admission among all older people living in the community, but may be associated with older people's different functional decline patterns.

Screening of older community-dwelling people at risk for death and hospitalization: the Assistenza Socio-Sanitaria in Italia project

OBJECTIVES

To develop and validate mortality and hospitalization prognostic tools based upon information readily available to primary care physicians (PCPs).

DESIGN

Population-based cohort study. Baseline predictors were patient demographics, a seven-item questionnaire on functional status and general health, use of five or more drugs, and previous hospitalization.

SETTING

Community-based study.

PARTICIPANTS

Prognostic indexes were developed in 2,470 subjects and validated in 2,926 subjects, all community-dwelling, aged 65 and older, and randomly sampled from the rosters of 98 PCPs in Florence, Italy.

MEASUREMENTS

Fifteen-month mortality and hospitalization.

RESULTS

Two scores were derived from logistic regression models and used to stratify participants into four groups. With Model 1, based upon the seven-item questionnaire, mortality rate ranged from 0.8% in the lowest-risk group (0-1 point) to 9.4% in the highest risk group (> or = 3 points), and hospitalization rate ranged from 12.4% to 29.3%; area under the receiver operating characteristic curves (AUC) was 0.75 and 0.60, respectively. With Model 2, considering also drug use and previous hospitalization, mortality and hospitalization rates ranged from 0.3% to 8.2% and from 8.1% to 29.7%, for the lowest-risk to the highest-risk group; the AUC increased significantly only for hospitalization (0.67).

CONCLUSION

Prediction of death and hospitalization in older community-dwelling people can be easily obtained with two indexes using information promptly available to PCPs. These tools might be useful for guiding clinical care and targeting interventions to reduce the need for hospital care in older persons.

Predicting nursing home admission in the U.S: a meta-analysis

BACKGROUND

While existing reviews have identified significant predictors of nursing home admission, this meta-analysis attempted to provide more integrated empirical findings to identify predictors. The present study aimed to generate pooled empirical associations for sociodemographic, functional, cognitive, service use, and informal support indicators that predict nursing home admission among older adults in the U.S.

METHODS

Studies published in English were retrieved by searching the MEDLINE, PSYCINFO, CINAHL, and Digital Dissertations databases using the keywords: "nursing home placement," "nursing home entry," "nursing home admission," and "predictors/institutionalization." Any reports including these key words were retrieved. Bibliographies of retrieved articles were also searched. Selected studies included sampling frames that were nationally- or regionally-representative of the U.S. older population.

RESULTS

Of 736 relevant reports identified, 77 reports across 12 data sources were included that used longitudinal designs and community-based samples. Information on number of nursing home admissions, length of follow-up, sample characteristics, analysis type, statistical adjustment, and potential risk factors were extracted with standardized protocols. Random effects models were used to separately pool the logistic and Cox regression model results from the individual data sources. Among the strongest predictors of nursing home admission were 3 or more activities of daily living dependencies (summary odds ratio [OR] = 3.25; 95% confidence interval [CI], 2.56-4.09), cognitive impairment (OR = 2.54; CI, 1.44-4.51), and prior nursing home use (OR = 3.47; CI, 1.89-6.37).

CONCLUSION

The pooled associations provided detailed empirical information as to which variables emerged as the strongest predictors of NH admission (e.g., 3 or more ADL dependencies, cognitive impairment, prior NH use). These results could be utilized as weights in the construction and validation of prognostic tools to estimate risk for NH entry over a multi-year period.

Predicting nursing home admission in the U.S: a meta-analysis

BACKGROUND

While existing reviews have identified significant predictors of nursing home admission, this meta-analysis attempted to provide more integrated empirical findings to identify predictors. The present study aimed to generate pooled empirical associations for sociodemographic, functional, cognitive, service use, and informal support indicators that predict nursing home admission among older adults in the U.S.

METHODS

Studies published in English were retrieved by searching the MEDLINE, PSYCINFO, CINAHL, and Digital Dissertations databases using the keywords: "nursing home placement," "nursing home entry," "nursing home admission," and "predictors/institutionalization." Any reports including these key words were retrieved. Bibliographies of retrieved articles were also searched. Selected studies included sampling frames that were nationally- or regionally-representative of the U.S. older population.

RESULTS

Of 736 relevant reports identified, 77 reports across 12 data sources were included that used longitudinal designs and community-based samples. Information on number of nursing home admissions, length of follow-up, sample characteristics, analysis type, statistical adjustment, and potential risk factors were extracted with standardized protocols. Random effects models were used to separately pool the logistic and Cox regression model results from the individual data sources. Among the strongest predictors of nursing home admission were 3 or more activities of daily living dependencies (summary odds ratio [OR] = 3.25; 95% confidence interval [CI], 2.56-4.09), cognitive impairment (OR = 2.54; CI, 1.44-4.51), and prior nursing home use (OR = 3.47; CI, 1.89-6.37).

CONCLUSION

The pooled associations provided detailed empirical information as to which variables emerged as the strongest predictors of NH admission (e.g., 3 or more ADL dependencies, cognitive impairment, prior NH use). These results could be utilized as weights in the construction and validation of prognostic tools to estimate risk for NH entry over a multi-year period.

The PRO-AGE study: an international randomised controlled study of health risk appraisal for older persons based in general practice

BACKGROUND

This paper describes the study protocol, the recruitment, and base-line data for evaluating the success of randomisation of the PRO-AGE (PRevention in Older people-Assessment in GEneralists' practices) project.

METHODS/DESIGN

A group of general practitioners (GPs) in London (U.K.), Hamburg (Germany) and Solothurn (Switzerland) were trained in risk identification, health promotion, and prevention in older people. Their non-disabled older patients were invited to participate in a randomised controlled study. Participants allocated to the intervention group were offered the Health Risk Appraisal for Older Persons (HRA-O) instrument with a site-specific method for reinforcement (London: physician reminders in electronic medical record; Hamburg: one group session or two preventive home visits; Solothurn: six-monthly preventive home visits over a two-year period). Participants allocated to the control group received usual care. At each site, an additional group of GPs did not receive the training, and their eligible patients were invited to participate in a concurrent comparison group. Primary outcomes are self-reported health behaviour and preventative care use at one-year follow-up. In Solothurn, an additional follow-up was conducted at two years. The number of older persons agreeing to participate (% of eligible persons) in the randomised controlled study was 2503 (66.0%) in London, 2580 (53.6%) in Hamburg, and 2284 (67.5%) in Solothurn. Base-line findings confirm that randomisation of participants was successful, with comparable characteristics between intervention and control groups. The number of persons (% of eligible) enrolled in the concurrent comparison group was 636 (48.8%) in London, 746 (35.7%) in Hamburg, and 1171 (63.0%) in Solothurn.

DISCUSSION

PRO-AGE is the first large-scale randomised controlled trial of health risk appraisal for older people in Europe. Its results will inform about the effects of implementing HRA-O with different methods of reinforcement.