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BACKGROUND: The management of persons with multimorbidity challenges healthcare systems tailored to individual diseases. A person-centred care approach is advocated, in particular for persons with multimorbidity. The aim of this study was to describe the co-creation and piloting of a proactive, person-centred chronic care approach for persons with multimorbidity in general practice, including facilitators and challenges for successful implementation. METHODS: A participatory action research (PAR) approach was applied in 13 general practices employing four subsequent co-creation cycles between 2019 and 2021. The target population included adults with ≥3 chronic conditions. Participating actors were general practitioners (GPs), practice nurses (PNs), patients (target group), the affiliated care cooperation, representatives of a health insurer and researchers. Each cycle consisted of a try-out period in practice and a reflective evaluation through focus groups with healthcare providers, interviews with patients and analyses of routine care data. In each cycle, facilitators, challenges and follow-up actions for the next cycle were identified. Work satisfaction among GPs and PNs was measured pre and at the end of the final co-creation cycle. RESULTS: Identified essential steps in the person-centred chronic care approach include (1) appropriate patient selection for (2) an extended person-centred consultation, and (3) personalised goalsetting and follow-up. Key facilitators included improved therapeutic relationships, enhanced work satisfaction for care providers, and patient appreciation of extended time with their GP. Deliberate task division and collaboration between GPs and PNs based on patient, local setting, and care personnel is required. Challenges and facilitators for implementation encompassed a prioritisation tool to support GPs appropriately who to invite first for extended consultations, appropriate remuneration and time to conduct extended consultations, training in delivering person-centred chronic care available for all general practice care providers and an electronic medical record system accommodating comprehensive information registration. CONCLUSIONS: A person-centred chronic care approach targeting patients with multimorbidity in general practice was developed and piloted in co-creation with stakeholders. More consultation time facilitated better understanding of persons' situations, their functioning, priorities and dilemma's, and positively impacted work satisfaction of care providers. Challenges need to be tackled before widespread implementation. Future evaluation on the quadruple aims is recommended.
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Medicina Geral , Clínicos Gerais , Adulto , Humanos , Multimorbidade , Assistência Centrada no Paciente , Pesquisa sobre Serviços de Saúde , Relações Médico-PacienteRESUMO
BACKGROUND: Persons with multimorbidity may gain from person-centred care compared with the current protocolised chronic-disease management in Dutch general practice. Given time constraints and limited resources, it is essential to prioritise those most in need of an assessment of person-centred chronic-care needs. AIM: To develop and validate a prioritisation algorithm based on routine electronic medical record (EMR) data that distinguishes between patients with multimorbidity who would, and those who would not, benefit from an extended person-centred consultation to assess person-centred chronic-care needs, as judged by GPs. DESIGN AND SETTING: A mixed-methods study was conducted in five general practices in the north-west region of the Netherlands. Four out of the five practices were situated in rural areas. METHOD: Multivariable logistic regression using EMR data to predict the GPs' judgement on patients' anticipated benefit from an extended consultation, as well as a thematic analysis of a focus group exploring GPs' clinical reasoning for this judgement were conducted. Internal validation was performed using 10-fold cross-validation. Multimorbidity was defined as the presence of ≥3 chronic conditions. RESULTS: In total, EMRs from 1032 patients were included in the analysis; of these, 352 (34.1%) were judged to have anticipated benefit. The model's cross-validated C-statistic was 0.72 (95% confidence interval = 0.70 to 0.75). Calibration was good. Presence of home visit(s) and history of myocardial infarction were associated with anticipated benefit. Thematic analysis revealed three dimensions feeding anticipated benefit: GPs' cause for concern, patients' mindset regarding their conditions, and balance between received care/expected care needed. CONCLUSION: This algorithm may facilitate automated prioritisation, potentially avoiding the need for GPs to personally triage the whole practice population that has multimorbidity. However, external validation of the algorithm and evaluation of actual benefit of consultation is recommended before implementation.
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Algoritmos , Registros Eletrônicos de Saúde , Medicina Geral , Multimorbidade , Assistência Centrada no Paciente , Encaminhamento e Consulta , Humanos , Países Baixos , Feminino , Masculino , Doença Crônica/terapia , Pessoa de Meia-Idade , Idoso , Grupos Focais , Clínicos GeraisRESUMO
BACKGROUND: Unplanned admissions to hospital represent a hazardous event for older people. Timely identification of high-risk individuals using a prediction tool may facilitate preventive interventions. AIM: To develop and validate an easy-to-use prediction model for unplanned admissions to hospital in community-dwelling older adults using readily available data to allow rapid bedside assessment by GPs. DESIGN AND SETTING: This was a retrospective study using the general practice electronic health records of 243 324 community-dwelling adults aged ≥65 years linked with national administrative data to predict unplanned admissions to hospital within 6 months. METHOD: The dataset was geographically split into a development (n = 142 791/243 324, 58.7%) and validation (n = 100 533/243 324, 41.3%) sample to predict unplanned admissions to hospital within 6 months. The performance of three different models was evaluated with increasingly smaller selections of candidate predictors (optimal, readily available, and easy-to-use models). Logistic regression was used with backward selection for model development. The models were validated internally and externally. Predictive performance was assessed by area under the curve (AUC) and calibration plots. RESULTS: In both samples, 7.6% (development cohort: n = 10 839/142 791, validation cohort: n = 7675/100 533) had ≥1 unplanned hospital admission within 6 months. The discriminative ability of the three models was comparable and remained stable after geographic validation. The easy-to-use model included age, sex, prior admissions to hospital, pulmonary emphysema, heart failure, and polypharmacy. Its discriminative ability after validation was AUC 0.72 (95% confidence interval = 0.71 to 0.72). Calibration plots showed good calibration. CONCLUSION: The models showed satisfactory predictive ability. Reducing the number of predictors and geographic validation did not have an impact on predictive performance, demonstrating the robustness of the model. An easy-to-use tool has been developed in this study that may assist GPs in decision making and with targeted preventive interventions.
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Medicina Geral , Hospitalização , Humanos , Idoso , Feminino , Masculino , Estudos Retrospectivos , Hospitalização/estatística & dados numéricos , Medição de Risco , Idoso de 80 Anos ou mais , Registros Eletrônicos de Saúde , Vida Independente , Dados de Saúde Coletados Rotineiramente , Fatores de Risco , Admissão do Paciente/estatística & dados numéricosRESUMO
BACKGROUND: Successfully introducing and maintaining care innovations may depend on the interplay between care setting, the intervention and specific circumstances. We studied the factors influencing the introduction and maintenance of a Multidisciplinary Integrated Care model in 10 Dutch residential care homes. METHODS: Facilitating and impeding factors were studied and compared at the time of introduction of the interRAI-LTCF assessment method in residential care homes as well as three years later, by surveys and semi structured interviews among nurse staff, managers, and physicians. RESULTS: Facilitating factors at introduction were positive opinions of staff and family physicians about the changes of the process of care and the anticipated improvement of quality of care. Staff was positive about the applicability of the software to support the interRAI-LTCF assessments. Impeding factors were time constraints to complete interRAI-LTCF assessments and insufficient computer equipment.In the maintenance phase, the positive attitude of the location manager and the perceived benefits of the care model and the interRAI-LTCF assessment method were most important. Impeding factors after 3 years remained the lack of time to complete the assessments and lack of sufficient computer equipment. CONCLUSIONS: Impeding and facilitating factors were comparable in the initial and maintenance phase. Adoption of the interRAI-LTCF assessment method depended on positive opinions of staff and management, continuing support of staff and the availability of sufficient computer equipment.
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Técnicas de Apoio para a Decisão , Difusão de Inovações , Avaliação Geriátrica , Instituição de Longa Permanência para Idosos , Adulto , Idoso , Idoso de 80 Anos ou mais , Atitude do Pessoal de Saúde , Feminino , Pesquisas sobre Atenção à Saúde , Humanos , Masculino , Países Baixos , Pesquisa QualitativaRESUMO
BACKGROUND: Routinely collected clinical data based on electronic medical records could be used to define frailty. AIM: To estimate the ability of four potential frailty measures that use electronic medical record data to identify older patients who were frail according to their GP. DESIGN AND SETTING: This retrospective cohort study used data from 36 GP practices in the Dutch PHARMO Data Network. METHOD: The measures were the Dutch Polypharmacy Index, Charlson Comorbidity Index (CCI), Chronic Disease Score (CDS), and Frailty Index. GPs' clinical judgement of patients' frailty status was considered the reference standard. Performance of the measures was assessed with the area under the receiver operating characteristic curve (AUC). Analyses were done in the total population and stratified by age and sex. RESULTS: Of 31 511 patients aged ≥65 years, 3735 (11.9%) patients were classified as frail by their GP. The CCI showed the highest AUC (0.79, 95% confidence interval [CI] = 0.78 to 0.80), followed by the CDS (0.69, 95% CI = 0.68 to 0.70). Overall, the measures showed poorer performance in males and females aged ≥85 years than younger age groups (AUC 0.55-0.58 in females and 0.57-0.60 in males). CONCLUSION: This study showed that of four frailty measures based on electronic medical records in primary care only the CCI had an acceptable performance to assess frailty compared with frailty assessments done by professionals. In the youngest age groups diagnostic performance was acceptable for all measures. However, performance declined with older age and was least accurate in the oldest age group, thereby limiting the use in patients of most interest.
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Fragilidade , Idoso , Masculino , Feminino , Humanos , Fragilidade/diagnóstico , Idoso Fragilizado , Estudos Retrospectivos , Avaliação Geriátrica , Doença Crônica , Atenção Primária à SaúdeRESUMO
INTRODUCTION: In ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home care and nursing homes, where most older persons with CCCs receive care, professionals often lack appropriate decision support suitable and sufficient to address the medical and functional complexity of persons with CCCs. This EU-funded project aims to develop decision support systems using high-quality, internationally standardised, routine care data to support better prognostication of health trajectories and treatment impact among older persons with CCCs. METHODS AND ANALYSIS: Real-world data from older persons aged ≥60 years in home care and nursing homes, based on routinely performed comprehensive geriatric assessments using interRAI systems collected in the past 20 years, will be linked with administrative repositories on mortality and care use. These include potentially up to 51 million care recipients from eight countries: Italy, the Netherlands, Finland, Belgium, Canada, USA, Hong Kong and New Zealand. Prognostic algorithms will be developed and validated to better predict various health outcomes. In addition, the modifying impact of pharmacological and non-pharmacological interventions will be examined. A variety of analytical methods will be used, including techniques from the field of artificial intelligence such as machine learning. Based on the results, decision support tools will be developed and pilot tested among health professionals working in home care and nursing homes. ETHICS AND DISSEMINATION: The study was approved by authorised medical ethical committees in each of the participating countries, and will comply with both local and EU legislation. Study findings will be shared with relevant stakeholders, including publications in peer-reviewed journals and presentations at national and international meetings.
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Inteligência Artificial , Serviços de Assistência Domiciliar , Humanos , Idoso , Idoso de 80 Anos ou mais , Envelhecimento , Algoritmos , Doença Crônica , Estudos Observacionais como AssuntoRESUMO
This study aims to benchmark mean societal costs per client in different home care models and to describe characteristics of home care models with the lowest societal costs. In this prospective longitudinal study in 6 European countries, 6-month societal costs of resource utilization of 2060 older home care clients were estimated. Three care models were identified and compared based on level of patient-centered care (PCC), availability of specialized professionals (ASP) and level of monitoring of care performance (MCP). Differences in costs between care models were analyzed using linear regression while adjusting for case mix differences. Societal costs incurred in care model 2 (low ASP; high PCC & MCP) were significantly higher than in care model 1 (high ASP, PCC & MCP, mean difference 2230 (10%)) and in care model 3 (low ASP & PCC; high MCP, mean difference 2552 (12%)). Organizations within both models with the lowest societal costs, systematically monitor their care performance. However, organizations within one model arranged their care with a low focus on patient-centered care, and employed mainly generalist care professionals, while organizations in the other model arranged their care delivery with a strong focus on patient-centered care combined with a high availability of specialized care professionals.
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This study aims to develop and validate a prediction model of societal costs during a period of 6-months in older community care-recipients across multiple European countries. Participants were older community care-recipients from 5 European countries. The outcome measure was mean 6-months total societal costs of resource utilisation (healthcare and informal care). Potential predictors included sociodemographic characteristics, functional limitations, clinical conditions, and diseases/disorders. The model was developed by performing Linear Mixed Models with a random intercept for the effect of country and validated by an internal-external validation procedure. Living alone, caregiver distress, (I)ADL impairment, required level of care support, health instability, presence of pain, behavioural problems, urinary incontinence and multimorbidity significantly predicted societal costs during 6 months. The model explained 32% of the variation within societal costs and showed good calibration in Iceland, Finland and Germany. Minor model adaptations improved model performance in The Netherland and Italy. The results can provide a valuable orientation for policymakers to better understand cost development among older community care-recipients. Despite substantial differences of countries' care systems, a validated cross-national set of key predictors could be identified.
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Most countries aim to allocate home health care to those in need in a fair and equal way. Equal allocation implies that the amount of home care a person receives would reflect the level of health impairment and the need for resources. It is not clear whether countries succeed in attaining this. Our objective was to explore signs of (un)equal home health care provisioning across care organizations and across European health countries. We used data of the IBenC study collected from 2718 older community care recipients from 33 organizations in 6 Western European countries (www.ibenc.eu). We benchmarked differences of provided and expected formal care time across organizations and countries. Expected formal care hours were estimated by multiplying the overall sample's mean formal hours with recipients' case mix weights from interRAI's resources utilization group profiles. We found substantial variations in provided formal care time among organizations both within and across countries that could not be explained by the case mix differences of recipients. This implied presence of inequality of home care provisioning. These findings may alert professionals and policy makers striving for equal home health care provisioning for dependent older persons.
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BACKGROUND: The objective was to identify predictors of societal costs covering formal and informal care utilization by older home care clients in 11 European countries. METHODS: Societal costs of 1907 older clients receiving home care for 12 months from the Aged in Home care (AdHoc) study were estimated using the InterRAI Minimum Data Set for Home Care's (MDS-HC) resource use items. Predictors (medical, functional, and psychosocial domains) of societal costs were identified by performing univariate and multivariate generalized linear model analyses. RESULTS: Mean societal costs per participant were 36 442, ranging from 14 865 in Denmark to 78 836 in the United Kingdom. In the final multivariate model, country, being married, activities of daily living (ADL) dependency, cognitive impairment, limitations of going out, oral conditions, number of medications, arthritis, and cerebro vascular accident (CVA) were significantly associated with societal costs. CONCLUSIONS: Of the predictors, ADL dependency and limitations of going out may be modifiable. Developing interventions targeted at improving these conditions may create opportunities to curtail societal costs.