Evalueren van kwaliteit van leven bij thuiswonende ouderen

2021 ◽  
Keyword(s):  
Quality Of Life ◽  
Social Care ◽  
Kwaliteit Van Leven ◽  
Life Tool ◽  
Onderzoek Naar ◽  
Care Outcomes

De groeiende groep thuiswonende ouderen in Nederland vraagt om een goede ondersteuning door inzet van de juiste diensten, zoals huishoudelijke hulp of dagbesteding. Het bepalen van belangrijke uitkomsten is daarin cruciaal en hiervoor zijn brede uitkomsten in termen van kwaliteit van leven (KvL) relevant, waarbij gekeken wordt naar de invloed van diensten op iemands mogelijkheden of capabilities. In dit artikel worden de ontwikkeling en inhoud van de Adult Social Care Outcomes Toolkit (Nederlandstalige versie, ASCOT-NL) en de Extended Quality of Life Tool (EQLT) beschreven en de toepassingsmogelijkheden in de evaluatie van zorg belicht. Beide instrumenten beogen effecten van zorg op KvL van thuiswonende ouderen te meten op meerdere relevante domeinen. De ASCOT-NL kent acht domeinen; de EQLT bevat deze acht domeinen en voegt daar zes domeinen aan toe, hetgeen resulteert in totaal veertien domeinen. De domeinen van de ASCOT-NL zijn gebaseerd op de doelen van sociale ondersteuning en zorg; de aanvullende domeinen van de EQLT zijn gebaseerd op empirisch onderzoek naar KvL vanuit het perspectief van thuiswonende ouderen en de manier waarop zorg kan bijdragen aan KvL.

scholarly journals Valuing informal carers’ quality of life using best-worst scaling—Finnish preference weights for the Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer)

2021 ◽  
Author(s):  
Lien Nguyen ◽  
Hanna Jokimäki ◽  
Ismo Linnosmaa ◽  
Eirini-Christina Saloniki ◽  
Laurie Batchelder ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Learning Effect ◽  
Social Care ◽  
Term Care ◽  
Second Best ◽  
Best Worst Scaling ◽  
Care Outcomes ◽  
Mnl Model ◽  
Preference Weights

AbstractThis study developed Finnish preference weights for the seven-attribute Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer) and investigated survey fatigue and learning in best-worst scaling (BWS) experiments. An online survey that included a BWS experiment using the ASCOT-Carer was completed by a sample from the general population in Finland. A block of eight BWS profiles describing different states from the ASCOT-Carer were randomly assigned to each respondent, who consecutively made four choices (best, worst, second best and second worst) per profile. The analysis panel data had 32,160 choices made by 1005 respondents. A scale multinomial logit (S-MNL) model was used to estimate preference weights for 28 ASCOT-Carer attribute levels. Fatigue and learning effects were examined as scale heterogeneity. Several specifications of the generalised MNL model were employed to ensure the stability of the preference estimates. The most and least-valued states were the top and bottom levels of the control over daily life attribute. The preference weights were not on a cardinal scale. We observed the position effect of the attributes on preferences associated with the best or second-best choices. A learning effect was found. The established preference weights can be used in evaluations of the effects of long-term care services and interventions on the quality of life of service users and caregivers. The learning effect implies a need to develop study designs that ensure equal consideration to all profiles (choice tasks) in a sequential choice experiment.

scholarly journals Measuring Carer Outcomes in an Economic Evaluation: A Content Comparison of the Adult Social Care Outcomes Toolkit for Carers, Carer Experience Scale, and Care-Related Quality of Life Using Exploratory Factor Analysis

2020 ◽  
Vol 40 (7) ◽  
pp. 885-896 ◽  
Author(s):  
Lidia Engel ◽  
Stacey Rand ◽  
Renske Hoefman ◽  
Jessica Bucholc ◽  
Cathrine Mihalopoulos ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Economic Evaluation ◽  
Exploratory Factor Analysis ◽  
Social Care ◽  
Spillover Effects ◽  
Carer Experience Scale ◽  
Related Quality ◽  
Care Outcomes

Background. To incorporate the spillover effects experienced by carers providing informal care in health policy decisions, new carer-related preference-based measures have been developed for use in economic evaluation, which include the Adult Social Care Outcomes Toolkit for Carers (ASCOT-Carer), Carer Experience Scale (CES), and Care-Related Quality of Life (CarerQoL). The aim of this study was to investigate the extent to which these 3 instruments measure complementary or overlapping constructs. Methods. Data were derived from an online survey undertaken with carers residing in Australia. An exploratory factor analysis was conducted to ascertain the underlying latent constructs of the 3 measures. Results. Data from 351 informal carers yielded a 5-factor model describing general quality of life outside caring, problems due to caring, fulfilment from caring, social support with caring, and relationship with the care recipient. Most of the ASCOT-Carer and the CarerQol items loaded onto the first and second factors, respectively. The greatest overlap was observed between CarerQol and CES items loading onto the other 3 shared common factors. Limitations. Online data collection resulted in inconsistent responses, which had to be removed to yield logical data. A convenience sampling approach may have compromised the generalizability of study findings. Conclusion. Although some overlap was observed, the 3 carer-related preference-based measures seem to tap into different constructs of carer-related quality of life and caring experiences and cannot be used interchangeably.

scholarly journals Carer Social Care-Related Quality of Life Outcomes: Estimating English Preference Weights for the Adult Social Care Outcomes Toolkit for Carers

2019 ◽  
Vol 22 (12) ◽  
pp. 1427-1440 ◽  
Author(s):  
Laurie Batchelder ◽  
Juliette Malley ◽  
Peter Burge ◽  
Hui Lu ◽  
Eirini-Christina Saloniki ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Social Care ◽  
Life Outcomes ◽  
Quality Of Life Outcomes ◽  
Related Quality ◽  
Care Outcomes ◽  
Preference Weights

A systematic review of randomised controlled trials of psychosocial interventions for acute mental health inpatients

2021 ◽  
Vol 10 (3) ◽  
pp. 1-17
Author(s):  
Laura D Wainwright ◽  
Gillian Haddock ◽  
Charlotte Dunster-Page ◽  
Katherine Berry
Keyword(s):  
Quality Of Life ◽  
Methodological Quality ◽  
Randomised Controlled Trials ◽  
Social Care ◽  
Psychosocial Interventions ◽  
Controlled Trials ◽  
Patient Functioning ◽  
Electronic Search ◽  
Randomised Controlled

Background/Aims Inpatient wards provide an opportunity to intervene with medical, psychological and social care to contain distress and prevent future relapse. However, they have been criticised for an over-reliance on medication and risk management with limited psychosocial interventions. The aim of this study was to investigate clinical trials of psychosocial interventions for inpatients to identify interventions that are effective at improving quality of life, symptoms or patient functioning. Methods An electronic search of six databases was conducted for papers published from 1806 up until February 2017. A total of 18 randomised controlled trials was identified in which outcomes for symptoms, quality of life or functioning were reported. Results Overall, 15 trials showed a statistically significant result for at least one outcome. Seven categories were identified from the 18 studies, at least one in each category was found to be effective for symptoms, quality of life or functioning. The majority were effective (15 out of 18). Conclusions Given that the methodological quality was generally low and number of randomised controlled trials were small, it is difficult to draw definitive conclusions. Recommendations include more and repeated trials using rigorous methods of testing and reporting.

Thriving in the 21st Century: Outcome Assessment, Practice Parameters, and Accountability

PEDIATRICS ◽  
1995 ◽  
Vol 96 (4) ◽  
pp. 831-835 ◽  
Author(s):  
David A. Bergman
Keyword(s):  
Quality Of Life ◽  
Health Care ◽  
Health Outcomes ◽  
Practice Guidelines ◽  
Scientific Evidence ◽  
Care Practice ◽  
Health Care Outcomes ◽  
Effective Manner ◽  
Care Outcomes

The past two decades have brought about major health care changes that have been driven by an ever-increasing cost of health care, practice variability, and medical malpractice litigation. These changes pose a challenge to pediatricians to contain costs, to reduce inappropriate use of health care services, and to demonstrate improved health care outcomes. To meet this challenge, a new "clinical tool kit" is required, one that will allow the pediatrician to analyze current practices and to document effective interventions. Two of the major tools in this kit are practice guidelines and outcomes assessment instruments. Practice guidelines are optimal care specifications that provide an analytic framework for defining high-quality care and measuring health care outcomes. Ideally, these guidelines should be developed from scientific evidence. In practice, however, scientific evidence to support the majority of recommendations made in guidelines is insufficient. Consequently, these recommendations are instead developed by expert consensus. Measurement of health outcomes includes clinical outcomes, patient satisfaction, cost and use, and quality of life. Health care organizations have become very sophisticated in measuring cost and use, but considerably less work has been done in the patient-centered areas of satisfaction and quality of life. This is particularly true for children, because measures are dependent on the viewpoint chosen (parent, child, or teacher), the age of the child, and the adjustment for severity of illness. Analyzing practice patterns and improving health outcomes will not be easy tasks to accomplish. For the pediatrician to use these tools in an efficient and effective manner, a new research agenda and new skills will be required.

Management of dementia

2020 ◽  
pp. 557-570
Author(s):  
Sarah Cullum ◽  
Tesema Taye
Keyword(s):  
Quality Of Life ◽  
Social Care ◽  
Ethical Issues ◽  
Family Members ◽  
Dementia Care ◽  
Psychosocial Aspects ◽  
People With Dementia

The cornerstone of dementia care is social care, and much of this is delivered by the families and carers of people with dementia. The management of dementia should therefore focus on supporting and developing the care provided by family members and carers in the community, because their education and enablement will help to optimize the quality of life for all people living with dementia. This chapter concentrates on the assessment and management of people with dementia in the early and later stages of the disorder. At both stages we consider engagement, autonomy, respect, protection, and ethical issues, as well as describing the clinical and psychosocial aspects of treatment. The emphasis is on the broader principles of management, which apply to people with dementia of any aetiology, their families, carers, and communities, and take into account the different settings in which they may present.

Investigating the relative value of health and social care related quality of life using a discrete choice experiment

2019 ◽  
Vol 233 ◽  
pp. 28-37 ◽  
Author(s):  
Brendan Mulhern ◽  
Richard Norman ◽  
Richard De Abreu Lourenco ◽  
Juliette Malley ◽  
Deborah Street ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Social Care ◽  
Relative Value ◽  
Health And Social Care ◽  
Related Quality ◽  
Value Of Health

scholarly journals Improving quality of life in cancer patients through higher participation and health literacy: study protocol for evaluating the oncological social care project (OSCAR)

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Johann Frick ◽  
Daniel Schindel ◽  
Pimrapat Gebert ◽  
Ulrike Grittner ◽  
Liane Schenk
Keyword(s):  
Quality Of Life ◽  
Cancer Patients ◽  
Patient Reported Outcomes ◽  
Social Care ◽  
The Social ◽  
Patient Reported ◽  
Mixed Method Design ◽  
Insurance Funds ◽  
Health Insurance Funds

Abstract Background Cancer patients experience psychological and social distress due to their medical treatment and social issues. However, continuous and specialized social support is still lacking. In Germany, a group of company health insurance funds has developed an approach to support cancer patients with monthly structured interviews conducted by specially trained Social Care Nurses. The nurses will identify patient needs in order to provide help with medical, personal, and social matters. One aim of the scientific evaluation is to analyze the effect of the consultations on various patient-reported outcomes, especially quality of life. The evaluation concept will be described in this study protocol. Methods/design The evaluation is a non-randomized, controlled, multi-center intervention study with a mixed-method design. It consists of three research modules which include primary data from questionnaires, and claims data from the health insurance funds. In Module 1, cancer patients will be recruited to form an intervention group (OSCAR, n = 150) and a control group (n = 200) in four study centers for a period of 1 year. One baseline and three follow-up questionnaires will be conducted to survey the patient-reported outcomes. Relevant secondary outcomes are health literacy, participation, and physician-patient communication. In Module 2, claims data will be used to analyze cost effects and thereby assess effectivity and hospitalization. Module 3 will involve a qualitative analysis of project diaries kept by the Social Care Nurses. The diaries will record the nurses’ practical experiences and the benefits of deploying OSCAR across the German healthcare system. Discussion OSCAR is an innovative way of providing cancer patients with continuous support to improve their quality of life. The evaluation concept aims to assess the effects of the monthly consultations by the Social Care Nurses on the patients, and will use a mixed-method design. The results are important for assessing the transferability of OSCAR to the healthcare system as a whole. Trial registration German Clinical Trials Register (DRKS-ID: DRKS00013640). Registered 29 December 2017.

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