What matters to me – a web-based preference elicitation tool for clients in long-term care: a user-centred design

Abstract Background: During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this qualitative descriptive study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of long-term care. Methods: We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration: Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis. Results: The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties. Conclusion: By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool ‘What matters to me’. This tool may assist the elicitation of client’s preferences in their search for long-term care.

Download Full-text

What matters to me – A web-based preference elicitation tool for clients in long-term care: a user-centred design

10.21203/rs.2.15499/v1 ◽

2019 ◽

Author(s):

Catharina Margaretha van Leersum ◽

Albine Moser ◽

Ben van Steenkiste ◽

Marion Reinartz ◽

Esther Stoffers ◽

...

Keyword(s):

Long Term Care ◽

Well Being ◽

Preference Elicitation ◽

End Users ◽

Term Care ◽

Web Based ◽

User Centred Design ◽

Care Services ◽

What Matters

Abstract Background: During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this usability study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of long-term care. Methods: We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration: Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis. Results: The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties. Conclusion: By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool ‘What matters to me’. This tool may assist the elicitation of client’s preferences in their search for long-term care.

Download Full-text

Clients and professionals elicit long-term care preferences by using ‘What matters to me’: A process evaluation

10.21203/rs.3.rs-35163/v3 ◽

2021 ◽

Author(s):

Catharina Margaretha van Leersum ◽

Albine Moser ◽

Ben van Steenkiste ◽

Judith R.L.M. Wolf ◽

Trudy van der Weijden

Keyword(s):

Process Evaluation ◽

Long Term Care ◽

Preference Elicitation ◽

Term Care ◽

Digital Version ◽

The Impact ◽

Care Evaluation ◽

Consultation Time ◽

What Matters

Abstract Background: ‘What matters to me’ is a five-category preference elicitation tool to assist clients and professionals in choosing long-term care. This study aimed to evaluate the use of and experiences with this tool.Methods: A mixed-method process evaluation was applied. Participants were clients, relatives, and professionals. They were all involved in decision-making on long-term care. Data collection comprised online user activity logs (N=71), questionnaires (N=38), and interviews (N=20). Descriptive statistics was used for quantitative data, and a thematic analysis for qualitative data.Results: Sixty-nine percent of participants completed one or more categories in an average time of 6.9 (±0.03) minutes. The tool was rated 6.63 (±0.88) out of seven in the Post-Study System Usability Questionnaire (PSSUQ). Ninety-five percent experienced the tool as useful in practice. Suggestions for improvement included a separate version for relatives and a non-digital version. Although professionals thought the potentially extended consultation time could be problematic, all participants would recommend the tool to others.Conclusion: ‘What matters to me’ seems useful to assist clients and professionals with preference elicitation for long-term care. Evaluation of the impact on consultations between clients and professionals by using ‘What matters to me’ is needed.

Download Full-text

Clients and professionals elicit long-term care preferences by using ‘What matters to me’: A process evaluation

10.21203/rs.3.rs-35163/v2 ◽

2020 ◽

Author(s):

Catharina Margaretha van Leersum ◽

Albine Moser ◽

Ben van Steenkiste ◽

Judith R.L.M. Wolf ◽

Trudy van der Weijden

Keyword(s):

Process Evaluation ◽

Long Term Care ◽

Preference Elicitation ◽

Term Care ◽

Digital Version ◽

The Impact ◽

Care Evaluation ◽

Consultation Time ◽

What Matters

Abstract Background: ‘What matters to me’ is a five-category preference elicitation tool to assist clients and professionals in choosing long-term care. This study aimed to evaluate the use of and experiences with this tool.Methods: A mixed-method process evaluation was applied. Participants were clients, relatives, and professionals. They were all involved in decision-making on long-term care. Data collection comprised online user activity logs (N=71), questionnaires (N=38), and interviews (N=20). Descriptive statistics was used for quantitative data, and a thematic analysis for qualitative data.Results: Sixty-nine percent of participants completed one or more categories in an average time of 6.9 (±0.03) minutes. The tool was rated 6.63 (±0.88) out of seven in the Post-Study System Usability Questionnaire (PSSUQ). Ninety-five percent experienced the tool as useful in practice. Suggestions for improvement included a separate version for relatives and a non-digital version. Although professionals thought the potentially extended consultation time could be problematic, all participants would recommend the tool to others.Conclusion: ‘What matters to me’ seems useful to assist clients and professionals with preference elicitation in long-term care. Evaluation of the impact on consultations between clients and professionals by using ‘What matters to me’ is needed.

Download Full-text

OP31 Developing and improving a web-based tool for clients in long-term care: a user-centred design

10.1136/spcare-2019-acpicongressabs.31 ◽

2019 ◽

Author(s):

C van Leersu ◽

A Moser ◽

B van Steenkiste ◽

E Stoffers ◽

M Reinartz ◽

...

Keyword(s):

Long Term Care ◽

Term Care ◽

Web Based ◽

User Centred Design

Download Full-text

Clients and professionals elicit long-term care preferences by using ‘What matters to me’: A process evaluation

10.21203/rs.3.rs-35163/v1 ◽

2020 ◽

Author(s):

Catharina Margaretha van Leersum ◽

Albine Moser ◽

Ben van Steenkiste ◽

Judith R.L.M. Wolf ◽

Trudy van der Weijden

Keyword(s):

Process Evaluation ◽

Long Term Care ◽

Preference Elicitation ◽

Term Care ◽

Digital Version ◽

The Impact ◽

Care Evaluation ◽

Consultation Time ◽

What Matters

Abstract Background ‘What matters to me’ is a five-category preference elicitation tool to assist clients and professionals in choosing long-term care. This study aimed to evaluate the use of and experiences with this tool. Methods A mixed-method process evaluation was applied. Participants were clients, relatives, and professionals. They were all involved in decision-making on long-term care. Data collection comprised online user activity logs (N = 71), questionnaires (N = 38), and interviews (N = 20). Descriptive statistics was used for quantitative data, and a thematic analysis for qualitative data. Results Sixty-nine percent of participants completed one or more categories in an average time of 6.9 (± 0.03) minutes. The tool was rated 6.63 (± 0.88) out of seven in the Post-Study System Usability Questionnaire (PSSUQ). Ninety-five percent experienced the tool as useful in practice. Suggestions for improvement included a separate version for relatives and a non-digital version. Although professionals thought the potentially extended consultation time could be problematic, all participants would recommend the tool to others. Conclusion ‘What matters to me’ seems useful to assist clients and professionals with preference elicitation in long-term care. Evaluation of the impact on consultations between clients and professionals by using ‘What matters to me’ is needed.

Download Full-text

Design and Development of a Web-based Delirium Preventive Application for Long-term Care Facilities: A Methodological Study (Preprint)

10.2196/preprints.26092 ◽

2020 ◽

Author(s):

Kyoung Ja Moon ◽

Chang-Sik Son ◽

Jong-Ha Lee ◽

Mina Park

Keyword(s):

Risk Factors ◽

Long Term Care ◽

Cloud System ◽

Evidence Based ◽

Methodological Study ◽

Term Care ◽

Web Based ◽

Care Facilities ◽

Delirium Prevention

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

Download Full-text

Measuring What Matters Across International Long-Term Care Settings

Innovation in Aging ◽

10.1093/geroni/igab046.609 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 160-160

Author(s):

Kirsten Corazzini ◽

Michael Lepore

Keyword(s):

Long Term Care ◽

Assessment Tool ◽

Term Care ◽

Common Data Elements ◽

Person Centered Care ◽

Care Assessment ◽

Centered Care ◽

Data Elements ◽

What Matters

Abstract Measuring what matters most to residents, relatives and staff in residential long-term care settings is critical, yet underdeveloped in our predominantly frailty and deficits-focused measurement frameworks. The Worldwide Elements to Harmonize Research in Long-Term Care Living Environments (WE-THRIVE) consortium has previously prioritized measurement concepts in the areas of care outcomes, workforce and staffing, person-centered care, and care context. These concepts include knowing the resident and what matters most to the resident, and outcomes such as quality of life, and personhood. We present findings of our currently recommended measures, including both general population and dementia-specific measures, such as the Person-Centered Care Assessment Tool (PCAT), the Personhood in Dementia Questionnaire (PDQ), and the ICEpop CAPability Measure for Older People (ICECAP-O). We also describe remaining gaps in existing measures that will need to be addressed to fully specify common data elements focused on measuring what matters most to residents, relatives and staff.

Download Full-text