Improving Care for Frail Older Adults Using a Digital Needs Assessment Tool (Frailty)

Integrating Health and Social Service Needs for Frail Elders at Point of Care: Development and Evaluation of an IT-based Digital Needs-assessment Tool

The goal of this trial is to evaluate whether a digital needs-assessment tool can improve care planning and outcomes for frail older adults (aged 60 years and above) hospitalized in Singapore. The tool is designed to identify patients' health and social service needs and support better care coordination after hospital discharge.

The main questions it aims to answer are:

• Does the use of a digital needs-assessment tool improve the identification and management of health and social service needs in frail older adults?
• Does this approach improve patient outcomes, such as quality of life, care satisfaction, and healthcare utilization after discharge?

Participants will:

• Respond to a baseline questionnaire
• Receive a personalized care plan based on identified needs by the tool
• Be followed up at 1 month and 3 months after discharge through surveys
• Some participants will receive additional follow-up phone calls to review care needs and service use
• A subset of participants will take part in interviews to share their care experiences

Study Overview

• Status: Not yet recruiting
• Conditions: Frail Older Adults; Geriatric Syndromes; Frail Elderly Patients
• Intervention / Treatment: Behavioral: Core: SST-informed care planning; Behavioral: Additional telephone calls

Detailed Description

Older adults with frailty frequently experience multiple medical, functional, and social challenges following hospital discharge. Evidence from the Health and Social Service Needs study indicates that patients discharged with unmet health and health-related social service (HASS) needs have poorer post-discharge outcomes, including increased healthcare utilization. While frailty screening is commonly used to identify high-risk patients, frailty status alone does not identify the specific actionable needs that could mitigate health deterioration or support community living.

During hospitalization, assessments of these needs are typically conducted through referrals to medical social workers, patient navigators, case managers, or geriatricians. These referrals are discretionary and vary across providers and settings, contributing to inconsistent care delivery. Such approaches are resource-intensive and difficult to sustain under workforce constraints and may lead to missed identification of needs or delays in discharge, increasing the risk of unmet needs during care transitions.

This study evaluates the implementation of a needs-based assessment approach using the Simple Segmentation Tool (SST), a brief digital instrument developed in Singapore by Matchar et al. (2017). The SST is designed to rapidly identify likely actionable HASS needs and support care planning and referral processes. The tool can be completed in approximately 2-3 minutes by trained healthcare professionals, including physicians, nurses, and case managers, and is supported by an algorithm developed by a multidisciplinary expert panel.

Following enrollment, hospital staff will complete the SST based on participants' clinical and social circumstances. Care plans will be generated using outputs from the SST and reviewed with participants and/or their caregivers. If a participant is readmitted within three weeks of discharge, the SST assessment will be repeated following the subsequent discharge to ensure that care plans reflect updated or evolving needs. Participants who decline recommended services will remain enrolled in the study but will not be counted toward the target sample size of 200 participants.

Participants will complete a baseline questionnaire during hospitalization and will be followed after discharge with structured surveys administered at one month and three months. These surveys will assess post-discharge outcomes related to health status, care experiences, and healthcare utilization. Qualitative interviews will also be conducted with a subset of patients and healthcare staff to explore experiences, perceived value, and implementation challenges associated with SST-guided care planning.

To support care coordination, internal stakeholders and external community service providers, coordinated by the Agency for Integrated Care Care-Referral Team, will use a shared framework to facilitate service linkage and care transitions. Service activation and follow-up will be tracked, and any failures in linkage will be communicated to a central coordinating team to support resolution and continuity of care.

Prior to the main study, a pilot phase involving up to 10 patient volunteers will be conducted to assess workflow feasibility, clarity of study materials, and questionnaire length. Pilot participants will provide informed consent, and data collected during this phase will not be included in research analyses. Feedback from the pilot will be used to refine study procedures and materials prior to full implementation.

• Study Type: Interventional
• Enrollment (Estimated): 200
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Shenglin Zheng, Ph.D.; Phone Number: 6580325886; Email: sz61@nus.edu.sg

Study Locations

• Singapore
  • Singapore, Singapore
    • Changi General Hospital (CGH)
    • Contact: Barbara H Rosario, FRCP (Lond); Phone Number: 6569366528; Email: rosario.barbara.helen@singhealth.com.sg

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Patient participant: (i) Aged >= 60 years at the time of recruitment; (ii) identified as frail, with a CFS score >= 5 and/or modified HFRS intermediate and high frailty risk (mHFRS) score >=5; (iii) Singapore citizens or permanent residents; (iv) able to speak and understand English, Chinese or Malay.
• Proxy (when responding on behalf of eligible patients): (i) Relative or friend of the patient participant; (ii) Aged 21 years or older; (iii) Familiar with the older adult's health and social situation.

Exclusion Criteria:

• Patient participant: (i) Currently involved in another study or (ii) residents of nursing homes, or (iii) patients known to home hospice or home palliative care services with a life expectancy of less than 6 months.
• Proxy: primary caregivers who are foreign domestic workers will be excluded from the study.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: SST + care coordination calls; Participants will receive a digital needs assessment during hospitalization and a personalized care plan. After discharge, participants will be randomized in a 1:3 ratio. Participants will receive two follow-up calls from care coordinators to review care needs and support care coordination.	Behavioral: Core: SST-informed care planning; The Simple Segmentation Tool (SST) is used to assess multidimensional needs and generate individualized care recommendations. Participants receive SST-informed care plan and referral to appropriate health and social services.; Behavioral: Additional telephone calls; Participants will receive two structured post-discharge care coordination phone calls to support service uptake, address barriers, and facilitate follow-up on recommended services.
Experimental: SST only; Participants will receive a digital needs assessment during hospitalization and a personalized care plan.	Behavioral: Core: SST-informed care planning; The Simple Segmentation Tool (SST) is used to assess multidimensional needs and generate individualized care recommendations. Participants receive SST-informed care plan and referral to appropriate health and social services.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Service initiation rate	The proportion of enrolled participants who successfully initiate at least one recommended health or social support service	30 days after discharge

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Health-related quality of life	Change in health-related quality of life measured using the 5-level EQ-5D (EQ-5D-5L). The EQ-5D-5L essentially consists of the EQ-5D descriptive system, where Index Score calculated based on country-specific preference (Singapore in this context) and the EuroQol Visual Analogue Scale (EQ-VAS) (range: 0 to 100) were reported. For both measures, higher scores indicate better health-related quality of life.	Baseline, 1-month and 3-month follow-ups
Healthcare Utilisation	Healthcare service utilisation obtained from electronic medical records (EMR), including number of emergency department visits, hospital admissions, outpatient visits, and visits to healthcare professionals.	180 days and 360 days post-discharge
Usability of SST	Usability was measured using the System Usability Scale (SUS), a 10-item instrument providing a global score from 0 to 100. Higher scores indicate better perceived usability.	24 hours after the first administered SST
Intervention appropriateness (implementation outcome)	Assessed using the Intervention Appropriateness Measure (IAM) among staff involved in the care of patients using the SST, with total scores ranging from 4-20. Higher scores indicate greater appropriateness.	3-month follow-up
Quality of care and continuity	Quality of care and continuity is measured using the adaptive Patient Continuity of Care Checklist (PCCQ). Items are rated on a 5-point Likert scale and scores range from 5-30. Higher scores indicate a higher level of perceived continuity of care.	1-month and 3-month follow-ups
Mortality	All-cause mortality assessed using electronic medical records (EMR), defined as death occurring from the time of enrollment.	180 and 360 days post-discharge
Service quality of SST	Perceived service quality was measured using an adaptive Electronic Service Quality Scale (E-S-QUAL) consisting of 19 items. Respondents first distributed 100 points across the four dimensions Efficiency, Fulfillment, System Availability, and Privacy, to reflect relative importance. Items were then rated on a 5-point Likert scale. Higher scores indicating a better perception of electronic service quality.	24 hours after the first administered SST
Care experience	Patient-reported experience is measured using Client Satisfaction Questionnaire (CSQ-4). Total scores range from 4 to 16, where higher scores indicate greater satisfaction with care.	1-month and 3-month follow-ups
Intervention feasibility (implementation outcome)	Assessed using the Feasibility of Intervention Measure (FIM) among staff involved in the care of patients using the SST. Total scores range from 4-20 and higher scores indicate greater feasibility.	3-month follow-up
Normalization process (implementation outcome)	Assessed using the Normalisation Measure Development (NoMAD) among staff involved in the care of patients using the SST. Total scores range from 0-100. Higher scores indicate better normalization.	3-month follow-up
Intervention acceptability (implementation outcome)	Measured by the Acceptability of Intervention Measure (AIM)among staff involved in the care of patients using the SST, with a total score ranging from 4-20. Higher scores indicate greater acceptability.	3-month follow-up

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Healthcare costs	Healthcare utilisation costs and billing data obtained from EMR, including hospital and outpatient service costs.	180 and 360 days post-discharge
Unmet needs and service utilization	Assessment of assistance participants received since the last hospital discharge (18-item)	1-month and 3-month follow-ups
Caregiver burden (proxy participants only)	Caregiver burden measured using the 4-item Zarit Burden Interview, administered to proxies who are primary caregivers.	Baseline, 1-month and 3-month follow-ups
Resilience	Change in psychological resilience measured using the Connor-Davidson Resilience Scale (CD-RISC 10), with total scores ranging from 0 from 4. Higher scores indicate a higher level of psychological resilience.	Baseline, 1-month and 3-month follow-ups
Social support	Change in social connectedness and support measured using the Lubben Social Network Scale-Revised (LSNS-R), with total scores ranging from 0 to 60. Higher scores indicate a larger and more robust social network.	Baseline, 1-month and 3-month follow-ups
Depressive symptoms	Change in depressive symptoms measured using the Patient Health Questionnaire-2 (PHQ-2) with total scores ranging from 0 to 6. Higher scores indicate a greater likelihood of depressive symptoms.	Baseline, 1-month and 3-month follow-ups
Loneliness	Change in loneliness using the Three-Item Loneliness Scale, with total scores ranging from 3 to 9. Higher scores indicate a greater perception of loneliness.	Baseline, 1-month and 3-month follow-ups
Physical activity	Change in physical activity levels measured using the Physical Activity Scale for the Elderly (PASE).	Baseline, 1-month and 3-month follow-ups
Instrumental Activities of Daily Living	Change in functional ability measured using Lawton Instrumental Activities of Daily Living (IADL), with total scores ranging from 0-16. Higher scores indicate greater functional independence.	Baseline, 1-month and 3-month follow-ups
Activities of Daily Living	Change in functional ability measured using Katz Index of Independence in Activities of Daily Living (ADL), with total scores ranging from 0-12. Higher scores indicate greater functional independence.	Baseline, 1-month and 3-month follow-ups

Collaborators and Investigators

• Sponsor: Duke-NUS Graduate Medical School
• Collaborators: Changi General Hospital; Agency for Integrated Care, Singapore
• Investigators: Principal Investigator: Angelique Chan, Ph.D., Duke-NUS Graduate Medical School

Publications and helpful links

General Publications

• Chong JL, Low LL, Chan DYL, Shen Y, Thin TN, Ong MEH, Matchar DB. Can we understand population healthcare needs using electronic medical records? Singapore Med J. 2019 Sep;60(9):446-453. doi: 10.11622/smedj.2019012. Epub 2019 Jan 15.
• Chong JL, Matchar DB. Benefits of Population Segmentation Analysis for Developing Health Policy to Promote Patient-Centred Care. Ann Acad Med Singap. 2017 Jul;46(7):287-289. No abstract available.
• Chong JL, Low LL, Matchar DB, Malhotra R, Lee KH, Thumboo J, Chan AW. Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community. BMC Geriatr. 2020 Feb 27;20(1):78. doi: 10.1186/s12877-020-1480-9.
• Matchar D, Vashishtha R, Jing X, Sivapragasam N, Sim R, Chong JL. Development and validation of a brief assessment of normative health and health-related social needs using the Simple Segmentation Tool. BMC Health Serv Res. 2025 Feb 11;25(1):230. doi: 10.1186/s12913-025-12364-x.
• Chong JL, Matchar DB, Tan Y, Sri Kumaran S, Gandhi M, Ong MEH, Wong KS. Population Segmentation Based on Healthcare Needs: Validation of a Brief Clinician-Administered Tool. J Gen Intern Med. 2021 Jan;36(1):9-16. doi: 10.1007/s11606-020-05962-4. Epub 2020 Jun 30.

Study record dates

Study Major Dates

• Study Start (Estimated): May 1, 2026
• Primary Completion (Estimated): December 30, 2026
• Study Completion (Estimated): December 30, 2027

Study Registration Dates

• First Submitted: April 14, 2026
• First Submitted That Met QC Criteria: May 5, 2026
• First Posted (Actual): May 12, 2026

Study Record Updates

• Last Update Posted (Actual): May 12, 2026
• Last Update Submitted That Met QC Criteria: May 5, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: Integrated Care; Care Coordination; Frail Older Adults; Simple Segmentation Tool; Needs Assessment Tool; Health and Health-related Social Service
• Other Study ID Numbers: CIRB: 2024-2130; MOH-001199-00 (Other Grant/Funding Number: National Research Foundation (NRF), Singapore)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No