Impact of Implementing a Real Time Frequent Admitter Risk Score (FAM-FACE-SG) on Readmission Rates

NCT ID: NCT02815462

Last Updated: 2023-04-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

WITHDRAWN

Clinical Phase

NA

Study Classification

INTERVENTIONAL

Study Start Date

2016-08-31

Study Completion Date

2017-08-31

Brief Summary

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In an earlier study using electronic health records (EHR), the investigators have identified nine factors to be significantly associated with FA risk. These nine predictors include Furosemide intravenous 40 milligrams or more; Admissions in the past one year; Medifund status; Frequent emergency department use; Anti-depressants treatment in past one year; Charlson comorbidity index; End Stage Renal Failure on dialysis; Subsidized ward stay and Geriatric patient. The investigators have combined these nine predictors into the FAM-FACE-SG score for FA risk (defined as 3 or more inpatient admissions in the following 12 months). The FAM-FACE-SG risk score has the advantage of being deployed in our hospital's enterprise data repository known as Electronic Health Intelligence System or eHINTs for short, on a real-time or near real-time basis. On a daily basis, data from multiple data sources are extracted, transformed and loaded onto the eHINTS system. The system can be programmed to run every midnight to provide risk scores the following morning for patients admitted the previous day.

In this trial, the intervention is to combine the FAM-FACE-SG risk score in addition to a decision making algorithm to guide referrals to various transitional care services based on needs assessment on nursing and function. The primary objective is to evaluate the impact of our intervention in improving healthcare utilization (hospital readmissions, emergency department (ED) attendances, length of stay up to 90 days post-discharge).

Detailed Description

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In an earlier study using electronic health records (EHR), The investigators have identified nine factors to be significantly associated with FA risk. These nine predictors include Furosemide intravenous 40 milligrams or more; Admissions in the past one year; Medifund status; Frequent emergency department use; Anti-depressants treatment in past one year; Charlson comorbidity index; End Stage Renal Failure on dialysis; Subsidized ward stay and Geriatric patient. The investigators have combined these nine predictors into the FAM-FACE-SG score for FA risk (defined as 3 or more inpatient admissions in the following 12 months). The FAM-FACE-SG risk score has the advantage of being deployed in our hospital's enterprise data repository known as Electronic Health Intelligence System or eHINTs for short, on a real-time or near real-time basis. On a daily basis, data from multiple data sources are extracted, transformed and loaded onto the eHINTS system. The system can be programmed to run every midnight to provide risk scores the following morning for patients admitted the previous day.

In this trial, the intervention is to combine the FAM-FACE-SG risk score in addition to a decision making algorithm to guide referrals to various transitional care services based on needs assessment on nursing and function. The primary objective is to evaluate the impact of our intervention in improving healthcare utilization (hospital readmissions, emergency department (ED) attendances, length of stay up to 90 days post-discharge).

The aims of this cluster RCT are to: (1) evaluate the impact of implementing the FAM-FACE-SG risk score in addition to a decision making algorithm to guide Patient Navigator (PN) referrals to various transitional care services based on needs assessment on nursing and function on improving healthcare utilization (hospital readmissions, emergency department (ED) attendances, length of stay up to 90 days post-discharge); (2) measure the implementation of the risk score (Fidelity of the PNs in adhering to the protocol in recruiting patients according the score priority; Referral rate of the PNs to various transitional care services; Qualitative feedback from PNs on the perceived benefits and behavior change after receiving the scores); (3) conduct an economic analysis of the cost-benefit of implementing the risk score.

Conditions

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Patient Readmission

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

NONE

Study Groups

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Intervention

FAM-FACE-SG risk score + decision making algorithm

Group Type EXPERIMENTAL

FAMFACESG

Intervention Type OTHER

\- PNs will receive the FAM-FACE-SG FA risk scores for frequent admitters admitted to their ward.

FAMFACESG

Intervention Type OTHER

\- PNs will be instructed to prioritize intervention of frequent admitters for intervention based on the FA risk score.

FAMFACESG

Intervention Type OTHER

* For high and moderate risk patients who do not require transitional home care (THC), PN will do the case management and follow up.
* For high and moderate risk patients \& have complex nursing and / or high functional needs, PNs will refer these patients for THC.
* For mild risk patients, PNs will refer them to care coordinator.

FAMFACESG

Intervention Type OTHER

\- For low risk patients, PNs will continue usual hospital care.

Control

Usual Care

Group Type ACTIVE_COMPARATOR

Control

Intervention Type OTHER

\- Usual hospital Care

Interventions

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FAMFACESG

\- PNs will receive the FAM-FACE-SG FA risk scores for frequent admitters admitted to their ward.

Intervention Type OTHER

Control

\- Usual hospital Care

Intervention Type OTHER

FAMFACESG

\- PNs will be instructed to prioritize intervention of frequent admitters for intervention based on the FA risk score.

Intervention Type OTHER

FAMFACESG

* For high and moderate risk patients who do not require transitional home care (THC), PN will do the case management and follow up.
* For high and moderate risk patients \& have complex nursing and / or high functional needs, PNs will refer these patients for THC.
* For mild risk patients, PNs will refer them to care coordinator.

Intervention Type OTHER

FAMFACESG

\- For low risk patients, PNs will continue usual hospital care.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Singapore General Hospital wards with patient navigators
* Patients who are frequent admitters (defined as 3 or more hospital admissions in the preceding 12 months)

Exclusion Criteria

* Haematology, Oncology, Emergency department, obstetrics and neonatology wards
Minimum Eligible Age

21 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Singapore General Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Lian Leng Low

Role: PRINCIPAL_INVESTIGATOR

Singapore General Hospital

Locations

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Singapore General Hospital

Singapore, , Singapore

Site Status

Countries

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Singapore

References

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Kripalani S, Theobald CN, Anctil B, Vasilevskis EE. Reducing hospital readmission rates: current strategies and future directions. Annu Rev Med. 2014;65:471-85. doi: 10.1146/annurev-med-022613-090415. Epub 2013 Oct 21.

Reference Type BACKGROUND
PMID: 24160939 (View on PubMed)

Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009 Apr 2;360(14):1418-28. doi: 10.1056/NEJMsa0803563.

Reference Type RESULT
PMID: 19339721 (View on PubMed)

Robst J. Developing Models to Predict Persistent High-Cost Cases in Florida Medicaid. Popul Health Manag. 2015 Dec;18(6):467-76. doi: 10.1089/pop.2014.0174. Epub 2015 Jun 23.

Reference Type RESULT
PMID: 26102363 (View on PubMed)

Longman JM, I Rolfe M, Passey MD, Heathcote KE, Ewald DP, Dunn T, Barclay LM, Morgan GG. Frequent hospital admission of older people with chronic disease: a cross-sectional survey with telephone follow-up and data linkage. BMC Health Serv Res. 2012 Oct 30;12:373. doi: 10.1186/1472-6963-12-373.

Reference Type RESULT
PMID: 23110342 (View on PubMed)

Low LL, Vasanwala FF, Ng LB, Chen C, Lee KH, Tan SY. Effectiveness of a transitional home care program in reducing acute hospital utilization: a quasi-experimental study. BMC Health Serv Res. 2015 Mar 14;15:100. doi: 10.1186/s12913-015-0750-2.

Reference Type RESULT
PMID: 25888830 (View on PubMed)

Other Identifiers

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SGH_OIC_FAMFACESG/5/2016

Identifier Type: -

Identifier Source: org_study_id

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