Clinical trial NCT02815462: Impact of Implementing a Real Time Frequent Admitter Risk Score (FAM-FACE-SG) on Readmission Rates
Official title: Impact of Implementing a Real Time Frequent Admitter Risk Score (FAM-FACE-SG) on Readmission Rates: a Pragmatic Cluster Randomised Controlled Trial (RCT).
Study type: INTERVENTIONAL
Overall status: WITHDRAWN
Phase: NA
Conditions: Patient Readmission
Keywords: Frequent hospital admissions
Risk stratification
Readmissions
Lead sponsor: Singapore General Hospital
Sponsor class: OTHER
First posted: 2016-06-28
Enrollment: 0
Sex: ALL
Minimum age (years): 21
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: 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: 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.

Eligibility criteria: 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

Primary outcomes:
measure: 90-day readmission rate
timeFrame: 90 days
Secondary outcomes:
measure: 30-day readmission rate
timeFrame: 30 days
measure: 30-day ED attendance rate
timeFrame: 30 days
measure: 90-day ED attendance rate
timeFrame: 90 days
measure: index hospital admission length of stay
timeFrame: 90 days
measure: cumulative length of stay 90 days after index hospital discharge
timeFrame: 90 days
measure: Fidelity of the PNs in following the protocol in recruiting patients according the score priority
timeFrame: 90 days
measure: Proportion of high and medium risk patients recruited in both intervention and control groups
timeFrame: 90 days
measure: Referral rate of the PNs to various transitional care services
timeFrame: 90 days
measure: Qualitative feedback from PNs on the perceived benefits and behaviour change after receiving the scores
timeFrame: 1 year
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: Singapore General Hospital
Study officials:
affiliation: Singapore General Hospital
name: Lian Leng Low
role: PRINCIPAL_INVESTIGATOR
References:
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citation: 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.
citation: 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.
citation: 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.