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| Name | Class |
|---|---|
| Philips Healthcare | INDUSTRY |
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This study is being done to evaluate the impact of a system called CareSage. The CareSage system is a technology that uses clinical data to monitor, identify and target care to patients at risk of being transported to the hospital. The investigators want to see whether the CareSage system is effective in helping to identify hospital admissions which can be prevented.
The growing elderly population and rising rates of costly chronic disease have led to the development of preventative homecare management opportunities to improve health outcomes and reduce the number of patients who enter costly inpatient care. Partners HealthCare at Home (PHH) is a preventative homecare management system which offers general care as well as specialized services to help patients and their loved ones manage chronic conditions at home. Such continuity of care is achieved through a multidisciplinary clinical team and the integration of telemonitoring into the patient's care plan.
The Philips Lifeline Personal Emergency Response Service (PERS), a wearable button device worn on the wrist or as a pendant, is a telemonitoring device available to patients receiving care through PHH. When the patient presses the button, the patient is immediately connected with a Lifeline response agent. Philips Lifeline (PLL) has developed CareSage, a predictive analytics engine that combines continuous monitoring with predictive analytics. The clinical interface (CareSage platform) helps care teams monitor the patient's calculated risk scores for emergency transport. The algorithm used by this integrated risk assessment system was originally developed after studying a large cohort of the PERS subscribers (N = ~600,000). In Phase 1 of this study the algorithm was validated among a cohort (N = 3,335) of PHH patients to predict emergency transports in this population (AUC = .76).
In Phase 2 of this study, the investigators will conduct a prospective, randomized trial of 370 patients to assess the effect of the risk assessment CareSage platform and PHH tailored interventions on the rate of readmissions, quality of life, and the overall cost of medical care. The investigators hypothesize that a multidisciplinary intervention approach could significantly reduce the healthcare resource utilization in patient at high risk for hospitalization. The intervention will flag those patients at the highest risk for hospital transport, alert the patient's care team that an intervention may be needed, thereby targeting care at high risk patients who are most likely to get readmitted. By predicting which patients are at high risk of hospital transport which may lead to hospitalization, targeting interventions at those patients and engaging patients with their care team, the investigators hope to reduce readmissions, hospital days, and rates of mortality in high risk patients.
The goal of this 2-arm randomized controlled study is to assess the impact of the CareSage risk assessment platform on 90- and 180-day Emergency Department (ED) visits in a cohort of PHH patients. All patients will receive the PERS device and be followed for a total of 9 months, including an initial 3-month observation period and followed by a 6-month intervention period. At the beginning of the observation period (baseline), enrolled patients will be randomized into 2 groups: the Intervention Group or the Control Group. During the observation period the CareSage algorithm will calibrate using patient data (both groups) collected during this interval from the PERS device. Then, during the intervention period, patients in the intervention group will be actively monitored by the CareSage algorithm and will receive tailored PHH interventions if flagged as being at high risk for emergency transport. Patients in the control group will receive care as usual during the intervention period. All data collected during the study will be used to further strengthen the CareSage algorithm developed in the Phase I of this study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group A | Experimental | This group will include a cohort of 185 participants who will be monitored by the CareSage risk assessment platform. Tailored interventions, using a Stepped-Care Approach, will be targeted to patients flagged as high risk for emergency transport during the 6-month intervention period. |
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| Group B | No Intervention | This group will include a cohort of 185 participants where study staff will not see if patients are flagged by the CareSage risk assessment platform as being at high or low risk for emergency transport during the 6-month intervention period. Patients will continue to receive care as usual. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Lifeline CareSage Flagging | Other | Patients in the intervention group will receive active monitoring by the CareSage risk assessment platform and clinical interface, including nurse triage calls and tailored PHH interventions. Beginning at month 4, the CareSage algorithm will assess patients' risk for emergency transport every 30 days. Patients identified as high risk will receive nurse triage calls and, depending on their needs, tailored care according to a stepped-care approach. The principal goals will be to reinforce the patients' education, ensure compliance with medications and diet, and identify recurrent symptoms amenable to treatment on an outpatient basis to avoid readmissions |
| Measure | Description | Time Frame |
|---|---|---|
| Number of participants who visit the emergency department 90 and 180 days after the three month observational period and assessed by reviewing the medical records | To assess the impact of the CareSage risk assessment platform and tailored PHH intervention on the 90- and 180- day ED visits. | 9 months after study enrollment |
| Measure | Description | Time Frame |
|---|---|---|
| Emergency Transport use | Patient usage of emergency transport | 9 months after study enrollment |
| 30-, 90- and 180- day readmissions | Data pertaining to the 30-day readmissions will be collected in the intervention period (6 months). |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Kamal Jethwani, MD, MPH | Massachusetts General Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Partners Healthcare at Home | Waltham | Massachusetts | 02451 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29743156 | Derived | Palacholla RS, Fischer NC, Agboola S, Nikolova-Simons M, Odametey S, Golas SB, Op den Buijs J, Schertzer L, Kvedar J, Jethwani K. Evaluating the Impact of a Web-Based Risk Assessment System (CareSage) and Tailored Interventions on Health Care Utilization: Protocol for a Randomized Controlled Trial. JMIR Res Protoc. 2018 May 9;7(5):e10045. doi: 10.2196/10045. |
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| 9 months after study enrollment |
| Total number of avoidable hospital admissions using Center for Medicare and Medicaid Services (CMS) criteria | Total number of avoidable hospital admissions | 9 months after study enrollment |
| Total medical expenses attributable to the avoidable admissions | Total medical expenses attributable to the avoidable admissions | 9 months after study enrollment |
| Mortality rates | Patient deaths | 9 months after study enrollment |
| Time to readmission | Length of time before patient was readmitted. | 9 months after study enrollment |
| Patient quality of life | This outcome will be assessed using a validated questionnaire- Short-form 12 version 2 (SF-12v2) | 9 months after study enrollment |
| Patient satisfaction with the service | Patient and provider satisfaction with the service will be evaluated using a Satisfaction survey designed specifically for this study | 9 months after study enrollment |
| Patient leakage | Number of patients who have been admitted to hospitals outside of the Partners network will be assessed by patient self-disclosure at close-out | 9 months after study enrollment |
| PLL switch rate from No to Yes-Payment at the end of the study. | The PLL switch rate from No to Yes-Payment will be evaluated at the end of the study by using the billing accounts from Phillips | 9 months after study enrollment |
| Total number of hospital admissions assessed by reviewing the medical record | Total number of hospital admissions for participants | 9 months after study enrollment |