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The overall goal of the project is to reduce pain-related, 30-day readmission rates for sickle cell disease (SCD) patients. The investigators want to see if a mobile phone application (app) can help decrease the need for repeat admission to the hospital because of sickle cell pain.
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Pain is the main reason why SCD patients are admitted and readmitted to the hospital. In fact, readmission rates of SCD patients are higher than those of asthmatics and diabetics. In order to reduce 30-day hospital readmission rates and improve patient care quality, the Affordable Care Act and Centers for Medicare and Medicaid Services have established the Readmissions Reduction Program. In keeping with this effort, the investigators propose a methodology and supporting technology that has the potential to change the way SCD patients are monitored after hospital discharge and in turn, decrease readmission rates. This methodology also has the potential to enhance the quality of life of SCD patients by improving patient reporting, self-efficacy, and increasing patient/provider engagement when there is worsening pain and increased admission/readmission risk. This software platform uses validated Patient Reported Outcome Measurement Information System (PROMIS) measures to remotely monitor SCD patients' pain and related outcomes after hospital discharge. With this initial study, the investigators propose to use this monitoring platform to identify the predictors of readmission, to develop a readmission prediction engine, and to design the next version of the app with built in interventions to address those readmission risks. This monitoring platform could also increase healthcare provider engagement when there is a worsening of patients' pain and/or an increased risk of readmission. In order to build and optimize this monitoring platform, the investigators have assembled a team of engineers, hematologists, pain researchers, and statisticians that have worked together, and who collectively have the expertise to develop and test the feasibility and predictive value of the application in a large population of SCD patients.
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150 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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