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INTRODUCTION: Neurofibromatosis Type 1 (NF1) is an autosomal dominant genetic condition in which chronic pain is a predominant issue. Given the rarity of the disease, there are limited psychosocial treatments for individuals with NF1 suffering with chronic pain. Using mobile applications can facilitate psychosocial treatments; however, there are consistent issues with engagement. Utilizing a mixed methodology, the current study evaluated the customized iCanCope mobile application for NF1 on increasing engagement through the usage of contingency management. METHODS: A mixed methods study from a subset of data coming from a randomized clinical trial that occurred from January 2021 to August 2022 was undertaken. Two groups (iCC and iCC + CM) were exposed to the customized iCanCope mobile application in which engagement data were captured in real-time with daily check-ins for interference, sleep, mood, physical activity, energy levels, goal setting, and accessing article content (coping strategies). Additionally, semi-structured interviews were conducted to gain insight into the participants' experience at the end of the trial. RESULTS: Adults (N = 72) were recruited via NF patient advocacy groups. Significant differences were noted between the groups in total articles read (p = 0.002), goals achieved (p = 0.017), and goals created (p = 008). Additionally, there were significant differences observed between user-generated goals and those that were app recommended (p < 0.001). Both groups qualitatively reported positive feedback on the customized mobile application, indicating that continued usage and engagement of the mobile application were acceptable. CONCLUSIONS: Employing customized mobile applications for adults with NF1 along with contingency management can leverage self-managed pain treatments while providing auxiliary resources to this population.
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OBJECTIVE: We deployed a Remote Patient Monitoring (RPM) program to monitor patients with coronavirus disease 2019 (COVID-19) upon hospital discharge. We describe the patient characteristics, program characteristics, and clinical outcomes of patients in our RPM program. METHODS: We enrolled COVID-19 patients being discharged home from the hospital. Enrolled patients had an app, and were provided with a pulse oximeter and thermometer. Patients self-reported symptoms, O2 saturation, and temperature daily. Abnormal symptoms or vital signs were flagged and assessed by a pool of nurses. Descriptive statistics were used to describe patient and program characteristics. A mixed-effects logistic regression model was used to determine the odds of a combined endpoint of emergency department (ED) or hospital readmission. RESULTS: A total of 295 patients were referred for RPM from five participating hospitals, and 225 patients were enrolled. A majority of enrolled patients (66%) completed the monitoring period without triggering an abnormal alert. Enrollment was associated with a decreased odds of ED or hospital readmission (adjusted odds ratio: 0.54; 95% confidence interval: 0.3-0.97; p = 0.039). Referral without enrollment was not associated with a reduced odds of ED or hospital readmission. CONCLUSION: RPM for COVID-19 provides a mechanism to monitor patients in their home environment and reduce hospital utilization. Our work suggests that RPM reduces readmissions for patients with COVID-19 and provides scalable remote monitoring capabilities upon hospital discharge. RPM for postdischarge patients with COVID-19 was associated with a decreased risk of readmission to the ED or hospital, and provided a scalable mechanism to monitor patients in their home environment.