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Patient Interaction Phenotypes With an Automated SMS Text Message–Based Program and Use of Acute Health Care Resources After Hospital Discharge: Observational Study

Patient Interaction Phenotypes With an Automated SMS Text Message–Based Program and Use of Acute Health Care Resources After Hospital Discharge: Observational Study

Patients eligible for the original study were adults (aged 18 y or older) who received care in 30 primary care practices within the University of Pennsylvania Health System; discharged to home from an acute care hospital; and identified as medium to high risk at the time of discharge (using an Epic Systems Corporation developed and validated point score based on clinical information presented in prior literature and generally available in the electronic health record [EHR]; see Multimedia Appendix 1 for further

Klea Profka, Agnes Wang, Emily Schriver, Ashley Batugo, Anna U Morgan, Danielle Mowery, Eric Bressman

J Med Internet Res 2025;27:e72875

A Resource-Efficient, High-Dose, Gamified Neurorehabilitation Program for Chronic Stroke at Home: Retrospective Real-World Analysis

A Resource-Efficient, High-Dose, Gamified Neurorehabilitation Program for Chronic Stroke at Home: Retrospective Real-World Analysis

Data from the 17 patients (8 women; mean age of 54.8 y, SD 14.1 y; time from first stroke episode: mean 5.4 y, SD 4.7 y; Table 1) who completed the training program and underwent both sets of clinical assessments were analyzed retrospectively. As this was a real-world clinical implementation, the sample size for analysis was limited by patient availability, clinical capacity to provide care, and the availability of clinical service data.

Spencer A Arbuckle, Anna Sophie Knill, Michelle H Chan-Cortés, Gabriela Rozanski, Anastasia Elena Ford, Louis T Derungs, John W Krakauer, Naveed Ejaz, David Putrino, Jenna Tosto-Mancuso, Meret Branscheidt

JMIR Serious Games 2025;13:e69335