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Patient Reported Outcome Measures

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A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme.

The journal of prevention of Alzheimer's disease
BACKGROUND: It is important to use outcome measures for novel interventions in Alzheimer's disease (AD) that capture the research participants' views of effectiveness. The electronic Person-Specific Outcome Measure (ePSOM) development programme is un...

Predicting Disease-Free Lung Cancer Survival Using Patient Reported Outcome (PRO) Measurements with Comparisons of Five Machine Learning Techniques (MLT).

Studies in health technology and informatics
The study was to develop the lung cancer patients' prediction model for predicting 5-year survival after completion of treatment by using Machine Learning Technology (MLT), adding patient reporting (PRO) measurements of lung cancer survivors to a var...

Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Clinical orthopaedics and related research
BACKGROUND: Identifying patients at risk of not achieving meaningful gains in long-term postsurgical patient-reported outcome measures (PROMs) is important for improving patient monitoring and facilitating presurgical decision support. Machine learni...

Real World Patient-reported Outcomes in HIV-infected Adults Switching to EVIPLERA®, Because of a Previous Intolerance to cART. PRO-STR Study.

Current HIV research
BACKGROUND: To investigate the impact of switching from stable Combined Antiretroviral Therapy (cART) to single-tablet regimen (RPV/FTC/TDF=EVIPLERA® /COMPLERA®) on patient- reported outcomes in HIV-infected adults who cannot tolerate previous cART, ...

Making Sense of Patient-Generated Health Data for Interpretable Patient-Centered Care: The Transition from "More" to "Better".

Studies in health technology and informatics
The rise of health consumers and the accumulation of patient-generated health data (PGHD) have brought the patient to the centerstage of precision health and behavioral science. In this positional paper we outline an interpretability-aware framework ...