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Patient Reported Outcome Measures

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Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning.

Journal of surgical oncology
In this review, we aim to assess the current state of science in relation to the integration of patient-generated health data (PGHD) and patient-reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We wil...

From protocolized to person-centered chronic care in general practice: study protocol of an action-based research project (COPILOT).

Primary health care research & development
AIM: To develop a proactive person-centered care approach for persons with (multiple) chronic diseases in general practice, and to explore the impact on 'Quadruple aims': experiences of patients and professionals, patient outcomes and costs of resour...

Stakeholders' Perspectives on Medication Adherence Enhancing Interventions.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
With an approximately 50% prevalence rate, medication nonadherence is a significant healthcare challenge that increases the risk of potentially avoidable adverse events and associated costs ranging from $949 to $44 190 per person annually. The ISPOR ...

Exploring the Potential of Non-Proprietary Language Models for Analysing Patient-Reported Experiences.

Studies in health technology and informatics
Large language models (LLMs) are increasingly being explored for various applications in medical language processing. Due to data privacy issues, it is recommended to apply non-proprietary models that can be run locally. Therefore, this study aims to...

Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.

Japan journal of nursing science : JJNS
AIM: Patient-reported outcome measures (PROMs) are increasingly used in palliative care to evaluate patients' symptoms and conditions. Healthcare providers often collect PROMs through conversations. However, the manual entry of these data into electr...

Integrating Clinical Data and Patient-Reported Outcomes for Analyzing Gender Differences and Progression in Multiple Sclerosis Using Machine Learning.

Studies in health technology and informatics
Multiple sclerosis (MS) is a complex neurodegenerative disease with a variable prognosis that complicates effective management and treatment. This study leverages machine learning (ML) to enhance the understanding of disease progression and uncover g...

Machine Learning-Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer.

JCO clinical cancer informatics
PURPOSE: Palliative care is recommended for patients with cancer with a life expectancy of <12 months. Machine learning (ML) techniques can help in predicting survival outcomes among patients with cancer and may help distinguish who benefits the most...

Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.

JCO clinical cancer informatics
PURPOSE: Adverse effects of chemotherapy often require hospital admissions or treatment management. Identifying factors contributing to unplanned hospital utilization may improve health care quality and patients' well-being. This study aimed to asses...

Patient-Reported Outcomes for Robot-Assisted Laparoscopic Extravascular Renal Vein Stent Placements for Nutcracker Syndrome.

Journal of endourology
Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric artery (SMA) and the abdominal aorta. Nutcracker syndrome refers to the presence of nutcracker phenomenon with symptoms. Between 2016 and 2022, we perfor...