AIMC Topic: Patient Reported Outcome Measures

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Psychometric Properties of a Machine Learning-Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study.

Journal of medical Internet research
BACKGROUND: Medication adherence plays a critical role in controlling the evolution of chronic disease, as low medication adherence may lead to worse health outcomes, higher mortality, and morbidity. Assessment of their patients' medication adherence...

Patient-reported outcome measures compared to clinician reported outcomes regarding incontinence and erectile dysfunction in localized prostate carcinoma after robot assisted radical prostatectomy: Impact on management.

Urologic oncology
PURPOSE/ BACKGROUND: Patient-reported outcome measures (PROMs) are widely used after robot assisted radical prostatectomy (RARP) in order to evaluate the impact/burden of the treatment. The most bothersome side effects of RARP are urine incontinence ...

Surgical outcomes and patient-centred perioperative programs.

Journal of clinical monitoring and computing
Perioperative medicine is changing, and its goals are expanding. More and more attention is paid to the surgical experience and the patient's quality of life. Patient-reported data represent a useful tool in this context. Patient-reported outcomes me...

Population-Based Applications and Analytics Using Patient-Reported Outcome Measures.

The Journal of the American Academy of Orthopaedic Surgeons
The intersection of big data and artificial intelligence (AI) has resulted in advances in numerous areas, including machine learning, computer vision, and natural language processing. Although there are many potentially transformative applications of...

An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.

JAMA network open
IMPORTANCE: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups.

State-of-the-art Applications of Patient-Reported Outcome Measures in Spinal Care.

The Journal of the American Academy of Orthopaedic Surgeons
Patient-reported outcome measures (PROMs) assign objective measures to patient's subjective experiences of health, pain, disability, function, and quality of life. PROMs can be useful for providers in shared decision making, outcome assessment, and i...

Exactech Equinoxe anatomic versus reverse total shoulder arthroplasty for primary osteoarthritis: case controlled comparisons using the machine learning-derived Shoulder Arthroplasty Smart score.

Journal of shoulder and elbow surgery
BACKGROUND: The role of reverse total shoulder arthroplasty (rTSA) for glenohumeral osteoarthritis (GHOA) with an intact rotator cuff remains unclear with prior investigations demonstrating similar patient-reported outcome measures (PROMs) to anatomi...

Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM).

BMC medical informatics and decision making
BACKGROUND: Evaluating patients' experiences is essential when incorporating the patients' perspective in improving healthcare. Experiences are mainly collected using closed-ended questions, although the value of open-ended questions is widely recogn...

Predicting Patient-Reported Outcomes Following Surgery Using Machine Learning.

The American surgeon
Patient-reported outcomes (PROs) enable providers to identify differences in treatment effectiveness, postoperative recovery, quality of life, and patient satisfaction. By allowing a shift from disease-specific factors to the patient perspective, PRO...