Pharmaceutical Innovation and its Implications for Nursing, Medical Records, and Diagnostics Practice | ||||
| The Medical Journal of Cairo University | ||||
| Volume 89, December, December 2021, Page 3175-3183 PDF (409.71 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjcu.2021.371109 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| DOAA ALI ALYAMI, MUBARAK SAUD ALANAZI, REHAM MOHAMMAD ALSOULAIMI,NOOR FAHAD ALSHURAIM, NOURA ABDULLAH ALKHARJI , NORA MOHAMMED ALDOSARY , WEJDAN AMEIN ABDULLAH, JEHAN KHELAIF ALANAZI,; Asma Saad Al-Qahtani, WAEL IBRAHIM AL GHANIM , JUMANA SAUD ALGHAMDI , MARIAM ADNAN ALKHADRAWI AFAF SNITAN AL- OTAIBI, NAHID AHMAD LAMFON,JEHAD HASSAN ALSHAIKH , ABDULLAH ALHUMAIDI ALHARBI | ||||
| K | ||||
| Abstract | ||||
| Background: Patient-generated health data (PGHD) refers to health-related information collected directly from patients to address health issues. In the field of cancer, PGHD is increas-ingly utilized to inform regulatory decisions and assess treat-ment quality. This data includes self-reported health and treat-ment records, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, mobile devices, and the Internet of Things have facilitated the collection of PGHD both during clinical visits and in everyday life. Regula-tory and scientific entities, including the US Food and Drug Administration and the Institute of Medicine, have recognized the importance of PGHD. Aim of Work: The objective of this study is to provide a comprehensive summary of the clinical, regulatory, technical, and analytic aspects of PGHD in cancer research and health-care. The study aims to evaluate the evidence supporting the use of PGHD for monitoring symptoms, with a particular focus on patient-reported outcomes (PROs). Methods: The assessment includes a review of existing literature and frameworks surrounding PGHD. It discusses the current methods for digital phenotyping, which involves the re-al-time collection and analysis of biometric, behavioral, self-re-port, and performance data using electronic devices. Addition-ally, the study explores the analytical potential of PGHD within the context of big data and artificial intelligence in medicine. Results: The findings highlight the benefits of integrating PGHD into clinical treatment, including improved symptom monitoring and enhanced patient engagement. However, chal-lenges remain in integrating PROs and biometric data into elec-tronic medical records, analyzing complex biometric datasets, and redesigning clinical workflows. The evidence supporting the use of biometric data is currently more limited compared to that of PROs. Conclusion: Despite the existing difficulties, the potential advantages of PGHD suggest that it is likely to be increasingly incorporated into cancer research and clinical treatment. The study emphasizes the need for continued exploration of solu-tions to overcome the challenges associated with PGHD inte-gration | ||||
| Keywords | ||||
| Patient-Generated Health Data (PGHD); Patient- Reported Outcomes (PROs); Digital Phenotyping Cancer Research; Big Data and Artificial Intel- ligence | ||||
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