ISSN: 2165-7386

Journal of Palliative Care & Medicine
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  • Commentary   
  • J Palliat Care Med 14: 720,
  • DOI: 10.4172/2165-7386.1000720

Strengthening Quality Metrics for Palliative Care Studies

Josh Passel*
Department of Palliative Medicine and Supportive Care, Kasturba Medical College, India
*Corresponding Author : Josh Passel, Department of Palliative Medicine and Supportive Care, Kasturba Medical College, India, Email: joshpassel@gmail.com

Received Date: Dec 02, 2024 / Published Date: Dec 30, 2024

Abstract

Palliative care plays a vital role in enhancing the quality of life for patients with serious illnesses, yet the lack of standardized and robust quality metrics has hindered the consistent evaluation of care outcomes. Strengthening quality metrics for palliative care studies is essential to better assess the effectiveness of interventions, guide clinical decision-making, and ensure patient-centered care. This paper explores current gaps in quality metrics, emphasizing the need for multidimensional tools that measure not only physical symptoms but also emotional, social, and spiritual well-being. It highlights the importance of patient-reported outcomes (PROs) and the integration of emerging technologies, such as digital health tools and artificial intelligence, to capture real-time, individualized data. Additionally, the paper discusses the challenges of balancing standardized metrics with the personalization required in palliative care and addresses the ethical considerations related to data collection and patient privacy. By strengthening and refining quality metrics, this research aims to improve the overall delivery of palliative care, ensuring that patient experiences and outcomes are accurately reflected and optimized across diverse healthcare settings.

Citation: Josh P (2024) Strengthening Quality Metrics for Palliative Care Studies. J Palliat Care Med 14: 720 Doi: 10.4172/2165-7386.1000720

Copyright: © 2024 Josh P. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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