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Quantitative challenges facing patient-centered outcomes research

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Abstract

Patient-centered outcomes research collects and analyzes data from patients and other stakeholders to improve health care delivery and outcomes and guide health care decisions. However, there are a number of challenges in conducting quantitative analyses of patient-centered data. This article provides an overview of the analytical challenges and describes approaches to consider to overcome the challenges, as well as directions for future development.

Financial & competing interests disclosure

All authors are employees of RTI health solutions. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Key issues

  • Healthcare policies, treatment decisions and regulatory reviews have increased awareness regarding the collection of data about health outcomes that matter most to patients and their caregivers.

  • Patient-centered outcomes research is essential for incorporating the patient perspective. This area of research faces many quantitative challenges in data analysis including multidimensionality, multiplicity, sample size, missing data, interpretability and clinical relevance, and translation and comparability. In addition to the challenges that each of these issues brings, each are inter-related and may be more acute in patients with severe disease burden or with a rare disease.

  • Guidance and quantitative tools have been developed for patient-centered outcomes instrument development and evaluation to help address and overcome these challenges. This article examines several of the quantitative challenges and describes approaches to consider for overcoming the challenges, as well as directions for future development.

  • It is important to consider these challenges and address the potential problems related to patient-centered outcomes measures to ensure the final results are valid, meaningful and informative for healthcare decisions and outcomes that are most important to the patients.

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