Quantifying complexity in translational research: an integrated approach

Abstract

Purpose

The purpose of this paper is to quantify complexity in translational research. The impact of major operational steps and technical requirements is calculated with respect to their ability to accelerate moving new discoveries into clinical practice.

Design/methodology/approach

A three-phase integrated quality function deployment (QFD) and analytic hierarchy process (AHP) method was used to quantify complexity in translational research. A case study in obesity was used to usability.

Findings

Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, the authors found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice.

Research limitations/implications

As the method is mainly based on subjective opinion, some argue that the results may be biased. However, a consistency ratio is calculated and used as a guide to subjectivity. Alternatively, a larger sample may be incorporated to reduce bias.

Practical implications

The integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects.

Originality/value

Current conceptual models in translational research provide little or no clue to assess complexity. The proposed method aimed to fill this gap. Additionally, the literature review includes various features that have not been explored in translational research.

Citation

A. Munoz, D., Black Nembhard, H. and L. Kraschnewski, J. (2014), "Quantifying complexity in translational research: an integrated approach", International Journal of Health Care Quality Assurance, Vol. 27 No. 8, pp. 760-776. https://doi.org/10.1108/IJHCQA-01-2014-0002