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Using Multifactorial Experiments for Comparative Effectiveness Research in Physician Practices with Electronic Health Record
Two key challenges related to conducting comparative effectiveness research are the lack of available data and the lack of rigorous techniques for efficiently and quickly testing the effectiveness of the many possible ways of implementing components of care. The confluence of two things offers the p...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AcademyHealth
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371450/ https://www.ncbi.nlm.nih.gov/pubmed/25848579 http://dx.doi.org/10.13063/2327-9214.1037 |
Sumario: | Two key challenges related to conducting comparative effectiveness research are the lack of available data and the lack of rigorous techniques for efficiently and quickly testing the effectiveness of the many possible ways of implementing components of care. The confluence of two things offers the promise of overcoming these challenges: (1) the increased adoption of electronic health records (EHRs), which can provide easier access to clinical information, and (2) burgeoning appreciation for an under-used but powerful statistical research and evaluation method for multifactor interventions known as multifactor experimental design. The use of multifactorial experiments paired with EHR data has great potential to help providers conduct rapid-cycle comparative effectiveness research and examine alternative ways of implementing care. Its power is its ability to enable scientifically rigorous testing of many facets of care provision simultaneously in real-world settings where change is ongoing. In this paper, we identify the opportunities for using efficient multifactorial designs and EHR data to evaluate quality-improvement efforts in physician practices. We illustrate the power of multifactorial designs through several examples relevant to physician practices with EHRs, such as evaluating clinical decision support features and studying components of a patient-centered medical home. |
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