Department of Quantitative Health Sciences

Our Goal: Your Research Success

The Department of Quantitative Health Sciences has expertise in all aspects of clinical research. From study design to statistical analysis to preparing funding applications, we will help you and your department achieve sound scientific results from your research project in a timely manner. Each year, we co-author hundreds of publications and receive millions of dollars in external funding. We have the knowledge and skills to partner with each Cleveland Clinic Institute.

Cleveland Clinic has its own team of biostatisticians, epidemiologists, outcomes researchers, database developers and programmers in the Department of Quantitative Health Sciences. Our pledge is to be better, faster, and/or less expensive than any research group that operates outside Cleveland Clinic. To find out more about how we can serve you, try our Skill Finder.

QHS: An Excellent Resource for You!

Here are just a few areas the department specializes in:

  • Clinical Trial Design
  • Biostatistics
  • Epidemiology
  • Statistical Genetics
  • Outcomes Research
  • Quality-of-life Assessment
  • Database Development

The Department is available to all Cleveland Clinic physicians, researchers, and support staff on a pay-as-you-go or dedicated-FTE fee basis. Do you need help training staff for an upcoming research project? We will teach your residents, fellows, medical students and support team about conducting clinical studies, efficient data collecting methods, and other important research skills.

Read more in our department brochure (PDF).


With comparative effectiveness of interventions increasingly coming into focus, and with the ongoing establishment of large, robust observational clinical data registries, methods for better understanding patient heterogeneity and variation in treatment response are continuing to be developed. In January’s issue of Medical Decision Making, Jarrod Dalton and colleagues present a technique for empirical modeling of treatment effectiveness for binary outcomes, demonstrating its use with observational data on percutaneous coronary intervention or coronary artery bypass grafting for coronary revascularization.


In the field of population pharmaco-kinetics/dynamics (PK/PD) inter-individual variability is represented by model parameter distributions. In this paper Radivoyevitch et al. compare stochastic process PD models that capture the probability of complete eradication of colony forming units (CFU) to standard deterministic PD models that track only average CFU numbers. For neonatal intravenous gentamicin dosing regimens directed against Escherichia coli, stochastic calculations predict that the first dose is crucial. For example, a single 6mg/kg dose is predicted to have a higher eradication probability than four daily 4mg/kg doses. Conclusion: regimens with larger first doses but smaller total doses deserve further investigation.

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