Data Analysis
At Heorfy Consulting, we are aware of the importance of handling information rigorously, from data collection and coding to analysis. We are sure that it is the only way to get the best evidence achievable of your project. To ensure this, our work follow the well-known reporting guidelines for main study types, such as the CONSORT for randomized trials or the STROBE for observational studies, and the recommendations from the joint ISPOR‐ISPE Special Task Force on real‐world evidence in health care decision making.
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At Heorfy Consulting, we are experts in applying advanced statistical methods and machine learning algorithms to primary and secondary healthcare data.
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At Heorfy Consulting, we are skilled in a whole variety of statistical methods, such as standard descriptive analysis, multivariate techniques, multivariable regression models suited for any type of data and underlying mechanism of observation, and meta-analysis. Advanced methods of survival analysis and longitudinal outcomes are at the core of our expertise.
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Healthcare industry is taking steps into using machine learning in clinical trials. The value of this data depends on the transparency of algorithms, robustness of data, and extrapolation to real-world [ref]. At Heorfy Consulting, we are familiar with standard and novel machine learning algorithms, including bagging and boosting methods.
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Given that machine learning in healthcare research can have a direct impact on people’s lives, claims emerging from this kind of research should be done with the same rigor as clinical trials [ref]. At Heorfy Consulting, we are aware of the importance of being critical of the data (what do these data reflect) and metrics used to evaluate the performance of the models obtained.
