A natural experiment often occurs spontaneously without the intervention of the researcher, in which case, participants randomly enter into either the control group of the treatment group. On the other hand, quasi-experimental research designs often have subjective criterions based on the researcher’s selection. In this regard, there is no random allocation to the control and treatment groups. Typically, both examine phenomena causes; nevertheless, true experiments influence the phenomena by controlling its significant factors as the preferred design. Contrarily, since it is inherently impossible to control all major aspects, quasi-experimental designs are essential while implementing a research design.
The title for the research article is, “A Quantitative Observational Study of Physician Influence on Hospital Costs.” The authors are Herbert Wong, Ph.D., Zeynal Karaca, Ph.D., and Teresa B. Gibson, Ph.D., and its purpose is the determination of hospital costs variability across physicians and physicians attributes.
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The methodology of the study was a randomized experimental condition with control groups having similar probabilities of receiving both the control as well as intervention condition. Subsequently, the instruments used in data extrapolation were propensity score matching and regression analysis.
The independent variable was the observable provider characteristics, while the dependent ones were clinical risks, patient demographics, hospital characteristics, and socioeconomic characteristics.
The measurement tools in the research study were quite valid. Since the purpose of regression analysis is the prediction of behavior based on historical information, the study’s use of this tool enabled scholarly prediction of the behavior of the dependent variables, based on the independent one; that is, how physician characteristics influence hospital costs characteristics (dependent variables).
Essentially, replication studies often attempt to verify the validity of prior research findings. In this regard, prior research often materializes as being both applicable and accurate. Since replication studies often alter one or more variables such as sector of industry and sample population among others, this research is highly replicable.
