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Received Nov 19; Accepted Aug Abstract Quasi-experimental study designs, often described as nonrandomized, pre-post intervention studies, are common in the medical informatics literature. Yet little has been written about the benefits and limitations of the quasi-experimental approach as applied to informatics studies.
This paper outlines a relative hierarchy and nomenclature of quasi-experimental study designs that is applicable to medical informatics intervention studies. In addition, the authors performed a systematic review of two medical informatics journals, the Journal of the American Medical Informatics Association JAMIA and the International Journal of Medical Informatics IJMIto determine the number of quasi-experimental studies published and how the studies are classified on the above-mentioned relative hierarchy.
They hope that future medical informatics studies will implement higher level quasi-experimental study designs that yield more convincing evidence for causal links between medical informatics interventions and outcomes.
Background Quasi-experimental studies encompass a broad range of nonrandomized intervention studies. These designs are frequently used when it is not logistically feasible or ethical to conduct a randomized controlled trial.
Examples of quasi-experimental studies follow. As one example of a quasi-experimental study, a hospital introduces a new order-entry system and wishes to study the impact of this intervention on the number of medication-related adverse events before and after the intervention.
As another example, an informatics technology group is introducing a pharmacy order-entry system aimed at decreasing pharmacy costs.
The intervention is implemented and pharmacy costs before and after the intervention are measured. In medical informatics, the quasi-experimental, sometimes called the pre-post intervention, design often is used to evaluate the benefits of specific interventions.
The increasing capacity of health care institutions to collect routine clinical data has led to the growing use of quasi-experimental study designs in the field of medical informatics as well as in other medical disciplines. However, little is written about these study designs in the medical literature or in traditional epidemiology textbooks.
The example of a pharmacy order-entry system aimed at decreasing pharmacy costs will be used throughout this article to illustrate the different quasi-experimental designs.
We discuss limitations of quasi-experimental designs and offer methods to improve them. We also perform a systematic review of four years of publications from two informatics journals to determine the number of quasi-experimental studies, classify these studies into their application domains, determine whether the potential limitations of quasi-experimental studies were acknowledged by the authors, and place these studies into the above-mentioned relative hierarchy.
Methods The authors reviewed articles and book chapters on the design of quasi-experimental studies. The potential methodological flaws of quasi-experimental medical informatics studies, which have the potential to introduce bias, were also identified.
In addition, a summary table outlining a relative hierarchy and nomenclature of quasi-experimental study designs is described. In general, the higher the design is in the hierarchy, the greater the internal validity that the study traditionally possesses because the evidence of the potential causation between the intervention and the outcome is strengthened.
First, we determined the number of quasi-experimental studies. We then classified these studies on the above-mentioned hierarchy. We also classified the quasi-experimental studies according to their application domain. The categories of application domains employed were based on categorization used by Yearbooks of Medical Informatics — and were similar to the categories of application domains employed by Annual Symposiums of the American Medical Informatics Association.
Because the quasi-experimental study design has recognized limitations, we sought to determine whether authors acknowledged the potential limitations of this design.
Examples of acknowledgment included mention of lack of randomization, the potential for regression to the mean, the presence of temporal confounders and the mention of another design that would have more internal validity. One author ADH reviewed all the papers to identify the number of quasi-experimental studies.
The three authors then convened as a group to resolve any disagreements in study classification, application domain, and acknowledgment of limitations.
Results and Discussion What Is a Quasi-experiment? Quasi-experiments are studies that aim to evaluate interventions but that do not use randomization.
Similar to randomized trials, quasi-experiments aim to demonstrate causality between an intervention and an outcome. Quasi-experimental studies can use both preintervention and postintervention measurements as well as nonrandomly selected control groups.
Using this basic definition, it is evident that many published studies in medical informatics utilize the quasi-experimental design. Although the randomized controlled trial is generally considered to have the highest level of credibility with regard to assessing causality, in medical informatics, researchers often choose not to randomize the intervention for one or more reasons: Each of these reasons is discussed below.
Ethical considerations typically will not allow random withholding of an intervention with known efficacy. Thus, if the efficacy of an intervention has not been established, a randomized controlled trial is the design of choice to determine efficacy.
But if the intervention under study incorporates an accepted, well-established therapeutic intervention, or if the intervention has either questionable efficacy or safety based on previously conducted studies, then the ethical issues of randomizing patients are sometimes raised. In the area of medical informatics, it is often believed prior to an implementation that an informatics intervention will likely be beneficial and thus medical informaticians and hospital administrators are often reluctant to randomize medical informatics interventions.Therefore a quasi-experimental design in itself is an experiment which holds some similar characteristics to true experiments with an exception of random selection.
It is often applied to case studies and when conducting true experiments are not feasible. This lesson explores the basic definition of why there is the label of quasi-experimental design in addition to what types of designs are quasi-experimental.
into his scheme of experimental design, with the defections from experimentation to essay writing, often accompanied by conversion from a behaviorism to Gestalt EXPERIMENTAL AND QUASI-EXPERIMENTAL DESIGNS FOR RESEARCH 3 osely overoptimistic and were accompanied. Context of this essay is a detailed historical field research on the psycho–sociology of a modern secret society called Ordo Templi Orientis (O.T.O.).
Essay about Quasi-experimental Design - I. Jackson (), even-numbered chapter exercises, p 2. The recommended design for this type of study is a non-equivalent control group post-test only design.
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