The conclusions from such a study may not be as solid as those from prospective studies. For example, one might look at a group of lung cancer patients and compare them to a group of patients without lung cancer to examine the prevalence of smoking in each group. Nobody is being selected on that basis, so the opportunity for selection bias is limited.Īnother type of study is fully retrospective: the groups are selected on the basis of the outcome of interest. lung cancer) is something that develops or becomes apparent during the course of the study. One could not assign a person randomly to be a lifetime cigarette smoker or non-smoker. Sometimes called a “prospective cohort study,” these studies often fall short of the “gold standard” of a randomized trial, because the assignment to the treatment or control group is usually not random. Although prior information from the participants might be used, the primary focus is what happens to each group during the period of the study. This information would typically be compared to similar information from non-smokers. However, in such cases, there is also an aspect of tracking events into the future.Ī good example is a study following cigarette smokers over time, to see what medical conditions they contract during the study. For example, participants may be asked if they had any medical conditions as a child, e.g. Cohort and panel studies, which often follow a group over time, often collect information about the past. Some prospective studies have retrospective aspects. There is a temptation to modify the question being studied as the data are examined.Similarly, the exact data (or subset of data) used to answer the question can be drawn in a way that produces the desired answer, or a more noteworthy or interesting answer.Since the data are already available, the question to be answered can be influenced by the data.Prospective studies are generally regarded as cleaner and more reliable, due to several shortcomings of retrospective studies: The definition of the problem under study does not change once the data collection starts.Ī retrospective study is one in which you look backwards at data that have already been collected or generated, to answer a scientific (usually medical) problem. what you’re measuring, who you’re measuring, how many subjects, etc.), and then gathers data in the future in accordance with the design. Building on this example, the presentation will enumerate important data elements and design considerations for study start-up and ongoing management and analysis of singular studies that utilize one retrospective dataset (e.g., electronic health records (EHR)) and one prospective dataset (e.g., EDC) as well as multi-year, multi-dataset drug and disease registries that utilize large amounts of both prospective and retrospective data.A prospective study is one that identifies a scientific (usually medical) problem to be studied, specifies a study design protocol (e.g. Based in the design and conduct of actual studies, the presentation will conceptualize a hybrid study design and targeted data management and analysis approach.

This presentation will explore design and operational considerations for hybrid retrospective-prospective studies, including merging databases of different sizes and formats and analyzing data from individual and pooled datasets with a focus on which data can and should be captured, such as efficacy/effectiveness outcomes, healthcare resource utilization (HRU), and costs/claims. When conceptualizing a hybrid analytic approach, researchers should give thought to the use and potential repurposing of existing data sources, the structure of ”new” data sources (e.g., EDC) and planning analyses for individual, partially merged, and fully merged datasets. Such hybrid studies generally involve integration of datasets from multiple electronic sources such as electronic data capture (EDC) systems for clinical trials and observational studies, claims databases held by public and private payers, and myriad others.

This hybrid approach is supported by the United States National Institutes of Health (NIH) and multiple health technology assessment bodies.

12/2016: Making Choices on the Journey to Universal Health Care Coverage: From Advocacy to AnalysisĬomparing active prospective treatment or observational arms with data from historical (i.e., retrospective) controls can save time and money in the evaluation and assessment of investigational and marketed pharmaceutical and biologic products as well as medical devices.

2/2017: “Mapping Studies” In Cost-Utility Analyses: New Recommendations From ISPOR Task Force.

2/2017: ISPOR Releases New Task Force Recommendations for the Development of Clinician-Reported Outcome Assessments.

Prospective vs retrospective study