Observational Studies

Abstract

Studies can be observational or experimental. With an observational study, the investigator does not determine the assignment of subjects, and there might not be a control group. If there is a control group, assignment of the independent variable (exposure or intervention) is not under the control of the investigator. Observational studies can be rigorously conducted, but the lack of random assignment of the exposure/intervention introduces confounding and bias. Thus, the quality of evidence resulting from observational studies is lower than that of experimental randomized controlled trials (RCTs). An observational study might be performed if an RCT is unethical, impractical, or outside the control of the investigator. There are many types of prospective and retrospective observational study designs. However, an observational study design should be avoided if an experimental study is possible. Sophisticated statistical approaches can be used, but this does not elevate an observational study to the level of an RCT. Regardless of quality, an observational study cannot establish causality.

Keywords: case control; case series; cohort study; cross-sectional study; interrupted time series; matched case control; observational study; prospective study; quasi experimental; retrospective study.

Fig. 1.

Prospective versus retrospective study.

Fig. 2.

Example of an interrupted time series. Thirty-day all-cause emergency department (ED) revisit rate among subjects with COPD exacerbation who were discharged from ED observation unit (ED-Obs) (outcome measure) is displayed on a statistical process control p-chart. Due to month-to-month variation in the number of subjects discharged from ED-Obs, the time series on the x axis is based on every 10 consecutive subjects. The dates on the x axis signify the date of last encounter with the subject. The 30-d all-cause ED revisit rate (%) is on the y axis. The baseline period extends from August 2014–September 2016, showing a stable system with common-cause (random) variation only. The last subgroup in the baseline period has 15 subjects, after which the bundle testing began in August 2016. During the post-bundle period, the data show a system shift with 8 consecutive observations below the center line (49%). New control limits were hence calculated with a new average of 30%. From reference . ED = emergency department.

Fig. 3.

An example of a retrospective comparison cohort. The outcome (mortality) is identified, and then exposures (rural hospital, urban non-teaching hospital, and urban teaching hospital) are compared. From reference . OR = odds ratio.

Fig. 4.

Case-control study scheme.