What Outcomes Research Measures
Outcomes research evaluates the end results of healthcare interventions, including clinical outcomes, functional status, patient experience, and cost effectiveness. RHIA candidates should be familiar with the basic study designs used in this research and the role of health information data in supporting it.
Study Design Basics
- Randomized controlled trial: participants are randomly assigned to intervention or control groups, considered the strongest design for establishing causation but often impractical for studying rare outcomes or long term effects.
- Cohort study: a defined group is followed over time to observe outcomes, which can be prospective or retrospective.
- Case control study: compares individuals with a specific outcome to those without it, looking backward to identify differing exposures.
- Cross sectional study: captures data at a single point in time, useful for measuring prevalence but not for establishing cause and effect.
Secondary Data Use
Much outcomes research relies on secondary data, meaning data originally collected for clinical or administrative purposes, such as coded claims data or EHR extracts, rather than data collected specifically for the study. This raises considerations about data quality, completeness, and whether the coded data accurately reflects the clinical concept being studied.
Bias and Confounding
Candidates should recognize common threats to validity, including selection bias, where the study population is not representative, and confounding, where an outside variable influences both the exposure and the outcome, creating a misleading association. Risk adjustment methods attempt to control for confounding when comparing outcomes across different patient populations or facilities.
Institutional Review and Data Governance
Research using identifiable health information typically requires Institutional Review Board approval and either patient authorization or an IRB approved waiver of authorization. HIM departments often manage the release of information process for research requests and verify that IRB approval documentation is on file before releasing data.
Statistical Significance vs. Clinical Significance
A result can be statistically significant, meaning unlikely due to chance, without being clinically meaningful. RHIA candidates are expected to understand this distinction conceptually when interpreting research findings presented in exam scenarios.
Exam Tip
When a question describes researchers looking backward at existing records to compare patients who did and did not experience an outcome, this describes a case control study, a design frequently confused with cohort studies on the exam.