This post has been superseded. Please refer to the updated post on the same topic.
We all use these words in clinical medicine: observations, assessments, diagnosis, medical condition, adverse event, outcome measure, endpoint. But what do they really mean? The published definitions are all over the map, often imprecise and inconsistent. I have conducted informal polls of medical reviewers at FDA and, guess what, they mean different things to different people. These are highly educated, highly experienced people. The same problem exists in academia and industry. I see this in the wide variability in how these words are used in study protocols.
Standardizing the definitions of these common term has been a topic of interest to me. How can we automate the processing of clinical data if we can't all agree on definitions for these basic terms in clinical medicine? Using best practices for how to define things, I have come up with the following "working definitions" that I think are unambiguous and internally consistent...i.e. enables humans and information systems to clearly distinguish them apart. I'd also like to think they are accurate in how they're used or should be used in clinical medicine. I present them here in no particular order other than some naturally flow from others.
1. Clinical Observation: a measure of the physical, physiological, or psychological state of an individual.
Note: A Clinical Observation is ideally observed by a qualified individual, following a standard process, but without implying a cause. Many clinical observations simply reflect a normal physiological state. e.g. BP 120/80 mmHg.
1(a). Symptom: a Clinical Observation that can only be observed by the patient (e.g. pain). Synonym: Subjective Observation
1(b). Sign: a Clinical Observation that can be observed by someone other than the patient (e.g. blood pressure). Synonym: Objective Observation.
Note: Signs can also be self-observed, for example, fingerstick glucose or blood pressure using an appropriate home monitoring device.
1(c). Outcome Measure: A Clinical Observation that is of interest for some research activity (e.g. clinical or epidemiological study). The outcome measure is intended to support one or more objectives in a research project. e.g.: Hemoglobin A1C in a diabetes study.
1(d). Patient Reported Outcome (PRO) is an Outcome Measure that is also a Symptom.
2. Endpoint: A combination of 3 concepts:  one or more Outcome Measures,  a time element describing when the outcome measure is collected,  and an algorithm describing how the Outcome Measures are combined for analysis (optional). (Credit goes to Roomi Nusrat, M.D. for this one) Example: Percent change from baseline in HgbA1C measured at 12 weeks.
Note: I find Outcome Measure and Endpoint often used interchangeably. Sometimes they are very close: e.g. Viral Load (outcome measure); Viral Load at 6 weeks (endpoint).
2(a). Composite Endpoint: an Endpoint with two or more distinct Outcome Measures.
3. Medical Condition: a disease, injury, or disorder that interferes with well-being. It is associated with a pathophysiology. It is also associated with a duration (i.e. an event).
Note: Medical conditions are the target of medical interventions (one notable exception is Pregnancy; though not a disorder it is the target of prenatal care to help prevent pregnancy-related complications). Medical conditions explain the presence of abnormal clinical observations. We often confuse a clinical observation (e.g. low serum sodium at a single point in time) with the medical condition that gives rise to it (e.g. hyponatremia). I write about this distinction in more detail in a previous post.
3(a). Adverse Event: A Medical Condition that emerges or worsens following a Medical Intervention. Note: there is no presumption of causality.
3(b). Adverse Reaction: An Adverse Event that is caused or worsened by a Medical Intervention. Here causality is presumed.
3(c). Treatment Emergent Adverse Event: [I'm putting this here as a placeholder as I'm still looking for a good definition. I think the key features of a TE AE is that it is an Adverse Event associated with a specific Medical Intervention, and some algorithm is defined to establish the temporal association. I welcome suggestions].
3(d). Indication: A Medical Condition that is the target of a Medical Intervention; i.e. the reason the Medical Intervention is performed.
4. Medical Intervention: An activity intended to affect (e.g. treat, cure, prevent, diagnose, mitigate) a Medical Condition. e.g. Drug Administration, Surgery, Device implantation.
5. Assessment: An analysis of one or more Clinical Observations to characterize a Medical Condition.
Note: Sometimes assessment is used to mean the collection of a clinical observation. I would like to see us move away from this use as it is confusing. The clinical process is first observe or measure clinical observations then assess one or more clinical observations to identify/characterize medical conditions.
6. Diagnosis: this is an overloaded term in clinical medicine. It has two definitions depending on whether it's used to mean a process or a thing.
Diagnosis (the process): An Assessment to identify the presence of a Medical Condition.
Diagnosis (the thing): A Medical Condition identified for the first time via an Assessment.
So we can say: Q. What did the diagnosis (diagnostic assessment process) show? A: Adult Onset Diabetes Mellitus. OR
Q. What is the diagnosis? A: Adult Onset Diabetes Mellitus.
Note: Because Diagnosis (the thing) is a Medical Condition, one can define a start/onset date as the date of the first Clinical Observation associated with the condition, as well as the diagnosis date, which is the date the diagnostic assessment was complete, i.e. the date the Medical Condition was first identified via an assessment. As we all know, these are often not the same.
One interesting question is can a Medical Condition be an Outcome Measure in a study? The way they are defined here, Outcome Measures are always Clinical Observations, not Medical Conditions. A stroke prevention study might define Stroke as the primary Outcome Measure, but is it really? A close inspection reveals that it's really the symptoms and signs of the stroke that are important (i.e. what we can observe/measure). Stroke is clinically very heterogenous and can present in many different ways, so we need to describe what Clinical Observations are most likely indicative of a stroke? (e.g. paralysis, numbness, visual loss, etc.) These, then, are the true Outcome Measures. So when we see a Medical Condition as an Outcome Measure, there needs to be an adjudication process (i.e. Assessment) to define the Clinical Observations that need to be measured and analyzed to assure the Medical Condition is present.
I welcome comments to refine these and make them more useful. I think the interesting part comes in converting these definitions into OWL representations, to enable computers to reason across the data. This remains a research interest of mine. Maybe I'll get into that in a future post.