By Jonathan D. Gold, MD MHA MSc FAMIA FHIMSS
March 25, 2024
Challenge yourself:
When is a temporal phrase interpretable, but not plottable?
Which temporal perspective is most useful for understanding an outbreak of cholera?
How can we mitigate the inherent inexactitude of an inferred date?
‘Interpretable’ versus ‘Plottable’ Temporal Phrases
For a temporal phrase to be understood it will often include a specific point or range in time, a general chronology or sequence of events, or the possibility of when an event may have occurred. Unlike a computer, for a person to infer a temporal meaning for an event, a phrase is not required to include the use of numbers, dates or other clearly defined time units or phases. Even the existence of an event that does not include when it occurred or an ambiguous start, may imply temporality that a person can generally understand, e.g., “Previously, the patient experienced headaches, but that was some time ago.”
On the other hand, at a minimum, the practical use of plotting events on a patient’s health timeline requires some sort of measurable timeframes. With the goal of compiling a unified timeline of health-related events for a patient, organizing, and incorporating the free text found in a patient’s multiple records provides a robust reservoir of data.
The minimum requirements to calculate temporality from free text in an entry and add it to a health timeline can be stated as follows:
“To be utilizable, temporal text must permit quantified interpretation leading to a specific point or range in time either by calling out a specific timeframe (like age or date) or giving a quantifiable time association with a timestamp and associated with either an element or event.”
Temporal Perspectives for Events
Three temporal views provide important vantages for understanding events—biographic (the patient age when an event occurs) [1], differential (time measurement from one point to another point between stages in an event or between different events), and extrinsic (the time/date or date range associated with an event). [2]
A biographic perspective is utilized when identifying patients with similar disease patterns for use in predictive modeling. A differential view is valuable when comparing similar disease progressions, for example, the time between the diagnosis of diabetes mellitus, type 2, and the onset of chronic kidney disease. Extrinsic dates help put a patient’s events in perspective particularly in the light of public health events (e.g., food poisoning at a restaurant, pandemic spread in a region, etc.).
Three Temporal Views |
Patient age (in days) at event (Biographic)* |
Point to point between events (Differential) |
Date (or date range) of event (Extrinsic) |
*patient’s birthdate = Day 1 |
A health timeline graphically displays a patient’s longitudinal medical record. One example, Figure 1, includes all three views—biographic, differential, and extrinsic.
While it would be desirable to plot events as a single point in time, often the exact time or date of events remains elusive. Therefore, while it is necessary to add an event to the timeline at a specific point, depending on the precision that can be placed on that assignation, minimum and maximum values showing the potential range of when the event occurred should be included. Hence, the best estimation of when the event took place serves as the midpoint (“Point in Time”) where the event is charted, but lower and upper limits are also marked. Figure 2.
Conclusion
Utilizing temporal statements, at a minimum, requires a quantifiable clue to allow events to be mapped. Three important perspectives should be addressed and included when plotting an event's occurrence. Where the timing of an event is inferred from a temporal statement, the best estimate of when the event took place and lower and upper delimiters delineating the expected range of when it could have occurred are all important data points.
[1] In temporal measurement, patient age should typically be stored as age in days, such that, a patient’s birthdate equals ‘Day 1’. In practical terms for general needs, the age is converted back into years, months, weeks, or days, as appropriate. When building predictive models, comparing patients with similar medical events at similar ages and following similar sequences, can aid in prognosticating the expected outcomes or progression of disease for patients depending on which interventions are taken.
[2] Extrinsic temporality serves a particularly important role in epidemiological or public health studies. One example is searching for a unifying event in multiple patient histories (e.g., exposure to a pathogen at a specific location on a specific date).
댓글