HLTH 2120 Week 2 Health Data Terminology Brief Example

Five Words Held Apart: Data, Information, Structured Entry, Free Text and the Three Things People Mean by the Record, Tested on One Admission Weight

Student Name

Walden University

HLTH 2120: Health Informatics

Instructor Name

Month Day, Year

Five Words Held Apart: Data, Information, Structured Entry, Free Text and the Three Things People Mean by the Record, Tested on One Admission Weight

Purpose

Informatics discussions go wrong when people use the same word for different things. A nurse, a coder and a records manager can all say "the record" and mean three different collections of documents. This brief separates five terms that are often blurred and then tests each distinction on one concrete example: the weight recorded for a patient admitted to a medical-surgical unit. If a distinction cannot be applied to that one weight, it is not useful. The example is a composite drawn from common practice, not a real patient.

Data and Information

Data are recorded values without interpretation. Information is data placed in a context that gives it meaning for a purpose. Informatics texts commonly describe a hierarchy running from data to information to knowledge, in which each level adds context and interpretation (Hoyt & Hersh, 2022).

Test on the example. The entry "82" in a field labeled weight is data. It becomes information only when the reader knows the unit (kilograms, not pounds), the date and time, whether it was measured on a scale or reported by the patient and whose weight it is. "82 kg, measured on the bed scale at 1410 on admission" is information a pharmacist can use to calculate a weight-based dose. "82" alone is dangerous, because a reader who assumes pounds would calculate a dose less than half of what the patient needs. The distinction holds: the same number is data or information depending on the context recorded with it.

Structured Entry and Free Text

Structured entry records a value in a predefined field with rules about what it may contain, such as a number, a unit chosen from a list and a date. Free text records language typed or dictated by the writer, without constraints on form. Structured data can be counted, compared, checked and passed automatically to other systems; free text can capture nuance and context that no field anticipated, but a computer cannot reliably use it without processing it first (Rosenbloom et al., 2011).

Test on the example. On most units the admission weight is entered in a structured flowsheet field with a unit selector and a required method of measurement. That structure is what allows the weight to flow into pharmacy dosing tools and nutrition calculations. But suppose the nurse also writes in a free-text note: "Patient unable to stand; weight per daughter, who thinks he has lost weight recently." That sentence carries the most important fact about the number, that it may be wrong, and it sits where no dosing tool will read it. The distinction holds, and it shows the cost of each form: the structured field travels but loses nuance, the free text keeps nuance but stays put.

Three Things People Mean by the Record

People use "the record" for at least three different collections, and confusing them causes real problems.

The electronic health record system. The software and everything stored in it, including drafts, audit logs, alerts and data the organization uses for operations.

The legal health record. The documents and data an organization defines, in its own policy, as its official business record of care, the version it produces in response to a subpoena or court order. Organizations decide what belongs in it, and professional guidance recommends that each organization define it explicitly (American Health Information Management Association, 2011).

The designated record set. Under the HIPAA Privacy Rule, the records a covered entity uses to make decisions about individuals, including medical and billing records, which the individual may inspect, obtain copies of and ask to have corrected (45 C.F.R. § 164.501). This set can be larger than the legal health record, because it includes billing records.

Test on the example. The admission weight in the flowsheet belongs to all three. The draft weight the nurse started to enter and canceled exists in the system's audit log, so it is part of the first collection, but it is not part of the legal health record under most organizations' policies and would not normally be produced for a court. The daughter's statement in the free-text note is part of all three. If the patient later asked to see his records, the weight and the note would be released because they are in the designated record set, and he could ask to amend a weight he believed was wrong. The distinction holds, and it shows that a question like "is that in the record?" has three possible answers.

Two Related Terms: Metadata and Provenance

Two more terms come up constantly in this course and are worth placing beside the five. Metadata is data about data: the unit, the timestamp, the user who entered a value and the method of measurement are all metadata about the weight. Much of what turns data into information, in the sense defined above, is metadata. Provenance is the history of where a value came from and how it changed. A weight whose provenance shows it was measured on a bed scale by the admitting nurse and never edited deserves more trust than one whose provenance shows it was copied from a prior admission. Electronic systems record a great deal of metadata automatically, in audit logs, but often do not display it where clinicians make decisions. That gap between what the system knows and what the screen shows is one of the recurring themes of informatics.

Why the Distinctions Matter

Holding these terms apart is not academic tidiness. The data and information distinction explains why a weight without a unit is a safety risk. The structured and free text distinction explains why the most important caveat about the weight never reached the pharmacist. And the three meanings of the record explain why a records manager, a lawyer and a patient can give different answers about the same entry without any of them being wrong. In the rest of this course, when I write about the record, I will say which of the three I mean, and when I write about data quality, I will separate a missing value from a value missing its context.

The example also previews next week's assignment. The weight does not stay in the flowsheet. It moves into pharmacy, nutrition and quality reports, and at every step it can lose the context that made it information. Following that movement is the next task.

References

American Health Information Management Association. (2011). Fundamentals of the legal health record and designated record set. Journal of AHIMA, 82(2), Expanded online version.

Definitions, 45 C.F.R. § 164.501 (2024).

Hoyt, R. E., & Hersh, W. R. (Eds.). (2022). Health informatics: Practical guide (8th ed.). Lulu.com.

Rosenbloom, S. T., Denny, J. C., Xu, H., Lorenzi, N., Stead, W. W., & Johnson, K. B. (2011). Data from clinical notes: A perspective on the tension between structure and flexible documentation. Journal of the American Medical Informatics Association, 18(2), 181-186. https://doi.org/10.1136/jamia.2010.007237