6.1 Developing Clinical Templates for Data Capture

Test plan task 2.A opens Domain 2 — the largest domain on the CEHRS exam — with template development. Knowledge statements 2.K1 through 2.K3 add the content included in clinical templates, the types of information required for specific templates, and the common uses of clinical templates. A template is not cosmetic: it decides what becomes queryable data and what disappears into prose.

What a Clinical Template Is

A clinical template is a pre-built documentation form that presents a defined set of fields for a specific clinical context. The three organizing principles named in the test plan are:

Related constructs the specialist will meet: order sets bundle orders for a condition (Section 7.4); smart phrases or macros insert reusable text into a note; flowsheets capture repeated discrete values over time.

Template Anatomy

A well-built encounter template typically contains:

1. Header — patient identity banner, encounter type, date of service, provider
2. Reason for visit / chief complaint — short structured picker plus a free-text field for the patient's own words
3. History elements — HPI prompts, review of systems checkboxes, PFSH fields
4. Vitals and measurements — numeric fields with units and reference-range logic
5. Structured clinical data — problem selection, medication and allergy reconciliation prompts, screening instruments
6. Examination — body-system sections appropriate to the specialty
7. Assessment — diagnosis picker bound to SNOMED CT/ICD-10-CM
8. Plan — order set links, patient education links, follow-up interval
9. Attestation — signature block and, where applicable, supervising provider cosignature

Structured Versus Narrative — the Central Design Decision

Every field is a choice between data and prose.

Over-structuring is a real failure mode: a template with 200 checkboxes that clinicians click through without reading produces data that is technically discrete and clinically meaningless. Under-structuring buries everything in prose. The working rule is to structure what is acted on, measured, or reported, and leave the rest as narrative.

Design Pitfalls

• Pre-populated normal findings. A template that opens with every review-of-systems box marked "negative" and every exam finding marked "normal" documents an examination that may not have happened. It is the same compliance exposure as note cloning (Section 5.3) and can support a False Claims Act allegation. Templates should default to blank and require affirmative entry.
• Fields nobody completes. Unused fields train users to skip sections, and skipped sections eventually include the ones that matter.
• Duplicated capture. The same value collected in two places diverges, then a report has to choose which copy is true.
• Specialty mismatch. A general medicine exam template used in dermatology forces the clinician into free text and destroys the structured capture the template was built for.
• Hidden required fields that block signing without explaining why, which drives workarounds.
• Copy-forward defaults that carry the entire prior note into the new encounter automatically.

Governance and Change Control

Template changes are configuration changes to a legal record, so they follow a controlled path:

1. Request — submitted with the clinical rationale and the requesting specialty
2. Review — clinical informatics and the affected specialty confirm the content is appropriate and does not conflict with policy or coding rules
3. Build in a non-production environment — never edited live
4. Test — including whether structured fields land in the right database elements and feed the intended measures
5. Compliance check — no pre-populated normals, no auto-inserted findings, attestation language intact
6. Communicate — using the update-notice pattern in Section 4.6
7. Deploy with version control — dated versions retained, because a record must be interpretable against the template in effect at the time
8. Monitor — post-deployment review of completion rates and documentation audits

The EHR specialist's role in this chain is usually gathering requirements, building or configuring in the test environment, validating that data lands where it should, and coordinating communication — not unilaterally deciding clinical content.