Journal: BMC Medical Informatics and Decision Making

Article Title: Combining structured and unstructured data in EMRs to create clinically-defined EMR-derived cohorts

doi: 10.1186/s12911-021-01441-w

Figure Lengend Snippet: Visual representation of data tables extracted from Cerner Millenium EMR systems. Cerner EMR systems were extracted as data tables which are linked by encounter key. Data tables were linked by encounter key and include information about encounters, diagnoses (ICD-10 and SNOMED CT), pathology, forms (e.g. ED triage assessments, medication forms, discharge letters), notes (e.g. progress notes) and many more. Encounter level information were further linked to person level information by person key and included patient medical history and social history. The size of the raw file associated with each table is shown next to the table name. The data tables are listed in order of file size with the biggest files related to free-text information and scanned ECG images. The figure represents data extracted for a single 3 month time period (1/4/17–30/6/17)

Article Snippet: The data experts then mapped the clinical criteria to discrete data tables within the Cerner Millennium EMR system to locate the data elements required for identification of patients using these clinical criteria (Step 3, Fig. ).

Techniques:

Journal: Ophthalmology Science

Article Title: Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies

doi: 10.1016/j.xops.2024.100666

Figure Lengend Snippet: A, Distribution of data elements classified into 8 subject categories for the default and local Cerner modules. B, Match type breakdown of data elements in each category.

Article Snippet: A, Distribution of all default Cerner and local Cerner module mappings by vocabulary of the target standard concept.

Techniques:

Journal: Ophthalmology Science

Article Title: Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies

doi: 10.1016/j.xops.2024.100666

Figure Lengend Snippet: Distribution of Mappings for the Default Cerner Millennium Eye Examination and a Localized Cerner Ophthalmology Module by Mapping Type and Vocabulary

Article Snippet: A, Distribution of all default Cerner and local Cerner module mappings by vocabulary of the target standard concept.

Techniques:

Journal: Ophthalmology Science

Article Title: Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies

doi: 10.1016/j.xops.2024.100666

Figure Lengend Snippet: A, Distribution of all default Cerner and local Cerner module mappings by vocabulary of the target standard concept. Match type distribution for mappings with target standard concepts in SNOMED ( B ) or LOINC ( C ) vocabularies. LOINC = Logical Observation Identifiers, Names, and Codes; SNOMED = Systematized Nomenclature of Medicine.

Article Snippet: A, Distribution of all default Cerner and local Cerner module mappings by vocabulary of the target standard concept.

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Journal: Pediatric Quality & Safety

Article Title: A Quality Improvement Initiative to Improve Pediatric Discharge Medication Safety and Efficiency

doi: 10.1097/pq9.0000000000000671

Figure Lengend Snippet: Unmatched reasons for Cerner inpatient vs MAP inpatient.

Article Snippet: One, in this regard, would consider partnering with the Acute Care Cardiology Collaborative (PAC), whose mission includes improving “cardiac acute care outcomes” and “family and staff experience.” – Furthermore, in Figure , Figure 2, Supplemental Digital Content, Unmatched reasons for Cerner outpatient vs. Cerner inpatient, http://links.lww.com/PQ9/A505 , and Figure 3, Supplemental Digital Content, Unmatched reasons for Cerner outpatient vs. MAP® outpatient, http://links.lww.com/PQ9/A505 , we provide the readers with reasons for medication mismatches, which can be the focus of future interventions to improve medication accuracy.

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