Sentence examples for classification of encounters from inspiring English sources

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For surveillance systems to be comparable, the classification of encounters into episodes of illness is an important methodological problem that deserves additional attention.

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The title is derived from ufologist J. Allen Hynek's classification of close encounters with aliens, in which the third kind denotes human observations of actual aliens or "animate beings".

The re-classification of inpatient encounters substantially impacted the observed prevalence of medical conditions occurring in the inpatient setting and the consistency in prevalence estimates between the databases.

When looking at classification in all four areas, 82.7% of encounters had correct classification in all areas under pIMCI compared to 90.9% under eIMCI (p < 0.001).

Within ambulatory clinics, ILI was defined as presence of fever (either measured temperature >99.9°F, or fever as a reason for visit) plus reason for visit of cough, "flu" or influenza, or ILI-related International Classification of Diseases, 9th Revision, encounter diagnosis (codes 079.99, 466.0, 487.1, 382.00, 465.9).

Additionally, reviewers considering the economic perspective should consider undertaking classification of the economics studies encountered in a review, and critical appraisal of their methodological quality, using a purpose-specific, established checklist prior to the final decision to include or exclude such studies [ 19, 20].

In contrast, Optum had 83.18% concordance in classification of 2012 claims from inpatient encounters before and after standardization, but the consistency varied over time.

Individuals from the depression-free cohort with 2 or more health claims diagnoses of depression based on face-to-face clinical encounters (International Classification of Diseases, Ninth Revision, diagnosis code 296 (major depressive disorder), 309 (adjustment disorder with depression), or 311 (depressive disorder)) during the study period 1998 2003 were considered cases of depression.

The purpose of the current study was to develop and examine the validity of algorithms using hospital encounter (International Classification of Diseases, 10th revision [ICD-10]) codes and physician claim codes for the detection of CKD assessed against a reference standard of estimated glomerular filtration rate (eGFR) determined with laboratory values.

The use of two text-similarity-recognition programs also improved the rate of detection and, in some theses, significantly increased the classification of the gravity of the plagiarism encountered.

It allows classification of the patient's reason for encounter (RFE), the problems/diagnosis managed, interventions, and the ordering of these data in an episode of care structure.

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