BMC Med Inform Decis Mak - Determinants of frequency and longevity of hospital encounters' data use.

Tópicos

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Resumo

CKGROUND: The identification of clinically relevant information enables improvement in user interfaces and in data management. However, it is difficult to identify what information is important in daily clinical care, and what is used occasionally. This study aims to determine for how long clinical documents are used in a Hospital Information System (HIS).METHODS: The access logs of 3 years of usage of a HIS were analysed concerning report departmental source, type of hospital encounter, and inpatient encounter ICD-9-CM main diagnosis. Reports median life indicates the median time elapsed between information creation and its usage. The models that better explains report views over time were explored.RESULTS: The number of report views in the study period was 656,583. Fifty two percent of the reports viewed by medical doctors in emergency encounters were from previous encounters - 21% at outpatient attendance, 19% in inpatient (wards) and 12% during emergency encounters. In an inpatient setting, 20% of the reports viewed were produced in previous encounters. The median life of information in documents is 1.5 days for emergency, 4.8 days for inpatient and 37.8 days for outpatient encounters. Immune-hemotherapy reports reach their median lives faster (7 days) than clinical pathology (15 days), gastroenterology (80 days) and pathology (118 days). The median life of reports produced in inpatient encounters varied from 36 days for neoplasms as the main diagnosis to 0.7 days for injury and poisoning. The model with the best fit (R2 > 0.9) was the exponential.CONCLUSIONS: The usage of past patient information varied significantly according to patient age, type of information, type of hospital encounter and medical cause (main diagnosis) for the encounter. The exponential model is a good fit to model how the reports are seen over time, so the design of user interfaces and repository management algorithms should take it in consideration.

Resumo Limpo

ckground identif clinic relev inform enabl improv user interfac data manag howev difficult identifi inform import daili clinic care use occasion studi aim determin long clinic document use hospit inform system hismethod access log year usag analys concern report department sourc type hospit encount inpati encount icdcm main diagnosi report median life indic median time elaps inform creation usag model better explain report view time exploredresult number report view studi period fifti two percent report view medic doctor emerg encount previous encount outpati attend inpati ward emerg encount inpati set report view produc previous encount median life inform document day emerg day inpati day outpati encount immunehemotherapi report reach median live faster day clinic patholog day gastroenterolog day patholog day median life report produc inpati encount vari day neoplasm main diagnosi day injuri poison model best fit r exponentialconclus usag past patient inform vari signific accord patient age type inform type hospit encount medic caus main diagnosi encount exponenti model good fit model report seen time design user interfac repositori manag algorithm take consider

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