- Klíčová slova
- přeprava speciálních přípravků,
- MeSH
- financování zdravotní péče * MeSH
- klinické kódování metody MeSH
- krevní transfuze ekonomika zákonodárství a právo MeSH
- léčivé přípravky * zásobování a distribuce MeSH
- zdravotní pojištění ekonomika organizace a řízení zákonodárství a právo MeSH
- Publikační typ
- souhrny MeSH
- Geografické názvy
- Česká republika MeSH
ÚZIS ČR ve spolupráci s IPVZ zahájil v říjnu 2018 odborné vzdělávání kodérů pro nově vyvíjený systém CZ-DRG. Třídenní kurz realizovaný pod záštitou ministra zdravotnictví má za cíl zajistit vzdělávání pracovníků v dané problematice tak, aby byli plně seznámeni s novým klasifikačním systémem CZ-DRG a správným použitím jeho metodických materiálů k aplikaci výstupů projektu do praxe... Očekávaným výsledkem realizovaného kurzu je zvýšení dostupných kapacit profesionálů v tomto oboru a předpokládané zlepšení kvality dat produkovaných ve zdravotnictví (vykazování pro administrativní a statistické účely, systémy úhrad, business inteligence, data mining a manažerské rozhodování, věda a výzkum).
- MeSH
- financování zdravotní péče MeSH
- formuláře a záznamy - kontrola a vedení MeSH
- hospitalizace ekonomika MeSH
- klinické kódování * metody MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- novinové články MeSH
BACKGROUND: Narrative medical reports do not use standardized terminology and often bring insufficient information for statistical processing and medical decision making. Objectives of the paper are to propose a method for measuring diversity in medical reports written in any language, to compare diversities in narrative and structured medical reports and to map attributes and terms to selected classification systems. METHODS: A new method based on a general concept of f-diversity is proposed for measuring diversity of medical reports in any language. The method is based on categorized attributes recorded in narrative or structured medical reports and on international classification systems. Values of categories are expressed by terms. Using SNOMED CT and ICD 10 we are mapping attributes and terms to predefined codes. We use f-diversities of Gini-Simpson and Number of Categories types to compare diversities of narrative and structured medical reports. The comparison is based on attributes selected from the Minimal Data Model for Cardiology (MDMC). RESULTS: We compared diversities of 110 Czech narrative medical reports and 1119 Czech structured medical reports. Selected categorized attributes of MDMC had mostly different numbers of categories and used different terms in narrative and structured reports. We found more than 60% of MDMC attributes in SNOMED CT. We showed that attributes in narrative medical reports had greater diversity than the same attributes in structured medical reports. Further, we replaced each value of category (term) used for attributes in narrative medical reports by the closest term and the category used in MDMC for structured medical reports. We found that relative Gini-Simpson diversities in structured medical reports were significantly smaller than those in narrative medical reports except the "Allergy" attribute. CONCLUSIONS: Terminology in narrative medical reports is not standardized. Therefore it is nearly impossible to map values of attributes (terms) to codes of known classification systems. A high diversity in narrative medical reports terminology leads to more difficult computer processing than in structured medical reports and some information may be lost during this process. Setting a standardized terminology would help healthcare providers to have complete and easily accessible information about patients that would result in better healthcare.
- MeSH
- chorobopisy MeSH
- klinické kódování metody MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- mezinárodní klasifikace nemocí MeSH
- SNOMED MeSH
- terminologie jako téma MeSH
- vyprávění MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
Objective: To develop Logical Observation Identifeers Names and Codes (LOINC) codes to represent constitutional cytogenetic test results for electronically exchanging coded and structured result reports. The LOINC codes developed must be feexible and sustainable for easy maintenance. The goal is to create a standard set of codes that are feexible enough to be used for all unique conventional and molecular cytogenetic results. Design: Patient de-identifeed sample result reports were obtained from ARUP Laboratories for a variety of normal and abnormal constitutional studies using G-banding, FISH and array-CGH. Information models were created to capture the semantic relationships of the key data elements that existed in the reports. Sample reports were subsequently obtained from Emory and Mayo Clinic Cytogenetics Laboratories to verify the information models. The information models were then used to guide the systematic creation of the LOINC codes. Results: A post-coordinated approach was used in developing the LOINC codes for cytogenetics test results. LOINC panel codes were created to represent the hierarchical structures implied by the reports. A master panel was created to contain three LOINC subpanels; each of the three subpanels held the structure for chromosome analysis results that uses a difeerent technique. Conclusion: The LOINC codes we created met our objective and will allow the use of well established health informatics standards to exchange coded and structured cytogenetic test results between testing laboratories and ordering institutions. Use of standard structures and terminologies for cytogenetic results is critical for efeective communication between testing laboratories and clinicians. This minimizes misinterpretation, leads to consistency, and provides the EHR systems feexibility of customizing formatting to present more clinician-friendly reports.
