Lesson 1Administrative identifiers: patient ID, case number, insurance number, an national identifiersExplains key administrative identifiers used inna German HIS/KIS, like patient ID, case number, insurance number, an national identifiers. Covers formats, uniqueness, assignment rules, an cross system integration.
Patient ID generation and uniquenessCase number lifecycle and reuse rulesInsurance and policy number formatsNational identifiers and legal limitsIdentifier mapping across systemsLesson 2Mandatory fields checklist an business rules: required vs optional fields an rationaleDetails which admission fields mus get captured, which ones optional, an why. Explains legal, clinical, an billing drivers fi mandatory data, plus configuration a field rules, error messages, an workflows fi incomplete records.
Legal and regulatory field requirementsClinical safety critical data elementsBilling and reimbursement driven fieldsConfiguring required versus optional flagsHandling incomplete or missing dataLesson 3Audit trails fi master data changes: required metadata (user, timestamp, reason) an retention requirementsDescribes how audit trails capture changes to admission master data. Covers required metadata like user, timestamp, an reason, plus retention rules, legal requirements, an how fi review an report pon historical changes.
Events that must be audited in HISUser, timestamp, and reason metadataViewing and exporting change historyRetention periods and legal demandsProtecting audit logs from tamperingLesson 4Admission-specific fields: admission date/time, admission type (elective/emergency), reason fi admission, referral sourceCovers admission specific fields like date an time, admission type, reason, an referral source. Explains dem impact pon clinical workflows, capacity planning, billing, an statutory reporting requirements.
Admission date and time capture rulesElective versus emergency admission typeClinical and administrative reason fieldsReferral source and pathway codingImpact on billing and official reportsLesson 5Duplicate detection methods: deterministic an probabilistic matchin, blockin keys, manual review workflowsCovers methods fi detect duplicate patient records usin deterministic an probabilistic matching. Explains blockin keys, similarity scorin, thresholds, an manual review workflows fi confirm, merge, or reject suspected duplicates.
Deterministic matching rules and limitsProbabilistic matching and scoringBlocking keys and index optimizationThresholds for auto and manual reviewReview queues and decision loggingLesson 6Data entry standards an value lists: controlled vocabularies, drop-downs, an validation rules fi reduce variationExplains how standardized value lists an validation rules improve admission data quality. Covers controlled vocabularies, dropdowns, code systems, an format checks fi reduce variation, typos, an incompatible entries cross systems.
Designing controlled vocabulariesDropdowns and search based selectionCode systems and local value mappingSyntactic and semantic validation rulesMaintaining and updating value listsLesson 7Ward/bed/bed-management fields an responsible clinical team assignmentExplains how wards, rooms, an beds model inna HIS/KIS an link to patients. Covers assignin responsible clinical teams, handlin transfers, occupancy status, an ensurin accurate location data fi care, billin, an reportin.
Ward and room master data structureBed status codes and occupancy rulesAssigning responsible clinical teamHandling transfers and internal movesLocation data for billing and reportingLesson 8Common master data fields inna German HIS/KIS at admission (name, DOB, gender, insurance, Versichertenart)Introduces typical German HIS/KIS admission fields, includin personal data, insurance details, an Versichertenart. Explains field purpose, format expectations, an how dese values drive billin, reportin, an cross-system communication.
Core identity data: name, DOB, genderInsurance provider and contract detailsVersichertenart and coverage categoriesLanguage, religion, and special needsCountry, citizenship, and residency dataLesson 9Preventin duplicates durin registration: search strategies, alerts, an merge/merge reversal policiesFocuses pon preventin duplicate records at registration time. Covers effective search strategies, phonetic an fuzzy search, real time alerts, merge policies, an safe merge reversal procedures fi correct mistakes.
Standardized pre registration search stepsPhonetic and fuzzy search techniquesReal time duplicate alerts and warningsMerge policies and approval rulesMerge reversal and error correctionLesson 10Contact an demographic fields: address, emergency contact, next a kin, legal guardianDetails demographic an contact fields captured at admission, includin address, phone, emergency contacts, next a kin, an legal guardians. Explains usage fi communication, consent, billin, an data protection.
Patient address and contact channelsEmergency contact data and usageNext of kin and relationship detailsLegal guardian and custody fieldsData protection for contact details
