Lesson 1Administrative identifiers: patient ID, case number, insurance number, and national identifiersExplains key administrative identifiers used in German HIS/KIS, such as patient ID, case number, insurance number, and national identifiers. Covers formats, uniqueness, assignment rules, and 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 and business rules: required vs optional fields and rationaleDetails which admission fields must be captured, which are optional, and why. Explains legal, clinical, and billing drivers for mandatory data, plus configuration of field rules, error messages, and workflows for 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 for master data changes: required metadata (user, timestamp, reason) and retention requirementsDescribes how audit trails capture changes to admission master data. Covers required metadata such as user, timestamp, and reason, plus retention rules, legal requirements, and how to review and report on 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 for admission, referral sourceCovers admission specific fields such as date and time, admission type, reason, and referral source. Explains their impact on clinical workflows, capacity planning, billing, and 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 and probabilistic matching, blocking keys, manual review workflowsCovers methods to detect duplicate patient records using deterministic and probabilistic matching. Explains blocking keys, similarity scoring, thresholds, and manual review workflows to 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 and value lists: controlled vocabularies, drop-downs, and validation rules to reduce variationExplains how standardised value lists and validation rules improve admission data quality. Covers controlled vocabularies, dropdowns, code systems, and format checks to reduce variation, typos, and incompatible entries across 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 and responsible clinical team assignmentExplains how wards, rooms, and beds are modelled in HIS/KIS and linked to patients. Covers assigning responsible clinical teams, handling transfers, occupancy status, and ensuring accurate location data for care, billing, and reporting.
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 in German HIS/KIS at admission (name, DOB, gender, insurance, Versichertenart)Introduces typical German HIS/KIS admission fields, including personal data, insurance details, and Versichertenart. Explains field purpose, format expectations, and how these values drive billing, reporting, and cross-system communication.
Core identity data: name, DOB, genderInsurance provider and contract detailsVersichertenart and coverage categoriesLanguage, religion, and special needsCountry, citizenship, and residency dataLesson 9Preventing duplicates during registration: search strategies, alerts, and merge/merge reversal policiesFocuses on preventing duplicate records at registration time. Covers effective search strategies, phonetic and fuzzy search, real time alerts, merge policies, and safe merge reversal procedures to 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 and demographic fields: address, emergency contact, next of kin, legal guardianDetails demographic and contact fields captured at admission, including address, phone, emergency contacts, next of kin, and legal guardians. Explains usage for communication, consent, billing, and data protection.
Patient address and contact channelsEmergency contact data and usageNext of kin and relationship detailsLegal guardian and custody fieldsData protection for contact details
