Guides for healthcare decision processes
Practical guides on pre-authorization, SUT compliance, clinical decision support and data protection. Each guide opens with a short answer, walks through the steps and answers common questions.
Reducing denials in health insurance pre-authorization
The main causes of pre-authorization denials are missing documents, coding errors, weak medical necessity and coverage gaps. Steps for hospitals and insurers.
Read the guidePreventing SUT non-compliance in SGK hospital billing
How hospitals prevent SUT non-compliance before billing SGK: checking discharge summaries, ICD-10 codes, required reports and invoice lines, and the role of AI.
Read the guideCriteria for choosing a hospital clinical decision support system
Choosing a hospital clinical decision support system: check local language and rules, in-house data, cited sources, EHR integration, validation and a POC.
Read the guideAI-assisted pre-authorization and fraud review in health insurance
How AI supports health insurance pre-authorization and fraud review: coverage, limit and clinical checks, fraud signals, and why the specialist decides.
Read the guideUsing AI without patient data leaving the institution
To use AI in healthcare under the GDPR and KVKK, keep patient data inside the institution, mask it in-house and make every output auditable. Steps and FAQs.
Read the guideThe patient digital twin in clinical decision-making
A patient digital twin merges HBYS and Medula records into one live profile. What it is, how it supports clinical decisions, how to build one, where data stays.
Read the guideHow general-purpose chatbots differ from clinical decision support systems
General-purpose chatbots are not tied to patient records or local rules. How clinical decision support systems differ, and safe-use principles for physicians.
Read the guideTurkish medical AI models and how they are built
What a Turkish medical AI model is and how it is built: continued pre-training (CPT), LoRA adapters, GraphRAG, agentic orchestration and clinical validation.
Read the guideThe role of agentic AI in clinical and administrative healthcare work
Agentic AI completes multi-step work by using tools. This guide covers where agents help in healthcare, their limits, the rule engine and human approval.
Read the guideGetting a safe second opinion from AI as a physician
Physicians get a safe AI second opinion by asking with clinical context, checking sources and reasoning, and protecting patient data. The decision stays theirs.
Read the guideAI in writing and structuring discharge summaries
AI can structure discharge summaries, suggest ICD-10 codes and check SUT billing consistency, while the physician approves text and codes. Steps for safe use.
Read the guideStarting a hospital AI project with a proof of concept
How to run an AI proof of concept in a hospital: a single process in scope, data kept in-house, success criteria set in advance, stakeholders and scale-up.
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Clinical intelligence that sees the unseen and anticipates what comes next.