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SNOMED CT During the Admission: A Realistic Operating Model for Concurrent Care-Process Management, Quality Control, and Quality Assurance in a General Hospital

Abstract The central implementation question is not whether SNOMED CT can improve coding at discharge, but whether it can become part of the care process itself. The answer is yes, but only under specific socio-technical conditions. SNOMED CT is most useful during admission when it is used as the semantic layer for working diagnoses, procedural events, pathway activation, clinical context, task orchestration, and real-time feedback , rather than as a retrospective abstraction exercise. Official SNOMED CT guidance explicitly frames the terminology as a means to “collect once and use many times,” and as an enabler of point-of-care analytics, decision support, and reporting that directly benefit clinicians and patients. In practice, this means that diagnoses and procedures must be recorded in small, workflow-specific SNOMED CT subsets; linked to timestamps, locations, and care states; and continuously reused for clinically relevant alerts, meaningful dashboards, and quality assurance (QA...
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From Hospital Building to Hospital System: How Structure, Organization, and Process Management Are Likely to Evolve in a Hybrid Era

Introduction A terminology of "monoliths" for "High-Complexity Hubs" and "swarms" for "Distributed Care Network" is evocative rather than standard in health-services research, but it captures a real and increasingly well-documented transformation. The academic and policy literature more commonly describes this transition as a move toward  centralization of high-complexity services  alongside  decentralization of appropriate care  through integrated, people-centred networks, telemedicine, hospital-at-home models, virtual wards, and hub-and-spoke systems. In that sense, the future hospital is not disappearing; it is being reconstituted as a  networked institution : centralized where rarity, risk, and capital intensity require concentration, and decentralized where continuity, accessibility, and lower-acuity care favor delivery closer to the patient. In this essay I want to argue that hospitals will evolve along three interlocking dimensions.  S...
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A Belgian Implementation Blueprint for WHO ICD-11/WHO ICHI-Based MDCs and DRGs in Relation to SNOMED CT

Abstract A defensible Belgian pathway to Major Diagnostic Categories (MDCs) and Diagnosis Related Groups (DRGs) based on WHO ICD-11 and WHO ICHI could be built as a three-layer architecture: SNOMED CT for point-of-care clinical semantics, WHO ICD-11 Mortality and Morbidity Statistics (MMS) and WHO International Classification of Health Interventions (ICHI) for classification of diagnoses and interventions, and a transparent national grouper that consumes standardized episode variables and produces reimbursement classes. That architecture should not assume the existence of an official global SNOMED CT→WHO ICD-11 or SNOMED CT→WHO ICHI reimbursement-grade map. WHO states that the outcome of WHO ICD-11/SNOMED CT mapping collaboration remains under discussion and is not guaranteed, while WHO’s ICD-11 licensing materials also state that mappings and crosswalks are not covered by the base WHO ICD-11 licence and may require separate written agreement. SNOMED International documents official ma...
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Implementing abuse and fraud detection in DRG-based payment: an integrated approach using analytics, patient-level costing, and evidence-based practice

1. Introduction Major Diagnostic Categories (MDCs) and Diagnosis-Related Groups (DRGs) underpin prospective (case-based) payment by assigning inpatient stays to clinically coherent groups and paying a predetermined amount based largely on a relative weight (resource intensity) multiplied by a standardized/base rate, with further policy adjustments (e.g., wage index, teaching, disproportionate share, outliers). Under Medicare’s Inpatient Prospective Payment System (IPPS), for example, the US  Office of Inspector General (OIG) in the USA describes the operational payment logic as “DRG weight × standardized amount,” with additional adjustments layered onto the base payment. Prospective payment improves cost discipline, but it also creates predictable gaming surfaces: when revenue depends on coded diagnoses/procedures and discharge status, some actors can increase payment by manipulating codes, fragmenting bills, or selecting “profitable” patients (cherry picking/lemon dropping). The ...
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