Some thoughts on health and healthcare

Introduction A “shift-left” data quality strategy in an Electronic Health Record (EHR) means that data are validated, standardized, governed, and made clinically usable at the point where they are created, rather than corrected later in a data warehouse, registry, audit process, medical coding or AI pipeline. In a European acute hospital, this is not merely an informatics improvement. It is a patient-safety intervention, a clinical governance obligation, and a regulatory compliance strategy under the General Data Protection Regulation (GDPR), the European Health Data Space Regulation (EHDS), and the Artificial Intelligence Act when EHR data feed AI-enabled clinical decision support systems. The central argument of my essay is that a shift-left EHR data quality strategy should be implemented as a risk-based clinical safety programme, not as a purely technical data-cleaning project. It should prioritize data elements that directly affect diagnosis, medication safety, care escalation, han...

Abstract An acute hospital can be clinically successful and financially healthy only when quality management, clinical practice, operational efficiency, patient outcomes, and reimbursement are governed as one integrated system. The Donabedian model provides the conceptual logic: structures shape care processes, and processes determine outcomes. Value-based healthcare (VBHC) adds the strategic objective: maximize patient-relevant outcomes relative to the cost of achieving them. Evidence-based medicine and evidence-based practice provide the epistemic standard for clinical decisions, while Diagnosis Related Groups (DRG) impose a financial discipline by linking hospital revenue to case mix, coding, resource use, and length of stay. Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) ensure that “success” is not reduced to mortality, complications, throughput, or margin alone. The Electronic Health Record (EHR), supported by Clinical Decision Support ...

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 ...