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POINT OF CARE - DIABETES (POC-D) Revolutionizing diabetes care in resource limited settings

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  Point-of-Care Diabetes Model  ABSTRACT: We summarize key patient variables by domain, noting their relevance to glycemic control and complication risk. Adults with Type 1 and Type 2 diabetes are considered separately. Each bullet below lists variables that can be measured at low cost (anthropometry, basic labs, etc.) or important phenotypic/genetic factors. Type 1 Diabetes Variables ·          Demographics (Age, Sex): Age at onset and current age affect disease course. Adult-onset T1D (LADA) often has slower progression, whereas younger adults may have more labile control. (No specific citation; clinical observation.) ·          Anthropometric (Height, Weight, BMI, Waist): Weight and BMI are used for insulin dosing. Excess weight in T1D (sometimes called “double diabetes”) reflects insulin resistance and raises cardiovascular risk. Normal-to-low BMI is common at onset, bu...
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What if we can organise the flow

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​ Large corporate hospitals with high patient volumes face several critical challenges in optimizing patient flow. The primary issue is systemic bottlenecks  that create cascading delays across the entire care continuum, from emergency department (ED) boarding to discharge coordination.[1][2]   Limited Real-Time Visibility Hospitals struggle with lack of real-time data on patient status, bed availability, and resource location across departments. Without integrated information systems providing live updates, administrators cannot respond quickly to surges in patient volume or identify emerging bottlenecks before they escalate. This creates blind spots that prevent efficient resource allocation during peak times.[3][2][1]   Bed Management and Discharge Delays Inefficient bed utilization and delayed discharge processes represent major obstacles. Room turnover delays and poor discharge coordination cause patients to occupy beds longer than necessary, limiting availability fo...
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