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1.
Healthcare Informatics Research ; : 112-122, 2022.
Article in English | WPRIM | ID: wpr-925042

ABSTRACT

Objectives@#The aim of this study was to characterize the benefits of converting Electronic Medical Records (EMRs) to a common data model (CDM) and to assess the potential of CDM-converted data to rapidly generate insights for benefit-risk assessments in post-market regulatory evaluation and decisions. @*Methods@#EMRs from January 2013 to December 2016 were mapped onto the Observational Medical Outcomes Partnership-CDM (OMOP-CDM) schema. Vocabulary mappings were applied to convert source data values into OMOP-CDM-endorsed terminologies. Existing analytic codes used in a prior OMOP-CDM drug utilization study were modified to conduct an illustrative analysis of oral anticoagulants used for atrial fibrillation in Singapore and South Korea, resembling a typical benefit-risk assessment. A novel visualization is proposed to represent the comparative effectiveness, safety and utilization of the drugs. @*Results@#Over 90% of records were mapped onto the OMOP-CDM. The CDM data structures and analytic code templates simplified the querying of data for the analysis. In total, 2,419 patients from Singapore and South Korea fulfilled the study criteria, the majority of whom were warfarin users. After 3 months of follow-up, differences in cumulative incidence of bleeding and thromboembolic events were observable via the proposed visualization, surfacing insights as to the agent of preference in a given clinical setting, which may meaningfully inform regulatory decision-making. @*Conclusions@#While the structure of the OMOP-CDM and its accessory tools facilitate real-world data analysis, extending them to fulfil regulatory analytic purposes in the post-market setting, such as benefit-risk assessments, may require layering on additional analytic tools and visualization techniques.

2.
Singapore medical journal ; : 393-400, 2015.
Article in English | WPRIM | ID: wpr-337122

ABSTRACT

<p><b>INTRODUCTION</b>As the effectiveness of intensive glycaemic control is unclear and recommended glycaemic targets are inconsistent, this study aimed to ascertain the prevalence of dysglycaemia among hospitalised patients with diabetes mellitus in an Asian population and evaluate the current standards of inpatient glycaemic control.</p><p><b>METHODS</b>A retrospective observational study was conducted at a secondary hospital. Point-of-care blood glucose (BG) values, demographic data, medical history, glycaemic therapy and clinical characteristics were recorded. Dysglycaemia prevalence was calculated as proportions of BG-monitored days with at least one reading exceeding the cut points of 8, 10 and 15 mmol/L for hyperglycaemia, and below the cut point of 4 mmol/L for hypoglycaemia.</p><p><b>RESULTS</b>Among the 288 patients recruited, hyperglycaemia was highly prevalent (90.3%, 81.3% and 47.6% for the respective cut points), while hypoglycaemia was the least prevalent (18.8%). Dysglycaemic patients were more likely than normoglycaemic patients to have poorer glycated haemoglobin (HbA1c) levels (8.4% ± 2.6% vs. 7.3% ± 1.9%; p = 0.002 for BG > 10 mmol/L) and longer lengths of stay (10.1 ± 8.2 days vs. 6.8 ± 4.7 days; p = 0.007 for BG < 4 mmol/L). Hyperglycaemia was more prevalent in patients on more intensive treatment regimens, such as basal-bolus combination therapy and the use of both insulin and oral hypoglycaemic agents (100.0% and 96.0%, respectively; p < 0.001 for BG > 10 mmol/L).</p><p><b>CONCLUSION</b>Inpatient glycaemic control is suboptimal. Factors (e.g. type of treatment regimen, discipline and baseline HbA1c) associated with greater prevalence of dysglycaemia should be given due consideration in patient management.</p>


Subject(s)
Aged , Female , Humans , Male , Middle Aged , Blood Glucose , Diabetes Mellitus , Drug Therapy , Hospitals , Hyperglycemia , Drug Therapy , Hypoglycemia , Drug Therapy , Hypoglycemic Agents , Therapeutic Uses , Inpatients , Insulin , Therapeutic Uses , Point-of-Care Systems , Prevalence , Retrospective Studies , Singapore , Treatment Outcome
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