Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study |
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Affiliation: | 1. HEALTH—Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbh, Neue Stiftingtalstraße 2, 8010 Graz, Austria;2. Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria;3. Technical University of Graz, Institute of Health Care Engineering with European Notified Body of Medical Devices, Stremayrgasse 16/II, 8010 Graz, Austria;1. Paediatric Infectious Diseases, Rheumatology and Immunology Unit, Hospital Universitario Virgen del Rocío, Institute of Biomedicine of Seville (IBIS), Sevilla, Spain;2. Department of Pharmacy, Institute of Biomedicine of Seville (IBIS), Hospital Universitario Virgen del Rocío, Sevilla, Spain;1. School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran;2. Nutrition Research Center, Faculty of Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran;3. Students’ Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran;4. Nutritional Sciences Department, School of Nutritional Sciences and Food Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran;1. Department of Anesthesiology, Teikyo University, School of Medicine, University Hospital Mizonokuchi, 3-8-3 Mizonokuchi, Takatsu-ku, Kawasaki, Kanagawa 213-8507, Japan;2. Department of Medical Engineering, Teikyo University, School of Medicine, University Hospital Mizonokuchi, 3-8-3 Mizonokuchi, Takatsu-ku, Kawasaki, Kanagawa 213-8507, Japan;3. Engineering Development Division, Sango Co., Ltd, 5-35 Yawatayama, Miyoshi-cho, Miyoshi, Aichi 470-0224, Japan;4. Teikyo University Joint Program Center, 2-11-1 Kaga, Itabashi-ku, Tokyo 173-8605, Japan;5. Department of Anesthesiology, Saitama Medical University, Saitama International Medical Center, 1397-1 Yamane, Hidaka, Saitama 350-1241, Japan;1. Department of Nursing Science, University of Eastern Finland (UEF) (Faculty of Health Sciences), Kuopio, Finland;2. Clinical Development, Education and Research Unit of Nursing, Kuopio University Hospital (KUH), KYS, Finland;3. KUH, Clinical Education Center, Kuopio, Finland;4. Arcada University of Applied Sciences, Helsinki, Finland;5. KUH, Hospital Pharmacy, Kuopio, Finland;6. KUH, Science Service Center, Kuopio, Finland;7. Department of Nursing, Swansea University (College of Human and Health Sciences), Swansea, Wales, UK;8. Department of Nursing Science, UEF, Kuopio Campus, Kuopio, Finland |
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Abstract: | ObjectiveMost preventable adverse drug events and medication errors occur during medication ordering. Medication order entry and clinical decision support are available on paper or as computerized systems. In this post-hoc analysis we investigated frequency and clinical impact of blood glucose (BG) documentation- and user-related calculation errors as well as workflow deviations in diabetes management. We aimed to compare a paper-based protocol to a computerized medication management system combined with clinical workflow and decision support.MethodsSeventy-nine hospitalized patients with type 2 diabetes mellitus were treated with an algorithm driven basal-bolus insulin regimen. BG measurements, which were the basis for insulin dose calculations, were manually entered either into the paper-based workflow protocol (PaperG: 37 patients) or into GlucoTab®—a mobile tablet PC based system (CompG: 42 patients). We used BG values from the laboratory information system as a reference. A workflow simulator was used to determine user calculation errors as well as workflow deviations and to estimate the effect of errors on insulin doses. The clinical impact of insulin dosing errors and workflow deviations on hypo- and hyperglycemia was investigated.ResultsThe BG documentation error rate was similar for PaperG (4.9%) and CompG group (4.0%). In PaperG group, 11.1% of manual insulin dose calculations were erroneous and the odds ratio (OR) of a hypoglycemic event following an insulin dosing error was 3.1 (95% CI: 1.4–6.8). The number of BG values influenced by insulin dosing errors was eightfold higher than in the CompG group. In the CompG group, workflow deviations occurred in 5.0% of the tasks which led to an increased likelihood of hyperglycemia, OR 2.2 (95% CI: 1.1–4.6).DiscussionManual insulin dose calculations were the major source of error and had a particularly strong influence on hypoglycemia. By using GlucoTab®, user calculation errors were entirely excluded. The immediate availability and automated handling of BG values from medical devices directly at the point of care has a high potential to reduce errors. Computerized systems facilitate the safe use of more complex insulin dosing algorithms without compromising usability. In CompG group, missed or delayed tasks had a significant effect on hyperglycemia, while in PaperG group insufficient precision of documentation times limited analysis. The use of old BG measurements was clinically less relevant.ConclusionInsulin dosing errors and workflow deviations led to measurable changes in clinical outcome. Diabetes management systems including decision support should address nurses as well as physicians in a computerized way. Our analysis shows that such systems reduce the frequency of errors and therefore decrease the probability of hypo- and hyperglycemia. |
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Keywords: | Clinical decision support Medication management system Medication order entry Medication errors Type 2 diabetes mellitus Basal-bolus insulin therapy Best practice |
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