Outcomes of educational interventions in type 2 diabetes: WEKA data-mining analysis

Objective: To analyze which factors contribute to improvement in glycemic control in educational interventions in type 2 diabetes reported in randomized controlled trials (RCT) published in 2001-2005. Methods: Papers were extracted from Medline and Scopus using educational intervention and adults with type 2 diabetes as keywords. Inclusion criteria were RCT design. Data were analyzed with a data-mining program. Results: Of 464 titles extracted, 21 articles reporting 18 studies met the inclusion criteria. Data mining showed that for initial glycosylated hemoglobin (HbA1c) level ≤7.9% the diabetes education intervention achieved a small change in HbA1c level, or from +0.1 to -0.7%. For initial HbA1c ≥8.0%, a significant drop in HbA1c level of 0.8-2.5% was found. Data mining indicated that duration, educational content and intensity of education did not predict changes in HbA1c levels. Conclusion: Initial HbA1c level is the single most important factor affecting improvements in glycemic control in response to patient education. Data mining is an appropriate and sufficiently sensitive method to analyze outcomes of educational interventions. Diversity in conceptualization of interventions and diversity of instruments used for outcome measurements could have hampered actual discovery of effective educational practices. Practice implications: Participation in educational interventions generally seems to benefit people with type 2 diabetes. Use of standardized instruments is encouraged as it gives better opportunities to identify conclusive results with consequent development of clinical guidelines.