Low Indexes of Metabolism - Information to Teams (LIMIT)

Overview

The purpose of this study is to determine whether alerting primary care providers by email about low values of BMI, HbA1c% or cholesterol will affect treatment and improve overall survival and other health indexes of people older than 75 years.

Scientific background Interventions aimed to ameliorate malnutrition are important for elderly health and include dietary counseling and discontinuing unnecessary medicines. Emailing an alert regarding low BMI was found to improve dietary counseling numbers. Correlation between death and HbA1c% is U-shaped, with increased mortality under a 6.5% level in patients taking two anti-diabetic medicines. Sending an email alert regarding an over-tight control of diabetes was followed by a reduction in mortality. Death and cholesterol correlation is also U-shaped, with increased mortality and morbidity under 160 mg%. The investigator found no interventional study for this situation. Objectives To check whether alerting the primary care providers by email, about low values of BMI, HbA1c% or cholesterol will affect treatment and improve health indexes of people older than 75 years. Working hypotheses During a year, and relative to the control group, intervention emails may result in the following: * A decrease in mortality. * An increase in dietary counseling percentage and a decrease in prescribing anti-diabetic and cholesterol-lowering medicines. * A decrease in medical expenses and in other morbidity indexes. Type of research and methods of data collection This randomized controlled trial will be conducted entirely through the existing computer system. The participants (patients) will be assigned to the two Arms/Groups "Intervention Email" and "Control". It has three separate interventions: a. Alerting about a significant drop in BMI. b. Alerting about a low HbA1c% level in patients taking anti-diabetics. c. Alerting about a low cholesterol level in patients taking cholesterol-lowering medicines. The alerts will be sent to the primary clinicians. Method(s) of data analysis Differences between intervention groups and control groups will be analyzed using Chi-square test (or Fishers' exact test) for categorical variables and using T-test (or Two-sample Wilcoxon test) for continuous variables. Uniqueness and relevance Health service policy regarding signs of malnutrition and excessive medicinal treatment needs a relevant scientific knowledge base. Nutritional counseling and revision of medicinal treatment may dramatically affect health. This research deals with questions that have no commercial interest, but are important to the public.

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