SNOWDROP: Big Data for the joint management of medication-related falls for senior citizens

Big Data for the collaborative management of medication-related falls for the elderly. In the elderly, falls are the leading cause of injury. Medications are a major risk factor for falls. Because we lack tools to assess individualized risk, general practitioners (GPs) struggle with fall-related medication management for seniors and senior patients are not well equipped to engage in collaborative management of their medications.

Our goal in this project is to develop and evaluate a comprehensive data-driven scientific approach for valid prediction of personal fall risk that effectively supports joint medication management between seniors and family physicians.

The project has two objectives:

  1. Develop and validate prediction models based on electronic medical records (EMR) for assessing individualized risk of medication-related falls, and understand model limitations;
  2. Develop and evaluate a collaborative medication management strategy for older patients and family physicians. The prediction model, along with statements, will be embedded in NHGdoc, a decision support system, and provide personalized information relevant to GPs through their EMR, and personalized information relevant to patients through a patient portal.

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