Classification of Digital Health Interventions v 1.0

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Publish Date
Nov 16, 2022
 

Defining the Classification of Digital Health Interventions

The classification of digital health interventions is a way to categorize the different types of digital health interventions. It helps to understand the different types of interventions and how they can be used in different situations.
The primary target of this is the public health audience. It aims to promote an accessible and bridging language for health program planners to articulate the functionalities of digital health implementations.
 
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Source: WHO
 
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The WHO Classification of digital health interventions v1. 0 provides a shared language to describe the uses of digital technology for health, specifying discrete digital capabilities applicable to clients, health workers, health system managers, and data services.
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Benefits of Classification in Digital Health Interventions

Classification is a method of organizing and analyzing data. It is often used in digital health interventions to categorize patients into groups with similar characteristics, who can then be assigned to the same treatment.
Classification can be used for many benefits, such as:
  • Improving patient outcomes by assigning them to the most appropriate treatment group
  • Lowering costs by assigning patients to treatments that are more affordable
  • Reducing the risk of adverse events by assigning patients who have a history of these events to the appropriate treatment groups
This classification of Digital Health Interventions (DHIs) should be used in tandem with the of list Health System Challenges (HSC) in order to articulate how technology is addressing identified health needs, such as lack of service utilization.
 
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The Importance and Benefits of Classifying your Digital Intervention

Digital technologies such as wearables, websites, and mobile applications are increasingly used in interventions targeting physical activity (PA). Increasing access to such technologies makes an attractive prospect for helping individuals of low socioeconomic status (SES) in becoming more active and healthier. However, little is known about their effectiveness in such populations. The aim of this systematic review was to explore whether digital interventions were effective in promoting PA in low SES populations, whether interventions are of equal benefit to higher SES individuals and whether the number or type of behavior change techniques (BCTs) used in digital PA interventions was associated with intervention effects.
 

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