The Right E-Health Module Directly from the EHR

Challenge

Hundreds of specialised e-health modules make it difficult to choose the most relevant option quickly.
Searching external catalogues takes up clinical time and adds administrative pressure.
As a result, the potential of personalised hybrid care remains partly untapped.

From overload to overview

E-health platforms keep adding more specialised modules.
No clinician can know every module, target group and application.
Manual searching costs time, and suitable support is deployed late or not at all.

Result

Top 5/10personalised module recommendations based on current client context

1 clickto continue from a recommendation to the relevant module

Solution

01The assistant analyses relevant EHR data, including diagnosis, intake and questionnaires.
02Client context is matched with the metadata and content of the e-health catalogue.
03Opening the care plan triggers the selection at the point of decision.
04The clinician chooses and assigns the relevant module while retaining professional control.

A smart AI integration between the EHR and Minddistrict

How can a mental healthcare organisation help clinicians find exactly the right training for a client among hundreds of available e-health modules, without adding administrative pressure? Ideal Shift AI developed an intelligent digital assistant that connects the EHR with e-health platforms such as Minddistrict.

By combining available client information with the characteristics of the full e-health catalogue, the clinician receives evidence-informed, personalised recommendations. They appear not in a separate system, but precisely when the care plan is being created or updated.

From information overload to personalised care

E-health platforms offer an ever-growing range of specialised modules. This is valuable, but makes it practically impossible for clinicians to know every module, target group and potential application. Manual searching takes time and can mean that suitable digital support is used late or not at all.

The digital assistant takes over the demanding search and comparison work. The clinician remains in control and receives a concise, relevant selection instead of an entire catalogue.

How does the AI assistant work?

Data analysis: the assistant uses relevant available EHR context, including diagnosis, intake forms and questionnaires.

Metadata matching: this context is compared with the content, target groups and characteristics of the available Minddistrict modules.

Smart selection: the match produces a personalised top five or top ten of the most relevant modules.

Seamlessly embedded in the workflow

The recommendations appear when the clinician opens the care plan in the EHR. Rather than adding another task, the support becomes part of the existing decision-making moment.

After selecting a recommended training, such as Understanding your ADHD or Reducing social anxiety, the connection to Minddistrict opens. The clinician can then assign the selected module to the client.

What does it deliver?

Less search time because relevant e-health options are ready inside the EHR

Faster access to modules aligned with the client's current care needs

A lower barrier to making digital care part of regular treatment

Contextual support at the exact moment a decision is made

Human control over every final choice and assignment

From hundreds of e-health modules to the right top five directly in the EHR