Individual research recommendation details

Recommendation ID

CG123/5

Question

Use of a simple algorithm compared with a standard clinical assessment:- For people with a common mental health disorder, is the use of a simple algorithm (based on factors associated with treatment response), when compared with a standard clinical assessment, more clinically and cost effective?

Any explanatory notes
(if applicable)

Why is this important?:- There are well-established systems for the assessment of mental states, in primary and secondary care services, for common mental health disorders. One key function of such assessment is to identify both appropriate treatments and to obtain an indication of likely response to such treatments, thereby informing patient choice and leading to clinically and cost-effective interventions. Although the reliability of diagnostic systems is much improved, data on appropriate treatment response indicators remain poor, with factors such as chronicity and severity emerging as some of the most reliable indicators. Other factors may also be identified, which, if they could be developed into a simple algorithms, could inform treatment choice decisions at many levels in the healthcare system. Treatment choice can include complex assessment and discussion of options but the validity of such assessments appears to be low. Would the use of a number of simple indicators (for example, chronicity, severity and comorbidity) provide a better indication of likely treatment response? Using existing individual patient data, could a simple algorithm be developed for testing in a prospective study?
This should be tested in a two-stage programme of research: first, a review of existing trial datasets to identify potential predictors and then to develop an algorithm; second, a randomised controlled trial in which the algorithm is tested against expert clinical prediction.

Source guidance details

Comes from guidance

Common mental health problems: identification and pathways to care

Number

CG123

Date issued

May 2011

Other details