Who will do well, who will not?

This post was chosen as an Editor's Selection for ResearchBlogging.org
If I had a crystal ball, and could decide who would do well in self managing their pain, and who would not, what would I do? A holy grail for insurance companies and health economists and yes, clinicians, is to find some precise way to decide who needs the most help with their pain, and who will manage well without as much assistance – with the ultimate aim to reduce disabilty and therefore costs (both human and fiscal).

The problem is that so far, the experience of pain can’t be objectively measured, and ultimately, it’s the person experiencing the pain who will do or not do, and we have no way of deciding whether the person ‘should’ or ‘should not’ be expected to function well.

This poses an enormous problem in health and insurance. How on earth do we decide who should remain ‘sick’ and receiving support, be excused from working, and remain a patient; how do we decide who should be obliged to pull themselves together and get back to work?

Oh if only it were simple.  The problem is that in pain, the relationship between things like pain intensity, tissue damage (impairment) and disability is not at all straightforward – and to add to the mix, doctors may not really believe in or have the confidence to manage the very factors that seem to have the most influence.

One assessment instrument I know well is the Multidimensional Pain Inventory (MPI). This was first developed by Turk and Rudy 1988, and aims to use the responses from the quite lengthy questionnaire to profile patients.  Three main classifications are found – Adaptive Copers, Interpersonally Distressed and Dysfunctional. Because this instrument has been used widely in both research and clinical settings, it seems reasonably clear that the three classifications are stable and can be used to predict current and future disability and even response to self management of pain.

Adaptive copers are found to be managing reasonably well, if they continue managing their pain the way they are, they will probably become somewhat less disabled and distressed over time; Interpersonally distressed people are likely to feel socially isolated or socially unsupported, and their relationships may be at risk – and this is likely to have long term impact on their disability; people classified into the  Dysfunctional group are probably going to remain disabled if they don’t receive assistance to manage their pain well – and even if they do receive treatment, may not respond as well to it as those in other groupings.

In the paper I’ve cited today, in the period of 7 years after a pain management programme, patients were monitored for their use of disability or sick days.  What was found was that those who were classified at treatment phase into the Dysfunctional group continued to use sick leave the most of the three groups even after treatment.

While this at face value looks rather sad for the utility of the pain management programmes, I should add that the difference between the Adaptive copers and the Dysfunctional group wasn’t statistically significant.  A more telling characteristic was that those in the Dysfunctional group who had used a lot of sick leave prior to the pain management programme were more likely to continue to do so after the programme.

What does this suggest?

1.  Psychological profiles can, and do, accurately predict outcomes even up to 7 years later.  Impairment/diagnosis/pain intensity doesn’t predict nearly as well, so why oh why is there so much reliance on these in compensation and insurance management?

2. A cynic might say ‘Why even try to treat people in the Dysfunctional group?’  After all, despite treatment, they continue to use sick leave, why not ignore that group and simply treat the others – catch the ‘low hanging fruit’ as it were.  Focus rehabilitative efforts on those who will benefit, and stop pouring resources at people who may not manage well despite our best efforts.

There’s some sense in doing just this.  Choose people who will benefit from a specific strategy, give them the best, then watch the results come in – it makes their lives better, it ensures your programmes outcomes are good, and it’s not nearly as challenging (and therefore it’s much easier) for clinicians to do the work.

The fly in the ointment is that the ongoing costs associated with those people who don’t do well is enormous.  Not only in direct costs of compensation or benefits, and not only in the human costs of their distress and suffering, but also in the associated costs of other health services people in this group end up using.  It’s this group of people who tend to seek more treatment for their pain, often of the biomedical kind, who develop comorbidities due to other health conditions, and who need supportive services like home help and social support more than those who do well.

It would be grand if psychosocial factors were truly accepted by all treatment providers (including doctors looking to abolish the pain) as more influential on outcomes than impairment and pain intensity.  The implication being that then these factors would get the attention much earlier and more intensively than they are currently – and maybe fewer people would land up in the ‘Dysfunctional’ group.

I would love to see self management promoted by all clinicians working in chronic pain management as the ideal.  I’d also love it if self management wasn’t seen as a failure of pain reduction approaches.

Bergström, G., Bergström, C., Hagberg, J., Bodin, L., & Jensen, I. (2010). A 7-year follow-up of multidisciplinary rehabilitation among chronic neck and back pain patients. Is sick leave outcome dependent on psychologically derived patient groups? European Journal of Pain, 14 (4), 426-433 DOI: 10.1016/j.ejpain.2009.06.008


    1. That’s definitely a truism – but still raises my point, do we then not offer input to those who have never managed well, because the treatment predictors show they won’t do well? Or should we offer increased input to this group because they need more? I’m still uncertain…

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