Article Text

PDF

The right treatment to the right patient at the right time
  1. E M H Haldorsen
  1. Haukeland University Hospital, Bergen, Norway
  1. Correspondence to:
 Dr Psychol E M H Haldorsen, The Outpatient Spine Clinic, Haukeland University Hospital, Box 1, 5021 Bergen, Norway; 
 ellen.haldorsen{at}haukeland.no

Statistics from Altmetric.com

A multitude of variables have been presumed to influence and predict return to work

In an attempt to prevent a development to chronic pain (which concerns about 10%), occupational physicians and other health professionals should be able to identify patients with a high risk of chronic disability at an early stage. It is well known that the longer individuals are out of work, the less likely they are to return to work. A multitude of variables have been presumed to influence and predict return to work. The most commonly assessed predictors include medical factors, sociodemographic factors, job related information, and psychological variables. There has been growing recognition that the lack of consistency in reporting findings in this area may be due to the heterogeneity of the patients studied. In general, combinations of sets of predictors seem more important than single predictors.

The article by Hogg-Johnson and Cole in this issue1 is a methodologically strong addition to publications in this important field. In a prospective cohort of 907 injured workers (mean age 38.6 years; 49% men; 59% back injuries, 27% upper limb injuries, and 15% lower limb injuries), they have developed a model of prognosis predicting length of time receiving workers’ compensation benefits using factors measured during the initial four weeks. The data were collected by telephone interviews, first at baseline (the first contact), then at 4, 10, 16, and 52 weeks post-injury. Workers were recruited at workers compensation claim registration. Outcome was duration on total temporary wage replacement benefits.

The authors found that body region specific functional status, change in pain, workplace offers of arrangements for return to work, and recovery expectations were independently predictive of time on benefits (see table 5). Based on a risk score (the vector of selected variables), the patients were divided into six groups from very low risk to very high risk (see fig 2). At four months, only one third of the highest risk group had gone off benefits. In comparison, over 95% in the lowest risk group had done so.

It was surprising that the authors ended up with as many as six prognostic groups. In their predictive study among acute and subacute back pain patients, Linton and Hallden used three groups.2 In a randomised controlled study by Haldorsen et al, the patients, who were long term sick listed because of musculoskeletal pain, were divided into good, medium, or poor prognosis by using a standardised psychological–physiotherapeutic screening instrument.3 I think it is necessary to investigate this further on. How many prognostic groups are actually necessary for giving the right treatment to the right patient at the right time? Are there any sex differences concerning the characteristics of the patients in the different groups?

“How many prognostic groups are actually necessary for giving the right treatment to the right patient at the right time?”

There are several strengths in this study—investigation of early prognostic factors for chronic pain from acute pain, relatively large sample group, large number of variables included, and time dependent nature of potential prognostic factors have been taken into account, for example, “change in pain”. On the other hand, the prognosis was measured by the patient’s own report; the authors did not use any objective measures. I miss an explanation of why they chose not to include objective measures of functional capacity. Furthermore, the authors use a classification unknown to me of the different complaints (back pain, upper limb, and lower limb). What is meant by back pain, both upper and lower back? What about upper limb—do these patients also have neck pain? I also wonder whether the authors have available information about which type of treatment (if any) the patients have participated in during the follow up period.

In the last sentence of the discussion, the authors write: “ ... these results may lead to interventions which will facilitate more rapid return to work ...” In our study we found that choice of treatment (ordinary treatment, light multidisciplinary, or extensive multidisciplinary treatment) was especially important for patients classified to have poor prognosis for return to work. Extensive multidisciplinary treatment for these patients seemed to be superior both from the patient’s point of view, as well as from an economic perspective. The patients classified as having a good prognosis had no additional treatment effect measured by return to work by participating in an extensive multidisciplinary treatment programme.3

The results of prognostic studies give evidence for a better utilisation of the resources by performing an easy screening of the patients before treatment, and allocating the patients to adequate treatment. We found that mostly men (61%) were classified as having a good prognosis, while women (71%) were classified as having a medium or poor prognosis. In addition, we found that older patients were found to a greater extent to have poor prognosis, compared with younger patients.3 These findings are not supported by the study by Hogg-Johnson and Cole.1

Hogg-Johnson and Cole1 found that workplace offers of arrangements for return to work were predictive of time on benefits. Another study by Haldorsen et al showed that follow up meetings between supervisors and employees seemed to be important in enhancing work environmental changes and increasing the number of employees returning to work.4

Patients with low back pain constitute a heterogenous group and I believe that there never will be a single test or a single question that will work for all patients. Used in the right way a simple screening instrument can help health professionals better identify patients who may have poor prognosis for return to work, but we have to be flexible in the use of such an instrument. We must be aware of what and how we communicate to the patient, and what treatment we offer. Besides information and fear reduction, increasing activity despite pain, and frequent follow up seem to be important factors in handling chronic low back pain.5

The results of the study by Hogg-Johnson and Cole1 are interesting (also because of the statistical methods used) and need to be investigated further. A short screening instrument for identification of patients with different prognosis for return to work will also be of great value in the clinical guidelines for patients with low back pain.

A multitude of variables have been presumed to influence and predict return to work

REFERENCES

View Abstract

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.