Surgical research review

Using quality-of-life measurements in clinical practice

Assimilating quality-of-life information into clinical practice

Information from quality of life research can be applied at the macro, meso, or micro levels. The macro level of decision-making affects large communities of people, such as a governmental jurisdiction. The meso level affects a targeted group of patients. The micro level deals with the individual patient with the purpose of effecting a health benefit for that patient.⁶ It is at this level, that of the individual patient, on which this review will focus its attention.

Most surgeons will receive

Using quality-of-life data in clinical decision-making

When surgeons would initially use quality-of-life information is in making a treatment choice for a particular patient. Essentially this is taking meso-level data and applying it to the micro level. As with any application of clinical research to the individual patient, the first question to ask is, “Is my patient in the same group of patients in which the intervention worked?” For example, a quality of life study of the effects of doxorubicin-based chemotherapy after operations for breast

Caveats and difficulties

There are several caveats and difficulties in the use of quality-of-life measures in clinical practice5, 36 which can be divided generally into instrument-related, clinician-related, health care delivery system–related, and patient-related. With respect to instruments, the problem centers on which instruments to use and when. There is no universal instrument that is valid, reliable, appropriate for the disease or its treatment, and assesses all of the aspects of quality of life important to the

Conclusions

Although applying quality-of-life measures to everyday clinical practice poses challenges, there are clear advantages to the physician and to the patient. The most important of these is in treatment choice, when treatments are primarily for symptom relief or if treatments may have noticeable side effects. Clinical decision-making can be enhanced using such measures as predictive or prognostic tools and in monitoring patient response to treatment or disease recurrence. Communication with