Clinical Prediction Rules(CPR) in Physiotherapy

Clinical prediction rules are research-based tools that quantify the contributions of relevant patient characteristicsto provide numeric indices that assist clinicians in making predictions. Clinical prediction rules have been used to describe thelikelihood of the presence or absence of a condition, assist in determining patient prognosis, and help the classification of patientsfor treatment. The recent rapid rise in the use of clinical prediction rules raises questions about the conditions under which theymay be used most appropriately. What is the potential role of clinical prediction rules in physiotherapy practice and what are thestrategies by which clinicians can determine their appropriate use for a given clinical setting? Conclusion Clinical predictionrules use quantitative methods to build upon the body of literature and expert opinion and can provide quick and inexpensiveestimates of probability. Clinical prediction rules can be of great value to assist clinical decision making but should not be usedindiscriminately. They are not a replacement for clinical judgment and should complement rather than supplant clinical opinionand intuition. The development of valid clinical prediction rules should be a goal of physiotherapy research. Specific areas in needof attention include deriving and validating clinical prediction rules to screen patients for potentially serious conditions for whichcurrent tests lack adequate diagnostic accuracy or have unacceptable cost and risk, and to assist in classification of patientsfor treatments that are likely to result in substantially different outcomes in heterogeneous groups of patients. [Beattie P andNelson R (2006) Clinical prediction rules: What are they and what do they tell us? Australian Journal of Physiotherapy52: 157–163]

Source- http://ajp.physiotherapy.asn.au/AJP/52-3/AustJPhysiotherv52i3Beattie.pdf
Improve decision making in the PT practice.
Provide PTs with diagnostic information gleaned from the H&P the can serve as an accurate predictor calling for more expansive diagnostic testing.
Assist with subgrouping patients into more specific classifications that allow for better choices for treatment strategies.
Assist in determining when a particular treatment may not be beneficial.