- A clinical predication rule (CPR) is a combination of clinical findings that statistically predicts the probability of a condition or outcome of a treatment.
- CPRs use condensed information and the smallest number of indicators possible to help clinicians make informed, efficient decisions.
- Commonly used clinical prediction rules include Wells Score, Ranson Criteria, Ottowa Ankle Rules and the Model for End-Stage Liver Disease.
- Clinical prediction rules may fall into one of three categories: diagnostic, prognostic or prescriptive.
- Diagnostic CPRs are designed to aid in determining the likelihood that a patient has or does not have a specific diagnosis.
- Prognostic clinical prediction rules predict the likelihood of a specific outcome, for example mortality.
- Clinical prediction rules that identity the best course of treatment or the best intervention for a specific type of patient are termed ‘prescriptive’ CPRs.
- CPRs are developed using a three-step process. First, factors with predictive value are identified. Second, the rule is tested. Last, usefulness is measured.
- The benefit? CPRs have advantages over human clinical decision-making. Rules are statistically tested removing human inconsistency from clinical judgment.
- Ultimately, clinical prediction rules can improve patient outcomes, save clinician time, decrease cost of care and increase patient satisfaction.
Taking the guesswork out of clinical decision making and instead relying on tried and true algorithms confers substantial advantages for the nurse practitioner. Relying on statistically based algorithms helps you as an NP make clinically sound decisions ensuring the best course of diagnosis, treatment and ultimately the best possible outcome for your patient. These rules back the decisions you make with science and stats protecting you legally and preventing unnecessary testing, a major pitfall of our medical system. Familiarity with clinical prediction rules pertaining to your specialty area is fundamental to helping guide your practice.
Which clinical prediction rules do you use in your specialty area?
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