Introduction: Systematic reviews often form the basis of evidence-based guidelines. However, studies have shown that clinicians are often not familiar with sytematic reviews or guidelines due to their long and unwieldy nature and are therefore not able to apply them appropriately during the clinical care process. In order to encourage implementation of evidence, a clear, succinct healthcare pathway is needed. This can be achieved through a clinical guideline algorithm.
A guideline algorithm is a flow chart of the recommendations described in the guideline, where boxes define the clinical problem leading to a clear decision point. A logical sequence should be maintained so that all decisions flow from the questions that precede them.
Development of the UK NICE clinical guideline for the primary and secondary prevention of osteoporotic fracture resulted in the synthesis of large amounts of evidence based on a number of systematic reviews and health technology appraisals. This presented the challenge to develop an effective management algorithm that could easily be used in clinical practice and validly summarise the evidence.

Objective: To develop an algorithm to crystallize the guidelines key management recommendations for the primary and secondary prevention of osteoporotic fracture

Methods: Following the synthesis of evidence for the guideline, recommendations were drafted for risk assessment, diagnosis and treatment of patients at high risk of osteoporotic fracture. In order to develop the algorithm, descriptor variables were selected for these areas of the guideline. Care was taken to ensure that the variables were clearly accessible and observable. The main outcome of the algorithm is to prevent fracture from occurring. The algorithm was developed by sketching out sets of boxes containing either 'yes' or 'no' questions, flowing into answer boxes. Difficulties encountered in reducing systematic review evidence to an algorithm are described.

Results: The resulting clinical algorithm can assist clinicians in both primary care and public health to successfully identify and treat patients at high risk of osteoporosis.

Conclusion: Clinical algorithms can validly summarise systematic reviews in a format which helps with comprehension and application of complex clinical evidence