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A swarm intelligence-based procedure to detect critical conditions of a patient, affected by a specific disease, at an early stage in absence of clinician, is proposed. The procedure is to be integrated inside a remote health care system for patients at home, where some physiological parameters related to a specific disease are being monitored. A significant variation in the monitored parameters can lead the patient to a critical state, thus the proposed method is aimed at predicting a possible future bad condition of the patient on the basis of past measurements. Moreover, different physiological parameters contribute to diverse degrees in dissimilar diseases; consequently, a swarm intelligence-based method is proposed for optimizing the weight of each parameter for a more accurate diagnosis. The proposed approach has been validated experimentally under the framework of the industrial research project Patient Diagnosis and Monitoring at Domicile (PADIAMOND: co-funded by EU and the company Filia srl, Caserta, Italy).