The development of biomedical signal processing algorithms typically assumes that the data can be sampled at an uniform rate and without loss of samples. Although this is a valid assumption for Holter applications or clinical testing, these assumptions become questionable in the presence of remote monitoring of patients through inherently lossy communication networks. The task for the networking engineers has been to create better, more reliable algorithms to avoid packet losses from affecting the signal processing algorithms. The questions this paper poses are ii) how would the current algorithms react to losses, and ii) what alternatives are available to still guarantee reliable monitoring and detection of emergency events. For the latter, we consider two options: the use of current algorithms after a loss concealment stage, and the design of loss aware algorithms. We propose a simple, yet powerful model of the network under a variety of packet loss channels as well as data packetization mechanisms. Extensive numerical results are provided for the sensitivity and predictivity of standard EKG algorithms under a variety of network scenarios, showing that even small percentages of packet losses can have a significant impact on the algorithm’s performance. We use the MIT- BIH arrhythmia database and simple loss concealment mechanisms to illustrate the caveats and opportunities of future, network-aware biomedical algorithms.