We introduce a new software, Efficient Detection of Hydrogen Bonds (EDHB), that systematically detects hydrogen bonds based on the nearest neighbors algorithm. EDHB classifies inter- and intramolecular hydrogen bonds as well as hydrogen bond networks. EDHB outperforms commonly used hydrogen bond detection methods in terms of speed of execution. An important additional feature of EDHB is that information from preceding quantum chemical studies (i.e., natural bond orbital analysis data and second energy derivative information) can be used to determine the electrostatic/covalent character of the hydrogen bonds and to calculate local-mode hydrogen bond force constants as a quantitative measure of their intrinsic strength. We applied EDHB to a diverse set of 163 proteins. We identified hydrogen bond networks forming intramolecular rings of different sizes as a common feature playing an important role for specific secondary structure orientations such as α-helixes and turns. However, these networks do not have a significant influence on the hydrogen bond strength. Our comprehensive local-mode analysis reveals the interesting result that the hydrogen bond angle is the governing factor determining the hydrogen bond strength in a protein. EDHB offers a broad range of application possibilities. In addition to proteins, EDHB can be generally used to detect and characterize hydrogen bonds in protein-ligand interactions, water clusters, and other systems where a hydrogen bond plays a critical role, as well as during molecular dynamics simulations. The program is freely available at https://github.com/ekraka/EDHB.