By definition, voice recognition is the process of collecting and picking of voices and sounds and feeding them into a computer program as electric signals, so that they may be in future detected from the codes they have been assigned (Dahl, Tamparo, Pooler & Lindh, 2009). Every individual has his own unique voice and due to different dialects, different words may have different meaning in different contexts, and this poses a challenge to voice recognition (Casciato, 2011). For this reason, voice recognition uses two common approaches, the template matching and feature analysis approaches. Template matching is the most basic approach, whereby the data is fed as electronic data through the microphone through analog-to-digital converter. The meaning is then encoded and matched with the template. This is the more effective method of the two. Feature analysis on the second approach, and instead of using the exact words when uploading the templates, feature analysis uses the near-similar words. This means therefore that there is no total accuracy in retrieval and recognition of voice. In areas where correct message is critically needed, feature analysis system is not the ideal approach to use because information and messages may be distorted or misinterpreted. Voice recognition has been applied in many organizations and industries especially those that emphasize on efficient information, communication and technology because it has proved to be a fast and efficient way of relating and communication of message and information. The health industry is no exception. It has been applied in many health facilities in communication, with the advancement and development of information and technology in many states especially in the developed and the developing states (Dahl, Tamparo, Pooler & Lindh, 2009). It has been applied in the health facilities’ different departments such as the front office, hospital wards etc, and when well applied, it saves time and more clients are served per given time. Effectiveness of voice recognition Template marching is more effective compared to the feature analysis approach (Parente, Kock & Sonsini, 2004). In the health department, Electronic Health Record (EHR) has mainly been used in speech recognition. This is because it is an effective way of communication and relaying of message. Advantages Speech recognition saves time, which is important in every organization and with time, it also saves money. Speech recognition is a fast and efficient way of communication and passing a message to staff members and other concerned people. For example, speech recognition has been used to give lectures, whereby physicians use the voice recognition software to dictate notes. Application of Voice recognition voice recognition also enhances better use of computer information and technology. With the use of computer Information and Technology, it is easier to save the messages and retrieve them when needed. This reduces saving of work is easier because there is no bulk saving, since all that is needed is a memory card, CD or a diskette. That way, the message can easily be retrieved (Dahl, Tamparo, Pooler & Lindh, 2009). Disadvantages The use of voice recognition also comes with disadvantages. The