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The Use of Voice Recognition Software to Improve Efficiency in Clinical Documentation

The Use of Voice Recognition Software to Improve Efficiency in Clinical Documentation

Technology is the foundation of nursing informatics. One of the technologies related to this field is electronic health records (EHRs), designed to enhance care. It is becoming mandatory in clinical documentation, and three factors drive its adoption:

  • Federal government initiatives. Hospitals and clinicians who adopt EHRs and demonstrate their use in ways that can improve the effectiveness, safety, and quality of care receive incentive payments through Medicare.
  • A shift in reimbursement from fee for service to pay for performance or quality has encouraged healthcare organizations to adopt EHRs.
  • Such technology is associated with improved patient care by increasing patient documentation access and reducing medication errors.

The availability of patient data in the EHR system increases access to complete and accurate information for better decisions and the initiation of appropriate treatment. While adopting EHRs presents many benefits, physicians are reluctant to use them due to inherent problems because the technology increases physicians’ workload due to robust documentation, which also decreases the time for direct care.

Negative Impact of EHRs

Although the advent of an EHR has revolutionized nursing, its adoption rate is low due to the increased time burden of data entry. The use of technology for documentation requires more time as compared to paper records. Such an increase decreases the time necessary for interacting with patients and delivering direct care. According to Kapoor (2014), physicians in the emergency department spend 31% of their working time documenting in the EHR system or entering data in a computer and 25% delivering direct care to patients. Compared to paper records, electronic ones decrease time efficiency by approximately 8.4 to 17.4% (Kapoor, 2014). Such long documentation time leads to frustration on the part of physicians and patients.


Voice recognition software has effectively reduced clinical documentation time by enabling physicians to document in real-time. According to Kapoor (2014), it enables them to speak into a microphone as a computer system types their words on the screen. The software lets physicians record their observations, assessments, and treatment plans virtually anywhere to access the EHR. It eliminates the need for entering notes into a computer. After reviewing 42 articles, Ajami (2016) found out that the voice recognition application provides an opportunity for improving the documentation process by reducing the time for recording patient data. The study has also discovered that the time spent preparing and editing medical reports provided by the software is more than the one necessary for manual documentation by about 54 seconds (Ajami, 2016). However, voice recognition technology has significantly reduced documentation time by more than five days. As a result, the software increases the period physicians interact with patients by decreasing the time needed for typing by almost an hour daily. It leads to higher physician productivity. They spend many hours documenting in an EHR using a mouse and a keyboard. By reducing the documentation time, voice recognition software enables clinicians to spend more time with patients. However, the study found it could be more effective in computers with more than one user and noisy environments (Ajami, 2016). Noise may lead to transcription errors, which require time for editing, but the process is faster than either writing patient notes by hand or manual typing. Consistent with these findings, Hodgson, Magrabi, and Coiera (2017) have stated that the performance of voice recognition software may be affected by background noise and the quality of a microphone. The technology requires a noise-free environment to improve efficiency in clinical documentation. Since clinicians spend substantial time documenting patient data, integrating voice recognition software in an EHR is needed to improve efficiency.

Technological advancements have increased the availability of voice recognition software. Patel and Harbord (2012) note that it is installed in emerging technologies such as tablets and smartphones. Voice recognition can be undertaken using hand-held devices, eliminating the need to add more computers to ensure each device has one user. Hodgson et al. (2017) say voice recognition software reduces transcription expenses. A voice-driven EHR eliminates or reduces transcription time by allowing clinicians to document patient data.

Moreover, voice recognition software improves patient care by enabling the documentation of more detailed information and the faster delivery of results. Patient data recorded via voice contain details that physicians require to complete a patient assessment. The faster delivery of information enables the rapid formulation of treatment plans early enough to prevent complications of adverse medical effects.

The integration of voice recognition software into an EHR offers many benefits. It decreases documentation time, increases clinical contact with patients, and ensures accurate, high-quality, and detailed notes. Hodgson et al. (2017) assert that continued improvement in voice recognition technologies will offer more benefits. Its accuracy and speed may eliminate the barrier to the adoption of EHRs by improving the data entry process. However, training is needed to successfully integrate voice recognition software in the EHR system. A study conducted by Patel and Harbord (2012) found that clinicians discontinue voice recognition software due to the need for adequate training. Thus, extensive initial training is essential to increase the acceptance of voice recognition software.


An EHR is associated with a substantial cost of documentation due to the increased time needed for data entry. Voice recognition software offers opportunities to streamline data entry, reduce documentation time, enhance the quality of the process, and increase the period clinicians interact with patients. The software can facilitate the adoption of EHRs among physicians and enable them to deliver high-quality and safe patient care. Leveraging voice recognition software, clinicians can infuse patient data with their direct assessment and observations using their words.

đź“Ž References:

1. Ajami, S. (2016). Use of speech-to-text technology for documentation by healthcare providers. The National Medical Journal of India, 29(3), 148-152.
2. Hodgson, T., Magrabi, F., & Coiera, E. (2017). Efficiency and safety of speech recognition for documentation in the electronic health record. Journal of the American Medical Informatics Association, 24(6), 1127-1133. https://doi.org/10.1093/jamia/ocx073
3. Kapoor, S. (2014). Electronic health records: Critique and solutions. Retrieved from https://d-scholarship.pitt.edu/21438/1/kapooressayfinal1.pdf
4. Patel, K., & Harbord, M. (2012). Digital dictation and voice transcription software enhances outpatient clinic letter production: A crossover study. Frontline Gastroenterology, 3(3), 162–165. https://doi.org/10.1136/flgastro-2011-100100