Technology in Healthcare: Are the current electronic medical record systems as efficient as we think they are?
By: Andre Fabian and Jeremy Cote
It can be ascertained that the quality of healthcare received by patients is linked to the quality of notes taken by the healthcare team. The advent of the electronic era has introduced a wide array of technologies into many aspects of society, with the field of healthcare being one of the most prominent. Following Obama’s approval of the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009, the adoption of electronic medical record systems skyrocketed nationwide (BaytechIT). With this in mind, it becomes imperative to address potential deficiencies of such systems to ensure satisfaction among patients and efficiency among healthcare teams.
One of the most common trends in electronic note-taking includes an increase in the length and redundancy of visit notes. Given the accessibility of templates and auto-filling softwares, many providers demonstrate an increasing reliability on pre-generated blocks of text. However, due to the complexity of each individual patient case, reuse of these templates may prove ineffective at concisely addressing the primary relevant issues, while posing the risk of missed nuances. A study by Rule et al. illustrated these patterns in an outpatient clinical setting. From a pool of over 2.7 million notes written by over six thousand authors in almost fifty specialties, there was an apparent sixty percent increase in the median length of visit notes, coupled with an eleven percent increase in redundancy of content. This suggests that there may be underlying drawbacks to what, at face value, appears to be a more efficient system.
However, the introduction of customizable note-taking templates is not the answer, as they also appear to contribute to a reduction in efficiency. Due to the lack of standardization among some electronic medical records, a research team investigated its potential connection to clinician experience. In Hultman et al., investigators recorded objective data on time spent reviewing patient notes. Their findings highlighted a limitation of unstandardized electronic note-taking systems, citing a 0.9 to 1.9 minute increase in time spent reading. This data is further supported by a study performed by Hollingsworth et al. that shows current faculty and resident physicians are spending 51.3% and 53.7% of their time performing indirect care respectively. As time for physician-patient interactions is already severely limited by the sheer number of patients under a physician’s care, it becomes important to implement policy that maximizes time for direct patient interaction.
These observations point towards a theme of “information overload,” defined by Clynch and Kellett as the phenomena in which healthcare providers hone in on their respective areas of the medical record exclusively. According to their research, a mere thirty-eight percent of providers’ notes are ever read by anyone besides the author themself. Beyond the inefficiency caused by this “chart isolation,” an additional concern lies in the diagnosis of comorbid conditions. The reduction in provider collaboration in regards to note-taking can directly lead to critical mistakes As a result, it becomes apparent that current medical documentation processes are inefficient and require reevaluation.
Looking forward to new solutions, Speech Recognition (SR) technology has been the leading new documentation style in the healthcare industry. SR uses advanced software that detects sound spoken into a microphone and converts it directly into text onto documents. A study by Callaway et al. highlighted a reduction in clinical report turnaround time from 89 hours when transcription was used to 19 hours when SR was used, saving the facility $45,500 over 6 months. Additionally, a study by Blackley et al. compared dictated notes to typed notes, finding that “dictated notes had a higher mean quality score by 1.1 points, were more complete, and included more sufficient information.” Additionally, “Participants felt that SR saves them time, increases their efficiency, and allows them to quickly document more relevant details.” However, given the novelty of SR, healthcare providers hold some initial hesitations towards adopting the new SR systems. A study performed by Dinari et al. found that the primary barrier for nurses using SR systems was the “lack of specialized, technical, and experienced staff to teach nurses how to work with speech recognition systems,” followed by the “inadequate training of nurses.” As a resolution to the initial difficulties navigating the software and to further aid the transition to dictation note taking, educational programs and resources should be made available to healthcare providers in order to increase familiarization and efficiency.
Additionally, alongside the implementation of SR systems, a study by Kahn et al. at UCLA showed that the use of a standardized template for medical documentation significantly increased all domains of the PDQI-9 alongside multiple competency items, leading to 25% fewer lines used and an average signing time of 1.3 hours earlier.
Ultimately, the implementation of dictation based notes through Sound Recognition Systems alongside the use of standardized note templates for medical documentation will continue to improve both the quality and efficiency of medical documentation for healthcare providers. As a result, this increases the amount of time available for healthcare professionals to spend face-to-face with patients, which has been linked with patient satisfaction and overall well-being.
Jeremy Cote and Andre Fabian are both incoming seniors, Physiological Sciences majors, and THINQ interns.
Works Cited
Blackley, Suzanne, et al. “Physician Use of Speech Recognition versus Typing in Clinical Documentation: A Controlled Observational Study.” International Journal of Medical Informatics, 15 May 2020, doi.org/10.1016/j.ijmedinf.2020.104178.
Callaway, Edward C et al. “Speech recognition interface to a hospital information system using a self-designed visual basic program: initial experience.” Journal of digital imaging vol. 15,1 (2002): 43–53. doi:10.1007/BF03191902
Clynch, Neil, and John Kellett. “Medical Documentation: Part of the Solution, or Part of the Problem? A Narrative Review of the Literature on the Time Spent on and Value of Medical Documentation.” International Journal of Medical Informatics, 15 Dec. 2014, doi.org/10.1016/j.ijmedinf.2014.12.001.
Dinari, Fatemeh, et al. “Benefits, Barriers, and Facilitators of Using … — Wiley Online Library.” Edited by Esmat Mashouf, Wiley Online Library, 12 June 2023, onlinelibrary.wiley.com/doi/full/10.1002/hsr2.1330.
Hollingsworth, Jason, et al. “How Do Physicians and Nurses Spend Their Time in the Emergency Department?” Annals of Emergency Medicine, 4 Nov. 2005, doi.org/10.1016/S0196–0644(98)70287–2.
Hultman, Gretchen M et al. “Challenges and Opportunities to Improve the Clinician Experience Reviewing Electronic Progress Notes.” Applied clinical informatics vol. 10,3 (2019): 446–453. doi:10.1055/s-0039–1692164
Manor-Shulman, Orit, et al. “Quantifying the Volume of Documented Clinical Information in Critical Illness.” Journal of Critical Care, 11 Dec. 2007, doi.org/10.1016/j.jcrc.2007.06.003.
Rule A, Bedrick S, Chiang MF, Hribar MR. Length and Redundancy of Outpatient Progress Notes Across a Decade at an Academic Medical Center. JAMA Netw Open. 2021;4(7):e2115334. doi:10.1001/jamanetworkopen.2021.15334
Kahn, Daniel, et al. “A Prescription for Note Bloat: An Effective Progress Note Template.” Journal of Hospital Medicine, vol. 13, no. 6, 2018, pp. 378–382, https://doi.org/10.12788/jhm.2898.
