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2DIGITAL TRANSFORMATION OF MEDICAL CARE IN UZBEKISTAN: POSITIVE OUTCOMES OF AUTOMATIC
SPEECH RECOGNITION
1Islamov B.A., 2Teshayev R.K.
1Professor of Tashkent State University of Economics, Doctor of Economic Sciences, Professor.,
Uzbekistan
2Doctoral student at International Westminster University in Tashkent https://doi.org/10.5281/zenodo.13141558
Abstract. Medical professionals in Uzbekistan are still compelled to rely mostly on hard copy paper charts while providing care to citizens. Even if the internet communication is becoming more and more integrated into other areas of the business, this phenomenon still requires a lot of time and resources when it comes to medical one. In many relatively more developed foreign healthcare systems, the sophisticated use of contemporary information technology (IT) in healthcare institutions—particularly the digitization of electronic health records (EHR), which facilitates the easy exchange of vital data among all stakeholders in the healthcare system—has been shown to be a useful tool for improving treatment quality, lowering costs, and eliminating errors. Thus, the Ministry of Health has developed a new plan for the Digitalization of the Health System for 2021-2025 (E-Health-2025). Consequently, in recent years, there has been a fast acceleration of ICT integration into medical institutions' operations, and systems for electronic document management are currently being adopted. The goal here is to provide the general population with healthcare as quickly, simply, and effectively as possible. However, there are some roadblocks in the system that impede the EHR integration process. These problems might include data security, which is essential to preserve as the republic's healthcare sector quickly becomes data-intensive, and the conservative medical staff's unwillingness to follow all software-related procedures because of their lack of computer literacy. Aside from that, there are other illogical actions taken by medical professionals, such as copying and pasting patient data, which results in a significant volume of inaccurate and duplicated medical data. The potential benefit of voice-to-text enabled text recording during consultations has been emphasized and strongly backed by pertinent research, observations, on-site modeling, and quasi-experimental testing in order to address these unworkable aspects within our research.
Keywords: ASR, speech recognition, healthcare management, medical data management, voice-to-text enabled typing, digitalization, management.
Critical Literature Review
With the process of digitizing various aspects of Uzbek economy, Electronic Health Records (EHRs) play a major role in the growth of the national healthcare system by providing quick access to patient information. Nevertheless, despite the advancements and benefits that EHR systems provide to the healthcare sector, a number of issues arise when these digital records are implemented. These issues include medical staff support for successful implementation, software usability, and manual typing difficulties among medical professionals. In this study of the literature, we offer an empirical understanding of the most prevalent issues that impede the deployment of EHRs, such as keyboarding issues and a lack of assistance from the medical staff
in utilizing the system. This review's main goal is to pinpoint the precise issues around the typing difficulty and the lack of assistance from medical staff, which is a significant barrier to the successful adoption of EHRs. This knowledge will serve as the cornerstone for sensible tactics aimed at enhancing acceptance and driving the essential demand for the application of ASR systems as a remedy. The chapter also evaluates the efficacy of the current approaches to the implementation sluggishness of EHRs.
In many nations throughout the world, the use of EHRs in the healthcare sector has proven essential to modernizing patient care and enhancing overall healthcare results. One of the main advantages of electronic health records, according to a review of the literature on the advantages and difficulties of implementing them in different healthcare settings, is that doctors can obtain quick access to patient data in an electronic format following successful implementation (Kose et al., 2023). With more readable data available, medical providers can make better decisions and provide higher-quality care. The availability of medical records on computers and the internet makes it easier for departments, hospitals, and patients to safely and effectively communicate patient information when they relocate. Furthermore, several studies have demonstrated that the integration of electronic health records can save healthcare costs and enhance the quality of treatment by speeding clinical workflows and medical staff administrative operations (Atasoy et al., 2019).
The widespread use of EHRs has a favorable impact on the quality of healthcare services as well. According to research, e-ordering, closed-loop drug administration, and better clinical documentation are just a few ways that using electronic health records might enhance medication management (Atasoy et al., 2019). Moreover, physicians may do clinical trials, epidemiological research, medication safety monitoring, and illness registries with the use of EHRs. In this sense, it benefits the nation's economy by advancing both public health outcomes and medical research as a whole. But as the most recent scholarly research has clearly shown, there are never any issues or slowdowns when the country's healthcare system switches from traditional paper-based records to electronic ones. The problem of manual typing, the requirement for thorough training and support for healthcare providers, and the cost of implementation are among the many grave concerns that impede the successful adoption of electronic health records. Other concerns include worries about patient privacy and data security.
In order to improve patient care and healthcare delivery, the broad adoption of EHRs in healthcare settings has been a major priority in many countries (Stanberry, 2011). It has been discovered that the issues resulting from data input time and efficiency are what slow down the pace of digitalization.
According to academic research, doctors' reluctance is largely due to the fact that entering data into an EHR requires more time and effort than with traditional paper-based records, which is a new activity that takes time (Devkota & Devkota, 2014). The inability to write well or use the EHR's interface with ease is the primary reason why clinicians frequently complain that EHR systems take up time and interfere with their workflow, which lowers productivity and efficiency (Gold & McLaughlin, 2016).
Another major obstacle to the uniform interchange of patient data and the potential benefits of EHRs is the lack of applicability and interoperability between various EHR systems. Put another way, healthcare professionals in numerous nations, including the Republic of Uzbekistan, use software from various manufacturers that has unique features and programming languages.
Because of this, it is frequently not possible for old medical data to be shown in new medical software when patients relocate to a different location or institution. Furthermore, especially for smaller healthcare institutions with less resources, the upfront costs of establishing and maintaining EHR systems can be a major disincentive (Gold & McLaughlin, 2016).
Numerous studies indicate that the dynamics of doctor-patient relationships have been significantly impacted by the broad implementation of EHRs in healthcare settings. Researchers have discovered that when physicians rely more on computers and screens during consultations, there may be less face-to-face interaction between them and their patients. This can have a discernible impact on the standard of treatment and patient satisfaction. Following its implementation, data entry and documentation responsibilities on computer systems became more important in the everyday work of healthcare professionals (Konnoth & Scheffler, 2020). Due to the transition to electronic health records, physicians may now find it difficult to focus on both the patient and the computer screen. This can lead to a decrease in eye contact and attentive listening when patients disclose health issues. Management scientists have conducted observational and ethnographic research that has brought to light the significant influence that computers have on how doctors and patients interact during office visits. These studies have shown that doctors find it difficult to maintain a balance between using the digital interface and talking to their patients.
The abilities needed to utilize EHRs efficiently—like typing quickly and figuring out complicated user interfaces—don't often match up with the primary capabilities of healthcare professionals. Physicians may prioritize data entry activities above patient-centered communication because they lack the requisite computer skills or familiarity with the EHR system. An further factor in the decline of in-person interactions between physicians and patients is the cognitive strain that comes with trying to listen to a patient, evaluate their medical requirements, and record information in the electronic health record (EHR) all at the same time.
In order to lessen the detrimental effects on doctor-patient interactions, researchers have stressed how crucial it is to build electronic health records (EHRs) with user experience and workflow concerns in mind. The disconnect between the demands of technology and the human elements of patient care can be lessened by addressing the usability issues with EHR systems and offering thorough training to medical staff (Kim, 2013).
Another important issue that came to light during the implementation and use of EHRs is how common it is for healthcare providers to copy and paste patient information into electronic health records. This is frequently because they are reluctant to manually enter data or have poor typing skills. Patient safety and the veracity of medical data can be seriously jeopardized by copy-pasting in electronic health records. Reusing old, irrelevant, or erroneous information inside the patient's electronic record is more likely when healthcare personnel copy and paste data rather than physically inputting it. This may make it more difficult to determine the accurate, current status of the patient's health and course of therapy, which might lead to mistakes in diagnosis or inappropriate treatment choices. One case study, for instance, discovered that material that had been copied and pasted resulted in a patient's readmission for a potentially fatal illness since the required prescription was not given.
In electronic health records, copy-pasting techniques create further problems with missing data and the inability to distinguish between actual negative numbers and undocumented information. Clinicians may be reluctant to enter information that is not easily accessible because they are uncomfortable using a keyboard, which might result in incomplete records. Efforts to
decrease data entry mistakes, improve organized data documentation, and use natural language processing to extract pertinent information from clinical notes are some strategies to deal with this (Wells et al., 2013).
The Potential Benefits of Voice-to-Text Enabled Automatic Speech Recognition (ASR) Typing for in resolving difficulties linked to EHR deployment and utilization.
The potential advantages of integrating voice-to-text enabled automated speech recognition (ASR) technology into the EHR process are one innovative approach that has drawn scholarly interest (Payne, 2016). According to the literature, voice-to-text integration can increase the uptake and utilization of electronic health records. By helping healthcare personnel swiftly capture and transcribe patient data, these devices save time and effort when manually entering data into an electronic system. This might thus result in better clinical guidelines being followed, greater documentation, and ultimately better patient care. Additionally, research has shown that voice-to-text capable EHRs can solve some of the problems that now plague current EHR systems. According to Atasoy et al. (2019), these technologies can specifically aid in reducing problems like laborious user interfaces, challenging implementations, and the length of time needed to utilize standard EHR systems. For instance, a research carried out in Turkey discovered that the nation had almost entirely adopted EHRs, with the potential to use these digital systems to save costs and enhance healthcare quality (Kose et al., 2023). Comparably, an analysis of the literature on the digitization of patient care highlighted the noteworthy advancements in the adoption of EHRs while also emphasizing the necessity of resolving persistent issues with user interface and implementation to fully reap the rewards of these technologies (Kose et al., 2023). The efficiency and productivity of healthcare professionals may benefit from the use of voice-to-text capabilities. Based on our analysis of a few experimental trials, we have shown that using voice-enabled EHRs can result in a 50% decrease in documentation time, freeing up more time for doctors to interact with patients and deliver better treatment (Payne, 2016). Additionally, the integration of voice-to-text technology can aid in mitigating inequalities in healthcare quality and access for physicians as well as between departments of health. These technologies can enhance the electronic health record's usability and accessibility for all patients, including those from marginalized or underserved communities that face a shortage of medical personnel, by lowering the obstacles connected with traditional EHR data entry (Gibbons et al., 2011). According to the data that is currently available, voice-to-text enabled automated speech recognition integrated with EHR systems can significantly increase the uptake and utilization of these technologies in healthcare settings. These skills may support the continuous transformation of patient care and the provision of high-quality, evidence-based healthcare by strengthening documentation, increasing workflow efficiency, and encouraging health equity.
The decrease in typographical mistakes in clinical information transcription is an additional benefit of utilizing ASR in conjunction with EHR. These errors can have detrimental effects on patient safety and treatment quality. In the past, medical professionals were prone to making mistakes because of inadequate record-keeping, transcribing errors, or failing to link a patient's medical history to their current course of treatment. Some of these problems have been addressed by the switch to electronic health records (EHRs), which offer a consolidated, searchable collection of patient data. According to a research, 80% of outpatient visits resulted in physicians being unable to retrieve pertinent information in paper-based records, underscoring the benefits of a digital approach (Rustagi & Singh, 2012). This study suggests that efficient automation and
natural language processing in EHR systems can lower transcription mistakes even further and enhance the quality of the data. Furthermore, minimizing typographical errors may be achieved by organized data entry and a reduction in human data input (Wells et al., 2013). To fully realize the promise of Electronic Health Records (EHRs) to improve patient care, it will be imperative to integrate cutting-edge technology like voice-based interfaces and data analytics (Payne, 2016).
Improving data completeness in EHR systems is another benefit of ASR technology in the healthcare sector. There is mounting evidence that the issues posed by inadequate, diverse, and noisy data—which frequently define EHR systems—can be greatly mitigated by including ASR. A thorough analysis of the literature demonstrates the many advantages of integrating ASR technology into EHR processes. ASR has shown promise in streamlining documentation procedures, lowering administrative loads, and enhancing the caliber and precision of patient data collection (Payne, 2016). Researchers found that using ASR in conjunction with EHRs significantly increased data completeness, with up to 95% of the necessary patient information accurately recorded by medical practitioners compared to another group of doctors who employed manual typing (Atasoy et al., 2019). The study examined the effects of EHR digitization. Furthermore, a number of studies indicate that the combination of machine learning and natural language processing methods with automatic speech recognition (ASR) has made it possible to extract insightful information from unorganized clinical notes, facilitating more thorough and information-based choices in healthcare settings.
Positive outcomes of ASR technology in the healthcare field include enhancing doctors' satisfaction and minimizing cognitive burden. The potential of this software technology to reduce fatigue and improve the general efficacy of EHR systems in healthcare settings has been brought to light by recent study. ASR can reduce healthcare practitioners' cognitive load by automating the clinical documentation process, freeing them up to concentrate more on patient engagement and making choices (Kim, 2013). Studies already conducted have demonstrated that using ASR in EHR systems may save the amount of time spent documenting by up to 50%, leading to notable productivity increases and more time spent with patients. Moreover, automated patient symptom and clinical data charting can boost the electronic health record's correctness and comprehensiveness, which will improve patient safety and care quality (Reid et al., 2005). Patients in the study reported feeling more involved in their care when healthcare providers could maintain eye contact and have more natural conversations during the clinical encounter. According to one study, the integration of artificial intelligence (ASR) into EHR systems has also been found to improve patient participation by reducing the physical and mental barriers associated in conventional EHR interfaces (Perez-Stable et al., 2019). ASR technology adoption presents a promising way to lessen cognitive load, increase clinician productivity, and improve the patient experience overall as healthcare organizations continue to struggle with the problems brought on by EHR systems (Reid et al., 2005).
Research methodology
We developed a novel algorithm for electronic health record creation as part of our study, with the goal of reducing the amount of time needed to create patient notes, their quality, and the satisfaction of doctors with the process. Two regional hospital settings hosted observations, interviews, and on-site modeling for the study project. Enabling physicians to create electronic health records with the fewest possible mistakes and in the shortest amount of time was the primary
objective. The system was expected to demonstrate its security, portability, ease of use, and— above all—time-saving capabilities.
In contrast to doctors typing by hand, the voice-to-text enabled system was modeled on-site using interviews, observations, and a combination of quantitative and qualitative (qausi-experimental) research methods. More precisely, the goal of the study was to have physicians record a brief audio message, no more than five minutes, during or soon after medical interviews, when their impressions of the patient's history and examination were still fresh. One of the Android applications was utilized to use a personal smartphone to record audio in order to capture voice recordings made during rounds. Because of its widespread use and simplicity in application development, this device was selected. We explored commercial recording applications and devices, but for our purposes, they were either too expensive, too complicated, or did not offer secure audio data transfer over the internet. Testing confirmed that the standard microphone on contemporary smartphones can record well enough to facilitate ASR (automated speech recognition).
Using a quasi-experimental research design, the study evaluated how well ASR technology performed in terms of cutting down on EHR filling time as compared to conventional typing techniques. The purpose of this kind of research methodology is to attempt to determine whether there is a cause-and-effect relationship between an independent and dependent variable. The quasi-experimental designs lack random assignment, in contrast to the actual experimental designs. This is mostly due to the fact that the purpose of our research was to evaluate the efficacy of ASR solely in the hospital context. This suggests that individuals did not merely happen to fall into the different medical specialties from various hospitals at random. The observing researcher instead had the same doctor physically enter notes into the EHR during the patient interview and subsequently fill them out using the ASR so that they could compare the amount of time spent on either method.
The quasi-experimental approach has a few benefits. It first provides practical application. It may be created at a hospital, where treatments happen naturally during consultations, making the outcomes more pertinent and useful. The best way to do this is to test in actual healthcare settings to make sure the results have direct and useful application to the context where the gadgets would be deployed. Since our research is only intended to verify the effectiveness of ASR in hospitals, quasi-experiments are easier to implement because they do not require random assignment. This is especially true in the busy work environment of medical interviews between a doctor and a patient, where randomizing of the participants would make organization difficult or even impossible.
Secondly, employing this kind of study methodology raises important ethical issues. In most situations, random assignment of other study designs might provide an ethical dilemma, particularly in the context of medical settings. We can use contemporary technologies to examine the impacts of an intervention thanks to quasi-experimental design. Our studies may be conducted with the least possible interference to participants' regular activities thanks to this research approach, which is essential in scenarios when patient care and workflow must continue uninterrupted.
The fact that research conducted in real-world settings, including hospitals, will show actual practice and results instead of controlled and falsified groups, is a third essential factor in the use of the quasi-experimental method, which hospitals and physicians are more likely to
support and trust. Aside from that, because our study results were initially based on real-world surroundings from different hospitals, we may more readily apply them to various similar medical settings.
Discussion of Results
The T-statistic test, which measures the ratio of the variance of the group means to the variability of the samples, was used to determine whether ASR technology significantly reduces the time required for EHR filling. After the primary data collection was finished, the results were interpreted in light of the hypothesis. A greater difference between the groups is indicated by a higher absolute value of the t-statistic. This independent t-test was used to examine how long it takes to fill up electronic health records (EHRs) using ASR dictation vs manual typing. The amount of time required for ASR dictation compared to manual typing was significantly different; t(C) = t-value, p = p-value. These findings imply that, in comparison to manual typing, ASR dictation considerably shortens the time needed for EHR filling. To be more precise, it was shown that clinicians who manually typed each health record on a keyboard took 23 minutes to complete each EHR when analyzing all 120 samples using Stata; in contrast, utilizing an ASR reduced this time to just 17.8 minutes per EHR (see figure 1).
Paired t test
Variable Obs Mean Std, err. Std. dev. [95SS coirf. interval]
ASRtra^e Manuals 120 120 17. S .641317S 23.05S33 .8544902 7.0252S4 9.360471 16.53013 21.36636 19.069S7 24.75031
diff 120 5.25S333 .3979105 4.35SS91 -6.046236 -4.470431
mean(diff) = mean H0: mean(diff) = 0 (ASRtranscripti-'e - Manualtypingti^ Degrees 'S) t of freedom = -13.2149 119
Ha: mean(diff) < 0 Pr(T < t) - O.0000 Ha: mean(diff) Pr(|T| > |t|) = 8 = 0 .0000 Ha: mean(diff) > 0 Pr(T > t) = 1.0000
end of do -file
The clinicians were more inclined to enter more medical data into electronic health records (EHRs) since it was easier to dictate than to type, hence the size of the EHRs varied depending on the situation. To be more precise, 273 words was the average (mean) amount of words typed each EHR. In contrast, physicians were able to create electronic health records (EHRs) with an average word count of 356 when they dictated their notes into a microphone. Our fourth hypothesis, which states that "the amount of applicable medical data put into EHRs increased when doctors used ASR instead of typing," is supported by this. This translates to 30.4% more medical records for each patient, expressed as a percentage. We computed the average time spent typing per 100 words in order to precisely determine the transcription speeds of both approaches because each EHR has a different size. The Stata extract below shows that typing 100 words by hand takes an average of 8.8 minutes, but typing 100 words by use of an ASR only takes 5.2 minutes.
Put another way, we were able to save up to 41% of the time that clinicians spent filling out EHRs by using ASR. To assess the beneficial impact of this technology, we must multiply the time saved in each EHR by the number of doctor interviews that occur each day, which comes to 16,7. By using voice-to-text capable transcribing, we can calculate that each doctor can save up to 60.1 minutes per working day. This additional time might be used for conducting more interviews
in places where there is a scarcity of medical professionals and lengthy wait times. The main research hypothesis, which states that "creating EHRs with the usage of ASR technology is significantly more time saving than manual typing," has been verified, leading to this result. The uptake and utilization of EHRs have been positively impacted by the incorporation of voice-to-text capabilities. By speeding up the process of obtaining and transcribing patient data, this technology helps healthcare providers save time and effort while manually entering data into an electronic system. This has therefore raised the possibility of better clinical guidelines being followed, greater documentation, and ultimately better patient care. Additionally, research has shown that voice-to-text capable EHRs can solve some of the problems that now plague current EHR systems. In particular, because the majority of the doctors reported a favorable experience and satisfaction, ASR technology minimized concerns like difficult to use user interfaces, challenges with deployment, and the significant amount of time needed to utilize standard EHR systems (see chart 1). Furthermore, the testing has supported the ideas of Cognitive Load Theory (CLT) and Human-Computer Interaction (HCI), which examine how computer technology is designed and used with an emphasis on human-computer interfaces.
The additional hypothesis we tested in this research was whether or not the use of ASR affected the behavior tendencies of doctors. It was specifically intended to measure the extent to which ASR prevents physicians from copying and pasting data from current EHRs in favor of typing. To investigate this theory, we administered a survey to physicians, inquiring about their inclination to replicate text from the current electronic health record (EHR) when they are hesitant to input.
Chart 1: Doctor's tendency to replicate existing data
pasting
tendency when reluctant to Wpe
No; 6; 5%
Copy pasting tendency Yes
Copy pasting tendency No
Copy pasting
tendency Yes ; 114; 95%
As seen in chart 1 above, the great majority of physicians (95%) stated that they typically copy and paste pre-existing EHRs in order to save the administrative work of typing prior to testing ASR. Of 120 doctors, just 5%, or 6 of them, said that they don't replicate pre-made templates. When asked what drove them to replicate, the majority of them said that it was their inability to use a computer, their dislike of typing, and their desire to save time. Furthermore, many physicians claim that the Ministry of Healthcare has recently mandated the simultaneous maintenance of both traditional handwritten health records and computerized ones. This is mostly because the state has not yet formally decided to fully switch to electronic form documentation, and the government is
currently evaluating EHRs. Due to the Ministry's excessive number of changes and withdrawals in this area over the past ten years, physicians continue to have doubts about the efficacy of EHR systems.
Doctors were provided with support and all the necessary gear and software to use ASR for filling up the most extensive and fundamental sections of the electronic health record (EHR) in order to examine the impact of ASR on physicians' propensity to duplicate pre-existing health data. Following many patient interviews, the patients were asked if they would rather use voice to text dictation if it was available, or if they would rather copy and paste information already in the record and make changes. It is now clear that most doctors would still prefer to copy and paste the current medical records in order to reuse them. The majority of doctors use the fact that they frequently deal with complex medical vocabulary that is challenging to write or even speak as justification for their propensity to copy. Furthermore, the majority of the patients' medical illnesses and diseases have been observed to be quite comparable to those of the majority of other patients. Therefore, they prefer replicating the previous template records and making minor edits to them in order to reduce the amount of time and effort required for insertion. However, a somewhat higher percentage of doctors stated that they would prefer to use ASR rather than copying and pasting after becoming acquainted with the technology and its functioning. More precisely, 16 physicians out of 120 stated that they would stop copying and pasting if they had the chance to use dictation properly. Prior to test findings, this inclination was 7.5% lower than typical. Stated differently, ASR is a technique that lowers the rate of duplication by greater than 7%.
Chart 2: Doctor's tendency to replicate existing data when ASR is available
Copy pasting tendency No; 16; 13%
Copy
■ Copy pasting tendency Yes
■ Copy pasting tendency No Yeg'7104;
This finding is consistent with ideas in Behavioral Economics, Human-Computer involvement (HCI), and Cognitive Load Theory (CLT) that emphasize the need to minimize unproductive activities and maximize user involvement through the design and usage of computer interfaces. The experiment supports the CLT hypothesis, which emphasizes how lowering cognitive load may enhance decision-making and efficiency, by demonstrating how the doctor's propensity to copy and paste is lessened. Because the findings gave us new perspectives on the ways in which cognitive and environmental variables affect physicians' decisions, behavioral economics theory has also been validated. The hypothesis's relevance to the research problem stems from the applicability of HCI theory, which emphasizes the optimization of user interfaces
to promote accurate and efficient documentation methods in medical settings. By streamlining the EHR preparation process, ASR technology offers an enhanced user experience that may lessen the temptation to copy and paste data. We can now provide credence to the CLT hypothesis, which postulates that making documentation chores less cognitively taxing might encourage more thoughtful and less impulsive action. The theory is further supported by an analysis of our data from the perspective of behavioral economics, which explains how user behavior may be influenced by ease of use and reduced effort, hence decreasing the usage of copying and pasting. Several prior studies have examined the impact of adding ASR technology to the clinical document loading process and set the stage to investigate its influence on the 'copy-paste' propensity into clinical documentation workflow, as was covered in the research's preceding chapter. The majority of the body of research supports both our findings and the idea that healthcare providers now routinely use the copy-pasting feature in EHR systems because, when used properly and sensibly after validating the data, it can reduce data entry time and increase efficiency. Nonetheless, there has long been a dearth of data precisely expressing the percentage of doctors that copy and paste. We have calculated a 7.5% decrease in the rate of copying and pasting as a result of our study's ability to close this gap by presenting concrete data on how ASR affects documentation procedures in Uzbek healthcare settings.
Based on ideas from behavioral economics, CLT, and HCI, the notion that ASR technology deters physicians from copying and pasting patient data onto new EHRs was put forth. ASR has been able to promote more original data entry and lessen the need for copying and pasting in Uzbek by streamlining the documentation process and lowering cognitive burden. We examined how frequently clinicians copied and pasted information in EHRs made with ASR technology vs those made by hand typing in order to test this theory. Among the participants were physicians who were randomized to the manual typing and ASR groups. The frequency of copied and pasted entries in a standardized set of EHRs and the physicians' perceptions of their own temptation to do the same with old EHRs were the main findings. Our findings illustrate the useful advantages of ASR technology in fostering accurate and efficient documentation processes, which advances the theoretical knowledge of HCI, CLT, and behavioral economics. The results corroborate the idea that sophisticated user interfaces, like ASR, can improve the quality of documentation by lowering cognitive burden and deterring ineffective behavior. Furthermore, despite a marginal reduction of 7.5%, the majority of healthcare providers still prefer copying and pasting at a rate of 87% to 95%. These insights into the application of ASR technology in healthcare could potentially direct future research and development in this area.
Conclusion
The results obtained on the basis of the experiment showed that up to 41% time was saved when creating an electronic text using the method of writing voice text. This time saved can be potentially used to eliminate problems of doctors shortage in vulnerable areas of the country including rural areas where there are too long queues to doctors' interview. These doctors could save more time on administrative tasks such as typing by using ASR technology and the extra time could be used to interview more patients. Moreover, due to the convenience of the method, the tendency of doctors to re-copy existing medical forms decreased by 7.5% because with the ease of the technology doctors were not tempted to copy and paste the existing EHR repeatedly which can also contribute to the elimination of redundant data in electronic health records. Apart from
these findings, ASR has also highlighted its positive contribution in minimizing spelling errors in
EHRs as well as more data completeness.
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