Electronic Medical Records (EMRs) play a crucial role in modern healthcare by streamlining the organization, storage, and retrieval of patient data, reducing manual workload, and enhancing the accuracy and accessibility of medical information. They enable quick access to complete patient histories, improve visualization of health trends, and support collaborative, evidence-based care. Unlike traditional paper-based records, which are prone to errors, misplacement, and limited sharing, EMRs offer secure, easily shareable, and integrated digital solutions that connect healthcare providers, administrative staff, patients, researchers, and public health officials. EMRs bring several advantages, including improved data accuracy, reduced duplication of tests, and real-time access to medical information, though challenges such as high implementation costs, training needs, and data security risks remain. Looking ahead, EMRs aim to achieve greater interoperability, integrate AI-driven predictive healthcare, empower patients through secure digital access, and connect with wearable devices and Iot technologies, ultimately fostering a more patient-centered and efficient healthcare ecosystem.

THESIS REVIEWS

1. Title: A study of evaluating the impact of electronic medical records on healthcare delivery system
2. This study examines the effect of electronic health record (EHR) digitalization on healthcare facility operational efficiency in india, focusing on the SmartCare system. It reveals that EHRs improve access to patient information, streamline workflows, reduce documentation errors, and enhance communication among healthcare providers. However, challenges such as limited resources, staff resistance, privacy concerns, and integration difficulties hinder full adoption. The research recommends improved funding, staff training, and robust change management to maximize the benefits of EHRs in low-resource settings.

2. Nurses’ perceptions about and confidence in using an electronic medical record system
3. This thesis focuses on nurses’ perceptions and confidence in using Electronic Medical Record (EMR) systems within a hospital setting in Muscat, Oman. It explores how factors such as experience, training, and feedback influence nurses’ confidence and usability of EMRs. The study found that while most nurses acknowledged the importance of EMRs in improving patient care and integrating into their daily routines, many lacked prior experience and sufficient training. Confidence was higher among nurses with longer exposure to EMRs, whose suggestions for improvements were considered, and when system data were updated and relevant. The research emphasizes the need for ongoing training, system customization, and active nurse involvement to enhance EMR adoption and improve healthcare delivery.

3. Assessment of factors influencing nurses acceptance of electronic medical record in a large hospital
4. This thesis investigates factors influencing nurses’ acceptance of Electronic Medical Records (EMRs) in hospital using the Technology Acceptance Model (TAM). It highlights how perceived usefulness, ease of use, system quality, IT support, and management engagement affect nurses’ willingness to adopt EMRs. The study surveyed nursing staff and found a strong positive correlation between system quality, top management support, and nurses’ perceptions, leading to better acceptance of EMRs. Demographics such as education level, experience, and computer literacy also influenced acceptance. The findings emphasize the importance of user-friendly systems, adequate training, and supportive organizational culture to enhance EMR adoption, ultimately improving patient care quality.

4. Examining the implementation challenges and benefits of electronic health records (EHR) systems in large hospital settings
5. This thesis examines the implementation challenges and benefits of Electronic Health Records (EHR) systems in large Indian hospital settings. It highlights how EHRs improve patient care, clinical decision-making, workflow efficiency, and healthcare coordination while reducing errors and redundant tests through tools like Clinical Decision Support (CDS), Computerized Physician Order Entry (CPOE), and Health Information Exchange (HIE). However, it also identifies major challenges, including high initial costs, technical complexities, staff resistance, inadequate training, and security and privacy concerns. Using quantitative research with structured surveys and structural equation modeling, the study reveals that staff training, organizational support, and robust data protection measures are crucial for maximizing the perceived benefits and minimizing risks. It concludes that while EHR implementation faces cultural, technological, and organizational hurdles, addressing these proactively can lead to sustainable improvements in healthcare delivery and patient outcomes in India.

METHODOLOGY

Aim:

1. To Present the EMR [Electronic Medical Records] In healthcare system. it also depicts the errors and limitations.

Objectives:

1. To evaluate EMR patients, whether EMR reduce time.
2. Improve quality of care that access how EMRs enhance patient outcomes reduce medical errors, and promote evidence –based medicine.
3. Enhance patient safety by evaluate the impact of EMRs on reducing adverse events, medication errors and improving patient safety.
4. Increase efficiency by analyze how EMRs streamline clinical workflows reduce paperwork, and improve productivity.
5. Improve accessibility and coordination that examine how EMRs facilitate sharing of patient information among healthcare providers ,improving continuity of care
6. Reduce costs by investigate the financial impact of EMRs on healthcare delivery ,including reduced administrative costs and improved resource allocation

Research Method:

1. The study population comprises healthcare professionals, including doctors, nurses, and administrative staff, working in large hospital settings where EHR systems are implemented. Participants with prior knowledge of EHR systems will be recruited using a purposive sampling strategy. The sample size is determined to be 350 participants to ensure adequate representation and statistical power.

Data collection:

1. Data will be collected using a structured questionnaire designed to capture information on both the challenges and benefits associated with EHR system implementation. Demographics, EHR system utilisation, perceived obstacles, and perceived advantages are all included in the questionnaire. Depending on participant choices and accessibility, both online and paper-based questionnaires will be used for data collection. Participants will get guarantees about the privacy and anonymity of their answers Survey overview:

ETHICAL CONSIDERATION

1. Ethical approval from the relevant Ethics Committee, institutional  research board (IRB) Will be obtained before data collection begins.
2. Prior to their Involvement In the research each subject will provide their Informed Permission.
3. The freedom to withdraw from the study at any time will be communicated to participants.
4. Throughout the study procedure, precautions will be taken to guarantee participant data privacy and confidentiality.

RESULT ANALYSIS

1. Analysis- doctors

Table:1.1 Frequency distribution of variables among the doctors

 The above table shows that the Majority (85.4%) of the participants rated EMRs as very easy or somewhat easy.Only 5.2% found them difficult. It indicates EMRs are broadly accessible and easy to use, which supports adoption.

Then Most of the respondents were use EMRs daily (68.8%), with 27.1% using them a few times a week. It represents that  EMRs are integrated into routine clinical workflows, showing strong reliance.

Majority of the participants (83.3%)were responded EMRs as very or somewhat user-friendly. It implicates that  Usability is high, however  ~9% still felt difficult, indicating room for improvement.

More than half of the participantsratedthe Lack of training (52.1%) is the top barrier, followed by technical issues (24%).

89.6% of the doctors  reported productivity gains (significant or somewhat). Most of the participants were respond (77.1%) technical support as adequate or very adequate , but ~22% remain neutral or dissatisfied.

Majority of the doctors (86.5% )expressed confidence in data security.It shows that High data security  in EMRs for safeguarding patient information, reinforcing transparency and accountability.

33.3% of the doctors  reported very high ROI, but another 33.3% were neutral.Itrepresents  Financial benefits are recognized by many of the doctors.

92.7% reported improved interactions (significant or somewhat) in the patients.EMRs enhance patient engagement and communication.93.8% reported improved quality of care.Itreveals  that EMRs contribute to better healthcare outcomes.

2.Analysis-Nurses

Table2.1:Frequency distribution of variables

From the table 2.1 ,Most participants found the system easy to use, with 83% rating ease of use as very or somewhat easy, and nearly half reported using the EMR a few times a week or more frequently.

Usability was generally well-rated, with 68% describing the system as very or somewhat user-friendly, though a small portion (16%) reported some difficulty.

EMR integration into existing workflows was also viewed favorably, with 76% indicating very or somewhat integrated, while only 15% felt it was unintegrated.

Perceptions of clinical impact were highly positive: 87% stated the EMR significantly or somewhat supports patient care, and reliability was similarly rated well, with 83% describing the system as very or somewhat reliable.

Respondents reported strong effectiveness in reducing documentation errors (86% effective) and misidentification errors (90% showing reduction).

Additionally, 86% agreed that EMR reduces paper use, reflecting acceptance of digital transition. Overall satisfaction was high, with 80% being very or somewhat satisfied with the EMR system.

These findings collectively indicate that users perceive the EMR as usable, helpful, reliable, and beneficial to both clinical workflow and patient safety

3.Analysis -Technician

Table 3.1:Frequency Distribution of Variables

The above table shows that the most respondents found the EMR system easy to use, with over 70% rating it as very or somewhat easy, and nearly half using it multiple times per hour or per day.

Usability perceptions were highly positive, with 87% describing the system as very or somewhat user-friendly.

 The most common primary challenge was lack of training, followed by technical issues and staff resistance.

 Productivity improved for the majority, with nearly 90% reporting significant or moderate increases. Technical support was viewed as adequate by most users.

 EMR use was also seen as effective in reducing documentation errors and misidentification, with over 80% reporting improvements.

A majority of the participants strongly agreed that EMR use reduces paper, and overall satisfaction was high, with 82% being very or somewhat satisfied.

4. Analysis-Management

Table4.1 Frequency distribution of variables

The above table shows that most participants found the EMR system easy to learn, with 85% reporting it was very or somewhat easy, and the majority (55%) using it at least once a day. Half rated the system as highly usable, and 70% were very satisfied with improvements in operational efficiency.

Patient access improved for most users, with 70% reporting moderate to significant improvement. Documentation accuracy also improved, with 80% indicating better accuracy after digitization.

Communication and collaboration were rated excellent or good by 80% of participants. Adoption challenges were mainly related to technical issues (50%) and inadequate training (25%). Perceptions of data security were generally positive, with 80% expressing confidence in system security.

Finally, long-term ROI was viewed favorably by most respondents, with 60% rating it very positive and 25% mostly positive

5.Analysis-Patient

Table 5.1 Frequency distribution of variables

The table consisted mostly of adults aged 18–30 years (42.2%) and 31–45 years (34.4%), with very few below 18 (3.3%) or above 60 (2.2%).

Most participants were relatively new to the healthcare facility, with 42.2% attending for less than one year and 24.4% being first-time seekers.

Education levels were mainly high school or below (34.4%) and bachelor’s degree holders (37.8%).

The most common concern regarding digital medical records was data accuracy (56.7%), followed by privacy and security (20%). Over half (51.1%) felt digital records significantly enhanced care participation, while 33.3% reported slight improvement.

Most visitors came once a month (40%) or once a week (34.4%). Waiting times were usually between 15–60 minutes. Digital records were viewed as extremely or somewhat useful by 64.4% of participants, and 68.9% felt their concerns were addressed well.

Overall satisfaction was high, with 70% reporting a positive experience and very few expressing dissatisfaction.

6.Analysis - Comparison between groups

Table 6.1 Association between the improved health care and role

The chi-square analysis shows a significant association between participants r role and perceived improvement in healthcare outcomes (χ² = 70.643, df = 16, p < .001).

Doctors and nurses reported the highest levels of perceived improvement, with the majority rating outcomes as “excellent” or “good.”

Technicians and management staff also showed predominantly positive ratings, although management responses were more polarized, with most selecting “excellent.”

 In contrast, patients showed more varied responses, with fewer “excellent” ratings and a higher proportion of “moderate” and “poor” evaluations compared to healthcare providers.

Overall, these results suggest that healthcare professionals perceive stronger improvements in healthcare outcomes than patients

Table 6.2 Association between the Health disparity and role

The above table shows that significant association between role and perceptions of health disparity (χ² = 83.922, df = 12, p < .001). Doctors, nurses, technicians, and management staff generally rated health disparity more favorably, with most selecting “excellent” or “good,”

In contrast, patient responses were markedly different: nearly one-third (34.4%) rated health disparity as “poor,” and none rated it as “moderate,” suggesting strong concerns about unequal healthcare experiences.

Table 6.3 Mean distribution between job role and improved healthcare

The  results indicate a significant difference in perceptions of improved healthcare across participants  roles (F = 17.065, df = 4, p < .001). Management reported the highest mean rating (M = 4.33, SD = 0.59), followed closely by nurses (M = 4.14, SD = 0.63) and technicians (M = 4.09, SD = 0.78), suggesting these groups perceive substantial improvements in healthcare. Doctors and patients reported lower mean scores (M = 3.43 and 3.76, respectively), indicating comparatively more moderate perceptions. These findings suggest that healthcare providers, particularly those in management and frontline roles, perceive greater improvements in care quality than patients and doctors do, highlighting differences in perspectives across roles.

Table 6.4 Mean distribution between job role and improved health population

The table  results indicate a significant difference in perceptions of improved population health across stakeholder roles (F = 12.986, df = 4, p < .001). Technicians (M = 4.20, SD = 0.93) and nurses (M = 4.13, SD = 0.80) reported the highest mean scores, reflecting strong perceptions that population health has improved. Management (M = 3.95, SD = 0.72) and patients (M = 3.75, SD = 0.65) reported moderately high scores, while doctors had the lowest mean rating (M = 3.43, SD = 0.73), suggesting comparatively lower perceptions of population health improvements.

CONCLUSION

The study aimed to evaluate perceptions of digital healthcare systems across different participants, with objectives to assess improvements in healthcare quality, population health, patient engagement, cost reduction, and transparency. Analysis revealed significant differences across roles: management, nurses, and technicians reported the highest perceived improvements, while doctors and patients generally rated outcomes more moderately. Patient engagement was positively viewed across all roles, though doctors perceived slightly lower levels, and patients expressed greater concern regarding health disparities. Overall, the findings indicate that the expected outcomes—enhanced healthcare quality, population health, engagement, cost-efficiency, and transparency—were largely achieved from the perspective of healthcare providers, while patient feedback highlights the need to address equity and perceived care gaps to fully realize these outcomes.

REFERENCE

1. Ng’andu, D., &Haabazoka, L. (Year). A study of the effect of health records digitalization on healthcare facility operational efficiency. University of Zambia.
2. Nurses’ perceptions and confidence in using electronic medical record (EMR) systems in a hospital setting in Muscat, Oman.
3. Aldosari, B., Al-Mansour, S., Aldosari, H., &Alanazi, A. (2018). Assessment of factors influencing nurses’ acceptance of electronic medical record in a Saudi Arabia hospital. Informatics in Medicine Unlocked, 10, 82–88. https://doi.org/10.1016/j.imu.2017.12.007
4. Ahammed, N., Pareek, N., &Tanwar, V. (2024). Examining the implementation challenges and benefits of electronic health records (EHR) systems in large hospital settings. International Journal of Advanced Academic Studies, 6(2), 59–66. https://doi.org/10.33545/27068919.2024.v6.i1a.1153
5. Ramesh, S., & Subramanian, P. (2025). Doctors’ perceptions of electronic medical record adoption in a private hospital in India: A mixed-methods study. BMC Health Services Research, 25(4), Article 12877. https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-025-12877-5
6. Rajan, S., &Prakash, A. (2020). Developing a standard EHR framework for India: Challenges and opportunities. Health Services & Outcomes Research, 16(2), 45–56. https://doi.org/10.1007/s10742-020-00238-0
7. Muyepa, A., & Stringer, J. (2014). ZEPRS: Zambia Electronic Perinatal Record System—Lessons from a national-level EMR. Journal of Medical Informatics in Developing Countries, 8(1), 22–29.
8. McKinney, M., &Basnet, R. (2018). Implementing Bahmni EMR in a rural Nepalese hospital: Lessons learned. BMJ Global Health, 3(Suppl 2), e000587. https://pmc.ncbi.nlm.nih.gov/articles/PMC5874496/
9. Al-Kahtani, A., &Almutairi, H. (2021). Electronic health record adoption in GCC countries: A systematic review. Middle East Journal of Health Informatics, 9(3), 112–125.
10. Liu, C., et al. (2017).The role of EHR in operational efficiency in healthcare organizations*.
11. Hersh, W. R., et al. (2015).Health Information Technology and Quality of Care: A Systematic Review of the Literature
12. Kellermann, A. L., & Jones, S. S. (2013).The Role of Health Information Technology in Addressing the Quality and Efficiency Challenges of U.S. Health Care*.