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EMR Implementation In Saudi Arabian Hospital Conclusion Chapter

King Khalid University Hospital implemented a new system called The Electronic System for integrated Health Information or E-SIHI. The results from the data for clinical documentation before the implementation of E-SIHI revealed the most documentation when it came to 'physical examinations' in relation to ICU and OB/BYN. However, in Medicine and Surgery, there were low percentages for clinical documentation with Medicine at 35% and Surgery at 43%. The data revealed across the board both Medicine and Surgery had low clinical documentation with the lowest standing at 18% for Surgery in the 'assessment' area. A 2013 update review demonstrated hospitals had little clinical documentation for complications associated with esophagectomy. Meaning assessment of complications, reactions to medicine, length of stay, and postoperative quality of life were not performed. This had to with a lack of a standard system for monitoring and documentation. The review recommended newer assessment tools to allow better monitoring of patient complications and outcomes after surgeries like esophageal resection. "Newer systems of assessing surgical complication severity include the Accordion and Clavien grading systems. New endoscopic and interventional approaches to treating anastomotic leak and stricture and chyle leak can selectively decrease length of stay and costs of managing complications" (Low & Bodnar, 2013, p. 535). Perhaps these newer systems can improve the clinical documentation of surgeries, especially in the 'assessment' section.

While the results provided visible improvement in certain areas in regards to clinical documentation, the new system implementation had no impact on the section 'length of stay'. The most affected, 'Physical Examination' and 'Assessment' improved the most using E-SIHI. The 'Estimated Discharge Date' and 'Patient Education' improved the least and actually decreased in percentages with the new system implementation showing it works for 3 out of the 5 sections. Because of this, the new system implementation requires modifications to improve clinical documentation in all 5 sections.

A 2012 EMR study examining the transition from paper records to electronic records saw gains when hospitals implemented an easy to use electronic system. However, when hospitals implemented a more advanced system, there was a visible decrease in quality of services, especially in regards to accuracy of documentation.

Among all hospitals, implementing Level_3 systems yielded an incremental 0.35-0.49%age point increase in quality (over Level_2) across three conditions. Hospitals in bottom quartile of baseline quality increased 1.16-1.61%age points across three conditions for reaching Level_3. However, transitioning to Level_4 yielded an incremental decrease of 0.90-1.0 points for three conditions among all hospitals and 0.65-1.78 for bottom quartile hospitals (Appari, Eric Johnson, & Anthony, 2012, p. 354).

This means that hospitals benefit from easier to understand electronic systems than more advanced ones. Either King Khalid University staff need to be trained more effectively on how to use the new system or the system must be simplified in order to decrease error rates and increase accuracy and clinical documentation.

There were improvements in the medical reconciliation aspect of King Khalid University Hospital. With an improvement of 9% from 76% to 85%, the new system implementation improved all departments, especially the Medicine department with a 48% improvement from 32% Medication Reconciliation fully completed.to 80%. Some department lowered their percentages nevertheless. These are ICU with a 7% decrease from 93% to 86%, OB/GYN with a 10% decrease from 100% to 90%, and Surgery with a 6% decrease from 83% to 77%. Further analysis is needed to understand why these decreases happened. While it is positive that the mean percentage increase after system implementation, the decreases in percentage in 3 of the 7 departments reveals a need for reassessment.

Before new system implementation, the medication error rate of King Khalid University Hospital was 4,440. These medication errors included prescribing, preparation, administration, dispensing, and monitoring. Improvements in the previous sections showed some success with the new system implementation. Conversely, no success came from the new system implementation for medication error rate. In fact, the data revealed the medication error rate increased many times over from 15% to 85%. Why then does a system increase medication error rate if it is meant to increase clinical documentation thereby increasing accuracy via transcription?

This is something that will be investigated further in the recommendations section. There were positive changes still, when examining mean value of wrong labeling of Specimens in female phlebotomy. The Mean value of wrong labeling fell from 0.02% to 0.00% showing some positive performance with the new system implementation. EMRs as hypothesized, led to an increase in medication...

There were some positives such as increased medical documentation and medical reconciliation along with a decrease in wrong labelling, but the system needs improvement and the staff operating the system need additional training.
The research methodology provided results that revealed poor overall performance for the e-SIHI system in regards to clinical documentation and medication errors. This is not to say E-SIHI does not work. This just means King Khalid University Hospital staff need time in adjusting to the system and perhaps further training so as to increase accuracy while using the system. Adjustment from paper-based records to electronic records takes time.

While electronic health records are extremely helpful when it comes to data collection and data transference, it also takes a long time for staff to be trained and get used to performing certain actions. The medical professionals ay King Khalid University Hospital are highly trained and qualified. However, the transition in just a short time will not produce 100% improvement. To see some improvement is a positive step forward towards a complete overhaul of the medical records system and effective performance within the hospital.

The first step to improve the effectiveness of the system is introduction of new techniques that may help provide a higher rate of efficiency and quality. A 2013 study examined the positive results from EMRs called 'chart biopsy'. The use of EMRs or as others refer to EHRs has facilitated a developing new practice that referred to as pre-handoff or chart biopsy: "the activity of selectively examining portions of a patient's health record to gather specific data or information about that patient or to get a broader sense of the patient and the care that patient has received" (Hilligoss & Zheng, 2013, p. 260). The study identifies three functions of chart biopsy. They are:

1. receiving a summary of the patient;

2. organizing for handoff as well as successive care;

3. and shielding against possible partialities.

Chart biopsies seem to influence significant organizational and clinical processes. Among these are the quality and nature of handoff interactions, including the quality of care, and the suitability of dispositioning of patients. Chart biopsies may be a way to improve E-SIHI in some of the areas the results demonstrated decreases in quality and accuracy. Remembering back to simplicity as a key means of improving transition from paper to electronic records, chart biopsies is just one of several solutions that will be examined in the recommendations section as well as what can be done with regards to the potential of a new system being introduced. This is because while some of the results were positive, they were not enough to say the E-SIHI should be kept.

Perhaps the solution lies in a gradual transition from paper records to electronic records. Meaning, a facilitation of both paper and electronic health records. This can help those not technologically savvy become used to the shift from paper to electronic records while still maintaining a high level of patient care and data collection. A 2014 study revealed the various feelings associated with EHR use and how physicians attempting to avert uncertainty avoided EHR use while those not affected by uncertainty used it more. "Drawing on theories from the medical and organizational literatures, we identified three categories of perceptions of uncertainty: reduction, absorption, and hybrid. Uncertainty reductionists tended to exhibit high levels of EHR use, uncertainty absorbers tended to exhibit low levels of EHR use" (Lanham et al., 2014, p. 73).

By attempting to understand why the E-SIHI system was not as successful as anticipated, the next steps for College of Medicine King Khalid University Hospital will prove more fruitful in the near future. Aside from the negatives, the positives like medical reconciliation shows that some aspects of the system are working and should be carried over to continue providing improvements with respects to certain medical errors. EHRs are a crucial and vital step to improving medical care. Electronic data is easy to use, easy to collect, and fast to transfer from one place to another. However, hospitals and clinics need time to make a transition like this effective.

Hospitals and clinics need to perform this transition gradually. This is especially true if the system is complicated or complicated for the medical staff at these hospitals and clinics. Additional training will allow the implementation of new systems like E-SIHI to be easier. However, a simpler system implementation, even a hybrid one may be easier overall.

Recommendations

College of Medicine King Khalid University Hospital has begun the process of converting paper records to electronic records. They have an IT department with an acting Chairman…

Sources used in this document:
References

Appari, A., Eric Johnson, M., & Anthony, D. (2012). Meaningful Use of Electronic Health Record Systems and Process Quality of Care: Evidence from a Panel Data Analysis of U.S. Acute-Care Hospitals. Health Serv Res, 48(2pt1), 354-375. http://dx.doi.org/10.1111/j.1475-6773.2012.01448.x

Boonstra, A., Versluis, A., & Vos, J. (2014). Implementing electronic health records in hospitals: a systematic literature review. BMC Health Services Research, 14(1), 370. http://dx.doi.org/10.1186/1472-6963-14-370

Chandra, H., Pandey, R., Sarkar, A., Naik, S., & Aggarwal, R. (2016). Introducing the Computer Aided Information Technology -- An Administrative Experience in Government Tertiary Care Hospital (An Innovation for Effective, Efficient and Healthy Practices by E-Governance). Indian Journal of Medical Informatics, 1(2), 68-81. Retrieved from http://www.ijmi.org/index.php/ijmi/article/view/327

Hilligoss, B. & Zheng, K. (2013). Chart biopsy: an emerging medical practice enabled by electronic health records and its impacts on emergency department -- inpatient admission handoffs. Journal of The American Medical Informatics Association, 20(2), 260-267. http://dx.doi.org/10.1136/amiajnl-2012-001065
Kellermann, A. & Jones, S. (2013). What It Will Take to Achieve the As-Yet-Unfulfilled Promises Of Health Information Technology. Health Affairs, 32(1), 63-68. http://dx.doi.org/10.1377/hlthaff.2012.0693
Kern, L., Barron, Y., Dhopeshwarkar, R., Edwards, A., & Kaushal, R. (2012). Electronic Health Records and Ambulatory Quality of Care. J GEN INTERN MED, 28(4), 496-503. http://dx.doi.org/10.1007/s11606-012-2237-8
Lanham, H., Sittig, D., Leykum, L., Parchman, M., Pugh, J., & McDaniel, R. (2014). Understanding differences in electronic health record (EHR) use: linking individual physicians' perceptions of uncertainty and EHR use patterns in ambulatory care. Journal of The American Medical Informatics Association,21(1), 73-81. http://dx.doi.org/10.1136/amiajnl-2012-001377
Low, D. & Bodnar, A. (2013). Update on Clinical Impact, Documentation, and Management of Complications Associated with Esophagectomy. Thoracic Surgery Clinics, 23(4), 535-550. http://dx.doi.org/10.1016/j.thorsurg.2013.07.003
Murdoch, T. & Detsky, A. (2013). The Inevitable Application of Big Data to Health Care. JAMA, 309(13), 1351. http://dx.doi.org/10.1001/jama.2013.393
Sharma, L., Chandrasekaran, A., Boyer, K., & McDermott, C. (2016). The impact of Health Information Technology bundles on Hospital performance: An econometric study. Journal of Operations Management, 41, 25-41. http://dx.doi.org/10.1016/j.jom.2015.10.001
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