Part 3_ Reworkflow Design

This gap analysis identifies inefficiencies in the electronic health record system (EHR-S) and recommends the optimization of the EHR-S. This optimization will enable the health information systems to improve the healthcare quality. The gaps identified were due to the standard workflow that is not working optimally as needed in the EHR-S. To improve the healthcare quality, the EHR-S needs to redesign and systematize the workflow practice (Davis-Ajami, Costa, & Kulik, 2014). It is recommended that an informatic department and a quality department be established as the first steps in improving the quality of healthcare systems.

One way to redesign the workflow is to renovation the preventive screening. With the new workflow, if a nurse receives preventive screening alert, the nurse can start a laboratory order without obtaining authorization from the physician. This new design will not only save time but will also assist the healthcare to ensure the patients get preventive screening, thus improving the healthcare quality.

Analysis of How the Identified Issues Relate to EHR

Disease Management health agencies are involved in population-based surveillance of diabetes occurrences and diabetes preventive involvements. Information produced over the continuum of diabetes care, and population-based surveillance is of enthusiasm to patients, their guardians, healthcare providers and disease managment health officers. However, there is no incorporation crosswise over different information systems EHR-S, laboratory information management systems (LIMS), disease managment health registries, and quality measurement registries (Glaser, 2008); that are involved in the health data exchanges identified with diabetes care. Because of the absence of integration with EHR systems, disease managment health organizations use stand alone non-clinical information sources, for example, in state and national surveys for diabetes surveillance. There is no accord on the general content of data exchange crosswise over clinical and disease managment health information systems (American Diabetes Association, 2015).

Current-State Workflow

The patient visits the healthcare provider where the clerk conducts registration, obtains patient consent(s), and starts the encounter in EHR-S. The Nurse obtains vital signs and enters data into EHR-S. Then, the physician conducts the exam and enters exam data into EHR-S. The care manager communicates with clincial practice guideline manager to retrieve the care guidelines for the chronic disease (diabetes) and queries the database determining that the Patient is due for a HbA1c test and to generate reminder.

Next, the physician orders HbA1c test via EHR-S and the Nurse receives the order via EHR-S, draws blood specimen, completes that order in EHR-S sends the specimen to the laboratory. Then, EHR-S sends the Order transaction to LIMS. The EHR-S receives order completion notification from LIMS using the lab messaging technical framework. The EHR-S receives HcA1c test Results from LIMS, which may be conducted using either messaging or document sharing.

If the order completion notification indicates abnormal results, EHR-S notifies appropriate physician to review results. This may use a forthcoming HIE alert profile, which will communicate the abnormal results and support confirmation of receipt of the abnormal results by the physician. If the results are normal, the physician communicates HcA1c test results to patient.

The care manager generates care plan based on the Hb1c test results and then the physician reviews the care plan. The EHR-S generates care quality reports based on the HbA1c test results, and EHR-S receives notification that diabetes surveillance reports are available in health information exchange (HIE). Then, the health care providers and support staff downloads diabetes surveillance reports from HIE into EHR-S.

Flow of Activities in the Laboratory

The laboratory receives HbA1c test order via EHR-S, and the laboratory personnel processes the specimen (receives/logs-in/analyze) and enters HbA1c test results into LIMS. Then, the LIMS send order completion notification and HbA1c test results into EHR-S and then publishes the HbA1c test results into HIE. The HIE allows health care providers and patients to safely access shared patient’s medical information electronically by improving the quality, time, and cost of patient care (Saba & McCormick, 2015).

The Flow of Activities in the Disease Management Diabetes Information System

The disease management information system (DM-IS) receives order completion notification from HIE and downloads pseudonymized HbA1c test results from HIE. The Diseae Manager Program Officer (Data Manager or Case Manager) runs diabetes surveillance reports periodically as required by jurisdiction. Then, the DM-IS publishes diabetes surveillance information systems reports via HIE.

Lessons Learned

Based on the feedback I received, I eliminated some of the acronyms like LIMS and used laboratory instead. Also, according to Davis-Ajami, Costa and Kulik (2014) that gap analysis is critical in not only identifying, but also understanding and addressing bridge gaps that frustrate the delivery of quality services in nursing practice. In this light, conducting a gap analysis offers structure for gathering information, as well as, a process for finding solutions to address the deficiencies effectively (Brokel, 2009). The effect is mapping out, as well as, sustaining corrective actions that help close quality chasm.

Conclusion

The difficulties faced in fighting diabetes has been largely attributed to the fragmented, duplicative, and disorganized healthcare systems that emphasizes on acute conditions and complications than on controlling this chronic disease American Diabetes Association, 2015). The workflow developed in this paper describes a diabetes registry system that changes the way healthcare providers manages patients with diabetes. The implementation of this Diabetic Healthcare will help in coordinating the accountabilities for intervening and monitoring patients in the system with ease.

Reference

American Diabetes Association (2015). Standards of medical care in diabetes. Retrieved from

http://www.diabetes.org/research-and-practice/we-support-your-doctor/clinical-practice-recommendations.html

Brokel, J. M. (2009). The infusing clinical decision supports interventions into electronic health records. Urologic Nursing, 29(5), 345–352

Davis-Ajami, M. L., Costa, L., & Kulik, S. (2014). Gap analysis: Synergies and opportunities for effective nursing leadership. Nursing Economics, (1), 17.

Glaser, J. (2008). Clinical decision support: The power behind the electronic health record. Healthcare Financial Management, 62(7), 46–48, 50–51. 

Saba, V. K., & McCormick, K. A. (2015). Essentials of nursing informatics (6th ed.). New York,

NY: McGraw-Hill.

Walden University M.S. in Nursing

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