Introduction
It is important to note that an electronic health record (EHR) system is a healthcare enhancement instrument designed to improve the organization, collection, sorting, filtering, and analysis of medical data. It is enabled by technological advancements in recent decades, which allowed healthcare professionals to better their decision-making as well as accuracy in delivering healthcare services. The given analysis will primarily focus on assessing an existing market clinical decision support system or CDSS as well as its unintended consequences.
System Development Life Cycle (SDLC) Implementation and Evaluation Stages: Proposed EHR/EHR Application/Feature
System Development Life Cycle
The system development life cycle, or SDLC, is a circular process outlining critical phases of each step taken in order to ensure a smooth and effective integration of a system into healthcare operations. SDLC is comprised of five core stages, which include planning, analysis, design, implementation, and evaluation (Egwoh & Nonyelum, 2017). The implementation stage is the most vital step in the practical realization of the previous planning and testing processes, where the system is integrated into operations. It is critical to ensure that all the actions undertaken are adherent to the plan with consideration for maintenance and unexpected barriers (Egwoh & Nonyelum, 2017). The role of the DNP is to assist the technical team by ensuring that data quality is properly assessed, processed, and guided, and new workflows are established. For the evaluation stage, the system’s impact and improvement changes are assessed by using comparative analyses with the metrics collected before the integration (Egwoh & Nonyelum, 2017). The role of the DNP is to ensure that the comparison is conducted in accordance with the core priorities of a healthcare organization by focusing on patient outcomes, patient safety, healthcare service quality, and medical error reduction.
CDSS and Parkland Health and Hospital System
The CDSS is a clinical decision support tool integrated within the EHR environment. An example of a CDSS existing in the current market is McKesson Corporation’s CDSS called Personal Health Adviser (PHA) (Islam et al., 2021). It is prevalently utilized in the healthcare market as a “computerized decision support software (CDSS)-integrated telephone triage (TT)” (Islam et al., 2021, p. 107). One of the largest users of the CDSS is UK’s public health service NHS. The purpose of the PHA is to make decision-making processes quicker, more accurate, and more effective in emergency departments, which are struggling with high demands and overcrowding (Islam et al., 2021). Its largest client and user is NHS, which continues to utilize the CDSS in its emergency departments successfully. The identified organization is Parkland Health and Hospital System, which is considered to be the most overflown ED in the US (Bean, 2022). PHA will be mainly used for clinical decision-making purposes to reduce medical errors as well as improve the speed of decision-making. Since many steps in decision-making and approvals essentially follow the same pattern outlined by protocols and codes, using technology is a plausible solution.
Healthy People 2030
The PHA CDSS meets two developmental objectives of Health IT of Healthy People 2030. The system extension contributes to increasing “the proportion of hospitals with access to necessary electronic information – HC/HIT-D06” (U.S. Department of Health and Human Services, 2020, para. 4). In addition, it increases “the proportion of doctors with electronic access to information they need – HC/HIT-D07” (U.S. Department of Health and Human Services, 2020, para. 4). It should be noted that time is one of the most critical and deciding factors in an ED environment, where the decision is primarily halted and slowed by the lack of essential data on a patient. The PHA CDSS allows relying on efficient telephone triage to prepare all the arrangements for a specific patient beforehand in order to provide the healthcare service as soon as the individual arrives. The latter is achieved through PHA by enabling greater access to electronic health information for both hospitals and doctors.
HITECH
Two of the key goals of the HITECH Act of 2009 include system interoperability and medical device integration. System interoperability refers to the creation of a framework “to connect EHR systems so that physicians can easily share their patients’ records with other providers regardless of the software being used” (Reisman, 2017, p. 573). In other words, it is about two systems being able to freely and efficiently exchange data when needed. Medical device integration is a solution where patients’ vital signs data collected from a wide range of medical instruments is automatically integrated into the EHR (Reisman, 2017). The PHA partly meets the interoperability goal of HITECH by facilitating the patient arrangement preparation by obtaining the patient data from the EHRs. In addition, an emergency team delivering the person can be considered a small system on its own with the most recent data on the patient’s condition. However, the PHA best meets the medical device integration goal by integrating data from the emergency team’s devices into a larger network.
NQF
One identifiable National Quality Forum metric that can be used to evaluate end-user or stakeholder satisfaction with the system post-implementation is 0289 Median Time to ECG. It is the “median time from emergency department arrival to ECG (performed in the ED prior to transfer) for acute myocardial infarction (AMI) or Chest Pain patients (with Probable Cardiac Chest Pain)” (National Quality Forum, 2022, para. 1). It is an ideal metric to use since PHA is primarily about time reduction between patient data collection to healthcare service delivery. If a patient’s information is collected beforehand and arrangements are made before his or her arrival, then the delivery of ECG will be significantly faster, leading to a decrease in the meantime.
Evidence
The evidence needed to determine whether further training for system users is required post-implementation comes from a research article with a case analysis of NHS and PHA. After nursing professionals were trained in a span of three to six months, “nurse-operators’ CDSS protocol choice matched the gold standard 94.1% agreement at baseline and 98.7% at follow-up” (Islam et al., 2021, p. 107). In other words, the initial training of nursing specialists is not sufficient since more improvements can be made within the first several months after the implementation of a system.
Additional Metric
An additional metric proposed for the assessment of the effectiveness of PHA is to measure the median time of the process of preparation and collection of patient data itself. In other words, it will provide a more systematic overview of how much time is needed to make arrangements for a patient on the way to ED (Islam et al., 2021). It can be a determining factor in a high-demand environment, where several patients are being delivered to the department.
Assessing E-iatrogenesis or the Unintended Consequences of the PHA
One major unintended consequence of PHA is a reliance on telephone triage, which can become a barrier to the full digitalization of healthcare processes since it relies on telephone calls as well as human specialists. The approach itself is highly effective, but it has a low ceiling for automating the processes since calls are mostly about verbal communication rather than purely digital (Kirkley, 2019). Creating a technology with the ability to replace an effective telephone triage is not as easy as with other medical services. Therefore, the unintended consequence is the inability of EDs to fully integrate the patient data collection into the existing systems reducing interoperability (Azarm et al., 2017).
The proposed remediation plan is to have an electronic health platform or system built around PHA since the latter is irreplaceable in the near future. The emphasis needs to be put on training nursing professionals operating the process to ensure that triage is their sole responsibility to increase efficiency, safety, and quality (Reisman, 2017). The inter-professional team needs to build around the triage team as well to fully maximize preparedness and speed of preparation for the patient’s arrival.
Conclusion
In conclusion, the given assessment analyzed a CDSS system called PHA proposed for America’s one of the most overcrowded EDs, Parkland Health and Hospital System. The system is an extension of EHR designed to make a telephone triage highly time efficient and quick. It meets the HITECH goal of medical device integration since the devices in emergency service vehicles become integrated into a larger system through the process. Its major unintended consequence is an inability to fully integrate the process through digitalization and automation since it inherently relies on human verbal communication. Since there is no foreseeable replacement in the near future, it is recommended to focus on building the procedural environment around telephone triage by focusing on training.
References
Azarm, M., Backman, C., Kuziemsky, C., & Peyton, L. (2017). Breaking the healthcare interoperability barrier by empowering and engaging actors in the healthcare system. Procedia Computer Science, 113, 326-333.
Bean, M. (2022). 30 hospitals with the most ER visits.Hospital Review. Web.
Egwoh, A. Y., & Nonyelum, O. F. (2017). A software system development life cycle model for improved students’ communication and collaboration. International Journal of Computer Science & Engineering Survey, 8(4), 1-10.
Islam, F., Sabbe, M., Heeren, P., & Milisen, K. (2021). Consistency of decision support software-integrated telephone triage and associated factors: A systematic review. BMC Medical Informatics and Decision Making, 21, 107.
Kirkley, L. (2019). Telephone triage protocols: Training, sustaining, and overcoming barriers to use.AAACN Viewpoint, 41(1), 3-8. Web.
National Quality Forum. (2022). Median time to ECG. Web.
Reisman, M. (2017). EHRs: The challenge of making electronic data usable and interoperable.Pharmacy and Therapeutics, 42(9), 572–575. Web.
U.S. Department of Health and Human Services. (2020). Health IT. Web.