Part 3:   | Nursing

Clinical Requirement:

WorkflowRedesignModelAnalysis.docx 1 Part 2 Model Analysis Your Name Institution Name of Course Your Professor Due Date Part 2 Model Analysis Summary of the Gap Analysis Results Gap analysis, also referred to as the need analysis is is needed in EHR today’s comparison to the wanted position in the future as it is needed elsewhere (Conti, 2022). This study, therefore, engages previously sought analysis to establish the results obtained, how they relate to set objectives, and some identified loopholes within the system. The following are some of the results as identified by the analysis. First, the analysis was able to establish the existing gaps between patient registration information and the existing health records information. Ogilvie (2020) shows that the identification of inconsistencies between the patient-recorded information and the already existing health records is one of the steps to reducing the amount of time required to accomplish the refill process. The process was also able to identify a few more loopholes within the system, which included the following. First, there were delays encountered in the retrieval of patient data in custody with facility clerks due to the inconvenience of the manual filling system. To embrace a smoothly running process, Ogilvie (2020) advocates for the endorsement of an automatic filing system. Next, in efforts to explain the variance in data records between patient-recorded information and already existing file records, the analysis found that inefficiencies existed between the communication models embraced by the medical staff in obtaining the data from the serviced patients, featuring as clients in this case. Another result of the analysis was the identification of an existing skill gap, which was based on the interviews that were carried out. The interviews revealed that individual members of the staff found it beneficial to have tailored bits of training in particular areas where the workflow as a whole needed to be improved. This can be used to ensure consistent improvement in the workflow. As for the process of refilling medications, the investigation revealed that there is a requirement for the implementation of process automation in order to influence the drug refilling procedure. Given the findings of this model, it is imperative that a greater amount of focus be placed on the implementation of an automated medicine refill system. How the Results Address Goals Set From the set objectives, the following is an analysis of how obtained results align to address set goals. First, in the goal set to identify significant gaps, the results obtained can be seen to align with this objective. The results depict that manual procedures used to record patient data for the filling process are a significant contributor to inefficiencies and variances with already existing patient records. In response to this, a set objective to achieve seamless processes aligns with the model results that recognize the need for process automation to avoid discrepancies from the manual system (Zheng et al., 2020). Next, the skill gap aligns with the model objective to address the gaps that work towards enhancing the staff’s capacity to tackle automated processes. Gaps/Issues in Current Workflow The identified model analysis effectively demonstrates the major concern in the current workflow as the complexities in the integration of the manual filing system with the automated EHR system (McGonigle & Mastrian, 2022). Before the process reaches the medical assistant, clerks have an earlier interaction with the patient’s data, which they convey to the automated system. Clerks, therefore, appear as intermediaries between the manual filing and the automated system. In the interview questions, however, clerks recommended in-person training with the automated system. Questions also arise about the accuracy of clerks in keying in patient-retrieved data. Secondly, the variance between retrieved existing client information to obtained data from the communication inefficiencies that arise between clerks and the patient in the data recording phase is attributed. Limited automation in the conclusion part of the refill process also accounts for the inefficient procedure of medical refills. This time-consuming process is evident when the pharmacist has to make manual/ verbal communications to the client/patient explaining medication prescriptions or the reason for failure. Manual communications increase the likelihood of error by lacking real-time updates (Zheng et al., 2020). Thus, it should be eliminated. Issues Relation to EHRs and any Meaningful Objectives The major concern of delays attributed to the manual integration with the automated system has a direct relation with the EHR, where clerks interact as intermediaries between both systems. In the meaningful use objective, a conflicting concern arises where a seamless transition is expected, but instead, the system amounts to time wastage. The gap in communication inefficiencies, on the other hand, has a direct relation to the EHR through a denied real-time update of the system. Towards the meaningful objective, McGonigle and Mastrian (2022) show that inefficient communication between pharmacists and patients in communicating refill communications poses a significant safety threat to the patients. Refined Model To summarize, the final model, which is depicted in Figure 1, tries to get rid of redundant tasks inside the system to make it more efficient by integrating some manual functions into the electronic health record system. The workflow gap, on the other hand, continues to exist, which involves the clerk still manually involved in the process of processing client requests and acquiring patient data for the reimbursement appeal. However, the system is improved and more efficient once the duties have been transferred to the MA, all of the procedures that are involved are then automated. The system will automatically create relevant answers in the form of text messages, explaining the reason for failure or prescriptions if a refill is permitted, regardless of whether the request is approved or whether it is denied. Figure 1: Refined model References. Conti, S. (2022). Filling the Gap Between Potential and Actual Usefulness of Electronic Health Record (EHR) Data as Patient-Level Evidence.  Medical Decision Making, 42, 973 - 974. https://doi.org/10.1177/0272989X221129229 McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. Ogilvie, J. (2020, September 2). Patient-centered, integrated healthcare quality measures could improve health literacy, language access, and cultural competence. National Academy of Medicine. https://nam.edu/patient-centered-integrated-health-care-quality-measures-could-improve-health-literacy-language-access-and-cultural-competence/ Zheng, K., Ratwani, R. M., & Adler-Milstein, J. (2020). Studying Workflow and Workarounds in Electronic Health Record-Supported Work to Improve Health System Performance. Annals of Internal Medicine, 172(11 Suppl), S116–S122. https://doi.org/10.7326/M19-0871 image1.png WorkflowModelAnalysis.docx 2 Workflow Model Analysis Your Name Institutional Affiliation Your Course Your instructor Due Workflow Model Analysis The workflow issue, how it is tied to EHR and meaningful use objective(s) related to it In the context of electronic health records (EHRs), one of the workflow issues that arises is the problem of patient registration and the checking of the patient's medical history, especially the procedure of medical refills before and after the implementation of EHR. This problem is connected to electronic health records (EHRs) in the sense that mistakes associated with EHRs would undoubtedly be caused by incorrect setup of EHR systems or incorrect usage of EHRs (Zheng et al., 2020). These mistakes would otherwise put the confidentiality of the information contained in EHRs at risk, which would result in inaccuracies that would in turn reduce the quality of care provided to patients and put their safety at risk (Zheng et al., 2020). The meaningful use objectives that are associated with this workflow problem comprise the provision of care that is both safe and of high quality to all patients, as well as the guarantee of convenience in the delivery of medical care. Analyze the workflow issue IOM six aims of care (patient-centered, timely, effective, efficient, equitable, and safe). The six aims of care were established to guide the evaluation of healthcare delivery (McGonigle & Mastrian, 2022). With the patient's registration and medical history in mind, the aims of care can be analyzed as follows: Patient-centered- the patient's wants, needs, and comfort should be the first consideration throughout the registration process. Is the registration process user-friendly? Is the patient's perspective sought after to fill out their medical history accurately and completely? Timely- how long does it take for a patient to finish the registration process? As a result of ineffective registration processes, is there a wait time for appointments or for access to medical records? Effective- does it capture a full medical history and other pertinent information to guarantee proper treatment; Has the registration procedure been inefficient, resulting in duplicate or missing information in the patient records? Efficient- does it save time and effort for both staff and patients by streamlining and optimizing the registration process to cut down on administrative tasks and wait times. Equitable- does the registration procedure take into account the various requirements of the patient population, guaranteeing that everyone has equal access to healthcare services? Safe- is patient information kept private and protected during the registration process? Does the system have safeguards to avoid the accidental or intentional omission of vital medical data? List 2–3 goals you have set for your gap analysis and what you hope to accomplish by examining the workflow concern you selected. Finding the most significant gaps in patient registration and health history information is one of the goals. In order to avoid unnecessary delays in the refill process, it is necessary to identify the points of bottlenecks (Ogilvie, 2020). The second goal is to find out whether there's a way to automate the whole process so that it runs as smoothly as possible. This section focuses on the electronic health record (EHR)-enabled drug refill procedure. Lastly, for both present and future needs, the study must pinpoint skill gaps that may necessitate personalized training. In order to address these crucial elements that affect the quality and safety of patient-accessible care, it is necessary to examine the workflow process. Describe your methods of data collection and the individuals you will observe, consult, and/or interview. Include any relevant narrative statements, checklists, interview questions, or other tools you commonly use to collect data in a workflow analysis. The primary methods of data collection will mostly involve observation and interviews. The clerks and medical assistants will be interviewed. Unless the medical assistants and clerks are really busy, it will be required to conduct the interviews orally (Tate & Smallwood, 2021). In such instance, these experts will be provided with written questions that they may finish whenever it is most convenient for them. The questions that will be asked verbally and in written surveys will be identical. As the EHR streamlines the procedure of drug refills, every information will be considered in the observation. It is also necessary to review the medical records. They will be asked the questions that are shown in the following instrument. Question Reply Shortly discuss the medication refill procedure? Which shortcomings do you face in the procedure? What are the key areas that you face interruptions? Which zones have been improved/are high effectual in the workflow? What rating can you give to the functionality of this workflow? Any outdated activities that you think should be removed without affecting the workflow severely? Explain how you will minimize disruption in the workflow during observations and how you will avoid bias as you conduct your gap analysis. It will be necessary to do the observations at critical places when movements are limited in order to prevent disturbances in the workflow during the observation activity. We will try not to ask for interpretations of what is happening during the observation process by inquiring about each point in advance. So, there will be zero disruption during the activity. By taking careful notes during verbal information gathering, the possibility of bias in the gap analysis process caused by selective recollection, inconsistent data collection, or information bias can be eliminated (Tate & Smallwood, 2021). To ensure that no detail is missed or overlooked throughout the gap analysis, sufficient time will be set up to observe each procedure. Standardized interviews will help eliminate problems like interviewer bias. In computer-assisted interviews, extraneous questions will be skipped over, and inconsistent material may be rapidly identified and removed. It ensures that the data that will be utilized for analysis is standardized and polished Describe how you will record, quantify, and analyze the data you collect. Explain how you will establish baseline metrics to normalize data from different sources of information. Information will be documented by providing concise summaries of every procedure as it is seen. The statistics gathered from the in-person interviews will be entered into a database by use of the questionnaire. For individuals who would rather fill out a paper questionnaire, recording will be a breeze as they will just provide pre-recorded data. Here, the data to be analyzed will be mostly qualitative data since the main interest is in the procedures involved in the medication refill process. The method will also record any inefficiencies or delays that are observed. These details will also be gleaned from the surveys and interviews. The areas that need to be addressed will include those that are identified as problematic in the interviews and questionnaire, as well as those that are seen (McGonigle & Mastrian,2022). For the sake of uniformity, it will be necessary to review all of the data. In order to identify the pattern, it is necessary to synchronize the sequence in which these actions occur. An overview in the form of a gap analysis or work flow will be provided, outlining the likely areas that need to be enhanced. Illustration of the current state workflow The implementation of EHR is evident from the aforementioned workflow, however a significant part of the medication refill procedure is still manual and time-consuming (CGI, 2014). For example, before the medical assistant can access the patient's chart, the clerk must retrieve it, attach the fax, and submit the information. The minute the doctor decides to renew or not renew the prescription, the medical assistant must get in touch with the patient or pharmacist once again. Better or automated methods can replace all of the bolded phases below. Chart retrieved, faxed medical request and assessments (clerk) GGR Refill request received by fax(clerk) Chart and slip put in basket (clerk) Client chart taken, clips refill appeal (clerk) Yes No Renew medication (MA) Reason documented for decline (MA) Send eRx to pharmacy through EHR (MA) Refill appeal complete (MA) Chart put back on tray (Clerk) Patient told the cause for rejection (MA) References. CGI. (2014). Health information integration: Using gap analysis to develop relevant solutions. Retrieved from https://www.cgi.com/sites/default/files/white-papers/cgi-health-integration-gap-analysis-paper.pdf McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. Ogilvie, J. (2020, September 2). Patient-centered, integrated health care quality measures could improve health literacy, language access, and cultural competence. National Academy of Medicine. https://nam.edu/patient-centered-integrated-health-care-quality-measures-could-improve-health-literacy-language-access-and-cultural-competence/ Tate, A., & Smallwood, C. (2021). Comparing the efficiency of paper-based and electronic data capture during face-to-face interviews. PloS one, 16(3), e0247570. https://doi.org/10.1371/journal.pone.0247570 Zheng, K., Ratwani, R. M., & Adler-Milstein, J. (2020). Studying Workflow and Workarounds in Electronic Health Record-Supported Work to Improve Health System Performance. Annals of internal medicine, 172(11 Suppl), S116–S122. https://doi.org/10.7326/M19-0871 image5.png image6.png image7.png image8.png image9.png image1.png image2.png image3.png image4.png