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Power Form Optimization Proposal Daniella A. Wride College of Health Professions, Western Governors University Master of Science in Nursing, Nursing Informatics Beth Gordy 08/14/

Executive Summary (Completed in C855 Capstone Course) Note: The Executive Summary of your proposal paper is done as the last step of the paper, after completing your capstone CPE. Do not include the Executive Summary, Phase IV Monitoring, Maintaining, Supporting, and Evaluating, or Conclusion in your performance assessment submission for the Nursing Informatics Field Experience course. Planning and Analysis Designing and Building Implementing and Analysis Monitoring, Maintaining, Supporting, and Evaluating

The scholarly theory that will act as the project’s theoretical framework is the Change Theory. “Change theory is the study of change in individuals or social systems such as organizations. Understanding change theory provides a framework for effectively planning and implementing change in social systems and organizations. Healthcare information systems have a major impact on the structure and functions of healthcare delivery systems. They bring about significant change. The approach to managing the change process may result in a more effective and efficient healthcare delivery system or it may result in increased dissatisfaction and disruption,” (Nelson & Staggers, 2014). Changing the way documentation is done can come across as more burdensome for the end user. “The most common change for health professionals and informaticians is the introduction of or upgrade to a health information system. A commonly used model of the stages within the change is the System Life Cycle (SLC),” (Nelson & Staggers, 2014). This proposed system optimization aims to make the workflow easier, in turn increasing the number of times these Power Forms are documented on. Theoretical Framework and Process The theoretical framework that underlies this proposal is the Change Theory and the System Development Life Cycle. This will include four phases that will ultimately have the system enter the default value “See Scanned Report”. This system optimization change will save bedside nurses valuable time and allow them more time to focus on physical patient care. This autofill feature will also help to increase the utilization of these Power Forms and decrease the number of manual charting errors.

Phase one is the Planning and Analysis Phase. This will include the development of a table of the key informatics stakeholders and a summary of their roles and responsibilities in proposing change, innovation, and improvement to the usage of the EHR. The next task will be to perform a critical review of 10 sources from the literature or internet resources related to my system optimization proposal idea. I will then schedule and conduct a needs assessment meeting with key stakeholders and industry professionals and perform a Gap Analysis. Next a strength/weakness/opportunity/threat (SWOT) analysis will be performed on the organization’s readiness for change. A workflow analysis will be performed prior to the system optimization. Phase Two is the Design and Build Phase. This will present the opportunity to develop an Entity Relationship Diagram (ERD). This will include the data elements and the relationships between entities. Next, an interactive dashboard will be created to help evaluate real-time data regarding the system optimization. The next task will be to create Key Performance Indicators (KPIs) which will help the organization to make future decisions regarding the system optimization change. Phase Three is the Implementing and Testing Phase. The first task of this phase will be to create a Gantt Chart. This will help provide a visible timeline for the proposed project. The second task of Phase Three will be to perform System Integration Testing (SIT). This will test the integration of the changes that will be made to the current system and workflow. After SIT, User Acceptance Testing (UAT) will be performed. UAT helps the team to know if the changes made are compatible and accepted into the new workflow. Phase Four is the Monitoring, Maintaining, Supporting, and Evaluating Phase. This will include the maintenance and monitoring of the system optimization. This is done by documenting various maintenance or monitoring tasks. This includes the process or requirements

The system optimization proposal will allow for increased safety and decrease harm done to patients. By pre-programing the system to enter “See Scanned Report” when entering data into the Power Forms this will help to decrease data entry errors and improve safety for our patients. Ensuring the correct data is entered is imperative to patient safety. One study showed that “Improved safety and teamwork culture has been associated with decreased patient harm within specific units in hospitals or hospital groups,” (Berry et al., 2020). This article helped explain that improving this safety culture will help lead to decreased hospital mortality through the entire hospital system. The aim of this system optimization is to help create less time spent charting, reduce charting errors, and increase the patient's safety. “The existence of effective communication among health professionals reduces redundancy, saves time and increases patient safety and team satisfaction,” (Figueiredo & Potra, 2019). By improving the Power Form data that must be entered will help to do just that. This article helps to identify resources that can be used to help improve the communication and redundancy of handover information that must be transferred manually into the patient’s chart. A Systematic Review and Meta-Analysis was supported by the US National Library of Medicine of the National Institutes of Health (NIH). During this review, it was found that “rapid adoption of electronic health records (EHRs) following the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act has led to advances in both individual- and population-level health. HITECH has improved healthcare quality, patient safety, and diagnostic accuracy through enhanced data management and timely reuse; interoperable systems have facilitated care continuity and monitoring of compliance metrics. EHR-facilitated, guideline-based care has been associated with reduced redundancies and streamlined billing

administration,” (Moy et al., 2021). This helps to highlight that without system optimization, the EHR is less likely to function as intended. The optimization of these 16 Power Forms will help to create more reliable interoperable systems and streamlined documentation within the EHR. Also, this will help decrease errors, and improve healthcare quality and patient safety. Increase end-user experience and teamwork Prior to the system optimization, the end-user was required to enter not only the patient’s lab values, but a normal reference range for each lab entered. By implementing this new workflow we can increase the end-user's experience in a positive way and increase the amount of teamwork being done. A study highlighted in the Oxford Academic Journal states that, “The EHR, a tool intended to improve our ability to care for patients, has had the unintended consequence of impairing efficiency of practice, largely because of poor usability, the requirements for its use in regulatory reporting, and a shift of clerical data entry work to clinicians...In response, health systems are investigating ways to improve the provider experience, with a key priority being to enable provider efficiency within the EHR. An individual approach is to provide targeted EHR training to clinicians,” (DiAngi et al., 2019). One way this system optimization will help providers with their experience and efficiency is to automate the lab value reference range. This will help eliminate errors, decrease time spent charting, and improve workflow. One objective for this system optimization is to decrease the amount of time charting while increasing the number of times the Power Forms are used to enter Non-Intermountain Lab data. One study suggests that “to enjoy the benefits of documentation while simultaneously alleviating nurses’ negative experiences, our analysis points to at least three elements that could

documentation to release time back to direct patient care,” (Cooper et al., 2021). This article helps to support the system optimization proposal by helping us understand the current demands of clinical documentation and how nurses view how their time is spent with their patients. By further breaking down the workflow and proposing this system optimization we can help improve how time is spent caring for our patients. An integrative review of the concept of Patient Centered Care (PCC) shows that, “PCC is indeed a method of providing care, or the way in which nurses deliver care. To be person- centred, the nurse must recognise the person as unique, form meaningful partnerships, open a space within the doing of their day to involve and engage with the person, allowing the person control and power of their care,” (Byrne et al., 2020). In order to provide more PCC there must be time and space allowed for that relationship and connection to form. Prior to the system optimization, more time was being spent entering lab value data. Now with the change to the Power Forms, this frees up the nurse to have more interaction with the patient at the bedside, thus leading to more focused PCC. As a bedside nurse for a little more than ten years, I can say that the burden of documentation is never-ending. There is always something to chart whether that be an assessment, intervention, medication, patient response, hourly rounding, and so much more. So having the opportunity to automate even just a small portion of this task is extremely helpful, valuable, and time-saving. A quantifying study performed by Columbia University and Harvard Medical School showed that, “documentation burden is a well-documented problem within healthcare, and improvement requires understanding of the scope and depth of the problem across domains. Increased automated device integration and novel approaches to decrease data capture burden (e.g., voice recognition), may increase nurses’ available time for interpretation,

annotation, and synthesis of patient data while also further advancing the richness of information within patient records,” (Collins et al., 2018). One study highlighted that although the implementation of an EHR was intended to help reduce charting time it in fact added more to that time spent documenting. The study states that “implementation of a structured and standardized EHR was associated with 8.5% decrease in time for dedicated patient care during consultations in one center and 8.3% increase in dedicated documentation time in another center. These results are in line with physicians' concerns that the introduction of a structured and standardized EHR might lead to more documentation burden and less time for dedicated patient care,” (Joukes et al., 2018). This system optimization is to help streamline and automate more of the workflow to help lessen the burden of documenting and increase the amount of times the Power Forms are used. With these sources the system optimization is shown to improve end-user and patient satisfaction by increasing the amount of times the Power Forms are filled out due to ease of workflow. This will in turn decrease safety events and prevent patient harm. The system optimization will also improve team work and time spent at the bedside as this will be a much faster way to document the Non-Intermountain Lab results. Gap or Problem in Context of Literature Prior to system optimization, nurses were having to manually enter Non-Intermountain Lab Data into 16 different Power Forms. Not only entering the patient’s result, but normal value ranges for all lab values entered. This was time-consuming, increased cost, increased risk for error in documentation, and decreased use of the Power Forms themselves. From the literature in part B it was identified that to provide Patient Centered Care (PCC) the care team must diligently

I then scheduled and conducted a needs assessment meeting with key stakeholders and industry professionals and preformed a Gap Analysis. By preforming this Gap Analysis it helped to clearly see how the 16 Power Forms were functioning currently, define the gap in care, and propose an action plan for improvement. I then created a workflow analysis that proposed the change to the 16 Power Forms. This helped clearly define the end goal for our end users and view exactly how their workflows would be impacted. Next a strength/weakness/opportunity/threat (SWOT) analysis was performed on the organization’s readiness for change. This helped the team to see the reasoning behind why the proposed system optimization would be beneficial to our team. By analyzing the strengths and opportunities versus the weakness and threats it was proposed we move forward with the system optimization plan. The strength and opportunities, such as, process improvement, increasing utilization of the Power Forms, optimizing the utilization of resources, spending less time charting, and more time at the bedside made it clear that we should move forward with the proposed system optimization. Needs Assessment To perform the needs assessment, I first had to identify the organization's current needs and the Key Stakeholders that will be involved. Please see Table 2 Key Stakeholders table in the Appendix for further information. This led to the system optimization proposal to autofill the text “See Scanned Report” into the 16 Non-Intermountain Lab Power Forms to help increase the utilization of these forms. I then met with Key Stakeholders to collect information and gather data. This helped to better understand the Gap in care and come up with the system optimization

proposal, workflow analysis, and SWOT analysis. I then met with the Key Stakeholders again and presented my various analysis’ and asked for feedback on the proposed system optimization. Gap Analysis The system requires users to input each normal range value for a lab result entered from a Non-Intermountain lab. There was an update to the Non-Intermountain lab forms requiring the reference ranges if a value is entered. This has led to less utilization of the Power Forms altogether. The reference range needs to be entered OR the report needs to be scanned and indicated on the form that the report has been scanned. The Gap analysis helped to identify that we could configure the Non-Intermountain lab Power Forms to autofill the reference ranges with the text “See scanned report. The Gap Analysis helped to further identify that a label would need to be added to this indicating that the staff filling out the form should not click on the button to auto-fill the reference ranges until after they have scanned the report. End users would then need to add a label to the forms as requested and update sections to be compliant with Build & Config Power Form standards. Please visit the Appendix to view Table 3 Gap Analysis for System Optimization. Workflow Analysis Prior to the system optimization a workflow analysis was performed. It was found that the amount of data entry for nurses for Non-Intermountain Lab results was burdensome and time- consuming. This led to less usage of the Power Forms themselves. The development of a workflow analysis was completed. Please see Figure 1 Workflow Analysis Diagram in the Appendix to view the completed diagram.

The identified strengths were decreasing time spent charting, process improvement, better utilization of resources, and a more streamlined process. The opportunities were innovation and technological advancement, less time charting, more time at the bedside, and less margin of error for manually entered data. The SWOT analysis helped to determine that the system optimization proposal would be very beneficial to the organization. The organizational readiness is clear with the strength and opportunities that were identified because the goal is to increase the utilization of the Power Forms and that is what the system optimization will do. Feasibility Analysis After analyzing the resources needed, and the resources available, performing a Gap Analysis, Workflow Analysis, SWOT Analysis, and meeting with Key Stakeholders the proposed system optimization change is feasible. The Gap analysis shows that the system requires the user to input each normal range value for a lab result entered from a Non-Intermountain Lab. By feasibly implementing this change the user's Workflow will be improved by spending less time charting, increasing the number of times the forms are used, decreasing the margin for error with manually entering data, and increasing the utilization of resources. Proposal for Addressing Identified Gap or Need The proposal is to autofill the sections of the 16 Non-Intermountain Lab data Power Forms with “See scanned report”. This will eliminate the need for the bedside nurse to manually enter the normal value range for labs. This will help increase the utilization of these Power Forms. Leading to more Patient-Centered Care, less margin for error, and an improved documentation process.

Phase II: Designing and Building Entity Relationship Diagram (ERD) The entity relationship diagram (ERD) tables, including the data elements and relationships were based upon the following query provided by a Key Stakeholder: clinical_event = c, encntr_alias = ea, prsnl = p1, encounter = e, encntr_alias = ea2, person = pe, encntr_loc_hist = e join e1 where c.encntr_id = e1.encntr_id and c.event_end_dt_tm between e1.beg_effective_dt_tm and e1.end_effective_dt_tm join ea where e1.encntr_id = ea.encntr_id join p1 where c.verified_prsnl_id = p1.person_id join e where c.encntr_id = e.encntr_id join ea2 where ea2.encntr_id = e.encntr_id join pe where pe.person_id= e.person_id With this provided query I was able to include all the data elements and relationships required for the system optimization. Please see Figure 2 Entity Relationship Diagram in the Appendix for the completed diagram. The ERD will allow for further inquiries to be made later down the road to show the effectiveness of the system optimization. There are seven entities within this ERD. They are Clinical Event, Event Location History, encntr_alias, Encounter, person, prsnl, and encntr_alias2. The entity Clinical Event has a Primary Key of clinical_event_id. The attributes are c.encntr_id, c.event_end_dt_tm, c.performed_dt_time, c.event_cd, c.updt_dt_tm, and c.verified_prsnl_id. There is a one or more to one and only one relationship with the c.verified_prsnl_id to p1.person attribute from the prsnl entities. There is a one and only one to one and only one relationship with c.encntr_id to e1.encntr_id from the Encounter Location History entity. The next relationship is a one and only one to one and only one from c.encntr_id to e.encntr_id from the Encounter entity. The next relationship is a one or more to a one or more

only relation on this entity is a one or more to one and only one from pe.person_id to e.person_id from the Encounter entity. The entity prsnl is next, the Primary Key is person_id. The attributes are person_id, p1.active_ind, p1.person, and p1.end_effective_dt_tm. There is a one and only one to one or more relationship between p1.person to c.verified_prsnl_id from the Clinical Event entity. The last entity is the encntr_alias2 which has a Primary Key of ea2.encntr_id. The attributes are ea2.encntr_id, ea2.alias, ea2.encntr_alias_type_cd, and ea2.active_ind. There is a one and only one to a one and only one relationship between ea2.encntr_id and e.encntr_id from the Encounter entity. Dashboard The Non-Intermountain Power Forms were implemented, and the optimization and use of each Power Form have gone up over the last few months of implementation. Please refer to Figure 3 Dashboard Diagram for a visual. There are six interactive dashboard platforms. Count of table by year and month, count of time by year and month, count of table by event, count of table by encounter type, count of table by facility, and count of table by unit. Both the count of table by year and month and the count of time by year and month allow an overlook at how often the Power Forms are being accessed and documented. As you can see the number of times these Power Forms have been documented has gone up since implementation of the system optimization. As for the count of table by event this allows us to funnel down to view which Non-Intermountain Lab Power Form is being used the most out of the 16 that were involved in this system optimization. Next the count of table by encounter type allows us to see what type of encounter the patient was being see for. Whether that be as an

inpatient, in a clinic, etc. The count of table by facility shows how often each hospital is using the Power Forms over time. The count of table by unit further details specific units that are using the 16 Power Forms. All of these show how often the Power Forms are being used from January 2023 to June 2023. KPI and Data Element Descriptions KPI 1: Optimize Non-intermountain Power Forms to all 16 Non-Intermountain Power Forms. The Non-Intermountain Power Forms were implemented, and the optimization and use of each Power Form has gone up over the last few months of implementation. The measurements were calculated by calculating the number of times the Power Forms were used from January 2023 to June 2023. This data was entered into Excel and then exported to Power BI. An interactive dashboard was then created to help measure these metrics and provide real-time progress updates. Within the interactive dashboard, we are able to funnel down to each one of the 16 Power Forms or view them as a whole. KPI 2: Measure the utilization of the updated Non-Intermountain Power Forms. As shown on the provided dashboard, once the Non-Intermountain Power Forms were updated the utilization of each Power Form has gone up over time. The measurements were calculated by counting the number of times the Power Forms were used from January 2023 to June 2023. This data was entered into Excel and then exported to Power BI. An interactive dashboard was then created to help measure these metrics and provide real-time progress updates. There are six interactive dashboard platforms. Count of table by year and month, count of time by year and month, count of table by event, count of table by encounter type, count of table by facility, and count of table by unit.