Responses

Victoria Discussion:

Hello All,

My proposal focuses on streamlining prior authorization (PA) workflows for pediatric autism therapy services to reduce care delays, administrative burdens, and financial strain. To evaluate program success, we will measure a reduction in PA turnaround time from 10 to 7 business days within six months, a 30% decrease in initial PA denial rates within one year, and a 20% improvement in staff satisfaction based on pre-and post-implementation surveys (American Medical Association, 2024; Virginia Mason Institute, 2023). Success will also be indicated by achieving a 25% reduction in administrative errors associated with manual data entry by deploying Robotic Process Automation (RPA) tools (Council for Affordable Quality Healthcare, 2024).

Data analysis will leverage a Salesforce-based electronic health record (EHR) system and centralized SharePoint Lists to track PA submissions, approval times, and administrative errors in real-time. Monthly reporting will be used to monitor progress against benchmarks, while staff surveys administered through Microsoft Forms will assess workflow efficiency and satisfaction changes. The financial impact will be evaluated through a return-on-investment (ROI) analysis that compares denied claims and administrative overhead before and after implementation. Sources of this information include routine accounts receivable reporting reviewed on a month-over-month (MoM) basis.  This comprehensive, data-driven approach will provide leadership and potential funders with clear, objective insights into the program’s effectiveness and opportunities for continuous improvement (Eramo, 2022).

References

American Medical Association. (2024).  2024 AMA prior authorization physician survey results.  https://www.ama-assn.org

Council for Affordable Quality Healthcare. (2024).  2024 CAQH index report.  https://www.caqh.org

Eramo, L. A. (2022). Healthcare leaders share lessons learned.  hfm (Healthcare Financial Management), 76(6), 24–27.  https://research.ebsco.com/linkprocessor/plink?id=a1d6da70-2348-37ad-bafb-2c2a1dd71719

Virginia Mason Institute. (2023).  Case study: Prior authorization improvement.  https://www.virginiamasoninstitute.org

Christine Discussion:

The focus of my capstone project is to increase community-based mental health services, specifically an extended observation unit (EOU), to reduce avoidable ED visits, thereby reducing psychiatric boarding in the ED. 

I have chosen outcome measures to be assessed at 3 months, 6 months, and 12 months post EOU implementation. By the end of three months, 25% of patients will have a cursory evaluation by a psychiatric medication provider within 30 minutes of arrival to determine the need for emergency medication to stabilize acute symptoms (i.e., agitation, withdrawal, etc.); 25% of patients will receive a comprehensive psychiatric evaluation within two hours of arrival; 25% of patients will have a discharge plan initiated within six hours of arrival; and 25% of patients will have a discharge risk assessment within two hours of their anticipated discharge. These percentages increase to 50% by the end of six months and to 100% by the end of 12 months and ongoing.

Types of data for program analysis include qualitative data and quantitative data. Qualitative data can help to capture information regarding the patient’s experience and attitude towards a program (Tenny et al., 2022). Quantitative data measures values, typically expressed as numbers. Quantitative data can help test and identify causal relationships (Williams, 2021). While the literature suggests that a combination of both qualitative and quantitative data analysis is best for demonstrating the result of a program, both the overarching and program specific objectives rely on quantitative data to demonstrate progress towards the outcome measures.

To track progress related to completing a cursory evaluation and a comprehensive psychiatric evaluation within 30 minutes of arrival and within two hours of arrival respectively, we will track time from admission of each patient to initiation of each patient’s evaluations to capture the time lapse. This can be done using the EHR, which utilizes time stamps, such as patient arrival time. The provider can manually input into the EHR the time they started each of their evaluations. Many EHRs have automated report functions, and this can be used to run a report of this data. Displaying this on a dashboard can be a helpful way to share the data with staff in real time as well as track benchmarks and trends in the data over time (Team Sigma, 2025).

A similar method can be used to track progress related to discharge plans being initiated within six hours of patient arrival. The EHR can again be used to track arrival time to the EOU. The clinician initiating the discharge plan can manually enter into the EHR the time they started the discharge plan with the patient. A report can be run, and the information displayed on a dashboard.

            The last outcome measure also relies on tracking time. In this case, the anticipated discharge time and whether a risk assessment was completed within two hours of the anticipated discharge time. To track this, it might be helpful for the staff to utilize a real time digital tracking board within the EHR. It would contain a list of patients in the EOU and their anticipated discharge time as well as the time frame in which the risk assessment would need to be completed to meet the outcome measure. Keniston et al. (2021) suggest that a tool such as this can help to provide real time patient information regarding discharge as well as promote multidisciplinary communication regarding discharge needs.

        

References

Engstrom, T., Shteiman, M., Kelly, K., Sullivan, C., & Pole, J. D. (2024). What is measured

matters: A scoping review of analysis methods used for qualitative patient reported experience measure data.  International Journal of Medical Informatics,  190, 1-9. https://doi.org/10.1016/j.ijmedinf.2024.105559

Keniston, A., McBeth, L., Pell, J., Bowden, K., Metzger, A., Nordhagen, J., Anthony, A., Rice, J.,

& Burden, M. (2021). The effectiveness of a multidisciplinary electronic discharge readiness tool: Prospective, single-center, pre-post study.  JMIR Human Factors,  8(4), e27568. https://doi.org/10.2196/27568

Team Sigma. (2025).  Guide to data dashboards. https://www.sigmacomputing.com/blog/guide-

to-dashboards

Tenny, S., Brannan, J. M., & Brannan, G. D. (2022, September 18). Qualitative Study. In

StatPearls. StatPearls Publishing. Retrieved April 28, 2025 from https://www.ncbi.nlm.nih.gov/books/NBK470395/

Williams, T. (2021, June 14).  Why is quantitative research important? Grand Canyon University.             https://www.gcu.edu/blog/doctoral-journey/why-quantitative-research-important