GRADING RUBRIC MUST BE FOLLOWED
Develop an 8–10-page proposal in which you pull together your prior recommendations and stakeholder analysis to create a compelling proposal for implementation of contemporary data analysis tools, and practices to improve organizational and patient outcomes. SUPPORT WITH PEER REVIEWED JOURNALS AND OTHER PROFESSIONAL REFERENCES
Questions to Consider:
- Who is the target audience for your proposal and what are their strategic priorities?
- What are the data drivers that help substantiate the need for organization improvement and decision-making?
- What are the organization’s strategic goals?
- How can the EHR or HIM help to achieve these?
- What types of key data can be extracted from the EHR or HIM to help improve workflow?
- What types of patient data are most valuable for reducing risk?
- What additional information should be added to the EHR or HIM to improve patient outcomes?
You have been asked to create a proposal for improving data collection and analysis using Vila Health’s current HIM system. Despite being Meaningful Use certified, the leadership team feels that the organization needs to make better use of patient data to improve clinical outcomes, quality, and efficiency.
Your board of directors has asked you to prepare a full proposal and they are relying on you to provide them with the most current and relevant information to help them decide on the next steps related to improvements and analysis.
Before you begin to create your proposal, you should consider completing the following:
Step One – Understand Your Audience
Complete the following:
- Determine which key stakeholders and decision makers demonstrate the greatest influence on the organization.
- Who are the key stakeholders and what are their priorities?
- Identify each category of data required to drive decision making and improve organizational performance for implementation of an EHR or HIM system (for example, patient satisfaction surveys.)
- Align EHR or HIM components with the organization’s strategic goals.
Step Two – Data Analysis Recommendations
- Research methods for communicating data analysis recommendations to audiences that are not well versed in data practices or terminology.
- Determine the most relevant data best practices for the audience, organization, and EHR or HIM systems.
- Research contemporary data analysis best practices and tools.
- Remind yourself of Independence Medical Center’s clinical goals, needs, and financial and technical readiness.
For this assessment, you will create an 8–10-page proposal that summarizes findings, aligns the appropriate data with the organization’s strategic goals, identifies current trends in data analytics, and provides recommendations for next steps based on your assessment of the organization’s readiness to proceed. You should feel free to draw on relevant aspects of the previous assessments in this course to help you complete this assessment.
Your proposal will be evaluated on the following criteria:
- Explain recommendations related to technological and logistical changes to an organization’s health information management system.
- Explain how data products and outcomes from recommendations align with an organization’s administrative and clinical goals.
- Analyze how contemporary data analysis trends could be leveraged to improve current practices in an organization.
- Recommend best practices for collecting data, securely storing data and converting data analytics into useful and understandable deliverables.
- Apply relevant evidence and best practices to target proposal messaging to stakeholders.
- Communicate proposal in a professional, clear, and concise way.
- Integrate relevant sources to support assertions, correctly formatting citations and references using current APA style.
EHR Data Considerations
These resources discuss patient involvement in data usage, how patient portals help give patients more control, awareness and an improved patient experience, and how data can expand predictive modeling in health.
- Blumenthal, D., & Squires, D. (2015). Giving patients control of their EHR data. Journal of General Internal Medicine, 30(1), 42–43.
- Westra, B. L., Christie, B., Johnson, S. G., Pruinelli, L., LaFlamme, A., Park, J. I., . . . Speedie, S. (2016). Expanding interprofessional EHR data in i2b2. AMIA Joint Summits on Translational Science, 2016, 260–268.
- Zhao, J., Henriksson, A., Asker, L., & Boström, H. (2015). Predictive modeling of structured electronic health records for adverse drug event detection. BMC Medical Informatics and Decision Making, 15(4), S1.
Health information management and informatics is largely about quality improvement. These resources discuss how medical informatics can advance quality.
- Baxter, C., Dell, R., Publ, S., & Race, R. (2013). Assessing and improving EHR data quality. Journal of AHIMA, 84(3), 48–53.
- Drake, K. (2015). Using EHR data to enhance quality improvement. Nursing Management, 46(12), 56.
- Wang, J. J., Cha, J., Sebek, K. M., McCullough, C. M., Parsons, A. S., Singer, J., & Shih, S. C. (2014). Factors related to clinical quality improvement for small practices using an EHR. Health Services Research, 49(6), 1729–1746.
- Health and medical informatics; new health and medical informatics study results reported from J. Taggart et al (structured data quality reports to improve EHR data quality). (2015).Information Technology Newsweekly, pp. 110.