using!the!datadriven!policymaking!model!as!a!template!to...
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Stage Three involves analyzing, clarifying and dissemina7on of informa7on. What does the data indicate about the current state of affairs? This por7on of the model includes analyzing the data, clarifying the limita7ons of current knowledge and dissemina7ng the research findings (Weinick & Shin, 2004).
Using The Data-‐Driven Policymaking Model As A Template To Aid DNP Students In Analyzing and Evalua7ng Policy O. Danny Lee, PhD, APRN-‐CNS, CNE; Janet Jones, DNS, APRN-‐CNS, & Lisa C. Bayhi, DNP, ACNP, FNP, FAANP
Southeastern Louisiana University
Introduction
Example of The Data-‐Driven Policymaking Model used by a DNP Student to support the DNP Project “Health Policy Analysis of Nurse Prac77oner Ini7a7ves To Develop Advocacy Strategies Towards Full Prac7ce In Louisiana” Purpose To illustrate how the Data-‐Driven Policymaking Model can be used as a template and guide for DNP students in analyzing and evalua7ng policy. Objec7ves Par7cipants will understand and be able to discuss the importance of health care policy for advocacy in health care. Par7cipants will have an understanding of and be able to discuss of the Data-‐Driven Policymaking Model. Par7cipants will understand and be able to discuss the important connec7on between health care policy analysis and advance prac7ce. Par7cipants will understand and be able to discuss the important connec7on between health care policy analysis in suppor7ng evidence base prac7ce.
Stage One
Stage Two Stage Three Conclusion
Stage Four is the ac7on phase and is where policy op7ons, which are supported by the data, are explored. The project is assembled in order to explore specific evidence based alterna7ve policies for NP prac7ce. In addi7on, an es7ma7on of the impact of previous and current ini7a7ves was considered in the prepara7on of the ac7on process. Included in the final product are ways to mi7gate these nega7ve impacts of selected policies and to advance the posi7ve influences (Shamian & Shamian-‐Ellen, 2011). This ac7on stage culminates with the produc7on of a white paper that includes the policy analysis and evalua7on with recommenda7ons for policy changes within Louisiana and an algorithmic advocacy plan.
Stage Two examines the data available to aid policy development. What data are available to support policy decisions? Assembling a matrix of available data resources and iden7fying the need for new or addi7onal data is necessary in this stage (Shamian & Shamian-‐Ellen, 2011). Many types of data resources were explored including state records of legisla7on, acts, board rules and regula7ons as well as stakeholder perspec7ve through state records of mee7ng minutes, speeches, presenta7ons and memos. Na7onal data bases, for example, CDC and AHRQ will be examined for state health and demographic facts. The data resources also include state legislature, statutes, rules and regula7ons, health ranking, expenditures on healthcare, income levels, social structure, overall healthcare ranking and the cost of healthcare in each state. An inventory has been developed of current and past ini7a7ves as well as a determina7on of available measures for implementa7on (Shamian & Shamian-‐Ellen, 2011).
Stage One includes defini7ons and priori7es and iden7fies the policy problem. Louisiana state statutes do not allow NP prescrip7ve or NP prac7ce without physician oversight. As a consequence, rules and regula7ons have not met the Consensus Model goals, or the IOM ideals. Thus, the policy problem ques7on is what eviden7al changes to prac7ce are required in Louisiana healthcare policy to gain the defini7on of AANP full NP prac7ce?
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