Hospital Observational Project Analysis: Doctor/Nurse Commmunication
Description
This paper comes from a consulting project that the consulting firm, New Venture Group (NVG), did for a hospital in the southwest United States. The name of the hospital as well as the names of the hospitalists and units for the hospital will be withheld for confidentiality reasons. The hospital will be referred to as the ‘client’ throughout this paper. New Venture Group is a management consulting firm associated with Arizona State University (ASU), W.P. Carey School of Business and The Barrett Honors College. NVG recruits their consultants directly from the upper-class student body. NVG takes on projects from a wide variety of clients to provide real-world solutions comparable to that of other management consulting firms in the industry.
The client wanted to look into ways to improve patient satisfaction. To improve patient satisfaction the consulting team performed research and held a data collection. The team researched literature for possible improvements in technology, management procedures, and hospital operations protocols. The team then provided the findings and possible implementations to the client. Another item the team looked into was communication between night shift hospitalists and nurses, and possible ways to improve their communication. In the winter of 2010 a data collection was held at the client hospital that measured several different metrics of hospitalist
urse communication. In early 2011 a NVG team provided a descriptive statistics analysis of the results to the client. After the team’s first presentation I joined NVG and the team with this client. The client wanted to dig deeper into the data to find any patterns that were inherent in the data that were not immediately obvious from descriptive statistics. To do this I built over a 150 different regressions to dig from the data as many different patterns that could be found. Most of these regressions found many non-interesting results and a few did find significant interesting results. A report was sent to the client with all the results found. This paper is structured differently than the one delivered to the client in that only the significant interesting results are included and terminology will used for an audience who is familiar with statistics and mathematics. The work in this paper is the combined result of the whole team. My most specific input in this project is the quantitative analysis section. The other parts of this paper are also included so that the reader can see the full results of this consulting project.
The client wanted to look into ways to improve patient satisfaction. To improve patient satisfaction the consulting team performed research and held a data collection. The team researched literature for possible improvements in technology, management procedures, and hospital operations protocols. The team then provided the findings and possible implementations to the client. Another item the team looked into was communication between night shift hospitalists and nurses, and possible ways to improve their communication. In the winter of 2010 a data collection was held at the client hospital that measured several different metrics of hospitalist
urse communication. In early 2011 a NVG team provided a descriptive statistics analysis of the results to the client. After the team’s first presentation I joined NVG and the team with this client. The client wanted to dig deeper into the data to find any patterns that were inherent in the data that were not immediately obvious from descriptive statistics. To do this I built over a 150 different regressions to dig from the data as many different patterns that could be found. Most of these regressions found many non-interesting results and a few did find significant interesting results. A report was sent to the client with all the results found. This paper is structured differently than the one delivered to the client in that only the significant interesting results are included and terminology will used for an audience who is familiar with statistics and mathematics. The work in this paper is the combined result of the whole team. My most specific input in this project is the quantitative analysis section. The other parts of this paper are also included so that the reader can see the full results of this consulting project.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2012-05
Agent
- Author (aut): Guggisberg, Michael
- Thesis director: Ahn, Seung
- Committee member: Brooks, Daniel
- Contributor (ctb): Werner, Kathleen
- Contributor (ctb): Barrett, The Honors College