Assessment task 3: Analysis of supplied patient data
Intent: This assessment item focuses on the development of data analysis and presentation skills in order to make recommendations that are congruent with contemporary literature.
Objective(s): This assessment task addresses subject learning objective(s):
A, B, D and E
This assessment task contributes to the development of graduate attribute(s):
1.2 and 4.2
Due: 10.00pm 05 May 2015
Length: Maximum 2500 words
Task: You have been engaged as a consultant to the Local Health District (LHD). The LHD governing council requires you to develop a report based on the ‘UTS Hospital’ data to address issues related to Outlier Admissions (patients with a length of stay over 30 days) . The governing council is primarily interested in the analysis, and expects clear recommendations that apply to, and are
implementable by, ‘UTS Hospital’.
1. Locate the UTS Hospital data file from the Data Files folder in UTSOnline.
2. Produce a written report no longer than 2500 words for the LHD council based on the supplied data (UTS Hospital data file) and the following topic items that includes tables or graphs as appropriate (for example, to show comparisons). NB The word limit excludes tables and appendices.
3. The report must contain a data analysis strategy, the analysis, and appropriate reference to the literature.
1. With reference to Australian and overseas literature, briefly describe:
• the current percentage of patients who stay longer than expected for their AR-DRG, including those identified as outlier admissions
• factors (internal and external) likely to influence length of stay
• approaches used to prevent outliers and reduce length of stay for these admissions
Analyse the UTS Hospital dataset as follows:
1. Create a profile of outlier patients (those who stay more than 30 days)
a) include both individual and episode characteristics (e.g. age and others you identify in the literature)
b) include the proportion of the dataset that these patients comprise
c) compare this to a profile of all patients in this data set
2. For outlier patients:
• describe the most common individual and episode variables that occur in these long stay cases
• identify the most common principal and secondary diagnoses
• identify the most common principal and secondary procedures
• compare the length of stay of outlier patients to non-outlier patients in the same (or related) AR-DRG and/or the same MDCs
3. Based primarily on your analyses, but with reference to the literature:
• identify important points that might suggest interventions to reduce the length of stay for outlier patients
• make specific recommendations to reduce the number of outliers and reduce their length of stay
Requirements / Notes
1. Investigate the issues by:
• researching the issue in the literature
• designing a data analysis strategy
• conducting the analysis
• making recommendations
2. Appropriately reference all material, however you do not need to reference the supplied dataset.
3. Ensure you read the marking criteria.
4. Develop an understanding of each of the data elements in the dataset. Do not limit your analysis to the most obvious variables.
5. The supplied dataset is relatively small so it is not expected that the analyses here would be definitive. You are expected to treat the dataset as if there were more cases than there actually are, so that the solutions you may suggest should be considered to be more valid than they will actually be with this selection of data. You do not need to note this in the report.
6. Secondary diagnoses are defined as any diagnosis after the principal.
7. Appendices may be included but will not contribute to the grade for this assessment
8. Report formats vary, but usually contain:
• Background / Literature
• Method / Data Analysis Strategy
• Results / Findings
• Discussion & Recommendations
• 10% Constructs a review of the literature to identify and discuss issues relevant to the topic
• 20% Designs a clear and logical data analysis strategy that is logically sequenced and structured andaddresses the points raised in the topic
• 20% Performs an analysis of the supplied data in a manner consistent with the data analysis strategyto provide appropriate answers to the points raised in the topic
• 30% Recommends contemporary and achievable approaches to address the points raised in the topic
• 10% Validates perspectives through correct interpretation of relevant and current literature ( year 2003)
• 10% Produces correct grammar, spelling, formatting, style (report) and referencing