92917 Using Health Care Data for Decision Making

Subject objectives - Upon successful completion of this subject students should be able to:

A. Access and manipulate supplied data in order to generate reports and make recommendations;

B. Consider the relationship between data, information, knowledge and wisdom and how these elements inform practice, management, and policy in the context of international trends;

C. Examine the relationship between datasets and information literacy;

D. Explain the data elements in contemporary health data terminologies;

E. Create a variety of ways in which complex issues can be effectively communicated for a variety of target audiences.

Assessment task 1: Workbook Exercise

Intent: This assessment item focuses on the elements of administrative data and related key concepts and how to analyse health data.

Task: Students are to answer a series of questions via UTSOnline. A selection of multiple choice, multiple answer, true/false, matching statements, short text response, and ordering questions may be included.

Questions may:

- require manipulation of the supplied UTS Hospital data using Microsoft Excel;

- require access to sources on the International Classification of Diseases and the list of Australian Refined Diagnosis Related Groups, available through the UTS library and/or UTSOnline;

- relate to casemix, including, but not limited to, AR-DRGs;

- relate to basic statistical concepts;

- relate to important concepts and definitions.

Students will receive feedback and grades via UTSOnline.

Assessment task 2: Short Statements

Intent: This assessment item focuses on the ability to concisely respond to specific questions and to demonstrate an understanding of the management and application of health data.

Task:

1. Read the following case scenario.

2. Provide a response to each of the five sections that demonstrates an understanding of the application and management of health data and refers to literature related to the identified issues and associated tasks.

3. In each response, apply your findings to the hospital so as to assist the executive group in decision making and planning.

Case Scenario - Windy Hospital

Windy hospital is a well-established charitable hospital operated on a not for profit basis. It has 250 beds in an inner-city location. The population of the local community, from which it draws the majority of its patients, is ageing: 40% are over the age of 65 years. Windy hospital has an excellent reputation for innovative care, rapid uptake of new technologies, teaching and research. It gets very little support from the government for running costs, although previous governments have been generous in meeting the cost of new buildings and refurbishing old buildings.

The hospital is in financial difficulty. Over 90% of the funding to the hospital for acute inpatients comes from private health insurers. The remainder is from the Department of Veterans Affairs, patients who pay for their own admissions, compensable patients from motor vehicle and workplace insurance and patients whose stay is paid from a research grant. The rate of reimbursement from private insurers is based on a negotiated rate for each AR-DRG. Each insurance fund negotiates the rate it pays for each AR-DRG individually each year with the hospital (i.e. a type of casemix- or activity-based funding). The fees are based on the average length of stay for each AR-DRG using the Australian cost weights.

The Chief Executive Office (CEO) has called a special meeting of the executive to discuss the issues facing the hospital and to plan the action they need to take. Present at the meeting are the Director of Nursing (DON), the Chief Financial Officer (CFO) and the Chief Information Officer (CIO).

1. The DON suggested that the problem is that casemix-based funding using AR-DRGs are not the best method to record performance because they do not suit the type of patients treated by Windy Hospital. She said that the majority of patients are older and more complex, and need to stay longer than the average length of stay for each AR-DRG. She suggested that AR-DRGs are useless for measuring the hospital's performance when the length of stay of the patients was different to that of the average hospital. She was of the view that the hospital should go back to the insurance funds and negotiate a return to the funding of patients on a fixed per diem basis.

Provide a short statement (~ 300 words) for the executive that identifies the pros and cons of casemix-based funding approach compared to a fixed per diem rate. Provide the executive with a recommendation.

2. The CIO disagreed that the age and complexity of the patient made the DRG system useless. He noted that there were many examples where older patients or those with more complex care, that needed a longer length of stay, had been classified into a different AR-DRG. Windy hospital is using AR-DRG version 5, and he was not sure if this was the most recent version.

Provide a short statement (~300 words) with two or three examples of where the AR-DRG had been split to allow for patients of different age or complexity in the current version of AR-DRGs in use in Australia. Given the nature of Windy Hospital's patients, outline to the executive the implications of changing AR-DRG versions.

3. The CIO was also sceptical of the practices of the coding staff in coding ICD-10-AM diagnoses and ACHI procedures. He suggested that clinical coders might not always select the correct diagnostic and procedure information from the notes, leading to incorrect AR-DRG classification.

Provide a short statement (~300 words) that identifies potential issues with coding practices, including the potential rate of incorrect codes, suggested causes, and ramifications. Identify potential solutions for the executive to implement to address the issues identified.

4. The CFO expressed the view that it was not incorrectly classified AR-DRG, age or complexity of the patients that was the problem. She noted that the average length of stay was exactly that - an average - and because Windy hospital's patients were old and complicated they were likely to stay longer than average and be on the expensive side of the average cost for a given AR-DRG.

Provide a short statement (~300 words) that identifies one or more potential issues with using the average for a measure of central tendency. Describe for the executive how this issue (or issues) may be addressed in activity based (AR-DRG) funding approaches.

5. The CEO said that there was no reason to believe that Windy hospital's patients in a given AR-DRG classification were older or more complex than the patients in the same AR-DRG at a different hospital. He noted that there were established methods in use to compare the performance of similar hospitals.

Provide a short statement (~300 words) on the way peer hospitals are compared within Australia. Identify, for the executive, the peer groups used in Australia. Provide an example of a benchmark used for comparing hospitals and identify the type of patients where there could be a particular issue with falling outside that benchmark. Describe the implications for the hospital.

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.

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 data from 'UTS Hospital' (an Australian public hospital situated in New South Wales) to address issues related to AR-DRGs E69A/B/C 'Bronchitis & Asthma (with or without comorbidities or complicating diagnoses; in AR-DRG v4.1, also split by age)'. The governing council is primarily interested in the analysis, and expects clear recommendations that apply to, and are implementable by, 'UTS Hospital'.

-Locate the UTS Hospital data file from the Data Files folder in UTSOnline.

-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.

-The report must contain brief background literature, a data analysis strategy, the analysis, and appropriate recommendations that integrate the findings and the background literature.

-Includes tables or figures as appropriate (for example, to profile the target group or to show comparisons).

Topic: Asthma & Bronchitis (AR-DRG E69A/B/C)

(Note: there is an issue with this categorisation but that is not in your purview; in-depth discussion of that issue is not necessary)

A: Background Literature

With reference to Australian and overseas literature, briefly:

1. Define these AR-DRGs, including the diagnoses usually associated with them

2. Describe the current prevalence & incidence of antenatal admissions to acute hospitals, and any relevant trends

3. Describe approaches used to prevent hospitalisation and decrease length of stay for asthma & bronchitis

B: Analysis

Analyse the UTS Hospital dataset as follows:

1. Create a profile of patients in AR-DRGs E69a, E69b & E69c

1.1 include both individual and episode characteristics (e.g. age [an individual characteristic] and length of stay [an episode characteristic], and others you identify in the literature)

1.2 include the proportion of the dataset that these patients comprise

1.3 compare this to a profile of all patients in this dataset

2. For patients in AR-DRGs E69a, E69b & E69c:

2.1 identify the most common principal and secondary diagnoses

2.2 identify the most common principal and secondary procedures

2.3 compare the length of stay for patients in AR-DRGs E69a, E69b & E69c to patients in related AR-DRGs, and/or the same MDCs

C: Analysis

Based primarily on your analyses, but with reference to the literature:

1. Identify important points in your analyses that might suggest interventions to reduce the incidence of hospitalisation and length of stay in AR-DRGs E69a, E69b & E69c

2. Make specific recommendations to reduce the incidence of hospitalisation and length of stay for patients in AR-DRGs E69a, E69b & E69c.