# Economic Evaluation and Decision-Making in Healthcare: A Comprehensive Analysis

Explore the intricate world of healthcare economics and decision-making in our comprehensive analysis. Delve into the four key economic evaluation studies, uncovering their similarities and distinctions. Calculate quality-of-life indices and mean quality-adjusted life years, providing essential insights into patient well-being. Witness the impact of a groundbreaking intervention on patients' lives, with significant improvements backed by statistical significance. Discover the financial, direct, and societal costs associated with the intervention, and determine its cost-effectiveness. Finally, we weigh the results against a societal cutoff value to make informed policy decisions. This journey offers a holistic view of healthcare decision-making, bridging economics with patient welfare.

## Problem Description:

The data analysis assignment involves a comprehensive analysis of economic evaluations and decision-making related to the quality of life for HIV positive patients living with AIDS. It encompasses four questions that tackle topics like economic evaluations, quality-of-life indices, cost analysis, and decision-making based on cost-effectiveness.

Question 1: Economic Evaluation Studies (20 points)

Summary: In this question, we explore the similarities and differences between the four types of economic evaluations: cost-effectiveness analysis (CEA), cost utility analysis (CUA), cost-benefit analysis (CBA), and cost-minimization analysis (CMA).

• CEA: Measures costs against clinical effectiveness, often using life-years or QALYs.
• CUA: Similar to CEA but quantifies results in terms of utility or quality of life.
• CBA: Compares monetary benefits with costs, quantifying benefits in monetary terms.
• CMA: Compares costs with similar clinical effectiveness, only considering costs.

In Summary: These evaluations all compare costs and benefits but differ in how benefits are measured and the assumption of clinical effectiveness.

Question 2: Quality of Life Index Calculation (10 points)

Summary:This question focuses on calculating the quality-of-life index using given data from a dataset (HATTOT variable) and the mean number of years patients have lived with AIDS.

1. Quality-of-life Index Calculation: Quality-of-life score = 97.8/145 (or 67.45%).
2. Mean Quality-Adjusted Life Years (QALYs) Calculation: QALYs = 17.7 years * 0.6745 = 11.9387.

Question 3: Impact of New Intervention (10 points)

Summary: This question considers the effect of a new intervention on patients' quality of life after 20 years and evaluates statistical significance.

• Mean Change in QALYs: Experimental group: 18 - 11.9387 = 6.0613.
• Statistical Significance: Significant improvement (p < 0.05) based on a t-test for independent samples.

Interpretation: The intervention significantly improved patients' quality of life.

QALYs at baseline QALYs at study end Statistical Significance
Experimental group As per question 2b above 18 p < 0.05, t-test for independent samples
Control group Same baseline as experimental group 13.5

Question 4: Cost Analysis (20 points)

Summary: This question delves into the financial, direct, and societal costs associated with the new treatment and control groups over 20 years.

1. Financial Cost of Treatment: Experimental group: \$10,500; Control group: \$14,000.
2. Direct Cost of Treatment: Experimental group: \$6,000; Control group: \$0.
3. Societal Cost of Treatment: Experimental group: \$12,000; Control group: \$18,000.
4. Incremental Cost per QALY (Financial Cost Model): \$2,333.33.
5. Incremental Cost per QALY (Direct Cost Model): \$1,333.33.
6. Incremental Cost per QALY (Societal Cost Model): -\$1,333.33.

Interpretation: The new treatment is cost-effective in the direct and societal cost models, with the societal model indicating cost savings.

Question 5: Decision Making (20 points)

Summary: This question involves making a policy decision based on cost-effectiveness.