23787 HEALTH TECHNOLOGY ASSESSMENTAssessment Task 3 – Version 1 (please…

Recent Question/Assignment 23787 HEALTH TECHNOLOGY ASSESSMENTAssessment Task 3 – Version 1 (please refer to the assignment allocation to ensure you are completing the version to…

Recent Question/Assignment 23787 HEALTH TECHNOLOGY ASSESSMENTAssessment Task 3 – Version 1 (please refer to the assignment allocation to ensure you are completing the version to which you have been allocated).Due Date: Midnight, Monday 28th October 2019 Overall contribution to assessment: 60%NameStudent NumberThe aim of this assessment is to construct a simple decision tree diagram to assess the cost-effectiveness of a new cervical screening test when compared to the current screening test. The assessment task comprises a series of structured stages, including the preparation of a written brief health technology assessment report. All stages contribute to the assessment (the marks for each stage are shown below).Your report should follow the outline provided below.Please note that you DO NOT REQUIRE dedicated economic modelling software to complete this task. All of the calculations can be undertaken easily with a calculator or in Excel.Your completed assessment should be submitted through TURNITIN – via UTS Online. DO NOT EMAIL YOUR ASSESSMENT TO THE COURSE COORDINATOR.Please label your attachment with your name and student number as follows: 23787_Assessment_3_First name_Last name_Student NumberYour completed assessment task should have1. An executive summary that represents a brief health technology assessment report. This should summarise your answers and be structured under the following headings:· Objectives· Methods· Data· Results· Key areas of uncertainty· Discussion· RecommendationThe executive summary should be no more than 500 words. (10 marks)Mark Allocation for ES: 10 marks (as follows):Presents all sections of executive summary as requested 1 markEach section of the executive summary presents the relevant information from the main body of the report 2 marksThe information is presented clearly and can be followed easily 2 marksThe summary clearly identifies the model parameters that are the most uncertain and have the greatest impact on the cost-effectiveness result 1 markThe discussion demonstrates a clear understanding of the analysis and its implications 2 marksThere is a clear recommendation that is justified by the results 2 marks2. A structured report that presents the answers to each of Parts One to Six of the task, including calculations where required. (Contribution to overall marks are shown for each part) (50 marks in total)Part One: Calculating the accuracy of two test alternatives (10 marks)Screening tests for cervical cancer aim to identify pre-cancerous changes in the cervix that could develop into cervical cancer. If the pre-cancerous tissues are identified early and removed, then cervical cancer can be prevented from developing.The Comparator – In the conventional Pap smear, the doctor collecting the cells smears them on a microscope slide and applies a fixative. This slide is then sent to a laboratory for evaluation. Studies of the accuracy of conventional (current) Pap smear tests report:· Sensitivity 73%· Specificity 94%The New Test – The new test works in exactly the same way as the current test, however themanufacturer believes that the sensitivity of the new test is better. Below are the results of a cohort study that tested the new cervical screening test. Note that all women were 30 years of age when tested.New Test Disease Status TotalCervical cancer (+ve) Cervical cancer (-ve)Test (Positive) 44 34Test (Negative) 9 560TotalA) For the new cervical screening test define the following, and include the number of individuals in each group.· True positive· False positive· True negative· False negative(1 mark for each – 4 total)B) Calculate the sensitivity and specificity for the new test.(2 marks for each – 4 total)C) Compared with the current test, the new test was evaluated using a different cohort of women and in a different laboratory. Does this influence the sensitivity and specificity of the new test?(2 marks total)Part Two: Construct a decision tree (10 marks)Your task is to assess the cost-effectiveness of screening women when they reach the age of 30. We also assume that everyone who is invited to participate in the screening program receives a cervical screening test (i.e. the uptake rate of the test is 100%).Draw a decision tree to determine whether the new cervical screening test is more cost-effective than the current test. To do this you need to create a decision node with the option to accept the new test or the current test. For each test, the terminal nodes should reflect the possible outcomes of the test result (e.g. True positive etc…). AT THIS POINT YOU DO NOT NEED TO POPULATE THE TREE – THAT WILL FOLLOW IN THE SUBSEQUENT STEPS. Please provide a picture of your unpopulated tree.Mark Allocation for Part Two: 10 marks (as follows):Correctly identifies the use of a decision tree 2 marksCorrectly identifies and labels the elements of the decision tree 4 marksProvides a picture of the decision tree in report 2 marksBriefly discusses the patient flow through the decision tree 2 marksPart Three: Estimating the benefit of testing (5 marks)To populate the decision tree, we need to estimate the benefits and costs of each test option. The benefits of screening are measured in terms of quality adjusted life years (QALYs) gained (i.e. quality-of-life multiplied by the number of years in that health state).· Utility score – A time-trade off study conducted on the same cohort of women that received the new test demonstrated that:o The average utility in the non-cancer group (test negative) was 0.92.o The average utility in the non-cancer group (test positive) was 0.91 (slight reduction in utility due to further investigations and concern of possible cancer)o The average utility in the cancer group (not detected by the test) was 0.50 (This reduced utility is due to the side-effects of treatment and the impact of the disease).o The average utility in the cancer group (detected by the test and treated early) is 0.87 (there is a slight reduction in quality of life due to early treatment.· Survival – Long-term registry data were used to estimate the additional survival (note that this is the additional survival beyond 30 years of age, which is the age when a person would be screened in this model)o The average survival of a 30 year old woman with cervical cancer (not detected early) is an additional 5 years.o The average survival of a 30 year old woman with cervical cancer that is detected early and treated (i.e. detected with a positive test results) is an additional 40 years.o For all other 30 year old women (no cancer) the average survival is an additional 40 years.A) Calculate the average QALYs for individuals with the following possible test outcomes:· True positive· False positive· True negative· False negative(1/2 mark for each – 2 total)B) In this model, all outcomes (costs and benefits) are undiscounted. Why do we discount future costs and benefits? Why might discounting costs and benefits at the same rate penalize preventative health programs?(1.5 marks for each part – 3 total)Part Four: Estimating Costs (5 marks)The tables below were taken from a longitudinal cohort study of women that participated in the current screening program. The unit costs are provided in Table 1. Table 2, contains an inventory of all the resources used, on average, by an individual depending upon their test result.· For example, an individual identified as being ‘true positive’ would require the following resources for the two tests under comparison:o Current test – 1 x current test, 2 x GP visits, 1 x further examination – earlytreatment. Therefore, their treatment would cost – 1 x $50 + (2 x $35) + 1 x $1,000 = $1,120o New test – 1 x new test, 2 x GP visits, 1 x further examination – early treatment. Therefore, their treatment would cost – 1 x $400 + (2 x $35) + 1 x $1,000 = $1,470Combine the information from Tables 1 and 2 below to generate the total cost of each screening outcome. Do this for both the current test and the new test scenarios.Table 1: Unit costsDescription CostCurrent test $50New Test $400GP appointment $35Further examination – No treatment $500Further examination – Early treatment $1,000Delayed treatment $50,000Table 2: Resources use for each possible alternativeCurrent test New Test GP visit Further exam – no treat Further exam – early treat Delayed treatmentCurrenttest True Positive 1 2 1False positive 1 2 1True negative 1 1False negative 1 1 1New Test True Positive 1 2 1False positive 1 2 1True negative 1 1False negative 1 1 1NOTE: All costs calculated should be presented to two decimal places.Mark Allocation for Part Four: 5 marks (as follows):Correctly identifies the cost elements 1 markAllocates costs correctly to each test outcome for current test 2 marksAllocates costs correctly to each test outcome for new test 2 marksPart Five: Cost-utility analysis (10 marks)You should now have the following information:· Accuracy of the current and new cervical screening tests· A decision tree that reflects the possible outcomes of both tests· An estimate of the QALYs gains for each alternative· An estimate of the resource use (cost) of each alternativeThe final information that you need to complete the analysis is the prevalence of cervical cancer in this population. In this example, we are screening women 30 years of age; the prevalence of cervical cancer in this cohort is 3 in 1,000 or (0.003)A) Complete Table 3: Model parameters using the information from Part One to Part Four.Table 3: Model ParametersParameter description Current Test New TestPrevalence of cervical cancer 0.003 0.003Sensitivity of test 0.73Specificity of test 0.94Cost – True PositiveCost – False PositiveCost – True NegativeCost – False negativeQALYs – True PositiveQALYs – False PositiveQALYs – True NegativeQALYs – False negative(1 mark total)B) You now need to combine this information into your decision tree to determine the cost-effectiveness of the new test relative to the current test. Provide your answer as an incremental cost-effectiveness ratio (ICER; i.e. cost/QALY gained). Provide the diagram of your populated decision tree at this stage.· Hint: Remember that you need to calculate the expected value (costs and QALYs) of each alternative before you can estimate the cost-effectiveness. It is easier to calculate the expected value if you start at the end of the tree, rather than the beginning (i.e. you need to roll-back the decision tree – see lecture notes for example)Mark Allocation for Part Five (B): 8 marks (as follows):Correctly allocates the parameter values to the decision tree 2 marksCorrectly estimates the expected value of each strategy 3 marksCorrectly estimates and presents the ICER 2 marksProvides a diagram of the decision tree 1 markC) If the decision maker has set an explicit threshold of $50,000 / QALY gained, would you say the new test is cost-effective? Explain your answer.(1 mark total)Part 6: Sensitivity Analysis (10 marks)The decision maker would like you to determine the cost-effectiveness of the new test in a population of women without a family history of cervical cancer. In this low risk cohort of women, the prevalence of cervical cancer is 5 in 10,000 (0.0005).A) Calculate the ICER of the new test relative to the current test in this low-risk population of women.(2 marks total)B) Why do you think the cost-effectiveness of the new test is sensitive to the prevalent risk of cervical cancer in the population?(2 marks total)C) In the original model (hint: assuming prevalence = 0.003), we assumed a 20 min GP appointment costs $35. However, an audit of general practices conducting the new test shows that 50% of GPs charge patients a double appointment (2 x 20 mins) at each visit. NOTE: THE DOUBLE GP APPOINTMENT CHARGE APPLIES TO ONLY THE NEW TEST. How does this change your ICER? Explain your answer.Mark Allocation for Part Six (C): 4 marks (as follows):Correctly allocates the change in cost in the decision tree 1 markCorrectly estimates and presents the ICER 1 markProvides a clear explanation of the result 2 marksD) Is the model sensitive to any other parameters? Please justify your answer.(2 marks total) Let’s block ads! (Why?)

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