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To ensure that the resources of the health care sector are used effectively, new technologies need to be evaluated before implementation to examine if they generate health outcomes at an acceptable cost. This information can be collected by performing health economic evaluations in which the costs and health outcomes of different technologies are compared. To estimate the effect on health care budgets, there is also a need for information about the prevalence of the specific disease. Health outcomes in health economic evaluations are often measured in quality-adjusted life years (QALYs), which are calculated by multiplying the remaining life years after an intervention by a weight representing the health-related quality of life (HRQoL) during those years. This thesis aims to provide deeper knowledge of the health economic aspects of diabetic retinopathy (DR), an eye complication that affects patients with diabetes and may in the worst case lead to blindness. The focus is on three empirical and two methodological health economic research questions. The empirical research areas cover prevalence, costs, and HRQoL related to patients with DR. The methodological research questions explore the performance of different methods for estimation of QALY weights. This is of interest since it has been argued that the most common methods for estimating QALY weights may not capture all relevant vision-related aspects of quality of life. The analyses comprehend the validity of different methods for estimating QALY weights among patients with DR and if the results of one of the specific methods for estimating QALY weights, the time trade-off (TTO) exercise, are affected by patients’ subjective life expectancy (SLE). The empirical results demonstrate that DR is seen in approximately 40% and 30% of patients with type I and type II diabetes respectively, indicating that the prevalence of DR has decreased in both of these patient groups. Healthcare costs vary considerably between different severity levels of the disease, being estimated at €26, €257, €216, and €433 per patient per year for background retinopathy, proliferative diabetic retinopathy (PDR), diabetic macular oedema (DMO), and PDR combined with DMO respectively. Blindness due to DR is associated with an increased use of transportation services, caregiving services, and assistive technologies as well as productivity losses. This suggests that preventing the progression of DR may lower healthcare costs. Patients with vision impairment due to DR have lowered HRQoL in various dimensions, but the diagnosis of DR in itself has only a limited effect on HRQoL. The results on the methodological research questions show that different methods for estimating QALY weights seem to give different results. In comparison to EQ-5D, the Health Utilities Index Mark 3 (HUI-3) is the most sensitive method for detecting differences in QALY weights due to DR, and if decisions are to be made based on values from the general public, it can be recommended for use in cost-utility analyses of interventions directed at DR. Neither of the direct methods, TTO and the visual analogue scale, seems to be sensitive to differences in visual function, and more research is needed concerning the role of vision in people’s responses to the TTO exercises. In TTO exercises with time frames based on actuarial life expectancy, the patients’ SLE has an effect on their willingness to trade off years for full health. Thus, applying time frames deviating from patients’ SLE may result in biased QALY weights. Such bias may appear stronger within patient populations than within the general public. In conclusion, this thesis offers estimates for prevalence, costs, and QALY weights that can be used in economic evaluations of interventions directed at DR and as benchmarks for future DR research in order to follow up consequences of changes in diabetes care. In addition, it demonstrates that the choice of method for estimating QALY weights may have an impact on whether an intervention is considered cost-effective.

No description available.

Background: The ability to measure health and the value of improving or declining health is crucial to the evaluation of health care interventions. Many generic and disease specific health status measures exist for use in patients with rheumatoid arthritis (RA). The Overall Status in Rheumatoid Arthritis (OSRA) measure is a new and simple measure with early evidence of construct validity. Generic health profiles with attached utility weights such as the EuroQol EQ-5D and the SF-6D (calculated from the Medical Outcome Study 36-item short-form health survey) allow the quantification of a patient's health relative to perfect health and death, and can be used to estimate quality adjusted life years (QALYs). The EQ-5D is extensively used in RA, but has potential limitations. The SF-6D appears to have potential, but needs further evaluation. The aim of this thesis was to assess the validity and responsiveness of the EQ5D, SF-6D and OSRA in UK RA patients, and compare the performance and implications of the use of the EQ-5D and SF-6D.Methods and subjects: Patient data were obtained from three sources; the Steroids in Very Early Arthritis (STIVEA) (n=256) and British Rheumatoid arthritis Outcome Study Group (BROSG) (n=466) randomised controlled trials, and the British Society for Rheumatology Biologics Register (BSRBR) (n=129). The data used included lifestyle and demographic factors, disease activity (DAS28), functional disability (HAQ), X-rays to assess erosive damage, the EQ-5D and the SF-6D. The OSRA was collected only in the BROSG trial. Visual analogue scales (VAS) of pain and fatigue were collected in BROSG and STIVEA. Construct validity was tested by correlating the EQ-5D, SF-6D and OSRA with a range of outcome measures for RA. Responsiveness to change was assessed using minimum important differences (MID), effect size (ES) and standardised response means (SRM), and compared using ratios. EQ-5D profiles placing arthritis patients in utility states 'worse than death' (negative scores) were described and assessed using linear and logistic regression. The implications of using the EQ-5D and SF-6D in economic evaluation were compared by cost-effectiveness analyses of the BROSG trial. Results: The correlation of the EQ-5D and SF-6D was moderate to high (0.67). Both measures had moderate to high correlations with disease activity, physical function, joint damage and fatigue. The OSRA Activity (OSRA-A) and Damage (OSRA-D) correlated strongly with measures of related aspects of disease. The EQ-5D, SF-6D and OSRA discriminated between known differences in health status across groups defined by social deprivation and disease activity. The EQ-5D MID was 0.04 for improvement and 0.10 for deterioration. The SF-6D MID was 0.04 in both directions. The SF-6D was more responsive to improvement (EQ-5D: SF-6D ES ratio 0.78-0.88) and the EQ-5D more responsive to deterioration (ES ratio 1.14) in health. The OSRA-A was the most sensitive disease specific measure in the BROSG trial, and the OSRA-D was more responsive than the HAQ. The factors associated with being in a 'worse than death' health state were male gender, the HAQ, SF-36 mental composite scale, pain VAS, and erythrocyte sedimentation rate (a marker of inflammation). Pain was the predominant factor and was scored at the most extreme level in every worse than death profile. The cost-effectiveness analyses (BROSG trial), found net quality adjusted life years (QALYs) were greater for the EQ-5D (0.07) than the SF-6D (0.05), but had higher variance than the SF-6D. Conclusions: The EQ-5D and SF-6D appear valid and responsive to changes in health in RA, but measure subtly different aspects of health. There are issues with both measures, and cost-effectiveness conclusions of a study could differ according to which measure was used. The EQ-5D may be more likely to demonstrate that an intervention is cost effective than the SF-6D, due to its larger mean change in response to change in health status. The OSRA is valid for use in RA and its responsiveness suggests potential for inclusion in clinical trials.

Medical decision problems are extremely complex owing to their dynamic nature, large number of variable factors, and the associated uncertainty. Decision support technology entered the medical field long after other areas such as the airline industry and the manufacturing industry. Yet, it is rapidly becoming an indispensable tool in medical decision making problems including the class of sequential decision problems. In these problems, physicians decide on a treatment plan that optimizes a benefit measure such as the treatment cost, and the quality of life of the patient. The last decade saw the emergence of many decision support applications in medicine. However, the existing models have limited applications to decision problems with very few states and actions. An urgent need is being felt by the medical research community to expand the applications to more complex dynamic problems with large state and action spaces. This thesis proposes a methodology which models the class of sequential medical decision problems as a Markov decision process, and solves the model using a simulation based reinforcement learning (RL) algorithm. Such a methodology is capable of obtaining near optimal treatment strategies for problems with large state and action spaces. This methodology overcomes, to a large extent, the computational complexity of the value-iteration and policy-iteration algorithms of dynamic programming. An average reward reinforcement-learning algorithm is developed. The algorithm is applied on a sample problem of treating hereditary spherocytosis. The application demonstrates the ability of the proposed methodology to obtain effective treatment strategies for sequential medical decision problems.

<p>Air pollution and a general concern for lack of physical activity in North America have motivated governments to encourage non-motorized modes of transportation. A key infrastructure component for these forms of transportation is sidewalks. The City of Saskatoon has identified the need to formalize sidewalk management policies to demonstrate diligence for community protection regarding sidewalk safety. Prioritization of sidewalk maintenance and rehabilitation actions must be objective and minimize risk to the community. Most research on prioritization of pedestrian facilities involved new construction projects. This research proposes a decision model that prioritizes a given list of existing unsafe sidewalk locations needing maintenance or rehabilitation using a direct measure of pedestrian safety, namely, quality-adjusted life years lost per year. </p><p>A decision model was developed for prioritizing a given list of unsafe sidewalk locations, aiding maintenance and rehabilitation decisions by providing the associated risk to pedestrian safety. The model used data mostly from high quality sources that had already been collected and validated. Probabilities and estimations were used to produce value-added decision policy.</p> <p>The decision analysis framework applied probability and multi-attribute utility theories. This study differed from other research due to the inclusion of age and gender groups. Total average daily population of the city was estimated. This population was distributed to sidewalk locations using probabilities for trip purposes and a locations ability to attract people relative to the city total. Then trip injury events were predicted. Age and gender distribution and trip injury type estimations were used to determine the impact of those injuries on quality of life.</p><p>There exist much observable high quality data that can be used as indicators of unknown or unobserved events. A decision policy was developed that prioritizes unsafe sidewalk locations based on the direct safety impact on pedestrians. Results showed that quality-adjusted life years lost per year sufficiently prioritized a given list of unsafe sidewalk locations. It was demonstrated that the use of conditional probabilities (n=594) allowed for the ability to abstract data representing a different source population to another. Average daily population confined and distributed within the city boundary minimized problems of accuracy. Gender-age distribution was important for differentiating the risk at unsafe sidewalk locations. Concepts from this research provide for possible extension to the development of sidewalk service levels and sidewalk priority maps and for risk assessment of other public services.</p>

<p>Air pollution and a general concern for lack of physical activity in North America have motivated governments to encourage non-motorized modes of transportation. A key infrastructure component for these forms of transportation is sidewalks. The City of Saskatoon has identified the need to formalize sidewalk management policies to demonstrate diligence for community protection regarding sidewalk safety. Prioritization of sidewalk maintenance and rehabilitation actions must be objective and minimize risk to the community. Most research on prioritization of pedestrian facilities involved new construction projects. This research proposes a decision model that prioritizes a given list of existing unsafe sidewalk locations needing maintenance or rehabilitation using a direct measure of pedestrian safety, namely, quality-adjusted life years lost per year. </p><p>A decision model was developed for prioritizing a given list of unsafe sidewalk locations, aiding maintenance and rehabilitation decisions by providing the associated risk to pedestrian safety. The model used data mostly from high quality sources that had already been collected and validated. Probabilities and estimations were used to produce value-added decision policy.</p> <p>The decision analysis framework applied probability and multi-attribute utility theories. This study differed from other research due to the inclusion of age and gender groups. Total average daily population of the city was estimated. This population was distributed to sidewalk locations using probabilities for trip purposes and a locations ability to attract people relative to the city total. Then trip injury events were predicted. Age and gender distribution and trip injury type estimations were used to determine the impact of those injuries on quality of life.</p><p>There exist much observable high quality data that can be used as indicators of unknown or unobserved events. A decision policy was developed that prioritizes unsafe sidewalk locations based on the direct safety impact on pedestrians. Results showed that quality-adjusted life years lost per year sufficiently prioritized a given list of unsafe sidewalk locations. It was demonstrated that the use of conditional probabilities (n=594) allowed for the ability to abstract data representing a different source population to another. Average daily population confined and distributed within the city boundary minimized problems of accuracy. Gender-age distribution was important for differentiating the risk at unsafe sidewalk locations. Concepts from this research provide for possible extension to the development of sidewalk service levels and sidewalk priority maps and for risk assessment of other public services.</p>

Cost-utility analysis is one method of determining the cost effectiveness of nursing interventions. It is heralded by the World Health Organization as the measure to determine allocation of resources. This method of measurement includes calculation of both the cost of quality-adjusted life years (QALY) and the cost of disability-adjusted life years (DALY). The purpose of this article is to present cost-utility analysis as a relevant measure for describing the value of registered nurses. First the article will present a short overview of cost effectiveness, along with a discussion of two cost-effectiveness measures, cost-effective analysis and cost-utility analysis. Then the measurement of quality-adjusted life years and disability-adjusted life years will be presented. The article will conclude by challenging nurses to develop cost-utility analyses into a meaningful and useful methodology that can provide nursing with a process to measure the economic outcomes of our nursing interventions.

Cost-utility analysis is one method of determining the cost effectiveness of nursing interventions. It is heralded by the World Health Organization as the measure to determine allocation of resources. This method of measurement includes calculation of both the cost of quality-adjusted life years (QALY) and the cost of disability-adjusted life years (DALY). The purpose of this article is to present cost-utility analysis as a relevant measure for describing the value of registered nurses. First the article will present a short overview of cost effectiveness, along with a discussion of two cost-effectiveness measures, cost-effective analysis and cost-utility analysis. Then the measurement of quality-adjusted life years and disability-adjusted life years will be presented. The article will conclude by challenging nurses to develop cost-utility analyses into a meaningful and useful methodology that can provide nursing with a process to measure the economic outcomes of our nursing interventions.

Introdução: Há poucos estudos avaliando qualidade de vida relacionada à saúde (QVRS) e anos de vida ajustados para qualidade de vida (QALY) em pacientes com câncer que necessitam internação em unidades de terapia intensiva. O objetivo deste estudo foi avaliar sobrevida, QVRS e QALY durante o seguimento a longo prazo de pacientes com câncer internados em UTI. Métodos: Realizamos uma coorte prospectiva de pacientes com câncer admitidos em duas UTIs do estado de São Paulo. Coletamos dados na admissão da UTI, incluindo QVRS antes da doença aguda que motivou internação em UTI e no seguimento em 15 dias, 3 meses, 6 meses, 12 meses e 18 meses para avaliar a QVRS e status vital. Adicionalmente, o status vital foi avaliado em 24 meses. QVRS foi determinada com o questionário EQ-5D-3L. A sobrevida foi calculada com o estimador de Kaplan-Meier e o QALY com uma adaptação do estimador Zhao e Tsiatis. Resultados: Foram incluídos 792 pacientes. A média de idade foi 61,6±14,3 anos, 42,5% dos pacientes eram do sexo feminino e metade foi admitida após cirurgia eletiva. A média do escore SAPS3 foi 47,4±15.6. A probabilidade de sobreviver 12 e 18 meses foi 42.4% e 38.1%, respectivamente. A média do índice de utilidade da QVRS antes da internação na UTI foi 0,47±0,43, aos 15 dias pós-admissão a UTI 0,41±0,44, aos 3 meses 0,56±0,42, aos 6 meses 0,60±0,41, aos 12 meses 0,67±0,35 e aos 18 meses 0,67±0,35. A probabilidade de atingir 12 e 18 meses de vida ajustados para qualidade de vida foi de 30.1% e 19.1%, respectivamente. Houve diferenças estatisticamente significativas do tempo de sobrevida e QALY conforme as características de base consideradas (admissão após cirurgia eletiva, cirurgia de urgência ou clínica; SAPS3; extensão do câncer; status do câncer; cirurgia prévia; quimioterapia prévia; radioterapia prévia; capacidade funcional; e QVRS prévia). No entanto, apenas QVRS prévia e capacidade funcional foram associados a QVRS ao longo do seguimento de 18 meses. Conclusão: Em pacientes com câncer admitidos em UTI, a sobrevida, QVRS e QALY a longo prazo são limitados. Entretanto, há bastante variabilidade entre os pacientes nestes desfechos clínicos que é associada a características simples presentes na admissão à UTI e que podem auxiliar a equipe de saúde a avaliar o prognóstico / Introduction: Only few studies assessed health-related quality of life (HRQOL) and quality-adjusted life years (QALY) of cancer patients admitted to intensive care units (ICU). We aimed to assess the long-term HRQOL and QALY of cancer patients admitted to ICUs. Methods: We conducted a prospective cohort study of cancer patients admitted to two ICUs from the state of São Paulo, Brazil. We assessed the HRQOL with the EQ-5D-3L before ICU admission, 15 days, 3, 6, 12 and 18 months. In addition, the vital status was assessed at 24 months. Survival was calculated with the Kaplan-Meier estimator and QALY with the adapted Zhao and Tsiatis estimator. Results: The mean age of the subjects was 61.6 ± 14.3 years, 42.5% were female and half were admitted after elective surgery. The mean Simplified Acute Physiology Score (SAPS) 3 was 47.4 ± 15.6. Survival at 12 and 18 months was 42.4% and 38.1%, respectively. The mean EQ5D utility measure before admission to the ICU was 0.47±0.43, at 15 days it was 0.41±0.44, at 90 days 0.56±0.42, at 6 months 0.60±0.41, at 12 months 0.67±0.35 and at 18 months 0.67±0.35. The probabilities for attaining 12 and 18 months of quality-adjusted survival were 30.1% and 19.1%, respectively. There were statistically significant differences in survival time and QALYs according to all assessed baseline characteristics (ICU admission after elective surgery, emergency surgery or medical admission; SAPS3; cancer extension; cancer status; previous surgery; previous chemotherapy; previous radiotherapy; performance status; and previous HRQOL). Only the previous HRQOL and performance status were associated with the HRQOL during the 18-month follow-up. Conclusion: Long-term HRQOL, survival and QALY expectancy of cancer patients admitted to the ICU are limited. Nevertheless, these clinical outcomes exhibit wide variability among patients and are associated with simple characteristics present at the time of ICU admission, which may help healthcare professionals estimate patients\' prognose