Donepezil treatment for Alzheimer's disease was found to be cost-effective compared to no treatment or memantine treatment based on a discrete event simulation model. Specifically:
1) Treatment with donepezil resulted in an average of 0.13 more quality-adjusted life years (QALYs) gained per patient compared to no treatment, with average savings of €7,007 and €9,893 from healthcare and societal perspectives respectively.
2) For patients with moderate to moderately-severe AD, donepezil compared to memantine resulted in an average of 0.01 more QALYs gained per patient, with average savings of €1,960 and €2,825 from healthcare and societal
The process of healthcare is undertaken so that people can benefit from the intervention. An economic evaluation looks at all the implications of deciding to choose one way of providing care over another, not just the costs. This means that any effect the service, good or bad, has on the patient or customer needs to be investigated
There is often more than one way of doing something in healthcare.
For
example, there may be two different drugs that can be used to treat
depres sion, or two surgical techniques for the management of dysmenorrhoea.
Note that interventions may be compared against each other ( for example
antibiotic A against antibiotic B) or against a ' do nothing' scenario.
There are different ways in which we can choose one of these options.
We may
decide to pick the more effective surgical technique, or we may decide to
select the less costly antidepressant. Economic evalu ation is a generic term for
techniques that are used to identify, measure and value both the costs and the
outcomes of healthcare interventions. An economic evaluation is concerned
with identifying the differences in costs and outcomes between options. It can
be defined as a study that compares the costs and benefits of two or more
alternative interventions; so, the main components are costs and benefits
In a cost
benefit analysis (CBA) the outcomes of the two alternatives
are measured using monetary values, that is, the monetary value
attached to the health states produced by the two interventions.
CUA is a formal economic technique for assessing the efficien
cy of healthcare interventions. It is
considered by some to be a specific type of cost effectiveness analysis in which the measure of
effectiveness is a utility or preference adjusted outcome.
A comparative risk assessment of burden of disease and injury attributable to...Chuco Diaz
Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time.
The process of healthcare is undertaken so that people can benefit from the intervention. An economic evaluation looks at all the implications of deciding to choose one way of providing care over another, not just the costs. This means that any effect the service, good or bad, has on the patient or customer needs to be investigated
There is often more than one way of doing something in healthcare.
For
example, there may be two different drugs that can be used to treat
depres sion, or two surgical techniques for the management of dysmenorrhoea.
Note that interventions may be compared against each other ( for example
antibiotic A against antibiotic B) or against a ' do nothing' scenario.
There are different ways in which we can choose one of these options.
We may
decide to pick the more effective surgical technique, or we may decide to
select the less costly antidepressant. Economic evalu ation is a generic term for
techniques that are used to identify, measure and value both the costs and the
outcomes of healthcare interventions. An economic evaluation is concerned
with identifying the differences in costs and outcomes between options. It can
be defined as a study that compares the costs and benefits of two or more
alternative interventions; so, the main components are costs and benefits
In a cost
benefit analysis (CBA) the outcomes of the two alternatives
are measured using monetary values, that is, the monetary value
attached to the health states produced by the two interventions.
CUA is a formal economic technique for assessing the efficien
cy of healthcare interventions. It is
considered by some to be a specific type of cost effectiveness analysis in which the measure of
effectiveness is a utility or preference adjusted outcome.
A comparative risk assessment of burden of disease and injury attributable to...Chuco Diaz
Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time.
Economic impact of homeopathic practice in general medicine in Francehome
Abstract
Health authorities are constantly searching for new ways to stabilise health expenditures. To explore this issue, we
compared the costs generated by different types of medical practice in French general medicine: i.e. conventional
(CM-GP), homeopathic (Ho-GP), or mixed (Mx-GP).
Data from a previous cross-sectional study, EPI3 La-Ser, were used. Three types of cost were analysed: (i) consultation
cost (ii) prescription cost and (iii) total cost (consultation + prescription). Each was evaluated as: (i) the cost to Social
Security (ii) the remaining cost (to the patient and/or supplementary health insurance); and (iii) health expenditure
(combination of the two costs).
With regard to Social Security, treatment by Ho-GPs was less costly (42.00 € vs 65.25 € for CM-GPs, 35 % less). Medical
prescriptions were two-times more expensive for CM-GPs patients (48.68 € vs 25.62 €). For the supplementary health
insurance and/or patient out-of-pocket costs, treatment by CM-GPs was less expensive due to the lower consultation
costs (6.19 € vs 11.20 € for Ho-GPs) whereas the prescription cost was comparable between the Ho-GPs and the
CM-GPs patients (15.87 € vs 15.24 € respectively) . The health expenditure cost was 20 % less for patients consulting
Ho-GPs compared to CM-GPs (68.93 € vs 86.63 €, respectively). The lower cost of medical prescriptions for Ho-GPs
patients compared to CM-GPs patients (41.67 € vs 63.72 €) was offset by the higher consultation costs (27.08 € vs 22.68 €
respectively). Ho-GPs prescribed fewer psychotropic drugs, antibiotics and non-steroidal anti-inflammatory drugs.
In conclusions management of patients by homeopathic GPs may be less expensive from a global perspective and may
represent an important interest to public health.
El Estudio que Demostró el Control de la Industria de la Enfermedad sobre la Medicina
Este nuevo estudio, el primero en su tipo, comparó específicamente el nivel de publicidad farmacéutica con la cantidad y tipo de publicaciones acerca de suplementos alimenticios. Los autores revisaron un año de publicaciones de los 11 journals más grandes del mundo como por ejemplo el Journal of the American Medical Association, New England Journal of Medicine, British Medical Journal, Canadian Medical Association, Annals of Internal Medicine, Archives of International Medicine, Archives of Pediatric and Adolescent Medicine, Pediatrics and Pediatric Research y el American Family Physician.
My small effort to present an article with PPT presentation for learning purpose.
Color codes in the article PDF document:
1) Green for positive criticism
2) Red for negative criticism
3) Yellow for important points
3)
IT-Projekt für die elektronische Kommunikation der Leistungserbringer und Versorgungsanalyse bei der Hilfsmittel-Versorgung im Rahmen des DMP-Diabetes entsprechend § 67 und § 11
Abs. 4 SGB V.
Fuzzy Bi-Objective Preventive Health Care Network DesignGurdal Ertek
Preventive healthcare is unlike healthcare for a cute ailments, as people are less alert to their unknown medical problems.In order to motivate public and to attain desired participation levels for preventive programs,the attractiveness of the healthcare facility is a major concern.Health economics literature indicates that attractiveness to a facility is significantly influenced by proximity of the clients to it.Hence attractiveness is generally modeled as a function of distance.However, abundant empirical evidence suggests that other qualitative factors such as perceived quality, attractions nearby, amenities, etc. also influence attractiveness. Therefore, are alistic measures hould in corporate the vagueness in the concept of attractiveness to the model.The public policymakers should also maintain the equity among various neighborhoods, which should be considered as a second objective.Finally, even though general tendency in the literature is to focus on health benefits,the cost effectiveness is still a factor that should be considered.In this paper,a fuzzy bi-objective model with budget constraints of the problem is developed.Later,by modelling the attractiveness by means of fuzzy triangular numbers and treating the budget constraint as a soft constraint, a modified (and more realistic)version of the model is introduced. Two solution methodologies, namely fuzzy goal programming and fuzzy chance constrained optimization are proposed as solutions.Both the original and the modified models are solved within the framework of a case study in Istanbul,Turkey.In the case study,the Microsoft Bing Map is utilized in order to determine more accurate distance measures among the nodes.
http://ertekprojects.com/gurdal-ertek-publications/
https://link.springer.com/article/10.1007/s10729-014-9293-z
Economic impact of homeopathic practice in general medicine in Francehome
Abstract
Health authorities are constantly searching for new ways to stabilise health expenditures. To explore this issue, we
compared the costs generated by different types of medical practice in French general medicine: i.e. conventional
(CM-GP), homeopathic (Ho-GP), or mixed (Mx-GP).
Data from a previous cross-sectional study, EPI3 La-Ser, were used. Three types of cost were analysed: (i) consultation
cost (ii) prescription cost and (iii) total cost (consultation + prescription). Each was evaluated as: (i) the cost to Social
Security (ii) the remaining cost (to the patient and/or supplementary health insurance); and (iii) health expenditure
(combination of the two costs).
With regard to Social Security, treatment by Ho-GPs was less costly (42.00 € vs 65.25 € for CM-GPs, 35 % less). Medical
prescriptions were two-times more expensive for CM-GPs patients (48.68 € vs 25.62 €). For the supplementary health
insurance and/or patient out-of-pocket costs, treatment by CM-GPs was less expensive due to the lower consultation
costs (6.19 € vs 11.20 € for Ho-GPs) whereas the prescription cost was comparable between the Ho-GPs and the
CM-GPs patients (15.87 € vs 15.24 € respectively) . The health expenditure cost was 20 % less for patients consulting
Ho-GPs compared to CM-GPs (68.93 € vs 86.63 €, respectively). The lower cost of medical prescriptions for Ho-GPs
patients compared to CM-GPs patients (41.67 € vs 63.72 €) was offset by the higher consultation costs (27.08 € vs 22.68 €
respectively). Ho-GPs prescribed fewer psychotropic drugs, antibiotics and non-steroidal anti-inflammatory drugs.
In conclusions management of patients by homeopathic GPs may be less expensive from a global perspective and may
represent an important interest to public health.
El Estudio que Demostró el Control de la Industria de la Enfermedad sobre la Medicina
Este nuevo estudio, el primero en su tipo, comparó específicamente el nivel de publicidad farmacéutica con la cantidad y tipo de publicaciones acerca de suplementos alimenticios. Los autores revisaron un año de publicaciones de los 11 journals más grandes del mundo como por ejemplo el Journal of the American Medical Association, New England Journal of Medicine, British Medical Journal, Canadian Medical Association, Annals of Internal Medicine, Archives of International Medicine, Archives of Pediatric and Adolescent Medicine, Pediatrics and Pediatric Research y el American Family Physician.
My small effort to present an article with PPT presentation for learning purpose.
Color codes in the article PDF document:
1) Green for positive criticism
2) Red for negative criticism
3) Yellow for important points
3)
IT-Projekt für die elektronische Kommunikation der Leistungserbringer und Versorgungsanalyse bei der Hilfsmittel-Versorgung im Rahmen des DMP-Diabetes entsprechend § 67 und § 11
Abs. 4 SGB V.
Fuzzy Bi-Objective Preventive Health Care Network DesignGurdal Ertek
Preventive healthcare is unlike healthcare for a cute ailments, as people are less alert to their unknown medical problems.In order to motivate public and to attain desired participation levels for preventive programs,the attractiveness of the healthcare facility is a major concern.Health economics literature indicates that attractiveness to a facility is significantly influenced by proximity of the clients to it.Hence attractiveness is generally modeled as a function of distance.However, abundant empirical evidence suggests that other qualitative factors such as perceived quality, attractions nearby, amenities, etc. also influence attractiveness. Therefore, are alistic measures hould in corporate the vagueness in the concept of attractiveness to the model.The public policymakers should also maintain the equity among various neighborhoods, which should be considered as a second objective.Finally, even though general tendency in the literature is to focus on health benefits,the cost effectiveness is still a factor that should be considered.In this paper,a fuzzy bi-objective model with budget constraints of the problem is developed.Later,by modelling the attractiveness by means of fuzzy triangular numbers and treating the budget constraint as a soft constraint, a modified (and more realistic)version of the model is introduced. Two solution methodologies, namely fuzzy goal programming and fuzzy chance constrained optimization are proposed as solutions.Both the original and the modified models are solved within the framework of a case study in Istanbul,Turkey.In the case study,the Microsoft Bing Map is utilized in order to determine more accurate distance measures among the nodes.
http://ertekprojects.com/gurdal-ertek-publications/
https://link.springer.com/article/10.1007/s10729-014-9293-z
Homeopathic treatment of patients with chronic sinusitis: A prospective obser...home
This observational study showed relevant improvements that persisted for 8 years
in patients seeking homeopathic treatment because of sinusitis. The extent to which the observed
effects are due to the life-style regulation and placebo or context effects associated with the
treatment needs clarification in future explanatory studies.
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...hiij
Treatment management in cancer patients is largely based on the use of a standardized set of predictive
and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be
useful for selecting treatments because they directly predict the response to a treatment. The latter are used
to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease.
Current intelligent systems can be a solution for transferring advancements in molecular biology into
practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis
of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating
domain knowledge in predictive and prognostic models for personalized treatment. Our personalized
medicine support system provides the needed support in complex decisions and can be incorporated into a
treatment guide for selecting molecular targeted therapies.
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...hiij
Treatment management in cancer patients is largely based on the use of a standardized set of predictive
and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be
useful for selecting treatments because they directly predict the response to a treatment. The latter are used
to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease.
Current intelligent systems can be a solution for transferring advancements in molecular biology into
practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis
of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating
domain knowledge in predictive and prognostic models for personalized treatment. Our personalized
medicine support system provides the needed support in complex decisions and can be incorporated into a
treatment guide for selecting molecular targeted therapies.
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RI...hiij
Treatment management in cancer patients is largely based on the use of a standardized set of predictive and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be useful for selecting treatments because they directly predict the response to a treatment. The latter are used to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease. Current intelligent systems can be a solution for transferring advancements in molecular biology into practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating domain knowledge in predictive and prognostic models for personalized treatment. Our personalized medicine support system provides the needed support in complex decisions and can be incorporated into a treatment guide for selecting molecular targeted therapies.
PERSONALIZED MEDICINE SUPPORT SYSTEM: RESOLVING CONFLICT IN ALLOCATION TO RIS...hiij
Treatment management in cancer patients is largely based on the use of a standardized set of predictive
and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be
useful for selecting treatments because they directly predict the response to a treatment. The latter are used
to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease.
Current intelligent systems can be a solution for transferring advancements in molecular biology into
practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis
of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating
domain knowledge in predictive and prognostic models for personalized treatment. Our personalized
medicine support system provides the needed support in complex decisions and can be incorporated into a
treatment guide for selecting molecular targeted therapies.
ABSTRACT
Objective: Stroke is one of the leading causes of death and disabilities worldwide. Cost-effectiveness analysis helps identify neglected opportunities
by highlighting interventions that are relatively inexpensive, yet have the potential to reduce the disease burden substantially. In India, there are
wide social and economic disparities. Socioeconomic environment influences occupation, lifestyle, and nutrition of social classes which in turn would
influence the prevalence and profile of stroke. By reduction of delays in access to hospital and improving provision of affordable treatments can
reduce morbidity and mortality in patients with stroke in India. This study is designed to measure and compare the costs (resources consumed) and
consequences (clinical, economic, and humanistic) of pharmaceutical products and services and their impact on individuals, healthcare systems and
society.
Methods: The purpose of this study is to analyze and conduct a cost-effectiveness analysis for the treatment of stroke in Guntur City Hospitals.
The patients were treated either with aspirin or clopidogrel. The health outcomes were measured using Modified Rankin Scale, A prominent risk
assessment scale for stroke. The pharmacoeconomic data were computed from the patient data collection forms.
Result: The incremental cost-effectiveness ratio of aspirin and clopidogrel were calculated to be Rs. 8046.2/year.
Conclusion: The study concludes that aspirin has the increased socioeconomic impact when compared to Clopidogrel and we can see that the earlier
therapy has supported discharge, home-based rehabilitation along with reduced hospital stay and hence preferable.
Keywords: Stroke, Pharmacoeconomics, Cost-effectiveness analysis, Aspirin, Clopidogrel, Incremental cost-effectiveness ratio.
Description This is a continuation of the health promotion pro.docxmecklenburgstrelitzh
Description
This is a continuation of the health promotion program proposal, part one, which you submitted previously. Please approach this assignment as an opportunity to integrate instructor feedback from part I and expand on ideas adhering to the components of the MAP-IT strategy. Include necessary levels of detail you feel appropriate to assure stakeholder buy-in.
Directions
For this assignment add criteria 5-8 as detailed below:
5. Propose a health promotion program using an evidence-based intervention found in your literature search to address the problem in the selected population/setting. Include a thorough discussion of the specifics of this intervention which include resources necessary, those involved, and feasibility for a nurse in an advanced role. Be certain to include a timeline. ( 3 paragraph. You may use bullets if appropriate).
6. Thoroughly describe the intended outcomes. Describe the outcomes in detail concurrent with the SMART goal approach. (1 paragraph).
7. Provide a detailed plan for evaluation for each outcome. (1 paragraph).
8. Thoroughly describe possible barriers/challenges to implementing the proposed project as well as strategies to address these barriers/challenges. (1 paragraph).
9. Conclude the paper with a Conclusion paragraph. Don’t type the word “Conclusion”. Here you will share your insights about this strategy and your expectations regarding achieving your goals. (1 paragraph).
Paper Requirements
Your assignment should be 3 pages (excluding title page, references, and appendices), following APA standards.
Remember, your Proposal must be a scholarly paper demonstrating graduate school level writing and critical analysis of existing nursing knowledge about health promotion.
Please add this section to the PART 1 ATTACHED , must be one document for the entire work, AGAIN this 4 pages you will do now, please add it to the PART 1 ATTACHED, add references for this section and put them properly in APA style with the previously in the PART 1.
[removed]
Running head: CONGESTIVE HEART FAILURE Page 2
Patients with Congestive Heart failure and Increased Readmission Rates
Florida National University
NGR 6638
Professor Alexander Garcia Salas DNP, MSN, ARNP, FNP-C
Congestive heart failure (CHF), which affects millions of people, especially the elderly, is a significant and expanding public health concern. According to research, CHF accounts for between 12 and 15 million office visits and 6.5 million inpatient days annually (Hollier, 2021). Unfortunately, this approach leads to disease progression and rehospitalizations for many CHF patients because of insufficient care, unclear discharge instructions, and a lack of follow-up visits. These higher rehospitalization rates are driving up expenses and indicating that existing care strategies for CHF are not the most effective. Therefore, evidence-based t.
The Challenges Associated with Evaluating the Cost Benefit of Gene Therapies ...Covance
Despite the growing availability of approved gene therapies, decision-makers face significant challenges when evaluating pricing and reimbursement of these novel therapeutics. From determining cost-benefit ratios, setting out patient access criteria and designing reimbursement plans, this white paper explores some of the complex aspects of value assessment for gene therapies, and discusses results from a survey of key decision-makers across Germany, Sweden and the UK responsible for making pricing and reimbursement decisions.
Chronic disease (CD) such as kidney disease and causes severe challenging issues to the people all around the world. Chronic kidney disease (CKD) and diabetes mellitus (DM) are considered in this paper. Predicting the diseases in earlier stage, gives better preventive measures to the people. Healthcare domain leads to tremendous cost savings and improved health status of the society. The main objective of this paper is to develop an algorithm to predict CKD occurrence using machine learning (ML) technique. The commonly used classification algorithms namely logistic regression (LR), random forest (RF), conditional random forest (CRF), and recurrent neural networks (RNN) are considered to predict the disease at an earlier stage. The proposed algorithm in this paper uses medical code data to predict disease at an earlier stage.
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Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
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Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
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physicians may hesitate to treat patients accordingly Previous economic evaluations in AD have measured
given drug acquisition cost considerations [7]. Research outcomes using highly aggregated health states, and
on the cost effectiveness of cholinesterase inhibitors is thus were not able to capture the benefits associated
therefore important to provide decision makers with the with treatment in adequate detail. Furthermore, they
best possible economic evidence to determine whether have often modeled the disease either based on single
concerns over drug acquisition costs are legitimate. domains (e.g., MMSE–Mini-Mental State Examination)
Over the last decade, numerous studies have measured or global domains (e.g., CDR–Clinical Dementia Rating
the cost-effectiveness of treatments for AD [8,9], most eval- Scale), losing the ability to capture the effects of treat-
uating the cost-effectiveness of cholinesterase inhibitors. ment on the full spectrum of AD symptoms. This was
Eight studies have investigated donepezil [10-17], with all driven in part by limitations in data accessible to ana-
but one indicating that donepezil was cost-effective. In lysts and the difficulty of tracking progression on multi-
Germany, a recent study showed that donepezil was also ple measures using traditional Markov model
cost-effective in the German setting, with a base case esti- techniques. In addition, most of these models were
mated cost-effectiveness ratio of €4,264 per CDR–Clinical designed as cohort models with no ability to account for
Dementia Rating Scale gained [18]. individual characteristics in predicting outcomes, varia-
Previous cost-effectiveness studies have modeled AD bility in outcomes over the course of the disease or
progression in terms of cognitive function alone, func- other relevant factors that might influence important
tional status alone, a single global severity measure, or determinants of long term outcomes, such as persistence
progression to the need for “Full Time Care”. Our study with treatment. The shortcomings of modeling studies
uses an alternative modeling approach to estimate dis- in AD have been extensively debated in the literature
ease progression in terms of correlated changes in cog- [8,9,25,26].
nition, behavior and function. The model was initially Our study adopts an alternative approach in an
constructed for analyses set in the UK [19]. attempt to overcome some of these limitations. First, it
addresses limitations of existing models that focus on a
Methods single measure of disease severity alone to model the
The discrete event simulation developed for the evalua- evolution of AD, by modeling the disease using mea-
tion of donepezil’s cost-effectiveness in the UK [19,20] sures of cognition, behaviour and function. Second, it is
was adapted for Germany. The model calculates out- an individual simulation that is not encumbered by the
comes from the perspective of both the statutory health limitations imposed by Markovian structures such as an
insurance and care insurance (Gesetzliche Krankenversi- inability to account for individual characteristics by rely-
cherung/Soziale Pflegeversicherung, GKV/SPV), and ing on cohort mean values or the use of aggregate
from the societal perspective. The GKV/SPV perspective health states (e.g., mild, moderate, severe; full-time care,
encompasses direct medical costs borne by statutory pre-full time care) instead of continuous measurement
healthcare insurance including drug costs, costs for of disease progression. Finally, as the model employed
monitoring and service provision as well as patient care in this study is an individual patient simulation, it allows
costs borne by long-term care insurance. The societal for consideration of variation in patient characteristics
perspective comprises both direct and indirect costs, the and disease progression, allows for simulation of persis-
latter including costs of caregiver time. A discount rate tence with treatment, implementation of clinical stop-
of 3.0% was used for both costs and benefits [21]. In the ping rules, and time varying treatment effects and is
base case analyses, the time horizon is 10 years in order therefore able to capture disease progression and treat-
to capture all potential benefits over the course of the ment effects with greater accuracy. The model has been
disease. built using ARENA (Version 11) software.
Figure 1 provides an overview of the model flow. First,
Model overview simulated patients are created and individual, unique
To allow for individual level modelling, discrete event attributes are assigned. Each patient is then copied twice
simulation was used as the modeling technique, captur- and the three identical patients are assigned to either no
ing heterogeneity in disease progression and other out- treatment, donepezil 10 mg or memantine 20 mg.
comes, as well as tracking correlated changes on Patients are then followed over the course of the simula-
multiple domains on continuous rather than aggregated tion with their characteristics updated over time. The
discrete scales. The approach also allows for persistence simulation measures disease severity based on cognition
with treatment to be captured, factoring in time-depen- (using the MMSE), behaviour (using the Neuropsychia-
dence and the impact of treatment discontinuation on tric Inventory, NPI), activities of daily living (ADLs) and
both costs and disease progression in a realistic manner instrumental activities of daily living (IADL). In order to
[22-24]. preserve the correlation amongst these measures of
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Memantine
Assign
Accumulate
Disease
Outcomes
Donepezil Progression
Create Clone Delay to (Cost,
(MMSE
Patient Patient Next Event Location of
ĺ NPI
Care, QALYs
No ĺ ADL
Care Time)
Treatment ĺ IADL)
None Update
Disease
Progression
Stop
(MMSE
Move to Treatment
ĺ NPI
Event Exit
ĺ ADL
ĺ IADL) Model
GP Visit
Death
End of Model
Figure 1 Simplified representation of the Alzheimer’s disease simulation flow.
severity, integrated equations were developed which behavioral disturbances. IADL and ADL thresholds were
sequentially predict changes in MMSE, followed by NPI, arbitrarily set to their mid-point values of 50.
ADLs, and IADLs. Changes in cognition are first pre- In the simulation, patients can discontinue treatment
dicted for a simulated individual, which then influence either based on pre-defined stopping rules, or for other
changes in NPI, ADLs, and IADLs. Furthermore, changes unrelated reasons. As there are currently no defined
in ADL scores are used as part of the prediction of stopping rules in Germany (e.g., stopping treatment
changes in IADL scores. Based on a given patient’s char- when MMSE scores fall below 10), this option has only
acteristics at any point in time, including treatment status been explored in the sensitivity analyses. Mortality is
and current disease severity, costs, health utilities and also modeled, although given that neither cholinesterase
caregiver outcomes are calculated and accumulated over inhibitors nor memantine have been associated with
the appropriate time period. The model also reports time improvements in survival, time of death is assigned to
spent with non-severe symptoms as defined by MMSE, each individual prior to treatment assignment, thereby
NPI, ADL or IADL scores. MMSE scores below 10 were ensuring that survival is identical in all groups.
assumed to represent severe disease according to cur-
rently accepted definitions for severe cognitive impair- Data sources
ment. For NPI, a cluster analysis of psychiatric symptoms Population
using the NPI of 122 Alzheimer’s disease patients in the An individual patient data set constructed using baseline
US [27] was used as the basis for assigning a threshold of information from donepezil clinical trials [28-30] is
28 for the NPI as representing highly symptomatic sampled from, to create simulated patients. Characteristics
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carried in the model include patient age, sex, use of psy- PM represents patients’ previous MMSE measure-
chiatric medications, MMSE, NPI, ADL- and IADL scores, ment, partitioned over the MMSE scale. PM1–PM3 are
as well as caregiver age and sex. The trials chosen to pro- calculated as: PM1 = min(PrevMMSE, 9), PM2 = max[0,
vide the sample patients were those that had data on as min(PrevMMSE-9, 9)], and PM3 = max[0, min(Pre-
many target variables as possible, and taken together vMMSE-18, 12)]. δi represents a random intercept para-
include all AD severity levels [19]. meter, allowing the pattern of decline to vary between
The age and sex distributions of AD patients in Ger- patients. The MMSE scale itself ranges from 0 to 30.
many [31] were used to assign sampling weights to indivi- To apply a treatment effect for donepezil, a similar
duals in the data set in order to ensure that the age and model was fitted to the donepezil trial data to identify
sex profile of the simulated population was consistent with differences in rate of cognitive decline [19]. In the first
that of the German AD patient population. Furthermore, 20 weeks of treatment, the estimated coefficients for
analyses are specified according to subgroups of interest, treatment effect on annual rate of change was 6.16 and
so that sampling is restricted to the relevant population 2.47 over weeks 20 to 52. After 1 year, further treatment
(e.g., patients with mild to moderate AD, as defined by was assumed to simply maintain previous gains (i.e. the
baseline MMSE scores). treatment term in the rate of change equation is set to
Disease progression and treatment effects 0). Note that these coefficients are not the sole determi-
To improve on existing economic evaluations by includ- nant of treatment effect size given that rate of change in
ing the effects of disease on behavior and function, data MMSE is also influenced by individuals’ previous rate of
were analyzed from the CERAD (Consortium to Estab- decline and overall disease severity. Furthermore, the
lish A Registry for Alzheimer’s Disease) registry [32], coefficients for treatment effect influence the annual
and seven donepezil clinical trials in AD [28-30,33-36], rate of change, and are applied differentially depending
including data from open label extensions of two of the on time on treatment and how long patients remain on
studies [37,38]. Trial data included 2,700 patients from treatment. In order to test the validity of the effect size
the US, Canada, UK, France, and five Nordic countries, calculations, simulated effect sizes at 6 months were
with up to 52 weeks of follow-up. The inclusion of trials compared to the observed effect sizes in the clinical
in the current analyses was based on several criteria. trials [20], with the simulation resulting in an estimate
Most importantly, to develop equations related to dis- of improvement of 1.92 points on the MMSE for done-
ease progression and treatment effects, access to patient pezil versus no treatment, compared to the observed
level data was required. In selecting trials to be included 1.88 point difference.
in the patient level analyses, studies had to be Phase III NPI was predicted based on the donepezil trials where
or later, had to include a measure of baseline MMSE, NPI data were collected. It was modeled as change from
and had to include at least one of the effectiveness out- NPI at baseline.
comes included in the model. Studies conducted in spe- ChangeNPI = (5.74 − 0.64Donepezil + 0.03Weeks − 0.59NPIbase − 0.001NPI • Weeks
cial populations (e.g., women only, Apo-E subtypes, +0.24NPIrecent − 1.74White − 3.82Black + 2.34PsyMed + 0.12MMSEbase − 0.22MMSErecent + δi ) • 1.44
nursing home residents only); or of open label design
Donepezil represents the treatment effect of donepezil,
only were excluded, as were dose finding studies.
Weeks stands for weeks of follow-up in the simulation,
While MMSE data over time were available from trial
NPI base is the patient’s baseline NPI, NPI recent is the
data the patterns of change observed in CERAD were
patient’s last NPI. White and Black are dummy variables
more consistent with previous findings on progression
for race (All Other Races was the reference), PsyMed is
of AD in untreated patients [39-41] and were therefore
a dummy variable for patients treated with psychiatric
used to model the natural history of cognitive changes
medications at baseline, MMSE base represents the
in the absence of treatment. A piecewise linear regres-
patient’s MMSE at baseline, and MMSErecent represents
sion model was fitted to the annual rate of change in
the patient’s previous MMSE. δ i represents a random
MMSE. This approach allows for a different slope in dif-
intercept parameter, which allows the pattern of decline
ferent intervals of the MMSE scale to reflect differences
to vary between patients. Patient age and sex, as well as
in the rate of change at different disease stages. Vari-
rate of MMSE decline were also tested as predictors,
ables considered included patient age at baseline, sex,
but failed to reach a significance level of 0.05. The equa-
disease duration, baseline MMSE, and rate of decline in
tion for NPI was derived based on a normalized scale of
the first year (labeled PrevRate). The following MMSE
0 to 100, and is therefore multiplied by 1.44 to rescale it
equation was derived, retaining variables significant at
to the standard 0 to 144 range for the NPI.
the 0.05 level:
As changes in NPI are influenced by patients’ baseline
RateofChange = −5.4663 − 0.4299PM1 − 0.0042PM2 + 0.1415PM3 − 0.0791PrevRate and most current MMSE, the treatment effect of done-
+0.0747Age + δi
pezil is realized both through the treatment coefficient
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and its influence on MMSE over time [19]. The treat- Table 1 Changes in placebo-adjusted effectiveness
ment effect coefficient, therefore, only partially accounts outcomes for donepezil and memantine
for the impact of treatment on NPI changes, as patients Outcome Donepezil Memantine Difference
on treatment will generally have better MMSE scores. MMSE (0-30) 1.16 0.48 -0.68
For example, a patient who has a 1 point treatment NPI (0-144) -2.40 -2.76 -0.36
effect on MMSE, will experience a total treatment effect Function (0-100) -4.44 -2.35 2.09
on NPI of 1.44*[(-0.22 × 1) -0.64], or -1.27. Relative Risk of Drop-Out 1.18 0.66 0.62
For the scales that measure function (ADL and IADL)
standardized scales ranging from 0 (best function) to
100 (worst function) were created based on the available duration (10 years in base case), based on clinical stop-
clinical trial data. ping rules (e.g., MMSE falling below 10 as explored in
As with NPI, ADL and IADL equations predict change the sensitivity analyses), or other non-specified reasons.
from baseline: The analyses are based on the assumption that patients
RateofChangeADL = 1.35 − 0.81Donepezil + 0.06Weeks − 0.79ADLbase + 0.71ADLprevious
who stop treatment lose all treatment benefits over the
+0.12MMSEbase + 0.09Age + 0.81PsyMed − 3.05Black − 0.49MMSErecent + δi course of the subsequent 6 weeks [37].
Hazard ratios for premature treatment discontinuation
RateofChangeIADL = 1.27 + 0.63Donepezil + 0.17Weeks − 0.06Donepezil • Weeks − 0.84IADLbase are derived from the donepezil clinical trial data and
+0.002IADLWeek + 0.84IADLprevious − 0.67Male + 0.20MMSEbase − 0.28MMSErecent
applied to base discontinuation rates derived from actual
−0.16ADLbase + 0.18ADLrecent + δi
practice data in the UK [43] (Table 2) as there are no
Age stands for the patient’s age at baseline in years. equivalent data available for Germany. The hazard ratios
Potential predictors considered for inclusion (at 0.05 are based on a Cox regression model in which MMSE
level) were treatment, time, baseline and most recent and the rate of decline in MMSE were updated over
ADL/IADL, baseline and most recent MMSE, baseline time. Demographic variables were also tested as predic-
and most recent NPI, age, sex, treatment, and use of tors of discontinuation but were not significant (0.05)
anti-psychotic medications. and not retained.
For ADL scores, donepezil’s effect was modeled Mortality
directly through the treatment effect and the terms for German-specific survival data were obtained from the
patients’ most recent MMSE. For IADLs, treatment German Federal Statistical Office [44]. As there are no
comes into play through the treatment term, as well as disease specific survival data for Germany available, gen-
patients’ most recent MMSE and ADL scores. der-specific differences in survival for the UK and Ger-
Additional technical details on the equations used in man populations aged 65 years and older were applied
the simulation have been published elsewhere [19]. to survival times from the Medical Research Council’s
Standard errors and a validation that simulated results cognitive function and ageing study (MRC CFAS), and
on treatment effect from the predictive equations and time to death functions derived based on patient age
compare well to observed results on treatment effect are and gender at baseline [45]. Mortality was assumed to
also available [20], although IADL treatment effect sizes be unaffected by treatment.
were underestimated at 6 months. For NPI, the simu- Medical costs
lated treatment effect size was 1.75 points compared to Daily treatment costs of €4.20 for donepezil 10 mg and
the observed 1.68 for ADL, the simulated effect size was €3.83 for memantine 20 mg were derived from the Rote
2.55 points compared to an observed 2.59 and for Liste®.[46]. Patients on active therapy were assumed to
IADLs, the simulated effect size was 1.69 points com- incur costs associated with biannual visits to their physi-
pared to an observed 3.79. cian. Costs for outpatient service provision, such as GP
As head-to-head data were not available for meman- or specialist visits, dementia tests, laboratory tests or
tine, the simulation predicts disease progression and imaging are based on the German tariff EBM 2008 [46].
treatment persistence for patients on memantine using Direct patient care costs per disease state are based on
the parameters for patients on donepezil, but modifies a 2007 publication on the cost effectiveness of donepezil
these parameters using the difference between 6-month in Germany [18,47], and inflated to 2008 Euros, using
placebo adjusted clinical trial results for memantine the harmonized index of consumer prices for Germany
20 mg and donepezil 10 mg in moderate to severe AD [48]. It provides monthly costs by severity level which
patients (Table 1). Data for memantine were extracted were interpolated to provide estimates for intermediate
from a Cochrane meta-analysis [42]. disease severity stages (Table 3). The same cost was
Persistence applied regardless of location of care because health
Patients can stop treatment in the simulation either by state costs included costs for both ambulatory care and
reaching the end of the user-specified treatment nursing homes.
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Table 2 Baseline discontinuation rates for patients on donepezil and memantine
Months 0-3 Months 0-6 Months 6-12 Annual Risk After 12 Months
Donepezil 5.1% 5.1% 10.2% 10.3%
Memantine 3.1% 3.1% 6.3% 6.3%
Caregiver time costs finer gradient, these results were fit to a simple linear
Caregiver time was linked to disease severity parameters regression which predicted the proportion of patients
[20] based on an equation derived from two of the institutionalized as 64.35% - 2.86% × MMSE, with rates
donepezil clinical trials where these data were available, varying from 0% for those at the mildest stages of the
and took the form of [29,30]: disease to 50% for those with severe AD.
Health utilities
CareMinutesPerDay = 76.41 + 1.8Agecg + 93.02Malecg + 85.56Malepatient − 6.47MMSE
+0.58NPI + 2.66ADL + 2.61IADL + 20.55PsyMed Patients’ health utilities were estimated based on a pre-
viously published regression equation [51] which used
Agecg stands for the caregiver’s age, Malecg is a dummy the EQ-5D to derive health utilities for 272 AD patients
variable for the caregiver’s sex, and Malepatient for the in Nordic countries [19]. The NPI term in the published
patient’s sex. Patient age and relation of patient to care- equation was based on the brief NPI, and was modified
giver (spouse, child, or other) were other parameters to reflect the full NPI range (0 to 144) used in the simu-
tested but dropped for lack of significance with p > lation. The final equation took the following form and is
0.10. The p-value for PsyMed was 0.25 but it was applied in the model by using patients’ values (e.g.,
retained as it was a confounding variable (i.e., dropping MMSE score) over the course of the simulation to cal-
it biased the values of the other coefficients). culate the appropriate QALYs to be assigned to that
In sensitivity analyses, an alternative assignment of patient:
caregiver time was used, with caregiver time calculated
Utility = 0.408 + 0.010MMSE − 0.004NPI − 0.159Institutionalized + 0.051Caregiver
based solely on patient’s MMSE score using estimates
reported for Germany [47]. Caregiver time was valued at
MMSE represents the patient’s current MMSE, NPI
€5.21 per hour based on a published study [18,47].
represents the patient’s current NPI. Institutionalized is
Location of care
a dummy variable for whether the patient is institutio-
Costs and time by location of care are accumulated
nalized. Caregiver indicates whether the patient lives
based on the severity of disease patients experience over
with their caregiver.
the course of the simulation. Similarly, time spent by
Caregiver utilities are assigned based on equations
patients in institutions is allotted as percentage of the
derived from the donepezil trial data where caregivers
time that the patient was alive. Institutionalization rate
completed the SF-36 [20,28-30]. Scores were trans-
was calculated based on institutionalization rates of AD
formed to health utilities [52] and a linear repeated
patients in Germany [50] which were reported as 42.9%
measures model was used to develop the following
for patients with MMSE scores below 20, and 0% for
equation:
those with scores of 20 or higher. In order to produce a
Table 3 Cost inputs
Care costs by disease severity (MMSE) Monthly costs Source
Mild ≥ 25 €184 Adapted from Teipel et al. 2007[18]
≥ 20 - < 25 €593
Moderate ≥ 15 - < 20 €1,275
≥ 10 - < 15 €1,958
Severe < 10 €2,981
Drugs Treatment costs Source
per day**
Donepezil 10 mg €4.20 Rote Liste® 2008[49]
Memantine 20 mg €3.83 Rote Liste® 2008[49]
Outpatient treatment monitoring Costs per quarter Source
GP visit, geriatric assessment, MMSE test (one per quarter) €53.47* EBM2008[46]
* Including once-quarterly lump-sum for GP visit (€37.74), geriatric assessment (€ 13.69) and MMSE test (€2.04)
** Treatment costs per day are calculated based on the N3 package price provided in the Rote Liste® converted to a daily cost based on the number of tablets
per pack
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CaregiverUtility = 0.90 − 0.003AgeCG + 0.03MaleCG + 0.001Agepatient + 0.00MMSE − 0.001NPI associated with an average QALY gain of 0.01 per
−0.001ADL − 0.0004IADL − 0.01PsyMed
patient versus memantine (0.01 undiscounted), and care-
Patient sex and relation of patient to caregiver giver QALYs gained at less than < 0.001. The reduction
(spouse, child, or other) were other variables tested but in time patients spend institutionalized also falls by just
dropped for lack of significance with p > 0.10. PsyMed over 10 days per patient. For patients with moderately
and IADL had p-values of 0.20 but were retained as they severe AD, donepezil still dominates no treatment,
were confounders. although consistent with findings in the UK [20]. Cross
reference Getsios 2010, per patients savings were lower
Analyses at €8,043, as were both patient and caregiver QALYs
Base case analyses were run for patients with mild to gained, at 0.120 and 0.013, respectively. Memantine also
moderate AD (26 ≥ MMSE ≥ 10) treated with donepezil led to lower overall costs and improved QALYs relative
10 mg versus no treatment, and for patients with mod- to no treatment, although both savings and QALYs
erate AD (MMSE 10-19) on donepezil versus meman- gained, although savings were 35% lower compared to
tine 20 mg over a 10 year time horizon. those with donepezil, and QALYs gained 13% lower.
The following parameters were varied in the probabil- In one-way sensitivity analyses key parameters such as
istic sensitivity analyses: treatment effects on MMSE, caregiver time, costs, utilities, institutionalization and
NPI, ADL, and IADL, patient care costs, caregiver time treatment effects were varied. Regardless of the varia-
regression parameters, patient and caregiver utility tion, donepezil remained dominant compared to both
regression parameters, the proportion of patients living no therapy and memantine. Rates of treatment disconti-
in the community by disease severity, and treatment dis- nuation and the duration of treatment had the strongest
continuation rates. influence on the extent of savings and health benefits
Standard errors were available for many parameters (Table 5).
from the parameter source data, reflecting the study In probabilistic sensitivity analyses, donepezil dominates
sampling error. Where standard errors were not avail- no treatment in almost all replications from both the
able, 25% of the parameter mean was used to assign an health care payer and societal perspectives (Figure 2). Ver-
assumed 95% confidence interval from which standard sus memantine, donepezil dominates in 70% of replica-
error estimates were derived. A normal distribution was tions, and leads to savings in 95% of replications (Figure 3).
assumed for parameters on continuous variables, while For the analyses versus memantine, at a threshold of
proportion parameters on discrete variables were 10,000 Euro/QALY, donepezil was cost-effective from both
assumed to be beta distributed. perspectives in over 90% of replications.
Results Discussion
In patients with mild to moderately severe AD (26 ≥ The discrete event simulation developed for donepezil
MMSE ≥ 10), donepezil dominates no treatment from provides a flexible framework for the assessment of treat-
both the GKV/SPV perspective, with savings averaging ing AD patients with donepezil. By integrating patients’
€7,007 per patient (€7,323 undiscounted). From the individual characteristics, heterogeneity in the population,
societal perspective where savings increase to €9,893 per disease progression and outcomes can be captured. Dis-
patient (€10,384 undiscounted) (Table 4), donepezil ease progression was modeled not solely relying on 1 year
treatment is associated with an increase in QALYs aver- RCT data, but also using longer term CERAD registry
aging 0.13 per patient (0.14 undiscounted). For care- data, which allows for a more realistic representation of
givers, donepezil treatment increases QALYs by 0.01 the disease course. The model allows for analysis of popu-
compared to caregivers of untreated patients (0.02 lation subgroups, with different settings for time horizon,
undiscounted). Donepezil also increases the amount of treatment duration, discontinuation rules, and treatment
time patients spend with MMSE scores above 10 by an effects. Cost, utility and caregiver inputs can be specified
average of 24 weeks per patient, NPI scores below 28 by for different severity ranges and locations of care, or can
almost 6 weeks, and ADL/IADL scores below 50 by be specified using predictive equations, making adaptation
more than 7 and 3 weeks, respectively. In patients with of the model and incorporation of new data easier.
moderate including moderately-severe AD (20 > MMSE The analyses for Germany indicate that donepezil is
≥ 10), donepezil also dominates memantine, although clearly cost-effective in the treatment of patients with
savings are smaller, averaging €1,960 per patient (€2,097 mild to moderately-severe AD. In the base case and all
undiscounted) from the GKV/SPV- and €2,825 per one-way sensitivity analyses, donepezil dominated no
patient (€3,012 undiscounted) from the societal perspec- treatment and memantine in all scenarios evaluated.
tive. QALY gains are clearly smaller, with donepezil Results of the probabilistic sensitivity analyses were also
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Table 4 Base case results by disease severity for the 10 years following treatment initiation*
Patients with MMSE ≥ 10 and ≤ 26 versus untreated patients Untreated Donepezil Net difference
Survival (undiscounted, in years) 4,870 4,870 0,000
Drug Costs €0 € 4,625 €4,625
Total Non-Drug Direct Costs €126,863 €115,231 -€11,632
Total Direct Costs €126,863 €119,856 -€7,007
Indirect Costs €87,138 €84,253 -€2,885
Total Costs €214,001 €204,108 -€9,893
Years with MMSE > 10 1,972 2,435 0,463
Years with NPI < 28 2,680 2,794 0,114
Years with ADL < 50 1,896 2,036 0,140
Years with IADL < 50 0,241 0,303 0,062
Years in Institution 1,663 1,457 -0,206
Total Care Time (Years) 1,908 1,845 -0,063
QALYs (Patient) 1,659 1,790 0,131
QALYs (Caregiver) 3,272 3,287 0,014
QALYS (Patient + Caregiver) 4,931 5,077 0,146
Health Care Direct Cost/QALY (Patient + Caregiver) Dominant
Societal Total Cost/QALY (Patient +Caregiver) Dominant
Patients with MMSE ≥ 10 and < 20 versus memantine Memantine Donepezil Net difference
Survival (undiscounted, in years) 4,909 4,909 0,000
Drug Costs €4,972 €4,696 -€276
Total Non-Drug Direct Costs €129,702 €128,019 -€1,684
Total Direct Costs €134,674 €132,715 -€1,960
Indirect Costs €89,572 €88,707 -€ 865
Total Costs €224,246 €221,422 -€2,825
Years with MMSE > 10 2,023 2,801 0,058
Years with NPI < 28 2,808 2,751 -0,058
Years with ADL < 50 1,772 1,835 0,062
Years with IADL < 50 0,186 0,209 0,023
Years in Institution 1,702 1,673 -0,028
Total Care Time (Years) 1,961 1,942 -0,019
QALYs (Patient) 1,663 1,677 0,014
QALYs (Caregiver) 3,276 3,279 0,003
QALYS (Patient + Caregiver) 4,939 4,956 0,017
Health Care Direct Cost/QALY (Patient + Caregiver) Dominant
Societal Total Cost/QALY (Patient +Caregiver) Dominant
*All outcomes are presented at discounted values
highly favorable with donepezil dominating no treatment no treatment, the results of this study are much more in
in virtually all replications, and leading to savings in the line with previous findings for Germany [19], where a
comparison with memantine in 95% of replications. With base-case ICER of €4,264 per QALY for donepezil ver-
the availability of generic cholinesterase inhibitors, cost sus placebo was estimated. That study also indicated
savings should be even greater, although the contribution that starting treatment early leads to cost reductions
of the cost of treatment with donepezil to overall costs is and therefore improved cost-effectiveness. The more
modest, representing less than 2.5% of total costs in favorable predictions from our simulation are chiefly a
patients with mild to moderately-severe AD. result of the greater sensitivity of our model in captur-
Our model differs from most previous economic mod- ing changes in cognition, and in the case of indirect
els in AD in that we model disease progression over costs, the consideration of not only cognition, but also
several domains using continuous scales, rather than patient function and behavioral symptoms.
using a single domain and/or limiting outcomes to a The current simulation is not without limitations. For
small number of discrete health states. Although more example, the longest-duration of head to head clinical
favorable overall with donepezil predicted to dominate trial data available was for 1 year versus placebo [29].
9. Hartz et al. BMC Neurology 2012, 12:2 Page 9 of 12
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Table 5 One-way sensitivity analyses
Analysis QALYs Total Cost per QALYs Total Cost per
costs QALY costs QALY
Patients with Patients with
MMSE 10-26: MMSE 10-20:
donepezil versus donepezil versus
no treatment memantine
Base Case 0.146 -€9,893 Dominant 0.017 -€2,825 Dominant
Caregiver Time Effects of Disease Severity ↓ 25%† 0.146 -€9,171 Dominant 0.017 -€2,608 Dominant
Patient Care Cost ↓ 25%‡ 0.146 -€6,911 Dominant 0.017 -€2,417 Dominant
Patients institutionalized ↓ 25% 0.135 -€9,893 Dominant 0.015 -€2,825 Dominant
Patient Utility Effects of Disease Severity ↓ 25% 0.124 -€9,893 Dominant 0.015 -€2,825 Dominant
Stop Treatment if MMSE < 10 0.132 -€11,006 Dominant 0.018 -€2,279 Dominant
Stop Treatment if MMSE Deteriorates on any Scale after 6 Months 0.140 -€9,691 Dominant 0.054 -€4,578 Dominant
5 Year Time Horizon 0.140 -€10,172 Dominant 0,016 -€2,578 Dominant
Treatment Effects ↓ 25%† 0.107 -€5,930 Dominant 0.023 -€3,379 Dominant
No Discontinuation 0.204 -€13,215 Dominant 0.041 -€4,301 Dominant
Double Discontinuation 0.106 -€7,412 Dominant 0.003 -€1,760 Dominant
Treatment Duration 5 Years 0.140 -€10,171 Dominant 0.016 -€2,580 Dominant
Treatment Duration 1 Year 0.042 -€2,704 Dominant 0.008 -€991 Dominant
Alternative caregiver time effect (German data)[47] 0.146 -€16,677 Dominant 0.017 -€3,288 Dominant
Alternate disease severity definition based on German convention MMSE 0.151 -€9,486 Dominant 0.019 -€3,448 Dominant
ranges *
†
Coefficients in regression equations relating to disease severity (MMSE, NPI, ADL, and IADL) were reduced by 25%
‡
All patient care costs were reduced by 25%
* Mild MMSE ≥ 18, moderate MMSE 10-17, severe MMSE < 10
With the assumption that continued treatment after 1 treatment is discontinued. Comparisons with memantine
year serves as a maintenance function only with no are subject to even greater uncertainty, as no head-to-
further slowing of the rate of disease progression, we head trial data are available, requiring indirect compari-
have adopted a conservative approach consistent with sons based on pooled trial results. Clearly, incorporation
most other modeling studies in this area. Furthermore, of head to head clinical trial data versus memantine
we assume that all benefits are lost within 6 weeks if would strengthen comparisons and yield more robust
5000
0
-0.1 0 0.1 0.2 0.3 0.4
-5000
-10000
Costs
-15000
-20000
-25000
-30000
QALYs
Figure 2 Cost-effectiveness scatter plot for patients with 26 ≥ MMSE ≥ 10: donepezil versus no treatment. Distribution of replications:
0.8% in upper right quadrant (donepezil leads to incremental costs and higher QALYs), 99.2% in lower right quadrant (donepezil dominant,
leading to lower costs and higher QALYs).
10. Hartz et al. BMC Neurology 2012, 12:2 Page 10 of 12
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5000
3000
1000
-0.15 -0.1 -0.05 -1000 0 0.05 0.1 0.15
Costs
-3000
-5000
-7000
-9000
QALYs
Figure 3 Cost-effectiveness scatter plot for patients with 20 > MMSE ≥ 10: donepezil versus memantine. Distribution of replications:
69.8% in lower right quadrant (donepezil dominant, leading to lower costs and higher QALYs), 25.2% in lower left quadrant (donepezil leads to
lower costs and lower QALYs), 4.6% in upper left quadrant (donepezil dominated, leading to higher costs and lower QALYs), and 0.4% in the
upper right quadrant (donepezil leads to higher costs and higher QALYs).
results. In addition, the current analyses evaluate mem- those at the most severe stages of the disease, compared to
antine monotherapy versus donepezil monotherapy. well under €7,000 per patient for those at the most mild
Although memantine also be used as an add-on treat- stages. Finally, although wide variation exists in the valua-
ment to cholinesterase inhibitors, this was not evaluated, tion of informal care, with donepezil dominant over no
as the focus of these analyses was on the cost-effective- treatment and memantine, even when these costs are con-
ness of donepezil, and not memantine. sidered, the method of assigning costs to caregiver time
The source population for the trial data was not Ger- would only influence the extent of savings associated with
man, though it was weighted for the age and sex distri- donepezil. Of note, however, the hourly costs assigned to
bution of German AD patients when defining the caregiver time are substantially lower than those used in
simulated population. Other limitations of the data recent German costing studies in dementia [52,54,55].
revolve around assigning costs and utilities associated
with different degrees of disease severity. A recent Conclusions
review paper on health utilities [53] used in economic These analyses indicate that donepezil is highly cost-
evaluations, noted the limited amount of data on sever- effective in the treatment of mild to moderate AD in
ity specific health utilities in populations with AD, and Germany, and is likely associated with significant cost
the poor correlation between patient-based utilities, and savings when compared to untreated patients. While
those derived by caregiver proxy. benefits over memantine are modest, the base case and
The cost data for Germany are based entirely on MMSE sensitivity analyses results suggest a high likelihood that
ranges (i.e., they do not consider behavior or function). donepezil would lead to cost savings if used in place of
Furthermore published German cost data for AD at the memantine.
time of the analysis were scant, with only one publication
providing suitable information [47]. A number of studies Funding
on dementia and AD costs were published in 2011 This research was funded by Eisai GmbH, Germany.
[52,54-56]. Those studies that did report costs by severity Eisai GmbH was informed throughout the process of
of disease [52,54,55], all found that costs increase mark- data collection and analyses, and contributed to the
edly with increased disease severity, consistent with the research through critical review of results and
data used in the current model and therefore would not manuscript.
alter our conclusions. The one study that examined costs
in patients with AD, for example [54] found that the
Abbreviations
annual costs of the disease average €13,080 per patient per CDR: Clinical Dementia Rating Scale; MMSE: Mini-Mental State Examination;
year (€ 2009), but approached €25,000 per patient for AD: Alzheimer’s disease; NPI: Neuropsychiatric Inventory; ADLs: Activities of
11. Hartz et al. BMC Neurology 2012, 12:2 Page 11 of 12
http://www.biomedcentral.com/1471-2377/12/2
daily living; IADL: Instrumental activities of daily living; CERAD: Consortium to 8. Green C: Modelling disease progression in Alzheimer’s disease: a review
Establish a Registry for Alzheimer’s Disease; MRC CFAS: Medical Research of modelling methods used for cost-effectiveness analysis.
Council’s cognitive function and ageing study. Pharmacoeconomics 2007, 25(9):735-750.
9. Cohen JT, Neumann PJ: Decision analytic models for Alzheimer’s disease:
Acknowledgements state of the art and future directions. Alzheimers Dement 2008,
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1
B214 Baquba Building, Conington Road, SE13 7FF London, UK. 2United 11. Fagnani F, Lafuma A, Pechevis M, Rigaud AS, Traykov L, Seux ML, Forette F:
BioSource Corporation, 430 Bedford Street, Suite 300, Lexington Office Park, Donepezil for the treatment of mild to moderate Alzheimer’s disease in
Lexington, MA 02420, USA. 3United BioSource Corporation, 185 Dorval France: the economic implications. Dement Geriatr Cogn Disord 2004,
Avenue Suite 500, Dorval, Quebec H9S 5J9, Canada. 4United BioSource 17(1-2):5-13.
Corporation, 7101 Wisconsin Avenue, Bethesda, MD 20814, USA. 5Becton, 12. Green C, Picot J, Loveman E, Takeda A, Kirby J, Clegg A: Modelling the cost
Dickinson UK Limited, The Danby Building, Edmund Halley Road, Oxford effectiveness of cholinesterase inhibitors in the management of mild to
Science Park, Oxford OX4 4DQ, UK. moderately severe Alzheimer’s disease. Pharmacoeconomics 2005,
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Authors’ contributions 13. O’Brien BJ, Goeree R, Hux M, Iskedjian M, Blackhouse G, Gagnon M,
SH participated in the drafting of the manuscript, data collection, Gauthier S: Economic evaluation of donepezil for the treatment of
contribution to model analyses and interpretation of results. DG participated Alzheimer’s disease in Canada. J Am Geriatr Soc 1999, 47(5):570-578.
in the Model concept/design, data analyses and interpretation, critical 14. Jonsson L, Lindgren P, Wimo A, Jonsson B, Winblad B: The cost-
revision of article. SB contributed to model design and implementation, data effectiveness of donepezil therapy in Swedish patients with Alzheimer’s
analyses, and drafting of the manuscript. ST contributed to the data/model disease: a Markov model. Clin Ther 1999, 21(7):1230-1240.
analyses and critical revision of article. GM contributed to the model 15. Neumann PJ, Hermann RC, Kuntz KM, Araki SS, Duff SB, Leon J,
concept/design, critical revision/approval of the article (funding approved in Berenbaum PA, Goldman PA, Williams LW, Weinstein MC: Cost-
cooperation with German Eisai affiliate). effectiveness of donepezil in the treatment of mild or moderate
Alzheimer’s disease. Neurology 1999, 52(6):1138-1145.
Competing interests 16. Wimo A, Winblad B, Engedal K, Soininen H, Verhey F, Waldemar G,
DG, ST, SB (SH is a former employee) are all employees of a consulting Wetterholm AL, Mastey V, Haglund A, Zhang R, et al: An economic
company, which has conducted research on behalf of Eisai, including evaluation of donepezil in mild to moderate Alzheimer’s disease: results
research on donepezil. They have not received any reimbursements, fees, of a 1-year, double-blind, randomized trial. Dement Geriatr Cogn Disord
funding, or salary from an organization that could gain or lose financially 2003, 15(1):44-54.
from the publication of this manuscript. Partial funding for this manuscript 17. Stewart A, Phillips R, Dempsey G: Pharmacotherapy for people with
was provided by Eisai, and Eisai will be financing the processing charge. Alzheimer’s disease: a Markov-cycle evaluation of five years’ therapy
Eisai reviewed the manuscript and Grant Maclaine, one of the co-authors using donepezil. Int J Geriatr Psychiatry 1998, 13(7):445-453.
was an employee of Eisai at the time of manuscript preparation. Eisai placed 18. Teipel SJ, Ewers M, Reisig V, Schweikert B, Hampel H, Happich M: Long-
no restrictions on the content of the manuscript. They do not hold any term cost-effectiveness of donepezil for the treatment of Alzheimer’s
stocks or shares. The only data used in the study that are not publicly disease. Eur Arch Psychiatry Clin Neurosci 2007, 257(6):330-336.
available are those from the donepezil clinical trials (although results from 19. Getsios D, Blume S, Ishak KJ, Maclaine GD: Cost effectiveness of donepezil
these trials are all publicly available). Ethics approval for these trials had in the treatment of mild to moderate Alzheimer’s disease: A UK
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the manuscript. Eisai provided funding for manuscript development and will 20. Getsios D, Blume S, Ishak KJ, Maclaine GD: Supplemental Digital Content:
pay the manuscript processing charge. Data, other than those from the Cost Effectiveness of Donepezil in the Treatment of Mild to Moderate
donepezil clinical trials, are publicly available. Results from the donepezil Alzheimer’s Disease. 2010 [http://download.lww.com/
clinical studies have been separately published and ethics committee wolterskluwer_vitalstream_com/PermaLink/PCZ/A/
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21. Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG).
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