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I am a Ph.D. candidate at China Medical University. We are conducting a project to develop a methodological quality assessment tool for health economic evaluation alongside pragmatic clinical trials. We sincerely invite scholars who are interested in health economic evaluation to participate in this survey. Your insights and participation in this survey would be invaluable to this study. This survey does not take more than fifteen minutes of your time. If you would like to participate, please click on the link below: https://qualtricsxmyzlnhzhd5.qualtrics.com/jfe/form/SV_0BWiD2usi20hmui. This link will redirect to the Qualtrics platform. For questions, please contact me at 2022110055@cmu.edu.cn or songrm97@gmail.com. Thank you for your time and consideration. Song Ruomeng, Ph.D. candidate China Medical University, China
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In the US, there have been many quality measures developed but with varying levels of confidence and reliability. Once a quality measure is developed and accepted, it continues to exist even when there are better measures that should replace it. The result is a growing list of measures that seem to be given equal weight in many applications. We need to develop a system that weights these measures according to their reliability. For example, the statistical significance of findings and sample size should be weighting factors. Reproducibility of results should be a big factor. You get the idea and that's all I have to offer.
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Hi to everybody.
I am a member of a working group at the Italian National Blood Center dealing with implementation of a Health Technology Assessment on the safety of intravenous iron administration in non-hospitalized settings.
How does it works in your country or did anyone of you implement specific local paths in this field?
Thank you
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Hello,
Sorry for that. Yes, in Australia, we can. We have primary care centres with general practitioners that can prescribe and then have the nurse administer.
Kind regards,
Alana
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What are some of the most frequently used quantitative methods in HTA. Which one of the Multi Criteria Decision Making method are used in HTA? What are advantage and disadvantages?
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To answer that fairly, It requires me to write a textbook, so I apologize for my brief answer.
Which one of the Multi Criteria Decision Making method are used in HTA?
This varies widely depending on healthcare organizations/countries. Each country has its own criteria/framework and even in UK NICE/NHS where I qualified is evolving constantly sometimes inconsistent (ICER threshold in general vs orphan disease vs cancer fund, value of year of life in NHS vs HT Treasury) . Some countries do not use MCDM or HTA !
What are some of the most frequently used quantitative methods in HTA?Economic evaluation most frequently Incremental Cost Effectiveness Ratios (ICER). Can be from narrow provider perspective or wider societal perspective. Most common models I have seen in NHS/NICE appraisals are decision tress, Markov, Partitioned survival models and to less degree microsimulation. Rare use of discrete event simulation because you get same results with Markov for less computational labor.
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Hello,
I am new to fmm. If I run a two component mixture model I will have two sets of predicted values (one for each component). I can also generate the posterior prob and the most likely latent class membership. How do I combine these two sets of values to produce single predicted values which correspond  to my dependent variable?
Thanks
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Dear statisticans and HTA experts ,
I am newbie and working on my first model using a markov model with probabilities varying according to time in state. After synthesis clinical trials, unfortunately I have difficulties to derive transition probabilities from pooled HR. How to calculate shape and scale parameter of Weilbull distribution from this pooled HR?
I really appreciate your helps. 
Kind regards
Cuc
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I hope that Andrew Paul McKenzie Pegman's answer works perfectly well for you.
In case it doesn't, please clarify some things:
- Probabilities varying with time in state and using Weibull distributions seems to say that you are not actually making a Markov model but that you are somehow including simulation of time to event with a Weibull distribution. Is that correct? Can you give some more detail on what you are doing?
- It seems impossible to me to estimate two Weibull parameters from one hazard ratio. However, since you have pooled data, why don't you use more information from the data than just the HRs?
- Since you say that you are a newbie: Do you have somebody mentoring or supervising your work?
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During clinical consultation doctors and nurses interview patients about their medical history. But, patients are usually not prepared for the clinical consultation. In theory, if patients administer their medical history on a computer/tablet before their appointment with the doctor or nurse, then they should be prompted and prepared for the medical history interview. This is one of the hypothetical advantages of patient-administered computerized history taking systems/automated medical history taking systems. What quantitative and/or qualitative factors measures exist that would assess if patients are prepared for the medical history interview?
I'm actually interested in identifying doctor-patient communication and non-communication measures that would determine if a group of patients who took an electronic medical history questionnaire were more prepared for a clinical consultation compared to a group that didn't take the electronic history questionnaire.
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There isnt any
I am just authoring
How to get the best from your GP practice to try to fill this gap!
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Question Closed. Thank you.
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Gamification, as you mentioned, is not one technique it is more about "learning from games" what makes them so engaging and motivating, using not only simple elements but "game-design elements in a non-game context" [1], meaning also mechanics, aesthetics and processes [2].
Motivation (and engagement) itself has it's theories. For example self-determination theory. There are theories focussing on the individuals needs, physical or psychological (content theories, e.g. [3]) and there are theories focussing on cognitive processes.
All of those approaches can be used to determine how to improve the usability of a system (and improve the user motivation) and to fit the users needs and requirements. To improve the user-motivation, it is key to understand the context of use, to analyse precisely what it is that motivates the user as an individual to enhance the correct motivational elements. Theories (gamification, psychology, motivation...) can be used to backup ideas and hypotheses for design decisions and can help us understand the underlying concepts of motivation and engagement. In the end, what motivates a user is determined by the users situation and context.
[1] Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011, September). From game design elements to gamefulness: defining gamification. In Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments (pp. 9-15). ACM.
[2] Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI(Vol. 4, No. 1, pp. 1-5). AAAI Press San Jose, CA.
[3] Maslow, A., & Lewis, K. J. (1987). Maslow's hierarchy of needs. Salenger Incorporated, 14, 987.
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I am working on an economic evaluation of a drug to promote wound healing on diabetic foot ulcers based on retrospective data (cost-consequences). I need to make a sensitivity analysis of efficacy and cost of the intervention. To an univariate analysis how to select the range of these variables? Which other alternatives can I use for the analysis?
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If the sensitivity analysis is intended to show robustness, then I think you should use plausible ranges and not and arbitrary percentage up and down.
I would also say that a plausible range is generally wider than a standard deviation up and down.
I would start with trying to find or estimate 95% confidence intervals.
Is that what you mean by "per cent intervals"?
If so, then I assume that the critique you got about that is because there may be more uncertainty than described by the confidence interval. That only describes uncertainty due to random error in a specific analysis. They should have given you some clue why they think that there is more uncertainty and preferably also suggest a way to determine actual uncertainty. It is hard for me to tell without detailed knowledge about your input parameters and their function in your evaluation.
(I don't know what you mean by "media analysis".)
I wish you the best of success with getting your degree and I hope that you will still want to continue with this type of work after you're done!
By the way: I would also love to know a bit more about how health economics is applied in Cuba.
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I am trying to assess effectiveness of neoadjuvant treatment for pancreatic cancer using Markov model. However RCTs do not yet exist for neoadjuvant therapy. The best available is prospective phase II trials which lack a control group. Can I perform a meta analysis of this existing data from which to calculate my transition probabilities or would multivariate analysis be better?
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The case you present is absolutely real and the discussion about this aspect is interesting as the type of information provided by longitudinal cohort interventional studies are not provided by RCTs. Provided the limitations are acknowledged the metanalytic approach is feasibile. Attached a document that I guess provides theoretical basis and numerous real examples.
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There is a number of the formulas for calculation of the cost-effectiveness of the projects, novel treatment modalities, surgery, drugs etc.
But how to calculate the cost-effectiveness of the diagnostic questionnaire?
How to retrieve the cost of analyses from the countries with the system of Health insurance? Should I take into account interests of the insurance companies? 
Thank you all in advance for your answers.
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Diagnostic tools present a complex challenge in cost-effectiveness analyses.  In general, before you can start, you need to understand the value of the information provided by the new diagnostic tool, in terms of how it changes treatment decisions and outcomes.   Specifically:
  • What is the current process of care?
  • At what point in the process is the new diagnostic information utilized?
  • For how many -- and which -- patients is the tool expected to yield information that differs from the previous information or assumption?
  • Among those patients, what proportion will have a change in care as a result of the new information?
  • How exactly will treatment change?
  • How does the effectiveness of the new treatment (including major or costly side effects) differ from the effectiveness of the treatment the patient would otherwise have received (including major or costly side effects)?
Once you have modeled how your diagnostic tool changes treatment paths and outcomes -- and for whom -- you can apply costs/utilities in accordance with your analytical objectives.  It's a challenge, but if you walk though the logic you will see quickly that the value of a diagnostic tool is often governed by the effectiveness of the treatments that might be applied as a result of the new information. 
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Dear Reader,
Please find below the detailled description of my current research and a couple of specific questions. I am glad for any opinion/input that you have on the topic, so please don't feel forced to answer the entire set of questions!
Many thanks and best regards
Stephan Schmidbauer
Preface
Combination treatments are an ever-increasing presence in oncology. In terms of explicitly approved drug combinations, the question is how the (additive) prices of these combinations can be reconciled with the financial power of the public healthcare system. If a clear advantage to overall survival can be demonstrated in a head-to-head clinical trial, the combination in question will usually be reimbursed. Often, however, manufacturers will refer to historical comparisons, one-arm trials, surrogate endpoints or adapted pathways for approval in order to provide evidence of efficacy. Despite subsequent approval, this leaves a significant degree of uncertainty in relation to efficacy and safety of new combination drugs. On the other hand, results on efficacy and safety in comparisons of phase II and III trials are frequently revealed to be in direct contrast (up to 50% of combinations are eventually found to be ineffective and/or unsafe, cf. doi:10.1038/nbt.2786 pmid:24406927).
A further case for consideration is the simultaneous administration (or sequential, if necessary) of drugs approved only as monotherapies; so-called “free combinations”. Aside from a pharmacological rationale, there is often no evidence to support such a regimen, yet the costs are additive.
  1. What data on efficacy, safety and (additional) benefit would you demand before reimbursing (as a payer) or prescribing (as a doctor) combination therapy instead of a monotherapy?
  2. Are surrogate parameters sufficient evidence of additional benefit in view of the significant (additional) cost of combination therapies?
  3. Do you differentiate between explicitly approved and “free” combinations when prescribing or reimbursing? (E.g. pertuzumab + trastuzumab vs. trastuzumab + anti-PD1; i.e. https://clinicaltrials.gov/ct2/show/NCT02129556?term=pembrolizumab+AND+breast&rank=1)
  4. How will you meet the financial challenges posed to your healthcare system by the foreseeable spread of combination drugs?
    • A:In your opinion, are the current combination drugs fairly priced?
    • B:Given that the value (to patient–relevant benefit) contributed by the individual partner of a drug combination  is normally unknown (i.e. it is unclear whether x months of drug 1 and y months of drug 2 contribute to i.e. Overall Survival ), how would you determine fair prices for the combination drugs?
  5. Do you view drugs reaching the market via accelerated approval processes more critically than drugs with full approval? If so, why? Do you reimburse/prescribe differently depending on the route to approval?
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Dear Stephan, this article, which I enclose, is not on the drug combinations in oncology. However, it addresses the issues of effectiveness, ethics and costs related to the introduction of new oncology drugs. I hope it will be useful to you.
Best regards, Maurizio
Cancer drugs, survival, and ethics
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In the SF12v1, four items are 2-level.
In de SF12v2, those items are 5-level.
I would like to know how I can convert the answers on the SF12v1 to the SF12v2.
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Well good luck with this problem. You should simply accept V1 - there is no  general "upgrading" algorithm that will enhance the 2-level responses into the magic 5-level system. Even if you could find an external dataset with BOTH versions coexistent you will have a sort of poor 2nd best solution if you could build such an algorithm.
SO what exactly is the problem in using V1 scoring .... is it because you don't get the expected/hoped for results maybe ?
There has to be a good/plausible rationale to justify modifying your raw data 
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Critics claim that there is an increasing number of drugs declared as “innovative” entering national markets even though they do not offer any additional benefit in comparison to the comparable therapies already available. Any opinions on this statement highly appreciated!
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Good question. Some independent drug review magazines look at this, eg Prescrire, which has an international English edition, and compiles its reports yearly. You can also look at the Germen Innovationsreport of the Technikerkrankenkasse. Look at the yearly data to see whether the rates are increasing.
My subjective impression is that they are actually not increasing, Look at the number of ACE inhibitors we've had, before patents started running out, and compare that to the number of statins or TNF-alpha inhibitors. If precision medicine turns out to be a really viable paradigm (I think the jury is still out on that, we'll see how gene therapy will play out), then it's reasonable to assume we'll see  less "me-too"s. But the visibility of the products is increasing, due to high prices and aggressive marketing, as Ranjita says above.
I agree with her, too, that "me-toos" can help drive down prices.This has been the topic of an article in the NEJM (ans-Georg Eichler, M.D., Hugo Hurts, M.Sc., Karl Broich, M.D., and Guido Rasi, M.D.N Engl J Med 2016; 374:1807-1809 May 12, 2016 DOI: 10.1056/NEJMp1601294). 
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Dear statisticans and HTA experts, 
 
I am still a "newbie" in health ecnomic modelling, but i am working on my first evaluation in metastatic melanom using a three-state markov model with the states PFS, PD, OS (my master thesis). I want to compare the available therapies for metastatic melanom. Unfortunately I have difficulties to derive transition probabilities. 
 
I found a HTA report (attached) which includes fitted distribution for the comparator. It states two log-logistic parameters for PFS and OS respectively and also the hazard ratios for the other interventions i want to compare with.
I also have a Kaplan-Meier plot (only for the comparator intervention).
 
Can you tell me, how I can derive my probabilities? Since I am not a good statistican, I dont know how to use the formulas probably. If I dont need to extrapolate the trial data, would it be easier?
 
Kind regards
Isabel from Germany
The parameters stated are on p. 63-65 in the attached HTA report
 
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 Hi Adnan,
It seems that you may be describing a bit different problem than I understood from Isabel.
Perhaps the following will be of help:
Rob
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I am specifically interested in publications that dealt with the development, validation and improvement of performance indicators in the cardiovascular or cerebrovascular diseases.
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Australas J Ageing. 2010 Mar;29(1):39-42. doi: 10.1111/j.1741-6612.2010.00411.x.
Performance indicators to measure dementia risk reduction activities in primary care.
Travers C1, Martin-Khan M, Lie D.
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I can only found generic instruments as the WLQ and the WPAIQ. Thanks
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You might want to refer to:
Wordsworth S, Thompson S. , An annotated cost questionnaire for patients: results of piloting, HERU Discussion Paper, 2001, Discussion Paper 03/01,
... Chapter 6 provides some useful guidance on measuring productivity loss in both chronic and acute conditions. Full description here: http://www.dirum.org/instruments/details/28#
DIRUM (Database of Instruments for Resource Use Measurement) also have details of certain instruments for 'skin'
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Focus would be on the Intermediate Care (IC) run mostly by NPOs which are subsidised by government and donations.
Possibility of doing a retrospective or prospective study
 either follow the patient route from hospitalization to intermediate care unit  
or create different strategies: hospitalisation, IC, and current status
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  • Thank you so much 
This is very helpful. Have a great day 
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I’m interested in the area of EdTech applied to reduce adverse event in the elderly but independent population, specifically in the area of medications interaction, aka, medication reconciliation. The main idea is to use interactive learning via mobile devices to follow up with elderly patients after they had been discharged from hospital and help them to better understand the risks of wrong medications combination and the importance of follow specific instructions, aka, health care (post discharge) plan; the final target goal will be to reduce readmissions due to adverse events associated with medication interaction. I can see 2 characteristics in the target population, 1) the possible lower literacy in the use of mobiles devices applications, and 2) the stress associated with the recent discharge from hospital. I’d appreciate any reference useful resources in those areas.
Thanks a lot.
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Uvernes, you've identified one of the problems with getting elderly patients to use technology as part of their (self) care: those who need help with their care are less likely to be able or willing to use technology (http://bit.ly/1KO0Oxc).
Any research in this area should take care to ensure that the demographic profile of the patients being  studyied is close to the profile of patients in general. Distributing an invitation to participate by email or social media, for example, will immediately exclude those who don't use technology.
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Hello
We are a Health Technology Assessment unit in a University hospital and we are actually gathering data on the efficacy of hybrid operating room dedicated (most of the time) to trauma care . The purpose of our investigation is to make evidence based recommendations for the implementation of hybrid operating room dedicated to trauma in our hospital. We are wondering if one of you can help us to identify a person to contact for filling a brief questionnaire about how it was implemented, reporting experience or any data on efficacy... This hybrid operating room must be equiped for angiography or chirurgical procedure as well as resuscitation and must be dedicated for trauma care most of the time. We have for reference the RAPTOR model implemented in Calgary (Canada) and Sydney (Australia).
Thank you for your collaboration
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Dear Renée
The topic you are investigating sounds very interesting. I’m an expert in simulation modelling in particular Discrete Events Simulation. With this tool you can actually “simulate” a setting simulating the operating room with the characteristics you are interested in. The simulation would allow you to find the optimal setting that will allow you to maximise the available resources. It would also help you determine the capacity of this room and potential queues, delays or waste of resources prior to its implementation. This type of modelling can help you in setting up the operating room you are interested in. I’ll be happy to have a chat if you find this interesting
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Commonly the term "acceptability" is used within evaluation of health technology or interventions.  However, I can't find any clear consensus as to what "acceptability" means as a researcher, some papers identify it as response rate others as likelihood for future use.  I'd be interested in your thoughts...
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Acceptability can address different dimensions (I discuss three, where I have experiences):
Is the benefit/risc ratio "good" enough from the point of view of patients?
Is the burden of disease worth an invasive/risky procedure (similar, but ot looking on benefit but on the -emotional-suffering)?
Is the benefit/price ratio good enough (if you have to pay for it yourself - is it worth the money)?
In an legal framework - patients may be obliged to undergo interventions to minimise damage following an injury or disease - "mitigation of damages" - then it could be a legal question, if someone has to undergo a procedure to mitigate long time effects. Example: retirement due to disease (coxarthrosis) - is hip replacement an acceptable treatment to prevent retirement (and the involved costs)?
So you can define it from the viewpoint of the patient = representing his preferences on health and life. Or you could define it from the viewpoint of a society (example: obligatory vaccination) to maximise the overall utility. Or from the viewpoint of someone (or some institution) who has to ensure (financial) consequences of a decision to undergo an intervention (pension fund).
In clinical research you may go for patient preferences. In health economics maximising the overall utility may guide the definition. In a legal framework its a question of legal interpretation.  
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The HTA approach is adopted by decision makers for assessing drug, medical device, treatments, but also immaterial resources as well as the organizative choices, care models, etc. Today few internationals studies have explored the use of HTA on nursing. Yet nursing plays a leading role in health care. How do you explain this?
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There is a very nice paper on this topic published a few years ago in the US, they give some answers to your question. THE CURRENT STATE OF NURSING SCHOOLS EDUCATION IN HEALTH ECONOMICS IN THE UNITED STATES by Maia Platt, University of Detroit Mercy & Andrea Kwasky, University of Detroit Mercy  
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I'm looking for a checklist or an outline of the steps designed specifically for the appraisal of health technology assessment articles.
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Health Technology Assessment (HTA) is defined as a specific form of policy analysis1 engaging multi-disciplinary groups to 'bridge between science and policy' and 'balancing between the ideals of scientific rigour and the realities of policy making'2. As  mentioned already, the content of HTAs reports can vary considerably and an all-encompassing checklist for their appraisal may not be appropriate.
Rather in the first instance,  checklists exist to appraise the components considered to inform a healthcare decision problem (i.e. policy)3 and equally (as work is designed to inform policy), checklists also exist to appraise the impact of the work on policy4.
The  individuals components of research required to inform an HTA are always dependent on each specific case under consideration (e.g. I have acted as an economist in studies using systematic reviews5, 6, trials7, 8 or both9). But whilst HTA have evolved as a research environment where one identifies conventional clinical research, HTA primarily function to inform policy.
The quality of the individual components is important and can be appraised using the various checklists (noting that quality assessment may be integral to HTA, particularly those using systematic reviews). For a compendium of the specific checklists, see EQUATOR network10 and on HTA processes NIHR Journals Library 'Information for authors’11.Specifically, as economist arguably performs policy analysis in HTAs, it is worth also worth firstly noting NIHR's 'Health Economics Checklist for Abstracts’12 and elsewhere comprehensive I previously reviewed the variety of checklist for appraising health economics analysis13.
References
1. "Health technology assessment", Wikipedia, The Free Encyclopedia http://en.wikipedia.org/wiki/Health_technology_assessment
2. D. Rotstein and A. Laupacis, “Differences between systematic reviews and health technology assessments: a trade-off between the ideals of scientific rigor and the realities of policy making.,” Int. J. Technol. Assess. Health Care, vol. 20, no. 2, pp. 177–83, Jan. 2004.
3. "A checklist for health technology assessment reports", The International Network of Agencies for Health Technology Assessment (INAHTA) , http://www.inahta.org/wp-content/uploads/2014/04/INAHTA_HTA_Checklist_English.pdf
5. R. Richardson, D. Trepel, A. Perry, S. Ali, S. Duffy, R. Gabe, S. Gilbody, J. Glanville, C. Hewitt, L. Manea, S. Palmer, B. Wright, and D. McMillan, “Screening for psychological and mental health difficulties in young people who offend: a systematic review and decision model,” Heal. Technol Assess, vol. 19, no. 1, 2015.
[6] "Early parenting interventions for families with young children showing severe attachment problems: an integrated evidence synthesis”, University of York http://www.york.ac.uk/healthsciences/research/mental-health/projects/archive/attachment/
7. Overend, K., Lewis, H., Bailey, D., Bosanquet, K., Chew-Graham, C., Ekers, D., Trépel, D., Gilbody, S. (2014). CASPER plus (CollAborative care in screen-positive EldeRs with major depressive disorder): study protocol for a randomised controlled trial. Trials, 15(1), 451. doi:10.1186/1745-6215-15-451
8. B. Wright, L. Tindall, E. Littlewood, J. Adamson, V. Allgar, S. Bennett, S. Gilbody, C. Verduyn, B. Alderson-Day, L. Dyson, D. Trépel, and S. Ali, “Computerised cognitive behaviour therapy for depression in adolescents: study protocol for a feasibility randomised controlled trial.,” BMJ Open, vol. 4, no. 10, p. e006488, Jan. 2014.
9. B. Wright, D. Marshall, D. Collingridge Moore, H. Ainsworth, L. Hackney, J. Adamson, S. Ali, V. Allgar, L. Cook, L. Dyson, E. Littlewood, R. Hargate, A. McLaren, D. McMillan, D. Trépel, J. Whitehead, and C. Williams, “Autism Spectrum Social Stories In Schools Trial (ASSSIST): study protocol for a feasibility randomised controlled trial analysing clinical and cost-effectiveness of Social Stories in mainstream schools.,” BMJ Open, vol. 4, no. 7, p. e005952, Jan. 2014.
10. Enhancing the QUAlity and Transparency Of health Research, http://www.equator-network.org
11. Information for authors, NIHR Journals Library, http://www.journalslibrary.nihr.ac.uk/information-for-authors
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I would like to compute bias corrected accelerated 95% confidence intervals for bootstrapped ROC curve analyses with the minimal sum of misclassification as cut-off criterion. Can anyone help me out? Any syntax for SPSS, SAS or R would be very appreciated.
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Two friends and colleagues of mine are renowned statisticians - both with academic appointments and one with private company.  I do not believe they are part of research gate, but , with your permission will forward emails on to them and seek their input on your behalf.
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Are there relevant studies about this?
I'm studying OA, trying to do a cost-utility analysis but I am having some problems with the efficacy evaluation.
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This publication could be very helpful:
Modelling the relationship between the WOMAC Osteoarthritis Index and EQ-5D.
Wailoo A, Hernandez Alava M, Escobar Martinez A.
Health Qual Life Outcomes. 2014 Mar 12;12:37
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I’m planning to investigate a framework about ethics in health technology assessment for elderly person. I read about various methods for assess policies in Canada. I’m really looking to find out what you’d consider to be the most efficient method as an ethical approach.
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I'm not clear about what you want to assess: if you want to assess health technologies, a good framework to start with is the Core Model(TM) developed by EUnetHTA (www.eunethta.eu). It has an ethical domain. Good luck!
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If yes, under what circumstances?
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Thank you for sharing your case and valuable advices. I would agree that you´ve made a right choice not moving on with indirect comparison - after all, it was a different route of administering a comparator. In my case there is a premise to do so, because clinical practice guidelines (CPG) clearly states that there is a drug comparator with the same indication. A device then is used (switched on) with cointervention (standard drug therapy) vs device off plus standard drug therapy. If there are studies with an intervention, that CPG addressed, vs standard drug therapy, that makes a chance for such comparison. Of course if all other PICO elements match.
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We are studying how to insert the results of economical evaluation of health technology in clinical guides or in health policies. We need references about it.
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Hi everybody
Definitely, You are right and It is emphasized that, all guidelines need to employ Economic Evaluations in CPGs. We can find thousands of sources for it. For example: NICE, NIHR, SIGN in Scotland, The Cochrane Library websites, etc. An interesting material for this query is the latest versions of NICE guidelines, in which cost effectiveness analysis results were attached to all CPGs.
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I am looking for comprehensive elaborations, presenting a set of criteria for introducing / adopting / market approval of drugs and medical devices. Could you recommend some reading?
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Start at EUnetHTA's website, www.eunethta.eu. Here is a paper on pharmaceuticals: Relative Effectiveness Assessment of Pharmaceuticals: Similarities and Differences in 29 Jurisdictions
Sarah Kleijnen, MSc1, 2, Corresponding author contact information, E-mail the corresponding author, Elisabeth George, PhD3, Scott Goulden, MSc3, Anne d'Andon, MD4, Pauline Vitré, PD, MSc4, Boguslawa Osińska, MSc5, Rafal Rdzany, PhD5, Steffen Thirstrup, MD, PhD6, Belen Corbacho, MSc7, Bence Z. Nagy, MSc8, Hubert G. Leufkens, PhD2, Anthonius de Boer, MD, PhD2, Wim G. Goettsch, PhD1, 2
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ISPOR also has a set of guidelines for PHARAMCOECONOMIC EVALUATION AT WWW.ISPOR.ORG
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Does every decision-maker (either in the public or private sector) decide using the same framework? Or the some indicators? How is the decision-making characterized?
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Dear Maria,
Regulatory standards plays an important role in medical device decision making, however as you mentioned decision making when it comes to acquisition of the device unfortunately doesn't always follow a formal pathway. Decisions can be made quite haphazardly based on using product from "same company" or comparatively cost effective. I find this article on institutional decision-making quite appropriate - http://www.sciencedirect.com/science/article/pii/S1532046403000558?np=y
Three type of factors influence decision making - environmental/cultural, social and cognitive. Please also see our article on purchasing of devices using mini-HTA - you will find it on researchgate. Looking forward to hearing your views on the topic.
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I am developing a questionnaire to assess the QALY gain/loss attached to a (temporary, short term) procedure. We are considering TTO (both standard and waiting time trade off) but I cannot find much in the literature about how to ensure the questions posed are valid and will return useful values. It was suggested that I look in the field of experimental economics, but I have so far failed to find much of use. Please can anyone offer any advise/evidence/publications?
Thanks
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Thanks so much, I really appreciate your help. Caz
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I need to assess readiness of our clients and the community for promoting health that may also provide management for some conditions using the existing technologies available in our settings. I am talking about developing country settings with cultural factors, where technology is not fully used as a tool for health benefits. Any ideas?
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I suggest using action research as your initial approach. This is because if you are going into a setting where there is little awareness or use of telehealth, doing surveys or interviews or focus groups may not give you the information you need because your participants can't give you feedback based on real world experience. Also telehealth services are highly specific, so getting generic responses might not translate well into the particular type of intervention you would like to implement. So I'd suggest a small scale implementation of your intended approach in collaboration with your participants, working with them to adapt your telehealth service, and collecting qualitative data as you proceed. Then later on once the service is operating you can plan a study which collects health outcome data.