Medical Informatics - Science topic

Have you considered exploring the link between computer and information literacy of healthcare professionals on the one hand and the development of patient health literacy on the other? You can do one research on computer and information literacy of healthcare professionals and another research on health literacy of patients. You can format the questions so that certain cause-and-effect relationships can be identified in the analysis of the answers. Good luck !

Thank you Sudheer Kumar Shukla.

14/10/2021: We are witnessing an epochal shift that has started from the Port Authority of Trieste and it's reverberating through all European ports. But, as you may imagine, Trieste Port, is not a simple gateway. It's not. It's the main access from all over the world and the majority of trades from China to Central Europe. Germany is starting to witness a total disruption of its supply chain logistics because of the fact that the silk road model, extraordinarily signed by its President D'Agostino and the Chinese President, has addressed important funds for the establishment of a Trans-European Transport Network. On the other side of the Upper Adriatic zone, Koper (Capodistria) is trying these days to compete with Trieste, by putting into practice only a part of its national infrastructure 2TDK, the biggest EVER conceptualized in Slovenia!

Now the cargos are trying to deliver in Koper. But at which environmental cost for a greenpass? Despite their proximity and same voltage line, Trieste and Koper's policies did not join! Result: the goods will pretend longer routes, bottlenecks at a slower speed (in this article you see all the deficiencies of the railways tracks, as a result of dozens and dozens of years on a diplomatic level, after the Yugoslavia abolishment and diaspora. We are witnessing a new chapter within the EU framework. International leaderships did not meet national interest: horizontally, common people of the harbors working class are going to unify under no flag, no color, no race diversity, all for a common universal right of working without a pass permit that is not transparent, time demanding and logistically impossible to be fulfilled for all thousands of workers, around the globe, daily. In the last section, I highlighted one year ago in 2020 the premises of this urgent crisis that seemed to happen, and it's happening: (the article has been acclaimed at ICCAUA 2021 in Turkey and has reached important authorities, hereby aforementioned; the list of references may also increment the scope of your research):

Please have look on our(Eminent Biosciences (EMBS)) collaborations.. and let me know if interested to associate with us

Here is our lab page: https://www.eminentbio.com/home/members

Here is our publication: https://www.eminentbio.com/home/Publication

Our recent publications In collaborations with industries and academia in India and world wide.

EMBS publication In association with Universidad Tecnológica Metropolitana, Santiago, Chile. Publication Link: https://pubmed.ncbi.nlm.nih.gov/33397265/

EMBS publication In association with Moscow State University , Russia. Publication Link: https://pubmed.ncbi.nlm.nih.gov/32967475/

EMBS publication In association with Icahn Institute of Genomics and Multiscale Biology,, Mount Sinai Health System, Manhattan, NY, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29199918

EMBS publication In association with University of Missouri, St. Louis, MO, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30457050

EMBS publication In association with Virginia Commonwealth University, Richmond, Virginia, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852211

EMBS publication In association with ICMR- NIN(National Institute of Nutrition), Hyderabad Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/23030611

EMBS publication In association with University of Minnesota Duluth, Duluth MN 55811 USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852211

EMBS publication In association with University of Yaounde I, PO Box 812, Yaoundé, Cameroon. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30950335

EMBS publication In association with Federal University of Paraíba, João Pessoa, PB, Brazil. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30693065

Eminent Biosciences(EMBS) and University of Yaoundé I, Yaoundé, Cameroon. Publication Link: https://pubmed.ncbi.nlm.nih.gov/31210847/

Eminent Biosciences(EMBS) and University of the Basque Country UPV/EHU, 48080, Leioa, Spain. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852204

Eminent Biosciences(EMBS) and King Saud University, Riyadh, Saudi Arabia. Publication Link: http://www.eurekaselect.com/135585

Eminent Biosciences(EMBS) and NIPER , Hyderabad, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29053759

Eminent Biosciences(EMBS) and Alagappa University, Tamil Nadu, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30950335

Eminent Biosciences(EMBS) and Jawaharlal Nehru Technological University, Hyderabad , India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/28472910

Eminent Biosciences(EMBS) and C.S.I.R – CRISAT, Karaikudi, Tamil Nadu, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30237676

Eminent Biosciences(EMBS) and Karpagam academy of higher education, Eachinary, Coimbatore , Tamil Nadu, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30237672

Eminent Biosciences(EMBS) and Ballets Olaeta Kalea, 4, 48014 Bilbao, Bizkaia, Spain. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29199918

Eminent Biosciences(EMBS) and Hospital for Genetic Diseases, Osmania University, Hyderabad - 500 016, Telangana, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/28472910

Eminent Biosciences(EMBS) and School of Ocean Science and Technology, Kerala University of Fisheries and Ocean Studies, Panangad-682 506, Cochin, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27964704

Eminent Biosciences(EMBS) and CODEWEL Nireekshana-ACET, Hyderabad, Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/26770024

Eminent Biosciences(EMBS) and Bharathiyar University, Coimbatore-641046, Tamilnadu, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27919211

Eminent Biosciences(EMBS) and LPU University, Phagwara, Punjab, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/31030499

Eminent Biosciences(EMBS) and Department of Bioinformatics, Kerala University, Kerala. Publication Link: http://www.eurekaselect.com/135585

Eminent Biosciences(EMBS) and Gandhi Medical College and Osmania Medical College, Hyderabad 500 038, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27450915

Eminent Biosciences(EMBS) and National College (Affiliated to Bharathidasan University), Tiruchirapalli, 620 001 Tamil Nadu, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27266485

Eminent Biosciences(EMBS) and University of Calicut - 673635, Kerala, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/23030611

Eminent Biosciences(EMBS) and NIPER, Hyderabad, India. ) Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29053759

Eminent Biosciences(EMBS) and King George's Medical University, (Erstwhile C.S.M. Medical University), Lucknow-226 003, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/25579575

Eminent Biosciences(EMBS) and School of Chemical & Biotechnology, SASTRA University, Thanjavur, India Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/25579569

Eminent Biosciences(EMBS) and Safi center for scientific research, Malappuram, Kerala, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30237672

Eminent Biosciences(EMBS) and Dept of Genetics, Osmania University, Hyderabad Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/25248957

EMBS publication In association with Institute of Genetics and Hospital for Genetic Diseases, Osmania University, Hyderabad Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/26229292

Sincerely,

Dr. Anuraj Nayarisseri

Principal Scientist & Director,

Eminent Biosciences.

Mob :+91 97522 95342

Thanks Safial Islam Ayon

Dear Professor/Researcher,

Book Chapter proposal(s) are invited for the edited book titled “Prospects of Blockchain Technology for Accelerating Scientific Advancement in Healthcare” to be published by “IGI Global, 701 E. ChocolateAve. Hershey, PA 17033, USA”.

Please visit the following link to propose a book Chapter:

Thanks & Regards,

GC Deka

This Ayurvedic concept of Predictive, Preventive and Personalized Medicine may be informative:

The question becomes the degree to which national economies are affected by disease burdens when the nature of that burden is unclear because of different standards of reportage. Similarly, if you mean data on supply--for instance ventilators or certain medications--if unreliable the limits of those records will result in a lack of resources at treatment sites. The effect on the economy in the first will involve the cost of unanticipated disease incidence or the expansion of diseases (for example in epidemic cases) that might have been anticipated, with better records, and thus better prepared for. Similarly, if it's about supply of equipments or pharmaceuticals the shortages that result from inconsistent records will mean either higher costs for emergency purchase or higher mortality/morbidity in the absence of necessary equipment or pharmaceuticals. If the numbers are sufficient--for instance provision of vaccines, or undercounting of those with critical conditions requiring extensive medication, the effect may be broadly economic as well as clnical.

I need Epilepsy and heart data set with iot+deep

email: yaghobzadehr@gmail.com

Hi,

I'm doing my PhD in health informatics. The top rank journal in health informatics is Journal of Medical Internet Research (JMIR) which itself has a bunch of sister journals e.g. JMIR mHealth and uHealth, JMIR mental health, JMIR diabetes, JMIR research protocols, etc. that you can choose depending on your paper topic: https://www.jmir.org

Hope this is a bit helpful. All the best.

Robab

Hi, there is a very similar question with some answers here:

While you can find generic criteria to evaluate, I think you also need to evaluate the needs that the technology should meet. These will differ from use case to use case, and hence it's difficult to say which would be the "best" mhealth app in any given situation.

Milena Cukic - Thank you for your question. To know the journal impact factor, you could either search the current version of the Journal Citation Report (JCR) published by Clarivate Analytics was known as The Institute for Scientific Information (ISI). The second way is to look at the website of the journal. Then search for the section - About This Journal (Abstracted and Indexed In).

The second method is secure. Back to your question for that journal. The website address https://www.springer.com/journal/41666

Now go down the webpage to the section "About This Journal". This journal is indexed in "EBSCO Discovery Service, Google Scholar, INSPEC, Institute of Scientific and Technical Information of China, Japanese Science and Technology Agency (JST), OCLC WorldCat Discovery Service, ProQuest-ExLibris Primo, and ProQuest-ExLibris Summary."

There is no mention of the Institute for Scientific Information (ISI). Therefore it is not listed and has no impact factor as per the Web of Science. Check Scopus. But this is a different citation system, and not all universities consider Scopus ranking or citations. It is usually the Web of Science. I hope this makes things clear to you.

Link for the grant

http://grants.nih.gov/grants/guide/pa-files/PAR-19-093.html

If you are interested in introducing analytics ML or AI, then a key issue to negotiate is the trustworthiness of the system and analytic products. The analytical algorithms and output are often based on the commercial or market relevant outcomes and measures. These are often not relevant to health or defined differently to well established epidemiological and biostatisticsl terms used in medicine. This may cause problems for interpretation by the clinical team who are trained in medical stats. Also non-medical analytic processes do not understand or take into account the wide range of biases present in clinical data or understand biological mechanisms and criteria for causation. These are important issues that need to be addressed.

Both ways.

Ayele - You can get the best PhD dessertation tittle on the issues of nursing, public health, nutrition or health informatics, pediatric problems and so on by following certain steps: 1) Write down a list of topics that you are interested in and choose a topic that you are most interested in, 2) Narrow your topic to something manageable and talk to potential supervisors, friends, fellow scholars, colleagues etc, 3) Define the problem - a well defined problem is research half done and make your title concise, simple and clear, 4) Do a brief survey of literature to know how much work has already been done and what are the gaps in knowledge, 5) Choose a title which highlight the purpose of the study, which can often include its context, outcomes, and important aspects of the research strategy adopted.

Dear Dr. Mehri,

Regarding the features you need, the journal of Acta Medica Informatica seems to be a good choice. You can find it here: https://actainformmed.org/

Good luck

Dear George

There are a number of good Open Source EHR's are available. Try looking at https://www.medfloss.org/ which is run by the IMIA Open Source Group.

I note you are in Public Health. Have you seen the District Hospital Information System (DHIS) which is Open Source on http://www.hisp.org/services/dhis-2/

I had the honour of chairing the IMIA OS group so I may sound a bit biased but in the UK 14 years ago I ran a commercial EHR to great effect.

Regards

Prof

i considered that data is not exist. it is privacy and secret for hospital due to protect data from decendants. so it will not be online

Go for inderscience

Hi Tariq, The special issue is already published in January 2018. Thank you. Prashant

For PACS archive, you also have Dicoogle. Check at: www.dicoogle.com

Its base on country. For Example for New Zealand ( NZULM ) For Australia MIMS etc..

Hi,

I work at the VIB Nanobody Core (https://corefacilities.vib.be/nsf), we make Nanobodies for all interested academic groups or companies. Our group was founded out of the lab that originally discovered the Nanobodies, so we know what we are doing ;-) . If you're interested or want more info, just let me know.

Best Regards

Hi,

- Several biomedical ontologies have been created. Ontologies such as SNOMED-CT are used to model the clinical terms and processes in order to provide the core terminology for the Electronic Health Records (EHR). The use of SNOMED-CT in Health Informatics Systems can lead to an interoperable EHR and due to that can enhance the interoperability between different HIS. The most significant biomedical ontologies will be described in terms of domain and use. Most of the ontologies and terminologies are available through web services via the BioPortal.

- UMLS repository is consisted from biomedical vocabularies and ontologies thatare developed by the US National Library of Medicine. UMLS covers most of thebiomedical terminology and it consists of over 60 vocabularies with 900,000 concepts and over 12 million relationships among these concepts. The most notable vocabularies that are integrated in UMLS are SNOMED-CT, ICD-10, Medical Subject Headings (MeSH), Gene Ontology and others. UMLS covers from clinical terms to

genetic information.

In addition, i suggest you to read these papers:

-

Best regards,

wiem

@Meng Ding,i think the Hololens uses the two depth sensor instead of  two rgb sensors.

1st,getting a density point cloud.The feature based or  optical-flow based is not enough to generate such density mesh as Hololens does now.

2nd,rgb sensor is not effective in dark environment,but Hololens does.RGBD sensor is more robust than rgb sensor.

For these two reasons,i think the MS would choose RGBD sensor.

Thanks Sir

Can recommend this book, https://www.crcpress.com/Guide-to-Health-Informatics-Third-Edition/Coiera/p/book/9781444170498 and to follow Coiera on Twitter and LinkedIn and groups in which he participates.

May trialect.com be a good candidate for this. General societies websites like ASCO, SIOP, and ESMO or specific ones like European Neuroendocrine Tumor Society may have interest to publish that too .

Peter, I believe that an important part of structuring you PhD topic is to develop a clear statement about the outcomes which you expect to deliver. 

Gamification is a popular application of technology to induce and support behaviour change. The behaviour which you hope to influence will (possibly) have an effect on the health of those people 'playing' your health games. 

That background leads to some important preliminary questions.

* What diseases or disease groups are likely to be improved through behaviour change?

* What are the changes in behaviour that will help?

* Can gamification induce, support or monitor those changes?

* What is the demographic/socioeconomic pattern of patients with your target diseases/disease groups?

* Which demographic/socioeconomic groups are likely to adopt and continue using a 'gamification' option as part of their health self-care?

* How good is the overlap between your 'disease' group and your 'user' group?

You may find that gamification is popular with 'People Like Us' (financially secure, tertiary educated, with good text, technical and health literacy), while the burden of chronic disease has its greatest impact on those who are the opposite - impoverished, poorly educated, and with low literacy.

I would recommend:

Kriglstein, S., Leitner, M., Kabicher-Fuchs, S., & Rinderle-Ma, S. (2016). Evaluation Methods in Process-Aware Information Systems Research with a Perspective on Human Orientation. Business & Information Systems Engineering, 58(6), 397–414. https://doi.org/10.1007/s12599-016-0427-3

Tremblay, M. C., Hevner, A. R., & Berndt, D. J. (2010a). Focus groups for artifact refinement and evaluation in design research. Communications of the Association for Information Systems, 26, 1.

Tremblay, M. C., Hevner, A. R., & Berndt, D. J. (2010b). The Use of Focus Groups in Design Science Research. In A. Hevner & S. Chatterjee, Design Research in Information Systems (Bd. 22, S. 121–143). Boston, MA: Springer US. Abgerufen von http://link.springer.com/10.1007/978-1-4419-5653-8_10

Thank you a lot for your input! The social inequity I am aware is very important and to be considered. But sometimes the circumstance you can change or implement somehting don´t offer to all critical endpoints that should be considered.

I also remember a study on health literacy showing, it is the ones with low HL who benefit most of any kind of supoort systems.

Thank you a lot for your great input again!

 Im a student of the Physics department. I don't have pendulum, but if you give me specifications or reference that contains specifications I might be able make one.

Thanks Feras, this is not quite what I am looking for however. By near misses, I mean: “... an event/situation in which a negative outcome could have occurred but did not, either by chance or because the problem was identified and corrected before a negative outcome occurred.” - Crane, 2015. 

For example, a situation where a surgeon nearly operates on the wrong leg, but the problem is caught in time. 

The cutting-egde advancement is enclosed.

Good luck !

Thanks so much. I wish you a successful completion of the Ph.D programme. I am looking forward to a future team work.

Thanks and stay blessed.

Aaron

Non-communicable chronic diseases like cardiovascular disease, diabetes, and mental health disorders have been widely researched and discussed but still you can contribute. Anyhow keeping your concerns, you can think for digitizing self monitoring for chronic hepatitis B or C, asthma, chronic obstructive pulmonary disease (COPD), chronic kidney disease, and kidney stones, I think exploring them would lead to good contribution.

Hi Rachel, 

Thank you for getting back to me. I look forward to hearing how your project progresses. Wishing you all the best,

Fran

Thank You 

Mary I will check them out I am sure there will be useful information in the two selected readings.

Regards

Harpinder Chima

by using fuzzification

If your question regards usability of the system then I recommend the System Usability Scale (SUS), a 5-point Likert scale that ranges from 1=strongly disagree to 5 = strongly agree for each of ten items, scoring produces a result from 0 to 100; it has a global mean score of 68 (SD, 12.5)¹. It is widely used for general usability testing because it has demonstrated reliability and internal consistency ranging from 0.85 to 0.90, and factor analysis shows that the factors load on two subscales, learnability, and usability.² 

¹Brooke J. SUS-A quick and dirty usability scale. Usability evaluation in industry 1996;189:194 

²Lewis JR, Sauro J: The factor structure of the system usability scale. In: Human Centered Design. Springer; 2009: 94-103.

The conference is for researchers in the field of indigenous knowledge; and it is about presenting research studies on African indigenous knowledge. The conference is taking place at the University of the Witwatersrand, in Johannesburg from October 25th - 28th, 2017.

You save costs by becoming a member of the African Association for the Study of Indigenous Knowledge Systems (AASIKS) and by registering early for the conference.

You can also donate generously to the Association so that the organization can provide financial assistance to post-graduate students in the field to be able to present their work. 

The DVUSD Continuous Improvement Journey is one of alignment and integration. Beginning with the Strategic Plan and guided by the Baldrige Framework, the district and schools draft Organizational Profiles that highlight details such as student-centered processes, programs, and information regarding our skilled workforce. The Organizational Profile also hosts the mission and vision statements, as well as the core values that define the DVUSD community. To ensure that continuous improvement is at the forefront of all decisions, Deer Valley seeks out feedback from external organizations that can lead to action. In our quest for effective and efficient process improvements, in which students receive the optimal education, Deer Valley employs the AdvancED protocols to maintain district-wide accreditation.

Deer Valley's Strategic Plan is the framework to focus and align our work through 2018. Thus, the entire Deer Valley organization will be positioned to ensure we are fulfilling the mission and achieving the vision of graduating life-long learners to successfully compete, lead, and positively impact the world.

Throughout the 2016-2017 school year, DVUSD will be gathering input from all stakeholders in support of refining our core values and strategic plan. We will examine ways to refine, refocus, and recommit to our district’s key strategic objectives. Continuous improvement is a journey, not an event. Deer Valley supports all employees in the implementation of continuous improvement principles aligned to the Strategic Plan. These principles are embedded throughout the organization through a variety of supports, including quarterly feedback for improvement plans. These CI efforts have been included within our historical story, Our Journey, in which our core values and priorities are portrayed.  Our Journey to Extraordinary. 

Dear Anders,

Good Morning,

Thank you for your knowledge sharing. I am looking to create a questionnaire on this topic mainly on radiation protection practices, procedure, dose limits and national and international standards with correlating Nepal situation. Hope if you have time you may also provide a resourceful idea to me also.

Thank You

May see the web link, if useful..

Hi Hans-Peter,

HIMMS has a very useful 7-stage model to measure hospital EHR implementations in the USA and also in Europe. Hospitals at stages 6 and 7 have implemented fully integrated EHRs. This is a vendor neutral model, so it does not matter which combination of software products are used, and in most hospitals there are a wide variety in use.

The link for the European hospitals is:

And the link for the latest list of hospitals in Europe at the stage 6/7 is below (there are about 50, most at stage 6).

Hope that helps.

I agree, thank you Christopher. Thank you!

Pat

The customers have unique personally identifiable information (PII) represented in biometric datasets. The PII entails privacy, trust, and security at all times. Cybercriminals seek PII for ransomware and illegal financial gains. To secure-biometric information is to employ secure server for effective authentications of transactions. Stolen biometric datasets could be used for impersonation to evade safeguards. Therefore, measures such as use of datasets for intended purposes only, destruction upon completion, access by trusted personnel only, closely supervised settings, extended access control, safeguarding the private key, and strong passwords (ePassports contents),

Attached is a sideward related article that I wrote some years ago, when IEC 62366 was new. I am a member of several IEC TC62D workgroups on medical devices standards, and the past 30 years learned me that human factors are by far dominant when it comes to incidents with medical devices. Hope you like the article...

Hi Ashwini, can you please explain your question:

MRSA means Methicillin-Resistant Staphylococcus Aureus.

MRSA is a bacteria. Are you talking about bacteriophages that attack Staph. Aureus?  

One mechanism could be "capping":

check this:

I recommend https://opendatakit.org if you plan to collect information.

Hello Negin Zarbakhsh 

please check the resources

Not sure if it's exactly what you're looking for, but the eHealth Observatory model provides sequential assessments comparing eHealth system promises with what's delivered:

There's also a group staring up in Canada:

Electronic Medical records are sensitive pieces of information that requires extensive and strong protection. Taking an example of a bankrupt hospital may put some light on the matter. A cancer hospital dealing with all stages of cancer patients filed for bankrupcy and was taken over by a loan lending bank. After the take over was complete, the bank officials scrutinized all such patient details who were in their last stages of cancer, had extremely less chances of survival and had pending loans with the same bank. The loan accounts for these patients was closed and the loan amounts forfeited. As a solution, one could use steganographic protocols to hide patient medical records (which are primarily text) within medical report images. In this case, only an authorized doctor or medical personnel may have access to the records. To all others, the existence of the records remains concealed.

Hope this helps a bit

To improve accuracy :

I think that is dependent for the dataset  and labeling,also you can use some classification algorithm in supervised machine learning.

To improve performance :

you need to re implement your algorithm in HPC computing using multiprocessing or using GPU language like : Open cl or CUDA . 

AMIA annual Symposium - each November - this year in Chicago Nov 12-16

Please see below for my previous discussion on this: 

Dear Editor,

We read with interest the article by Gibbs and Gibbs on the misuse of the word trend to describe ‘almost’ significant p values [1]. However, we believe this discussion of semantics is clouding a somewhat greater issue in the reporting of statistics in the scientific literature. As Gibbs and Gibbs noted, p values are inferential statistics that give the probability of obtaining a value the same or greater than that found if the null hypothesis was true. However, we argue that p values are outdated and for clinical studies in particular, their use should be avoided. This is not a new concept, however, we hope this letter will serve to remind the readership of the flaws in null hypothesis statistical testing. We will first highlight the problems related with the [mis]use of p values, and then discuss the advantages of estimation-based methods, illustrating this with a theoretical example.

Firstly, the use of p values can often detract from a more important issue when conducting a clinical study, the assessment of clinical significance. The misinterpretation of p values means that readers may mistake ‘statistical significance’ as ‘clinical significance’. As the calculation of p values is heavily dependent on sample size, large studies may demonstrate very small p values that are not clinically significant. In fact, such small p values may in fact be evidence against the use of a particular treatment, as it can make us more confident that a treatment will not have a clinically significant effect (see later example). Secondly, the choice of a significance level of p<0.05 is arbitrary. Such a level may have originated from statistician Ronald Fisher who suggested this as a sensible cut-off, although he never advocated this as an absolute rule [2]. It is absurd to suggest a study that reports a p value of 0.04 is ‘positive’ and another that reports a p value of 0.06 is negative [3]. Such ‘negative’ p values promote fear in researchers and students while also rendering a study less likely to be published [4].

Ever since the end of the 1970’s, the use of confidence intervals (CI) was proposed as an alternative to p values [5]. Confidence intervals present a range of values with which the population mean is likely to lie. More specifically, a 95% confidence interval states that should the experiment be repeated 100 times, the mean of 95 of these experiments would fall within this interval [6]. Such an approach is advocated by the International Committee of Medical Journal Editors who state ‘When possible, quantify findings and present them with appropriate indicators of measurement error or uncertainty (such as confidence intervals). Avoid relying solely on statistical hypothesis testing, such as P values, which fail to convey important information about effect size and precision of estimates’.

Confidence intervals contain a wealth of information as well as including all the information of a traditional p value. If the extreme limit of the confidence interval traverses the null result, then the p value is >0.05 (if 95% CI are used) [7]. Moreover, confidence intervals can be better used to assess the likelihood an intervention has a clinically significant effect. Consider an example, we wish to know the efficacy of two different analgesic agents (x and y) for treating postoperative pain. We undertake two randomised controlled trials (RCT) with both agents and pre-determine a clinically significant reduction in pain as 15mm (on a 100mm VAS) [8]. The first RCT with agent x enrols a large number of participants and demonstrates a mean difference of -5mm (95% CI -3mm to -7mm; p<0.001). The second study with agent y recruits much fewer participants and demonstrates a mean difference of -12mm (95% CI 0.1mm to -24.1mm; p=0.06). Although the p value of the first study is very low, the results indicate that we can be confident this agent does not produce a clinically significant effect and should therefore not be used. The second study, although not statistically significant, does not exclude a clinically significant effect and requires more studies to be conducted in order to increase power and narrow the confidence interval. If we had relied solely on statistical significance, widely different and erroneous conclusions would be made.

We accept that this argument is not new and we applaud the British Journal of Anaesthesia for promoting confidence intervals in their instructions for authors page. However, we feel that this letter should serve as a reminder to the readership both the flaws of p values and the advantages of confidence intervals. We hope this will also encourage authors to report confidence intervals wherever possible.

References

[1] Gibbs NM, Gibbs SV. Misuse of ‘trend’ to describe ‘almost significant’ differences in anaesthesia research. British Journal of Anaesthesia 2015: aev149.

[2] Sterne JA, Smith GD. Sifting the evidence—what's wrong with significance tests? Physical Therapy 2001; 81: 1464-1469.

[3] Rosnow RL, Rosenthal R. Statistical procedures and the justification of knowledge in psychological science. American Psychologist 1989; 44: 1276.

[4] Stern JM, Simes RJ. Publication bias: evidence of delayed publication in a cohort study of clinical research projects. British Medical Journal 1997; 315: 640-645.

[5] Rothman K. A show of confidence. New England Journal of Medicine 1978; 299: 1362-3.

[6] Gardner MJ, Altman DG. Confidence intervals rather than P values: estimation rather than hypothesis testing. British Medical Journal 1986; 292: 746-750.

[7] Cohen J. The earth is round (p < .05). American Psychologist 1994; 49: 997-1003, p. 997.

[8] Gallagher EJ, Liebman M, Bijur PE. Prospective validation of clinically important changes in pain severity measured on a visual analog scale. Annals of Emergency Medicine 2001; 38: 633–638.

Please, read the follow  similar articles for your research: 

MOBILE DEVICE MANAGEMENT FOR PERSONALLY CONTROLLED ELECTRONIC HEALTH RECORDS: EFFECTIVE SELECTION OF EVALUATION CRITERIA

http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1004&context=aeis 

An Enhanced Mobile-Healthcare Emergency System Based on Extended Chaotic Maps

http://dl.acm.org/citation.cfm?id=2559032 

Doctors and mHealth apps: chaos, evidence, creation

Making sense of apparent chaos: health-care provision in six country case studies

file:///C:/Users/gkol/Downloads/irrc-889-pavignani-michael-murru-beesley-hill.pdf 

Can you give me an idea about OSIM2? and for what purposes you use it?

I'm from Kenya and I have never heard about them.

Dear Sobechukwu

I don't really see the necessity to use a 'fetal' approach fro adults, particularly not, since a lot of work is available in this regardd.

Have you gone through the references and those mentioned as 'external links' on this issue in the Wikipedia article?:

That should give you ample of good quality papers and sites to look at.

Or, is this a misunderstanding and you are looking for something different here? May be, I am not understanding where you are heading to...... (?)

good luck!

Sibylel

See attached document

The MIT has just released a new version of their anonymised open access Intensive Care database: MIMIC-3. I have worked with version 2, and I can confirm the high quality of the data. Many incredible papers have been produced from MIMIC. The version 3 now contains nearly 60,000 ICU admissions, and the data structure has been simplified. Highly recommended! 

Well, probably that related directly whether the system can map to various terminology systems relating to the diagnostics (SNOMED CT, LOINC). Actually anything utilizing UMLS (http://www.nlm.nih.gov/research/umls/) might be good.

More info:

It seems you are asking for something like the Beck Depression Inventory (BDI), which comprises 21 items with 4 factors: cognitive, affective, motivational, and somatic

Try the below link for more information,:

The dataset can be treated as a classification problem (2 classes exactly) in this case if the patient is sick or is healthy(in case of people use as control case).

Perhaps have a look at Elske Ammenwerth's publications.

That is simply not true, Bradford. I agree that LCModel has its merits, and it performs well in most situations that a clinical researcher will usually come across. But its "black box approach" has ups *and* downs.

LCModel is easy to handle and normally gets you robust results. But it does not let you look under the hood. In critical situations, it is still just as good as the model you feed it with. The results may often seem temptingly straightforward where their interpretation should even be given extra care. See this article (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0084081): LCModel was seemingly capable of detecting dopamine (!) from 3T spectra with a self-simulated basis set. That's quite a claim, and without verification from a phantom or further simulations this may as well be a fitting artefact by LCModel. 

I am not saying LCModel is not a good tool, it definitely is (and that's why it has its price)! LCModel just needs someone who understands what it is doing. Tools like jMRUI require more interaction and expertise. But usually they don't write cheques they can't cash.

Apart from the Requirements mentioned by Dominic M. Mezzanotte, Sr.

Bharath Muthukumar, Abdelrahman Osman Elfak, Jeffrey Wallk

Try reading these articles:

Royce, W. W. (1970, August). Managing the development of large software systems. In proceedings of IEEE WESCON (Vol. 26, No. 8).

Zmud, R. W. (1980). Management of large software development efforts. MIS quarterly, 45-55.

Messerschmitt, D. G. (2004). Marketplace issues in software planning and design. Software, IEEE, 21(3), 62-70.

This is an interesting conversation about health literacy. I personally feel much of the responsibility for educating patients falls on the health care providers. There are many excellent tools to raise awareness of the issues and I though I would share a few here. Pfizer, the pharmaceutical company, has been a huge advocate for Clear Health Communication for years and I applaud their efforts. They have a new tool, A Health Literacy Assessment Tool for Patient Care and Research called the Newest Vital Sign (NVS) available in English & Spanish. It helps providers assess what the patient knows, and then using some of their clear health communication skills (in the link provided) we as health professionals can work to better communicate and get feedback on what the patient understands about their illness and any treatment options we are recommending.

The American Medical Association has a really powerful video on health literacy in America. Watch it to really see what we are missing by not looking for health literacy, it's been around for a while, but wow. (Every time I watch it I am moved by the impact of health literacy on patients.) We should never assume anything, plain language is important and it is not the patient's responsibility to tell us they "don't get it", because they will not. Providers need to think about this issue and I am glad it is being discussed here. There are great resources out there.

I would focus on preventing patient injury, not physician errors. 

Analogy: 

Seat belts do not prevent driver errors. 

Smoke detectors do not prevent people from playing with matches. 

Both prevent injuries, not errors. 

The hyperfocus on human errors by physicians or other personnel has not worked. 

There are many things we can do to prevent patient injury that have nothing to do with physician errors. We are not doing them because we think of preventing physician errors as the end all and be all of the subject matter.