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Can Blockchain Technology and Artificial Intelligence Cure What Ails Biomedical Research and Healthcare

Curator: Stephen J. Williams, Ph.D.

Updated 12/18/2018

In the efforts to reduce healthcare costs, provide increased accessibility of service for patients, and drive biomedical innovations, many healthcare and biotechnology professionals have looked to advances in digital technology to determine the utility of IT to drive and extract greater value from healthcare industry.  Two areas of recent interest have focused how best to use blockchain and artificial intelligence technologies to drive greater efficiencies in our healthcare and biotechnology industries.

More importantly, with the substantial increase in ‘omic data generated both in research as well as in the clinical setting, it has become imperative to develop ways to securely store and disseminate the massive amounts of ‘omic data to various relevant parties (researchers or clinicians), in an efficient manner yet to protect personal privacy and adhere to international regulations.  This is where blockchain technologies may play an important role.

A recent Oncotarget paper by Mamoshina et al. (1) discussed the possibility that next-generation artificial intelligence and blockchain technologies could synergize to accelerate biomedical research and enable patients new tools to control and profit from their personal healthcare data, and assist patients with their healthcare monitoring needs. According to the abstract:

The authors introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship value of the data.  They also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare.  In this system, blockchain and deep learning technologies would provide the secure and transparent distribution of personal data in a healthcare marketplace, and would also be useful to resolve challenges faced by the regulators and return control over personal data including medical records to the individual.

The review discusses:

  1. Recent achievements in next-generation artificial intelligence
  2. Basic concepts of highly distributed storage systems (HDSS) as a preferred method for medical data storage
  3. Open source blockchain Exonium and its application for healthcare marketplace
  4. A blockchain-based platform allowing patients to have control of their data and manage access
  5. How advances in deep learning can improve data quality, especially in an era of big data

Advances in Artificial Intelligence

  • Integrative analysis of the vast amount of health-associated data from a multitude of large scale global projects has proven to be highly problematic (REF 27), as high quality biomedical data is highly complex and of a heterogeneous nature, which necessitates special preprocessing and analysis.
  • Increased computing processing power and algorithm advances have led to significant advances in machine learning, especially machine learning involving Deep Neural Networks (DNNs), which are able to capture high-level dependencies in healthcare data. Some examples of the uses of DNNs are:
  1. Prediction of drug properties(2, 3) and toxicities(4)
  2. Biomarker development (5)
  3. Cancer diagnosis (6)
  4. First FDA approved system based on deep learning Arterys Cardio DL
  • Other promising systems of deep learning include:
    • Generative Adversarial Networks (https://arxiv.org/abs/1406.2661): requires good datasets for extensive training but has been used to determine tumor growth inhibition capabilities of various molecules (7)
    • Recurrent neural Networks (RNN): Originally made for sequence analysis, RNN has proved useful in analyzing text and time-series data, and thus would be very useful for electronic record analysis. Has also been useful in predicting blood glucose levels of Type I diabetic patients using data obtained from continuous glucose monitoring devices (8)
    • Transfer Learning: focused on translating information learned on one domain or larger dataset to another, smaller domain. Meant to reduce the dependence on large training datasets that RNN, GAN, and DNN require.  Biomedical imaging datasets are an example of use of transfer learning.
    • One and Zero-Shot Learning: retains ability to work with restricted datasets like transfer learning. One shot learning aimed to recognize new data points based on a few examples from the training set while zero-shot learning aims to recognize new object without seeing the examples of those instances within the training set.

Highly Distributed Storage Systems (HDSS)

The explosion in data generation has necessitated the development of better systems for data storage and handling. HDSS systems need to be reliable, accessible, scalable, and affordable.  This involves storing data in different nodes and the data stored in these nodes are replicated which makes access rapid. However data consistency and affordability are big challenges.

Blockchain is a distributed database used to maintain a growing list of records, in which records are divided into blocks, locked together by a crytosecurity algorithm(s) to maintain consistency of data.  Each record in the block contains a timestamp and a link to the previous block in the chain.  Blockchain is a distributed ledger of blocks meaning it is owned and shared and accessible to everyone.  This allows a verifiable, secure, and consistent history of a record of events.

Data Privacy and Regulatory Issues

The establishment of the Health Insurance Portability and Accountability Act (HIPAA) in 1996 has provided much needed regulatory guidance and framework for clinicians and all concerned parties within the healthcare and health data chain.  The HIPAA act has already provided much needed guidance for the latest technologies impacting healthcare, most notably the use of social media and mobile communications (discussed in this article  Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.).  The advent of blockchain technology in healthcare offers its own unique challenges however HIPAA offers a basis for developing a regulatory framework in this regard.  The special standards regarding electronic data transfer are explained in HIPAA’s Privacy Rule, which regulates how certain entities (covered entities) use and disclose individual identifiable health information (Protected Health Information PHI), and protects the transfer of such information over any medium or electronic data format. However, some of the benefits of blockchain which may revolutionize the healthcare system may be in direct contradiction with HIPAA rules as outlined below:

Issues of Privacy Specific In Use of Blockchain to Distribute Health Data

  • Blockchain was designed as a distributed database, maintained by multiple independent parties, and decentralized
  • Linkage timestamping; although useful in time dependent data, proof that third parties have not been in the process would have to be established including accountability measures
  • Blockchain uses a consensus algorithm even though end users may have their own privacy key
  • Applied cryptography measures and routines are used to decentralize authentication (publicly available)
  • Blockchain users are divided into three main categories: 1) maintainers of blockchain infrastructure, 2) external auditors who store a replica of the blockchain 3) end users or clients and may have access to a relatively small portion of a blockchain but their software may use cryptographic proofs to verify authenticity of data.

 

YouTube video on How #Blockchain Will Transform Healthcare in 25 Years (please click below)

 

 

In Big Data for Better Outcomes, BigData@Heart, DO->IT, EHDN, the EU data Consortia, and yes, even concepts like pay for performance, Richard Bergström has had a hand in their creation. The former Director General of EFPIA, and now the head of health both at SICPA and their joint venture blockchain company Guardtime, Richard is always ahead of the curve. In fact, he’s usually the one who makes the curve in the first place.

 

 

 

Please click on the following link for a podcast on Big Data, Blockchain and Pharma/Healthcare by Richard Bergström:

References

  1. Mamoshina, P., Ojomoko, L., Yanovich, Y., Ostrovski, A., Botezatu, A., Prikhodko, P., Izumchenko, E., Aliper, A., Romantsov, K., Zhebrak, A., Ogu, I. O., and Zhavoronkov, A. (2018) Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare, Oncotarget 9, 5665-5690.
  2. Aliper, A., Plis, S., Artemov, A., Ulloa, A., Mamoshina, P., and Zhavoronkov, A. (2016) Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data, Molecular pharmaceutics 13, 2524-2530.
  3. Wen, M., Zhang, Z., Niu, S., Sha, H., Yang, R., Yun, Y., and Lu, H. (2017) Deep-Learning-Based Drug-Target Interaction Prediction, Journal of proteome research 16, 1401-1409.
  4. Gao, M., Igata, H., Takeuchi, A., Sato, K., and Ikegaya, Y. (2017) Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds, Journal of pharmacological sciences 133, 70-78.
  5. Putin, E., Mamoshina, P., Aliper, A., Korzinkin, M., Moskalev, A., Kolosov, A., Ostrovskiy, A., Cantor, C., Vijg, J., and Zhavoronkov, A. (2016) Deep biomarkers of human aging: Application of deep neural networks to biomarker development, Aging 8, 1021-1033.
  6. Vandenberghe, M. E., Scott, M. L., Scorer, P. W., Soderberg, M., Balcerzak, D., and Barker, C. (2017) Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer, Scientific reports 7, 45938.
  7. Kadurin, A., Nikolenko, S., Khrabrov, K., Aliper, A., and Zhavoronkov, A. (2017) druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico, Molecular pharmaceutics 14, 3098-3104.
  8. Ordonez, F. J., and Roggen, D. (2016) Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition, Sensors (Basel) 16.

Articles from clinicalinformaticsnews.com

Healthcare Organizations Form Synaptic Health Alliance, Explore Blockchain’s Impact On Data Quality

From http://www.clinicalinformaticsnews.com/2018/12/05/healthcare-organizations-form-synaptic-health-alliance-explore-blockchains-impact-on-data-quality.aspx

By Benjamin Ross

December 5, 2018 | The boom of blockchain and distributed ledger technologies have inspired healthcare organizations to test the capabilities of their data. Quest Diagnostics, in partnership with Humana, MultiPlan, and UnitedHealth Group’s Optum and UnitedHealthcare, have launched a pilot program that applies blockchain technology to improve data quality and reduce administrative costs associated with changes to healthcare provider demographic data.

The collective body, called Synaptic Health Alliance, explores how blockchain can keep only the most current healthcare provider information available in health plan provider directories. The alliance plans to share their progress in the first half of 2019.

Providing consumers looking for care with accurate information when they need it is essential to a high-functioning overall healthcare system, Jason O’Meara, Senior Director of Architecture at Quest Diagnostics, told Clinical Informatics News in an email interview.

“We were intentional about calling ourselves an alliance as it speaks to the shared interest in improving health care through better, collaborative use of an innovative technology,” O’Meara wrote. “Our large collective dataset and national footprints enable us to prove the value of data sharing across company lines, which has been limited in healthcare to date.”

O’Meara said Quest Diagnostics has been investing time and resources the past year or two in understanding blockchain, its ability to drive purpose within the healthcare industry, and how to leverage it for business value.

“Many health care and life science organizations have cast an eye toward blockchain’s potential to inform their digital strategies,” O’Meara said. “We recognize it takes time to learn how to leverage a new technology. We started exploring the technology in early 2017, but we quickly recognized the technology’s value is in its application to business to business use cases: to help transparently share information, automate mutually-beneficial processes and audit interactions.”

Quest began discussing the potential for an alliance with the four other companies a year ago, O’Meara said. Each company shared traits that would allow them to prove the value of data sharing across company lines.

“While we have different perspectives, each member has deep expertise in healthcare technology, a collaborative culture, and desire to continuously improve the patient/customer experience,” said O’Meara. “We also recognize the value of technology in driving efficiencies and quality.”

Following its initial launch in April, Synaptic Health Alliance is deploying a multi-company, multi-site, permissioned blockchain. According to a whitepaper published by Synaptic Health, the choice to use a permissioned blockchain rather than an anonymous one is crucial to the alliance’s success.

“This is a more effective approach, consistent with enterprise blockchains,” an alliance representative wrote. “Each Alliance member has the flexibility to deploy its nodes based on its enterprise requirements. Some members have elected to deploy their nodes within their own data centers, while others are using secured public cloud services such as AWS and Azure. This level of flexibility is key to growing the Alliance blockchain network.”

As the pilot moves forward, O’Meara says the Alliance plans to open ability to other organizations. Earlier this week Aetna and Ascension announced they joined the project.

“I am personally excited by the amount of cross-company collaboration facilitated by this project,” O’Meara says. “We have already learned so much from each other and are using that knowledge to really move the needle on improving healthcare.”

 

US Health And Human Services Looks To Blockchain To Manage Unstructured Data

http://www.clinicalinformaticsnews.com/2018/11/29/us-health-and-human-services-looks-to-blockchain-to-manage-unstructured-data.aspx

By Benjamin Ross

November 29, 2018 | The US Department of Health and Human Services (HHS) is making waves in the blockchain space. The agency’s Division of Acquisition (DA) has developed a new system, called Accelerate, which gives acquisition teams detailed information on pricing, terms, and conditions across HHS in real-time. The department’s Associate Deputy Assistant Secretary for Acquisition, Jose Arrieta, gave a presentation and live demo of the blockchain-enabled system at the Distributed: Health event earlier this month in Nashville, Tennessee.

Accelerate is still in the prototype phase, Arrieta said, with hopes that the new system will be deployed at the end of the fiscal year.

HHS spends around $25 billion a year in contracts, Arrieta said. That’s 100,000 contracts a year with over one million pages of unstructured data managed through 45 different systems. Arrieta and his team wanted to modernize the system.

“But if you’re going to change the way a workforce of 20,000 people do business, you have to think your way through how you’re going to do that,” said Arrieta. “We didn’t disrupt the existing systems: we cannibalized them.”

The cannibalization process resulted in Accelerate. According to Arrieta, the system functions by creating a record of data rather than storing it, leveraging machine learning, artificial intelligence (AI), and robotic process automation (RPA), all through blockchain data.

“We’re using that data record as a mechanism to redesign the way we deliver services through micro-services strategies,” Arrieta said. “Why is that important? Because if you have a single application or data use that interfaces with 55 other applications in your business network, it becomes very expensive to make changes to one of the 55 applications.”

Accelerate distributes the data to the workforce, making it available to them one business process at a time.

“We’re building those business processes without disrupting the existing systems,” said Arrieta, and that’s key. “We’re not shutting off those systems. We’re using human-centered design sessions to rebuild value exchange off of that data.”

The first application for the system, Arrieta said, can be compared to department stores price-matching their online competitors.

It takes the HHS close to a month to collect the amalgamation of data from existing system, whether that be terms and conditions that drive certain price points, or software licenses.

“The micro-service we built actually analyzes that data, and provides that information to you within one second,” said Arrieta. “This is distributed to the workforce, to the 5,000 people that do the contracting, to the 15,000 people that actually run the programs at [HHS].”

This simple micro-service is replicated on every node related to HHS’s internal workforce. If somebody wants to change the algorithm to fit their needs, they can do that in a distributed manner.

Arrieta hopes to use Accelerate to save researchers money at the point of purchase. The program uses blockchain to simplify the process of acquisition.

“How many of you work with the federal government?” Arrieta asked the audience. “Do you get sick of reentering the same information over and over again? Every single business opportunity you apply for, you have to resubmit your financial information. You constantly have to check for validation and verification, constantly have to resubmit capabilities.”

Wouldn’t it be better to have historical notes available for each transaction? said Arrieta. This would allow clinical researchers to be able to focus on “the things they’re really good at,” instead of red tape.

“If we had the top cancer researcher in the world, would you really want her spending her time learning about federal regulations as to how to spend money, or do you want her trying to solve cancer?” Arrieta said. “What we’re doing is providing that data to the individual in a distributed manner so they can read the information of historical purchases that support activity, and they can focus on the objectives and risks they see as it relates to their programming and their objectives.”

Blockchain also creates transparency among researchers, Arrieta said, which says creates an “uncomfortable reality” in the fact that they have to make a decision regarding data, fundamentally changing value exchange.

“The beauty of our business model is internal investment,” Arrieta said. For instance, the HHS could take all the sepsis data that exists in their system, put it into a distributed ledger, and share it with an external source.

“Maybe that could fuel partnership,” Arrieta said. “I can make data available to researchers in the field in real-time so they can actually test their hypothesis, test their intuition, and test their imagination as it relates to solving real-world problems.”

 

Shivom is creating a genomic data hub to elongate human life with AI

From VentureBeat.com
Blockchain-based genomic data hub platform Shivom recently reached its $35 million hard cap within 15 seconds of opening its main token sale. Shivom received funding from a number of crypto VC funds, including Collinstar, Lateral, and Ironside.

The goal is to create the world’s largest store of genomic data while offering an open web marketplace for patients, data donors, and providers — such as pharmaceutical companies, research organizations, governments, patient-support groups, and insurance companies.

“Disrupting the whole of the health care system as we know it has to be the most exciting use of such large DNA datasets,” Shivom CEO Henry Ines told me. “We’ll be able to stratify patients for better clinical trials, which will help to advance research in precision medicine. This means we will have the ability to make a specific drug for a specific patient based on their DNA markers. And what with the cost of DNA sequencing getting cheaper by the minute, we’ll also be able to sequence individuals sooner, so young children or even newborn babies could be sequenced from birth and treated right away.”

While there are many solutions examining DNA data to explain heritage, intellectual capabilities, health, and fitness, the potential of genomic data has largely yet to be unlocked. A few companies hold the monopoly on genomic data and make sizeable profits from selling it to third parties, usually without sharing the earnings with the data donor. Donors are also not informed if and when their information is shared, nor do they have any guarantee that their data is secure from hackers.

Shivom wants to change that by creating a decentralized platform that will break these monopolies, democratizing the processes of sharing and utilizing the data.

“Overall, large DNA datasets will have the potential to aid in the understanding, prevention, diagnosis, and treatment of every disease known to mankind, and could create a future where no diseases exist, or those that do can be cured very easily and quickly,” Ines said. “Imagine that, a world where people do not get sick or are already aware of what future diseases they could fall prey to and so can easily prevent them.”

Shivom’s use of blockchain technology and smart contracts ensures that all genomic data shared on the platform will remain anonymous and secure, while its OmiX token incentivizes users to share their data for monetary gain.

Rise in Population Genomics: Local Government in India Will Use Blockchain to Secure Genetic Data

Blockchain will secure the DNA database for 50 million citizens in the eighth-largest state in India. The government of Andhra Pradesh signed a Memorandum of Understanding with a German genomics and precision medicine start-up, Shivom, which announced to start the pilot project soon. The move falls in line with a trend for governments turning to population genomics, and at the same time securing the sensitive data through blockchain.

Andhra Pradesh, DNA, and blockchain

Storing sensitive genetic information safely and securely is a big challenge. Shivom builds a genomic data-hub powered by blockchain technology. It aims to connect researchers with DNA data donors thus facilitating medical research and the healthcare industry.

With regards to Andhra Pradesh, the start-up will first launch a trial to determine the viability of their technology for moving from a proactive to a preventive approach in medicine, and towards precision health. “Our partnership with Shivom explores the possibilities of providing an efficient way of diagnostic services to patients of Andhra Pradesh by maintaining the privacy of the individual data through blockchain technologies,” said J A Chowdary, IT Advisor to Chief Minister, Government of Andhra Pradesh.

Other Articles in this Open Access Journal on Digital Health include:

Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.

Medical Applications and FDA regulation of Sensor-enabled Mobile Devices: Apple and the Digital Health Devices Market

 

How Social Media, Mobile Are Playing a Bigger Part in Healthcare

 

E-Medical Records Get A Mobile, Open-Sourced Overhaul By White House Health Design Challenge Winners

 

Medcity Converge 2018 Philadelphia: Live Coverage @pharma_BI

 

Digital Health Breakthrough Business Models, June 5, 2018 @BIOConvention, Boston, BCEC

 

 

 

 

 

 

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Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Reporter: Stephen J. Williams, PhD

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Speakers:
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

What is working and what needs to change in pricing models?

Robert:  He sees so many players in the onStevencology space discovering new drugs and other drugs are going generic (that is what is working).  However are we spending too much on cancer care relative to other diseases (their initiative Going Beyond the Surface)

Steven:  the advent of biosimilars is good for the industry

Patrick:  large effort in oncology, maybe too much (750 trials on Keytruda) and he says pharma is spending on R&D (however clinical trials take large chunk of this money)

Robert: cancer has gotten a free ride but cost per year relative to benefit looks different than other diseases.  Are we overinvesting in cancer or is that a societal decision

Gary:  maybe as we become more specific with precision medicines high prices may be a result of our success in specifically targeting a mutation.  We need to understand the targeted drugs and outcomes.

Patrick: “Cancer is the last big frontier” but he says prices will come down in most cases.  He gives the example of Hep C treatment… the previous only therapeutic option was a very toxic yearlong treatment but the newer drugs may be more cost effective and safer

Steven: Our blockbuster drugs could diffuse the expense but now with precision we can’t diffuse the expense over a large number of patients

President’s Cancer Panel Recommendation

Six recommendations

  1. promoting value based pricing
  2. enabling communications of cost
  3. financial toxicity
  4. stimulate competition biosimilars
  5. value based care
  6. invest in biomedical research

Patrick: the government pricing regime is hurting.  Alot of practical barriers but Merck has over 200 studies on cost basis

Robert:  many concerns/impetus started in Europe on pricing as they are a set price model (EU won’t pay more than x for a drug). US is moving more to outcomes pricing. For every one health outcome study three studies did not show a benefit.  With cancer it is tricky to establish specific health outcomes.  Also Medicare gets best price status so needs to be a safe harbor for payers and biggest constraint is regulatory issues.

Steven: They all want value based pricing but we don’t have that yet and there is a challenge to understand the nuances of new therapies.  Hard to align all the stakeholders together so until some legislation starts to change the reimbursement-clinic-patient-pharma obstacles.  Possibly the big data efforts discussed here may help align each stakeholders goals.

Gary: What is the data necessary to understand what is happening to patients and until we have that information it still will be complicated to determine where investors in health care stand at in this discussion

Robert: on an ICER methods advisory board: 1) great concern of costs how do we determine fair value of drug 2) ICER is only game in town, other orgs only give recommendations 3) ICER evaluates long term value (cost per quality year of life), budget impact (will people go bankrupt)

4) ICER getting traction in the public eye and advocates 5) the problem is ICER not ready for prime time as evidence keeps changing or are they keeping the societal factors in mind and they don’t have total transparancy in their methodology

Steven: We need more transparency into all the costs associated with the drug and therapy and value-based outcome.  Right now price is more of a black box.

Moderator: pointed to a recent study which showed that outpatient costs are going down while hospital based care cost is going rapidly up (cost of site of care) so we need to figure out how to get people into lower cost setting

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Speakers:
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

Seqster: Seqster is a secure platform that helps you and your family manage medical records, DNA, fitness, and nutrition data—all in one place. Founder has a genomic sequencing background but realized sequence  information needs to be linked with medical records.

HealthShareExchange.org :

HealthShare Exchange envisions a trusted community of healthcare stakeholders collaborating to deliver better care to consumers in the greater Philadelphia region. HealthShare Exchange will provide secure access to health information to enable preventive and cost-effective care; improve quality of patient care; and facilitate care transitions. They have partnered with multiple players in healthcare field and have data on over 7 million patients.

Innovacer

Data can be overwhelming, but it doesn’t have to be this way. To drive healthcare efficiency, we designed a modular suite of products for a smooth transition into a data-driven world within 4 weeks. Why does it take so much money to move data around and so slowly?

What is interoperatibility?

Ardy: We knew in genomics field how to build algorithms to analyze big data but how do we expand this from a consumer standpoint and see and share your data.

Lauren: how can we use the data between patients, doctors, researchers?  On the research side genomics represent only 2% of data.  Silos are one issue but figuring out the standards for data (collection, curation, analysis) is not set. Still need to improve semantic interoperability. For example Flatiron had good annotated data on male metastatic breast cancer.

David: Technical interopatabliltiy (platform), semantic interopatability (meaning or word usage), format (syntactic) interopatibility (data structure).  There is technical interoperatiblity between health system but some semantic but formats are all different (pharmacies use different systems and write different prescriptions using different suppliers).  In any value based contract this problem is a big issue now (we are going to pay you based on the quality of your performance then there is big need to coordinate across platforms).  We can solve it by bringing data in real time in one place and use mapping to integrate the format (need quality control) then need to make the data democratized among players.

Rakesh:  Patients data should follow the patient. Of Philadelphia’s 12 health systems we had a challenge to make data interoperatable among them so tdhey said to providers don’t use portals and made sure hospitals were sending standardized data. Health care data is complex.

David: 80% of clinical data is noise. For example most eMedical Records are text. Another problem is defining a patient identifier which US does not believe in.

 

 

 

 

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Medical Headline Misinformation Strikes Again: Claims About Vitamin D

Reporter: Stephen J. Williams, Ph.D.

A recent posting by a group called the Vitamin D Council (and put on this site) had referred to, and misquoted, the Mayo Clinic site on the role of vitamin D on various diseases. At first I was curious if this was actually reported on the Mayo site on claims of prevention of various cancers (as results from retrospective studies had been conflicting) and originally had made some strong comments. From comments made from this post I do agree that there is strong evidence about vitamin D supplementation for the prevention of rickets but as Mayo reviewed claims about vitamin D supplementation and prevention of certain diseases such as cancers and heart disease may not be as strong as some suggest.  My main concern was : is the clinical evidence strong enough for the role of vitamin D supplementation in a wide array of diseases and did Mayo make the claims as suggested in some media reports?  Actually Mayo does a very thorough job of determining the clinical evidence and the focus of vitamins and cancer risk will be a point of further discussion.

After consulting the Mayo clinic website it appears that the Vitamin D Council site had indeed misquoted and misrepresented the medical information contained within the Mayo Clinic website.

Medical Misinformation Is Probably The Most Hazardous and Biggest Risk Impacting a Healthy Lifestyle

The site had made numerous claims on role of vitamin D3 (cholecalciferol) in numerous diseases; making it appear there were definitive links between low vitamin D3 and risk of hypertension, cancer, depression and diabetes.

A little background on Vitamin D

From Wikipedia

Vitamin D refers to a group of fat-soluble secosteroids responsible for enhancing intestinal absorption of calcium, iron, magnesium, phosphate and zinc. In humans, the most important compounds in this group are vitamin D3 (also known as cholecalciferol) and vitamin D2 (ergocalciferol).[1] Cholecalciferol and ergocalciferol can be ingested from the diet and from supplements.[1][2][3] Very few foods contain vitamin D; synthesis of vitamin D (specifically cholecalciferol) in the skin is the major natural sources of the vitamin. Dermal synthesis of vitamin D from cholesterol is dependent on sun exposure (specifically UVB radiation).Vitamin D has a significant role in calcium homeostasis and metabolism. Its discovery was due to effort to find the dietary substance lacking in rickets (the childhood form of osteomalacia).[4]

also from Widipedia on Vitamin D toxicity

Vitamin D toxicity

Vitamin D toxicity is rare.[20] It is caused by supplementing with high doses of vitamin D rather than sunlight. The threshold for vitamin D toxicity has not been established; however, the tolerable upper intake level (UL), according to some research, is 4,000 IU/day for ages 9–71.[7] Whereas another research concludes that in healthy adults, sustained intake of more than 1250 μg/day (50,000 IU) can produce overt toxicity after several months and can increase serum 25-hydroxyvitamin D levels to 150 ng/ml and greater;[20][56] those with certain medical conditions, such as primary hyperparathyroidism,[57] are far more sensitive to vitamin D and develop hypercalcemia in response to any increase in vitamin D nutrition, while maternal hypercalcemia during pregnancy may increase fetal sensitivity to effects of vitamin D and lead to a syndrome of mental retardation and facial deformities.[57][58]

After being commissioned by the Canadian and American governments, the Institute of Medicine (IOM) as of 30 November 2010, has increased the tolerable upper limit (UL) to 2,500 IU per day for ages 1–3 years, 3,000 IU per day for ages 4–8 years and 4,000 IU per day for ages 9–71+ years (including pregnant or lactating women).[7]

Published cases of toxicity involving hypercalcemia in which the vitamin D dose and the 25-hydroxy-vitamin D levels are known all involve an intake of ≥40,000 IU (1,000 μg) per day.[57] Recommending supplementation, when those supposedly in need of it are labeled healthy, has proved contentious, and doubt exists concerning long-term effects of attaining and maintaining high serum 25(OH)D by supplementation.[61]

From the Mayo Clinic Website on Vitamin D

The Mayo Clinic has done a wonderful job curating the uses and proposed uses of vitamin D for various diseases and rates the evidence using a grading system A-F (as shown below):

Key to grades

A STRONG scientific evidence FOR THIS USE

B GOOD scientific evidence FOR THIS USE

C UNCLEAR scientific evidence for this use

D Fair scientific evidence AGAINST THIS USE (it may not work)

F Strong scientific evidence AGAINST THIS USE (it likely does not work)

Mayo has information for other natural products as well. As described below (and on the Mayo site here) most of the supposed evidence fails their criteria for a strong clinical link between diseases such as heart disease, hypertension, cancer and vitamin D (either parental or D3) levels.

The important take-home from the Mayo site is that there is strong evidence for the use of vitamin D in diseases related to the known mechanism of vitamin D such as low serum phosphate either due to kidney disease (Fanconi syndrome) or familial hypophosphatemia or in diseases surrounding bone metabolism like osteomalacia, rickets, dental cavities and even as a treatment for psoriasis or underactive parathyroid.

However most indications like hypertension, stroke, cancer prevention or treatment (other than supportive therapy for low vitamin D levels) get a poor grade (C or D) for clinical correlation from Mayo Clinic.

A Post in the Near Future will be a Curation of Validated Clinical Studies on Effects of Vitamins on Cancer Risk.

Below is taken from the Mayo Site:

Evidence

These uses have been tested in humans or animals.  Safety and effectiveness have not always been proven.  Some of these conditions are potentially serious, and should be evaluated by a qualified healthcare provider.

Grading rationale

Evidence grade Condition to which grade level applies
A

Deficiency (phosphate)

Familial hypophosphatemia is a rare, inherited condition in which there are low blood levels of phosphate and problems with vitamin D metabolism. It is a form of rickets. Taking calcitriol or dihydrotachysterol by mouth along with phosphate supplements is effective for treating bone disorders in people with this disease. Those with this disorder should be monitored by a medical professional.

A

Kidney disease (causing low phosphate levels)

Fanconi syndrome is a kidney disease in which nutrients, including phosphate, are lost in the urine instead of being reabsorbed by the body. Taking ergocalciferol by mouth is effective for treating low phosphate levels caused by Fanconi syndrome.

A

Osteomalacia (bone softening in adults)

Adults who have severe vitamin D deficiency may experience bone pain and softness, as well as muscle weakness. Osteomalacia may be found among the following people: those who are elderly and have diets low in vitamin D; those with problems absorbing vitamin D; those without enough sun exposure; those who undergo stomach or intestine surgery; those with bone disease caused by aluminum; those with chronic liver disease; or those with bone disease associated with kidney problems. Treatment for osteomalacia depends on the cause of the disease and often includes pain control and surgery, as well as vitamin D and phosphate-binding agents.

A

Psoriasis (disorder causing skin redness and irritation)

Many different approaches are used to treat psoriasis, including light therapy, stress reduction, moisturizers, or salicylic acid. For more severe cases, calcipotriene (Dovonex®), a man-made substance similar to vitamin D3, may help control skin cell growth. This agent is a first-line treatment for mild-to-moderate psoriasis. Calcipotriene is also available with betamethasone and may be safe for up to one year. Vitamin D3 (tacalcitol) ointment or high doses of becocalcidiol applied to the skin are also thought to be safe and well-tolerated.

A

Rickets (bone weakening in children)

Rickets may develop in children who have vitamin D deficiency caused by a diet low in vitamin D, a lack of sunlight, or both. Babies fed only breast milk (without supplemental vitamin D) may also develop rickets. Ergocalciferol or cholecalciferol is effective for treating rickets caused by vitamin D deficiency. Calcitriol should be used in those with kidney failure. Treatment should be under medical supervision.

A

Thyroid conditions (causing low calcium levels)

Low levels of parathyroid hormone may occur after surgery to remove the parathyroid glands. Taking high doses of dihydrotachysterol, calcitriol, or ergocalciferol by mouth, with or without calcium, may help increase calcium levels in people with this type of thyroid problem. Increasing calcium intake, with or without vitamin D, may reduce the risk of underactive parathyroid glands.

A

Thyroid conditions (due to low vitamin D levels)

Some people may have overactive parathyroid glands due to low levels of vitamin D, and vitamin D is the first treatment for this disorder. For people who have overactive parathyroid glands due to other causes, surgery to remove the glands is often recommended. Studies suggest that vitamin D may help reduce the risk of further thyroid problems after undergoing partial or total removal of the parathyroid glands.

A

Vitamin D deficiency

Vitamin D deficiency is associated with many conditions, including bone loss, kidney disease, lung disorders, diabetes, stomach and intestine problems, and heart disease. Vitamin D supplementation has been found to help prevent or treat vitamin D deficiency.

B

Dental cavities

Much evidence has shown that vitamin D helps prevent cavities; however, more high-quality research is needed to further support this finding.

B

Renal osteodystrophy (bone problems due to chronic kidney failure)

Renal osteodystrophy refers to the bone problems that occur in people with chronic kidney failure. Calcifediol or ergocalciferol taken by mouth may help prevent this condition in people with chronic kidney failure who are undergoing treatment.

C

Autoimmune diseases

Vitamin D may reduce inflammation and help prevent autoimmune diseases, including rheumatoid arthritis, multiple sclerosis, and Crohn’s disease. However, further high-quality research is needed to confirm these results.

C

Bone density (children)

Vitamin D improves bone density in children who are vitamin D deficient. However, results are unclear and more research is needed.

C

Bone diseases (kidney disease or kidney transplant)

Vitamin D has been studied for people with chronic kidney disease. The use of substances similar to vitamin D has been found to increase bone density in people with kidney disease. The effect of vitamin D itself is unclear. Further research is needed before conclusions can be made.

C

Cancer prevention (breast, colorectal, prostate, other)

Many studies have looked at the effects of vitamin D on cancer. Positive results have been reported with the use of vitamin D alone or with calcium. Vitamin D intake with or without calcium has been studied for colorectal, cervical, breast, and prostate cancer. A reduced risk of colorectal cancer has been shown with vitamin D supplementation. However, there is a lack of consistent or strong evidence. Further study is needed.

C

Fibromyalgia (long-term, body-wide pain)

Vitamin D has been studied for the treatment of fibromyalgia, but evidence is lacking in support of its effectiveness. Further study is needed.

C

Fractures (prevention)

Conflicting results have been found on the use of vitamin D for fracture prevention. The combination of alfacalcidol and alendronate has been found to reduce the risk of falls and fractures. However, further high-quality research is needed before firm conclusions can be made.

C

Hepatic osteodystrophy (bone disease in people with liver disease)

Metabolic bone disease is common among people with chronic liver disease, and osteoporosis accounts for the majority of cases. Varying degrees of poor calcium absorption may occur in people with chronic liver disease due to malnutrition and vitamin D deficiency. Vitamin D taken by mouth or injected may play a role in the management of this condition.

C

High blood pressure

Low levels of vitamin D may be linked to high blood pressure. Blood pressure is often higher during the winter season, at a further distance from the equator, and in people with dark skin pigmentation. However, the evidence is unclear. More research is needed in this area. People who have high blood pressure should be managed by a medical professional.

C

Immune function

Early research suggests that vitamin D and similar compounds, such as alfacalcidol, may impact immune function. Vitamin D added to standard therapy may benefit people with infectious disease. More studies are needed to confirm these results.

C

Seasonal affective disorder (SAD)

SAD is a form of depression that occurs during the winter months, possibly due to reduced exposure to sunlight. In one study, vitamin D was found to be better than light therapy in the treatment of SAD. Further studies are necessary to confirm these findings.

C

Stroke

Higher levels of vitamin D may decrease the risk of stroke. However, further study is needed to confirm the use of vitamin D for this condition.

C

Type 1 diabetes

Some studies suggest that vitamin D may help prevent the development of type 1 diabetes. However, there is a lack of strong evidence to support this finding.

C

Type 2 diabetes

Vitamin D has mixed effects on blood sugar and insulin sensitivity. It is often studied in combination with calcium. Further research is needed to confirm these results.

D

Cancer treatment (prostate)

Evidence suggests a lack of effect of vitamin D as a part of cancer treatment for prostate cancer. Further study is needed using other formulations of vitamin D and other types of cancer.

D

Heart disease

Vitamin D is recognized as being important for heart health. Overall, research is not consistent, and some studies have found negative effects of vitamin D on heart health. More high-quality research is needed to make a firm conclusion.

D

High cholesterol

Many studies have looked at the effects of vitamin D alone or in combination with other agents for high cholesterol, but results are inconsistent. Some negative effects have been reported. More research is needed on the use of vitamin D alone or in combination with calcium.

Other related articles on Vitamins and Disease were published in this Open Access Online Scientific Journal, include the following:

Multivitamins – Don’t help Extend Life or ward off Heart Disease and Improve state of Memory Loss

Diet and Diabetes

What do you know about Plants and Neutraceuticals?

Malnutrition in India, high newborn death rate and stunting of children age under five years

Omega-3 fatty acids, depleting the source, and protein insufficiency in renal disease

American Diet is LOW in four important Nutrients that have a direct bearing on Aging and the Brain

Parathyroids and Bone Metabolism

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