Computers in Biology and Medicine 59 (2015) 211–220
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Computers in Biology and Medicine journal homepage: www.elsevier.com/locate/cbm
An Indian eye to personalized medicine Shaurya Jauhari n, S.A.M. Rizvi Department of Computer Science, Jamia Millia Islamia, New Delhi, India
art ic l e i nf o
a b s t r a c t
Article history: Received 30 August 2013 Accepted 3 July 2014
Acknowledging the successful sequencing of the human genome and the valuable insights it has rendered, genetic drafting of non-human organisms can further enhance the understanding of modern biology. The price of sequencing technology has plummeted with time, and there is a noticeable enhancement in its implementation and recurrent usage. Sequenced genome information can be contained in a microarray chip, and then processed by a computer system for inferring analytics and predictions. Specifically, smart cards have been significantly applicable to assimilate and retrieve complex data, with ease and implicit mobility. Herein, we propose “The G-Card”, a development with respect to the prevalent smart card, and an extension to the Electronic Health Record (EHR), that will hold the genome sequence of an individual, so that the medical practitioner can better investigate irregularities in a patient's health and hence recommend a precise prognosis. & 2014 Elsevier Ltd. All rights reserved.
Keywords: G-Card Healthcare Human genome India Personalized medicine Smart card
1. Introduction Companies from private and cross-service platforms will be transacting in customized medicine and pharmacology. Personalized medicine per-se is an enormous challenge given the scope, complexity and usage-population. Also, named as precision medicine by few, personalized medicine is yet to see a long road to acceptance and proliferation [1]. But what is in store for a “developing” country like India. Well, there is already some buzz, but much will be uncovered with time and technology. Gupta et al. [2] have rendered an overview of how slow economy directly correlates to lack of early diagnosis and treatment. In the light of biomarker discovery, not only health know-how, but education, behavioral contexts, social ethics, all have a role to play.
2. Human Genome Project: conception to completion It would not be all appreciably acknowledged if a remark about the HGP is not made [3]. Way prior to that when Watson and Crick presented their work on DNA structure [4], it marked the “true” Abbreviations: EMR, Electronic Medical Records; EHR, Electronic Health Records; HGP, Human Genome Project; DOE, Department of Energy; NIH, National Institutes of Health; OHER, Office of Health and Environmental Research; NHGRI, National Human Genome Research Institute; HEP, Human Epigenome Project; HPP, Human Proteome Project; DTC, direct-to-consumer; SNP, Single Nucleotide Polymorphism; WHO, World Health Organization; DOHAD, Developmental Origins of Health and Diseases; HIE, Health Information Exchange n Corresponding author. E-mail addresses: [email protected] (S. Jauhari), [email protected] (S.A.M. Rizvi). http://dx.doi.org/10.1016/j.compbiomed.2014.07.001 0010-4825/& 2014 Elsevier Ltd. All rights reserved.
beginning of the genomic era. It embarked many concerned scientists and researchers to elaborate more on the underlying aspects of the molecular biology. The completion of the HGP in April 2003 had scattered the questions of annotation and genetic contemplation. The rackety nature of the biological data at the molecular level and its overlapping tendency obstructs their acceptance from practical and commercial standpoint. The then President of the United States, Bill Clinton and the then Prime Minister of Britain, Tony Blair (via satellite) announced the successful sequencing of the human genome and rightfully called it an edifice that will be extremely seminal towards understanding and building upon a new phase of medicine and hospitality [5]. Few people are aware of the fact that the HGP was commenced by physicists, primarily. The U.S. DOE and NIH collaborated for this grand scientific endeavor [5]. After a workshop in March 1986 in Santa Fe, New Mexico, the DOE's OHER, a realization was made by the research fraternity that “despite significant scientific, technical, and financial challenges, there was sound scientific justification to attempt the project and a reasonable expectation that the required technologies could be developed. Participants also agreed on including an educational and social component that examined the project's promises and limitations and the potential ramifications of making genomic information available [5]. Of course, an initiative of such stature invited international urge. Outside the United States of America, agencies gathered quick solidarity for the project initiation and completion. One of the frontrunners that were involved in bringing together all diverse groups was Wellcome Trust, UK [6]. It provided funding support to the project at a tier only second to the United States. It is also noteworthy that the HGP started-off with no roadmaps
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and was guided more by a vision; so much characteristic to any great scientific endeavor. Albeit certain pre-defined goals were deterministic [5]:
Identification of ALL the genes in the human DNA. Determination of the sequences of the three billion base pairs
that make up the human genome. Storage of the resulting data in the public databases. Improvement of data-analysis tools. Transfer of genomic technologies to the private sector. Addressal of ethical, legal, and social issues that might arise from the HGP.
The strategies for generating the human genome sequence, as adopted collaboratively by Celera and HGP, are illustrated in [7]. The gamut of HGP was stranded with the inertia and friction of the participating groups that persuaded their own methodologies for carrying out things effectively. These impediments were cleared by Celera Genomics, headed by J. Craig Venter that emerged as a private partnering company [5]. Its involvement was not welcomed by government bodies that had an idea about Celera getting access to public data, augmented to its private sum. [They] were unsure as to how exactly Celera is going to make use of the genome data, but they anticipated that contrary to the mandate issued by the NHGRI, the genome data would not be freely available to the public [5]. As the project neared completion, private–public entities jostled their way through; but humbly, at the end, the Clinton press conference would grade [it] a “tie”. The Human Genome paved way for several subprojects in its category: HEP [8] and HPP [9,10], which further attempt to decode the riddles of inter- and intra-regulation of genes and molecules broadly, in different biological states.
3. Business aspect Ever since the HGP gained momentum and acceptance, it has been a “guiding star” to most of the drug design and pharmaceutical oriented companies [11]. Working in close reference and tandem with the genomic data, aids efficient and to-the-point analysis. DTC companies are basking in the glory of genomics revolution, formalizing DNA tests that throw light on genetic traits and putative risks associated with disease induction [12]. The status of results offered by DTC (genomics) companies and their usefulness is arguable [12]. However, in a comparison made between two such companies, viz. 23andMe in Mountain View, California and Navigenics in Foster City, California, wherein the 13 disease sets of 5 patients was considered, the analyses reflect the huge potential that beholds under the aegis of personalized medicine [12]. Owing to the non-invasive methods for obtaining DNA samples from the patient viz. saliva, cheek swab, etc., the “first-time users” are less likely to feel apprehensive and reluctant. Tests can be ordered online and likewise is the display of results. The processing is carried out by distinctly identifying set of biomarkers in the particular patient and comparing them to the publically available ones [12]. Both companies (Navigenics and 23andMe), as per the patient data, assume varied parameters or aspects for predicting the proneness of a genetic disease. This directly implies that certain diseases can have better predictions as opposed to others. In an attempt to establish the results, it was found that for seven maladies, 50% or less of the predictions of two companies agreed across five individuals [12]. It is incumbent upon the companies to represent high risks articulately and also suggest biomarkers as potential drug targets. Even though, each company harnesses the same publically available data for elucidating the set of markers,
no two companies end up having the same due to the discrepancies in the selection criteria of the risk calculation based on the genome-wide association [12]. Also, for making strong predictions the markers have to be chosen after thoroughly studying mutations in expression levels and being as “modest” as possible. This can however be a subjective matter. The holy grail of predicting genetic disease after analyzing the whole genome sequence and making comparisons with the publically available data is the veracity of biomarkers [12]. The hindsight that the companies must contemplate upon is the community welfare. They must enter into a contract of mutual understanding and should have common grounds on selecting markers that have a thorough and deep-rooted effect. The two major polarizers with the defined technologies are the readiness to clinical validity and correlation to a disease state [13]. Most often today, the clinical genetic testing is carried out to elucidate the abnormality in a family, wherein the current and/or upcoming generations might be carriers of an aberration and might end up in an innate malady. This is technically commanded under SNPs testing, as opposed to whole genome sequencing, where comprehensive information can be construed to elicit disease traits and gene-wide associations. This scenario presents exciting opportunities as well as defiance for clinical medicine and its compliance to genetic analysis [13]. In addition, as a part of mandatory disclosure, the patient has to be apprised in all transparency about the various aspects of the sequencing procedure and its probable benefits. The legitimacy and validity have to be acknowledged with the greatest regard [13]. The information deciphered from the subject's genome sequencing will be actually quantifiable after it has been clinically verified. The patients must also be warned that they may be susceptible to many associated risks that correlate to behavioral traits and psychological aspects. Every patient will have to undergo distinct self-contemplation and decision making process, so as to ensure what is best for them and their social associations [13]. It may seem like the patient suffers in a short term but at large, in a longer run, on acknowledging the universality of the genomic insight, he/she will definitely benefit meticulously [13]. It is vital to understand that since genetic anomalies can be transferred from one generation to the next, every patient could face some negative social consequences after having children as carriers of the disorders [13]. When dealing with problem of such vast gamut, it will certainly goad a patient into tremendous inquisitiveness and a spate of eagerness will drive him/her into answering those queries and thence would require an expert voice to helm the correspondence into the right direction with as much subtlety as possible [13] (Fig. 1). The panel (Kelly E Ormond, Matthew T Wheeler, Louanne Hudgins, Teri E Klein, Atul J Butte, Russ B Altman, Evan A Ashley, Henry T Greely) proposes some practical considerations for the use of whole-genome sequencing data in clinical practice, as follows [13]:
The broad scope of the results will require that patients receive
complex and detailed information before they decide whether to be tested. Interpretation of genome sequences should take into account the limits of the sequencing method used. Easily accessible and well curated information about the links between genomic sequences and diseases needs to be created, maintained, and frequently updated. Physicians and patients will have to cope with enormous uncertainty in some results, particularly around variants of unknown importance, which might require analysis of genetic information from family members. Effective ways to convey meaningful information to patients about the many implications of their whole-genome sequences
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Fig. 1. Direct-to-consumer method for calculating disease risk [12].
Fig. 2. WHO analytics on Indian health: part 1.
need to be developed and training for appropriate specialists to convey this information funded. Whole-genome sequences will need to be reviewed regularly to incorporate new information about disease risks, and changes in assessment will have to be conveyed to patients.
To effectively conceive and accommodate the above aspects, certain lacunae have to be deliberated. Firstly, the outcomes and interpretations are specific to particular sequencing methods. There might be several conditions that are disregarded completely
or partially by a sequencing technique and thence rendering amiss results. Secondly, information to be aggregated from the whole genome sequencing warrants sufficient and precise information about the parts [13]. Currently, no such centrally maintained repository exists. Notwithstanding, the already rackety nature of the problem, in addition experts from the distinctive fields of genetic cardiology, bioinformatics, internal medicine, pharmacogenomics, and clinical genetics are required. Automating the entire knowledge adaptation will be highly desirable. Thirdly, sequencing is to reveal certain obscure information that is difficult to fit and
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home-in into the existing knowledge base. Many of such details are usable or otherwise. But since the context of usefulness of the data is unclear as of now, discarding it might not be a good idea. And herein lays the problem of recording it for future use. The dynamic nature of the data also raises questions about its validity and viability [13]. The frequent updates and soaring quantity harden the maintenance of the genetic information.
with magic and ancient beliefs that formed a large part of ancient civilizations and developments. As far as Indian healthcare goes, things are not looking very promising. The consensus carried out by Price Water House Coopers [14] and a report by Planning Commission India [15] clearly show the decrementing health status in India. As per the details given:
Population rise in India has given strong impetus to the proliferation of the healthcare industry;
Healthcare in India is one of the largest sectors and will remain
4. Healthcare in India: a context In India, even though in a very nascent stage, personalized medicine is making its mark. The Distributed Information store for Global Healthcare Technology (DIGHT) project (http://dight.sics. se/) is addressing the challenges of building a scalable and highly reliable information store for EHRs for the citizens of India. The project partners are SICS and the Indian Centre for Development of Advanced Computing (C-DAC), where SICS is responsible for the distributed storage aspects of the project, while C-DAC will work towards evolving an EHR standard for India. Also, with start-up companies like XCode Life Sciences (http://xcode.in/) and RxVault (http://www.rxvault.in/), India will soon be home to some serious personalized medication that will be offered as a generic scheme for all in the coming years. India is far known for its prevalence in traditional medicine and natural therapy. However, with the increasing pace of urbanization and readiness for globalization, this country's health concerns are far from being tractable. Illness and cure were closely associated
to be so due to inadequate remedial measures for the escalating malady rates; and the government spending on healthcare is greatly hampered by the poor and insufficient “distribution chain” of medical supplies to public hospitals. This is a colossal void to cover-up for the sake of infrastructure development, compatible for future model of custom-made therapeutics.
The WHO has marked India to join the club of nations having the highest reported cases of lifestyle disorders by 2020 [16]. Already considered “The Diabetes Capital of the World”, India now appears heading towards gaining another dubious distinction of becoming the lifestyle-related disease capital as well. Figs. 2 and 3 portray the detailed statistical analysis of the WHO study. Therefore, our primary “target customer” for the manuscript would be the governmental fraternity of India. We are certain about the veracity of the article and its usefulness in the country's context.
Fig. 3. WHO analytics on Indian health: part 2.
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Typically, an EHR consists of the following:
5. Medicine: an edifice 5.1. Medicine was conceived in sympathy and born out of necessity
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The patient's background including his ancestral details, family details, etc.
Breaking the traditional and ethnical barriers, which spun for centuries pertaining to distinct demographics, the medicine has evolved to be a more universal standard now, advocating for global well-being and prosperous health renderings [17]. Healthier population will not only be significantly benefitting a nation's growth but will also account for better dwelling environment. Even though countries and places have been long associated with their local medicinal ideals and practices, the real era of scientific medicine spawn from 1500 A.D. onwards [17]. The chronology witnessed Paracelsus tuning medicine to rational research, Fracastorius establishing the “theory of contagion”, Ambriose Pare advancing the art of surgery, Harvey's discovery of blood circulation, Leeuwenhoek's invention of microscope, Jenner's vaccination against small pox, and so on and so forth. To hive-off from the conventional practices was not really a consensual affair initially. There is a natural denial and baffle towards change. Now though, due to advancements in medicine and communication, this revolution has spurred a different view altogether of more effective dealing with the long existing and hard cured diseases. It has been a slow transition with fast acceptance that the inception of informatics or “omics” in general can bring about a significant alteration in dealing with, if not completely eradicating the maladies. Digitally analyzing the molecular chemistry and studying the networking of reactions, that complicate the entire disease-causing mechanism, make it a relatively simpler matter to be contemplated. Computer systems can deliver far more accurate, homed-in, and easily calculable outputs that can serve as ready-inputs for laboratory testing and verification [18].
6. Smart cards: an epitome of Electronic Health Records (EHR) Smart cards have been long valid and find their application in the form of a Subscriber Identification Module (SIM) card, driving licenses, travel cards, bank cards, etc. A smart card is typically a pocket-sized card, preferably materialized in plastic/fiber, and holds a chip which can be memory type, used for storing data or microprocessor type, used for transacting the data. Smart cards have proven reliability over magnetic-stripe and bar-code machine readable card systems [19], with enhanced security and easy maintenance. The plethora of healthcare data brings about new challenges to deal with its efficient management. In healthcare, embedded smart cards deliver superlative amenities out of clinicomechanical appliances. The topmost priority is the confidentiality to be ensured with every private medical record. Relative to this many survey based researches and meta-analyses have been conducted to ensure the wholeness of medical and procedural data that can be encapsulated within the domain of an EHR [20,21]. With reference to the “Integrated Care EHR”, as defined in ISO/ DTR 20514, an “EMR is a repository of information regarding the health of a subject of care in computer-processable form that is able to be stored and transmitted securely, and is accessible by multiple authorized users”. Already some socialized and civilized nations like France are already using smart cards to hold EHR. In the European Union, already a new scheme for health-card has been conceived [22,23]. It will not only facilitate better medical care but will also provide easy access and maintenance of clinical information.
The patient's medical history which convolves occurrences of clinical irregularities.
Medicines given and other therapeutic measures practised at the time.
Details of the medical practitioner dealing with the particular
case, including his/her registration number, affiliation with any organization, etc. With network availability, comparative analyses can be accomplished, subject to the appropriate software usage.
The usage of smart cards can deliver the following probable benefits:
They append the security status of the EHR by providing strong authentication.
Commercially available smart card software, and its further
updates and revisions, can aid improved health services amidst low hardware costs. This coupling is paving its way for a better healthcare delivery system. It forms the basis of easy mobility of data irrespective of site or systems. Reduced maintenance costs (less paper work and human-error proneness). Follow up services, such as reminders for health insurance renewal and next recommended check-up dates can be easily tracked [24].
It must also be noted that when the medical history of a patient is viewed in isolation much less or nil correlated information is seen. However, if the data is arranged in a chronological fashion, and documented from the scratch, as early as possible, (since birth), it can leave trail to significant prognostic cues. A prior standardization renders three basic models of EHR, as can be depicted via Table 3, viz. Inexpensive Data Media Model, Internet Patient Portal Model, and Personal Portable Device Model [25]. The authors have studied the e-commerce aspects (B2B and B2C) in light of the prevalent EHR standards and have deciphered that B2C mechanism is lucrative for both governments and consumers [25]. Many companies, established as well as startups, are ascertaining their role in making the most out of this opportunity. Not to mention, the developing countries are mostly reliant on the outsourced work.
7. Personalized medicine Now, when moving towards personalized medicine, the traditional medicinal practices have witnessed a paradigm-shift that is way quantum leap forward. Not just limited to adults, but medical disorders find equal occurrence in children too. Pediatrics has been strongly dealt and challenged with the scope and hope of personalized medicine [26]. As we foresee, the one inclusion, and a major one that can well be incorporated in the EHR values, is the human genome. It forms the platform for all metabolic activities being carried out in the human body and their mapping can help model correlational patterns at any stage. Even though active genes constitute approximately 1% of the combined DNA ( 6 billion base pairs), still they are the battleground for it all. Once the molecular activities have been deciphered, it becomes relatively easy to figure out causes of any malady that is currently treated using generic medicines.
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Table 1 Controlled medical vocabularies [31]. Vocabulary (abbreviation)
Technology
Definition
LOINC
Logical observation identifiers names and codes International Classification of diseases Systematized Nomenclature of Medicine-Clinical Terms Current Procedural Terminology, 4th Edition -
This repository holds names of the clinical observations and their corresponding universal codes. Regenstrief Institute Inc. runs the LOINC database and RELMA mapping program. Renowned classification scheme for clinical and epidemiological purposes.
ICD10 SNOMED-CT CPT 4 RxNORM ATC
Anatomic Therapeutic Chemical Classification of Drugs
Created by the College of American Pathologists (CAP) and maintained by the International Health Terminology Standards Development Organization (IHTSDO) in Denmark. Terms used by the physicians and health care professionals are coded here. Produced by the National Library of Medicine (NLM), this repository holds the vocabularies for mediation coding in pharmacy management software and market. Controlled by the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC), ATC is a repository of drugs.
Fig. 4. Factors affecting an individual's health.
8. Proposed methodology 8.1. The G-Card: intuition to implementation 8.1.1. Concept The G-Card is conceptualized keeping in mind the strong hold of EHR worldwide. In India, the “almost” successful AADHAR card has given a basis for maintaining the population based data electronically. This provides Indian people to avail benefits deriving out of several governmental schemes which can be oriented towards state or centre. DOHAD has established that a temporal data with implicit developmental states in a subject's therapeutic tenure throws good light on medical predictions and diagnostics. Abiding to the recommendations of the electronic medical record standards in India [27], the G-Card will endure greater precision and fulfill the “anytime–anywhere” initiative. It must also be noted that attendees for the patient can be disparately qualified, located, and compliant. It is therefore warranted, that a standard is implied to bring about smoothness and homogeneity [27]. To reiterate, these standards must be modifiable to accommodate the resonance of the changing demography of the medicine and clinical practice.
It [G-Card] garners vital particulars about the subject. A health symptom, when viewed in isolation, can have less meaning as opposed to analyzing a trend of disorders and marking the patterns of interest, temporally. These interpretations are vital for effective diagnostics and prognostic measures. On the same lines, the already existing framework for holding patient's medical data (recommended dataset – Table 4 can be referred) can be augmented with the patient's genome. This however can be carried out by keeping it [patient's genome] as a regular feature in the smart cards or establishing the G-Card as a different entity all together. We are of the view that the G-Card should be a disparate feature, so as to reduce complexity of data management, at least in the first go, and maybe merging other features to it as the advancements and adaptability are achieved through time. We also recommend, that every subject, not only in the time of despair, but also at least once in a shorter period of time, should visit the doctor and get prescription about his/her health as derived out of their genome. It can reveal some very seminal views that people are often casual about. Usually in India, people are not much concerned about their health until and unless something really un-innocuous confronts them. This is a highly disruptive mentality that needs to be nipped. People should be
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Table 2 Controlled exchange standards [31]. Vocabulary Technology (Abbreviation)
Definition
HL7 HL7 2.5.1 CCR DICOM
An XML based standard for transit and interoperability of clinical documents. Series of electronic messages based on non-XML, delimited syntaxes. Developed jointly by several organizations; contains instance-based status of a subject’s health condition. Used over TCP/IP, the biomedical data and laboratory instrumentation that uses images to represent information, is catered with DICOM and can be two-way communicated.
Health Level Seven Health Level Seven 2.x Continuity of Care Record Digital Imaging and Communications in Medicine.
Table 3 A comparison of the three models of EHR sharing and exchange with patients implementation [29].
Media
Inexpensive data media model
Internet patient portal model
Personal portable device model
Flash memory, CD-ROM, Smart card, etc.
None
PDA, cell phone, smart phone and Ultra Mobile PC (UPMC) 1. Better privacy than the Internet portal model 2. Easy to update 3. Personal reminders possible
Advantages
1. Low media cost 2. Small in size and highly portable 3. Good privacy
1. Easy access 2. No physical media
Disadvantages
1. Cannot be viewed without additional viewer and viewing device. 2. Not easy to update 3. Proneness of getting misplaced
1. Need Internet connection 2. Need a reliable and trusted back-end health information service provider 3. Privacy and security issues abound
Examples
MERIT-9 project (Japan); TMT project (Taiwan); Smart Card (Taiwan, Germany, Malaysia)
1. Bulkier 2. More expensive to own and maintain
Electronic Patient Folder (Germany); MyHealthOnLine (UK); TET/ TrEHRT Danish National Health Portal (Denmark) (APAMI, AMIA, EFMI, IMIA)
Table 4 Suggested EHR attributes by the recommendation committee [31].
UHID (as per AADHAR specifications) Patient name Patient age Patient occupation Patient phone number Emergency contact person name Emergency contact person address Emergency contact person email ID Care provider address Care provider email ID Insurance ID Episode type Encounter type Encounter date & time Present history Personal history Menstrual & obstetric history Immunization history Allergy history Clinical exam vitals diastolic BP Clinical exam temperature Clinical exam respiration rate Clinical exam weight Clinical exam observation Clinical summary Diagnosis code name Diagnosis (description) Treatment plan medication Treatment plan referral Other treatment plan details
required to contemplate that health is the primary goal and that living a healthy life will help them achieve everything else, not only for them but also for the people they care.
Alternate UHID Patient date of birth Patient gender Patient address Patient email ID Emergency contact person relationship Emergency contact person phone number Care provider name Care provider phone number Insurance status Organ donor status Episode number Encounter number Reason for visit Past history Family history Socio-economic status Allergy status Clinical exam vitals systolic BP Clinical exam pulse rate Clinical exam temperature source Clinical exam height Blood group Investigation results Diagnosis type Diagnosis code Treatment plan investigations Treatment plan procedure Other treatment plan type Current clinical status
8.1.2. Implementation As, can be derived out of the depicted graphic in Fig. 5, the G-Card will be provided as a very personal and unique identity to
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Fig. 5. Implementation of the G-Card. Table 5 Country-wise HCIT standards usage [31].
HL7 v2.5 HL7 v3 Only CDA ASTM CCR CCD openEHR IHE DICOM EDIFACT EHRCom
Australia
Austria
Canada
Denmark
England
Hong Kong
Netherlands
Sweden
Singapore
Taiwan
N N Y N N Y N N N N
N Y Y N N N Y Y N N
N Y Y N N N Y Y N N
N N N N N Y N N Y N
N Y Y Y Y N N N N N
Y Y Y N N N N N N N
N Y N N N N N N N N
N Y N N N Y N N N Y
N N N N N N N N N N
N N Y N N N N N N N
Table 6 Worldwide Healthcare IT (HCIT) programs [31]. Country
National Healthcare IT Program
Australia Austria Canada Denmark England Hong Kong Netherlands Singapore Sweden Taiwan
HealthConnect ELGA EHRS Blueprint MedCom Spine eHR Infrastructure AORTA EMRX National Patient Summary (NPO) Health Information Network (HIN)
every individual. It will hold their genome in a sequenced format and ready to be analyzed. On visiting a qualified medic, their G-Card will be considered for scanning and analyses via specialized hardware and software match. From the software technicality, the key is the Application Programming Interface (API) chosen. The commands called Application Protocol Data Units (APDUs) are capable of executions at very low levels, or they can be embedded into the APIs which enable interaction with the reader [28]. Most Software Development Kits (SDKs) facilitate interface development for smart card technology with the use of programming
languages like C, C þ þ, C#, that are inclusive of header files. The Personal Computer/Smart Card (PC/SC) standard is viable on all operating systems today, but it might not, still, support entire range of functions in disposal of smart cards from disparate manufacturers. And, from the hardware viewpoint, the terminals (self-contained computer systems primarily dedicated to smart card reading and data processing) feature operating system and development tools. They will be uniquely stratified under healthcare informatics and will accordingly function and facilitate. Connectivity in the terminals is typically via Transmission Control Protocol/Internet Protocol (TCP-IP) or GSM network. Many terminals today feature regular OS's making deployment easier such as Datastrip with windows CE or Exadigm with Linux [28]. This infrastructural coalition, of hardware and software, can be akin to current smart card reading systems (hardware) and software that pertain to genome sequencing analyses. They can be combined in a fashion that optimizes results in a standardized way (referring clinical ontology and imprints that are followed globally, as suggested by the informational tables that follow). Again, there is always a scope for improvement and the availability of highbandwidth network can always be desirable. From the database perspective, the patient data can be stored in the memory-type smart card, or remotely at a data centre. Data stored within the chip, can be accessed and updated offline and with ease via the particular API. If stored remotely, the network communication will
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aid the same. So, the network and database schema will be appropriately reckoned. This can facilitate a doctor referring other doctors and consulting them for making better predictions. The patient's genome will be compared with already existing genome sequences to construe the irregularities that may or may not be harmful. This information will be of the zenith importance. Now, after having the necessary evidence, the doctor and patient can undergo a series of referrals and discussions to arrive at a roadmap for a better and healthy lifestyle.
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Conflict of interest statement None declared.
Acknowledgment Also to be noted in the body text, the words “patient” and “subject” are referenced in synonymy. References
8.1.3. The counterparts A fair share of the genesis of the EHR was empowering the consumers [29]. Accessibility to one's health data is warranted by both the doctors and consumers. This makes a pervasive entity to undertake and amalgamate to advanced technologies like cloud computing [30], etc. Table 3 presents a comparative analysis of the existing EHR frameworks. While each has its pros and cons, none is superior to another per-se. The synchronization to the existing infrastructure and deployment and applicability strategies matters a lot. The harmonization of interoperability and standards of disparate contents of the EHR is vital. Standards can be stratified under vocabulary, context exchange, and clinical [31]. The report also suggests that Austria and Canada have the highest data exchange standard and adoption rate. Tables 5 and 6 exhibit enactment of HCIT standards in several countries. Vocabulary is quintessential for information exchange. Strict adherence to the protocol keeps the data from ambiguity and repetitiveness. There might be polymorphic nomenclature of the same technology, but differing with organization. To aid this, Controlled Medical Vocabularies (CMV) is considered which are detailed in Table 1 [31]. Clinical standards epitomize patient information in a more lucid fashion. They monitor the disease patient is suffering from, physician's recommendation of diagnostic tests and outlook on patient's condition, and the treatment given (Fig. 4). As per the specifications mentioned in [31] (which are considered minimal to any dataset designed to capture medical data of a patient), the following is a gist of the fields held. The details about the data-types, applicability and miscellaneous attributes can be studied in detail from the report [31] (Table 2).
9. Conclusion and summary With the standardization and proliferation of technology focussing medication, the G-Card will prove to be significantly useful in accessing nationwide healthcare status and thus aid the local and central governments to devise appropriate policies for unboxing better mechanisms to deal with a particular kind of a disease. It will also shed light on any limitations that the healthcare industry are facing in dealing with clinically oriented problems. The testing and therapeutics can have a wider scope, reaching out to different ethnicities and extrapolating methods of genetic medicine to all high and low. We have to ensure that sound health and good lifestyle, being every individual's right and necessity, get so delivered. Also, the predictions made out of generic data and the respective analyses are ostensible. To dredge out the actual actionable information, rigorous testing and repeated exhaustive analysis will be the ace. The G-Card can provide a foundation for such a process. To construe bio-markers is the most dramatic step in deciphering the key to good health. It can be used to provide valuable prescriptions to the patient for sustaining his/her fine health.
[1] “Towards Precision Medicine”, National Academies Press, Washington D.C., USA. International Standard Book Number-13: 978-0-309-22222-8, International Standard Book Number-10: 0-309-22222-2, Library of Congress Control Number: 2011943146. [2] S. Gupta, A. Venkatesh, S. Ray, S. Srivastava, Challenges and prospects for biomarker research: a current perspective from developing world, Biochim. Biophys. Acta (2014), http://dx.doi.org/10.1016/j.bbapap.2013.12.020 (Jan 7. pii: S1570-9639(14)00002-8). [3] National Human Genome Research Institute, National Institute of Health 〈http://www.genome.gov〉. [4] J.D. Watson, F.H.C. Crick (April 25), A structure for Deoxyribose Nucleic Acid, 171, Nature (1953) 737–738. [5] Quackenbush J., The Human Genome – The Book of Essential Knowledge, ISBN no. 978-1-936140-15-2. [6] The Wellcome Trust 〈http://www.wellcome.ac.uk/〉. [7] The Human Genome, Science, Genome Map, Science, vol. 291, 5507, 16 February 2001, pp. 1218 doi.10.1126/science.291.5507.1218. [8] Human Epigenome Project, 〈http://www.epigenome.org/〉. [9] Human Proteome Project, 〈http://www.thehpp.org/〉. [10] P. Legrain, R. Aebersold, A. Archakov, A. Bairoch, K. Bala, L. Beretta, J. Bergeron, C. Borchers, G.L. Corthals, C.E. Costello, E.W. Deutsch, B. Domon, W. Hancock, F. He, D. Hochstrasser, G. Marko-Varga, G.H. Salekdeh, S. Sechi, M. Snyder, S. Srivastava, M. Uhlen, C.H. Hu, T. Yamamoto, Y. Paik, G.S. Omenn, The human proteome project: current state and future direction, Mol. Cell. Proteomics (2011) (mcp.O111.009993). [11] L. Xie, X. Ge, H. Tan, L. Xie, Y. Zhang, et al., Towards structural systems pharmacology to study complex diseases and personalized medicine, PLoS Comput. Biol. 10 (5) (2014) e1003554. http://dx.doi.org/10.1371/journal. pcbi.1003554. [12] Pauline C. Ng, Sarah S. Murray, Samuel Levy, J. Craig Venter, An agenda for personalized medicine, Nature 461 (2009) (8 October, Available at)〈http:// www.gis.astar.edu.sg/internet/site/data/sup_data/2249/an_agenda_for_perso nalized_medicine.pdf〉. [13] Kelly E. Ormond, Matthew T. Wheeler, Lovanne Hudgins, Teri E. Klein, Atul J. Butte, Russ B. Altman, Evan A. Ashley, Henry T. Greely, Challenges in the clinical application of whole-genome sequencing, Lancet 375 (2010) 1749–1751 (doi: 1.1016/S0140-6736(10)60599-5). [14] Price Water House Coopers, Healthcare in India: Emerging market report, 2007. [15] Srinivasan R., Planning Commission of India, Healthcare in India-Vision 2020, 〈http://www.planningcommission.nic.in/reports/genrep/bkpap2020/26_bg2020.doc〉. [16] World Health Organization India, 〈http://www.whoindia.org/〉. [17] E. Ackerknecht, A Short History of Medicine, JHU Press, ISBN 978-0-80182726-6, 1982. [18] S. Hogarth, G. Javitt, D. Meizer, Annual review genomics, Hum. Genet. 9 (2008) 161–182. [19] “Smart Card Applications Healthcare”, Smart Card Alliance, 〈http://www. smartcardalliance.org/〉. [20] Watzlaf, et al., Standards for the content of the electronic health record, Perspectives in Health Information Management 1 (1) (Winter). [21] Crosson, et al., Typical electronic health record use in primary care practices and the quality of diabetes care, Ann. Fam. Med. 10 (2012) 221–227. http://dx. doi.org/10.1370/afm.1370. [22] 〈http://news.bbc.co.uk/2/hi/health/3569616.stm〉. [23] 〈http://news.bbc.co.uk/2/hi/health/1817562.stm〉. [24] Hung-Yu Chien, Jinn-Ke Jan, Yuh-Min Tseng, An efficient and practical solution to remote authentication: smart card, Comput. Secur. 21 (4) (2002) 372–375 (1 August)http://dx.doi.org/10.1016/S0167-4048(02)00415-7. [25] Li Y.C., Lee P.S., Jian W.S., Kuo C.H., Electronic Health Record Goes Personal World-wide, IMIA Yearbook 2009: Closing the Loops in Biomedical Informatics, 0943-4747. [26] W.G. Feero, A.E. Guttmacher, Genomics, personalized medicine, and pediatrics, Acad. Pediatr. 14 (1) (2014) 14–22. http://dx.doi.org/10.1016/j. acap.2013.06.008. [27] Sequist, et al., Implementation and use of an electronic health record within the indian health service, J. Am. Med. Inform. Assoc. 14 (2007) 191–197 http://dx.doi.org/10.1197/jamia.M2234. [28] “Smart Card and Security Basics”, Whitepaper, Cardlogix Corporation, 〈http:// www.smartcardbasics.com/〉.
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[29] “Study & Analysis of National EHR/EMR Programs Around the World”, Conducted by Medical Informatics Group, C-DAC, Pune as part of Project for Building Distributed National EHR funded by DIT, MCIT, Govt. of India. [30] T.S. Chen, C.H. Liu, T.L. Chen, C.S. Chen, J.G. Bau, T.C. Lin, Secure dynamic access control scheme of PHR in cloud computing, J. Med. Syst. 36 (6) (2012) 4005–4020. http://dx.doi.org/10.1007/s10916-012-9873-8. [31] “Recommendations On Electronic Medical Records Standards In India”, April 2013; recommendations of EMR Standards Committee, constituted by an order of Ministry of Health & Family Welfare, Government of India and coordinated by FICCI on its behalf.
Shaurya Jauhari is a research scholar in Bioinformatics at Jamia Millia Islamia, New Delhi, India since September 2012. Mr. Jauhari received his B.S. degree in Statistics,
Mathematics, and Computer Applications in 2005 from University of Lucknow, India and his MS degree in Computer Applications in 2009 from Uttar Pradesh Technical University, India. His research interests include cancer therapeutics, biomedical informatics, and biostatistics. Prior to working here, he served as a Network Assistant and a Software Engineer, from 2009 to 2012.
S.A.M. Rizvi is serving as Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India. With a vast academic experience and revered credibility, Dr. Rizvi is a frontrunner in interdisciplinary research and cross-platform training. His research interests include computer algorithms, artificial intelligence, bioinformatics, and design theory.
©2015 Elsevier
Contents lists available at ScienceDirect
Computers in Biology and Medicine journal homepage: www.elsevier.com/locate/cbm
An Indian eye to personalized medicine Shaurya Jauhari n, S.A.M. Rizvi Department of Computer Science, Jamia Millia Islamia, New Delhi, India
art ic l e i nf o
a b s t r a c t
Article history: Received 30 August 2013 Accepted 3 July 2014
Acknowledging the successful sequencing of the human genome and the valuable insights it has rendered, genetic drafting of non-human organisms can further enhance the understanding of modern biology. The price of sequencing technology has plummeted with time, and there is a noticeable enhancement in its implementation and recurrent usage. Sequenced genome information can be contained in a microarray chip, and then processed by a computer system for inferring analytics and predictions. Specifically, smart cards have been significantly applicable to assimilate and retrieve complex data, with ease and implicit mobility. Herein, we propose “The G-Card”, a development with respect to the prevalent smart card, and an extension to the Electronic Health Record (EHR), that will hold the genome sequence of an individual, so that the medical practitioner can better investigate irregularities in a patient's health and hence recommend a precise prognosis. & 2014 Elsevier Ltd. All rights reserved.
Keywords: G-Card Healthcare Human genome India Personalized medicine Smart card
1. Introduction Companies from private and cross-service platforms will be transacting in customized medicine and pharmacology. Personalized medicine per-se is an enormous challenge given the scope, complexity and usage-population. Also, named as precision medicine by few, personalized medicine is yet to see a long road to acceptance and proliferation [1]. But what is in store for a “developing” country like India. Well, there is already some buzz, but much will be uncovered with time and technology. Gupta et al. [2] have rendered an overview of how slow economy directly correlates to lack of early diagnosis and treatment. In the light of biomarker discovery, not only health know-how, but education, behavioral contexts, social ethics, all have a role to play.
2. Human Genome Project: conception to completion It would not be all appreciably acknowledged if a remark about the HGP is not made [3]. Way prior to that when Watson and Crick presented their work on DNA structure [4], it marked the “true” Abbreviations: EMR, Electronic Medical Records; EHR, Electronic Health Records; HGP, Human Genome Project; DOE, Department of Energy; NIH, National Institutes of Health; OHER, Office of Health and Environmental Research; NHGRI, National Human Genome Research Institute; HEP, Human Epigenome Project; HPP, Human Proteome Project; DTC, direct-to-consumer; SNP, Single Nucleotide Polymorphism; WHO, World Health Organization; DOHAD, Developmental Origins of Health and Diseases; HIE, Health Information Exchange n Corresponding author. E-mail addresses: [email protected] (S. Jauhari), [email protected] (S.A.M. Rizvi). http://dx.doi.org/10.1016/j.compbiomed.2014.07.001 0010-4825/& 2014 Elsevier Ltd. All rights reserved.
beginning of the genomic era. It embarked many concerned scientists and researchers to elaborate more on the underlying aspects of the molecular biology. The completion of the HGP in April 2003 had scattered the questions of annotation and genetic contemplation. The rackety nature of the biological data at the molecular level and its overlapping tendency obstructs their acceptance from practical and commercial standpoint. The then President of the United States, Bill Clinton and the then Prime Minister of Britain, Tony Blair (via satellite) announced the successful sequencing of the human genome and rightfully called it an edifice that will be extremely seminal towards understanding and building upon a new phase of medicine and hospitality [5]. Few people are aware of the fact that the HGP was commenced by physicists, primarily. The U.S. DOE and NIH collaborated for this grand scientific endeavor [5]. After a workshop in March 1986 in Santa Fe, New Mexico, the DOE's OHER, a realization was made by the research fraternity that “despite significant scientific, technical, and financial challenges, there was sound scientific justification to attempt the project and a reasonable expectation that the required technologies could be developed. Participants also agreed on including an educational and social component that examined the project's promises and limitations and the potential ramifications of making genomic information available [5]. Of course, an initiative of such stature invited international urge. Outside the United States of America, agencies gathered quick solidarity for the project initiation and completion. One of the frontrunners that were involved in bringing together all diverse groups was Wellcome Trust, UK [6]. It provided funding support to the project at a tier only second to the United States. It is also noteworthy that the HGP started-off with no roadmaps
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and was guided more by a vision; so much characteristic to any great scientific endeavor. Albeit certain pre-defined goals were deterministic [5]:
Identification of ALL the genes in the human DNA. Determination of the sequences of the three billion base pairs
that make up the human genome. Storage of the resulting data in the public databases. Improvement of data-analysis tools. Transfer of genomic technologies to the private sector. Addressal of ethical, legal, and social issues that might arise from the HGP.
The strategies for generating the human genome sequence, as adopted collaboratively by Celera and HGP, are illustrated in [7]. The gamut of HGP was stranded with the inertia and friction of the participating groups that persuaded their own methodologies for carrying out things effectively. These impediments were cleared by Celera Genomics, headed by J. Craig Venter that emerged as a private partnering company [5]. Its involvement was not welcomed by government bodies that had an idea about Celera getting access to public data, augmented to its private sum. [They] were unsure as to how exactly Celera is going to make use of the genome data, but they anticipated that contrary to the mandate issued by the NHGRI, the genome data would not be freely available to the public [5]. As the project neared completion, private–public entities jostled their way through; but humbly, at the end, the Clinton press conference would grade [it] a “tie”. The Human Genome paved way for several subprojects in its category: HEP [8] and HPP [9,10], which further attempt to decode the riddles of inter- and intra-regulation of genes and molecules broadly, in different biological states.
3. Business aspect Ever since the HGP gained momentum and acceptance, it has been a “guiding star” to most of the drug design and pharmaceutical oriented companies [11]. Working in close reference and tandem with the genomic data, aids efficient and to-the-point analysis. DTC companies are basking in the glory of genomics revolution, formalizing DNA tests that throw light on genetic traits and putative risks associated with disease induction [12]. The status of results offered by DTC (genomics) companies and their usefulness is arguable [12]. However, in a comparison made between two such companies, viz. 23andMe in Mountain View, California and Navigenics in Foster City, California, wherein the 13 disease sets of 5 patients was considered, the analyses reflect the huge potential that beholds under the aegis of personalized medicine [12]. Owing to the non-invasive methods for obtaining DNA samples from the patient viz. saliva, cheek swab, etc., the “first-time users” are less likely to feel apprehensive and reluctant. Tests can be ordered online and likewise is the display of results. The processing is carried out by distinctly identifying set of biomarkers in the particular patient and comparing them to the publically available ones [12]. Both companies (Navigenics and 23andMe), as per the patient data, assume varied parameters or aspects for predicting the proneness of a genetic disease. This directly implies that certain diseases can have better predictions as opposed to others. In an attempt to establish the results, it was found that for seven maladies, 50% or less of the predictions of two companies agreed across five individuals [12]. It is incumbent upon the companies to represent high risks articulately and also suggest biomarkers as potential drug targets. Even though, each company harnesses the same publically available data for elucidating the set of markers,
no two companies end up having the same due to the discrepancies in the selection criteria of the risk calculation based on the genome-wide association [12]. Also, for making strong predictions the markers have to be chosen after thoroughly studying mutations in expression levels and being as “modest” as possible. This can however be a subjective matter. The holy grail of predicting genetic disease after analyzing the whole genome sequence and making comparisons with the publically available data is the veracity of biomarkers [12]. The hindsight that the companies must contemplate upon is the community welfare. They must enter into a contract of mutual understanding and should have common grounds on selecting markers that have a thorough and deep-rooted effect. The two major polarizers with the defined technologies are the readiness to clinical validity and correlation to a disease state [13]. Most often today, the clinical genetic testing is carried out to elucidate the abnormality in a family, wherein the current and/or upcoming generations might be carriers of an aberration and might end up in an innate malady. This is technically commanded under SNPs testing, as opposed to whole genome sequencing, where comprehensive information can be construed to elicit disease traits and gene-wide associations. This scenario presents exciting opportunities as well as defiance for clinical medicine and its compliance to genetic analysis [13]. In addition, as a part of mandatory disclosure, the patient has to be apprised in all transparency about the various aspects of the sequencing procedure and its probable benefits. The legitimacy and validity have to be acknowledged with the greatest regard [13]. The information deciphered from the subject's genome sequencing will be actually quantifiable after it has been clinically verified. The patients must also be warned that they may be susceptible to many associated risks that correlate to behavioral traits and psychological aspects. Every patient will have to undergo distinct self-contemplation and decision making process, so as to ensure what is best for them and their social associations [13]. It may seem like the patient suffers in a short term but at large, in a longer run, on acknowledging the universality of the genomic insight, he/she will definitely benefit meticulously [13]. It is vital to understand that since genetic anomalies can be transferred from one generation to the next, every patient could face some negative social consequences after having children as carriers of the disorders [13]. When dealing with problem of such vast gamut, it will certainly goad a patient into tremendous inquisitiveness and a spate of eagerness will drive him/her into answering those queries and thence would require an expert voice to helm the correspondence into the right direction with as much subtlety as possible [13] (Fig. 1). The panel (Kelly E Ormond, Matthew T Wheeler, Louanne Hudgins, Teri E Klein, Atul J Butte, Russ B Altman, Evan A Ashley, Henry T Greely) proposes some practical considerations for the use of whole-genome sequencing data in clinical practice, as follows [13]:
The broad scope of the results will require that patients receive
complex and detailed information before they decide whether to be tested. Interpretation of genome sequences should take into account the limits of the sequencing method used. Easily accessible and well curated information about the links between genomic sequences and diseases needs to be created, maintained, and frequently updated. Physicians and patients will have to cope with enormous uncertainty in some results, particularly around variants of unknown importance, which might require analysis of genetic information from family members. Effective ways to convey meaningful information to patients about the many implications of their whole-genome sequences
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Fig. 1. Direct-to-consumer method for calculating disease risk [12].
Fig. 2. WHO analytics on Indian health: part 1.
need to be developed and training for appropriate specialists to convey this information funded. Whole-genome sequences will need to be reviewed regularly to incorporate new information about disease risks, and changes in assessment will have to be conveyed to patients.
To effectively conceive and accommodate the above aspects, certain lacunae have to be deliberated. Firstly, the outcomes and interpretations are specific to particular sequencing methods. There might be several conditions that are disregarded completely
or partially by a sequencing technique and thence rendering amiss results. Secondly, information to be aggregated from the whole genome sequencing warrants sufficient and precise information about the parts [13]. Currently, no such centrally maintained repository exists. Notwithstanding, the already rackety nature of the problem, in addition experts from the distinctive fields of genetic cardiology, bioinformatics, internal medicine, pharmacogenomics, and clinical genetics are required. Automating the entire knowledge adaptation will be highly desirable. Thirdly, sequencing is to reveal certain obscure information that is difficult to fit and
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home-in into the existing knowledge base. Many of such details are usable or otherwise. But since the context of usefulness of the data is unclear as of now, discarding it might not be a good idea. And herein lays the problem of recording it for future use. The dynamic nature of the data also raises questions about its validity and viability [13]. The frequent updates and soaring quantity harden the maintenance of the genetic information.
with magic and ancient beliefs that formed a large part of ancient civilizations and developments. As far as Indian healthcare goes, things are not looking very promising. The consensus carried out by Price Water House Coopers [14] and a report by Planning Commission India [15] clearly show the decrementing health status in India. As per the details given:
Population rise in India has given strong impetus to the proliferation of the healthcare industry;
Healthcare in India is one of the largest sectors and will remain
4. Healthcare in India: a context In India, even though in a very nascent stage, personalized medicine is making its mark. The Distributed Information store for Global Healthcare Technology (DIGHT) project (http://dight.sics. se/) is addressing the challenges of building a scalable and highly reliable information store for EHRs for the citizens of India. The project partners are SICS and the Indian Centre for Development of Advanced Computing (C-DAC), where SICS is responsible for the distributed storage aspects of the project, while C-DAC will work towards evolving an EHR standard for India. Also, with start-up companies like XCode Life Sciences (http://xcode.in/) and RxVault (http://www.rxvault.in/), India will soon be home to some serious personalized medication that will be offered as a generic scheme for all in the coming years. India is far known for its prevalence in traditional medicine and natural therapy. However, with the increasing pace of urbanization and readiness for globalization, this country's health concerns are far from being tractable. Illness and cure were closely associated
to be so due to inadequate remedial measures for the escalating malady rates; and the government spending on healthcare is greatly hampered by the poor and insufficient “distribution chain” of medical supplies to public hospitals. This is a colossal void to cover-up for the sake of infrastructure development, compatible for future model of custom-made therapeutics.
The WHO has marked India to join the club of nations having the highest reported cases of lifestyle disorders by 2020 [16]. Already considered “The Diabetes Capital of the World”, India now appears heading towards gaining another dubious distinction of becoming the lifestyle-related disease capital as well. Figs. 2 and 3 portray the detailed statistical analysis of the WHO study. Therefore, our primary “target customer” for the manuscript would be the governmental fraternity of India. We are certain about the veracity of the article and its usefulness in the country's context.
Fig. 3. WHO analytics on Indian health: part 2.
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Typically, an EHR consists of the following:
5. Medicine: an edifice 5.1. Medicine was conceived in sympathy and born out of necessity
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The patient's background including his ancestral details, family details, etc.
Breaking the traditional and ethnical barriers, which spun for centuries pertaining to distinct demographics, the medicine has evolved to be a more universal standard now, advocating for global well-being and prosperous health renderings [17]. Healthier population will not only be significantly benefitting a nation's growth but will also account for better dwelling environment. Even though countries and places have been long associated with their local medicinal ideals and practices, the real era of scientific medicine spawn from 1500 A.D. onwards [17]. The chronology witnessed Paracelsus tuning medicine to rational research, Fracastorius establishing the “theory of contagion”, Ambriose Pare advancing the art of surgery, Harvey's discovery of blood circulation, Leeuwenhoek's invention of microscope, Jenner's vaccination against small pox, and so on and so forth. To hive-off from the conventional practices was not really a consensual affair initially. There is a natural denial and baffle towards change. Now though, due to advancements in medicine and communication, this revolution has spurred a different view altogether of more effective dealing with the long existing and hard cured diseases. It has been a slow transition with fast acceptance that the inception of informatics or “omics” in general can bring about a significant alteration in dealing with, if not completely eradicating the maladies. Digitally analyzing the molecular chemistry and studying the networking of reactions, that complicate the entire disease-causing mechanism, make it a relatively simpler matter to be contemplated. Computer systems can deliver far more accurate, homed-in, and easily calculable outputs that can serve as ready-inputs for laboratory testing and verification [18].
6. Smart cards: an epitome of Electronic Health Records (EHR) Smart cards have been long valid and find their application in the form of a Subscriber Identification Module (SIM) card, driving licenses, travel cards, bank cards, etc. A smart card is typically a pocket-sized card, preferably materialized in plastic/fiber, and holds a chip which can be memory type, used for storing data or microprocessor type, used for transacting the data. Smart cards have proven reliability over magnetic-stripe and bar-code machine readable card systems [19], with enhanced security and easy maintenance. The plethora of healthcare data brings about new challenges to deal with its efficient management. In healthcare, embedded smart cards deliver superlative amenities out of clinicomechanical appliances. The topmost priority is the confidentiality to be ensured with every private medical record. Relative to this many survey based researches and meta-analyses have been conducted to ensure the wholeness of medical and procedural data that can be encapsulated within the domain of an EHR [20,21]. With reference to the “Integrated Care EHR”, as defined in ISO/ DTR 20514, an “EMR is a repository of information regarding the health of a subject of care in computer-processable form that is able to be stored and transmitted securely, and is accessible by multiple authorized users”. Already some socialized and civilized nations like France are already using smart cards to hold EHR. In the European Union, already a new scheme for health-card has been conceived [22,23]. It will not only facilitate better medical care but will also provide easy access and maintenance of clinical information.
The patient's medical history which convolves occurrences of clinical irregularities.
Medicines given and other therapeutic measures practised at the time.
Details of the medical practitioner dealing with the particular
case, including his/her registration number, affiliation with any organization, etc. With network availability, comparative analyses can be accomplished, subject to the appropriate software usage.
The usage of smart cards can deliver the following probable benefits:
They append the security status of the EHR by providing strong authentication.
Commercially available smart card software, and its further
updates and revisions, can aid improved health services amidst low hardware costs. This coupling is paving its way for a better healthcare delivery system. It forms the basis of easy mobility of data irrespective of site or systems. Reduced maintenance costs (less paper work and human-error proneness). Follow up services, such as reminders for health insurance renewal and next recommended check-up dates can be easily tracked [24].
It must also be noted that when the medical history of a patient is viewed in isolation much less or nil correlated information is seen. However, if the data is arranged in a chronological fashion, and documented from the scratch, as early as possible, (since birth), it can leave trail to significant prognostic cues. A prior standardization renders three basic models of EHR, as can be depicted via Table 3, viz. Inexpensive Data Media Model, Internet Patient Portal Model, and Personal Portable Device Model [25]. The authors have studied the e-commerce aspects (B2B and B2C) in light of the prevalent EHR standards and have deciphered that B2C mechanism is lucrative for both governments and consumers [25]. Many companies, established as well as startups, are ascertaining their role in making the most out of this opportunity. Not to mention, the developing countries are mostly reliant on the outsourced work.
7. Personalized medicine Now, when moving towards personalized medicine, the traditional medicinal practices have witnessed a paradigm-shift that is way quantum leap forward. Not just limited to adults, but medical disorders find equal occurrence in children too. Pediatrics has been strongly dealt and challenged with the scope and hope of personalized medicine [26]. As we foresee, the one inclusion, and a major one that can well be incorporated in the EHR values, is the human genome. It forms the platform for all metabolic activities being carried out in the human body and their mapping can help model correlational patterns at any stage. Even though active genes constitute approximately 1% of the combined DNA ( 6 billion base pairs), still they are the battleground for it all. Once the molecular activities have been deciphered, it becomes relatively easy to figure out causes of any malady that is currently treated using generic medicines.
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Table 1 Controlled medical vocabularies [31]. Vocabulary (abbreviation)
Technology
Definition
LOINC
Logical observation identifiers names and codes International Classification of diseases Systematized Nomenclature of Medicine-Clinical Terms Current Procedural Terminology, 4th Edition -
This repository holds names of the clinical observations and their corresponding universal codes. Regenstrief Institute Inc. runs the LOINC database and RELMA mapping program. Renowned classification scheme for clinical and epidemiological purposes.
ICD10 SNOMED-CT CPT 4 RxNORM ATC
Anatomic Therapeutic Chemical Classification of Drugs
Created by the College of American Pathologists (CAP) and maintained by the International Health Terminology Standards Development Organization (IHTSDO) in Denmark. Terms used by the physicians and health care professionals are coded here. Produced by the National Library of Medicine (NLM), this repository holds the vocabularies for mediation coding in pharmacy management software and market. Controlled by the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC), ATC is a repository of drugs.
Fig. 4. Factors affecting an individual's health.
8. Proposed methodology 8.1. The G-Card: intuition to implementation 8.1.1. Concept The G-Card is conceptualized keeping in mind the strong hold of EHR worldwide. In India, the “almost” successful AADHAR card has given a basis for maintaining the population based data electronically. This provides Indian people to avail benefits deriving out of several governmental schemes which can be oriented towards state or centre. DOHAD has established that a temporal data with implicit developmental states in a subject's therapeutic tenure throws good light on medical predictions and diagnostics. Abiding to the recommendations of the electronic medical record standards in India [27], the G-Card will endure greater precision and fulfill the “anytime–anywhere” initiative. It must also be noted that attendees for the patient can be disparately qualified, located, and compliant. It is therefore warranted, that a standard is implied to bring about smoothness and homogeneity [27]. To reiterate, these standards must be modifiable to accommodate the resonance of the changing demography of the medicine and clinical practice.
It [G-Card] garners vital particulars about the subject. A health symptom, when viewed in isolation, can have less meaning as opposed to analyzing a trend of disorders and marking the patterns of interest, temporally. These interpretations are vital for effective diagnostics and prognostic measures. On the same lines, the already existing framework for holding patient's medical data (recommended dataset – Table 4 can be referred) can be augmented with the patient's genome. This however can be carried out by keeping it [patient's genome] as a regular feature in the smart cards or establishing the G-Card as a different entity all together. We are of the view that the G-Card should be a disparate feature, so as to reduce complexity of data management, at least in the first go, and maybe merging other features to it as the advancements and adaptability are achieved through time. We also recommend, that every subject, not only in the time of despair, but also at least once in a shorter period of time, should visit the doctor and get prescription about his/her health as derived out of their genome. It can reveal some very seminal views that people are often casual about. Usually in India, people are not much concerned about their health until and unless something really un-innocuous confronts them. This is a highly disruptive mentality that needs to be nipped. People should be
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Table 2 Controlled exchange standards [31]. Vocabulary Technology (Abbreviation)
Definition
HL7 HL7 2.5.1 CCR DICOM
An XML based standard for transit and interoperability of clinical documents. Series of electronic messages based on non-XML, delimited syntaxes. Developed jointly by several organizations; contains instance-based status of a subject’s health condition. Used over TCP/IP, the biomedical data and laboratory instrumentation that uses images to represent information, is catered with DICOM and can be two-way communicated.
Health Level Seven Health Level Seven 2.x Continuity of Care Record Digital Imaging and Communications in Medicine.
Table 3 A comparison of the three models of EHR sharing and exchange with patients implementation [29].
Media
Inexpensive data media model
Internet patient portal model
Personal portable device model
Flash memory, CD-ROM, Smart card, etc.
None
PDA, cell phone, smart phone and Ultra Mobile PC (UPMC) 1. Better privacy than the Internet portal model 2. Easy to update 3. Personal reminders possible
Advantages
1. Low media cost 2. Small in size and highly portable 3. Good privacy
1. Easy access 2. No physical media
Disadvantages
1. Cannot be viewed without additional viewer and viewing device. 2. Not easy to update 3. Proneness of getting misplaced
1. Need Internet connection 2. Need a reliable and trusted back-end health information service provider 3. Privacy and security issues abound
Examples
MERIT-9 project (Japan); TMT project (Taiwan); Smart Card (Taiwan, Germany, Malaysia)
1. Bulkier 2. More expensive to own and maintain
Electronic Patient Folder (Germany); MyHealthOnLine (UK); TET/ TrEHRT Danish National Health Portal (Denmark) (APAMI, AMIA, EFMI, IMIA)
Table 4 Suggested EHR attributes by the recommendation committee [31].
UHID (as per AADHAR specifications) Patient name Patient age Patient occupation Patient phone number Emergency contact person name Emergency contact person address Emergency contact person email ID Care provider address Care provider email ID Insurance ID Episode type Encounter type Encounter date & time Present history Personal history Menstrual & obstetric history Immunization history Allergy history Clinical exam vitals diastolic BP Clinical exam temperature Clinical exam respiration rate Clinical exam weight Clinical exam observation Clinical summary Diagnosis code name Diagnosis (description) Treatment plan medication Treatment plan referral Other treatment plan details
required to contemplate that health is the primary goal and that living a healthy life will help them achieve everything else, not only for them but also for the people they care.
Alternate UHID Patient date of birth Patient gender Patient address Patient email ID Emergency contact person relationship Emergency contact person phone number Care provider name Care provider phone number Insurance status Organ donor status Episode number Encounter number Reason for visit Past history Family history Socio-economic status Allergy status Clinical exam vitals systolic BP Clinical exam pulse rate Clinical exam temperature source Clinical exam height Blood group Investigation results Diagnosis type Diagnosis code Treatment plan investigations Treatment plan procedure Other treatment plan type Current clinical status
8.1.2. Implementation As, can be derived out of the depicted graphic in Fig. 5, the G-Card will be provided as a very personal and unique identity to
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Fig. 5. Implementation of the G-Card. Table 5 Country-wise HCIT standards usage [31].
HL7 v2.5 HL7 v3 Only CDA ASTM CCR CCD openEHR IHE DICOM EDIFACT EHRCom
Australia
Austria
Canada
Denmark
England
Hong Kong
Netherlands
Sweden
Singapore
Taiwan
N N Y N N Y N N N N
N Y Y N N N Y Y N N
N Y Y N N N Y Y N N
N N N N N Y N N Y N
N Y Y Y Y N N N N N
Y Y Y N N N N N N N
N Y N N N N N N N N
N Y N N N Y N N N Y
N N N N N N N N N N
N N Y N N N N N N N
Table 6 Worldwide Healthcare IT (HCIT) programs [31]. Country
National Healthcare IT Program
Australia Austria Canada Denmark England Hong Kong Netherlands Singapore Sweden Taiwan
HealthConnect ELGA EHRS Blueprint MedCom Spine eHR Infrastructure AORTA EMRX National Patient Summary (NPO) Health Information Network (HIN)
every individual. It will hold their genome in a sequenced format and ready to be analyzed. On visiting a qualified medic, their G-Card will be considered for scanning and analyses via specialized hardware and software match. From the software technicality, the key is the Application Programming Interface (API) chosen. The commands called Application Protocol Data Units (APDUs) are capable of executions at very low levels, or they can be embedded into the APIs which enable interaction with the reader [28]. Most Software Development Kits (SDKs) facilitate interface development for smart card technology with the use of programming
languages like C, C þ þ, C#, that are inclusive of header files. The Personal Computer/Smart Card (PC/SC) standard is viable on all operating systems today, but it might not, still, support entire range of functions in disposal of smart cards from disparate manufacturers. And, from the hardware viewpoint, the terminals (self-contained computer systems primarily dedicated to smart card reading and data processing) feature operating system and development tools. They will be uniquely stratified under healthcare informatics and will accordingly function and facilitate. Connectivity in the terminals is typically via Transmission Control Protocol/Internet Protocol (TCP-IP) or GSM network. Many terminals today feature regular OS's making deployment easier such as Datastrip with windows CE or Exadigm with Linux [28]. This infrastructural coalition, of hardware and software, can be akin to current smart card reading systems (hardware) and software that pertain to genome sequencing analyses. They can be combined in a fashion that optimizes results in a standardized way (referring clinical ontology and imprints that are followed globally, as suggested by the informational tables that follow). Again, there is always a scope for improvement and the availability of highbandwidth network can always be desirable. From the database perspective, the patient data can be stored in the memory-type smart card, or remotely at a data centre. Data stored within the chip, can be accessed and updated offline and with ease via the particular API. If stored remotely, the network communication will
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aid the same. So, the network and database schema will be appropriately reckoned. This can facilitate a doctor referring other doctors and consulting them for making better predictions. The patient's genome will be compared with already existing genome sequences to construe the irregularities that may or may not be harmful. This information will be of the zenith importance. Now, after having the necessary evidence, the doctor and patient can undergo a series of referrals and discussions to arrive at a roadmap for a better and healthy lifestyle.
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Conflict of interest statement None declared.
Acknowledgment Also to be noted in the body text, the words “patient” and “subject” are referenced in synonymy. References
8.1.3. The counterparts A fair share of the genesis of the EHR was empowering the consumers [29]. Accessibility to one's health data is warranted by both the doctors and consumers. This makes a pervasive entity to undertake and amalgamate to advanced technologies like cloud computing [30], etc. Table 3 presents a comparative analysis of the existing EHR frameworks. While each has its pros and cons, none is superior to another per-se. The synchronization to the existing infrastructure and deployment and applicability strategies matters a lot. The harmonization of interoperability and standards of disparate contents of the EHR is vital. Standards can be stratified under vocabulary, context exchange, and clinical [31]. The report also suggests that Austria and Canada have the highest data exchange standard and adoption rate. Tables 5 and 6 exhibit enactment of HCIT standards in several countries. Vocabulary is quintessential for information exchange. Strict adherence to the protocol keeps the data from ambiguity and repetitiveness. There might be polymorphic nomenclature of the same technology, but differing with organization. To aid this, Controlled Medical Vocabularies (CMV) is considered which are detailed in Table 1 [31]. Clinical standards epitomize patient information in a more lucid fashion. They monitor the disease patient is suffering from, physician's recommendation of diagnostic tests and outlook on patient's condition, and the treatment given (Fig. 4). As per the specifications mentioned in [31] (which are considered minimal to any dataset designed to capture medical data of a patient), the following is a gist of the fields held. The details about the data-types, applicability and miscellaneous attributes can be studied in detail from the report [31] (Table 2).
9. Conclusion and summary With the standardization and proliferation of technology focussing medication, the G-Card will prove to be significantly useful in accessing nationwide healthcare status and thus aid the local and central governments to devise appropriate policies for unboxing better mechanisms to deal with a particular kind of a disease. It will also shed light on any limitations that the healthcare industry are facing in dealing with clinically oriented problems. The testing and therapeutics can have a wider scope, reaching out to different ethnicities and extrapolating methods of genetic medicine to all high and low. We have to ensure that sound health and good lifestyle, being every individual's right and necessity, get so delivered. Also, the predictions made out of generic data and the respective analyses are ostensible. To dredge out the actual actionable information, rigorous testing and repeated exhaustive analysis will be the ace. The G-Card can provide a foundation for such a process. To construe bio-markers is the most dramatic step in deciphering the key to good health. It can be used to provide valuable prescriptions to the patient for sustaining his/her fine health.
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Shaurya Jauhari is a research scholar in Bioinformatics at Jamia Millia Islamia, New Delhi, India since September 2012. Mr. Jauhari received his B.S. degree in Statistics,
Mathematics, and Computer Applications in 2005 from University of Lucknow, India and his MS degree in Computer Applications in 2009 from Uttar Pradesh Technical University, India. His research interests include cancer therapeutics, biomedical informatics, and biostatistics. Prior to working here, he served as a Network Assistant and a Software Engineer, from 2009 to 2012.
S.A.M. Rizvi is serving as Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India. With a vast academic experience and revered credibility, Dr. Rizvi is a frontrunner in interdisciplinary research and cross-platform training. His research interests include computer algorithms, artificial intelligence, bioinformatics, and design theory.
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