cdss implementation with cda generation and integration for health information exchange in cloud

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@ IJTSRD | Available Online @ ww ISSN No: 245 Inte R CDSS imple and integration for Pooja N. Umekar, Dr. H R. Department of Computer Scie ABSTRACT Electronic health record helps to impro and quality care of every individual p that to be stored in various hospital t information exchange. The clinic architecture(CDA) developed by seven(HL7) is core document standar interoperability of the document. reluctant to adopt interoperable hospita system due to its deployment cost ex handful countries. A problem arises eve hospitals start using the CDA docu because the data scattered in different d hard to manage. CDA document ge integration Service based on clou through which hospitals are enabled to generate CDA document per patient CDA document and physician and browse the clinical data in chronological To improve the accuracy and speed health care system is important to prov and efficient way. A clinical decision s (CDSS) is a health information techn that is designed to provide physicians an professionals with clinical decision su that is assistance with clinical decision The system is designed by using variou techniques to assist the diagnosis symptoms. Our system is designed wi Naïve Bayesian classification techniqu overcome the various data mining diagnose the patient symptoms. The N classification technique provide the d disease with the help of symptoms occur ww.ijtsrd.com | Volume – 2 | Issue – 4 | May-J 56 - 6470 | www.ijtsrd.com | Volum ernational Journal of Trend in Sc Research and Development (IJT International Open Access Journ ementation with CDA generatio r health information exchange Deshmukh, Prof. O. A. Jaisinghani, Prof ence & Engineering, DRGIT&R, Amravati, Mah ove the safety patient details, through health cal document Health level rd that ensure Hospitals are al information xcept for in a en when more ument format documents are eneration and ud computing o conveniently into a single patients can l order. of diagnosis, vide the faster support system nology system nd other he alth upport (CDS), making tasks. us data mining of patient’s ith the help of ue which has technique to Naïve Bayesian diagnosis of rs to the patient .“Clinical decision sup observations with health kn health choices by clinicians fo system implement (CDSS) c system looking towards the decision support system diagn patient and also the CDA is g in XML form and also it ca various platforms. With the time of patient would be saved of the patient is done. Keywords: Health informatio cloud computing, software privacy preserving 1. INTRODUCTION Electronic health record is th of patient and populatio information in digital format shared across different health shared through network information system or other i exchanges. Electronic health r range of data including st medication and allergies, personal statestics like age Health Level Seven has estab standard for clinical documen markup standard that speci semantics of ‘clinical docum exchange. The first version of 2001 [2]. Many projects gen entirely used in many coun Jun 2018 Page: 885 me - 2 | Issue 4 cientific TSRD) nal on e in cloud S.V. Khedkar harashtra, India pport systems link health nowledge to influence or improved health. Our clinical decision support e system CDSS clinical nose the diseases of the generated which will be an be integrated through help of this system the d and accurate diagnoses on exchange( HL7) CDA, as a service, CDSS , he systematize collection on electronically stored t. These records can be h care centers, record are connected, and vast information network and records (EHR) it include tatic medical history , immunization status, and weight , sex [1]. blished CDA as a major nts. CDA is a document ifies the structure and ments’ for the purpose of f CDA was developed in nerating CDA have been ntries. Active works are

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Electronic health record helps to improve the safety and quality care of every individual patient details, that to be stored in various hospital through health information exchange. The clinical document architecture CDA developed by Health level seven HL7 is core document standard that ensure interoperability of the document. Hospitals are reluctant to adopt interoperable hospital information system due to its deployment cost except for in a handful countries. A problem arises even when more hospitals start using the CDA document format because the data scattered in different documents are hard to manage. CDA document generation and integration Service based on cloud computing through which hospitals are enabled to conveniently generate CDA document per patient into a single CDA document and physician and patients can browse the clinical data in chronological order. To improve the accuracy and speed of diagnosis, health care system is important to provide the faster and efficient way. A clinical decision support system CDSS is a health information technology system that is designed to provide physicians and other health professionals with clinical decision support CDS , that is assistance with clinical decisionmaking tasks. The system is designed by using various data mining techniques to assist the diagnosis of patients symptoms. Our system is designed with the help of Naïve Bayesian classification technique which has overcome the various data mining technique to diagnose the patient symptoms. The Naïve Bayesian classification technique provide the diagnosis of disease with the help of symptoms occurs to the patient .Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health. Our system implement CDSS clinical decision support system looking towards the system CDSS clinical decision support system diagnose the diseases of the patient and also the CDA is generated which will be in XML form and also it can be integrated through various platforms. With the help of this system the time of patient would be saved and accurate diagnoses of the patient is done. Pooja N. Umekar | Dr. H R. Deshmukh | Prof. O. A. Jaisinghani | Prof S.V. Khedkar "CDSS implementation with CDA generation and integration for health information exchange in cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd14127.pdf Paper URL: http://www.ijtsrd.com/engineering/computer-engineering/14127/cdss-implementation-with-cda-generation-and-integration-for-health-information-exchange-in-cloud/pooja-n-umekar

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Page 1: CDSS implementation with CDA generation and integration for health information exchange in cloud

@ IJTSRD | Available Online @ www.ijtsrd.com

ISSN No: 2456

InternationalResearch

CDSS implementation with CDA generationand integration for health information exchange in cloud

Pooja N. Umekar, Dr. H R. DeshmukhDepartment of Computer Science

ABSTRACT Electronic health record helps to improve the safety and quality care of every individual patient details,that to be stored in various hospital through health information exchange. The clinical document architecture(CDA) developed by Health level seven(HL7) is core document standard that ensure interoperability of the document. Hospitals are reluctant to adopt interoperable hospital information system due to its deployment cost except for in a handful countries. A problem arises even when more hospitals start using the CDA document format because the data scattered in different documents are hard to manage. CDA document generation and integration Service based on cloud computing through which hospitals are enabled to conveniently generate CDA document per patient into a single CDA document and physician and patients can browse the clinical data in chronological order.

To improve the accuracy and speed of diagnosis, health care system is important to provide the faster and efficient way. A clinical decision support system (CDSS) is a health information technology system that is designed to provide physicians and other heprofessionals with clinical decision support (CDS), that is assistance with clinical decision –The system is designed by using various data mining techniques to assist the diagnosis of patient’s symptoms. Our system is designed with the Naïve Bayesian classification technique which has overcome the various data mining technique to diagnose the patient symptoms. The Naïve Bayesian classification technique provide the diagnosis of disease with the help of symptoms occurs to the

@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 4 | May-Jun 2018

ISSN No: 2456 - 6470 | www.ijtsrd.com | Volume

International Journal of Trend in Scientific Research and Development (IJTSRD)

International Open Access Journal

lementation with CDA generationand integration for health information exchange in cloud

Dr. H R. Deshmukh, Prof. O. A. Jaisinghani, Prof Science & Engineering, DRGIT&R, Amravati, Maharashtra, India

Electronic health record helps to improve the safety and quality care of every individual patient details,

stored in various hospital through health information exchange. The clinical document architecture(CDA) developed by Health level seven(HL7) is core document standard that ensure interoperability of the document. Hospitals are

rable hospital information system due to its deployment cost except for in a handful countries. A problem arises even when more hospitals start using the CDA document format because the data scattered in different documents are

generation and integration Service based on cloud computing through which hospitals are enabled to conveniently generate CDA document per patient into a single CDA document and physician and patients can browse the clinical data in chronological order.

To improve the accuracy and speed of diagnosis, health care system is important to provide the faster

A clinical decision support system (CDSS) is a health information technology system that is designed to provide physicians and other health

ecision support (CDS), –making tasks.

The system is designed by using various data mining techniques to assist the diagnosis of patient’s

Our system is designed with the help of on technique which has

come the various data mining technique to diagnose the patient symptoms. The Naïve Bayesian

vide the diagnosis of with the help of symptoms occurs to the

patient .“Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health. Our system implement (CDSS) clinical decision support system looking towards the system CDSS clinicaldecision support system diagnose the diseases of the patient and also the CDA is generated which will be in XML form and also it can be integrated through various platforms. With the help of this system the time of patient would be saved and accurate diaof the patient is done.

Keywords: Health information exchange( HL7) CDA, cloud computing, software as a service, CDSS , privacy preserving

1. INTRODUCTION

Electronic health record is the systematize collection of patient and population electronicallyinformation in digital format. These shared across different health care centers, record are shared through network connected,information system or other information network and exchanges. Electronic health records (EHR) itrange of data including static medical history , medication and allergies, immunization status, personal statestics like age and weight , sex [1]. Health Level Seven has established CDA as a major standard for clinical documents. CDA is a documentmarkup standard that specifies the structure and semantics of ‘clinical documents’ for the purpose of exchange. The first version of CDA was developed in 2001 [2]. Many projects generating CDA have been entirely used in many countries. Active works are

Jun 2018 Page: 885

6470 | www.ijtsrd.com | Volume - 2 | Issue – 4

Scientific (IJTSRD)

International Open Access Journal

lementation with CDA generation and integration for health information exchange in cloud

S.V. Khedkar Maharashtra, India

patient .“Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health. Our system implement (CDSS) clinical decision support system looking towards the system CDSS clinical decision support system diagnose the diseases of the patient and also the CDA is generated which will be in XML form and also it can be integrated through various platforms. With the help of this system the time of patient would be saved and accurate diagnoses

Health information exchange( HL7) CDA, cloud computing, software as a service, CDSS ,

Electronic health record is the systematize collection of patient and population electronically stored

mation in digital format. These records can be shared across different health care centers, record are shared through network connected, and vast information system or other information network and

Electronic health records (EHR) it include range of data including static medical history , medication and allergies, immunization status, personal statestics like age and weight , sex [1]. Health Level Seven has established CDA as a major standard for clinical documents. CDA is a document markup standard that specifies the structure and semantics of ‘clinical documents’ for the purpose of exchange. The first version of CDA was developed in 2001 [2]. Many projects generating CDA have been entirely used in many countries. Active works are

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International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470

@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 4 | May-Jun 2018 Page: 886

being done on improving interoperability based on open Electronic Health Records.

Our system consist of CDA generation with implementation of CDSS with the information exchange in cloud , basically the system will generate CDA with the help of patient’s information provided to the system , the CDA document consist of the general information provided by patient like his personal details and also the and then the CDSS is generated and when the sharing of CDA takes place privacy is preserved by encrypting the contact number of the patient so we can say that if any of the patient is suffering from disease first the patient is not carring the previous records of health issues so the doctor will be able to see the previous history and with the help of that doctor will be able to select the symptoms and give the prescription to patient.

2. LITERATURE REVIEW

Health Level Seven has established CDA as a major standard for clinical documents [3]. CDA is a document markup standard that specifies the structure and semantics of ‘clinical documents’ for the purpose of exchange. The first version of CDA was developed in 2001 and came out in 2005 [2]. Many projects adopting CDA have been successfully completed in many countries [4]. Active works are being done on improving semantic interoperability based on open Electronic Health Record [7]. To establish confidence in Health Information Exchange interoperability, more Health Information Services’s need to support CDA. However, the structure of CDA is complicated and the production of correct Clinical Document Architecture document is hard to achieve without understanding of the CDA sufficient experience with it. In addition, development the Health information system for hospitals vary so greatly that generation of CDA documents in hospital invariably requires a separate CDA generation system. The, hospitals are very reluctant to adopt a new system unless it is absolutely necessary for provision of care. As it is clear that the result, the adoption rate of EHR is very low except for in a few countries such as New Zealand or Australia [9]. In the few years the XML has became the important standard for exchange of information in health care services. When a patient is diagnosed at a clinic, a CDA document record is generated. The CDA document can be shared with other clinics if the patient agrees. The concept of family doctor does not exist in some countries, hence

it is common for a patient to visit a number of different clinics.

The exchange process of CDA document is in the following cases: when a doctor needs to study a patient’s medical history; when referral and reply letters are drafted for a patient cared by multiple clinics; when a patient is in emergency and the medical history needs to be reviewed. It takes increasing amount of time for the medical personnel record as the amount of exchanged CDA document increases because more documents means that data are distributed in different documents. This significantly delays the medical personnel in making decisions. Hence, when all of the CDA documents are integrated into a single document, the medical personnel is empowered to review the patient’s clinical history conveniently in chronological order. In general , hospitals information system are operated independently of each other. We propose a next generation hospital information system (HIS) based on HL7, clinical document architecture (CDA) including also an electronic health record and a clinical data repository (CDR) to enable the data sharing of medical information among medical and health information among health and medical institutions . We designed an XML schema through which an effective clinical document was generated from the HIS after defining the item regulations and the templates.

3. PROPOSED WORK

The system is going to perform follows.

The CDA document is generated in XML format.

The CDA will consist of the information of the patient the information consist of the name , patient id , symptoms etc

The CDA will be generated on two platforms, the information will be integrated from one to other platform.

The main purpose of our system is to implement CDSS with generation of CDA and integrating the health information exchange.

The system is going to give or create the cloud atmosphere.

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International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456

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CDA location Data items

CDA HEADER: Document

Information (creation time, template ID, language code, purpose) Patient’s information (ID, name, information (ID, name, represented Organization’s information (name,address, phone number)

CDA Body: Payers Advance

Directives Support Functional StatusProblems Family History Social History Allergies Symptoms Procedures Encounters Plan of Care

TABLE 1: CDA DOCUMENT:

4. CDSS IMPLEMENTATION

Fig 4.1 cdss system working

The above diagram shows the overall architecture of how CDSS it shows the actual working.

1. CDA generation generates CDA documents. .

2. CDA generation Interface uses the API provided by the cloud and relays the input data and receives CDA documents generated on cloud .

3. Template manager is responsible for managing the CDA documents generated in cloud server.

4. CDA generator collects patients data from hospital and generates CDA documents in template

5. CDA validator inspects whether the generated CDA documents complies with a CDA document complies with a CDA schema standards

International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456

@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 4 | May-Jun 2018

Information (creation time, template ID, language code, purpose) Patient’s information (ID, name, information (ID, name,

organization) Organization’s information (name,

Functional Status Problems Family History Social

Medications Procedures Encounters Plan

working

The above diagram shows the overall architecture of

CDA generation generates CDA documents. .

CDA generation Interface uses the API provided by the cloud and relays the input data and receives

nerated on cloud .

Template manager is responsible for managing the CDA documents generated in cloud server.

CDA generator collects patients data from hospital rates CDA documents in template.

CDA validator inspects whether the generated CDA documents complies with a CDA document

CDA schema standards.

6. The CDSS is generatedsymtomps to the systems diagnose.

The following steps takes place

1: Doctor Register with the System.

2: Doctor has to login the system with his authenticemail-id and password.

3: Doctor can add / edit / update /delete any number of disease, their symptoms, and their prescriptioninformation.

4: Doctor add patient information along with thesymptoms he is suffering from to the database andcheck for diagnosis.

5: Using Database will provide the historical medical data present in our database and processing with the help of Naïve Bayesian classifier algorithm.

6: After calculation, the predicted result will be send to the next level. On this level the probability of predicted disease risk will be calculated and top three disease having probability of more than 50% are displayed. In this algorithm the maximum probability disease risk will be calculated.

7: Now doctor check the patient symptoms once again and from the result generated in step 6, he suggest most suitable prescription for patient. Finally, proper predicted diseases willhelp to give proper prescription to the patients moreeffectively.

8: For more proper CDSS designing, doctor review his prescription suggested to the patient. Here he checks that, the patient gets cure form his providedprescription or not. If the patient gets cure then go tostep 9 or stop otherwise.

9: Check for any new symptoms that the patient issuffering from and already our CDSS data have. If any new symptoms are identified, Retrain symptoms to the particular database by addparticular disease For example: The CDSS is mainly used to diagnose the disease the symptoms are provided in the database and with the help of those symptoms , the diseases are being diagnose with the help of naviebayes algorithm.

International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470

Jun 2018 Page: 887

The CDSS is generated, when we give the symtomps to the systems in CDSS the disease is

takes place in CDSS,

Doctor Register with the System.

Doctor has to login the system with his authentic

Doctor can add / edit / update /delete any number disease, their symptoms, and their prescription

patient information along with the symptoms he is suffering from to the database and

Using Database will provide the historical medical present in our database and processing with the

Naïve Bayesian classifier fuzzywuzzy search

After calculation, the predicted result will be send the next level. On this level the probability of

disease risk will be calculated and top three having probability of more than 50% are

this algorithm the maximum probability will be calculated.

Now doctor check the patient symptoms once and from the result generated in step 6, he

suitable prescription for patient. Finally, predicted diseases will be diagnose, this will give proper prescription to the patients more

For more proper CDSS designing, doctor review prescription suggested to the patient. Here he

that, the patient gets cure form his provided n or not. If the patient gets cure then go to

Check for any new symptoms that the patient is suffering from and already our CDSS data have. If

new symptoms are identified, Retrain symptoms to the particular database by adding symptoms to

For example: The CDSS is mainly used to diagnose the disease the symptoms are provided in the database and with the help of those symptoms , the diseases are being diagnose with the

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International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470

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4.1. Work flow diagram of CDSS

Fig 4.1: the fig shows the how actually the cdss works.

5. ADVANTAGES:

Construction of a cloud computing environment and deployment of CDA generation and integration system based on it.

Generation of CDA documents on different developer platforms through Cloud.

CDSS have number of quality improvement benefits, including health care quality and enchanced patient outcomes.

Avoidance of errors and adverse events

Improves cost benefits and provider and patient satisfaction.

6. LIMITATIONS:

As a number of HIE based on CDA documents increases , interoperability is achieved ,but it also brings a problem while managing various CDA documents per patient becomes inconvenient as the clinical information for each patient is scattered in different documents .

The following problems were encountered while developing our CDA document generation and integration system. First, the default language of the Amazon Cloud OS is US English and it did not adequately handle Korean language.

CONCLUSION:

In this paper interoperability between hospitals not only helps improves patient safety and quality of service. It reduces time and resources spent on data format conversion. It avoids errors, it will show the correct information of the patient which is saved.

REFERENCES:

1. sung –hung lee , Jounhyunsmg ,and konkim “CDA generation and integration for health information exchange based on cloud computing systems “vol no 2 ,march / april 2016.

2. R. H. Dolin, L. Alschuler, S. Boyer, C. Beebe, F. M. Behlen, P. V.Biron, and A. Shabo, “The HL7 Clinical Document Architecture,” J. Am. Med. Inform. Assoc., vol. 13, no. 1, pp. 30–39, 2006.

3. R. H. Dolin, L. Alschuler, C. Beebe, P. V. Biron, S. L. Boyer, D. Essin, E. Kimber, T. Lincoln, and J. E. Mattison, “The HL7 Clinical Document Architecture,” J. Am. Med. Inform. Assoc., vol. 8, pp. 552–569, 2001

4. M. L. M€uller, F. Ǖckert, and T. B€urkle, “Cross-institutional data exchange using the clinical document architecture (CDA),” Int. J. Med. Inform., vol. 74, pp. 245–256, 2005.

5. H. Yong, G. Jinqiu, and Y. Ohta, “A prototype model using clinical document architecture (cda) with a japanese local standard: designing and implementing a referral letter system,” ActaMedOkayama, vol. 62, pp. 15–20, 2008..

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7. C. Mart_ınez-Costa, M. Men_arguez-Tortosa, and J. Tom_asFern_andez-Breis, “An approach for the semantic interoperability of ISOEN 13606 and OpenEHR archetypes,” J. Biomed.Inform., vol. 43,no. 5, pp. 736–746, Oct. 2010.

8. MR. Santos, MP. Bax, and D. Kalra, “Building a logical HER architecture based on ISO 13606 standard and semantic webtechnologies,” Studies Health Technol. Informat., vol. 160, pp. 161–165, 2010

9. K. Ashish, D. Doolan, D. Grandt, T. Scott, and D.W. Bates, “Theuse of health information technology in seven nations, ”Int. J. Med. Informat., vol. 77, no. 12, pp. 848–854, 2008