Group project slides of informatics infrastructure (1)
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Informatics involves turning data into useful information through standardized structures, digital evidence sources, data exchange standards, and processes that apply evidence to clinical situations. The key building blocks are standardized terminologies, digital health records, interoperability standards like HL7, and informatics skills. Informatics facilitates information sharing, improves healthcare quality and safety, and supports aggregating and applying clinical evidence to individual patients.
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Yehyun Park
Purdue University
01/02/2019
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Health Information Exchange (HIE) is an information system that promotes a secure sharing of critical information as well the inclusive access critical medical information about a patient electronically (Abdelhak et al, 2014). One merit of the use of such electronic systems in the U.S is that they occur in different verities. The HIE also offer different types of services. Evidently, a recent development has enabled the HIE systems to promote the Marketplace and regional institutional services concerning the health sector. The merit of HIE applications included the improvement of speed, Quality, safety and reduced relative prices of charge per patient for care. This is made possible by the quick sharing of critical information among the doctors, pharmacists, nurses among all the relevant health personnel. The HGIE systems are such that, they are technically enabled to provide quick response to information demand with the relevant urgency and thus aids in the making of vital patient’s data and medical progress devoid of medical errors, readmissions, and duplicate testing. The resulting system has a generally improved diagnosis.
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Data Standards, Data Quality, and Interoperability (2013
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Remove from myBoK
Editor's note: This update replaces the 2007 practice brief "Data Standards, Data Quality, and Interoperability."
Data quality and consistency are critical to ensuring patient safety, communicating delivery of health services, coordinating
care, and healthcare reporting. Assessing the quality and consistency of data requires data standards. This practice brief
provides health information management (HIM) professionals with a clear understanding of data standards as a tool to
enable interoperability and promote data quality.
The online version of this practice brief [...] is accompanied by an appendix that provides HIM professionals with a list of
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general data management processes to ensure information integrity and reliability. Evaluation of data validity, reliability,
completeness, and timeliness are accomplished through a combination of human and machine processes in healthcare, and
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Data Standards and Regulatory Framework
Data standards are "documented agreements on representations, formats, and definitions of common data. Data standards
provide a method to codify invalid, meaningful, comprehensive, and actionable ways, information captured in the course of
doing business." Rules to describe how the data is recorded to ensure consistency across multiple sources is another way to
think of data standards. Without data standards and data quality, the future of interoperability is bleak. Data fields and the
content of those fields need to be standardized.
Standards development organizations (SDOs) address a variety of aspects of health information and informatics. For
example, the American Society for Testing and Materials (ASTM) and Health Level Seven (HL7) target clinical data
standards. Insurance and remittance standards are a focus of the Accredited Standards Committee (ASC) X12. Standards to
transmit diagnostic images are developed through Digital Imaging and Communications in Medicine (DICOM). The
National Council for Prescription Drug Programs (NCPDP) represents pharmacy messages.
The Institute of Electrical and Electronics Engineers (IEEE), HL7, ASTM, and others develop data models and
frameworks. See the table on page 65 for a breakdown of regulatory agencies responsible for working with the American
National Standards Institute (ANSI) to drive data standards to achieve interoperability.
The AHIMA Leadership Model states that HIM professionals should serve as the leaders in healthcare organizations and in
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Data Standards, Data Quality, and Interoperability (2013
update)
Remove from myBoK
Editor's note: This update replaces the 2007 practice brief "Data Standards, Data Quality, and Interoperability."
Data quality and consistency are critical to ensuring patient safety, communicating delivery of health services, coordinating
care, and healthcare reporting. Assessing the quality and consistency of data requires data standards. This practice brief
provides health information management (HIM) professionals with a clear understanding of data standards as a tool to
enable interoperability and promote data quality.
The online version of this practice brief [...] is accompanied by an appendix that provides HIM professionals with a list of
standards to reference in data dictionary development, electronic health records, the exchange of health information, and
general data management processes to ensure information integrity and reliability. Evaluation of data validity, reliability,
completeness, and timeliness are accomplished through a combination of human and machine processes in healthcare, and
the list of data standard sources is a helpful reference guide when more detailed information is required.
Data Standards and Regulatory Framework
Data standards are "documented agreements on representations, formats, and definitions of common data. Data standards
provide a method to codify invalid, meaningful, comprehensive, and actionable ways, information captured in the course of
doing business." Rules to describe how the data is recorded to ensure consistency across multiple sources is another way to
think of data standards. Without data standards and data quality, the future of interoperability is bleak. Data fields and the
content of those fields need to be standardized.
Standards development organizations (SDOs) address a variety of aspects of health information and informatics. For
example, the American Society for Testing and Materials (ASTM) and Health Level Seven (HL7) target clinical data
standards. Insurance and remittance standards are a focus of the Accredited Standards Committee (ASC) X12. Standards to
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HI300 Unit 5 Standards for Electronic Data and Data Interchange -.docx
HI300 Unit 5: Standards for Electronic Data and Data Interchange - Discussion
Standard Development Organizations
Identify and research standard development organizations listed in the text on pp. 165–166
.
Select one of the organization’s websites and identify at least 3-4 facts about this organization and explain what it does.
Do not duplicate your classmates’ information. Note: You may explore the internet for recent articles about the organization and include this information as well.
When responding to your classmates describe similarities and differences between the organizations you researched.
Discussion responses should be strictly on topic, original with scholar references, and contribute to the quality of the discussion by making frequent informed references to lesson material.
NO PHARGIARISM!!
Below is the Chapter 4 reading for this assignment.
Standards for Electronic Data and Electronic Data Interchange
The original uniform data sets such as the UHDDS and the UACDS were created for use in paper-based (manual) health record systems. They were not designed to accommodate the data needs of the current healthcare delivery system or the demands of EHRs and clinical information systems.
Standards are needed in order for data to be easily, accurately, and securely communicated and exchanged electronically among various computer systems. This is referred to as interoperability. Without standards for interoperability, EHRs and the NHIN will not realize their full benefits (Thompson and Brailer 2004).
Many types of standards are being developed to support the EHR and health information exchange. Some involve defining record structure and content, others specify technical approaches for transmitting data, and still others provide rules for protecting the privacy and security of data.
Public and private organizations have been actively engaged in the process of developing healthcare informatics standards to support EHR development, interoperability, and information exchange. The federal government supports this work in a variety of ways. One example is the S&I Framework. According to Fridsma (2010 slide 4), the Framework “is the mechanism by which ONC will manage the implementation of specifications and the harmonization of existing health IT standards to promote interoperability nationwide.”
Definition of Data Standard for Electronic Data Exchange
Data standards provide the ability to record a certain data item in accordance with the agreed upon standard (Giannangelo 2007). Data content standards are “clear guidelines for the acceptable values for specified data fields” (Fenton et al. 2007). Data exchange standards are protocols that help ensure that data transmitted from one system to another remain comparable.
One of the purposes of HIPAA’s Administrative Simplification rules was to standardize information exchange and in August 2000, the Department of Health and Human Services (HHS) published regulations for electronic trans.
Amia now! session two
The document discusses how health information standards like HL7, X12N, LOINC and SNOMED enable interoperability between research information systems. It provides an overview of the HL7 Reference Information Model and vocabulary specifications that allow disparate clinical and administrative applications to exchange data. The presentation concludes with a discussion of City of Hope's Research Information Factory initiative to improve data sharing and analytics through a service-oriented architecture and integrated data repository based on health information standards.
CLOUD-BASED DEVELOPMENT OF SMART AND CONNECTED DATA IN HEALTHCARE APPLICATION
There is a need of data integration in cloud – based system, we propose an Information Integration and Informatics framework for cloud – based healthcare application. The data collected by the Electronic Health Record System need to be smart and connected, so we use informatica for the connection of data
from different database. Traditional Electronic Health Record Systems are based on different technologies, languages and Electronic Health Record Standards. Electronic Health Record System stores data based on interaction between patient and provider. There are scalable cloud infrastructures, distributed and heterogeneous healthcare systems and there is a need to develop advanced healthcare application. This advance healthcare application will improve the integration of required data and helps in fast interaction between the patient and the service providers. Thus there is the development of smart
and connected data in healthcare application of cloud. The proposed system is developed by using cloud platform Aneka.
J0956064
This document discusses health information technology (HIT) problems at Universiti Teknologi Malaysia's clinic. It begins with an introduction to HIT and its benefits, including cost reduction, quality improvement, and better patient experience. However, HIT implementation can be difficult and introduce new issues. The document then examines specific problems, including new errors from HIT systems, such as incorrect drug selections, and information overload for clinicians. It also notes challenges from the variety and complexity of clinic workflows. Interviews with clinic staff and doctors identified current HIT system problems at the Universiti Teknologi Malaysia clinic.
Public health information technology standards overview
The document summarizes the history and initiatives around establishing standards for health information technology and exchange in the US federal government from 2003-2010. It describes the Consolidated Health Informatics initiative which adopted messaging and vocabulary standards to allow federal agencies to share health information. It also discusses the Health Information Technology Standards Panel which worked to harmonize standards to enable information sharing and the certification criteria established in 2010 to ensure electronic health records can meet standards and achieve meaningful use.
Nur 3563 cis_group_project
This document summarizes a presentation on nursing informatics. It is split into sections created by 4 team members: Amanda, Tish, Amber, and Cindi. The sections discuss clinical information systems, their benefits and key players, components of electronic health records, clinical decision support systems, incorporating evidence-based practice, and costs, safety, education, and references related to implementing electronic health records.
ORIGINAL ARTICLEAn informatics framework for public health.docx
ORIGINAL ARTICLE
An informatics framework for public health
information systems: a case study
on how an informatics structure for integrated
information systems provides benefit in supporting
a statewide response to a public health emergency
Ivan J. Gotham • Linh H. Le • Debra L. Sottolano •
Kathryn J. Schmit
Received: 17 April 2013 / Revised: 8 October 2013 / Accepted: 23 January 2014 /
Published online: 8 February 2014
� Springer-Verlag Berlin Heidelberg 2014
Abstract This chapter illustrates how a well-established public health informatics
framework provides an integrated information system infrastructure that assures and
enhances the efficacy of public health emergency preparedness (PHEP) actions
throughout the phases of the health emergency event life cycle. Key PHEP activities
involved in supporting this cycle include planning; surveillance; alerting; resource
assessment and management; data-driven decision support; and intervention for
prevention and control of disease or injury in populations. Information systems
supporting these activities are most effective in assuring optimal response to an
emergent health event when they are integrated within an informatics framework
that supports routine (day to day) information exchange within the health infor-
mation exchange community. In late April 2009, New York State (NYS) initiated a
statewide PHEP response to the emergence of Novel Influenza A (H1N1), culmi-
nating in a statewide vaccination campaign during the last quarter of 2009. The
I. J. Gotham (&)
School of Public Health, Department of Health Policy Management University at Albany,
State University of New York , 1 University Place, Rensselaer, NY 12144, USA
e-mail: [email protected]
L. H. Le � K. J. Schmit
New York State Department of Health, Office of Information Technology Service,
Empire State Plaza, Room 148, Albany, NY 12237, USA
e-mail: [email protected]
K. J. Schmit
e-mail: [email protected]
L. H. Le
Department of Nursing, Sage College, Albany, NY 12180, USA
D. L. Sottolano
Center for Health Care Quality & Surveillance, New York State Department of Health,
875 Central Avenue, Albany, NY 12206, USA
e-mail: [email protected]
123
Inf Syst E-Bus Manage (2015) 13:713–749
DOI 10.1007/s10257-014-0240-9
http://crossmark.crossref.org/dialog/?doi=10.1007/s10257-014-0240-9&domain=pdf
http://crossmark.crossref.org/dialog/?doi=10.1007/s10257-014-0240-9&domain=pdf
established informatics framework of integrated information systems within NYS
conveyed significant advantages and flexibility in supporting the range of PHEP
activities required for an effective response to this health event. This chapter
describes, and provides, performance metrics to illustrate how a public health
informatics framework can enhance the efficacy of all phases of a public health
emergency response. It also provides informatics lessons learned from the event.
Keywords Public health informatics � Information systems �
.
CDSS implementation with CDA generation and integration for health informatio...
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 decision “making 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 .œClinical 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: http://www.ijtsrd.com/papers/ijtsrd14127.pdf http://www.ijtsrd.com/engineering/computer-engineering/14127/cdss-implementation-with-cda-generation-and-integration-for-health-information-exchange-in-cloud/pooja-n-umekar
A framework for secure healthcare systems based on big data analytics in mobi...
In this paper we introduce a framework for Healthcare Information Systems (HISs) based on big data
analytics in mobile cloud computing environments. This framework provides a high level of integration,
interoperability, availability and sharing of healthcare data among healthcare providers, patients, and
practitioners. Electronic Medical Records (EMRs) of patients dispersed among different Care Delivery
Organizations (CDOs) are integrated and stored in the Cloud storage area, this creates an Electronic
Health Records (EHRs) for each patient. Mobile Cloud allows fast Internet access and provision of EHRs
from anywhere and at any time via different platforms. Due to the massive size of healthcare data, the
exponential increase in the speed in which this data is generated and the complexity of healthcare data
type, the proposed framework employs big data analytics to find useful insights that help practitioners take
critical decisions in the right time. In addition, our proposed framework applies a set of security
constraints and access control that guarantee integrity, confidentiality, and privacy of medical information.
We believe that the proposed framework paves the way for a new generation of lower cost, more efficient
healthcare systems.
Advantages And Disadvantages Of EHR
1. The document discusses the advantages and disadvantages of implementing an electronic health record (EHR) system to replace a paper-based system.
2. A key disadvantage is the high cost of implementation, with the cost of Alberta's new clinical information system estimated at $1.6 billion over 10 years.
3. Another disadvantage is a lack of interoperability between existing EHR systems, which prevents patient information from being shared and understood across health settings.
iUZ.Talk - Cross-border Interoperability
iUZ has organised last 3rd July a talk about Cross-Border Interoperability and we've broadcasted live on Youtube.
This is the presentation document.
You can watch the event through our Youtube channel: http://youtu.be/k1KLgD8GF3Q
Application Sexual BehaviorGender and sexuality are intertwined.docx
Application: Sexual Behavior
Gender and sexuality are intertwined in many cultures. (Gardiner & Kosmitzki, 2011) Socialization agents teach the appropriate behaviors for gender and the acceptable sexual attitudes and behaviors within a culture. Cultural differences exist around the world and across countries. For example, cultural differences may exist through the number of partners allowed in a marriage, expectations for males and females, and knowledge and application of safe sex practices. Differences may also arise in what is permitted and acceptable, such as premarital sex, same-sex relationships, and extramarital relationships. The consequences for an individual deviating from these cultural expectations also vary from culture to culture.
For this Assignment,choose one sexual attitude (e.g., abstinence, monogamy, etc.) and one sexual behavior (e.g., chastity, infidelity, etc.).
The Assignment (4–5 pages)
· Use your Final Project culture of interest and select another culture of interest to you.
· Compare the similarities and differences of sexual attitudes and behaviors in each culture.
· Describe the cultural factors that influence sexual attitudes and behaviors.
· Explain how sexual attitudes and behaviors are perceived and displayed within each culture.
· Be specific and provide examples.
· Support your responses using the Learning Resources and the current literature.
Reference:
Gardiner, H., & Kosmitzki, C. (2011). Lives across cultures: Cross-cultural human development (5th ed.). Boston, MA: Prentice Hall.
Running head: MODERNIZING HEALTH INFORMATION INFRASTRUCTURE 1
MODERNIZING HEALTH INFORMATION INFRASTRUCTURE 6
Modernizing Health Information Infrastructure
Karese Holmes
HIMS 655 Health Data Management
Modernising Health Information Infrastructure
According to Davoudi et al., (2015) healthcare leaders experience challenges such as payment reform, exchange of health information, among others. Ideally, the nexus in the challenges is to ensure that data remains a trusted source that can be exchanged, shared, and accessed with ease. The American Health Information Management Association offers the basis of information and data governance through some fundamental principles. This principle includes accountability, transparency, integrity, protection, compliance, availability, retention, and disposition. The principles are critical for the data quality management model. Data quality management refers to the business process that guarantees the integrity of organisation information during the analysis, warehousing, application, and collection processes. The healthcare industry has some task to ensure a robust objective of the healthcare standards.
Significant limitation of the models
Data should apply security controls to offer data protection to guarantee data quality management in the American Health Information Management Association. Ideally, data needs to be protected in backup environments and stora.
Healthcare Interoperability: The Key to Leveraging Health Tech
Despite some setbacks, the digitalization of healthcare holds great promise for global health improvements. Health information technology (HIT) systems are taking over the healthcare industry.
For further information click here
https://www.mityung.com/
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Group project slides of informatics infrastructure (1)
- 1. What is informatics? Informatics is “the science and art of turning data into information.” (Hebda, 2013).
- 2. The building blocks of an informatics infrastructure are: Standardized terminologies and structures Digital sources of evidence Standards that facilitate healthcare data exchange Informatics processes that support the acquisition and application of evidence to a specific clinical situation Informatics competencies (Bakken, 2001). Let’s look at each of these in more detail.
- 3. Standardized terminologies and structures “Structured and controlled languages that have been developed according to terminology development guidelines and have been approved by an authoritative body.” (Hebda, 2013). This allows for information sharing between different applications. “The adoption of EHRs implemented with standardized terminology is proving to be a positive effect on the improvement of healthcare quality, efficiency, and patient safety.” (U.S. Department of Health and Human Services, 2009).
- 4. Data exchange standards Support the communication among computer- based systems to bring together patient data and decision logic. Facilitate the delivery of tailored health-related messages based on patient-specific data. Support aggregation of data across time and geography to link process to outcomes (Bakken 2001). In the past, data retrieval was primarily performed for use within a single institution. Changes in the healthcare delivery system now mandate exchange of client information between institutions (Hebda 2013)
- 5. Data exchange standards Health Level Seven International (HL7), an ANSI- accredited (standards developing organization (SDO), is the global authority on standards for interoperability of health information technology. HL7 does not develop software. It creates standards that allow healthcare information to be communicated across and between healthcare enterprises and communities. HL7 standards facilitate the exchange of clinical and administrative data among health information systems (Health Level Seven International 2007-2012).
- 6. Data exchange standards HL7 provides a comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery, and evaluation of health services (Health Level Seven International 2007-2012).
- 7. Informatics processes that support the acquisition and application of evidence to a specific clinical situation Integrate and link heterogeneous sources of evidence. Present clinician alerts related to potential adverse events. Use decision analytic techniques to tailor evidence to specific patients. Perform data modeling and aggregation in clinical data repositories. Perform data mining (Bakken 2001).