User:MDPNP/sandbox

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DRAFT[edit]

Medical Device "Plug-and-Play" Interoperability Program[edit]

Medical Device "Plug-and-Play" Interoperability Program
Established November 1st 2004
Director Julian Goldman, MD
Location Massachusetts General Hospital, Cambridge, MA, United States
Website www.mdpnp.org

Overview[edit]

The Medical Device "Plug-and-Play" Interoperability Program (MD PnP program), established in 2004, has become a recognized leader in the development of the concepts and capabilities for integrated clinical environments of the future. MD PnP Program research accelerates the adoption of medical device interoperability by providing interoperability building blocks ( use cases, standards, a neutral lab environment, and open research tools) and by changing clinical and market expectations of what can be achieved.

The program is affiliated with Massachusetts General Hospital (MGH), CIMIT (Consortia for Improving Medicine with Innovation & Technology), and Partners HealthCare System, with additional support from ( TATRC)), NIH/ NIBIB, and other federal agencies. Having evolved from the OR of the Future program at MGH, the MD PnP Program remains clinically grounded. The program takes a multi-faceted approach to addressing key barriers to achieving interoperability, including the development and support of suitable open standards (e.g. ASTM F2761-09 Integrated Clinical Environment, or ICE), and the elicitation, collection and modeling of clinical use cases and engineering requirements for the ICE platform and “ecosystem”.

The interdisciplinary, multi-institutional program team collaborates with diverse stakeholders (clinicians, biomedical and clinical engineers, academic engineering programs, healthcare delivery systems, regulatory agencies, medical device vendors, standards development organizations). Since the program’s inception, more than 800 clinical and engineering experts, and representatives of more than 100 companies and institutions have participated in plenary workshops/conferences, working group meetings, and focus groups to help shape the common goals and contribute their expertise.

The MD PnP Lab provides a vendor-neutral “ sandbox” to evaluate the ability of candidate interoperability solutions to solve clinical problems, to model clinical use cases (in a simulation environment), to develop and test related network safety and security systems, and to support interoperability and standards conformance testing.

History[edit]

The architecture and concepts embodied in the Integrated Clinical Environment (ICE) Standard [1] originated in the 2004 OR of the Future Plug-and-Play kick-off meeting [2]. Development of the standard, its publication, and use, parallels the growth and increased levels of support of the MD PnP Program’s research on medical device interoperability and safe medical device/HIT system integration.

Issues of medical device interoperability are apparent in the OR environment, given the range of disparate equipment used and the need to coordinate devices with clinical care. How to better address and deal with hazards caused by the absence of integration of devices and therapies was one theme of a meeting of stakeholders in 2004. From this meeting came the vision described by Dr. Julian Goldman for building the foundation for medical device plug-and-play interoperability: “an architectural framework for self-configuring, self-describing devices that enable devices to be automatically configured when connecting to a network, communicating their capabilities and control information to any appropriate control application or device. Eventually, all medical devices will interconnect through standardized hardware and software.”

Approach[edit]

Systems engineering approach to med device interop FOR patient safety and innovation.

Mission[edit]

The MD PnP Program is accelerating the adoption of medical device interoperability to enable the creation of complete and accurate electronic health records and the cost-effective development of innovative third-party medical “apps” for diagnosis, treatment, research, safety and quality improvements, equipment management, and adverse event detection and reporting when using networked medical devices for clinical care.

The MD PnP research team is working to develop sharable databases, tools, and applications that will enable a broader community of researchers and manufacturers to implement medical device interoperability. The program aims to reduce key barriers to achieving interoperability through:

  • Development and support of suitable open standards (e.g. ASTM F2761, Integrated Clinical Environment, or “ICE”)
  • Elicitation, analysis, and modeling of clinical use cases and system engineering requirements for an open architecture instantiation of ICE as a platform and “ecosystem”
  • Alignment of clinical, manufacturer, and FDA regulatory expectations
  • Implementation of prototype use cases in an open “sandbox” environment

Projects/Work of MD PnP Program[edit]

Clinical Scenario Development[edit]

A clinical scenario is a brief description of a clinical situation or event. MD PnP researchers use clinical scenarios to provide background and illustrate the need for the development of technical solutions. For each situation described, a clinical scenario will provide:

  • the Current State, typically an adverse event that has occurred to a patient
  • the Proposed State, a brief illustration of the improvement in safety and effectiveness obtained by

applying an integrated solution

Clinical Scenario Repository (CSR)[edit]

The Clinical Scenario Repository™ (CSRTM) is a web-based tool to help collect data to support a learning healthcare system to improve patient safety and the quality of clinical care. The CSR is intended to enable clinicians and non-clinicians (including patient’s family members) to document actual or potential adverse events, especially related to systems issues that are caused by or can be mitigated by device-integration based technology solutions. These “scenarios” will assist the healthcare community, including researchers, standards developers, regulators, and manufacturers, to solve intractable clinical system problems. The focus is on identifying and mitigating hazardous situations related to workflow, product usability, data integration, and the lack of effective medical device-HIT system integration. Collecting better event information and proposed solutions can help identify opportunities to improve existing devices and create new, more effective healthcare delivery.

Clinical Goals A primary motivating factor of the CSR is to collect information that is not currently collected, and by being under-reported, problems are not being solved. For example, numerous deaths and other preventable adverse events are caused by patient-controlled analgesia (PCA), but unless the infusion pump malfunctions, neither the adverse event nor suggestions for safer implementation of PCA (e.g. safety interlock with physiologic data) is reported by clinicians or patients to any identified national authority. The CSR would facilitate the reporting of this type of event to generate national data to identify and prioritize solutions. It will have a “like” function to reduce data re-entry and add a social networking aspect. The CSR is intended to acquire de-identified data from a different perspective as compared to the traditional reporting methodology. The Medical Device Reporting (MDR) regulation (21 CFR 803.1) requires that manufacturers and health professionals “report deaths and serious injuries that (a) device has or may have caused or contributed to.” These reports are used to “protect the public health by helping to ensure that devices are … safe and effective for their intended use.” The adverse event reports focus on capturing and documenting the event data (e.g. date of event, date of report, description of event), details on the medical device (e.g. manufacturer, serial number) and basic patient demographics. In contrast to the MDR, the perspective of the CSR is to identify events and/or elicit ideas for system-level solutions that cross the boundaries of specific manufacturers, regulated and non-regulated products, diverse users, and practice variability.

Technical Description The CSR, now in beta, has been designed as a flexible, scalable solution built on the Google Application Engine. The user interface is based on a tabbed design that allows easy navigation, selection and entry of information describing and documenting the clinical scenario (scenario description, identified contributing factors, description of clinical environment and equipment used), and proposals to address this scenario through changes in workflow, environment, and equipment. The system utilizes a dynamic client-server communication mechanism to allow the user to enter the information available at the moment and to save one’s progress based upon Asynchronous JavaScript and XML. Scenarios are intended to mature from initial entry as the result of collaborative interaction among users before being “approved” for general access. The database will be curated by having scenarios approved (content validated), returned to the user for additional clarification, or rejected by an administrator (administrator approval includes screening for privacy and other concerns). Additional functionality includes the ability to search data fields for keywords. To encourage collaboration, scenarios can be entered and reviewed only by registered users. [3]

Device Clock Synchronization[edit]

Unlike a cell phone or computer, most medical devices do not set their clocks using a network time reference. Like an old-fashioned VCR, the clocks are typically set manually twice a year for daylight savings time, or when the medical devices are serviced. The absence of automatic clock-setting capabilities in most devices—and the lack of time synchronization among the wide array of different medical devices used in a typical hospital—can result in inaccurate time-stamps of clinical data recorded in the electronic medical record (EMR). These inaccuracies also complicate the synchronization of data from multiple devices when analyzing adverse events. There is no widely adopted standard for medical device time management and no implementation guidelines are available. The MD PnP Program is documenting this problem and researching potential solutions.

Research Studies[edit]

Two studies (unpublished) have documented the problem–

  • Evaluation of the extent of the problem in 5 hospitals, by documenting medical device clock errors
  • Assessment of the personnel workload/cost required to manually perform DSTclock-changes

These studies are being funded by NIH/NIBIB and DoD/TATRC.

Related: HHS released Meaningful Use Stage 2 requirements on August 23, 2012

In this Final Rule, HHS reasserted the use of accurate time and date stamping of EHR data:

(g) “Synchronized clocks. The date and time recorded utilize a system clock that has been synchronized following (RFC 1305) Network TimeProtocol, (incorporated by reference in § 170.299) or (RFC 5905) Network Time Protocol Version 4, (incorporated by reference in § 170.299).”

For convenience, several of the 45 CFR 170 references to synchronized clocks have been provided. [4]

Integrated Clinical Environment[edit]

Interdisciplinary meetings convened by the MD PnP program identified key capabilities of a patient-centric integrated clinical environment. These capabilities, such as comprehensive data acquisition for the EMR and the integration of devices to enable real-time decision support, safety interlocks, and closed-loop control, can be achieved through the functions described in a new series of standards for the "Patient-Centric Integrated Clinical Environment" (ICE).

Forensic Data Logger[edit]

Medical devices are increasingly being networked, for example to populate the electronic health record (EHR). Problems with individual devices in such a system, or unexpected interactions between the devices, can cause device failures and may compromise patient safety. For example, the MD PnP Lab has documented a case of ventilator failure triggered by requesting data to send to the EHR. When this kind of incident occurs, clinicians, manufacturers, and regulators have the responsibility to investigate the cause of the problem and try to ensure that it does not happen again.

Planes, trains, and automobiles have “ black box recorders” – or “ data loggers” to support forensic data analysis. There is growing support for the belief that this capability is essential for clinical environments as well. [5]As described in standard ASTM F2761-09 on the Integrated Clinical Environment (ICE), even-logging functionality is necessary to address regulatory and liability concerns regarding networked medical device systems, and will also improve the forensic analysis of clinical adverse events and near misses.

The MD PnP Program is implementing a basic ICE Data Logger that will capture device and use data intended to facilitate analysis of adverse events and enable other types of analysis of device networks, and are planning to develop a functional prototype Data Logger that will capture data from medical devices in a time-synchronized, standardized, and trustworthy manner. This work will preview the power of these emerging capabilities, as existing standards do not yet support all the data that is needed from devices for recording and later analysis.

MD FIRE[edit]

Medical Device "Free Interoperability Requirements for the Enterprise" (MD FIRE) comprises a white paper and sample RFP and contracting language to promote the adoption of fully interoperable medical devices and systems in support of patient safety. Released on October 16, 2008, the MD FIRE document was drafted by the MD PnP Program's Interoperability Contracting Requirements Working Group, with convened experts from CIMIT, Massachusetts General Hospital, Partners HealthCare, Kaiser Permanente and Johns Hopkins. The MD FIRE document contains background and rationale, sample RFP terms and sample contract terms, and may be shared under the Creative Commons Attribution-Share Alike license. Released in August, 2012, the latest version of the MD FIRE document adds the U.S. Department of Veterans Affairs (VA) as a signatory, and is available on the MD PnP website. [6]

Participating Healthcare Delivery Organizations

  • Massachusetts General Hospital*
  • Partners HealthCare System*
  • Kaiser Permanente*
  • Johns Hopkins Medicine*
  • U.S. Department of Veterans Affairs

Open ICE[edit]

The MD PnP Program has developed an open source implementation of the Integrated Clinical Environment (ICE) standard as described in ASTM 2761-09(2013) and made it freely available on SourceForge. The platform consists of software device adapters for medical devices (including anesthesia machines, ventilators, and patient monitors), OMG DDS standard middleware, and demonstration applications. Research applications can be built on this platform to implement smart alarms, physiologic closed-loop control algorithms, data visualization, and clinical research data collection.

MD PnP is forming a broad user/developer community to inform the direction of development, operating under thebelief that this OpenICE implementation will reduce the time and cost of performing clinical studies, and lead to the development of an ecosystem of commercial and research interoperable apps and devices.

MDIDS[edit]

A reference compendium of medical device interface capabilities and data elements is in development which could enable more complete, effective, and safe device integration. This compendium, called Medical Device Interface Data Sheets (MDIDS), will serve as a reference for standards development organizations (SDOs), manufacturers, researchers, and clinical organizations.

  • Clinical organizations are contributing interface capabilities that will support more effective device-to-EMR integration, innovative clinical care, and more effective clinical management.
  • Medical device manufacturers are contributing expertise to ensure completeness of the MDIDS.
  • Standards development experts are matching MDIDS data elements to existing standards and helping to identify standards gaps that must be addressed.

HITSA[edit]

The inability of IT experts to investigate medical errors as a root cause of an issue with an IT symptom hampers all investigations, even those in which medical errors are not a root cause. The FDA manages medical device safety on a per-manufacturer or per-device basis. They don’t appear to have a process to investigate adverse events and perform a root cause analyses at a system level of vendors, medical devices, non-medical HIT equipment, installation options, and clinical usage. And most importantly, work with all of these parties to mitigate future risks as technologies and practice change.

The MD PnP Program envisions the creation of an “HIT Safety Administration” (HITSA) (or "Safety Board") that could, in collaboration with vendors, hospitals, NIST, ONC and FDA (and NLM and NSF) provide a test bed for HIT systems prior to deployment and for solving problems when they develop. Proposed standards and technologies could be assessed and problems addressed prior to adoption. Root cause analysis of adverse events and near misses could be performed in collaboration with vendors, as needed. Product defects or configuration problems could be addressed horizontally and solutions coordinated across industry, instead of by each hospital-vendor pair. Facilitation of adverse event analysis involving HIT systems may require the application of technologies that have been successful elsewhere, such as “black box” recorders for network medical device/HIT data.

SmartAmerica Testbed Challenge & Medical Device Cyber Physical Systems[edit]

The MD PnP program is deeply involved in the emerging discipline of cyber physical medical device systems (CPS). Opportunities for CPS-enabled innovation in medical device technology include, as examples, the introduction of coordinated interoperation of autonomous and adaptive devices, as well as new concepts for managing and operating physical medical systems using computation and control, miniaturized implantable smart sensing and actuating platforms, energy harvesting, body area networks, programmable materials, and new fabrication approaches such as 3D printing. The MD PnP research team presented a proposal at the White House in December 2013 to configure the MD PnP Interoperability Lab to serve as a Virtual Hospital for the SmartAmerica CPS Test Bed challenge. The Virtual Hospital test bed would provide remote and on-site access to high-bandwidth streaming data from the lab's simulated hospital environment. Data can be generated by simulators and medical devices in the lab, and accessed using an open source codebase. The test bed would enable data, simulated devices, or data processing algorithms from other CPS test beds to augment the lab's capabilities using the team's standards-based Integrated Clinical Environment (ICE), and provide access to clinicians serving as remote clinical consultants, or as a "Virtual Doctor," to answer medical questions related to incoming simulated medical data. The MD PnP Lab, including the “Virtual Hospital” capability, will be part of the Closed Loop Healthcare SmartAmerica use case.


Description of MD PnP Virtual Hospital CPS test bed:

  • Lab Environment: 1800 sq feet in Cambridge, MA – Laboratory of the MD PnP research program, supported in part by NSF, NIH/NIBIB, and DoD (TATRC). http://mdpnp.org/lab.php
  • Equipment: Diverse medical devices, including ventilators, vital signs monitors, device-specific networks and gateways, telemetry, intravenous infusion pumps, pulse oximeters, and personal health devices with standardized open source “ICE research interfaces”. Physical and software patient-signal simulators enable the creation of sharable data that does not contain protected health information.
  • Networking: Remotely accessible infrastructure to support emulation of diverse clinical environments, including operating rooms, intensive care unit, hospital rooms, and home healthcare.
  • Software: Open source software to compose medical devices and apps into an ICE system that interfaces with external systems such as EHRs, order entry systems, and big data analytics.
  • Connectivity to the NwHIN (Nationwide Health Information Network) via DIRECT and CONNECT (validated with a DoD AHLTA test bed); connectivity to the VA VistA EHR via MDWS (Medical Domain Web Services) interface; developing partnerships with regulatory/testing labs.

Committees and Cooperative Efforts with the Federal Government[edit]

The MD PnP Program has had an ongoing relationship with FDA, FCC, ONC HIT and other agencies to pursue a definition of the regulatory pathway for integrated medical device systems.

FDASIA[edit]

As a member of the Food and Drug Administration Safety Innovation Act (FDASIA) Workgroup of the Health IT Policy Committee (HITPC) MD PnP is involved with making recommendations to the National Coordinator for Health IT on a policy framework for the development and adoption of a nationwide health information infrastructure, including standards for the exchange of patient medical information.

MDISWG[edit]

As follow-up to the FDA workshop on Medical Device Interoperability held in January 2010, MD PnP Program Director, Dr. Julian Goldman, co-led the Prototype Regulatory Submission working group with participants from industry, clinical care, standards development organizations, and regulatory agencies,to develop a detailed risk / regulatory model for an integrated “prototype” regulatory submission, intended to allow FDA and interoperability stakeholders to identify and address issues in the process for regulatory approval.

This group handed off its work products to the FDA in the Spring of 2011, for further internal development at FDA, and has continued to meet as the Medical Device Interoperability Safety (MDIS) working group. MD PnP leadership in the MDIS Working Group resulted in industry consensus on the ICE approach as desirable for the Pre-IDE submission, which was submitted as a draft in February 2012, and discussed in a successful face-to-face meeting with the FDA in April.

With preliminary agreement from the FDA on the core approach of this submission, it is being further refined and will be resubmitted for an official response. The MDISWG expects to continue researching safety issues for systems of integrated medical devices and communicating these with the FDA.

===FDA MDICC

MD PnP worked with the FDA to form a Medical Device Interoperability Coordination Council (MDICC) to synchronize the multitude of efforts currently being pursued by different groups around device interoperability. The Clinical Needs & Clinical Landscape team, under the guidance of MD PnP Director, Dr. Julian Goldman, is compiling clinical examples that demonstrate clinical benefits that could be realized from interoperable medical devices. Identifying currently available capabilities as well as future needs (or gaps). Given the nascent state of medical device interoperability, articulation of future (desired) states is especially important to ensure that proposed technical solutions and standards will yield useful clinical capabilities. The future-state clinical scenarios will include interoperability among medical devices, among components of integrated medical device systems, among medical devices and EHRs, among medical devices and hospital IT / CIS systems, and among (personal) medical devices and telehealth data hubs.


Collaborators[edit]

University

Related publications[8] [9][10][11]
Related publications[13][14][15]
Related publications [17][18][19][20][21][22][23]

Other

  • Anakena Solutions [24]
  • Moberg Research [25]

Video Demonstrations and Selected Talks[edit]

Selected Awards[edit]

  • 2010 International Council on Systems Engineering (INCOSE) Pioneer Award
  • 2010 Continua Health Alliance Key Contributor Award
  • 2009 Association for the Advancement of Medical Instrumentation (AAMI) Foundation/Institute for Technology in Health Care Clinical Application Award
  • 2007 CIMIT Edward M Kennedy Award for Healthcare Innovation
  • 2007 First Place at the ASA Scientific Exhibition for “Improving the Safety of PCA Opioid Infusions by Integrating Patient Monitors and Infusion Pumps”

Funding[edit]

  • NIH/ NIBIB grant number 1U01EB012470
  • DoD/ TATRC awards W81XWH-09-1-0705 and W81XWH-12-C-0154
  • DoD/US Army Medical Research Acquisition Activity award number W81XWH-09-2-0001
  • NSF grant numbers CNS-10-35715, IIS-1239242, CNS-08-34524, and CNS-08-34709
  • NIST grant number 70NANB10H258

US government[edit]

Government agencies involved with the MD PnP program include:

Standards[edit]

MD PnP Research has directly supported the following standards activity

  • ASTM F2761[26] *AAMI/UL 2800
  • IEC 80001-1

References[edit]

  1. ^ ASTM F2761-09(2013) Medical Devices and Medical Systems – Essential safety requirements for equipment comprising the patient-centric integrated clinical environment (ICE) – Part 1: General requirements and conceptual model. http://www.astm.org/Standards/F2761.htm
  2. ^ Operating Room of the Future – a CIMIT/TATRC Symposium – developing a plug and play open networking standard (May 2004) http://www.mdpnp.org/uploads/May_04_MD_PnP_Meeting_Agenda.pdf.
  3. ^ Alonso D, Plourde J, Weininger S, Goldman JM. Web-Based Clinical Scenario RepositoryTM (CSRTM). Abstract for the Society for Technology in Anesthesia Annual Meeting, Orlando FL, January 17 2014.
  4. ^ ref to clocks
  5. ^ Duncan
  6. ^ http://mdpnp.org/mdfire.php
  7. ^ http://mdcf.santos.cis.ksu.edu/node/1
  8. ^ Requirements Specification for Apps in Medical Application Platforms, June 2012, Brian Larson, John Hatcliff, Sam Procter, Patrice Chalin (Kansas State University). SEHC '12. PDF
  9. ^ Rationale and Architecture Principles for Medical Application Platforms, April 2012, John Hatcliff (Kansas State University), Andrew King, Insup Lee (University of Pennsylvania), Alasdair MacDonald (eHealth Technology), Anura Fernando (Underwriters Laboratories), Michael Robkin (Anakena Solutions), Eugene Vasserman (Kansas State University), Sandy Weininger (US Food and Drug Administration) and Julian Goldman (Massachusetts General Hospital, CIMIT MD PnP Program). Proceedings of the 2012 International Conference on Cyber-Physical Systems. PDF
  10. ^ Component-Based App Design for Platform-Oriented Devices in a Medical Device Coordination Framework, January 2012, Kejia Li, Steve Warren, and John Hatcliff. Proceedings of the ACM SIGHIT International Health Informatics Symposium (IHI 2012), pp. 343-352. PDF
  11. ^ Prototyping Closed Loop Physiologic Control with the Medical Device Coordination Framework, May 2010. Andrew King, Dave Arney, Insup Lee, Oleg Sokolsky, John Hatcliff, Sam Procter, SEHC '10: PDF
  12. ^ http://rtg.cis.upenn.edu/medical/mdpnp.php3
  13. ^ Prototyping Closed Loop Physiologic Control with the Medical Device Coordination Framework by Andrew King, Dave Arney, Insup Lee, Oleg Sokolsky, John Hatcliff, and Sam Proctor
  14. ^ Synchronizing an X-ray and Anesthesia Machine Ventilator: A Medical Device Interoperability Case Study by David Arney, Julian M. Goldman, Susan F. Whitehead and Insup Lee, Proceedings of International Conference on Biomedical Electronics and Devices (BioDevices 2009), Porto, Portugal, January 14-17, 2009
  15. ^ Plug-and-Play for Medical Devices: Experiences from a Case Study, by David Arney, Sebastian Fischmeister, Julian M. Goldman, Insup Lee, and Robert Trausmuth, Biomedical Instrumentation & Technology, Volume 43, Issue 4 (July-August 2009) p.313-317.
  16. ^ http://publish.illinois.edu/cpsintegrationlab/people/lui-sha/
  17. ^ Y. Li, Y. Sun, P. Sondhi, L. Sha, and C. Zhai, “Reconstructing missing signals in multi-parameter physiologic data by mining the aligned contextual information”, in Proceedings of Computing in Cardiology Conference 2010, Belfast, Northern Ireland, United Kingdom, Sep. 26-29, 2010.
  18. ^ P. Sondhi, J. Sun, C. Zhai, R. Sorrentino, M. S. Kohn, S. Ebadollahi, and Y. Li, “Medical case-based retrieval by leveraging medical ontology and physician feedback”, UIUC-IBM at ImageCLEF 2010. CLEF
  19. ^ Y. Li, J. H, C. Zhai, and Y. Chen, “Improving one-class collaborative filtering by incorporating rich user information”, in CIKM 2010: Proceedings of the 19th ACM international conference on Information and knowledge management, Toronto, Canada, 2010. ACM. (acceptance ratio: 13.4%)
  20. ^ P. Sondhi, M. Gupta, C. Zhai and J. Hockenmaier, “Shallow information extraction from medical forum data”, in Proceedings of COLING 2010,pp. 1158-1166
  21. ^ C. Kim, M. Sun, S. Mohan, H. Yun, L. Sha, and T. F. Abdelzaher, “ A framework for the safe interoperability of medical devices in the presence of network failures”, in Proceedings of the 1st ACM/IEEE International Conference of Cyber-Physical Systems, 2010, pp. 149-158
  22. ^ M. Rahmaniheris, C. Kim, S. Bak, and L. Sha, “A multi-layer dependency framework for analysis of safety-critical embedded systems”, submitted to DSN 2011
  23. ^ Mu Sun, Qixin Wang, Lui Sha. Building Reliable MD PnP Systems. Joint Workshop On High Confidence Medical Devices, Software, and Systems (HCMDSS) and Medical Device Plug-and-Play (MD PnP) Interoperability. June, 2007.
  24. ^ http://www.anakenasolutions.com/about.html
  25. ^ http://www.mobergresearch.com/
  26. ^ ASTM F2761-09(2013) Medical Devices and Medical Systems – Essential safety requirements for equipment comprising the patient-centric integrated clinical environment (ICE) – Part 1: General requirements and conceptual model. http://www.astm.org/Standards/F2761.htm


Julian M. Goldman[edit]

Julian M. Goldman is an American anesthesiologist at the Massachusetts General Hospital, Medical Director of Biomedical Engineering for Partners HealthCare System, and Director of the Program on Medical Device Interoperability based at MGH, Partners, and CIMIT.

Dr. Goldman founded the Medical Device "Plug-and-Play" (MD PnP) Interoperability research program in 2004 to promote innovation in patient safety and clinical care by leading the adoption of safe, secure, patient-centric integrated clinical environments. The MD PnP team has been recognized by multiple awards, including the Edward M Kennedy award for Healthcare Innovation.

Dr. Goldman is Board Certified in Anesthesiology and Clinical Informatics. He completed anesthesiology residency and research fellowship in medical device informatics at the University of Colorado. He departed Colorado as a tenured associate professor to work as an executive of a medical device company. Subsequently, Dr. Goldman joined Harvard Medical School and the Department of Anesthesia, Critical Care, and Pain Medicine at MGH in 2002 as a staff anesthesiologist, where he served as a principle anesthesiologist in the MGH "Operating Room of the Future".

Dr. Goldman co-chaired the FCC mHealth Task Force, the HIT Policy Committee FDASIA Workgroup regulatory subgroup, and the FCC Consumer Advisory Committee healthcare working group. He served on the NSF CISE Advisory Committee, as a Visiting Scholar in the FDA Medical Device Fellowship Program, and as a member of the CDC BSC for the NCPHI. Dr. Goldman currently serves in leadership positions in several healthcare standardization and innovation organizations including Chair of ISO Technical Committee 121, Co-Chair of the AAMI Interoperability Working Group, Co-Chair of the Healthcare Task Group of the Industrial Internet Consortium, and Chair of the Use Case Working Group of the Continua Health Alliance (now the Personal Connected Health Alliance).

Dr. Goldman is an IEEE EMBS Distinguished Lecturer, and the recipient of the International Council on Systems Engineering Pioneer Award, American College of Clinical Engineering (ACCE) award for Professional Achievement in Technology, the AAMI Foundation/Institute for Technology in Health Care Clinical Application Award, and the University of Colorado Chancellor's "Bridge to the Future" award.

Research and training[edit]

Honors[edit]

Bibliography[edit]

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References[edit]

External links[edit]

OpenICE[edit]

OpenICE is a distributed system platform for connecting network nodes together - e.g.: medical devices found in an OR or ICU, blackbox recording applications (i.e. data logging), applications for clinical decision support (CDS), and external interfaces to other healthcare IT (HIT) systems like EMR flowsheets. OpenICE automates peer-to-peer node discovery, data publishing and subscribing between nodes, as well as proprietary medical device protocol translation. Users and developers of the OpenICE platform get the data they need, in a common sensible format, seamlessly delivered to the destinations they want.

OpenICE has been called an open clinical research platform, an abstraction layer for medical devices, a medical Internet of things (MIoT) platform, a cyber-physical system (CPS) test tool, an app hosting environment, amongst other names. The current version of OpenICE enables users to convert heterogeneous medical device data from supported devices into a common structure and protocol, and to exchange that data with demonstration clinical applications on a different machine (or machines). OpenICE includes several simple but useful sample applications as well as example code to help users to write their own.

History[edit]

Definitions[edit]

Open-source software licensing[edit]

Certifications[edit]

Open-source software development[edit]

Development model[edit]

Advantages and disadvantages[edit]

Development tools[edit]

Organizations[edit]

Funding[edit]

Free software[edit]

References[edit]

Further reading[edit]

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