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Showing posts with label ehr. Show all posts
Showing posts with label ehr. Show all posts
Tuesday, September 27, 2011
Monday, October 5, 2009
MIE2009: Medical Informatics Europe
I had the great pleasure of visiting Sarajevo, Bosnia-Herzogovina in early September to attend MIE2009: Medical Informatics in a United and Health Europe. It was a terrific conference, put on by Prof Klaus-Peter Adlassnig, Chair of the Scientific Programme Committee, Prof Izet Masic, Chair of the Local Organizing Committee, and Jacob Hofdijk, PhD, President of the European Federation for Medical Informatics. My kenote address on clinical decision support is available at the link above.
More importantly, however, there is a LOT going on in Europe with clinical informatics. See the many fantastic presentations available at http://www.hst.aau.dk/~ska/MIE2009/ProgramEventsMIE2009.htm.
Take a peek to get a quick update on what's going on in Europe! Enjoy.
More importantly, however, there is a LOT going on in Europe with clinical informatics. See the many fantastic presentations available at http://www.hst.aau.dk/~ska/MIE2009/ProgramEventsMIE2009.htm.
Take a peek to get a quick update on what's going on in Europe! Enjoy.
Thursday, May 14, 2009
The Clinical Decision Support Consortium
Background
Electronic health records (EHRs), when used effectively, can improve the safety and quality of medical care. For maximum benefit, however, EHRs must be paired with clinical decision support (CDS) systems to effectively influence physician behavior. CDS includes a variety of techniques designed to facilitate and guide doctors’ decision making toward evidence-based practice. Common examples of CDS include computerized checks for drug interactions and electronic reminders for screening tests like mammograms and Pap smears.
While the evidence that CDS can be effective is clear, current use and adoption of CDS is limited. In fact, most of what we know about CDS comes from only four academic medical centers and integrated delivery networks. Wider adoption of decision support has been held back by a variety of issues, including:
• Difficulty translating medical knowledge and guidelines into a form that can be used by EHRs.
• Technical challenges in developing a standard representation for CDS content that could be shared across sites.
• Absence of a central knowledge repository where human readable and executable guideline knowledge can be shared and stored.
• Challenges in integrating decision support into the clinical workflow and other barriers to IT adoption
• Limited capabilities for clinical decision support in commercially available electronic health record (EHR) systems.
The AHRQ Clinical Decision Support Consortium
While these issues have been barriers for adoption of clinical decision support systems they are surmountable, as evidenced by a small number of sites where decision support is pervasive. We believe that the biggest challenge to fostering widespread adoption of clinical decision support is in documenting, generalizing, and finally translating the experience from these advanced sites to a broader community of care sites. To address this challenge, investigators from Brigham and Women's Hospital, Harvard Medical School, and Partners HealthCare (PHS), have formed the AHRQ Clinical Decision Support Consortium (CDSC) in collaboration with the Regenstrief Institute, Kaiser Permanente Northwest Research Group, the Veterans Health Administration, Masspro, GE Healthcare, NextGen and Siemens Medical Solutions.
The goal of the CDSC is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology (IT) at scale – across multiple ambulatory care settings and EHR technology platforms.
Our work is guided by a series of high-value research questions:
• How do we improve the translation of knowledge in clinical practice guidelines into actionable clinical decision support in healthcare information technology?
• How do we optimally represent knowledge and data required to make actionable clinical decision support content in human readable and machine readable and executable forms?
• How do we collate, aggregate, and curate knowledge content for clinical decision support in a knowledge portal used by members of the CDS Consortium? How may we use such a tool to support knowledge management and collaborative knowledge engineering for clinical decision support at scale, across multiple healthcare delivery organizations, and multiple domains of medicine?
• How do we demonstrate broad adoption of clinical decision support at scale in different healthcare IT products that are used in disparate ambulatory care delivery settings? Such demonstrations may show the utility of a simplified clinical decision support knowledge specification in human readable form, as well as the utility of publicly available CDS web services, and their incorporation in CCHIT-certified electronic health records (EHR).
• How do we define and evaluate best practices in response to the above assessments and demonstrations? Evaluation must include an assessment of how to incorporate clinical decision support services at scale in a variety of vendor healthcare information technologies, as well as products developed in academic settings. Further, how do we deploy clinical decision support services in healthcare information technology in a manner that improves CDS impact?
• How do we broadly disseminate the lessons learned over the course of these investigations to key audiences, such as the academic informatics community, patient safety and quality groups, medical specialty societies, small office practice settings, and others?
CDS Consortium Activities
The CDS Consortium will carry out a series of activities over the next two to five years:
• Carry out an assessment of knowledge management practices: CDSC researchers will travel to a representative Consortium member site to gather information on their decision support systems and knowledge management practices. This team will use a mix of on site assessment methods, including in-depth interviews, and observations, as well as conduct follow-up visits to the sites after demonstrations have been completed.
• Translate guidelines into actionable decision support tools: The CDSC Knowledge Translation and Specification team (KTS) will select medical guidelines and develop standards and mechanisms for these guidelines into unambiguous knowledge specifications. Those specifications will be used in the subsequent service and demonstration projects.
• Build a knowledge portal and repository (KPR): The KPR team will develop knowledge management tools for use in the development, review, publication, cataloging and archival of clinical guidelines in human and machine-readable forms.
• Develop CDS Services: The CDS services team will take the knowledge specifications developed by the KTS team and develop publicly available web services that will implement the KTS team’s logic. These services will be made available to clinical information systems.
• Carry out demonstrations of CDS across sites: The CDS Demonstrations Team will implement decision support interventions using the content and services developed in the consortium. The initial demonstrations will occur in the Partners Longitudinal Medical Record (LMR) and will incorporate other sites in future years.
• Build “dashboards” to measure the success of our CDS: The CDS Dashboards Team will develop performance reporting tools and clinical dashboards so that providers and site clinical quality staff can review adherence to CDS Consortium guidelines.
• Evaluate our work: The evaluation team will coordinate CDSC evaluation activities across all teams and act as expert consultants to each team as they develop and carry out their evaluation plans.
• Make recommendations: Based on what we learn, the CDSC will make recommendations to electronic health record vendors, clinical content vendors and regulatory and certification authorities about best practices and capabilities for decision support.
• Disseminate our results: Along with Masspro, the Massachusetts quality improvement organization, and the AHRQ National Resource Center for Healthcare IT, we will share and publish our findings and clinical decision support content and best practices developed by the CDS Consortium. We will incorporate lessons learned about CDS into online learning modules for physicians as part of Masspro’s DOQ-IT University initiative, and in the AHRQ National Resource Center.
Conclusion
The CDS Consortium is confident that working together, with Agency for Healthcare Research and Quality (AHRQ) support, significant progress towards widespread adoption of clinical decision support can be made in a short period of time. We expect to deliver first results by the end of the first year of the study. More detailed information is available upon request. Please visit our public website for CDSC study: http://www.partners.org/cird/cdsc
Electronic health records (EHRs), when used effectively, can improve the safety and quality of medical care. For maximum benefit, however, EHRs must be paired with clinical decision support (CDS) systems to effectively influence physician behavior. CDS includes a variety of techniques designed to facilitate and guide doctors’ decision making toward evidence-based practice. Common examples of CDS include computerized checks for drug interactions and electronic reminders for screening tests like mammograms and Pap smears.
While the evidence that CDS can be effective is clear, current use and adoption of CDS is limited. In fact, most of what we know about CDS comes from only four academic medical centers and integrated delivery networks. Wider adoption of decision support has been held back by a variety of issues, including:
• Difficulty translating medical knowledge and guidelines into a form that can be used by EHRs.
• Technical challenges in developing a standard representation for CDS content that could be shared across sites.
• Absence of a central knowledge repository where human readable and executable guideline knowledge can be shared and stored.
• Challenges in integrating decision support into the clinical workflow and other barriers to IT adoption
• Limited capabilities for clinical decision support in commercially available electronic health record (EHR) systems.
The AHRQ Clinical Decision Support Consortium
While these issues have been barriers for adoption of clinical decision support systems they are surmountable, as evidenced by a small number of sites where decision support is pervasive. We believe that the biggest challenge to fostering widespread adoption of clinical decision support is in documenting, generalizing, and finally translating the experience from these advanced sites to a broader community of care sites. To address this challenge, investigators from Brigham and Women's Hospital, Harvard Medical School, and Partners HealthCare (PHS), have formed the AHRQ Clinical Decision Support Consortium (CDSC) in collaboration with the Regenstrief Institute, Kaiser Permanente Northwest Research Group, the Veterans Health Administration, Masspro, GE Healthcare, NextGen and Siemens Medical Solutions.
The goal of the CDSC is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology (IT) at scale – across multiple ambulatory care settings and EHR technology platforms.
Our work is guided by a series of high-value research questions:
• How do we improve the translation of knowledge in clinical practice guidelines into actionable clinical decision support in healthcare information technology?
• How do we optimally represent knowledge and data required to make actionable clinical decision support content in human readable and machine readable and executable forms?
• How do we collate, aggregate, and curate knowledge content for clinical decision support in a knowledge portal used by members of the CDS Consortium? How may we use such a tool to support knowledge management and collaborative knowledge engineering for clinical decision support at scale, across multiple healthcare delivery organizations, and multiple domains of medicine?
• How do we demonstrate broad adoption of clinical decision support at scale in different healthcare IT products that are used in disparate ambulatory care delivery settings? Such demonstrations may show the utility of a simplified clinical decision support knowledge specification in human readable form, as well as the utility of publicly available CDS web services, and their incorporation in CCHIT-certified electronic health records (EHR).
• How do we define and evaluate best practices in response to the above assessments and demonstrations? Evaluation must include an assessment of how to incorporate clinical decision support services at scale in a variety of vendor healthcare information technologies, as well as products developed in academic settings. Further, how do we deploy clinical decision support services in healthcare information technology in a manner that improves CDS impact?
• How do we broadly disseminate the lessons learned over the course of these investigations to key audiences, such as the academic informatics community, patient safety and quality groups, medical specialty societies, small office practice settings, and others?
CDS Consortium Activities
The CDS Consortium will carry out a series of activities over the next two to five years:
• Carry out an assessment of knowledge management practices: CDSC researchers will travel to a representative Consortium member site to gather information on their decision support systems and knowledge management practices. This team will use a mix of on site assessment methods, including in-depth interviews, and observations, as well as conduct follow-up visits to the sites after demonstrations have been completed.
• Translate guidelines into actionable decision support tools: The CDSC Knowledge Translation and Specification team (KTS) will select medical guidelines and develop standards and mechanisms for these guidelines into unambiguous knowledge specifications. Those specifications will be used in the subsequent service and demonstration projects.
• Build a knowledge portal and repository (KPR): The KPR team will develop knowledge management tools for use in the development, review, publication, cataloging and archival of clinical guidelines in human and machine-readable forms.
• Develop CDS Services: The CDS services team will take the knowledge specifications developed by the KTS team and develop publicly available web services that will implement the KTS team’s logic. These services will be made available to clinical information systems.
• Carry out demonstrations of CDS across sites: The CDS Demonstrations Team will implement decision support interventions using the content and services developed in the consortium. The initial demonstrations will occur in the Partners Longitudinal Medical Record (LMR) and will incorporate other sites in future years.
• Build “dashboards” to measure the success of our CDS: The CDS Dashboards Team will develop performance reporting tools and clinical dashboards so that providers and site clinical quality staff can review adherence to CDS Consortium guidelines.
• Evaluate our work: The evaluation team will coordinate CDSC evaluation activities across all teams and act as expert consultants to each team as they develop and carry out their evaluation plans.
• Make recommendations: Based on what we learn, the CDSC will make recommendations to electronic health record vendors, clinical content vendors and regulatory and certification authorities about best practices and capabilities for decision support.
• Disseminate our results: Along with Masspro, the Massachusetts quality improvement organization, and the AHRQ National Resource Center for Healthcare IT, we will share and publish our findings and clinical decision support content and best practices developed by the CDS Consortium. We will incorporate lessons learned about CDS into online learning modules for physicians as part of Masspro’s DOQ-IT University initiative, and in the AHRQ National Resource Center.
Conclusion
The CDS Consortium is confident that working together, with Agency for Healthcare Research and Quality (AHRQ) support, significant progress towards widespread adoption of clinical decision support can be made in a short period of time. We expect to deliver first results by the end of the first year of the study. More detailed information is available upon request. Please visit our public website for CDSC study: http://www.partners.org/cird/cdsc
Monday, May 11, 2009
HL7: Clinical Decision Support
This is the presentation made to the CIC (Clinical Interoperability Council) at HL7 in April, 2009, on Clinical Decision Support.
HL7: Clinical Decision Support
View more presentations from bfm.
Supporting Barack Obama for President
This slide show is from last fall when I had the oppotunity to speak on behalf of the Obama Campaign 2008. It was a privilege.
Supporting Barack Obama for President
View more presentations from bfm.
Tuesday, April 28, 2009
Testimony on HIT "Meaningful Use" at NCVHS April 28, 2009
The National Committee on Vital and Heath Statistics (NCVHS)
Executive Subcommittee special hearing on ‘meaningful use’ as proposed in the American Reinvestment and Recovery Act 2009
Panel 2: Meaningful Use capacity/functionality in EHRs
Marriott Wardman Park Hotel, Washington, D.C. 20008.
Tuesday, April 28, 2009
Panelist: Blackford Middleton, MD, MPH, MSc, FACP, FACMI, FHIMSS
Director, Clinical Informatics Research & Development
Chairman, Center for Information Technology Leadership
Partners HealthCare System, Boston, MA
Introduction:
Good morning. My name is Dr. Blackford Middleton. I am the Corporate Director for Clinical Informatics Research and Development, and of the Center for Information Technology Leadership, both at Partners Healthcare System, Boston, Massachusetts. I am also a member of the National Committee for Vital and Health Statistics, but today I am speaking in my capacity as someone who has been involved with electronic medical record use, design, implementation, and evaluation, in academic and industrial settings, for over 20 years.
It is an honor and a privilege for me to be with you today to discuss this critically important issue of ‘meaningful use’ of healthcare information technology (HIT) for US healthcare which I believe is essential as a prelude to healthcare reform, and transformation of our healthcare delivery systems into the information age, at last. I suggest that through no fault of our own, the physician-emperor has no clothes: we physicians have not invested figuratively, or financially, with HIT. There may be good reasons for this given that he who pays for HIT is not he who gains. Zbut, we can overcome this barrier with Stimulus, and healthcare reform.
Framing the discussion of ‘meaningful use’ of HIT
Briefly, allow me to describe several issues which motivate and frame my discussion of the meaningful use of HIT, which then will guide the discussion of essential functionality and capacities required of HIT which should warrant incentive payments.
The motivation for HIT is clear: in our current fractured, and unwired healthcare system, evidence suggests that physicians routinely practice in a state of incomplete information, and with an incomplete knowledge base required to effectively apply best evidence where it exists for clinical decision-making. With the knowledge-base in medicine continuing to explode, especially in light of the revolution in personalized care it is likely that the information needs problem for providers, and our patients, will only escalate.
When considering assessment and measurement of ‘meaningful use’ I suggest that we consider how HIT itself may play a role in producing reliable measures. HIT process measures could be a by-product of the use of the HIT itself, for example the per provider percentage of prescriptions written with an e-prescribing system. Measurement of meaningful use will require a strong ‘signal’ – something which can be measured reliably – and one that can discriminate between what is judged as meaningful use or not, and does so without bias, and cannot be used fraudulently to misrepresent use of the technology. Importantly, the measures should be independent of the particular technology per se, and apply whether a comprehensive thick client EMR, or a lightweight web-based system is being used.
While we consider our goals for transforming health care with the application of HIT, we must be wary of setting our sights too low, or settling for only an intermediate goal state in the journey toward robust HIT adoption. At the Center for Information Technology Leadership, for example, we find in our analyses that potentially many billions of dollars may be saved with the broad application of HIT. Our findings suggest that the two most important factors associated with the maximum value potential of HIT are seamless interoperability of healthcare data, and advanced clinical decision support. It is incumbent upon us to keep this long-range goal in mind even as we begin the journey with small steps.
Let us turn now to the goals of HIT adoption. Our first goal is improved care delivery: lower costs, improved quality, but I hope also we design a system that can enhance individual and community wellness, and research on what works and what does not. It is not about healthcare technology itself, of course, but rather what outcomes and redesign of our delivery system we can achieve with it. I suggest that defining clinical goals only is insufficient, and will not lead to a future state of coordinated and seamless care across different locations of care, healthcare organizations, and different technology solutions. Such systematic goals require us to think about requirements of the system itself to work efficiently; things like the ability to correctly identify the patient in any technology system, the seamless exchange and portability of data and information across systems, the availability of the best knowledge at the point of care in clinical decision support within any technology, and more. While these goals may not relate to one or another specific clinical goal, more importantly, they are relevant to helping us redesign our healthcare delivery system, as HIT is the enabler, and prelude, to other dimensions of healthcare reform to come. To achieve this vision, we will need a phased approach to incremental technology adoption that incrementally and inexorably moves us toward our combined goals.
Let me know now turn to the questions at hand regarding EHR functionality.
Questions:
1. What EHR capacities/functionalities are absolutely required to enable a safe, patient-centric, high-quality health care system that optimizes patient outcomes?
Several excellent descriptions of EHR capacities and functionalities exist currently. These include the 2003 Institute of Medicine Letter Report describing the EHR, HL7’s EHR Standard Functional Specification, as well as the certification criteria for ambulatory medical records 2008, and inpatient criteria in development from the Certification Commission for Healthcare Information Technology. Time will not allow reviewing each of these now, but common to all of these functional descriptions of EHR are the following core capabilities:
Data Access: aggregate all the relevant patient care data for review by the provider. This may include organizing the data in a variety of presentations, and numerically and semantically normalizing data from disparate data sources.
Knowledge Access: provide access to knowledge-based tools and services in the context of the clinical workflow. Readily provide an answer to the clinical question at hand, ‘one click away’.
Workflow and Clinical Decision Support: provide support for the clinical workflow both for the individual care provider, and care teams. In addition, provide clinical decision-support in the context of the clinical workflow, such as alerts, reminders, documentation assistance tools, care plans and guidelines, and diagnostic and therapeutic decision support as appropriate to both providers and patients.
Healthcare Information Exchange: facilitate information exchange between disparate sources for the purposes of data review for each and every clinical encounter. This should include all essential data elements such as current medications, allergies, problems and past medical history, laboratory and diagnostic test results, and patient demographics for example.
Let us now turn to the specific technologies that should be in use in 2011.
2. What are the critical EHR functionalities (e.g., e-prescribing, decision support, problem list management) of which providers should be required to demonstrate use in order to be earn an incentive as a “meaningful user” of certified EHR technology in 2011? Should the functionalities or other specific requirements to meet the statutory “meaningful use” criteria be different or specific to provider type (i.e., eligible professionals, hospitals)?
The language in HITECH within ARRA describes three broad areas; I concur with these capabilities being the areas of focus for 2011. In each case, in the written testimony I provide pointers to illustrative capabilities as defined in CCHIT certification criteria (these lists are not comprehensive).
- e-Prescribing: defined as electronically prescribing, and managing a medication list, with patient specific medication decision support (drug-drug, drug-lab, drug-allergy), medication history, allergies, including inpatient medication reconciliation, and medication administration
o For example, the functions described in CCHIT Ambulatory 2008 Criteria sets in AM04, AM05, AM11, AM19, and FN05, FN06, FN07, FN08, FN12, FN13;
o and Inpatient Criteria IP05 and FN05, IP06 and FN06, IP10, FN07, FN12, IP11, IP12, FN08, IP14, FN16, IP16)
- Healthcare Information Exchange: defined as the ability to aggregate, collate, and display in appropriate views all relevant patient care data from ancillary systems (for example, laboratories, radiology reports, patient demographic and administrative data, etc.). In addition, provide the ability to produce a Visit Summary (CCD), and exchange select data across and between healthcare organizations.
o For example, CCHIT 2008 AM09, AM14, IO-AM11, or HITSP ISO3/C32 specification with SNOMED-CT and Level 3 RxNORM
o And Inpatient Criteria IO IP-04 (Discharge), and IO IP-05 (Cross enterprise document sharing)
- Quality Data Reporting: defined as the ability to submit a standard quality data set to the appropriate authoritative agencies reflecting care quality, patient safety, and compliance with select standard quality measures
o CCHIT Ambulatory 2008 AM29, IO AM-14,
o For example, NQF HITEP-2 quality data set (QDS)
Should a distinction be allowed between provider types? With respect to the functionality described above, this observer would suggest that distinctions not be allowed between provider types. The above functionality should be in place and used by the relevant accountable providers for each and every clinical encounter or hospitalization.
4. What additional functionalities would be most important to require providers use by 2014 or 2015?
As the country moves toward universal adoption of electronic health records, the depth of functionality and interoperability to fully achieve the value potential of healthcare information technology must match the breath of adoption. By 2015, in addition to the above, the following functionalities should also be widely adopted to warrant incentive payments.
- Demonstrate the ability to reliably submit without tampering or fraud predefined measures of HIT use, and quality data reports
o This is critical to allow meaningful use to be assessed as a by-product of use
- Enhanced Structured and Coded Documentation
o Problem List, Medication List, Advanced Directives, Blood type, Adverse Events (never events), Family History, Medical History, Surgical/Procedure History, Social History, Chief Complaint, Healthcare Maintenance and Screening, observations required for quality measurement, for example.
o To improve the data we collect and input to clinical decision support and quality data reporting systems progressive standardization of documentation templates and controlled medical terminology
- Effective Workflow and Clinical Decision Support
o Team-based care coordination, healthcare maintenance and screening reminders, preventive care services, chronic care management, acute care management, triage, remote consultation and care collaboration
o Based upon the evidence, define minimal standard clinical decision support for 2014 (and possibly beyond)
- Knowledge Management Services
o Given the depth and breadth of clinical content and knowledge artifacts required to support effective workflow and clinical decision support, healthcare information technology solutions should have access to a national knowledge repository, and knowledge management services, to facilitate keeping all systems up to date with current best evidence and best practices
- Seamless and secure information exchange and interoperability
o Progressive standardization of essential clinical data sets to support healthcare information exchange and interoperability
- Personal Health Records
o A patient-controlled Personal Health Record provided either as an adjunct to provider-based systems, or through independent solutions, to support patient engagement and facilitate information exchange
3. Are these functionalities supported in current certified EHR products? If not, what are the gaps?
Time will not allow a comprehensive review of whether the functionalities described above are supported in current certified EHR products or not. The more advanced functionalities do not yet have certification criteria, and by the same token the certification process should not quell innovation in the marketplace to bring advanced technologies to life. Several core issues underlie this entire discussion on EHR functionalities, however, that if addressed from a national perspective could help facilitate obtaining both widespread adoption of HIT, and impact health care costs, and quality.
- National Patient Identifier
We have had a long debate in this country about the merits of a national patient identifier. This observer would suggest that the benefits far outweigh the risks and that we should move forward in developing and implementing this identifier with all appropriate policies and protections in place to ensure its safe and effective use.
- Standardized clinical data model and clinical terminology
While we have made dramatic progress in recent years thanks largely to the efforts of leading standards development organizations such as HL7, Integrating the Healthcare Enterprise, and the Healthcare Information Technology Standards Panel’s efforts on harmonization, we do not have a universally accepted and complete clinical data model, nor do we have standardized clinical terminology, for all essential clinical data elements. Every effort should be made to advance our progress in these areas as they undergird the successful design, implementation, and use of all healthcare information technologies.
- Standardized User Interface
We now recognize that the human computer interface of healthcare information technology itself may impact clinical workflow and outcomes. There is a growing literature on the unintended and untoward consequences of HIT use. This observer would suggest that a critical element for the successful design, implementation, and use of HIT is to standardize the user interface so that providers using any system can use it appropriately. This will, of course, also decrease training costs, and assist providers who provide care in more than one setting.
Acknowledgements
I would like to acknowledge several colleagues who provided valuable input to this testimony. Dr. Eric Pan and Mr. Douglas Johnston from the Center for Information Technology Leadership, and Drs. Adam Wright, and Dean Sittig, co-investigators in the AHRQ Clinical Decision Support Consortium.
Thank You!
Executive Subcommittee special hearing on ‘meaningful use’ as proposed in the American Reinvestment and Recovery Act 2009
Panel 2: Meaningful Use capacity/functionality in EHRs
Marriott Wardman Park Hotel, Washington, D.C. 20008.
Tuesday, April 28, 2009
Panelist: Blackford Middleton, MD, MPH, MSc, FACP, FACMI, FHIMSS
Director, Clinical Informatics Research & Development
Chairman, Center for Information Technology Leadership
Partners HealthCare System, Boston, MA
Introduction:
Good morning. My name is Dr. Blackford Middleton. I am the Corporate Director for Clinical Informatics Research and Development, and of the Center for Information Technology Leadership, both at Partners Healthcare System, Boston, Massachusetts. I am also a member of the National Committee for Vital and Health Statistics, but today I am speaking in my capacity as someone who has been involved with electronic medical record use, design, implementation, and evaluation, in academic and industrial settings, for over 20 years.
It is an honor and a privilege for me to be with you today to discuss this critically important issue of ‘meaningful use’ of healthcare information technology (HIT) for US healthcare which I believe is essential as a prelude to healthcare reform, and transformation of our healthcare delivery systems into the information age, at last. I suggest that through no fault of our own, the physician-emperor has no clothes: we physicians have not invested figuratively, or financially, with HIT. There may be good reasons for this given that he who pays for HIT is not he who gains. Zbut, we can overcome this barrier with Stimulus, and healthcare reform.
Framing the discussion of ‘meaningful use’ of HIT
Briefly, allow me to describe several issues which motivate and frame my discussion of the meaningful use of HIT, which then will guide the discussion of essential functionality and capacities required of HIT which should warrant incentive payments.
The motivation for HIT is clear: in our current fractured, and unwired healthcare system, evidence suggests that physicians routinely practice in a state of incomplete information, and with an incomplete knowledge base required to effectively apply best evidence where it exists for clinical decision-making. With the knowledge-base in medicine continuing to explode, especially in light of the revolution in personalized care it is likely that the information needs problem for providers, and our patients, will only escalate.
When considering assessment and measurement of ‘meaningful use’ I suggest that we consider how HIT itself may play a role in producing reliable measures. HIT process measures could be a by-product of the use of the HIT itself, for example the per provider percentage of prescriptions written with an e-prescribing system. Measurement of meaningful use will require a strong ‘signal’ – something which can be measured reliably – and one that can discriminate between what is judged as meaningful use or not, and does so without bias, and cannot be used fraudulently to misrepresent use of the technology. Importantly, the measures should be independent of the particular technology per se, and apply whether a comprehensive thick client EMR, or a lightweight web-based system is being used.
While we consider our goals for transforming health care with the application of HIT, we must be wary of setting our sights too low, or settling for only an intermediate goal state in the journey toward robust HIT adoption. At the Center for Information Technology Leadership, for example, we find in our analyses that potentially many billions of dollars may be saved with the broad application of HIT. Our findings suggest that the two most important factors associated with the maximum value potential of HIT are seamless interoperability of healthcare data, and advanced clinical decision support. It is incumbent upon us to keep this long-range goal in mind even as we begin the journey with small steps.
Let us turn now to the goals of HIT adoption. Our first goal is improved care delivery: lower costs, improved quality, but I hope also we design a system that can enhance individual and community wellness, and research on what works and what does not. It is not about healthcare technology itself, of course, but rather what outcomes and redesign of our delivery system we can achieve with it. I suggest that defining clinical goals only is insufficient, and will not lead to a future state of coordinated and seamless care across different locations of care, healthcare organizations, and different technology solutions. Such systematic goals require us to think about requirements of the system itself to work efficiently; things like the ability to correctly identify the patient in any technology system, the seamless exchange and portability of data and information across systems, the availability of the best knowledge at the point of care in clinical decision support within any technology, and more. While these goals may not relate to one or another specific clinical goal, more importantly, they are relevant to helping us redesign our healthcare delivery system, as HIT is the enabler, and prelude, to other dimensions of healthcare reform to come. To achieve this vision, we will need a phased approach to incremental technology adoption that incrementally and inexorably moves us toward our combined goals.
Let me know now turn to the questions at hand regarding EHR functionality.
Questions:
1. What EHR capacities/functionalities are absolutely required to enable a safe, patient-centric, high-quality health care system that optimizes patient outcomes?
Several excellent descriptions of EHR capacities and functionalities exist currently. These include the 2003 Institute of Medicine Letter Report describing the EHR, HL7’s EHR Standard Functional Specification, as well as the certification criteria for ambulatory medical records 2008, and inpatient criteria in development from the Certification Commission for Healthcare Information Technology. Time will not allow reviewing each of these now, but common to all of these functional descriptions of EHR are the following core capabilities:
Data Access: aggregate all the relevant patient care data for review by the provider. This may include organizing the data in a variety of presentations, and numerically and semantically normalizing data from disparate data sources.
Knowledge Access: provide access to knowledge-based tools and services in the context of the clinical workflow. Readily provide an answer to the clinical question at hand, ‘one click away’.
Workflow and Clinical Decision Support: provide support for the clinical workflow both for the individual care provider, and care teams. In addition, provide clinical decision-support in the context of the clinical workflow, such as alerts, reminders, documentation assistance tools, care plans and guidelines, and diagnostic and therapeutic decision support as appropriate to both providers and patients.
Healthcare Information Exchange: facilitate information exchange between disparate sources for the purposes of data review for each and every clinical encounter. This should include all essential data elements such as current medications, allergies, problems and past medical history, laboratory and diagnostic test results, and patient demographics for example.
Let us now turn to the specific technologies that should be in use in 2011.
2. What are the critical EHR functionalities (e.g., e-prescribing, decision support, problem list management) of which providers should be required to demonstrate use in order to be earn an incentive as a “meaningful user” of certified EHR technology in 2011? Should the functionalities or other specific requirements to meet the statutory “meaningful use” criteria be different or specific to provider type (i.e., eligible professionals, hospitals)?
The language in HITECH within ARRA describes three broad areas; I concur with these capabilities being the areas of focus for 2011. In each case, in the written testimony I provide pointers to illustrative capabilities as defined in CCHIT certification criteria (these lists are not comprehensive).
- e-Prescribing: defined as electronically prescribing, and managing a medication list, with patient specific medication decision support (drug-drug, drug-lab, drug-allergy), medication history, allergies, including inpatient medication reconciliation, and medication administration
o For example, the functions described in CCHIT Ambulatory 2008 Criteria sets in AM04, AM05, AM11, AM19, and FN05, FN06, FN07, FN08, FN12, FN13;
o and Inpatient Criteria IP05 and FN05, IP06 and FN06, IP10, FN07, FN12, IP11, IP12, FN08, IP14, FN16, IP16)
- Healthcare Information Exchange: defined as the ability to aggregate, collate, and display in appropriate views all relevant patient care data from ancillary systems (for example, laboratories, radiology reports, patient demographic and administrative data, etc.). In addition, provide the ability to produce a Visit Summary (CCD), and exchange select data across and between healthcare organizations.
o For example, CCHIT 2008 AM09, AM14, IO-AM11, or HITSP ISO3/C32 specification with SNOMED-CT and Level 3 RxNORM
o And Inpatient Criteria IO IP-04 (Discharge), and IO IP-05 (Cross enterprise document sharing)
- Quality Data Reporting: defined as the ability to submit a standard quality data set to the appropriate authoritative agencies reflecting care quality, patient safety, and compliance with select standard quality measures
o CCHIT Ambulatory 2008 AM29, IO AM-14,
o For example, NQF HITEP-2 quality data set (QDS)
Should a distinction be allowed between provider types? With respect to the functionality described above, this observer would suggest that distinctions not be allowed between provider types. The above functionality should be in place and used by the relevant accountable providers for each and every clinical encounter or hospitalization.
4. What additional functionalities would be most important to require providers use by 2014 or 2015?
As the country moves toward universal adoption of electronic health records, the depth of functionality and interoperability to fully achieve the value potential of healthcare information technology must match the breath of adoption. By 2015, in addition to the above, the following functionalities should also be widely adopted to warrant incentive payments.
- Demonstrate the ability to reliably submit without tampering or fraud predefined measures of HIT use, and quality data reports
o This is critical to allow meaningful use to be assessed as a by-product of use
- Enhanced Structured and Coded Documentation
o Problem List, Medication List, Advanced Directives, Blood type, Adverse Events (never events), Family History, Medical History, Surgical/Procedure History, Social History, Chief Complaint, Healthcare Maintenance and Screening, observations required for quality measurement, for example.
o To improve the data we collect and input to clinical decision support and quality data reporting systems progressive standardization of documentation templates and controlled medical terminology
- Effective Workflow and Clinical Decision Support
o Team-based care coordination, healthcare maintenance and screening reminders, preventive care services, chronic care management, acute care management, triage, remote consultation and care collaboration
o Based upon the evidence, define minimal standard clinical decision support for 2014 (and possibly beyond)
- Knowledge Management Services
o Given the depth and breadth of clinical content and knowledge artifacts required to support effective workflow and clinical decision support, healthcare information technology solutions should have access to a national knowledge repository, and knowledge management services, to facilitate keeping all systems up to date with current best evidence and best practices
- Seamless and secure information exchange and interoperability
o Progressive standardization of essential clinical data sets to support healthcare information exchange and interoperability
- Personal Health Records
o A patient-controlled Personal Health Record provided either as an adjunct to provider-based systems, or through independent solutions, to support patient engagement and facilitate information exchange
3. Are these functionalities supported in current certified EHR products? If not, what are the gaps?
Time will not allow a comprehensive review of whether the functionalities described above are supported in current certified EHR products or not. The more advanced functionalities do not yet have certification criteria, and by the same token the certification process should not quell innovation in the marketplace to bring advanced technologies to life. Several core issues underlie this entire discussion on EHR functionalities, however, that if addressed from a national perspective could help facilitate obtaining both widespread adoption of HIT, and impact health care costs, and quality.
- National Patient Identifier
We have had a long debate in this country about the merits of a national patient identifier. This observer would suggest that the benefits far outweigh the risks and that we should move forward in developing and implementing this identifier with all appropriate policies and protections in place to ensure its safe and effective use.
- Standardized clinical data model and clinical terminology
While we have made dramatic progress in recent years thanks largely to the efforts of leading standards development organizations such as HL7, Integrating the Healthcare Enterprise, and the Healthcare Information Technology Standards Panel’s efforts on harmonization, we do not have a universally accepted and complete clinical data model, nor do we have standardized clinical terminology, for all essential clinical data elements. Every effort should be made to advance our progress in these areas as they undergird the successful design, implementation, and use of all healthcare information technologies.
- Standardized User Interface
We now recognize that the human computer interface of healthcare information technology itself may impact clinical workflow and outcomes. There is a growing literature on the unintended and untoward consequences of HIT use. This observer would suggest that a critical element for the successful design, implementation, and use of HIT is to standardize the user interface so that providers using any system can use it appropriately. This will, of course, also decrease training costs, and assist providers who provide care in more than one setting.
Acknowledgements
I would like to acknowledge several colleagues who provided valuable input to this testimony. Dr. Eric Pan and Mr. Douglas Johnston from the Center for Information Technology Leadership, and Drs. Adam Wright, and Dean Sittig, co-investigators in the AHRQ Clinical Decision Support Consortium.
Thank You!
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