Perspective
Improving the quality of cancer care in America through health information technology Thomas W Feeley,1 George W Sledge,2 Laura Levit,3 Patricia A Ganz4,5 1
The Institute for Cancer Care Innovation, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA 2 Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, California, USA 3 National Cancer Policy Forum, The Institute of Medicine, Washington, DC, USA 4 Jonsson Comprehensive Cancer Center at the University of California, Los Angeles, California, USA 5 Schools of Medicine and Public Health, Los Angeles, California, USA Correspondence to Dr Thomas W Feeley, Division of Anesthesiology, UT MD Anderson Cancer Center, 1400 Holcombe Blvd, Unit 409, Houston, TX 77030, USA; [email protected] Received 11 September 2013 Accepted 4 November 2013 Published Online First 18 December 2013
To cite: Feeley TW, Sledge GW, Levit L, et al. J Am Med Inform Assoc 2014;21:772–775. 772
ABSTRACT A recent report from the Institute of Medicine titled Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis, identifies improvement in information technology (IT) as essential to improving the quality of cancer care in America. The report calls for implementation of a learning healthcare IT system: a system that supports patient–clinician interactions by providing patients and clinicians with the information and tools necessary to make well informed medical decisions and to support quality measurement and improvement. While some elements needed for a learning healthcare system are already in place for cancer, they are incompletely implemented, have functional deficiencies, and are not integrated in a way that creates a true learning healthcare system. To achieve the goal of a learning cancer care delivery system, clinicians, professional organizations, government, and the IT industry will have to partner, develop, and incentivize participation.
INTRODUCTION In the USA, there are many challenges to the delivery of high-quality cancer care. The information base is rapidly expanding with knowledge growth in genomics, proteomics, molecular testing, and pharmacology. The number of new patients with cancer is rising as our population ages. New therapies that prolong patients’ lives are leading to a large number of people living with and surviving cancer. Our cancer care delivery system is struggling to meet the needs of our patients, their families, and cancer care teams. Shortages in the cancer care workforce and the rapidly increasing costs of cancer care contribute to an impending crisis. In the past year the Institute of Medicine (IOM) released two major reports that address the key role of informatics in improving the healthcare delivery system. The first report, titled Best Care at Lower Cost: The Path to Continuously Learning Health Care in America, called for information technology (IT) to have a central role in delivering outstanding clinical care by creating a system that constantly collects and analyzes data from patients in a manner that leads to constant improvement in care.1 The newest report from the IOM, Delivering High Quality Cancer Care: Charting a New Course for a System in Crisis, highlights the problems facing our cancer care delivery system.2 The report identified IT as a critical component of the IOM’s conceptual framework for a high-quality cancer care delivery system (figure 1). In the framework, IT supports interactions between patients and clinicians by providing them with the information and
tools necessary to make well informed medical decisions. Health IT collects and reports quality metrics that drive internal improvement, inform the public, and reform payment to reward high quality care. It also plays a role in developing the evidence base from research. A key recommendation from this report is that clinicians, professional organizations, government, and the IT industry should engage in the development of a learning healthcare IT system for cancer that enables real-time analysis of data from cancer patients in a variety of settings. To accomplish this, the IOM encourages professional organizations, the Department of Health and Human Services, payers, patients, clinicians, IT developers, and investigators to develop the necessary components of a learning healthcare system with incentives for rapid implementation. The first national assessment of the quality of cancer care in the USA was sponsored by the IOM in 1999, and has as one of its major recommendations the need for better data systems in cancer to improve quality metric reporting.3 Over the 14 years since that first report, the development of IT as an aid to cancer care delivery has been slow and ineffective.4
A VISION FOR A LEARNING CANCER CARE SYSTEM A learning healthcare IT system for cancer should continually collect and analyze data from a variety of sources including cancer registries, clinical data from electronic health records, and clinical trials to provide the most up-to-date information for clinicians. The system should have patients as its core with data coming from individual patients reported directly by them and their cancer care teams. The rapid deployment of electronic health records is essential for this system, yet much more needs to be done to make the vision a reality. Efforts have been made to develop such systems, like the American Society of Clinical Oncology’s (ASCO) CancerLinQ.5 CancerLinQ has several goals: (1) to capture, aggregate, and analyze longitudinal patient data from any source; (2) to provide cancer care teams with real-time clinical decision support based on clinical guidelines; (3) to measure clinical performance using performance measures; and (4) to explore hypotheses from clinical datasets. Central to that new system is ASCO’s quality oncology practice initiative (QOPI), which has traditionally relied on manual chart abstraction. CancerLinQ will transition this program to eQOPI and allow automatic data abstraction. Following a successful 2012 prototype in breast cancer, CancerLinQ is being expanded to all cancers.6 7
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
Perspective Figure 1 The conceptual framework for a high-quality cancer care delivery system. A learning healthcare information technology system is a key element linking the ever expanding evidence base with the workforce and the patient.
Another major effort to develop a learning healthcare system is Kaiser Permanente’s HealthConnect system that links 9 million Kaiser patients with their healthcare teams over a wide geographic area. The system links outpatient and inpatient records, provides patients with the ability to send their care teams secure messages, and includes decision support for clinicians.8 Although both ASCO’s CancerLinq and Kaiser’s HealthConnect lack some essential elements for a learning healthcare system, both are in the early stages of development, and are examples of early efforts to address the needs for a learning healthcare system. To be complete, a learning healthcare system should address the needs of patients, the clinical workforce, clinical investigators, developers of quality metrics, and payers. The IOM’s report elaborates on these stakeholder needs.2 Patients need access to their electronic health information and should be able to download data into personal health records. They also need to be able provide patient-reported outcomes and information about their individual characteristics and behaviors, in order to inform clinical care and research. The clinical workforce needs improved real-time decision support informed by up-to-date clinical information. This is vital in an age of molecular and genetic information and an ever-expanding supply of targeted pharmacologic agents. The workforce also needs effective electronic tools to facilitate communication among the diverse group of clinicians likely to be caring for a patient, supportive care services, and essential administrative entities. The first four recommendations of the report address the need for patient-centered communication and shared decision making with a well-trained and coordinated workforce.2 Clinical investigators need information to facilitate enrollment of appropriate patients in clinical trials, larger databases with clinically relevant outcomes, and access to big data systems that match clinical information with genomic and proteomic characteristics of both the tumor and the host. Two recommendations in the report specifically address the data needs to improve the evidence base for cancer care.2 Cancer quality metrics developers need more robust IT systems to more efficiently develop meaningful metrics for cancer care delivery that can be applied for performance improvement and public reporting; transparency that does not
exist today. One recommendation from the report addresses the need for the development of a national quality reporting program for cancer care that would have IT at its core both from a metric development standpoint through automated reporting and analysis.2 Payers need systems that permit newer reimbursement models that move away from fee for service and begin to pay for cancer care based on high-quality clinical outcomes. The final two recommendations in the report highlight the path to providing accessible and affordable cancer care for all Americans.2 The goals of all 10 report recommendations are summarized in box 1.
CHALLENGES IN CREATING A LEARNING CANCER CARE SYSTEM Development of a learning healthcare system for cancer has been extremely slow to evolve. Despite the creation of the National Coordinator for Health Information Technology in 2004, accelerated with funding through the Hi-tech Act in 2009, a true learning healthcare system for cancer has yet to materialize. There are technical, implementation, and ethical challenges that need to be overcome for a learning cancer care system to become a reality. A major technical challenge is interoperability, necessary for exchange of data between institutions, among clinicians, with patients, payers, registries, and public reporting entities. Data standards need to be refined and adopted widely. Data need to be collected at the point of care or directly from the patient in a manner that can be easily standardized and extracted. Electronic health record developers need to work cooperatively to ensure that their systems communicate seamlessly with each other and with the appropriate networks. A second major technical challenge is the volume of critical data now being generated due to the proliferation of molecular and genetic testing made possible recently. Management of such big data platforms is new to healthcare yet essential to the construction of a learning healthcare system. Once collected, large data need to be easily extracted and reported from the data repository and appropriate analytic tools applied. While attempts have been made to address each of these technical challenges, there are few examples of a model system that has overcome all of these technical problems.
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
773
Perspective
Box 1 Goals of the 10 recommendations to improve the quality of cancer care in America 1.
Provide patients and their families with understandable information about cancer prognosis, treatment benefits and harms, palliative care, psychosocial support, and costs. 2. Provide patients with end-of-life care that meets their needs, values, and preferences. 3. Ensure coordinated and comprehensive patient-centered care. 4. Ensure that all individuals caring for cancer patents have appropriate core competencies. 5. Expand the breadth of data collected in cancer research for older adults and patients with multiple comorbid conditions. 6. Expand the depth of data collected in cancer research through a common set of data elements that capture patient-reported outcomes, relevant patient characteristics, and health behaviors. 7. Develop a learning healthcare information technology system for cancer that enables real-time analysis of data from cancer patients in a variety of care settings. 8. Develop a national quality reporting program for cancer care as a part of learning healthcare system. 9. Implement a national strategy to reduce disparities in access to cancer care for under-served populations by leveraging community interventions. 10. Improve the affordability of cancer care by leveraging existing efforts to reform payment and eliminate waste.
Implementation is also a challenge to moving forward. Many provider organizations are overwhelmed with performance improvement projects that rely on existing data collection and reporting systems. Implementation of a learning healthcare system will require major changes in the processes of care most clinical providers currently use. Major cultural changes will have to occur to uniformly adopt electronic record keeping and data sharing both with other clinical care providers and with patients themselves. The cost of making this transition is an additional implementation challenge. At a time when our healthcare costs are at an all-time high, making significant capital investments in totally new systems will be an economic challenge to providers and provider organizations. The creation of large datasets from cancer patients presents ethical challenges that must be addressed before a learning healthcare system for cancer can be fully achieved. Regulations protecting patient privacy run counter to collecting information from those same patients to learn from their course of disease and improve care for others. In a learning healthcare system the lines between clinical care and research become blurred and new ways of thinking about improving the quality of care using ongoing patient experiences must be addressed.
A PATH FORWARD The IOM’s report found that the creation of a learning healthcare system for cancer will require an effort on the part of many stakeholders including clinicians, professional organizations, the IT industry, and the federal government. The report made the
774
following recommendation to achieve A Learning Health Care IT System for cancer: Goal: Develop an ethically sound learning healthcare IT system for cancer that enables real-time analysis of data from cancer patients in a variety of care settings. To accomplish this: ▸ Professional organizations should design and implement the digital infrastructure and analytics necessary to enable continuous learning in cancer care. ▸ The Department of Health and Human Services should support the development and integration of a learning healthcare IT system for cancer. ▸ Centers for Medicare and Medicaid Services (CMS) and other payers should create incentives for clinicians to participate in this learning healthcare system for cancer, as it develops. The report indicated that clinicians must lead in the development of this new system leveraging professional organizations and the IT industry. Clinicians ensure that a resulting system will be clinically relevant and minimally intrusive to workflow. Professional organizations are already taking the lead in this area as evidenced by ASCO’s CancerLinQ project, which, while still a pilot program, embodies some of the essential elements outlined. The IT industry can assist in the development of data standards, collection systems, and standardized data repositories that facilitate reporting and analysis. It is imperative that vendors of electronic health records actively participate in this process since easily collected and extracted data is essential in a high-quality cancer care delivery system of the future. The federal government has a critical role coordinating these activities. The Department of Health and Human Services, through the Office of the National Coordinator for Health Information Technology and in cooperation with CMS, can develop regulatory guidance with financial incentives to accelerate the development of a learning healthcare system for cancer. Incentives need to be directed toward the IT industry to develop the tools and toward the care community to implement them. The meaningful use program is an example of how such programs can accelerate the deployment of needed health IT. Finally, the National Cancer Institute can fund innovative programs that enhance IT in its clinical trials programs and in studying other ways of advancing the quality of cancer care using IT. There is a crisis in the quality of care delivered to cancer patients in America today. Health IT can play a major role in improving that care. While this represents a major investment in resources, it is an investment our nation cannot ignore. Acknowledgements This project was supported by: AARP, American Cancer Society, American College of Surgeons’ Commission on Cancer, American Society for Radiation Oncology, American Society of Clinical Oncology, American Society of Hematology, California HealthCare Foundation, Centers for Disease Control and Prevention, LIVESTRONG, National Cancer Institute, National Coalition for Cancer Survivorship, Oncology Nursing Society, and Susan G Komen for the Cure. We thank the members of the IOM Committee on Improving the Quality of Cancer Care: Addressing the Challenges of an Aging Population and the project staff. The authors are responsible for the content of this article, which does not necessarily represent the views of the Institute of Medicine. Contributors All authors (TWF, GWS, LL and PAG) made substantial contribution to the conception and design of this manuscript and the opinions expressed in this opinion ( perspective) piece. In addition, all authors were involved in drafting the article and revising it critically for important intellectual content. All authors gave final approval of the version to be published. Funding This study was supported by Contract Nos. HHSN261200900003C and 200-2011-38807, TO #13 between the National Academy of Sciences and the National Cancer Institute and the Centers for Disease Control and Prevention. Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
Perspective REFERENCES 1 2 3 4
IOM (Institute of Medicine). Best care at lower cost: the path to continuously learning health care in America. Washington, DC: The National Academies Press, 2012. IOM (Institute of Medicine). Delivering high-quality cancer care: charting a new course for a system in crisis. Washington, DC: The National Academies Press, 2013. IOM (Institute of Medicine). Ensuring quality cancer care. Washington, DC: The National Academies Press, 1999. Spinks T, Albright HW, Feeley TW, et al. Ensuring quality cancer care: a follow-up review of the Institute of Medicine’s 10 recommendations for improving the quality of cancer care in America. Cancer 2012;118:2571–82.
5
6 7 8
ASCO (American Society of Clinical Oncology). 2012. CancerLinQ. Building a transformation in cancer care. http://www.asco.org/institute-quality/cancerlinq (accessed 22 Aug 2013) Sledge GW, Miller RS, Hauser R. CancerLinQ and the future of cancer care. Am Soc Clin Oncol Educ Book 2013;2013:430–4. Sledge GW, Hudis CA, Swain SM, et al. ASCO’s approach to a learning health care system in oncology. J Oncol Pract 2013;9:145–8. Kaiser Permanente HealthConnect Electronic Health Record. 2013. http://xnet.kp.org/ newscenter/aboutkp/healthconnect/ (accessed 4 Sep 2013)
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
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Improving the quality of cancer care in America through health information technology Thomas W Feeley,1 George W Sledge,2 Laura Levit,3 Patricia A Ganz4,5 1
The Institute for Cancer Care Innovation, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA 2 Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, California, USA 3 National Cancer Policy Forum, The Institute of Medicine, Washington, DC, USA 4 Jonsson Comprehensive Cancer Center at the University of California, Los Angeles, California, USA 5 Schools of Medicine and Public Health, Los Angeles, California, USA Correspondence to Dr Thomas W Feeley, Division of Anesthesiology, UT MD Anderson Cancer Center, 1400 Holcombe Blvd, Unit 409, Houston, TX 77030, USA; [email protected] Received 11 September 2013 Accepted 4 November 2013 Published Online First 18 December 2013
To cite: Feeley TW, Sledge GW, Levit L, et al. J Am Med Inform Assoc 2014;21:772–775. 772
ABSTRACT A recent report from the Institute of Medicine titled Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis, identifies improvement in information technology (IT) as essential to improving the quality of cancer care in America. The report calls for implementation of a learning healthcare IT system: a system that supports patient–clinician interactions by providing patients and clinicians with the information and tools necessary to make well informed medical decisions and to support quality measurement and improvement. While some elements needed for a learning healthcare system are already in place for cancer, they are incompletely implemented, have functional deficiencies, and are not integrated in a way that creates a true learning healthcare system. To achieve the goal of a learning cancer care delivery system, clinicians, professional organizations, government, and the IT industry will have to partner, develop, and incentivize participation.
INTRODUCTION In the USA, there are many challenges to the delivery of high-quality cancer care. The information base is rapidly expanding with knowledge growth in genomics, proteomics, molecular testing, and pharmacology. The number of new patients with cancer is rising as our population ages. New therapies that prolong patients’ lives are leading to a large number of people living with and surviving cancer. Our cancer care delivery system is struggling to meet the needs of our patients, their families, and cancer care teams. Shortages in the cancer care workforce and the rapidly increasing costs of cancer care contribute to an impending crisis. In the past year the Institute of Medicine (IOM) released two major reports that address the key role of informatics in improving the healthcare delivery system. The first report, titled Best Care at Lower Cost: The Path to Continuously Learning Health Care in America, called for information technology (IT) to have a central role in delivering outstanding clinical care by creating a system that constantly collects and analyzes data from patients in a manner that leads to constant improvement in care.1 The newest report from the IOM, Delivering High Quality Cancer Care: Charting a New Course for a System in Crisis, highlights the problems facing our cancer care delivery system.2 The report identified IT as a critical component of the IOM’s conceptual framework for a high-quality cancer care delivery system (figure 1). In the framework, IT supports interactions between patients and clinicians by providing them with the information and
tools necessary to make well informed medical decisions. Health IT collects and reports quality metrics that drive internal improvement, inform the public, and reform payment to reward high quality care. It also plays a role in developing the evidence base from research. A key recommendation from this report is that clinicians, professional organizations, government, and the IT industry should engage in the development of a learning healthcare IT system for cancer that enables real-time analysis of data from cancer patients in a variety of settings. To accomplish this, the IOM encourages professional organizations, the Department of Health and Human Services, payers, patients, clinicians, IT developers, and investigators to develop the necessary components of a learning healthcare system with incentives for rapid implementation. The first national assessment of the quality of cancer care in the USA was sponsored by the IOM in 1999, and has as one of its major recommendations the need for better data systems in cancer to improve quality metric reporting.3 Over the 14 years since that first report, the development of IT as an aid to cancer care delivery has been slow and ineffective.4
A VISION FOR A LEARNING CANCER CARE SYSTEM A learning healthcare IT system for cancer should continually collect and analyze data from a variety of sources including cancer registries, clinical data from electronic health records, and clinical trials to provide the most up-to-date information for clinicians. The system should have patients as its core with data coming from individual patients reported directly by them and their cancer care teams. The rapid deployment of electronic health records is essential for this system, yet much more needs to be done to make the vision a reality. Efforts have been made to develop such systems, like the American Society of Clinical Oncology’s (ASCO) CancerLinQ.5 CancerLinQ has several goals: (1) to capture, aggregate, and analyze longitudinal patient data from any source; (2) to provide cancer care teams with real-time clinical decision support based on clinical guidelines; (3) to measure clinical performance using performance measures; and (4) to explore hypotheses from clinical datasets. Central to that new system is ASCO’s quality oncology practice initiative (QOPI), which has traditionally relied on manual chart abstraction. CancerLinQ will transition this program to eQOPI and allow automatic data abstraction. Following a successful 2012 prototype in breast cancer, CancerLinQ is being expanded to all cancers.6 7
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
Perspective Figure 1 The conceptual framework for a high-quality cancer care delivery system. A learning healthcare information technology system is a key element linking the ever expanding evidence base with the workforce and the patient.
Another major effort to develop a learning healthcare system is Kaiser Permanente’s HealthConnect system that links 9 million Kaiser patients with their healthcare teams over a wide geographic area. The system links outpatient and inpatient records, provides patients with the ability to send their care teams secure messages, and includes decision support for clinicians.8 Although both ASCO’s CancerLinq and Kaiser’s HealthConnect lack some essential elements for a learning healthcare system, both are in the early stages of development, and are examples of early efforts to address the needs for a learning healthcare system. To be complete, a learning healthcare system should address the needs of patients, the clinical workforce, clinical investigators, developers of quality metrics, and payers. The IOM’s report elaborates on these stakeholder needs.2 Patients need access to their electronic health information and should be able to download data into personal health records. They also need to be able provide patient-reported outcomes and information about their individual characteristics and behaviors, in order to inform clinical care and research. The clinical workforce needs improved real-time decision support informed by up-to-date clinical information. This is vital in an age of molecular and genetic information and an ever-expanding supply of targeted pharmacologic agents. The workforce also needs effective electronic tools to facilitate communication among the diverse group of clinicians likely to be caring for a patient, supportive care services, and essential administrative entities. The first four recommendations of the report address the need for patient-centered communication and shared decision making with a well-trained and coordinated workforce.2 Clinical investigators need information to facilitate enrollment of appropriate patients in clinical trials, larger databases with clinically relevant outcomes, and access to big data systems that match clinical information with genomic and proteomic characteristics of both the tumor and the host. Two recommendations in the report specifically address the data needs to improve the evidence base for cancer care.2 Cancer quality metrics developers need more robust IT systems to more efficiently develop meaningful metrics for cancer care delivery that can be applied for performance improvement and public reporting; transparency that does not
exist today. One recommendation from the report addresses the need for the development of a national quality reporting program for cancer care that would have IT at its core both from a metric development standpoint through automated reporting and analysis.2 Payers need systems that permit newer reimbursement models that move away from fee for service and begin to pay for cancer care based on high-quality clinical outcomes. The final two recommendations in the report highlight the path to providing accessible and affordable cancer care for all Americans.2 The goals of all 10 report recommendations are summarized in box 1.
CHALLENGES IN CREATING A LEARNING CANCER CARE SYSTEM Development of a learning healthcare system for cancer has been extremely slow to evolve. Despite the creation of the National Coordinator for Health Information Technology in 2004, accelerated with funding through the Hi-tech Act in 2009, a true learning healthcare system for cancer has yet to materialize. There are technical, implementation, and ethical challenges that need to be overcome for a learning cancer care system to become a reality. A major technical challenge is interoperability, necessary for exchange of data between institutions, among clinicians, with patients, payers, registries, and public reporting entities. Data standards need to be refined and adopted widely. Data need to be collected at the point of care or directly from the patient in a manner that can be easily standardized and extracted. Electronic health record developers need to work cooperatively to ensure that their systems communicate seamlessly with each other and with the appropriate networks. A second major technical challenge is the volume of critical data now being generated due to the proliferation of molecular and genetic testing made possible recently. Management of such big data platforms is new to healthcare yet essential to the construction of a learning healthcare system. Once collected, large data need to be easily extracted and reported from the data repository and appropriate analytic tools applied. While attempts have been made to address each of these technical challenges, there are few examples of a model system that has overcome all of these technical problems.
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
773
Perspective
Box 1 Goals of the 10 recommendations to improve the quality of cancer care in America 1.
Provide patients and their families with understandable information about cancer prognosis, treatment benefits and harms, palliative care, psychosocial support, and costs. 2. Provide patients with end-of-life care that meets their needs, values, and preferences. 3. Ensure coordinated and comprehensive patient-centered care. 4. Ensure that all individuals caring for cancer patents have appropriate core competencies. 5. Expand the breadth of data collected in cancer research for older adults and patients with multiple comorbid conditions. 6. Expand the depth of data collected in cancer research through a common set of data elements that capture patient-reported outcomes, relevant patient characteristics, and health behaviors. 7. Develop a learning healthcare information technology system for cancer that enables real-time analysis of data from cancer patients in a variety of care settings. 8. Develop a national quality reporting program for cancer care as a part of learning healthcare system. 9. Implement a national strategy to reduce disparities in access to cancer care for under-served populations by leveraging community interventions. 10. Improve the affordability of cancer care by leveraging existing efforts to reform payment and eliminate waste.
Implementation is also a challenge to moving forward. Many provider organizations are overwhelmed with performance improvement projects that rely on existing data collection and reporting systems. Implementation of a learning healthcare system will require major changes in the processes of care most clinical providers currently use. Major cultural changes will have to occur to uniformly adopt electronic record keeping and data sharing both with other clinical care providers and with patients themselves. The cost of making this transition is an additional implementation challenge. At a time when our healthcare costs are at an all-time high, making significant capital investments in totally new systems will be an economic challenge to providers and provider organizations. The creation of large datasets from cancer patients presents ethical challenges that must be addressed before a learning healthcare system for cancer can be fully achieved. Regulations protecting patient privacy run counter to collecting information from those same patients to learn from their course of disease and improve care for others. In a learning healthcare system the lines between clinical care and research become blurred and new ways of thinking about improving the quality of care using ongoing patient experiences must be addressed.
A PATH FORWARD The IOM’s report found that the creation of a learning healthcare system for cancer will require an effort on the part of many stakeholders including clinicians, professional organizations, the IT industry, and the federal government. The report made the
774
following recommendation to achieve A Learning Health Care IT System for cancer: Goal: Develop an ethically sound learning healthcare IT system for cancer that enables real-time analysis of data from cancer patients in a variety of care settings. To accomplish this: ▸ Professional organizations should design and implement the digital infrastructure and analytics necessary to enable continuous learning in cancer care. ▸ The Department of Health and Human Services should support the development and integration of a learning healthcare IT system for cancer. ▸ Centers for Medicare and Medicaid Services (CMS) and other payers should create incentives for clinicians to participate in this learning healthcare system for cancer, as it develops. The report indicated that clinicians must lead in the development of this new system leveraging professional organizations and the IT industry. Clinicians ensure that a resulting system will be clinically relevant and minimally intrusive to workflow. Professional organizations are already taking the lead in this area as evidenced by ASCO’s CancerLinQ project, which, while still a pilot program, embodies some of the essential elements outlined. The IT industry can assist in the development of data standards, collection systems, and standardized data repositories that facilitate reporting and analysis. It is imperative that vendors of electronic health records actively participate in this process since easily collected and extracted data is essential in a high-quality cancer care delivery system of the future. The federal government has a critical role coordinating these activities. The Department of Health and Human Services, through the Office of the National Coordinator for Health Information Technology and in cooperation with CMS, can develop regulatory guidance with financial incentives to accelerate the development of a learning healthcare system for cancer. Incentives need to be directed toward the IT industry to develop the tools and toward the care community to implement them. The meaningful use program is an example of how such programs can accelerate the deployment of needed health IT. Finally, the National Cancer Institute can fund innovative programs that enhance IT in its clinical trials programs and in studying other ways of advancing the quality of cancer care using IT. There is a crisis in the quality of care delivered to cancer patients in America today. Health IT can play a major role in improving that care. While this represents a major investment in resources, it is an investment our nation cannot ignore. Acknowledgements This project was supported by: AARP, American Cancer Society, American College of Surgeons’ Commission on Cancer, American Society for Radiation Oncology, American Society of Clinical Oncology, American Society of Hematology, California HealthCare Foundation, Centers for Disease Control and Prevention, LIVESTRONG, National Cancer Institute, National Coalition for Cancer Survivorship, Oncology Nursing Society, and Susan G Komen for the Cure. We thank the members of the IOM Committee on Improving the Quality of Cancer Care: Addressing the Challenges of an Aging Population and the project staff. The authors are responsible for the content of this article, which does not necessarily represent the views of the Institute of Medicine. Contributors All authors (TWF, GWS, LL and PAG) made substantial contribution to the conception and design of this manuscript and the opinions expressed in this opinion ( perspective) piece. In addition, all authors were involved in drafting the article and revising it critically for important intellectual content. All authors gave final approval of the version to be published. Funding This study was supported by Contract Nos. HHSN261200900003C and 200-2011-38807, TO #13 between the National Academy of Sciences and the National Cancer Institute and the Centers for Disease Control and Prevention. Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
Perspective REFERENCES 1 2 3 4
IOM (Institute of Medicine). Best care at lower cost: the path to continuously learning health care in America. Washington, DC: The National Academies Press, 2012. IOM (Institute of Medicine). Delivering high-quality cancer care: charting a new course for a system in crisis. Washington, DC: The National Academies Press, 2013. IOM (Institute of Medicine). Ensuring quality cancer care. Washington, DC: The National Academies Press, 1999. Spinks T, Albright HW, Feeley TW, et al. Ensuring quality cancer care: a follow-up review of the Institute of Medicine’s 10 recommendations for improving the quality of cancer care in America. Cancer 2012;118:2571–82.
5
6 7 8
ASCO (American Society of Clinical Oncology). 2012. CancerLinQ. Building a transformation in cancer care. http://www.asco.org/institute-quality/cancerlinq (accessed 22 Aug 2013) Sledge GW, Miller RS, Hauser R. CancerLinQ and the future of cancer care. Am Soc Clin Oncol Educ Book 2013;2013:430–4. Sledge GW, Hudis CA, Swain SM, et al. ASCO’s approach to a learning health care system in oncology. J Oncol Pract 2013;9:145–8. Kaiser Permanente HealthConnect Electronic Health Record. 2013. http://xnet.kp.org/ newscenter/aboutkp/healthconnect/ (accessed 4 Sep 2013)
Feeley TW, et al. J Am Med Inform Assoc 2014;21:772–775. doi:10.1136/amiajnl-2013-002346
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