|Home | About | Journals | Submit | Contact Us | Français|
Much of what is currently documented in the electronic health record is in response toincreasingly complex and prescriptive medicolegal, reimbursement, and regulatory requirements. These requirements often result in redundant data capture and cumbersome documentation processes. AMIA's 2011 Health Policy Meeting examined key issues in this arena and envisioned changes to help move toward an ideal future state of clinical data capture and documentation. The consensus of the meeting was that, in the move to a technology-enabled healthcare environment, the main purpose of documentation should be to support patient care and improved outcomes for individuals and populations and that documentation for other purposes should be generated as a byproduct of care delivery. This paper summarizes meeting deliberations, and highlights policy recommendations and research priorities. The authors recommend development of a national strategy to review and amend public policies to better support technology-enabled data capture and documentation practices.
Since 2006, AMIA has convened an annual invitational Health Policy Meeting to examine emerging issues linking healthcare and health information technology (health IT) policy. The overarching objective of each meeting has been to further a national understanding of important topics in this domain and inform subsequent public policy deliberations and decisions. Previous meetings have focused on innovation challenges in health IT and informatics; unintended consequences of health IT and policy; informatics-enabled evidence-based care; and development and advancement of a national framework for health data use. Each meeting has identified policy recommendations and highlighted areas for further study and research. Post-meeting outputs have included reports, published in JAMIA, synthesizing conference outcomes.1–5 As described in this paper, AMIA's 2011 Health Policy Meeting focused on the current state of technology-enabled clinical data capture and documentation in the hope of shaping these key healthcare processes in the future.
Discussions about the future of clinical data capture and documentation should be viewed within the overall context of trends in the healthcare arena. Key aspects of this context include a vision for the transformation of the US healthcare system into a ‘learning healthcare system’; the ramp-up of electronic health records (EHRs) into an essential technology for healthcare improvement; and a growing system-wide emphasis on securing better health outcomes for both individuals and populations. A ‘learning healthcare system’, as defined in a 2007 Institute of Medicine (IOM) report, is ‘… designed to generate and apply the best evidence for the collaborative healthcare choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in healthcare’.6
Among the key prerequisites for the learning system is the ‘… comprehensive deployment and effective application of the full capabilities available in EHRs …’.7 A 2010 IOM workshop focused on clinical data as the knowledge generation engine that could provide the foundation for national efforts to transform health and healthcare.8 Shifts toward the next generation of health records that will yield the rich data to power this engine are currently underway. From the 1997 IOM report that found a long list of uses for EHRs9 to the 2010 report by the National Center for Health Statistics citing increased uptake10 to the 2012 announcement by the US Department of Health and Human Services (DHHS) that the EHR Incentive Program has spurred more than 100 000 healthcare professionals to use EHRs,11 evidence is growing that adoption and use of EHRs is gathering speed throughout the healthcare system.
Concurrent with these trends is the nationwide focus on improving healthcare quality, reducing costs and, ultimately, achieving better patient outcomes.12 EHRs play a key role in these efforts by providing access to data that can improve individual care as well as support clinical research, quality improvement efforts and the achievement of public health objectives—all of which work towards system-wide improvement of outcomes.13
Very early medical and health records can be found in ancient Egyptian papyri14 15; today's health records are in transition from paper to an electronic format. This transition is enabling the inclusion of multimedia elements in addition to clinical chart information, allowing mining of EHR data using sophisticated semantic and statistical techniques, and fostering experimentation with new approaches such as the integration of streaming media into EHRs.16 17
Historically, patients’ health records ideally contained comprehensive health information including medical and family history, list of recent symptoms, list of past and current medications, physical examination findings, results from diagnostic tests, clinicians’ assessments, and therapeutic procedures.18–20 Clinical data capture and documentation refer to the processes of eliciting and recording clinical histories, findings, observations, assessments, care interventions, and care plans in an individual's health record. The main purposes of these functions are to support and enhance health and healthcare by facilitating clinical reasoning and decision making by individual clinicians and allied health practitioners, and by promoting communication and coordination within and across clinical teams, ideally with patients as part of the care team.
There are concerns that documentation processes, practices, and requirements are heavily and inappropriately focused on payment and regulatory requirements rather than on care delivery, health promotion, and prevention.21–23 Much of what is currently documented and contained in the health record responds not to clinical needs but, instead, to diverse and increasingly complex and prescriptive medicolegal, reimbursement, accreditation, and regulatory requirements. Data capture and documentation processes are influenced strongly by multiple layers of federal and state regulations and private sector requirements and mandates such as health services utilization review, quality reporting, accreditation, payment justification, and licensure. This often results in redundant data capture and cumbersome documentation processes. A recent addition to the documentation burden is the requirement engendered by the Centers for Medicare & Medicaid Services’ (CMS) incentive payments for the Meaningful Use (MU) of EHRs to report specific data elements for MU objectives and clinical quality measures.24
The transition from paper to electronic documentation has introduced fundamental changes as existing paper-based practices are being adapted to an electronic environment. Increasing adoption and use of EHRs has raised concerns that the paradigm for electronic data capture and documentation is overly determined by the historical model of paper-based documentation,25 and that suboptimal documentation practices in the paper world will be propagated to the electronic world.
To realize the full potential envisioned by the IOM of the shift from paper to EHRs will require addressing fundamental issues: sorting out the different roles of documentation within a technology-enabled environment; determining what data are key to creating a vibrant learning healthcare system that is focused on securing better patient outcomes; identifying how electronic documentation of key data can best be integrated into clinical workflow; and clarifying the roles of care team members, including the patient, in creating and accessing the electronic record.
Previous research has focused on the potential value of electronic data capture and documentation as well as on the challenges they pose. This section provides selected highlights of recent work with an emphasis on workflow, documentation value and quality issues, and collaborative potential.
Considering the shift to electronic documentation, Weed described the need for electronic tools that ‘reveal the actions and thought processes of providers’, adding that such tools ‘would permit corrective feedback loops and quality control’.26 It is impossible to develop documentation tools that fit within clinicians’ work patterns unless those patterns are understood and acknowledged. Clinicians spend much of their daily working time on documentation.27–29 Electronic documentation allows faster and more complete access to the patient record.30 However, most studies assessing time efficiency have noted a substantial increase in time spent documenting by physicians when using an EHR compared with paper.31 Others have reported changes to workflow and an adverse effect on documentation quality, particularly as a result of the introduction and propagation of errors due to copy-and-paste.32–35 Where concise progress notes were once the norm, they may now contain many pages of laboratory test results, complete reports of radiographic studies, and detailed dispensing instructions for outpatient medications. Mixed results are reported for nursing. A consistent finding, however, is that, where nursing documentation efficiencies were found, these tended to be mitigated by the addition of new computer-related tasks.31 36 37
Discussing the ability to obtain reusable data from EHR systems, Rosenbloom et al38 39 examined the tension between expressivity and structured clinical documentation, considered ways to extract reusable data from clinical notes, and recommended that clinicians choose how to document patient care based on their workflow and note content needs. One method of understanding clinical note writing workflow is to study what is not being documented within formal clinical notes. Instead of progress notes that are an official part of the patient record, clinicians often rely on unofficial parallel forms of daily documentation such as ‘sign out’ notes in their day-to-day care of their patients. It is likely that a substantial amount of important clinical activity that never becomes part of the formal health record is captured in these informal paper documents. For example, clinical ‘to-do’ lists are commonly used to keep track of important care plan items and to facilitate the hand-off of clinical responsibilities.40
Stetson et al noted that documents are created for many different purposes and their value and quality may be assessed using different metrics that may not be compatible. For example, a note might be written to inform a colleague about the clinical status of a patient without concern that it generates a ‘comprehensive bill’. Thus, it might be deemed of high value with respect to clinical communication but poorly compliant and not supportive of billing or utilization review or clinical quality measures.41 Others have discussed the challenges to quality associated with excessive clutter and wrong information stored in electronic notes.33 34 Several investigators have analyzed detailed EHR system usage logs to determine how clinical documentation and data are used after they have been stored in the EHR.40 42–45 An analysis by Hripcsak et al showed that about 16% of attending physicians’ notes, 8% of resident physicians’ notes, and 38% of nurses’ notes were never read by anyone at all; however, it also revealed that clinical notes are sometimes viewed in the EHR months or even years after they are authored, buttressing the argument for persistent storage of, and access to, historical health information. The study did not shed light on which notes should be read by other members of the care team or what proportion of documentation was captured primarily for medicolegal, administrative, or research purposes.46
One of the benefits of electronic data capture and documentation is the potential to provide clinical decision support. However, East et al47 and Nelson et al48 have described problems with data accuracy and timeliness as major challenges for computerized decision support applications. Vawdrey et al49 assessed the quality of EHR documentation in the intensive care setting by measuring the percentage of time that manually-recorded and automatically-acquired data sources matched, as well as the charting delay (the interval between an individual collecting a measurement, such as a patient's blood pressure, and entering it in the EHR). Automated collection of physiological measurements and other parameters from devices such as bedside monitors, infusion pumps, and mechanical ventilators can reduce the documentation burden on clinicians and also improve the quality of data stored in EHRs.
Among the benefits of EHRs is the ability to foster clinical collaboration.50 However, a 2009 National Research Council report noted that EHRs provide little cognitive support for collaboration.51 O'Malley et al52 discussed ways in which EHRs have been shown to facilitate care coordination in physician practices as well as obstacles that inhibit realization of this goal; one example of the latter is the fact that existing reimbursement policies encourage documentation of billable events in EHRs and not of care coordination activities which are not billable. MacPhail et al53 reported on a qualitative multiple case study of coordination of diabetes care using EHRs in four Kaiser Permanente Medical Centers which showed that, while coordination was attained across providers, coordination challenges persisted. Chan et al54 described the development of five EHR-based care coordination measures for use in primary care and specialist settings, and assessed the relevance and acceptability of the measures by primary care providers.
Because of the importance of high quality documentation and data in supporting patient care, and given current initiatives encouraging EHR adoption and use, it is crucial to understand how documentation and data capture processes and related policies may be impacted by ‘going electronic’. The goals of the 2011 Health Policy Meeting were the following:
The meeting convened on December 6–7, 2011 in the metropolitan Washington, DC area. In the months leading up to the meeting, a Steering Committee comprised of AMIA members who are experts in the field set the meeting goals, prepared the agenda, and made suggestions about discussants, presenters, and attendees. The nearly 100 attendees included representatives from various segments of the health IT and informatics fields including providers, academicians, technology vendors, specialty societies, pharmaceutical companies, consulting firms, researchers, government agencies, and consumer advocates.
Plenary sessions provided context for the discussions and helped participants to focus on key issues in the dynamic area of technology-enabled data capture and documentation. Speakers included Jon White, Director, Health Information Technology (Health IT) Portfolio, Agency for Healthcare Research and Quality (AHRQ) and Farzad Mostashari, National Coordinator, Office of the National Coordinator for Health Information Technology (ONC). A panel discussion on research and innovation in this field featured presentations by Jim Cimino, Chief, Laboratory for Informatics Development, NIH Clinical Center; Bethany Daily, Administrative Director, Peri-Operative Strategic/Business Initiatives, Massachusetts General Hospital; and Hal Wolf, Senior Vice President and Chief Operating Officer, Kaiser Permanente.
Plenary sessions were followed by facilitated breakout discussions designed to help participants focus ideas, summarize comments and formulate recommendations, and action items. During the breakouts, participants explored the ways in which recording data for multiple purposes competes with the fundamental purpose of documentation of supporting sound clinical care. They highlighted the shortcomings of current approaches that impede efficient data capture and presentation, fall short of accurately representing clinicians’ thinking, and fail to accommodate clinical workflow. Breakout sessions also focused on ways in which advancing technologies are affecting documentation and data capture, and the role of policy in driving innovative change in the health record that will yield improvements in terms of data input and output. The sessions helped formulate potential recommendations to government, industry, academia, and other stakeholders that could enable the realization of the ideal state of electronic clinical data capture and documentation.
The major products of the meeting (see below) were policy-oriented recommendations and a suggested research agenda to strengthen the evidence base related to clinical data capture and documentation. Additionally, participants reviewed and refined a set of proposed principles (box 1), developed by the Steering Committee before the meeting, to guide the future evolution of high value data capture and documentation. Participants also discussed strategies to promote widespread dissemination and application of the principles.
Clinical data capture and documentation should:
Meeting participants also reviewed a proposed set of descriptors for high quality information that had been developed by the Steering Committee in advance of the meeting. These attributes include high sensitivityi (all of the information needed by the patient's care team is created and recorded) and high specificity (information that is not needed by the care team is not displayed); cogency (information is created and recorded in ways to make it easy to read, process, and act on by humans and computers); and actionability (information helps guide the patient's team in executing effective, safe, efficient, and satisfying interventions. Being actionable includes being computable, for example, in clinical prediction rules when appropriate to the patient's needs). While high sensitivity and high specificity are attributes of high quality information, it should also be noted that they are context-dependent. For example, an item of information might be highly useful and should be displayed to a decision maker when a diagnosis is being established, but of lower usefulness and should be hidden when management or disposition is the task at hand. Further refinement of these descriptors is needed to reflect these nuances.
Meeting participants concluded that high value documentation is important to—and representative of—high quality patient care. The consensus among participants was that, in the move to a technology-enabled healthcare environment, the main purposes of documentation should continue to be to support and enhance patient care by facilitating clinical reasoning and decision making of individual clinicians and by supporting team communication and coordination, with the inclusion of the patient. However, participants recognized that, given the growing complexity of care delivery and advances in heath IT and informatics, there is a need to transform the way we capture and document clinical care. To some extent, the industry has failed to exploit technology in ways that would help to capture and present healthcare data. With some reimbursement methods at least partially based on the amount of documentation, there is an incentive to document extensively. This leads to duplicate information, ‘captured’ repetitively, without any resultant improvement in the provision of care. Because more efficient patient assessment and information capture may have the potential to reduce payment, there is little incentive to explore alternative data capture or documentation practices.
Key findings and public policy recommendations discussed by meeting participants and refined by the authors are outlined below. The authors propose that public and private sector organizations work together to implement these recommendations.
Meeting participants highlighted several important questions and gaps in the evidence base pertaining to data capture and documentation that need to be addressed by additional research:
Below are recommendations for research activities to address these and other pressing questions related to data capture and documentation:
AMIA's 2011 Health Policy Meeting examined current issues related to clinical data capture and documentation and took the long look ahead to envision changes that would help realize an ideal future state of these functions. Thoughtful consideration by diverse stakeholders of the strengths and weaknesses of current approaches led to the identification of knowledge gaps and policy and research priorities, as described in this paper.
Technological advances in the documentation sphere will continue to emerge to enable the inclusion of increasingly sophisticated data—for example, capture and integration of genomic information in the EHR to help propel personalized medicine.55–57 While technology will make futuristic data capture opportunities possible, attention must continue to be paid to the core issues discussed during the meeting that are central to a learning healthcare system using a computer-based infrastructure. These include the need for data capture and presentation methods that support clinicians’ cognitive needs and workflow; the inclusion of the high quality data in the electronic record necessary to undergird national strategies to achieve better health outcomes for individuals and populations; and use of EHR documentation to support holistic approaches such as multidisciplinary team-based care and enhanced participation by patients in promoting health and treating illness.
By convening this meeting and disseminating this report, AMIA has identified technology-enabled clinical data capture and documentation as a critical issue in national efforts to achieve high quality health and healthcare. The AMIA Board of Directors reviewed this paper and endorsed the authors’ recommendations. The Board of Directors anticipates committing additional organizational resources to continue to advance the work of the meeting and will encourage other organizations to work collaboratively to pursue the recommendations and to continue this important public discourse.
AMIA would like to acknowledge the contributions of the many individuals who helped to plan and convene this meeting and to develop the resulting paper. David Bates, Meryl Bloomrosen, Caitlin Cusack, George Hripcsak, Gil Kuperman, Nancy Lorenzi, Lena Mamykina, Doug Peddicord, Trent Rosenbloom, Ted Shortliffe, Freda Temple, David Vawdrey, Jim Walker, Charlotte Weaver, and Adam Wright served as members of the Meeting Steering Committee. They were actively involved in and provided valuable input to all aspects of the planning process. AMIA also wants to acknowledge and thank the organizations that generously supported the meeting. Sponsors were Booz Allen, Kaiser, and Westat. The authors also wish to express their thanks to Freda Temple for her careful review and editing of all versions of the manuscript.
iSensitivity is used here in a statistical or epidemiological sense rather than referring to ‘sensitive’ patient information that is subject to privacy concerns.
Contributors: All authors contributed to writing and reviewing the manuscript.
Funding: This work received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors other than that described in the Acknowledgements.
Competing interest: None.
Provenance and peer review: Not commissioned; externally peer reviewed.