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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions 2 A Vision for 21st Century Health Care and Wellness The Institute of Medicine (IOM) defines health care quality as “the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge,” and in recent years, a broad consensus has emerged on the future health care environment. In the words of the IOM, health care should be:1 Safe—avoiding injuries to patients from the care that is intended to help them. Effective—providing services based on scientific knowledge to all who could benefit and refraining from providing services to those not likely to benefit, avoiding underuse and overuse, respectively. Patient-centered—providing care that is respectful of and responsive to individual patient preferences, needs, and values and ensuring that patient values guide all clinical decisions. Timely—reducing waits and sometimes harmful delays for both those who receive and those who give care. Efficient—avoiding waste, including waste of equipment, supplies, ideas, and energy. Equitable—providing care that does not vary in quality because of 1 Institute of Medicine, Crossing the Quality Chasm: A New Health System for the 21st Century, National Academy Press, Washington, D.C., March 2001.
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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions personal characteristics such as gender, ethnicity, geographic location, and socioeconomic status. The IOM vision calls for a health care system that is systematically organized and acculturated in ways that make it easy and rewarding for providers and patients to do the right thing, at the right time, in the right place, and in the right way. This vision entails many different factors (e.g., systemic changes in paying for health care, an emphasis on disease prevention rather than disease treatment). But none is more important than the effective use of information.2 Based on its observations and expertise, the committee identified a number of information-intensive aspects of the IOM’s vision for 21st century health care. Each bullet phrase below summarizes one of these important health care IT capabilities, followed by an illustrative vignette of what might be possible. The vignettes (displayed in italic type) are not comprehensive (i.e., they do not cover all aspects of the capability). Comprehensive data on patients’ conditions, treatments, and outcomes. A clinician needs to know what medications an elderly, memory-challenged patient is taking. Recognizing the important difference between medications prescribed and medications taken, the clinician asks the patient to bring all of his pill containers, both prescription and over-the-counter, to the appointment. She asks the patient to place all of the containers on a surface table computer, which automatically identifies the medications in each of the containers and counts the number of pills remaining in each container. The pill containers also carry RFID [radio-frequency identification] tags, on which the initial fill-up quantities of the containers are stored. The table can read these tags, and thereby make an inference about what pills were actually taken and provide information about likely compliance with a particular medication regime.3 Farther in the future, recognizing the differences in how 2 Institute of Medicine, The Computer-Based Patient Record: An Essential Technology for Health Care (Revised Edition), National Academy Press, Washington, D.C., 1997, available at http://www.nap.edu/openbook.php?isbn=0309055326; Institute of Medicine, Key Capabilities of an Electronic Health Record System: Letter Report, The National Academies Press, Washington, D.C., 2003, available at http://www.nap.edu/catalog.php?record_id=10781; Institute of Medicine, Patient Safety: Achieving a New Standard for Care, The National Academies Press, Washington, D.C., 2004, available at http://www.nap.edu/openbook.php?isbn=0309090776. 3 If purchase history were available to provide information on when the container was filled, inferences could be made about the frequency and timing of pill-taking, rather than only the total number of pills taken.
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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions individuals absorb or clear medications from their bodies, a blood sample of the patient in question is analyzed with a mass spectrometer or other similar device, and the resulting spectrum identifies the actual level of all drugs in the patient’s body. Combined with information from the smart table, a profile of the patient’s compliance and pharmacokinetics for each drug is generated. The clinical significance of the smart medications table and the mass spectrometer is that together they help to reduce uncertainty by synthesizing different views into the patient’s medication history. Cognitive support for health care professionals and patients to help integrate patient-specific data where possible and account for any uncertainties that remain.4 A primary care clinician needs to monitor a patient’s heart condition. Cardiac information is provided to the clinician not in the form of tables of numbers or individual EKG plots, but rather as an overlay on a visual animated structural model of the patient’s heart (not a generic heart) derived from various imaging modalities. The system displays the relevant functional information in summary form and provides an image of the heart in operation driven by all of the data that have been collected about the patient over time. Different time scales are available for display, and the clinician can display an animated image of the patient’s heart in operation as the patient is resting or exerting himself (i.e., in near-real time), or track how the structure of the heart has changed over the last 2 years using time-lapse-like sequences. Functional histories are also available. Histories are instantly available in easy-to-read form, with different parameter histories presented on similar-looking charts normalized to z-scores and timescales, showing upper and lower “normal” and physiologic bounds.5 The clinician also has the ability to drill down to any supporting piece of information that underlies the display. The clinical significance of an animated structural model is that it drastically reduces the cognitive effort needed for the clinician to visualize the heart functioning in this particular patient, freeing her to use those cognitive resources for other related tasks. The model also helps the patient to understand the medical situation at hand and assists both clinician and patient in determining an appropriate course of action. 4 In this report, “cognitive support” refers to IT-based tools and systems that provide users (clinicians and patients) with the information, abstractions, and models needed to achieve the IOM’s vision of health care quality. 5 See, for example, Seth Powsner and Edward Tufte, “Graphical Summary of Patient Status,” The Lancet 344(8919):386-389, August 6, 1994, available at http://www.stottlerhenke.com/projects/IPDRA2/info_resources/powsner_tufte_graphical_patient_summary.pdf.
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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions Cognitive support for health care professionals to help integrate evidence-based practice guidelines and research results into daily practice. A primary care clinician has a number of patients with various heart conditions. In order to help stay current with recent literature, he subscribes to alerts from the medical literature and learns that a particular heart disease guideline has been updated to include a new drug that reportedly prevents a difficult and expensive complication. After comparing it to other guidelines that he believes to be trustworthy, he decides to incorporate this new guideline into his practice. By clicking on a link, the clinician can download the guideline to his system, which also searches for and constructs several potential action flowcharts to meet the guideline’s goals, based on an internal computable model of clinic workflow and resources. He selects one and his disease management dashboards, order sets, and reminder systems are updated. (A dashboard is an easily viewed display that summarizes the health status of multiple patients.) The clinical significance of the literature alert system is that it enables the clinician to keep current and to systematically translate new knowledge into his practice while enabling the clinician and the patient to decide on the appropriate course of treatment. Instruments and tools that allow providers to manage a portfolio of patients and to highlight problems as they arise both within individual patients and within populations. The computer of an outpatient care provider displays the summary health status (a “dashboard”) of her 300 diabetic patients with color-codes and carefully designed graphical displays for clinical measures of the disease (blood sugar levels, A1C counts, and so on) that provide rapid assessment, at a glance, of the status of all patients: those who are managing illnesses successfully, those requiring intervention, and those who are marginal cases. When a diabetic patient visits her, the system reviews applicable guidelines, customizes an order set to the patient’s state and insurance plan (e.g., picks the preferred drug from the drug class), and reminds the physician to discuss the selected drug with the patient. Feedback indicating success is provided when the provider sees that the display indicators of her patients show successful management. The clinical significance of a summary health status display is that it gives the provider prompt feedback about where her attention is most needed in time to take corrective action. Rapid integration of new instrumentation, biological knowledge, treatment modalities, and so on, into a “learning” health care system that
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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions encourages early adoption of promising methods but also analyzes all patient experience as experimental data. A pediatrician in Los Angeles finds herself working with an ever growing set of young patients with severe asthma. A group of them have added her to their Facebook page where they run a special widget that shows her when and where they did moderate or high physical activity outdoors. The application does not rely on self-reporting. Rather, the young people run an application on their mobile phones that uploads an SMS message containing their current location every 30 seconds to a private account where an application processes and summarizes location-activity data generated from accelerometers on their phones. The doctor has recently introduced a new feature whereby her patients use special Bluetooth-equipped inhalers that report via the mobile phone each time the inhaler is used. The website then displays when and where they used their Bluetooth-enabled inhalers. In addition to viewing trends over time, and patterns based on time of year and day of the week, she runs an application that relates her patients’ activity to real-time pollution exposure models made available by the city. She uses the data to make a case to the city about other possible activity locations (e.g., different outdoor parks) and is soon going to enable her patients to sign up for automated customized alerts when they are overexerting themselves under hazardous environmental conditions. The clinical significance of an automated activity reporting and processing system is that it provides reliable data on what patients actually do (rather than what they say they do) in a form that is easy to understand, as well as additional detail to link to other data sources to clarify patterns, and delivery that is timely enough to support real-time feedback in time to change behavior. Accommodation of the growing heterogeneity of locales for the provision of care, including home instrumentation for monitoring and treatment, lifestyle integration, and remote assistance. A diabetic patient wears an active sensor that provides continuous blood-sugar readings. When these readings approach levels that indicate that actions need to be taken (e.g., taking an insulin shot, eating something), the sensor provides an indication to the patient. Acting with the patient’s prior consent, if the patient fails to take the necessary action (as would be indicated by increasingly dangerous readings), the sensor communicates with a cell phone to place a call to an emergency caregiver. Along with the patient’s vital signs and intake information (name, present location, and so on), the call also provides a summary of the relevant readings so that the caregiver can be dispatched to the site
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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions of the emergency and be prepared for what action should be taken. The clinical significance of an active sensor is that emergency intervention can be requested in the absence of patient action, and that the emergency response can be provided in advance with information that would otherwise have to be gathered immediately upon arrival. Empowerment of patients and their families in effective management of health care decisions and execution, including personal health records (as contrasted to medical records held by care providers), education about the individual’s conditions and options, and support of timely and focused communication with professional health care providers. The son of an elderly man hospitalized by a stroke needs to know about his father’s medical condition. Rather than waiting for hours by his father’s bedside to intercept a physician on rounds so that he can obtain authoritative information, he logs into a secure application that makes his father’s electronic health record (EHR) available on the Internet. But since he is not a physician himself, he invokes a data interpretation application that examines the data in the EHR and provides in lay language a summary of the important aspects of a patient’s medical condition, previously provided treatments, and treatment options under consideration. The application provides an interpretation (and the reasoning behind the interpretation) that is comparable to that which an experienced clinician could provide. The clinical significance of an automated EHR lay interpretation system is that the family can be kept in the decision-making loop, in a culturally sensitive way and on a more timely basis than is possible today, and potentially avoid delays often involved when families need time to make decisions—since they learn relevant facts sooner (perhaps even days sooner), they can start the process sooner. In addition to the data flowing from caregivers, the son can also enter information based on his knowledge of his father’s present state and medical history, providing caregivers with another source of information, and empowering the son to have a greater role in his father’s treatment.