Paul C Tang
Other Teaching Staff-Hourly, Medicine - Primary Care and Population Health
Bio
Dr. Tang is Adjunct Professor in the Clinical Excellence Research Center at Stanford University and a practicing internist at the Palo Alto Medical Foundation. Most recently, he was Vice President, Chief Health Transformation Officer at IBM Watson Health. He has served in executive administration roles in health systems for over 25 years. Prior to joining Watson Health, Dr. Tang was Vice President, Chief Innovation and Technology Officer at the Palo Alto Medical Foundation (PAMF), directing the David Druker Center for Health Systems Innovation, a disruptive innovation center focused on grand challenges in health. Dr. Tang led one of the earliest implementations of an Electronic Health Record (EHR) system in the country in 1996, and in 2000, he co-developed MyChart, the first commercial patient portal, with Epic.
Dr. Tang is an elected member of the National Academy of Medicine, and has served on numerous NAM study committees, including a patient-safety committee he chaired that published two reports: Patient Safety: A New Standard for Care, and Key Capabilities of an Electronic Health Record System. He is a member of the Health and Medicine Division committee of the National Academies of Science, Engineering, and Medicine. Dr. Tang was co-chair of the federal Health Information Technology Policy committee from 2009-2017. He has served as board chair for several health informatics professional associations, including the American Medical Informatics Association (AMIA). He has served on the boards of AMIA, National Quality Forum, AcademyHealth, Computer-based Patient Record Institute, Joint Health Information Technology Alliance, NAM Board on Health Care Services, and National eHealth Collaborative. Dr. Tang is a recipient of the Nicholas E. Davies Award for Excellence in Computer-based Patient Record System Implementation, and the AMIA Don E. Detmer Award for Health Policy Contributions in Informatics. He currently holds one patent and has 16 patents pending. He has published numerous papers in medical informatics, appearing in New England Journal of Medicine, JAMA, Health Affairs, Annals of Internal Medicine, and Journal of the American Medical Informatics Association. Dr. Tang is a Fellow of the American College of Physicians, the American College of Medical Informatics, the College of Healthcare Information Management Executives, and the Healthcare Information and Management Systems Society.
He received his B.S. and M.S. in Electrical Engineering from Stanford University and his M.D. from the University of California, San Francisco. He completed his residency in internal medicine at Stanford University and is a board-certified practicing internist at the Palo Alto Medical Foundation.
All Publications
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The Promise of Digital Health: Then, Now, and the Future.
NAM perspectives
2022; 2022
View details for DOI 10.31478/202206e
View details for PubMedID 36177208
View details for PubMedCentralID PMC9499383
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A retrospective look at the predictions and recommendations from the 2009 AMIA policy meeting: did we see EHR-related clinician burnout coming?
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2021; 28 (5): 948-954
Abstract
Clinicians often attribute much of their burnout experience to use of the electronic health record, the adoption of which was greatly accelerated by the Health Information Technology for Economic and Clinical Health Act of 2009. That same year, AMIA's Policy Meeting focused on possible unintended consequences associated with rapid implementation of electronic health records, generating 17 potential consequences and 15 recommendations to address them. At the 2020 annual meeting of the American College of Medical Informatics (ACMI), ACMI fellows participated in a modified Delphi process to assess the accuracy of the 2009 predictions and the response to the recommendations. Among the findings, the fellows concluded that the degree of clinician burnout and its contributing factors, such as increased documentation requirements, were significantly underestimated. Conversely, problems related to identify theft and fraud were overestimated. Only 3 of the 15 recommendations were adjudged more than half-addressed.
View details for DOI 10.1093/jamia/ocaa320
View details for Web of Science ID 000648977800008
View details for PubMedID 33585936
View details for PubMedCentralID PMC8068422
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Precision population analytics: population management at the point-of-care
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2021; 28 (3): 588-595
Abstract
To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.We developed disease-specific, machine-learning, patient-similarity models for hypertension (HTN), type II diabetes mellitus (T2DM), and hyperlipidemia (HL) using data on approximately 2.5 million patients in a large medical group practice. For each identified decision point, an encounter during which the patient's condition was not controlled, we compared the actual outcome of the treatment decision administered to that of the best-achieved outcome for similar patients in similar clinical situations.For the majority of decision points (66.8%, 59.0%, and 83.5% for HTN, T2DM, and HL, respectively), there were alternative treatment options administered to patients in the precision cohort that resulted in a significantly increased proportion of patients under control than the treatment option chosen for the index patient. The expected percentage of patients whose condition would have been controlled if the best-practice treatment option had been chosen would have been better than the actual percentage by: 36% (65.1% vs 48.0%, HTN), 68% (37.7% vs 22.5%, T2DM), and 138% (75.3% vs 31.7%, HL).Clinical guidelines are primarily based on the results of randomized controlled trials, which apply to a homogeneous subject population. Providing the effectiveness of various treatment options used in a precision cohort of patients similar to the index patient can provide complementary information to tailor guideline recommendations for individual patients and potentially improve outcomes.
View details for DOI 10.1093/jamia/ocaa247
View details for Web of Science ID 000637314400018
View details for PubMedID 33180897
View details for PubMedCentralID PMC7936526
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Personalized treatment options for chronic diseases using precision cohort analytics
SCIENTIFIC REPORTS
2021; 11 (1): 1139
Abstract
To support point-of-care decision making by presenting outcomes of past treatment choices for cohorts of similar patients based on observational data from electronic health records (EHRs), a machine-learning precision cohort treatment option (PCTO) workflow consisting of (1) data extraction, (2) similarity model training, (3) precision cohort identification, and (4) treatment options analysis was developed. The similarity model is used to dynamically create a cohort of similar patients, to inform clinical decisions about an individual patient. The workflow was implemented using EHR data from a large health care provider for three different highly prevalent chronic diseases: hypertension (HTN), type 2 diabetes mellitus (T2DM), and hyperlipidemia (HL). A retrospective analysis demonstrated that treatment options with better outcomes were available for a majority of cases (75%, 74%, 85% for HTN, T2DM, HL, respectively). The models for HTN and T2DM were deployed in a pilot study with primary care physicians using it during clinic visits. A novel data-analytic workflow was developed to create patient-similarity models that dynamically generate personalized treatment insights at the point-of-care. By leveraging both knowledge-driven treatment guidelines and data-driven EHR data, physicians can incorporate real-world evidence in their medical decision-making process when considering treatment options for individual patients.
View details for DOI 10.1038/s41598-021-80967-5
View details for Web of Science ID 000621767100017
View details for PubMedID 33441956
View details for PubMedCentralID PMC7806725
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Online disease management of diabetes: Engaging and Motivating Patients Online With Enhanced Resources-Diabetes (EMPOWER-D), a randomized controlled trial
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2013; 20 (3): 526-534
Abstract
To evaluate an online disease management system supporting patients with uncontrolled type 2 diabetes.Engaging and Motivating Patients Online With Enhanced Resources for Diabetes was a 12-month parallel randomized controlled trial of 415 patients with type 2 diabetes with baseline glycosylated hemoglobin (A1C) values ≥7.5% from primary care sites sharing an electronic health record. The intervention included: (1) wirelessly uploaded home glucometer readings with graphical feedback; (2) comprehensive patient-specific diabetes summary status report; (3) nutrition and exercise logs; (4) insulin record; (5) online messaging with the patient's health team; (6) nurse care manager and dietitian providing advice and medication management; and (7) personalized text and video educational 'nuggets' dispensed electronically by the care team. A1C was the primary outcome variable.Compared with usual care (UC, n=189), patients in the intervention (INT, n=193) group had significantly reduced A1C at 6 months (-1.32% INT vs -0.66% UC; p<0.001). At 12 months, the differences were not significant (-1.14% INT vs -0.95% UC; p=0.133). In post hoc analysis, significantly more INT patients had improved diabetes control (>0.5% reduction in A1C) than UC patients at 12 months (69.9 (95% CI 63.2 to 76.5) vs 55.4 (95% CI 48.4 to 62.5); p=0.006).A nurse-led, multidisciplinary health team can manage a population of diabetic patients in an online disease management program. INT patients achieved greater decreases in A1C at 6 months than UC patients, but the differences were not sustained at 12 months. More INT than UC patients achieved improvement in A1C (>0.5% decrease). Trial registered in clinical trials.gov: #NCT00542204.
View details for DOI 10.1136/amiajnl-2012-001263
View details for Web of Science ID 000317477500020
View details for PubMedID 23171659
View details for PubMedCentralID PMC3628059
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A global travelers' electronic health record template standard for personal health records
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2012; 19 (1): 134-136
Abstract
Tourism as well as international business travel creates health risks for individuals and populations both in host societies and home countries. One strategy to reduce health-related risks to travelers is to provide travelers and relevant caregivers timely, ongoing access to their own health information. Many websites offer health advice for travelers. For example, the WHO and US Department of State offer up-to-date health information about countries relevant to travel. However, little has been done to assure travelers that their medical information is available at the right place and time when the need might arise. Applications of Information and Communication Technology (ICT) utilizing mobile phones for health management are promising tools both for the delivery of healthcare services and the promotion of personal health. This paper describes the project developed by international informaticians under the umbrella of the International Medical Informatics Association. A template capable of becoming an international standard is proposed. This application is available free to anyone who is interested. Furthermore, its source code is made open.
View details for DOI 10.1136/amiajnl-2011-000323
View details for Web of Science ID 000298848100020
View details for PubMedID 21849333
View details for PubMedCentralID PMC3240759
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Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2006; 13 (2): 121-126
Abstract
Recently there has been a remarkable upsurge in activity surrounding the adoption of personal health record (PHR) systems for patients and consumers. The biomedical literature does not yet adequately describe the potential capabilities and utility of PHR systems. In addition, the lack of a proven business case for widespread deployment hinders PHR adoption. In a 2005 working symposium, the American Medical Informatics Association's College of Medical Informatics discussed the issues surrounding personal health record systems and developed recommendations for PHR-promoting activities. Personal health record systems are more than just static repositories for patient data; they combine data, knowledge, and software tools, which help patients to become active participants in their own care. When PHRs are integrated with electronic health record systems, they provide greater benefits than would stand-alone systems for consumers. This paper summarizes the College Symposium discussions on PHR systems and provides definitions, system characteristics, technical architectures, benefits, barriers to adoption, and strategies for increasing adoption.
View details for DOI 10.1197/jamia.M2025
View details for Web of Science ID 000236118000001
View details for PubMedID 16357345
View details for PubMedCentralID PMC1447551
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The missing link: Bridging the patient-provider health information gap
HEALTH AFFAIRS
2005; 24 (5): 1290-1295
Abstract
Widespread adoption of information technology is now regarded as a pathway to improving health care and achieving the Institute of Medicine's highly regarded six aims for redesigning care. Achieving these aims requires fresh approaches to health system design, including continuous healing relationships between physicians and patients and provision of tools to help patients be more active participants in their own care. Personal health records (PHRs) might allow patients and providers to develop new ways of collaborating and provide the basis for broader transformation of the health care system. Federal policies can be key catalysts in accelerating PHR development and adoption.
View details for DOI 10.1377/hlthaff.24.5.1290
View details for Web of Science ID 000235033400028
View details for PubMedID 16162575
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AMIA advocates national health information system in fight against national health threats
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
2002; 9 (2): 123-124
Abstract
To protect public health and national safety, AMIA recommends that the federal government dedicate technologic resources and medical informatics expertise to create a national health information infrastructure (NHII). An NHII provides the underlying information utility that connects local health providers and health officials through high-speed networks to national data systems necessary to detect and track global threats to public health. AMIA strongly recommends the accelerated development and wide-scale deployment of electronic public health surveillance systems, computer-based patient records, and disaster-response information technologies. Such efforts hold the greatest potential to protect our citizens from disaster and to deliver the best health care if disaster strikes.
View details for DOI 10.1197/jamia.M1051
View details for Web of Science ID 000175018400005
View details for PubMedID 11861625
View details for PubMedCentralID PMC344567
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SEMANTIC INTEGRATION OF INFORMATION IN A PHYSICIANS WORKSTATION
INTERNATIONAL JOURNAL OF BIO-MEDICAL COMPUTING
1994; 35 (1): 47-60
Abstract
Patient care is an information-intensive activity, yet physicians have few tools to effectively access and manage patient data. We studied physicians' information needs in an outpatient clinic, and developed a prototype physician's workstation (PWS) to address those needs. The PWS provides integrated access to patient information and uses embedded domain knowledge to enhance the presentation of clinical information to the physician. All the applications in the PWS share a common patient context, defined by the state of the internal patient model--semantic integration. Relevant data are presented together and higher-order alerts are generated by combining notable events with relevant data from the patient context. Semantic integration allows us to present and to operate on all patient data in a given patient's context, significantly enhancing the effectiveness with which information is presented to the physician.
View details for DOI 10.1016/0020-7101(94)90048-5
View details for Web of Science ID A1994NB28700005
View details for PubMedID 8175208
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MAJOR ISSUES IN USER-INTERFACE DESIGN FOR HEALTH PROFESSIONAL WORKSTATIONS - SUMMARY AND RECOMMENDATIONS
ELSEVIER SCI IRELAND LTD. 1994: 139-148
Abstract
Lack of good user interfaces has been a major impediment to the acceptance and routine use of health-care professional workstations. Health-care providers, and the environment in which they practice, place strenuous demands on the interface. User interfaces must be designed with greater consideration of the requirements, cognitive capabilities, and limitations of the end-user. The challenge of gaining better acceptance and achieving widespread use of clinical information systems will be accentuated as the variety and complexity of multi-media presentation increases. Better understanding of issues related to cognitive processes involved in human-computer interactions is needed in order to design interfaces that are more intuitive and more acceptable to health-care professionals. Critical areas which deserve immediate attention include: improvement of pen-based technology, development of knowledge-based techniques that support contextual presentation, and development of new strategies and metrics to evaluate user interfaces. Only with deliberate attention to the user interface, can we improve the ways in which information technology contributes to the efficiency and effectiveness of health-care providers.
View details for DOI 10.1016/0020-7101(94)90017-5
View details for Web of Science ID A1994MQ42300014
View details for PubMedID 8125627