Biomedical subjects
Publications and source records attributed to Peter D Stetson.
Timely completion of Discharge Summaries is a requirement of high quality care. We developed a system for writing electronic Discharge Summaries. DSUM Writer has generated 2464 of 7349 total summaries (34%) and has paid for itself during its first 8 weeks in production. DSUM Writer is a component of a suite of tools (eNote) for electronic physician documentation used to support clinical care, billing and narrative analysis research.
Evidence suggests that inadequate access to information and ineffective communication are proximal causes of errors and other adverse events in-patient care. Within the context of reducing these proximal causes of errors, we explore the use of novel information-based approaches to improve information access and communication in health care settings. This paper describes the approaches for and the design of extensions to a clinical information system used to improve information access and communication at the point of care using information-based handheld wireless applications. These extensions include clinical and information resources, event monitoring, and a virtual whiteboard (VWB).
PURPOSE: To estimate internal medicine residents' breadth of experience using a published curricular guide and an electronic medical record. METHOD: A cohort of 41 internal medicine residents at Columbia University Medical Center, a large, inner-city, primary and tertiary care center, were followed over their three years of training in the late 1990s. Residents were mapped to the patients they cared for, the diagnoses those patients were assigned, and the Federated Council for Internal Medicine (FCIM) competencies covered. The proportion and distribution of competencies covered (potential to achieve a competency) were measured. RESULTS: Residents covered 76% of priority 1 competencies (those identified by FCIM as optimally learned through direct responsibility for patients) and 67% of all competencies. Although the number of patients cared for was correlated with breadth of experience, the effect was small. Rare diagnoses appear to have been distributed well. CONCLUSION: Internal medicine residents had the potential to achieve the majority of competencies via direct patient care, but no residents achieved full coverage. The electronic medical record may provide a mechanism to track residents and study training programs.
Wireless handheld technology provides new ways to deliver and present information. As with any technology, its unique features must be taken into consideration and its applications designed accordingly. In the clinical setting, availability of needed information can be crucial during the decision-making process. Preliminary studies performed at New York Presbyterian Hospital (NYPH) determined that there are inadequate access to information and ineffective communication among clinicians (potential proximal causes of medical errors). In response to these findings, the authors have been developing extensions to their Web-based clinical information system including PalmCIS, an application that provides access to needed patient information via a wireless personal digital assistant (PDA). The focus was on achieving end-to-end security and developing a highly usable system. This report discusses the motivation behind PalmCIS, design and development of the system, and future directions.
At Columbia-Presbyterian Medical Center, a clinical information system (CIS) called WebCIS is used by health care providers. We have developed a palm-based extension to WebCIS, called PalmCIS, which provides physicians access to clinical data through a wireless connection. As part of PalmCIS, we have added links to two on-line information resources: PubMed and Micromedex.
At Columbia-Presbyterian Medical Center, free-text "Signout" notes are typed into the electronic record by clinicians for the purpose of cross-coverage. We plan to "unlock" information about adverse events contained in these notes in a subsequent project using Natural Language Processing (NLP). To better understand the requirements for parsing, Signout notes were compared to other common medical notes (ambulatory clinic notes and discharge summaries) on a series of quantitative metrics. They are shorter (mean length 59.25 words vs. 144.11 and 340.85 for ambulatory and discharge notes respectively) and use more abbreviations (26.88% vs. 20.07% and 3.57%). Despite being terser, Signout notes use less ambiguous abbreviations (8.34% vs. 9.09% and 18.02%). Differences were found using Relative Entropy and Squared Chi-square Distance in a novel fashion to compare these medical corpora. Signout notes appear to constitute a unique sublanguage of medicine. The implications for parsing free-text cross-coverage notes into coded medical data are discussed.
Successfully addressing patient safety requires detecting medical events effectively. Given the volume of patients seen at medical centers, detecting events automatically from data that are already available electronically would greatly facilitate patient safety work. We have created a framework for electronic detection. Key steps include: selecting target events, assessing what information is available electronically, transforming raw data such as narrative notes into a coded format, querying the transformed data, verifying the accuracy of event detection, characterizing the events using systems and cognitive approaches, and using what is learned to improve detection.
CONTEXT: Although patient safety is a major problem, most health care organizations rely on spontaneous reporting, which detects only a small minority of adverse events. As a result, problems with safety have remained hidden. Chart review can detect adverse events in research settings, but it is too expensive for routine use. Information technology techniques can detect some adverse events in a timely and cost-effective way, in some cases early enough to prevent patient harm. OBJECTIVE: To review methodologies of detecting adverse events using information technology, reports of studies that used these techniques to detect adverse events, and study results for specific types of adverse events. DESIGN: Structured review. METHODOLOGY: English-language studies that reported using information technology to detect adverse events were identified using standard techniques. Only studies that contained original data were included. MAIN OUTCOME MEASURES: Adverse events, with specific focus on nosocomial infections, adverse drug events, and injurious falls. RESULTS: Tools such as event monitoring and natural language processing can inexpensively detect certain types of adverse events in clinical databases. These approaches already work well for some types of adverse events, including adverse drug events and nosocomial infections, and are in routine use in a few hospitals. In addition, it appears likely that these techniques will be adaptable in ways that allow detection of a broad array of adverse events, especially as more medical information becomes computerized. CONCLUSION: Computerized detection of adverse events will soon be practical on a widespread basis.
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