Peter D. Stetson

Detecting Adverse Events Using Information Technology

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.

An Electronic Health Record Based on Structured Narrative

OBJECTIVE To develop an electronic health record that facilitates rapid capture of detailed narrative observations from clinicians, with partial structuring of narrative information for integration and reuse. DESIGN We propose a design in which unstructured text and coded data are fused into a single model called structured narrative. Each major clinical event (e.g., encounter or procedure) is represented as a document that is marked up to identify gross structure (sections, fields, paragraphs, lists) as well as fine structure within sentences (concepts, modifiers, relationships). Marked up items are associated with standardized codes that enable linkage to other events, as well as efficient reuse of information, which can speed up data entry by clinicians. Natural language processing is used to identify fine structure, which can reduce the need for form-based entry. VALIDATION The model is validated through an example of use by a clinician, with discussion of relevant aspects of the user interface, data structures and processing rules. DISCUSSION The proposed model represents all patient information as documents with standardized gross structure (templates). Clinicians enter their data as free text, which is coded by natural language processing in real time making it immediately usable for other computation, such as alerts or critiques. In addition, the narrative data annotates and augments structured data with temporal relations, severity and degree modifiers, causal connections, clinical explanations and rationale. CONCLUSION Structured narrative has potential to facilitate capture of data directly from clinicians by allowing freedom of expression, giving immediate feedback, supporting reuse of clinical information and structuring data for subsequent processing, such as quality assurance and clinical research.

Approach to mobile information and communication for health care.

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).

PalmCIS: A wireless handheld application for satisfying clinician information needs

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.

Quantifying clinical narrative redundancy in an electronic health record

OBJECTIVE Although electronic notes have advantages compared to handwritten notes, they take longer to write and promote information redundancy in electronic health records (EHRs). We sought to quantify redundancy in clinical documentation by studying collections of physician notes in an EHR. DESIGN AND METHODS We implemented a retrospective design to gather all electronic admission, progress, resident signout and discharge summary notes written during 100 randomly selected patient admissions within a 6 month period. We modified and applied a Levenshtein edit-distance algorithm to align and compare the documents written for each of the 100 admissions. We then identified and measured the amount of text duplicated from previous notes. Finally, we manually reviewed the content that was conserved between note types in a subsample of notes. MEASUREMENTS We measured the amount of new information in a document, which was calculated as the number of words that did not match with previous documents divided by the length, in words, of the document. Results are reported as the percentage of information in a document that had been duplicated from previously written documents. RESULTS Signout and progress notes proved to be particularly redundant, with an average of 78% and 54% information duplicated from previous documents respectively. There was also significant information duplication between document types (eg, from an admission note to a progress note). CONCLUSION The study established the feasibility of exploring redundancy in the narrative record with a known sequence alignment algorithm used frequently in the field of bioinformatics. The findings provide a foundation for studying the usefulness and risks of redundancy in the EHR.

Mining complex clinical data for patient safety research: a framework for event discovery

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.

Methodological Review: Content overlap in nurse and physician handoff artifacts and the potential role of electronic health records: A systematic review

PURPOSE The aims of this systematic review were: (1) to analyze the content overlap between nurse and physician hospital-based handoff documentation for the purpose of developing a list of interdisciplinary handoff information for use in the future development of shared and tailored computer-based handoff tools, and (2) to evaluate the utility of the Continuity of Care Document (CCD) standard as a framework for organizing hospital-based handoff information for use in electronic health records (EHRs). METHODS We searched PubMed for studies published through July 2010 containing the indexed terms: handoff(s), hand-off, handover(s), shift-report, shift report, signout, and sign-out. Original, hospital-based studies of acute care nursing or physician handoff were included. Handoff information content was organized into lists of nursing, physician, and interdisciplinary handoff information elements. These information element lists were organized using CCD sections, with additional sections being added as needed. RESULTS Analysis of 36 studies resulted in a total of 95 handoff information elements. Forty-six percent (44/95) of the information overlapped between the nurse and physician handoff lists. Thirty-six percent (34/95) were specific to the nursing list and 18% (17/95) were specific to the physician list. The CCD standard was useful for categorizing 80% of the terms in the lists and 12 category names were developed for the remaining 20%. CONCLUSION Standardized interdisciplinary, nursing-specific, and physician-specific handoff information elements that are organized around the CCD standard and incorporated into EHRs in a structured narrative format may increase the consistency of data shared across all handoffs, facilitate the establishment of common ground, and increase interdisciplinary communication.

Preliminary Development of the Physician Documentation Quality Instrument

OBJECTIVES This study sought to design and validate a reliable instrument to assess the quality of physician documentation. DESIGN Adjectives describing clinician attitudes about high-quality clinical documentation were gathered through literature review, assessed by clinical experts, and transformed into a semantic differential scale. Using the scale, physicians and nurse practitioners scored the importance of the adjectives for describing quality in three note types: admission, progress, and discharge notes. Psychometric methods including exploratory factor analysis were applied to provide preliminary evidence for the construct validity and internal consistency reliability. RESULTS A 22-item Physician Documentation Quality Instrument (PDQI) was developed. Exploratory factor analysis (n = 67 clinician respondents) on three note types resulted in solutions ranging from four (discharge) to six (admission and progress) factors, and explained 65.8% (discharge) to 73% (admission and progress) of the variance. Each factor solution was unique. However, four sets of items consistently factored together across all note types: (1) up-to-date and current; (2) brief, concise, succinct; (3) organized and structured; and (4) correct, comprehensible, consistent. Internal consistency reliabilities were: admission note (factor scales = 0.52-88, overall = 0.86), progress note (factor scales = 0.59-0.84, overall = 0.87), and discharge summary (factor scales = 0.76-0.85, overall = 0.88). CONCLUSION The exploratory factor analyses and reliability analyses provide preliminary evidence for the construct validity and internal consistency reliability of the PDQI. Two novel dimensions of the construct for document quality were developed related to form (Well-formed, Compact). Additional work is needed to assess intrarater and interrater reliability of applying of the proposed instrument and to examine the reproducibility of the factors in other samples.

Assessing Electronic Note Quality Using the Physician Documentation Quality Instrument (PDQI-9)

OBJECTIVE: To refine the Physician Documentation Quality Instrument (PDQI) and test the validity and reliability of the 9-item version (PDQI-9). METHODS: Three sets each of admission notes, progress notes and discharge summaries were evaluated by two groups of physicians using the PDQI-9 and an overall general assessment: one gold standard group consisting of program or assistant program directors (n=7), and the other of attending physicians or chief residents (n=24). The main measures were criterion-related validity (correlation coefficients between Total PDQI-9 scores and 1-item General Impression scores for each note), discriminant validity (comparison of PDQI-9 scores on notes rated as best and worst using 1-item General Impression score), internal consistency reliability (Cronbachs alpha), and inter-rater reliability (intraclass correlation coefficient (ICC)). RESULTS: The results were criterion-related validity (r = -.678 to .856), discriminant validity (best versus worst note, t = 9.3, p = .003), internal consistency reliability (Cronbachs alphas = .87-.94), and inter-rater reliability (ICC = .83, CI = .72-.91). CONCLUSION: The results support the criterion-related and discriminant validity, internal consistency reliability, and inter-rater reliability of the PDQI-9 for rating the quality of electronic physician notes. Tools for assessing note redundancy are required to complement use of PDQI-9. Trials of the PDQI-9 at other institutions, of different size, using different EHRs, and incorporating additional physician specialties and notes of other healthcare providers are needed to confirm its generalizability.

Development of an Ontology to Model Medical Errors, Information Needs, and the Clinical Communication Space

Medical errors are common, costly and often preventable. Work in understanding the proximal causes of medical errors demonstrates that systems failures predispose to adverse clinical events. Most of these systems failures are due to lack of appropriate information at the appropriate time during the course of clinical care. Problems with clinical communication are common proximal causes of medical errors. We have begun a project designed to measure the impact of wireless computing on medical errors. We report here on our efforts to develop an ontology representing the intersection of medical errors, information needs and the communication space. We will use this ontology to support the collection, storage and interpretation of project data. The ontologys formal representation of the concepts in this novel domain will help guide the rational deployment of our informatics interventions. A real-life scenario is evaluated using the ontology in order to demonstrate its utility.