Publications by authors named "Peter D Stetson"

49 Publications

When Predictive Models Collide.

JCO Clin Cancer Inform 2020 06;4:547-550

Department of Medicine, Digital Informatics and Technology Solutions, Memorial Sloan Kettering Cancer Center, New York, NY.

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http://dx.doi.org/10.1200/CCI.20.00024DOI Listing
June 2020

Interfaces for collecting data from patients: 10 golden rules.

J Am Med Inform Assoc 2020 03;27(3):498-500

Division of Health Informatics, Office of Physician-In-Chief, Memorial Sloan Kettering Cancer Center, New York, USA.

Memorial Sloan Kettering Cancer Center has more than a decade's experience creating online interfaces for obtaining data from patients as part of routine clinical care. We have developed a set of "golden rules" for design of these interfaces. Many relate to the knowledge imbalance between professional staff (whether medical or informatics) and patients, who are often old and sick and have limited knowledge of technology. Others relate to the clinical nature of the encounter: data cannot be taken from patients as part of clinical care unless there is a plan to act on whatever information is prepared. We also note that the plethora of marketing questionnaires makes patients suspicious of surveys: patient trust is hard to gain and easy to lose. Addition of these golden rules to standard approaches to interface design will maximize our ability to obtain data from patients and thus improve communication between patients and clinicians.
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http://dx.doi.org/10.1093/jamia/ocz215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025343PMC
March 2020

Ambulatory cancer care electronic symptom self-reporting (ACCESS) for surgical patients: a randomised controlled trial protocol.

BMJ Open 2019 09 17;9(9):e030863. Epub 2019 Sep 17.

Department of Surgery, Memorial Sloan Kettering Cancer Center, Manhattan, New York, USA.

Introduction: An increasing proportion of cancer surgeries are ambulatory procedures requiring a stay of 1 day or less in the hospital. Providing patients and their caregivers with ongoing, real-time support after discharge aids delivery of high-quality postoperative care in this new healthcare environment. Despite abundant evidence that patient self-reporting of symptoms improves quality of care, the most effective way to monitor and manage this self-reported information is not known.

Methods And Analysis: This is a two-armed randomised, controlled trial evaluating two approaches to the management of patient-reported data: (1) team monitoring, symptom monitoring by the clinical team, with nursing outreach if symptoms exceed normal limits, and (2) enhanced feedback, real-time feedback to patients about expected symptom severity, with patient-activated care as needed.Patients with breast, gynaecologic, urologic, and head and neck cancer undergoing ambulatory cancer surgery (n=2750) complete an electronic survey for up to 30 days after surgery that includes items from a validated instrument developed by the National Cancer Institute, the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Information provided to patients in the Enhanced Feedback group is procedure-specific and based on updated PRO-CTCAE data from previous patients. Qualitative interviews are also performed. The primary study outcomes assess unplanned emergency department visits and symptom-triggered interventions (eg, nursing calls and pain management referrals) within 30 days, and secondary outcomes assess the patient and caregiver experience (ie, patient engagement, patient anxiety and caregiver burden).

Ethics And Dissemination: This study is approved by the Institutional Review Board at Memorial Sloan Kettering Cancer Center. The relationships between the study team and stakeholders will be leveraged to disseminate study findings. Findings will be relevant in designing future coordinated care models targeting improved healthcare quality and patient experience.

Trial Registration Number: NCT03178045.
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http://dx.doi.org/10.1136/bmjopen-2019-030863DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6756418PMC
September 2019

Real-World Outcomes of an Automated Physician Support System for Genome-Driven Oncology.

JCO Precis Oncol 2019 24;3. Epub 2019 Jul 24.

Memorial Sloan Kettering Cancer Center, New York, NY.

Purpose: Matching patients to investigational therapies requires new tools to support physician decision making. We designed and implemented Precision Insight Support Engine (PRECISE), an automated, just-in-time, clinical-grade informatics platform to identify and dynamically track patients on the basis of molecular and clinical criteria. Real-world use of this tool was analyzed to determine whether PRECISE facilitated enrollment to early-phase, genome-driven trials.

Materials And Methods: We analyzed patients who were enrolled in genome-driven, early-phase trials using PRECISE at Memorial Sloan Kettering Cancer Center between April 2014 and January 2018. Primary end point was the proportion of enrolled patients who were successfully identified using PRECISE before enrollment. Secondary end points included time from sequencing and PRECISE identification to enrollment. Reasons for a failure to identify genomically matched patients were also explored.

Results: Data were analyzed from 41 therapeutic trials led by 19 principal investigators. In total, 755 patients were accrued to these studies during the period that PRECISE was used. PRECISE successfully identified 327 patients (43%) before enrollment. Patients were diagnosed with 29 tumor types and harbored alterations in 43 oncogenes, most commonly (21.3%), (14.1%), and (8.7%). Median time from sequencing to enrollment was 163 days (interquartile range, 66 to 357 days), and from PRECISE identification to enrollment 87 days (interquartile range, 37 to 180 days). Common reasons for failing to identify patients before enrollment included accrual on the basis of molecular alterations that did not match pre-established PRECISE genomic eligibility (140 [33%] of 428) and external sequencing not available for parsing (127 [30%] of 428).

Conclusion: PRECISE identified 43% of all patients accrued to a diverse cohort of early-phase, genome-matched studies. Purpose-built informatics platforms represent a novel and potentially effective method for matching patients to molecularly selected studies.
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http://dx.doi.org/10.1200/PO.19.00066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446398PMC
July 2019

Informing, Reassuring, or Alarming? Balancing Patient Needs in the Development of a Postsurgical Symptom Reporting System in Cancer.

AMIA Annu Symp Proc 2018 5;2018:166-174. Epub 2018 Dec 5.

Memorial Sloan-Kettering Cancer Center, New York, NY.

After ambulatory surgeries, patients who recover at home have multiple questions about wound healing, symptoms and medication side effects, and recovery expectations. We conducted user testing and rapid application development of a newly developed symptom reporting system that supports home-based recovery by inviting patients to self-report symptoms in the days after surgery and then receive an immediate feedback report giving context for their reported symptoms. Findings showed that some participants primarily valued reassurance, whereas others prioritized receiving alerts about potential problems. Results also showed that most patients wanted feedback framed as comparing their progress to their expected progress, not to that of other patients. The final feedback report provided patients with actionable recommendations, small graphs showing their progress, and with short "gist" text interpretations. The system has been implemented, and recruitment is ongoing for a large clinical trial of its effectiveness for reducing adverse events and unnecessary emergency or urgent care visits.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371281PMC
September 2019

Automated eligibility screening and monitoring for genotype-driven precision oncology trials.

J Am Med Inform Assoc 2016 07 25;23(4):777-81. Epub 2016 Mar 25.

Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY Division of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, NY.

The Information Systems Department at Memorial Sloan Kettering Cancer Center developed the DARWIN Cohort Management System (DCMS). The DCMS identifies and tracks cohorts of patients based on genotypic and clinical data. It assists researchers and treating physicians in enrolling patients to genotype-matched IRB-approved clinical trials. The DCMS sends automated, actionable, and secure email notifications to users with information about eligible or enrolled patients before their upcoming appointments. The system also captures investigators input via annotations on patient eligibility and preferences on future status updates. As of August 2015, the DCMS is tracking 159,893 patients on both clinical operations and research cohorts. 134 research cohorts have been established and track 64,473 patients. 51,192 of these have had one or more genomic tests including MSK-IMPACT, comprising the pool eligible for genotype-matched studies. This paper describes the design and evolution of this Informatics solution.
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http://dx.doi.org/10.1093/jamia/ocw020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370254PMC
July 2016

Implementation of a computerized patient handoff application.

AMIA Annu Symp Proc 2013 16;2013:1395-400. Epub 2013 Nov 16.

Department of Medicine, Columbia University, New York, NY ; Department of Biomedical Informatics, Columbia University, New York, NY;

For hospitalized patients, handoffs between providers affect continuity of care and increase the risk of medical errors. Most commercial electronic health record (EHR) systems lack dedicated tools to support patient handoff activities. We developed a collaborative application supporting patient handoff that is fully integrated with our commercial EHR. The application creates user-customizable printed reports with automatic inclusion of a variety of EHR data, including: allergies, medications, 24-hour vital signs, recent common laboratory test results, isolation requirements, and code status. It has achieved widespread voluntary use at our institution (6,100 monthly users; 700 daily reports generated), and we have distributed the application to several other institutions using the same EHR. Though originally designed for resident physicians, today about 50% of the application users are nurses, 40% are physicians/physician assistants/nurse practitioners, and 10% are pharmacists, social workers, and other allied health providers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900153PMC
May 2014

Enabling claims-based decision support through non-interruptive capture of admission diagnoses and provider billing codes.

AMIA Annu Symp Proc 2014 14;2014:1950-9. Epub 2014 Nov 14.

Department of Biomedical Informatics, Columbia University, New York, NY.

The patient problem list, like administrative claims data, has become an important source of data for decision support, patient cohort identification, and alerting systems. A two-fold intervention to increase capture of problems on the problem list automatically - with minimal disruption to admitting and provider billing workflows - is described. For new patients with no prior data in the electronic health record, the intervention resulted in a statistically significant increase in the number of problems recorded to the problem list (3.8 vs 2.9 problems post-and pre-intervention respectively, p value 2×10(-16)). The majority of problems were recorded in the first 24 hours of admission. The proportion of patients with at least one problem coded to the problem list within the first 24 hours increased from 94% to 98% before and after intervention (chi square 344, p value 2×10(-16)). ICD9 "V codes" connoting circumstances beyond disease were captured at a higher rate post intervention than before. Deyo/Charlson comorbidities derived from problem list data were more similar to those derived from claims data after the intervention than before (Jaccard similarity 0.3 post- vs 0.21 pre-intervention, p value 2×10(-16)). A workflow-sensitive, non-interruptive means of capturing provider-entered codes early in admission can improve both the quantity and content of problems on the patient problem list.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419872PMC
September 2015

An integrated billing application to streamline clinician workflow.

AMIA Annu Symp Proc 2014 14;2014:1141-9. Epub 2014 Nov 14.

Department of Biomedical Informatics, Columbia University, New York, NY ; Department of Medicine, Columbia University, New York, NY ; ColumbiaDoctors, New York, NY.

Between 2008 and 2010, our academic medical center transitioned to electronic provider documentation using a commercial electronic health record system. For attending physicians, one of the most frustrating aspects of this experience was the system's failure to support their existing electronic billing workflow. Because of poor system integration, it was difficult to verify the supporting documentation for each bill and impractical to track whether billable notes had corresponding charges. We developed and deployed in 2011 an integrated billing application called "iCharge" that streamlines clinicians' documentation and billing workflow, and simultaneously populates the inpatient problem list using billing diagnosis codes. Each month, over 550 physicians use iCharge to submit approximately 23,000 professional service charges for over 4,200 patients. On average, about 2.5 new problems are added to each patient's problem list. This paper describes the challenges and benefits of workflow integration across disparate applications and presents an example of innovative software development within a commercial EHR framework.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4420016PMC
August 2015

Provider-to-provider electronic communication in the era of meaningful use: a review of the evidence.

J Hosp Med 2013 Oct;8(10):589-97

Department of Biomedical Informatics, Columbia University, New York, New York; Department of Medicine, Columbia University, New York, New York.

Background: Electronic communication between providers occurs daily in clinical practice but has not been well studied.

Purpose: To assess the impact of provider-to-provider electronic communication tools on communication and healthcare outcomes through literature review.

Data Sources: Ovid MEDLINE, PubMed, Google Scholar, Cumulative Index to Nursing and Allied Health Literature, and Academic Search Premier.

Study Selection: Publication in English-language peer-reviewed journals. Studies provided quantitative provider-to-provider communication data, provider satisfaction statistics, or electronic health record (EHR) communication data.

Data Extraction: Literature review.

Data Synthesis: Two reviewers conducted the title review to determine eligible studies from initial search results. Three reviewers independently reviewed titles, abstracts, and full text (where appropriate) against inclusion and exclusion criteria.

Limitations: Small number of eligible studies; few described trial design (20%). Homogeneous provider type (physicians). English-only studies.

Conclusions: Of 25 included studies, all focused on physicians; most were observational (68%). Most (60%) described electronic specialist referral tools. Although overall use has been measured, there were no studies of the effectiveness of intra-EHR messaging. Literature describing the effectiveness of provider-to-provider electronic communications is sparse and narrow in scope. Complex care, such as that envisioned for the Patient Centered Medical Home, necessitates further research.
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http://dx.doi.org/10.1002/jhm.2082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4030393PMC
October 2013

Relationship between nursing documentation and patients' mortality.

Am J Crit Care 2013 Jul;22(4):306-13

Partners Healthcare Systems, Wellesley, MA 02481, USA.

Background: Nurses alter their monitoring behavior as a patient's clinical condition deteriorates, often detecting and documenting subtle changes before physiological trends are apparent. It was hypothesized that a nurse's behavior of recording optional documentation (beyond what is required) reflects concern about a patient's status and that mining data from patients' electronic health records for the presence of these features could help predict patients' mortality.

Methods: Data-mining methods were used to analyze electronic nursing documentation from a 15-month period at a large, urban academic medical center. Mortality rates and the frequency of vital sign measurements (beyond required) and optional nursing comment documentation were analyzed for a random set of patients and patients who experienced a cardiac arrest during their hospitalization. Patients were stratified by age-adjusted Charlson comorbidity index.

Results: A total of 15,000 acute care patients and 145 cardiac arrest patients were studied. Patients who died had a mean of 0.9 to 1.5 more optional comments and 6.1 to 10 more vital signs documented within 48 hours than did patients who survived. A higher frequency of comment and vital sign documentation was also associated with a higher likelihood of cardiac arrest. Of patients who had a cardiac arrest, those with more documented comments were more likely to die.

Conclusions: For the first time, nursing documentation patterns have been linked to patients' mortality. Findings were consistent with the hypothesis that some features of nursing documentation within electronic health records can be used to predict mortality. With future work, these associations could be used in real time to establish a threshold of concern indicating a risk for deterioration in a patient's condition.
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http://dx.doi.org/10.4037/ajcc2013426DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3771321PMC
July 2013

CT pulmonary angiography: increasingly diagnosing less severe pulmonary emboli.

PLoS One 2013 12;8(6):e65669. Epub 2013 Jun 12.

Department of Medicine, Columbia University Medical Center and NewYork-Presbyterian Hospital, New York, New York, United States of America.

Background: It is unknown whether the observed increase in computed tomography pulmonary angiography (CTPA) utilization has resulted in increased detection of pulmonary emboli (PEs) with a less severe disease spectrum.

Methods: Trends in utilization, diagnostic yield, and disease severity were evaluated for 4,048 consecutive initial CTPAs performed in adult patients in the emergency department of a large urban academic medical center between 1/1/2004 and 10/31/2009. Transthoracic echocardiography (TTE) findings and peak serum troponin levels were evaluated to assess for the presence of PE-associated right ventricular (RV) abnormalities (dysfunction or dilatation) and myocardial injury, respectively. Statistical analyses were performed using multivariate logistic regression.

Results: 268 CTPAs (6.6%) were positive for acute PE, and 3,780 (93.4%) demonstrated either no PE or chronic PE. There was a significant increase in the likelihood of undergoing CTPA per year during the study period (odds ratio [OR] 1.05, 95% confidence interval [CI] 1.04-1.07, P<0.01). There was no significant change in the likelihood of having a CTPA diagnostic of an acute PE per year (OR 1.03, 95% CI 0.95-1.11, P = 0.49). The likelihood of diagnosing a less severe PE on CTPA with no associated RV abnormalities or myocardial injury increased per year during the study period (OR 1.39, 95% CI 1.10-1.75, P = 0.01).

Conclusions: CTPA utilization has risen with no corresponding change in diagnostic yield, resulting in an increase in PE detection. There is a concurrent rise in the likelihood of diagnosing a less clinically severe spectrum of PEs.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0065669PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680477PMC
January 2014

AMIA board of directors response to Simborg perspective.

J Am Med Inform Assoc 2013 Jun;20(e1):e193-4

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http://dx.doi.org/10.1136/amiajnl-2013-001670DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3715362PMC
June 2013

Combining corpus-derived sense profiles with estimated frequency information to disambiguate clinical abbreviations.

AMIA Annu Symp Proc 2012 3;2012:1004-13. Epub 2012 Nov 3.

Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN, USA.

Abbreviations are widely used in clinical notes and are often ambiguous. Word sense disambiguation (WSD) for clinical abbreviations therefore is a critical task for many clinical natural language processing (NLP) systems. Supervised machine learning based WSD methods are known for their high performance. However, it is time consuming and costly to construct annotated samples for supervised WSD approaches and sense frequency information is often ignored by these methods. In this study, we proposed a profile-based method that used dictated discharge summaries as an external source to automatically build sense profiles and applied them to disambiguate abbreviations in hospital admission notes via the vector space model. Our evaluation using a test set containing 2,386 annotated instances from 13 ambiguous abbreviations in admission notes showed that the profile-based method performed better than two baseline methods and achieved a best average precision of 0.792. Furthermore, we developed a strategy to combine sense frequency information estimated from a clustering analysis with the profile-based method. Our results showed that the combined approach largely improved the performance and achieved a highest precision of 0.875 on the same test set, indicating that integrating sense frequency information with local context is effective for clinical abbreviation disambiguation.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3540457PMC
July 2013

Clinical documentation: composition or synthesis?

J Am Med Inform Assoc 2012 Nov-Dec;19(6):1025-31. Epub 2012 Jul 19.

Department of Biomedical Informatics, Columbia University, New York, USA.

Objective: To understand the nature of emerging electronic documentation practices, disconnects between documentation workflows and computing systems designed to support them, and ways to improve the design of electronic documentation systems.

Materials And Methods: Time-and-motion study of resident physicians' note-writing practices using a commercial electronic health record system that includes an electronic documentation module. The study was conducted in the general medicine unit of a large academic hospital.

Results: During the study, 96 note-writing sessions by 11 resident physicians, resulting in close to 100 h of observations were seen. Seven of the 10 most common transitions between activities during note composition were between documenting, and gathering and reviewing patient data, and updating the plan of care.

Discussion: The high frequency of transitions seen in the study suggested that clinical documentation is fundamentally a synthesis activity, in which clinicians review available patient data and summarize their impressions and judgments. At the same time, most electronic health record systems are optimized to support documentation as uninterrupted composition. This mismatch leads to fragmentation in clinical work, and results in inefficiencies and workarounds. In contrast, we propose that documentation can be best supported with tools that facilitate data exploration and search for relevant information, selective reading and annotation, and composition of a note as a temporal structure.

Conclusions: Time-and-motion study of clinicians' electronic documentation practices revealed a high level of fragmentation of documentation activities and frequent task transitions. Treating documentation as synthesis rather than composition suggests new possibilities for supporting it more effectively with electronic systems.
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http://dx.doi.org/10.1136/amiajnl-2012-000901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3534467PMC
April 2013

A new clustering method for detecting rare senses of abbreviations in clinical notes.

J Biomed Inform 2012 Dec 25;45(6):1075-83. Epub 2012 Jun 25.

Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37203, USA.

Abbreviations are widely used in clinical documents and they are often ambiguous. Building a list of possible senses (also called sense inventory) for each ambiguous abbreviation is the first step to automatically identify correct meanings of abbreviations in given contexts. Clustering based methods have been used to detect senses of abbreviations from a clinical corpus [1]. However, rare senses remain challenging and existing algorithms are not good enough to detect them. In this study, we developed a new two-phase clustering algorithm called Tight Clustering for Rare Senses (TCRS) and applied it to sense generation of abbreviations in clinical text. Using manually annotated sense inventories from a set of 13 ambiguous clinical abbreviations, we evaluated and compared TCRS with the existing Expectation Maximization (EM) clustering algorithm for sense generation, at two different levels of annotation cost (10 vs. 20 instances for each abbreviation). Our results showed that the TCRS-based method could detect 85% senses on average; while the EM-based method found only 75% senses, when similar annotation effort (about 20 instances) was used. Further analysis demonstrated that the improvement by the TCRS method was mainly from additionally detected rare senses, thus indicating its usefulness for building more complete sense inventories of clinical abbreviations.
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http://dx.doi.org/10.1016/j.jbi.2012.06.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3729222PMC
December 2012

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

Appl Clin Inform 2012 ;3(2):164-174

Department of Biomedical Informatics, Columbia University.

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 (Cronbach's 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 (Cronbach's 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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347480PMC
http://dx.doi.org/10.4338/aci-2011-11-ra-0070DOI Listing
January 2012

Commentary: time to sign off on signout.

Acad Med 2011 Jul;86(7):804-6

The physician signout note is a widely used clinical document that supports patient safety and care continuity during patient handoff in the hospital. Despite its centrality to patient care, the signout note is not considered an official document, and it is, therefore, not generally standardized or taught to medical trainees, nor is it usually integrated into electronic health records (EHRs). This commentary outlines several of the potential advantages to establishing the physician signout note as an official part of the medical record, such as the facilitation of information flow between signout notes and other parts of the patient chart and the possibility of integrating decision support tools into this important aspect of the clinical workflow. The authors address frequently encountered concerns regarding the establishment of the signout note as an official part of the medical record. They conclude by making recommendations for integrating signout notes into EHRs and using modern, social Web technologies in such an implementation.
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http://dx.doi.org/10.1097/ACM.0b013e31821d8409DOI Listing
July 2011

An analysis of team checklists in physician signout notes.

AMIA Annu Symp Proc 2010 Nov 13;2010:767-71. Epub 2010 Nov 13.

Columbia University, New York, NY.

Teams of physicians in the hospital collaboratively maintain checklists in informal "signout" documents to help organize, manage, and hand off critical patient-based tasks. We created an application within our commercial EHR that supports basic management of these checklists at two urban, academic medical centers. We collected and analyzed over 400,000 checklist tasks created in the application. We calculated the frequencies of terms and term-combinations (n-grams) in these lists, and compared these data with a previously described clinical task model. Our findings provide evidence for the generalizability of the original clinical task model, and provide the foundation for a more sophisticated physician checklist utility. This could contribute to improved efficiency and safety in patient care.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041400PMC
November 2010

Content overlap in nurse and physician handoff artifacts and the potential role of electronic health records: a systematic review.

J Biomed Inform 2011 Aug 2;44(4):704-12. Epub 2011 Feb 2.

Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA.

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.
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http://dx.doi.org/10.1016/j.jbi.2011.01.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3119775PMC
August 2011

Awareness of the Care Team in Electronic Health Records.

Appl Clin Inform 2011 ;2(4):395-405

Department of Biomedical Informatics, Columbia University, New York, NY.

OBJECTIVE: To support collaboration and clinician-targeted decision support, electronic health records (EHRs) must contain accurate information about patients' care providers. The objective of this study was to evaluate two approaches for care provider identification employed within a commercial EHR at a large academic medical center. METHODS: We performed a retrospective review of EHR data for 121 patients in two cardiology wards during a four-week period. System audit logs of chart accesses were analyzed to identify the clinicians who were likely participating in the patients' hospital care. The audit log data were compared with two functions in the EHR for documenting care team membership: 1) a vendor-supplied module called "Care Providers", and 2) a custom "Designate Provider" order that was created primarily to improve accuracy of the attending physician of record documentation. RESULTS: For patients with a 3-5 day hospital stay, an average of 30.8 clinicians accessed the electronic chart, including 10.2 nurses, 1.4 attending physicians, 2.3 residents, and 5.4 physician assistants. The Care Providers module identified 2.7 clinicians/patient (1.8 attending physicians and 0.9 nurses). The Designate Provider order identified 2.1 clinicians/patient (1.1 attending physicians, 0.2 resident physicians, and 0.8 physician assistants). Information about other members of patients' care teams (social workers, dietitians, pharmacists, etc.) was absent. CONCLUSIONS: The two methods for specifying care team information failed to identify numerous individuals involved in patients' care, suggesting that commercial EHRs may not provide adequate tools for care team designation. Improvements to EHR tools could foster greater collaboration among care teams and reduce communication-related risks to patient safety.
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http://dx.doi.org/10.4338/ACI-2011-05-RA-0034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3345520PMC
January 2011

Perioperative outcome and long-term mortality for heart failure patients undergoing intermediate- and high-risk noncardiac surgery: impact of left ventricular ejection fraction.

Congest Heart Fail 2010 Mar-Apr;16(2):45-9

Columbia University Medical Center, New York, NY, USA.

The impact of left ventricular ejection fraction (LVEF) on outcome in patients with heart failure (HF) undergoing noncardiac surgery has not been extensively evaluated. In this study, 174 patients (mean age, 75+/-12 years, 47% male, mean LVEF (47%+/-18%) underwent intermediate- or high-risk noncardiac surgery. Patients were stratified by LVEF, and adverse perioperative complications were identified and compared. Adverse perioperative events occurred in 53 patients (30.5%), including 14 (8.1%) deaths within 30 days, 26 (14.9%) myocardial infarctions, and 44 (25.3%) HF exacerbations. Among the factors associated with adverse perioperative outcomes in the first 30 days were advanced age (>80 years), diabetes, and a severely decreased LVEF (<30%). Long-term mortality was high, and Cox proportional hazards analysis demonstrated that LVEF was an independent risk factor for long-term mortality.
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http://dx.doi.org/10.1111/j.1751-7133.2009.00130.xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945730PMC
July 2010

Quantifying clinical narrative redundancy in an electronic health record.

J Am Med Inform Assoc 2010 Jan-Feb;17(1):49-53

Department of Biomedical Informatics, Columbia University, New York, New York, USA.

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.
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http://dx.doi.org/10.1197/jamia.M3390DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2995640PMC
April 2010

Development and evaluation of nursing user interface screens using multiple methods.

J Biomed Inform 2009 Dec 19;42(6):1004-12. Epub 2009 May 19.

Columbia University, New York, NY 10032, USA.

Building upon the foundation of the Structured Narrative Electronic Health Record (EHR) model, we applied theory-based (combined Technology Acceptance Model and Task-Technology Fit Model) and user-centered methods to explore nurses' perceptions of functional requirements for an electronic nursing documentation system, design user interface screens reflective of the nurses' perspectives, and assess nurses' perceptions of the usability of the prototype user interface screens. The methods resulted in user interface screens that were perceived to be easy to use, potentially useful, and well-matched to nursing documentation tasks associated with Nursing Admission Assessment, Blood Administration, and Nursing Discharge Summary. The methods applied in this research may serve as a guide for others wishing to implement user-centered processes to develop or extend EHR systems. In addition, some of the insights obtained in this study may be informative to the development of safe and efficient user interface screens for nursing document templates in EHRs.
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http://dx.doi.org/10.1016/j.jbi.2009.05.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2803697PMC
December 2009

Iterative evaluation of the Health Level 7--Logical Observation Identifiers Names and Codes Clinical Document Ontology for representing clinical document names: a case report.

J Am Med Inform Assoc 2009 May-Jun;16(3):395-9. Epub 2009 Mar 4.

School of Nursing, Columbia University School of Nursing. 630 W. 168 Street, Mail Box 6; New York, NY, 10032, USA.

The authors summarize their experience in iteratively testing the adequacy of three versions of the Health Level Seven (HL7) Logical Observation Identifiers Names and Codes (LOINC) Clinical Document Ontology (CDO) to represent document names at Columbia University Medical Center. The percentage of documents fully represented increased from 23.4% (Version 1) to 98.5% (Version 3). The proportion of unique representations increased from 7.9% (Analysis 1) to 39.4% (Analysis 4); the proportion reflects the level of specificity in the document names as well as the completeness and level of granularity of the CDO. The authors shared the findings of each analysis with the Clinical LOINC committee and participated in the decision-making regarding changes to the CDO on the basis of those analyses and those conducted by the Department of Veterans Affairs. The authors encourage other institutions to actively engage in testing healthcare standards and participating in standards development activities to increase the likelihood that the evolving standards will meet institutional needs.
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http://dx.doi.org/10.1197/jamia.M2821DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732231PMC
August 2009

What "to-do" with physician task lists: clinical task model development and electronic health record design implications.

AMIA Annu Symp Proc 2009 Nov 14;2009:624-8. Epub 2009 Nov 14.

Department of Biomedical Informatics, Columbia University, New York, NY,USA.

Clinical task, or "to-do" lists are a common element in the physician document known as signout. Such lists are used to capture and track patient care plan items, supporting daily workflow and collaborative patient management continuity across care transitions. While physician task lists have been shown to be important to patient safety, the tasks themselves have not been systematically examined for their subject matter, structure, or components. A manual sublanguage analysis of 500 signout tasks was conducted, and a hierarchical conceptual model for clinical tasks was inductively constructed. Tasks were classified by action type (Assess, Order, Communicate, Perform) and corresponding components. The most common task action types were Assess and Order. The most common task components were "What" type components such as Tests, including subtypes Laboratory and Imaging. This study yielded several important design considerations for future electronic health record systems that support collaborative clinical task management.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2815485PMC
November 2009

Content and structure of clinical problem lists: a corpus analysis.

AMIA Annu Symp Proc 2008 Nov 6:753-7. Epub 2008 Nov 6.

Department of Biomedical Informatics, Columbia University, New York, NY, USA.

In the interest of designing an automated high-level, longitudinal clinical summary of a patient record, we analyze traditional ways in which medical problems pertaining to the patient are summarized in the electronic health record. The patient problem list has become a commonly used proxy for a summary of patient history and automated methods have been proposed to generate it. However, little research has been conducted on how to structure the problem list in a manner most effective for supporting clinical care. This study analyzes the structure and content of the Past Medical History (PMH) sections of a large corpus of clinical notes, as a proxy for problem lists. Findings show that when listing patients history, physicians convey several semantic types of information, not only problems. Furthermore, they often group related concepts in a single line of the PMH. In contrast, traditional problem lists allow only a simple enumeration of coded terms. Content analysis goes on to reiterate the value of more complex representations as well as provide valuable data and guidelines for automated generation of a clinical summary.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655994PMC
November 2008

A competency-based curriculum to acculturate biomedical informatics students to the practice of medicine.

AMIA Annu Symp Proc 2008 Nov 6:1147. Epub 2008 Nov 6.

Columbia University, New York, NY, USA.

Biomedical informatics students who choose to study clinical information systems may not have significant clinical experience. A course was designed to "acculturate" these students to the practice of medicine through case-based presentations that span three competency areas: biomedicine, clinical workflow and practice, and applications in clinical informatics.
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November 2008

Alert override reasons: a failure to communicate.

AMIA Annu Symp Proc 2008 Nov 6:111-5. Epub 2008 Nov 6.

Department of Biomedical Informatics, Columbia University, New York, NY, USA.

In 2007, the Leapfrog CPOE standard required that all clinical alert overrides be accompanied by an override reason. We wanted to know how many of the free text comments left by clinicians were actually override reasons, and how many were other types of communication. We reviewed 3583 free text comments left voluntarily by clinicians while responding to an alert in a CPOE system. Of the comments received, 58% were override reasons, 28% were acknowledgment of the alert, 9% were content free and over 5% were misdirected communication, written with intent to reach someone who does not receive the alert comments. This is particularly concerning because much of the misdirected communication contained clinical instructions. Those clinical instructions were stored with the alert rather than with any clinical orders, and thus were not viewed by anyone receiving the orders. Our results show that free text alert comments may cause communication failures.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655991PMC
November 2008

Methods for building sense inventories of abbreviations in clinical notes.

AMIA Annu Symp Proc 2008 Nov 6:819. Epub 2008 Nov 6.

Department of Biomedical Informatics, Columbia University, New York, NY, USA.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656023PMC
November 2008