Erik G. Van Eaton

Surgeon Information Transfer and Communication: Factors Affecting Quality and Efficiency of Inpatient Care

Objective:To determine the nature of surgeon information transfer and communication (ITC) errors that lead to adverse events and near misses. To recommend strategies for minimizing or preventing these errors. Summary Background Data:Surgical hospital practice is changing from a single provider to a team-based approach. This has put a premium on effective ITC. The Information Transfer and Communication Practices (ITCP) Project is a multi-institutional effort to: 1) better understand surgeon ITCP and their patient care consequences, 2) determine what has been done to improve ITCP in other professions, and 3) recommend ways to improve these practices among surgeons. Methods:Separate, semi-structured focus group sessions were conducted with surgical residents (n = 59), general surgery attending physicians (n = 36), and surgical nurses (n = 42) at 5 medical centers. Case descriptions and general comments were classified by the nature of ITC lapses and their effects on patients and medical care. Information learned was combined with a review of ITC strategies in other professions to develop principles and guidelines for re-engineering surgeon ITCP. Results:A total of 328 case descriptions and general comments were obtained and classified. Incidents fell into 4 areas: blurred boundaries of responsibility (87 reports), decreased surgeon familiarity with patients (123 reports), diversion of surgeon attention (31 reports), and distorted or inhibited communication (67 reports). Results were subdivided into 30 contributing factors (eg, shift change, location change, number of providers). Consequences of ITC lapses included delays in patient care (77% of cases), wasted surgeon/staff time (48%), and serious adverse patient consequences (31%). Twelve principles and 5 institutional habit changes are recommended to guide ITCP re-engineering. Conclusions:Surgeon communication lapses are significant contributors to adverse patient consequences, and provider inefficiency. Re-engineering ITCP will require significant cultural changes.

Safety of using a computerized rounding and sign-out system to reduce resident duty hours.

Purpose To determine whether changing sign-out practices and decreasing the time spent in rounding and recopying patient data affect patient safety. Responding to limited resident duty hours, the University of Washington launched a computerized rounding and sign-out system (“UW Cores”). The system shortened duty hours by facilitating sign-out, decreasing rounding time, and sharply reducing the time spent in prerounds data recopying. Method This 14-week, randomized, crossover study involved 14 inpatient resident teams (6 general surgery, 8 internal medicine) at two hospitals. The authors measured resident-reported deviations in expected care that occurred during cross-coverage, medical errors, and institutionally reported adverse drug events (ADEs). Results The mean number of resident-reported deviations from expected care per 1,000 patient-days did not differ significantly between the control and UW Cores groups: 14.29 and 13.81, respectively (P = .85). The mean number of reported incidents involving errors was 6.33 per 1,000 patient-days for the control group and 5.61 per 1,000 patient-days for the UW Cores group (P = .68). The odds ratio of a reported overnight medical error under the UW Cores system was 1.01 (95% CI: 0.64, 1.60; P = .96). The odds ratio of an ADE while a resident is on an intervention team was 1.10 (95% CI: 0.69, 1.74; P = .70). Conclusions Managing information for sign-out and rounding with the UW Cores system, to reduce time spent in recopying patient data and in rounding on patients, improved continuity and enhanced resident efficiency without weakening systemic defenses against error or jeopardizing patient safety.

ACGME case logs: Surgery resident experience in operative trauma for two decades.

BACKGROUND Surgery resident education is based on experiential training, which is influenced by changes in clinical management strategies, technical and technologic advances, and administrative regulations. Trauma care has been exposed to each of these factors, prompting concerns about resident experience in operative trauma. The current study analyzed the reported volume of operative trauma for the last two decades; to our knowledge, this is the first evaluation of nationwide trends during such an extended time line. METHODS The Accreditation Council for Graduate Medical Education (ACGME) database of operative logs was queried from academic year (AY) 1989–1990 to 2009–2010 to identify shifts in trauma operative experience. Annual case log data for each cohort of graduating surgery residents were combined into approximately 5-year blocks, designated Period I (AY1989–1990 to AY1993–1994), Period II (AY1994–1995 to AY1998–1999), Period III (AY1999–2000 to AY2002–2003), and Period IV (AY2003–2004 to AY2009–2010). The latter two periods were delineated by the year in which duty hour restrictions were implemented. RESULTS Overall general surgery caseload increased from Period I to Period II (p < 0.001), remained stable from Period II to Period III, and decreased from Period III to Period IV (p < 0.001). However, for ACGME-designated trauma cases, there were significant declines from Period I to Period II (75.5 vs. 54.5 cases, p < 0.001) and Period II to Period III (54.5 vs. 39.3 cases, p < 0.001) but no difference between Period III and Period IV (39.3 vs. 39.4 cases). Graduating residents in Period I performed, on average, 31 intra-abdominal trauma operations, including approximately five spleen and four liver operations. Residents in Period IV performed 17 intra-abdominal trauma operations, including three spleen and approximately two liver operations. CONCLUSION Recent general surgery trainees perform fewer trauma operations than previous trainees. The majority of this decline occurred before implementation of work-hour restrictions. Although these changes reflect concurrent changes in management of trauma, surgical educators must meet the challenge of training residents in procedures less frequently performed. LEVEL OF EVIDENCE Epidemiologic study, level III; therapeutic study, level IV.

Resident education in 2011: Three key challenges on the road ahead

Two important changes in the past decade have altered the landscape of graduate medical education (GME) in the U.S. The national restrictions on trainee duty hours mandated by the Accreditation Council for Graduate Medical Education (ACGME) were the most visible and generated much controversy. Equally important is the ACGME Outcome Project, which mandates competency-based training. Both of these changes have unique implications for surgery trainees, who traditionally spent long hours caring for patients in the hospital, and who must be assessed in 2 broad domains: their medical care of pre- and postoperative patients, and their technical skill with procedures in and out of the operating room. This article summarizes 3 key challenges that lie ahead for surgical educators. First, the changes in duty hours in the past 7 years are summarized, and the conversation about added restrictions planned for July 2011 is reviewed. Next, the current state of the assessment of competency among surgical trainees is reviewed, with an outline of the challenges that need to be overcome to achieve widespread, competency-based training in surgery. Finally, the article summarizes the problems caused by increased reliance on handoffs among trainees as they compensate for decreased time in the hospital, and suggests changes that need to be made to improve safety and efficiency, including how to use handoffs as part of our educational evaluation of residents.

Availability of Structured and Unstructured Clinical Data for Comparative Effectiveness Research and Quality Improvement: A Multi-Site Assessment

Introduction: A key attribute of a learning health care system is the ability to collect and analyze routinely collected clinical data in order to quickly generate new clinical evidence, and to monitor the quality of the care provided. To achieve this vision, clinical data must be easy to extract and stored in computer readable formats. We conducted this study across multiple organizations to assess the availability of such data specifically for comparative effectiveness research (CER) and quality improvement (QI) on surgical procedures. Setting: This study was conducted in the context of the data needed for the already established Surgical Care and Outcomes Assessment Program (SCOAP), a clinician-led, performance benchmarking, and QI registry for surgical and interventional procedures in Washington State. Methods: We selected six hospitals, managed by two Health Information Technology (HIT) groups, and assessed the ease of automated extraction of the data required to complete the SCOAP data collection forms. Each data element was classified as easy, moderate, or complex to extract. Results: Overall, a significant proportion of the data required to automatically complete the SCOAP forms was not stored in structured computer-readable formats, with more than 75 percent of all data elements being classified as moderately complex or complex to extract. The distribution differed significantly between the health care systems studied. Conclusions: Although highly desirable, a learning health care system does not automatically emerge from the implementation of electronic health records (EHRs). Innovative methods to improve the structured capture of clinical data are needed to facilitate the use of routinely collected clinical data for patient phenotyping.

Technology-Enhanced Stepped Collaborative Care Targeting Posttraumatic Stress Disorder and Comorbidity After Injury: A Randomized Controlled Trial

Posttraumatic stress disorder (PTSD) and its comorbidities are endemic among injured trauma survivors. Previous collaborative care trials targeting PTSD after injury have been effective, but they have required intensive clinical resources. The present pragmatic clinical trial randomized acutely injured trauma survivors who screened positive on an automated electronic medical record PTSD assessment to collaborative care intervention (n = 60) and usual care control (n = 61) conditions. The stepped measurement-based intervention included care management, psychopharmacology, and psychotherapy elements. Embedded within the intervention were a series of information technology (IT) components. PTSD symptoms were assessed with the PTSD Checklist at baseline prerandomization and again, 1-, 3-, and 6-months postinjury. IT utilization was also assessed. The technology-assisted intervention required a median of 2.25 hours (interquartile range = 1.57 hours) per patient. The intervention was associated with modest symptom reductions, but beyond the margin of statistical significance in the unadjusted model: F(2, 204) = 2.95, p = .055. The covariate adjusted regression was significant: F(2, 204) = 3.06, p = .049. The PTSD intervention effect was greatest at the 3-month (Cohens effect size d = 0.35, F(1, 204) = 4.11, p = .044) and 6-month (d = 0.38, F(1, 204) = 4.10, p = .044) time points. IT-enhanced collaborative care was associated with modest PTSD symptom reductions and reduced delivery times; the intervention model could potentially facilitate efficient PTSD treatment after injury.

Preparing Electronic Clinical Data for Quality Improvement and Comparative Effectiveness Research: The SCOAP CERTAIN Automation and Validation Project.

Background: The field of clinical research informatics includes creation of clinical data repositories (CDRs) used to conduct quality improvement (QI) activities and comparative effectiveness research (CER). Ideally, CDR data are accurately and directly abstracted from disparate electronic health records (EHRs), across diverse health-systems. Objective: Investigators from Washington State’s Surgical Care Outcomes and Assessment Program (SCOAP) Comparative Effectiveness Research Translation Network (CERTAIN) are creating such a CDR. This manuscript describes the automation and validation methods used to create this digital infrastructure. Methods: SCOAP is a QI benchmarking initiative. Data are manually abstracted from EHRs and entered into a data management system. CERTAIN investigators are now deploying Caradigm’s Amalga™ tool to facilitate automated abstraction of data from multiple, disparate EHRs. Concordance is calculated to compare data automatically to manually abstracted. Performance measures are calculated between Amalga and each parent EHR. Validation takes place in repeated loops, with improvements made over time. When automated abstraction reaches the current benchmark for abstraction accuracy - 95% - itwill ‘go-live’ at each site. Progress to Date: A technical analysis was completed at 14 sites. Five sites are contributing; the remaining sites prioritized meeting Meaningful Use criteria. Participating sites are contributing 15–18 unique data feeds, totaling 13 surgical registry use cases. Common feeds are registration, laboratory, transcription/dictation, radiology, and medications. Approximately 50% of 1,320 designated data elements are being automatically abstracted—25% from structured data; 25% from text mining. Conclusion: In semi-automating data abstraction and conducting a rigorous validation, CERTAIN investigators will semi-automate data collection to conduct QI and CER, while advancing the Learning Healthcare System.

Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory

Pragmatic clinical trials (PCTs) are research investigations embedded in health care settings designed to increase the efficiency of research and its relevance to clinical practice. The Health Care Systems Research Collaboratory, initiated by the National Institutes of Health Common Fund in 2010, is a pioneering cooperative aimed at identifying and overcoming operational challenges to pragmatic research. Drawing from our experience, we present 4 broad categories of informatics-related challenges: (1) using clinical data for research, (2) integrating data from heterogeneous systems, (3) using electronic health records to support intervention delivery or health system change, and (4) assessing and improving data capture to define study populations and outcomes. These challenges impact the validity, reliability, and integrity of PCTs. Achieving the full potential of PCTs and a learning health system will require meaningful partnerships between health system leadership and operations, and federally driven standards and policies to ensure that future electronic health record systems have the flexibility to support research.

A nationwide survey of trauma center information technology leverage capacity for mental health comorbidity screening.

BACKGROUND Despite evidence that electronic medical record (EMR) information technology innovations can enhance the quality of trauma center care, few investigations have systematically assessed United States (US) trauma center EMR capacity, particularly for screening of mental health comorbidities. STUDY DESIGN Trauma programs at all US level I and II trauma centers were contacted and asked to complete a survey regarding health information technology (IT) and EMR capacity. RESULTS Three hundred ninety-one of 525 (74%) US level I and II trauma centers responded to the survey. More than 90% of trauma centers reported the ability to create custom patient tracking lists in their EMR. Forty-seven percent of centers were interested in automating a blood alcohol content screening process; only 14% reported successfully using their EMR to perform this task. Marked variation was observed across trauma center sites with regard to the types of EMR systems used as well as rates of adoption and turnover of EMR systems. CONCLUSIONS Most US level I and II trauma centers have installed EMR systems; however, marked heterogeneity exists with regard to EMR type, available features, and turnover. A minority of centers have leveraged their EMR for screening of mental health comorbidities among trauma inpatients. Greater attention to effective EMR use is warranted from trauma accreditation organizations.

Achieving and Sustaining Automated Health Data Linkages for Learning Systems: Barriers and Solutions

Introduction: Delivering more appropriate, safer, and highly effective health care is the goal of a learning health care system. The Agency for Healthcare Research and Quality (AHRQ) funded enhanced registry projects: (1) to create and analyze valid data for comparative effectiveness research (CER); and (2) to enhance the ability to monitor and advance clinical quality improvement (QI). This case report describes barriers and solutions from one state-wide enhanced registry project. Methods: The Comparative Effectiveness Research and Translation Network (CERTAIN) deployed the commercially available Amalga Unified Intelligence System™ (Amalga) as a central data repository to enhance an existing QI registry (the Automation Project). An eight-step implementation process included hospital recruitment, technical electronic health record (EHR) review, hospital-specific interface planning, data ingestion, and validation. Data ownership and security protocols were established, along with formal methods to separate data management for QI purposes and research purposes. Sustainability would come from lowered chart review costs and the hospital’s desire to invest in the infrastructure after trying it. Findings: CERTAIN approached 19 hospitals in Washington State operating within 12 unaffiliated health care systems for the Automation Project. Five of the 19 completed all implementation steps. Four hospitals did not participate due to lack of perceived institutional value. Ten hospitals did not participate because their information technology (IT) departments were oversubscribed (e.g., too busy with Meaningful Use upgrades). One organization representing 22 additional hospitals expressed interest, but was unable to overcome data governance barriers in time. Questions about data use for QI versus research were resolved in a widely adopted project framework. Hospitals restricted data delivery to a subset of patients, introducing substantial technical challenges. Overcoming challenges of idiosyncratic EHR implementations required each hospital to devote more IT resources than were predicted. Cost savings did not meet projections because of the increased IT resource requirements and a different source of lowered chart review costs. Discussion: CERTAIN succeeded in recruiting unaffiliated hospitals into the Automation Project to create an enhanced registry to achieve AHRQ goals. This case report describes several distinct barriers to central data aggregation for QI and CER across unaffiliated hospitals: (1) competition for limited on-site IT expertise, (2) concerns about data use for QI versus research, (3) restrictions on data automation to a defined subset of patients, and (4) unpredictable resource needs because of idiosyncrasies among unaffiliated hospitals in how EHR data are coded, stored, and made available for transmission—even between hospitals using the same vendor’s EHR. Therefore, even a fully optimized automation infrastructure would still not achieve complete automation. The Automation Project was unable to align sufficiently with internal hospital objectives, so it could not show a compelling case for sustainability.