Perceptions of Oncologists About Sharing Clinic Notes with Patients.

In a large survey (n = 809) conducted to understand how oncologists differ from nononcologists regarding routinely sharing visit notes with patients, oncologists were less likely to agree patient safety would improve (p = .03) or that patients would be offended after reading notes (p = .01); however, they agreed with nononcologists that sharing notes would lead to less candid documentation (69% vs. 73%; p = .39). Oncologists share a high level of worry about the impact of sharing notes on documentation practices, a concern that will need to be addressed as the practice of sharing visit notes expands to cancer care.

Closing the loop with an enhanced referral management system.

Objective: To evaluate the impact of a referral manager tool on primary care practices. Materials and Methods: We evaluated a referral manager module in a locally developed electronic health record (EHR) that was enhanced to improve the referral management process in primary care practices. Baseline (n = 61) and follow-up (n = 35) provider and staff surveys focused on the ease of performing various steps in the referral process, confidence in completing those steps, and user satisfaction. Additional metrics were calculated that focused on completed specialist visits, acknowledged notes, and patient communication. Results: Of 1341 referrals that were initiated during the course of the study, 76.8% were completed. All the steps of the referral process were easier to accomplish following implementation of the enhanced referral manager module in the EHR. Specifically, tracking the status of an in-network referral became much easier (+1.43 [3.91-2.48] on a 5-point scale, P < .0001). Although we found improvement in the ease of performing out-of-network referrals, there was a greater impact on in-network referrals. Discussion: Implementation of an electronic tool developed using user-centered design principles along with adequate staff to monitor and intervene when necessary made it easier for primary care practices to track referrals and to identify if a breakdown in the process occurred. This is especially important for high-priority referrals. Out-of-network referrals continue to present challenges, which may eventually be helped by improving interoperability among EHRs and scheduling systems. Conclusion: An enhanced referral manager system can improve referral workflows, leading to enhanced efficiency and patient safety and reduced malpractice risk.

Higher accuracy of complex medication reconciliation through improved design of electronic tools.

Objective: Investigate the accuracy of 2 different medication reconciliation tools integrated into electronic health record systems (EHRs) using a cognitively demanding scenario and complex medication history. Materials and Methods: Seventeen physicians reconciled medication lists for a polypharmacy patient using 2 EHRs in a simulation study. The lists contained 3 types of discrepancy and were transmitted between the systems via a Continuity of Care Document. Participants updated each EHR and their interactions were recorded and analyzed for the number and type of errors. Results: Participants made 748 drug comparisons that resulted in 53 errors (93% accuracy): 12 using EHR2 (3% rate, 0-3 range) and 41 using EHR1 (11% rate, 0-9 range; P < .0001). Twelve clinicians made completely accurate reconciliations with EHR2 (71%) and 6 with EHR1 (35%). Most errors (28, 53%) occurred in medication entries containing discrepancies: 4 in EHR2 and 24 in EHR1 (P = .008). The order in which participants used the EHRs to complete the task did not affect the results. Discussion: Significantly fewer errors were made with EHR2, which presented lists in a side-by-side view, automatically grouped medications by therapeutic class and more effectively identified duplicates. Participants favored this design and indicated that they routinely used several workarounds in EHR1. Conclusion: Accurate assessment of the safety and effectiveness of electronic reconciliation tools requires rigorous testing and should prioritize complex rather than simpler tasks that are currently used for EHR certification and product demonstration. Higher accuracy of reconciliation is likely when tools are designed to better support cognitively demanding tasks.

A Picture is Worth 1,000 Words. The Use of Clinical Images in Electronic Medical Records.

OBJECTIVE: To understand how clinicians utilize image uploading tools in a home grown electronic health records (EHR) system. METHODS: A content analysis of patient notes containing non-radiological images from the EHR was conducted. Images from 4,000 random notes from July 1, 2009 - June 30, 2010 were reviewed and manually coded. Codes were assigned to four properties of the image: (1) image type, (2) role of image uploader (e.g. MD, NP, PA, RN), (3) practice type (e.g. internal medicine, dermatology, ophthalmology), and (4) image subject. RESULTS: 3,815 images from image-containing notes stored in the EHR were reviewed and manually coded. Of those images, 32.8% were clinical and 66.2% were non-clinical. The most common types of the clinical images were photographs (38.0%), diagrams (19.1%), and scanned documents (14.4%). MDs uploaded 67.9% of clinical images, followed by RNs with 10.2%, and genetic counselors with 6.8%. Dermatology (34.9%), ophthalmology (16.1%), and general surgery (10.8%) uploaded the most clinical images. The content of clinical images referencing body parts varied, with 49.8% of those images focusing on the head and neck region, 15.3% focusing on the thorax, and 13.8% focusing on the lower extremities. CONCLUSION: The diversity of image types, content, and uploaders within a home grown EHR system reflected the versatility and importance of the image uploading tool. Understanding how users utilize image uploading tools in a clinical setting highlights important considerations for designing better EHR tools and the importance of interoperability between EHR systems and other health technology.

Accuracy and Completeness of Clinical Coding Using ICD-10 for Ambulatory Visits.

This study describes a simulation of diagnostic coding using an EHR. Twenty-three ambulatory clinicians were asked to enter appropriate codes for six standardized scenarios with two different EHRs. Their interactions with the query interface were analyzed for patterns and variations in search strategies and the resulting sets of entered codes for accuracy and completeness. Just over a half of entered codes were appropriate for a given scenario and about a quarter were omitted. Crohn's disease and diabetes scenarios had the highest rate of inappropriate coding and code variation. The omission rate was higher for secondary than for primary visit diagnoses. Codes for immunization, dialysis dependence and nicotine dependence were the most often omitted. We also found a high rate of variation in the search terms used to query the EHR for the same diagnoses. Changes to the training of clinicians and improved design of EHR query modules may lower the rate of inappropriate and omitted codes.

Development of a cognitive framework of patient record summary review in the formative phase of user-centered design.

Excellent usability characteristics allow electronic health record (EHR) systems to more effectively support clinicians providing care and contribute to better quality and safety. The Office of the National Coordinator for Health IT (ONC) therefore requires all vendors to follow a User-Centered Design (UCD) process to increase the usability of their products in order to meet certification criteria for the Safety-Enhanced Design part of the Meaningful Use (stage 2) EHR incentive program. This report describes the initial stage of a UCD process in which foundational design concepts were formulated. We designed a functional prototype of an EHR module intended to help clinicians to efficiently complete a summary review of an electronic patient record before an ambulatory visit. Cognitively-based studies were performed and the results used to develop a cognitive framework that subsequently guided design of a prototype. Results showed that clinicians categorized and reasoned with patient data in distinct patterns; they preferred to review relevant history in the assessment and plan section of the most recent note, to search for changes in health and for new episodes of care since the last visit and to look up current-day data such as vital signs. These basic concepts were represented in the design, for instance, by screen division into vertical thirds that had historical content to the left and most recent data to the right. Other characteristics such as visual association of contextual information or direct, one-click access to the assessment and plan section of visit notes were directly informed by our findings and refined in a series of UCD-specific iterative testing. Understanding of tasks and cognitive demands early in the UCD process was critically important for developing a tool optimized for reasoning and workflow preferences of clinicians.

Awareness and Use of the After-Visit Summary Through a Patient Portal: Evaluation of Patient Characteristics and an Application of the Theory of Planned Behavior.

BACKGROUND: Patient portals are being used to provide a clinical summary of the office visit or the after-visit summary (AVS) to patients. There has been relatively little research on the characteristics of patients who access the AVS through a patient portal and their beliefs about the AVS. OBJECTIVE: The aim was to (1) assess the characteristics of patients who are aware of and access the AVS through a patient portal and (2) apply the Theory of Planned Behavior (TPB) to predict behavioral intention of patients toward accessing the AVS provided through a patient portal. METHODS: We developed a survey capturing the components of TPB (beliefs, attitude, perceived norm, and perceived behavioral control). Over a 6-month period, patients with a patient portal account with an office visit in the previous week were identified using our organization's scheduling system. These patients were sent an email about the study and a link to the survey via their portal account. We applied univariate statistical analysis (Pearson chi-square and 1-way ANOVA) to assess differences among groups (aware/unaware of AVS and accessed/did not access AVS). We reported means and standard deviations to depict belief strengths and presented correlations between beliefs and attitude, perceived norm, and perceived behavioral control. We used hierarchical regression analysis to predict behavioral intention toward accessing the AVS through the patient portal. RESULTS: Of the 23,336 patients who were sent the survey, 5370 responded for a response rate of 23.01%. Overall, 76.52% (4109/5370) were aware that the AVS was available through the patient portal and 54.71% of those (2248/4109) accessed the AVS within 5 days of the office visit. Patients who accessed the AVS had a greater number of sessions with the portal (mean 119, SD 221.5) than those who did not access the AVS (mean 79.1, SD 123.3, P<.001); the difference was not significant for awareness of the AVS. The strongest behavioral beliefs with accessing the AVS were being able to track visits and tests (mean 2.53, SD 1.00) followed by having medical information more readily accessible (mean 2.48, SD 1.07). In all, 56.7% of the variance in intention to access the AVS through the portal was accounted for by attitude, perceived norm, and perceived behavioral control. CONCLUSIONS: Most users of a patient portal were aware that the AVS was accessible through the portal. Patients had stronger beliefs about accessing the AVS with the goal of timely and efficient access of information than with engaging in their health care. Interventions to improve patient access of the AVS can focus on providers promoting patient beliefs about the value of the AVS for tracking tests and visits, and timely and efficient access of information.

Cognitive Errors in Reconciling Complex Medication Lists.

Discrepancies between multiple electronic versions of patient medication records contribute to adverse drug events. Regular reconciliation increases their accuracy but is often inadequately supported by EHRs. We evaluated two systems with conceptually different interface designs for their effectiveness in resolving discrepancies. Eleven clinicians reconciled a complex list of 16 medications using both EHRs in the same standardized scenario. Errors such as omissions to add or discontinue a drug or to update a dose were analyzed. Clinicians made three times as many errors working with an EHR with lists arranged in a single column than when using a system with side-by-side lists. Excessive cognitive effort and reliance on memory was likely a strong contributing factor for lower accuracy of reconciliation. As errors increase with task difficulty, evaluations of reconciliation tools need to focus on complex prescribing scenarios to accurately assess effectiveness, error rate and whether they reduce risk to patient safety.

Coordination of care for complex pediatric patients: perspectives from providers and parents.

Coordinators help patients requiring complex chronic care manage frequent ambulatory visits and services received at home or from community-based agencies. EHRs directly support only a few of the required tasks as they do not allow access to all parties involved in care. Our goal was to examine how technology was used to coordinate efforts and to describe common barriers and facilitators. Insights may inform the design of tools that would effectively support identified goals. We conducted five hours of interviews with sixteen parents and six clinicians and characterized emergent themes from transcripts. Situational awareness, care and visit planning, document aggregation, abstraction and interpretation were tasks essential to coordination yet generally poorly supported by EHRs. Providers communicated primarily by email, telephone and by exchanging paper and scanned documents. A preliminary model of coordination that could be used in the planning and testing stages of a User Centered Design process is described.

How physicians document outpatient visit notes in an electronic health record.

BACKGROUND: Clinical documentation, an essential process within electronic health records (EHRs), takes a significant amount of clinician time. How best to optimize documentation methods to deliver effective care remains unclear. OBJECTIVE: We evaluated whether EHR visit note documentation method was influenced by physician or practice characteristics, and the association of physician satisfaction with an EHR notes module. MEASUREMENTS: We surveyed primary care physicians (PCPs) and specialists, and used EHR and provider data to perform a multinomial logistic regression of visit notes from 2008. We measured physician documentation method use and satisfaction with an EHR notes module and determined the relationship between method and physician and practice characteristics. RESULTS: Of 1088 physicians, 85% used a single method to document the majority of their visits. PCPs predominantly documented using templates (60%) compared to 34% of specialists, while 38% of specialists predominantly dictated. Physicians affiliated with academic medical centers (OR 1.96, CI (1.23, 3.12)), based at a hospital (OR 1.57, 95% CI (1.04, 2.36)) and using the EHR for longer (OR 1.13, 95% CI (1.03, 1.25)) were more likely to dictate than use templates. Most physicians of 383 survey responders were satisfied with the EHR notes module, regardless of their preferred documentation method. CONCLUSIONS: Physicians predominantly utilized a single method of visit note documentation and were satisfied with their approach, but the approaches they chose varied. Demographic characteristics were associated with preferred documentation method. Further research should focus on why variation exists, and the quality of the documentation resulting from different methods used.

Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial.

BACKGROUND: Accurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date. OBJECTIVE: To determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation. STUDY DESIGN AND METHODS: Inference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009-5/2010) and intervention (5/2010-11/2010) periods. RESULTS: 17,043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions. CONCLUSION: Problem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01105923.

Using a service oriented architecture approach to clinical decision support: performance results from two CDS Consortium demonstrations.

The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

BACKGROUND: Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. OBJECTIVE: To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. STUDY DESIGN AND METHODS: We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. RESULTS: Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. CONCLUSION: We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

An unintended consequence of electronic prescriptions: prevalence and impact of internal discrepancies.

Many e-prescribing systems allow for both structured and free-text fields in prescriptions, making possible internal discrepancies. This study reviewed 2914 electronic prescriptions that contained free-text fields. Internal discrepancies were found in 16.1% of the prescriptions. Most (83.8%) of the discrepancies could potentially lead to adverse events and many (16.8%) to severe adverse events, involving a hospital admission or death. Discrepancies in doses, routes or complex regimens were most likely to have a potential for a severe event (p=0.0001). Discrepancies between structured and free-text fields in electronic prescriptions are common and can cause patient harm. Improvements in electronic medical record design are necessary to minimize the risk of discrepancies and resulting adverse events.

Creating shareable decision support services: an interdisciplinary challenge.

Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points. We report in this paper on challenges we faced while pursuing this research: knowledge representation and modeling, data interchange and standards adoption, the process of getting agreement on content, logistics of integrating into a system that already has multiple CDS interventions, legal issues around privacy and access, inter-team communication and organization.

Evaluating nicotine replacement therapy and stage-based therapies in a population-based effectiveness trial.

Pharmacological interventions for smoking cessation are typically evaluated using volunteer samples (efficacy trials) but should also be evaluated in population-based trials (effectiveness trials). Nicotine replacement therapy (NRT) alone and in combination with behavioral interventions was evaluated on a population of smokers from a New England Veterans Affairs Medical Center. Telephone interviews were completed with 3,239 smokers, and 2,054 agreed to participate (64%). Participants were randomly assigned to one of four conditions: stage-matched manuals (MAN); NRT plus manuals (NRT + MAN); expert system plus NRT and manuals (EXP + NRT + MAN); and automated counseling plus NRT, manuals, and expert system (TEL + EXP + NRT + MAN). Assessments were completed at baseline, 10, 20, and 30 months. The point prevalence cessation rates at final follow-up (30 months) were MAN, 20.3%; NRT + MAN, 19.3%; EXP + NRT + MAN, 17.6%; and TEL + EXP + NRT + MAN, 19.9%. Stage-matched manuals provided cessation rates comparable with previous studies. The addition of NRT, expert system interventions, and automated telephone counseling failed to produce a further increase in intervention effectiveness.

Comparing participants and nonparticipants recruited for an effectiveness study of nicotine replacement therapy.

BACKGROUND: Interventions for smoking cessation have been typically evaluated on reactively recruited samples in clinical trials (efficacy trials). However, to have an impact on smoking rates in a general population, the intervention should also be evaluated with proactively recruited representative samples (effectiveness trials). PURPOSE: The characteristics of participants and two groups of nonparticipants recruited for a population-based nicotine replacement therapy study were compared. METHODS: All members of a large New England Veterans' Administration Medical Center were contacted, and interviews were completed with 3,239 identified smokers (at least 10 cigarettes per day). At the end of the interview, all smokers were offered participation in a multiple intervention study. Of the interviewed smokers, 2,915 verbally agreed to participate in the study (90%). Of those who gave initial verbal consent, 2,054 returned the written informed consent form and became participants (70%). RESULTS: The participants (full consent group) differed significantly from both nonparticipant groups-that is, the smokers who were interviewed but declined participation by active refusal (survey only group) and those who gave verbal consent but passively refused participation by failing to return the written consent form (verbal consent only group). Participants were more likely to be married, younger, and female; to live with others; and to have previously used or considered using nicotine replacement therapy. The survey only group was also more likely to be in the precontemplation stage (54%), whereas the participants were more likely to be in the contemplation (46%) or preparation stage (35%). The verbal consent only group was intermediate of the other two groups in stage-of-change characteristics. CONCLUSIONS: An important finding was that it is possible to recruit a large proportion of a sample of identified smokers to an nicotine replacement therapy study. However, the participants are likely to differ in significant ways from those who either actively or passively decline participation.

The use of computer telephony to provide interactive health information.

The use of information technology to provide health information to the public has grown at a rapid pace. Numerous sources of health care information within both the print and Internet media are now available. Yet, their availability raises concerns about the quality of the information provided and questions about which is the most effective method for transmitting health information to consumers. We present an interactive method of presenting high-quality health information that uses a new approach: an integration of the telephone and the computer also called computer telephony. Telephone-Linked Communication for Health Information (TLC-HI) is a computer-based telecommunications system that functions as an educator to people in search of answers to health-related issues. To create TLC-HI, we converted validated print-based consumer information into computer-controlled conversational dialogues. We discuss the potential that the TLC-HI approach holds for improving the way health information is communicated.