Andrew S. Karson

Patient Safety Concerns Arising from Test Results That Return after Hospital Discharge

Context Poor communication between inpatient and outpatient providers precedes many preventable adverse events that occur shortly after discharge. Contribution Forty-one percent of 2644 patients on the hospitalist services of 2 academic hospitals had pending laboratory or radiology results at discharge. Physician-reviewers deemed approximately 9% of these results potentially actionable. Physician surveys done 14 days after results were first available showed that physicians were unaware of many results and thought that about 13% of them required urgent action. Cautions Findings may not apply to nonacademic or nonhospitalist settings. Implications We need good integrated systems to assure follow-up of tests that are pending at discharge. The Editors Good communication between inpatient and outpatient physicians at the transition from hospital to home is critical to patient safety. However, the amount and complexity of information that must be relayed at hospital discharge are often overwhelming. Unfortunately, when communication breaks down, patients are at risk: More than half of all preventable adverse events occurring soon after hospital discharge have been related to poor communication among providers (1). Recently, the challenges to high-quality transitions of care have been increasingly recognized (2), and several factors may be contributing to communication failures at discharge. Although the introduction of hospitalist programs across the United States has produced positive results (3-5), the discontinuity of care inherent in the hospitalist model increases the likelihood of communication failures and makes thorough communication at discharge essential (6). Discontinuity is also an issue in teaching hospitals, where physicians-in-training may be responsible for some or all of the communication at discharge and, under new work-hour restrictions, may frequently change services or work in shifts. Whatever the cause, discontinuity of care at the inpatient-to-outpatient transition has been shown to be associated with medical errors (7). Among these errors is a failure to follow up on the results of laboratory tests and radiologic studies that return after discharge. Although timely follow-up on test results has received attention from the Agency for Healthcare Research and Quality (8) and failure to follow up on results has been recognized by a large malpractice insurer (9) as accounting for one quarter of diagnosis-related malpractice cases, few studies have addressed follow-up on test results pending at hospital discharge. Moore and colleagues (7) studied test follow-up errors, which were defined as having a test result noted as pending at discharge in the inpatient medical record but not acknowledged in the outpatient chart. Using retrospective chart review, they found this type of error in the records of 8% of all discharged patients and 41% of all patients discharged with pending test results, but their study design did not allow them to determine 1) whether clinicians were aware of the results and did not document them or 2) the clinical consequences of these errors. To our knowledge, no other studies have prospectively examined the prevalence and characteristics of test results that return after discharge or physician awareness of them. We hypothesized that test results pending at discharge are frequently overlooked in the handoff from the inpatient physician to the outpatient physician and that some of these results might have important clinical consequences for patients. Accordingly, we sought to prospectively determine the prevalence and characteristics of these potentially actionable results, to determine how often physicians are unaware of these results, and to evaluate the satisfaction of inpatient physicians with current systems for following up on results returning after discharge. Methods We carried out our study on the general medicine hospitalist services at 2 academic tertiary care centers in Boston, Massachusetts (hospitals A and B). The human research committee for both hospitals reviewed and approved the study design. The hospitals belong to the same integrated care-delivery network and share a common electronic clinical data repository that includes test results, discharge orders and summaries, ambulatory notes, and medication and problem lists. These data are accessible at all inpatient and outpatient sites through the same electronic medical record. In addition, all physicians use the same e-mail system. Hospital A has 3 hospitalist inpatient teams that each consist of 1 hospitalist attending physician, 1 internal medicine resident, and 2 interns. At hospital A, the hospitalist attending physician is usually responsible for all communication to outpatient physicians at discharge, as well as for follow-up on all pending test results that return after discharge. Hospital B has 2 types of hospitalist services. One is nonhousestaff and is staffed only by hospitalist and nonhospitalist attending physicians; the nonhospitalist attending physicians care for their own patients on this service, but for the purposes of the study, we categorized them as inpatient physicians. The other hospitalist service at hospital B is a teaching service of 4 teams, each with 1 hospitalist attending physician, 1 junior resident, and 3 interns. On these teams at hospital B, the junior resident is responsible for communication at discharge and follow-up on all pending test results. During the study, 16 hospitalists were responsible for patient discharges at hospital A, 15 hospitalist and 93 nonhospitalist attending physicians were responsible for discharges on the nonhousestaff service at hospital B, and 54 junior residents were responsible for discharges on the teaching service at hospital B. Patient Selection and Identification of Results Returning after Discharge Using the hospital computer systems, we prospectively identified 2644 consecutive patients discharged from February to June 2004. Shortly after each patients discharge, a research assistant entered into a database the patients identifying information, discharge diagnosis, and times and dates of hospital admission and discharge. He or she then tracked each patients pending test results by entering the patient on a watch list using a feature in a results-management system called Results Manager. Results Manager is a computer application that is fully integrated into the electronic medical record and is able to cull pending and final test results from the clinical data repository and to prioritize them on the basis of type of result and degree of abnormality. It was originally developed to track test results in the outpatient setting, and it has been evaluated and tested extensively in that setting but has not been used for inpatients (10). Data Collection We tracked test results with Results Manager for 14 days after patient discharge. A research assistant screened all laboratory and radiologic test results returning after discharge and excluded the results of tests done after discharge. Normal, near-normal, and stable results were excluded by using a predefined algorithm (Figure 1). If a result was abnormal, it was sent to 1 of 4 physician-reviewers who, using the electronic medical record, reviewed the discharge diagnosis; any related test results; and the discharge order, note, or summary (when available) to determine whether the result was potentially actionable. Any result mentioned in the discharge summary was excluded (these were most often final radiologic test results that did not differ from the preliminary results available to the inpatient team). Figure 1. Identifying results for physician review At both hospitals, the discharge order (including discharge diagnoses, medications, and follow-up appointments) was entered into the electronic medical record on the day of discharge and therefore was always available at the time of physician review. Of the 671 results that we reviewed, 525 (78%) were for patients who also had a dictated or typed discharge summary available at the time of review. When discharge summaries are completed after hospital discharge, inpatient physicians have access to the electronic medical record, including any test results that were not available on the day of discharge. The physician-reviewers are board-certified internists; 2 are hospitalists, and 2 are primary care physicians. If a physician-reviewer was involved in the care of a patient who had a result that required review, that result was sent to one of the other 3 reviewers. After reviewing the discharge order, the discharge summary, and related test results, the physician-reviewer used clinical judgment to determine whether the result required clinical action on the basis of the available information. A result was considered potentially actionable if it could change the management of the patient by requiring a new treatment or diagnostic test (or repeated testing), modification or discontinuation of a treatment or diagnostic testing, scheduling of an earlier follow-up appointment, or referral of the patient to another physician or specialist. The reviewer rated the result as definitely actionable, probably actionable, probably not actionable, or definitely not actionable. The reviewer also rated the urgency of the required action according to how soon it should occur: within 1 hour, 8 hours, 24 hours, 72 hours, 1 week, or 1 month. Surveys If the physician-reviewer defined a result as definitely actionable or probably actionable, either the inpatient physician or the primary care physician was surveyed by e-mail to determine whether he or she was aware of the result. At hospital A, the attending hospitalist was the inpatient physician surveyed; on the teaching service at hospital B, the junior resident was surveyed. On the nonhousestaff service at hospital B, the hospitalist or nonhospitalist attending physician was surveyed as the inpatient physician. The

Classifying and Predicting Errors of Inpatient Medication Reconciliation

BackgroundFailure to reconcile medications across transitions in care is an important source of potential harm to patients. Little is known about the predictors of unintentional medication discrepancies and how, when, and where they occur.ObjectiveTo determine the reasons, timing, and predictors of potentially harmful medication discrepancies.DesignProspective observational study.PatientsAdmitted general medical patients.MeasurementsStudy pharmacists took gold-standard medication histories and compared them with medical teams’ medication histories, admission and discharge orders. Blinded teams of physicians adjudicated all unexplained discrepancies using a modification of an existing typology. The main outcome was the number of potentially harmful unintentional medication discrepancies per patient (potential adverse drug events or PADEs).ResultsAmong 180 patients, 2066 medication discrepancies were identified, and 257 (12%) were unintentional and had potential for harm (1.4 per patient). Of these, 186 (72%) were due to errors taking the preadmission medication history, while 68 (26%) were due to errors reconciling the medication history with discharge orders. Most PADEs occurred at discharge (75%). In multivariable analyses, low patient understanding of preadmission medications, number of medication changes from preadmission to discharge, and medication history taken by an intern were associated with PADEs.ConclusionsUnintentional medication discrepancies are common and more often due to errors taking an accurate medication history than errors reconciling this history with patient orders. Focusing on accurate medication histories, on potential medication errors at discharge, and on identifying high-risk patients for more intensive interventions may improve medication safety during and after hospitalization.

Effect of an Electronic Medication Reconciliation Application and Process Redesign on Potential Adverse Drug Events A Cluster-Randomized Trial

BACKGROUND Medication reconciliation at transitions in care is a national patient safety goal, but its effects on important patient outcomes require further evaluation. We sought to measure the impact of an information technology-based medication reconciliation intervention on medication discrepancies with potential for harm (potential adverse drug events [PADEs]). METHODS We performed a controlled trial, randomized by medical team, on general medical inpatient units at 2 academic hospitals from May to June 2006. We enrolled 322 patients admitted to 14 medical teams, for whom a medication history could be obtained before discharge. The intervention was a computerized medication reconciliation tool and process redesign involving physicians, nurses, and pharmacists. The main outcome was unintentional discrepancies between preadmission medications and admission or discharge medications that had potential for harm (PADEs). RESULTS Among 160 control patients, there were 230 PADEs (1.44 per patient), while among 162 intervention patients there were 170 PADEs (1.05 per patient) (adjusted relative risk [ARR], 0.72; 95% confidence interval [CI], 0.52-0.99). A significant benefit was found at hospital 1 (ARR, 0.60; 95% CI, 0.38-0.97) but not at hospital 2 (ARR, 0.87; 95% CI, 0.57-1.32) (P = .32 for test of effect modification). Hospitals differed in the extent of integration of the medication reconciliation tool into computerized provider order entry applications at discharge. CONCLUSIONS A computerized medication reconciliation tool and process redesign were associated with a decrease in unintentional medication discrepancies with potential for patient harm. Software integration issues are likely important for successful implementation of computerized medication reconciliation tools.

Handoffs causing patient harm: a survey of medical and surgical house staff.

BACKGROUND Communication lapses at the time of patient handoffs are believed to be common, and yet the frequency with which patients are harmed as a result of problematic handoffs is unknown. Resident physicians were surveyed about their handoffpractices and the frequency with which they perceive problems with handoffs lead to patient harm. METHODS A survey was conducted in 2006 of all resident physicians in internal medicine and general surgery at Massachusetts General Hospital (MGH) concerning the quality and effects of handoffs during their most recent inpatient rotations. Surveys were sent to 238 eligible residents; 161 responses were obtained (response rate, 67.6%). RESULTS Fifty-nine percent of residents reported that one or more patients had been harmed during their most recent clinical rotation because of problematic handoffs, and 12% reported that this harm had been major. Overall quality of handoffs was reported to be fair or poor by 31% of residents. A minority of residents (26%) reported that handoffs usually or always took place in a quiet setting, and 37% reported that one or more interruptions during the receipt of handoffs occurred either most of the time or always. DISCUSSION Although handoffs have long been recognized as potentially hazardous, further scrutiny of handoffs has followed recent reports that handoffs are often marked by missing, incomplete, or inaccurate information and are associated with adverse events. In this study, reports of harm to patients from problematic handoffs were common among residents in internal medicine and general surgery. Many best-practice recommendations for handoffs are not observed, although the extent to which improvement of these practices could reduce patient harm is not known. MGH has recently launched a handoff-safety educational program, along with other interventions designed to improve the safety and effectiveness of handoffs, for its house staff and clinical leadership.

Primary care physician attitudes concerning follow-up of abnormal test results and ambulatory decision support systems

OBJECTIVES Failures to follow-up abnormal test results are common in ambulatory care. Information systems could assist providers with abnormal test result tracking, yet little is known about primary care providers attitudes toward outpatient decision support systems. METHODS A cross-sectional survey of 216 primary care physicians (PCPs) that utilize a single electronic medical record (EMR) without computer-based clinical decision support. RESULTS The overall response rate was 65% (140/216). Less than one-third of the respondents were satisfied with their current system to manage abnormal laboratory, radiographs, Pap smear, or mammograms results. Only 15% of providers were satisfied with their system to notify patients of abnormal results. Over 90% of respondents felt automated systems to track abnormal test results would be useful. Seventy-nine percent of our respondents believed that they could comply better with guidelines through electronic clinical reminders. CONCLUSIONS Most PCPs were not satisfied with their methods for tracking abnormal results. Respondents believed that clinical decision support systems (CDSS) would be useful and could improve their ability to track abnormal results.

Patient Perceptions of a Personal Health Record: A Test of the Diffusion of Innovation Model

Background Personal health records (PHRs) have emerged as an important tool with which patients can electronically communicate with their doctors and doctor’s offices. However, there is a lack of theoretical and empirical research on how patients perceive the PHR and the differences in perceptions between users and non-users of the PHR. Objective To apply a theoretical model, the diffusion of innovation model, to the study of PHRs and conduct an exploratory empirical study on the applicability of the model to the study of perceptions of PHRs. A secondary objective was to assess whether perceptions of PHRs predict the perceived value of the PHR for communicating with the doctor’s office. Methods We first developed a survey capturing perceptions of PHR use and other factors such as sociodemographic characteristics, access and use of technology, perceived innovativeness in the domain of information technology, and perceptions of privacy and security. We then conducted a cross-sectional survey (N = 1500). Patients were grouped into five groups of 300: PHR users (innovators, other users, and laggards), rejecters, and non-adopters. We applied univariate statistical analysis (Pearson chi-square and one-way ANOVA) to assess differences among groups and used multivariate statistical techniques (factor analysis and multiple regression analysis) to assess the presence of factors identified by the diffusion of innovation model and the predictors of our dependent variable (value of PHR for communicating with the doctor’s office). Results Of the 1500 surveys, 760 surveys were returned for an overall response rate of 51%. Computer use among non-adopters (75%) was lower than that among PHR users (99%) and rejecters (92%) (P < .001). Non-adopters also reported a lower score on personal innovativeness in information technology (mean = 2.8) compared to 3.6 and 3.1, respectively, for users and rejecters (P < .001). Four factors identified by the diffusion of innovation model emerged in the factor analysis: ease of use, relative advantage, observability, and trialability. PHR users perceived greater ease of use and relative advantage of the PHR than rejecters and non-adopters (P<.001). Multiple regression analysis showed the following factors as significant positive predictors of the value of PHR for communicating with the doctor’s office: relative advantage, ease of use, trialability, perceptions of privacy and security, age, and computer use. Conclusion Our study found that the diffusion of innovation model fits the study of perceptions of the PHR and provides a suitable theoretical and empirical framework to identify the factors that distinguish PHR users from non-users. The ease of use and relative advantage offered by the PHR emerged as the most important domains among perceptions of PHR use and in predicting the value of the PHR. Efforts to improve uptake and use of PHRs should focus on strategies that enhance the ease of use of PHRs and that highlight the relative advantages of PHRs.

Development of a tool within the electronic medical record to facilitate medication reconciliation after hospital discharge

Serious medication errors occur commonly in the period after hospital discharge. Medication reconciliation in the postdischarge ambulatory setting may be one way to reduce the frequency of these errors. The authors describe the design and implementation of a novel tool built into an ambulatory electronic medical record (EMR) to facilitate postdischarge medication reconciliation. The tool compares the preadmission medication list within the ambulatory EMR to the hospital discharge medication list, highlights all changes, and allows the EMR medication list to be easily updated. As might be expected for a novel tool intended for use in a minority of visits, use of the tool was low at first: 20% of applicable patient visits within 30 days of discharge. Clinician outreach, education, and a pop-up reminder succeeded in increasing use to 41% of applicable visits. Review of feedback identified several usability issues that will inform subsequent versions of the tool and provide generalizable lessons for how best to design medication reconciliation tools for this setting.

Risk of Thiazide-induced Hyponatremia in Patients with Hypertension

BACKGROUND Although hyponatremia is a well-recognized complication of treatment with thiazide diuretics, the risk of thiazide-induced hyponatremia remains uncertain in routine care. METHODS We conducted a retrospective cohort study using a multicenter clinical research registry to identify 2613 adult outpatients that were newly treated for hypertension between January 1, 2000 and December 31, 2005 at 2 teaching hospitals in Boston, Massachusetts, and followed them for up to 10 years. RESULTS Two hundred twenty patients exposed to ongoing thiazide therapy were compared with 2393 patients who were not exposed. In the exposed group, 66 (30%) developed hyponatremia (sodium ≤130 mmol/L). The adjusted incidence rate of hyponatremia was 140 cases per 1000 person-years for patients treated with thiazides, compared with 87 cases per 1000 person-years in those without thiazides. Patients exposed to thiazides were more likely to develop hyponatremia (adjusted incidence rate ratio, 1.61; 95% confidence interval [CI], 1.15-2.25). There was no significant difference in the risk of hospitalizations associated with hyponatremia (adjusted rate ratio, 1.04; 95% CI, 0.46-2.32) or mortality (adjusted rate ratio, 0.41; 95% CI, 0.12-1.42). The number needed to harm (to result in one excess case of incident hyponatremia in 5 years) was 15.02 (95% CI, 7.88-160.30). CONCLUSIONS Approximately 3 in 10 patients exposed to thiazides who continue to take them develop hyponatremia.

From Research to Daily Clinical Practice: What Are the Challenges in “Translation”?

BACKGROUND Translating research findings into sustainable improvements in clinical and patient outcomes remains a substantial obstacle to improving the quality and safety of care. The Agency for Healthcare Research and Quality funded two initiatives to assess strategies for improvements--Translating Research into Practice (TRIP). The TRIP II initiative supported 13 quality improvement projects. SURVEYING THE TRIP II STUDIES: The principal investigators (PIs) of the 13 projects were surveyed regarding encountered barriers to implementation at 6 months and 18 months (when they were also asked about solutions). RESULTS Seven of the 13 PIs responded to the survey at both times--6 and 18 months. For each project stage--Select a TRIP focus and develop intervention strategies (Stage 1), Conduct the intervention (Stage 2), and Measure the Impact (Stage 3)--barriers were described, and field-tested solutions were provided. For example, for Stage 2, if the target audience lacked buy-in and would not participate, solutions would be to get up-front buy-in from all staff, not just leaders; address root causes of problems; use opinion leaders and incentives; plan interventions ahead and provide make-up videos; and accept that targets vary in their readiness to change. DISCUSSION The framework and examples provided should help overcome challenges in any work in which research findings are applied to clinical practice.

Impact of implementing alerts about medication black-box warnings in electronic health records†

The Food and Drug Administration issues black‐box warnings (BBWs) regarding medications with serious risks, yet physician adherence to the warnings is low.