Person:

Bates, David

Ilan and Donchin have compared Israel and Canada's experiences in setting a national patient safety agenda. We broaden this comparison to include the U.S. experience, and suggest that there are three additional key steps which will be important in any national patient safety agenda, and which Israel in particular should consider. These are 1) using health information technology (HIT) to directly improve patient safety, 2) dissemination and broad use of checklists, and 3) measuring patient safety over time at the national level. Especially because of its already substantial commitment to HIT and well-developed HIT sector, Israel has a major opportunity to move forward rapidly in this area and to achieve broad impact on the safety front. This is a commentary on http://www.ijhpr.org/content/1/1/19/

Background: Treatment of severe sepsis is expensive, often encompassing a number of discretionary modalities. The objective of the present study was to assess intercenter variation in resource and therapeutic modality use in patients with severe sepsis. Methods: We conducted a prospective cohort study of 1028 adult admissions with severe sepsis from a stratified random sample of patients admitted to eight academic tertiary care centers. The main outcome measures were length of stay (LOS; total LOS and LOS after onset of severe sepsis) and total hospital charges. Results: The adjusted mean total hospital charges varied from $69 429 to US$237 898 across centers, whereas the adjusted LOS after onset varied from 15.9 days to 24.2 days per admission. Treatments used frequently after the first onset of sepsis among patients with severe sepsis were pulmonary artery catheters (19.4%), ventilator support (21.8%), pressor support (45.8%) and albumin infusion (14.4%). Pulmonary artery catheter use, ventilator support and albumin infusion had moderate variation profiles, varying 3.2-fold to 4.9-fold, whereas the rate of pressor support varied only 1.92-fold across centers. Even after adjusting for age, sex, Charlson comorbidity score, discharge diagnosis-relative group weight, organ dysfunction and service at onset, the odds for using these therapeutic modalities still varied significantly across centers. Failure to start antibiotics within 24 hours was strongly correlated with a higher probability of 28-day mortality (r2 = 0.72). Conclusion: These data demonstrate moderate but significant variation in resource use and use of technologies in treatment of severe sepsis among academic centers. Delay in antibiotic therapy was associated with worse outcome at the center level.

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 6,277 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.

Objective: Computerized provider order entry (CPOE) with clinical decision support (CDS) can help hospitals improve care. Little is known about what CDS is presently in use and how it is managed, however, especially in community hospitals. This study sought to address this knowledge gap by identifying standard practices related to CDS in US community hospitals with mature CPOE systems. Materials and Methods Representatives of 34 community hospitals, each of which had over 5 years experience with CPOE, were interviewed to identify standard practices related to CDS. Data were analyzed with a mix of descriptive statistics and qualitative approaches to the identification of patterns, themes and trends. Results: This broad sample of community hospitals had robust levels of CDS despite their small size and the independent nature of many of their physician staff members. The hospitals uniformly used medication alerts and order sets, had sophisticated governance procedures for CDS, and employed staff to customize CDS. Discussion The level of customization needed for most CDS before implementation was greater than expected. Customization requires skilled individuals who represent an emerging manpower need at this type of hospital. Conclusion: These results bode well for robust diffusion of CDS to similar hospitals in the process of adopting CDS and suggest that national policies to promote CDS use may be successful.

Objectives: To evaluate the impact of preoperative sepsis on risk of postoperative arterial and venous thromboses. Design: Prospective cohort study using the National Surgical Quality Improvement Program database of the American College of Surgeons (ACS-NSQIP). Setting: Inpatient and outpatient procedures in 374 hospitals of all types across the United States, 2005-12. Participants: 2 305 380 adults who underwent surgical procedures. Main outcome measures Arterial thrombosis (myocardial infarction or stroke) and venous thrombosis (deep venous thrombosis or pulmonary embolism) in the 30 days after surgery. Results: Among all surgical procedures, patients with preoperative systemic inflammatory response syndrome or any sepsis had three times the odds of having an arterial or venous postoperative thrombosis (odds ratio 3.1, 95% confidence interval 3.0 to 3.1). The adjusted odds ratios were 2.7 (2.5 to 2.8) for arterial thrombosis and 3.3 (3.2 to 3.4) for venous thrombosis. The adjusted odds ratios for thrombosis were 2.5 (2.4 to 2.6) in patients with systemic inflammatory response syndrome, 3.3 (3.1 to 3.4) in patients with sepsis, and 5.7 (5.4 to 6.1) in patients with severe sepsis, compared with patients without any systemic inflammation. In patients with preoperative sepsis, both emergency and elective surgical procedures had a twofold increased odds of thrombosis. Conclusions: Preoperative sepsis represents an important independent risk factor for both arterial and venous thromboses. The risk of thrombosis increases with the severity of the inflammatory response and is higher in both emergent and elective surgical procedures. Suspicion of thrombosis should be higher in patients with sepsis who undergo surgery.

Objectives: We investigated incidence rates to understand the nature of medication errors potentially introduced by utilizing a computerized physician order entry (CPOE) system in the three clinical phases of the medication process: prescription, administration, and documentation. Methods: Overt observations and chart reviews were employed at two surgical intensive care units of a 950-bed tertiary teaching hospital. Ten categories of high-risk drugs prescribed over a four-month period were noted and reviewed. Error definition and classifications were adapted from previous studies for use in the present research. Incidences of medication errors in the three phases of the medication process were analyzed. In addition, nurses' responses to prescription errors were also assessed. Results: Of the 534 prescriptions issued, 286 (53.6%) included at least one error. The proportion of errors was 19.0% (58) of the 306 drug administrations, of which two-thirds were verbal orders classified as errors due to incorrectly entered prescriptions. Documentation errors occurred in 205 (82.7%) of 248 correctly performed administrations. When tracking incorrectly entered prescriptions, 93% of the errors were intercepted by nurses, but two-thirds of them were recorded as prescribed rather than administered. Conclusion: The number of errors occurring at each phase of the medication process was relatively high, despite long experience with a CPOE system. The main causes of administration errors and documentation errors were prescription errors and verbal order processes. To reduce these errors, hospital-level and unit-level efforts toward a better system are needed.

Background: Although most outpatients are relatively healthy, many have chronic renal insufficiency, and high override rates for suggestions on renal dosing have been observed. To better understand the override of renal dosing alerts in an outpatient setting, we conducted a study to evaluate which patients were more frequently prescribed contraindicated medications, to assess providers’ responses to suggestions, and to examine the drugs involved and the reasons for overrides. Methods: We obtained data on renal alert overrides and the coded reasons for overrides cited by providers at the time of prescription from outpatient clinics and ambulatory hospital-based practices at a large academic health care center over a period of 3 years, from January 2009 to December 2011. For detailed chart review, a group of 6 trained clinicians developed the appropriateness criteria with excellent inter-rater reliability (κ = 0.93). We stratified providers by override frequency and then drew samples from the high- and low-frequency groups. We measured the rate of total overrides, rate of appropriate overrides, medications overridden, and the reason(s) for override. Results: A total of 4120 renal alerts were triggered by 584 prescribers in the study period, among which 78.2% (3,221) were overridden. Almost half of the alerts were triggered by 40 providers and one-third was triggered by high-frequency overriders. The appropriateness rates were fairly similar, at 28.4% and 31.6% for high- and low-frequency overriders, respectively. Metformin, glyburide, hydrochlorothiazide, and nitrofurantoin were the most common drugs overridden. Physicians’ appropriateness rates were higher than the rates for nurse practitioners (32.9% vs. 22.1%). Physicians with low frequency override rates had higher levels of appropriateness for metformin than the high frequency overriders (P = 0.005). Conclusion: A small number of providers accounted for a large fraction of overrides, as was the case with a small number of drugs. These data suggest that a focused intervention targeting primarily these providers and medications has the potential to improve medication safety.

BACKGROUND Although sleep deprivation has been shown to impair neurobehavioral performance, few studies have measured its effects on medical errors.

METHODS We conducted a prospective, randomized study comparing the rates of serious medical errors made by interns while they were working according to a traditional schedule with extended (24 hours or more) work shifts every other shift (an “every third night” call schedule) and while they were working according to an intervention schedule that eliminated extended work shifts and reduced the number of hours worked per week. Incidents were identified by means of a multidisciplinary, four-pronged approach that included direct, continuous observation. Two physicians who were unaware of the interns' schedule assignments independently rated each incident.

RESULTS During a total of 2203 patient-days involving 634 admissions, interns made 35.9 percent more serious medical errors during the traditional schedule than during the intervention schedule (136.0 vs. 100.1 per 1000 patient-days, P<0.001), including 56.6 percent more nonintercepted serious errors (P<0.001). The total rate of serious errors on the critical care units was 22.0 percent higher during the traditional schedule than during the intervention schedule (193.2 vs. 158.4 per 1000 patient-days, P<0.001). Interns made 20.8 percent more serious medication errors during the traditional schedule than during the intervention schedule (99.7 vs. 82.5 per 1000 patient-days, P=0.03). Interns also made 5.6 times as many serious diagnostic errors during the traditional schedule as during the intervention schedule (18.6 vs. 3.3 per 1000 patient-days, P<0.001).

CONCLUSIONS Interns made substantially more serious medical errors when they worked frequent shifts of 24 hours or more than when they worked shorter shifts. Eliminating extended work shifts and reducing the number of hours interns work per week can reduce serious medical errors in the intensive care unit.

Objective To evaluate the primary diagnoses and patterns of 30 day readmissions and potentially avoidable readmissions in medical patients with each of the most common comorbidities. Design: Retrospective cohort study. Setting: Academic tertiary medical centre in Boston, 2009-10. Participants: 10 731 consecutive adult discharges from a medical department. Main outcome measures Primary readmission diagnoses of readmissions within 30 days of discharge and potentially avoidable 30 day readmissions to the index hospital or two other hospitals in its network. Results: Among 10 731 discharges, 2398 (22.3%) were followed by a 30 day readmission, of which 858 (8.0%) were identified as potentially avoidable. Overall, infection, neoplasm, heart failure, gastrointestinal disorder, and liver disorder were the most frequent primary diagnoses of potentially avoidable readmissions. Almost all of the top five diagnoses of potentially avoidable readmissions for each comorbidity were possible direct or indirect complications of that comorbidity. In patients with a comorbidity of heart failure, diabetes, ischemic heart disease, atrial fibrillation, or chronic kidney disease, the most common diagnosis of potentially avoidable readmission was acute heart failure. Patients with neoplasm, heart failure, and chronic kidney disease had a higher risk of potentially avoidable readmissions than did those without those comorbidities. Conclusions: The five most common primary diagnoses of potentially avoidable readmissions were usually possible complications of an underlying comorbidity. Post-discharge care should focus attention not just on the primary index admission diagnosis but also on the comorbidities patients have.

Background: High override rates for drug-drug interaction (DDI) alerts in electronic health records (EHRs) result in the potentially dangerous consequence of providers ignoring clinically significant alerts. Lack of uniformity of criteria for determining the severity or validity of these interactions often results in discrepancies in how these are evaluated. The purpose of this study was to identify a set of criteria for assessing DDIs that should be used for the generation of clinical decision support (CDS) alerts in EHRs. Methods: We conducted a 20-year systematic literature review of MEDLINE and EMBASE to identify characteristics of high-priority DDIs. These criteria were validated by an expert panel consisting of medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. Results: Forty-four articles met the inclusion criteria for assessing characteristics of high-priority DDIs. The panel considered five criteria to be most important when assessing an interaction- Severity, Probability, Clinical Implications of the interaction, Patient characteristics, and the Evidence supporting the interaction. In addition, the panel identified barriers and considerations for being able to utilize these criteria in medication knowledge bases used by EHRs. Conclusions: A multi-dimensional approach is needed to understanding the importance of an interaction for inclusion in medication knowledge bases for the purpose of CDS alerting. The criteria identified in this study can serve as a first step towards a uniform approach in assessing which interactions are critical and warrant interruption of a provider’s workflow.