The Leapfrog CPOE evaluation tool has been promoted as a means of monitoring computerized physician order entry (CPOE). We sought to determine the relationship between Leapfrog scores and the rates of preventable adverse drug events (ADE) and potential ADE.
Materials and methods
A cross-sectional study of 1000 adult admissions in five community hospitals from October 1, 2008 to September 30, 2010 was performed. Observed rates of preventable ADE and potential ADE were compared with scores reported by the Leapfrog CPOE evaluation tool. The primary outcome was the rate of preventable ADE and the secondary outcome was the composite rate of preventable ADE and potential ADE.
Leapfrog performance scores were highly related to the primary outcome. A 43% relative reduction in the rate of preventable ADE was predicted for every 5% increase in Leapfrog scores (rate ratio 0.57; 95% CI 0.37 to 0.88). In absolute terms, four fewer preventable ADE per 100 admissions were predicted for every 5% increase in overall Leapfrog scores (rate difference −4.2; 95% CI −7.4 to −1.1). A statistically significant relationship between Leapfrog scores and the secondary outcome, however, was not detected.
Our findings support the use of the Leapfrog tool as a means of evaluating and monitoring CPOE performance after implementation, as addressed by current certification standards.
Scores from the Leapfrog CPOE evaluation tool closely relate to actual rates of preventable ADE. Leapfrog testing may alert providers to potential vulnerabilities and highlight areas for further improvement.
medication safety; computerized physician order entry; clinical decision support; Leapfrog
Primary care clinicians can play an important role in identifying individuals at increased risk of cancer, but often do not obtain detailed information on family history or lifestyle factors from their patients.
We evaluated the feasibility and effectiveness of using a web-based risk appraisal tool in the primary care setting.
Five primary care practices within an academic care network were assigned to the intervention or control group.
We included 15,495 patients who had a new patient visit or annual exam during an 8-month period in 2010–2011.
Intervention patients were asked to complete a web-based risk appraisal tool on a laptop computer immediately before their visit. Information on family history of cancer was sent to their electronic health record (EHR) for clinicians to view; if accepted, it populated coded fields and could trigger clinician reminders about colon and breast cancer screening.
The main outcome measure was new documentation of a positive family history of cancer in coded EHR fields. Secondary outcomes included clinician reminders about screening and discussion of family history, lifestyle factors, and screening.
Among eligible intervention patients, 2.0 % had new information on family history of cancer entered in the EHR within 30 days after the visit, compared to 0.6 % of eligible control patients (adjusted odds ratio = 4.3, p = 0.03). There were no significant differences in the percent of patients who received moderate or high risk reminders for colon or breast cancer screening.
Use of this tool was associated with increased documentation of family history of cancer in the EHR, although the percentage of patients with new family history information was low in both groups. Further research is needed to determine how risk appraisal tools can be integrated with workflow and how they affect screening and health behaviors.
risk appraisal; family history; cancer; primary care
The implementation of health information technology interventions is at the forefront of most policy agendas internationally. However, such undertakings are often far from straightforward as they require complex strategic planning accompanying the systemic organizational changes associated with such programs. Building on our experiences of designing and evaluating the implementation of large-scale health information technology interventions in the USA and the UK, we highlight key lessons learned in the hope of informing the on-going international efforts of policymakers, health directorates, healthcare management, and senior clinicians.
Chronic kidney disease (CKD) is increasingly common and under-recognized in primary care clinics, leading to low rates of stage-appropriate monitoring and treatment. Our objective was to determine whether electronic problem list documentation of CKD is associated with monitoring and treatment.
This is a cross-sectional observational study of patients with stage 3 or 4 CKD, defined as two past estimated glomerular filtration rates (eGFR) 15-60 mL/min/1.73 m2 separated by 90 days and collected between 2007-2008. We examined the association of problem list documentation with: 1) serum eGFR monitoring test, 2) urine protein or albumin monitoring test, 3) an angiotensin converting enzyme inhibitor or angiotensin receptor blocker (ACE/ARB) prescription, 4) mean systolic blood pressure (BP), and 5) BP control.
Out of 3,149 patients with stage 3 or 4 CKD, only 16% of patients had CKD documented on the problem list. After adjustment for eGFR, gender, and race/ethnicity and after clustering by physician, problem list documentation of CKD was associated with serum eGFR testing (97% with problem list documentation vs. 94% without problem list documentation, p = 0.02) and urine protein testing (47% with problem list documentation vs. 40% without problem list documentation, p = 0.04). After adjustment, problem list documentation was not associated with ACE/ARB prescription, mean systolic BP, or BP control.
Documentation of CKD on the electronic problem list is rare. Patients with CKD documentation have better stage-appropriate monitoring of the disease, but do not have higher rates of blood pressure treatment or better blood pressure control. Interventions aimed at increasing documentation of CKD on the problem list may improve stage-appropriate monitoring, but may not improve clinical outcomes.
Electronic health record; Electronic problem list; Chronic kidney disease; Primary care; Electronic medical record
Alert fatigue represents a common problem associated with the use of clinical decision support systems in electronic health records (EHR). This problem is particularly profound with drug–drug interaction (DDI) alerts for which studies have reported override rates of approximately 90%. The objective of this study is to report consensus-based recommendations of an expert panel on DDI that can be safely made non-interruptive to the provider's workflow, in EHR, in an attempt to reduce alert fatigue.
We utilized an expert panel process to rate the interactions. Panelists had expertise in medicine, pharmacy, pharmacology and clinical informatics, and represented both academic institutions and vendors of medication knowledge bases and EHR. In addition, representatives from the US Food and Drug Administration and the American Society of Health-System Pharmacy contributed to the discussions.
Recommendations and considerations of the panel resulted in the creation of a list of 33 class-based low-priority DDI that do not warrant being interruptive alerts in EHR. In one institution, these accounted for 36% of the interactions displayed.
Development and customization of the content of medication knowledge bases that drive DDI alerting represents a resource-intensive task. Creation of a standardized list of low-priority DDI may help reduce alert fatigue across EHR.
Future efforts might include the development of a consortium to maintain this list over time. Such a list could also be used in conjunction with financial incentives tied to its adoption in EHR.
clinical decision support; medication alerts; drug-drug interactions; alert fatigue; DDI alerts; computerized decision support systems
Variability in medical practice in the United States leads to higher costs without achieving better patient outcomes. Clinical practice guidelines, which are intended to reduce variation and improve care, have several drawbacks that limit the extent of buy-in by clinicians. In contrast, standardized clinical assessment and management plans (SCAMPs) offer a clinician-designed approach to promoting care standardization that accommodates patients’ individual differences, respects providers’ clinical acumen, and keeps pace with the rapid growth of medical knowledge. Since early 2009 more than 12,000 patients have been enrolled in forty-nine SCAMPs in nine states and Washington, D.C. In one example, a SCAMP was credited with increasing clinicians’ rate of compliance with a recommended specialist referral for children from 19.6 percent to 75 percent. In another example, SCAMPs were associated with an 11–51 percent decrease in total medical expenses for six conditions when compared with a historical cohort. Innovative tools such as SCAMPs should be carefully examined by policy makers searching for methods to promote the delivery of high-quality, cost-effective care.
At the 2011 American College of Medical Informatics (ACMI) Winter Symposium we studied the overlap between health IT and economics and what leading healthcare delivery organizations are achieving today using IT that might offer paths for the nation to follow for using health IT in healthcare reform. We recognized that health IT by itself can improve health value, but its main contribution to health value may be that it can make possible new care delivery models to achieve much larger value. Health IT is a critically important enabler to fundamental healthcare system changes that may be a way out of our current, severe problem of rising costs and national deficit. We review the current state of healthcare costs, federal health IT stimulus programs, and experiences of several leading organizations, and offer a model for how health IT fits into our health economic future.
Electronic Health Records/economics Health care Reform/trends*; cost-benefit analysis; information Systems/economics*; medical records systems; Computerized/economics; Developing/using computerized provider order entry; Natural-language processing; systems to support and improve diagnostic accuracy; other specific EHR applications (results review); patient safety; decision support; data exchange; system implementation and management issues; improving the education and skills training of health professionals; Developing/using clinical decision support (other than diagnostic) and guideline systems; Measuring/improving patient safety and reducing medical errors; clinical research informatics; information Retrieval; Collaborative technologies; methods for integration of information from disparate sources; Demonstrating return on IT investment; distributed systems; distributed systems
Health IT can play a major role in improving patient safety. Computerized physician order entry with decision support can alert providers to potential prescribing errors. However, too many alerts can result in providers ignoring and overriding clinically important ones.
To evaluate the appropriateness of providers’ drug-drug interaction (DDI) alert overrides, the reasons why they chose to override these alerts, and what actions they took as a consequence of the alert.
A cross-sectional, observational study of DDI alerts generated over a three-year period between January 1st, 2009, and December 31st, 2011.
Primary care practices affiliated with two Harvard teaching hospitals. The DDI alerts were screened to minimize the number of clinically unimportant warnings.
A total of 24,849 DDI alerts were generated in the study period, with 40% accepted. The top 62 providers with the highest override rate were identified and eight overrides randomly selected for each (a total of 496 alert overrides for 438 patients, 3.3% of the sample).
Overall, 68.2% (338/496) of the DDI alert overrides were considered appropriate. Among inappropriate overrides, the therapeutic combinations put patients at increased risk of several specific conditions including: serotonin syndrome (21.5%, n=34), cardiotoxicity (16.5%, n=26), or sharp falls in blood pressure or significant hypotension (28.5%, n=45). A small number of drugs and DDIs accounted for a disproportionate share of alert overrides. Of the 121 appropriate alert overrides where the provider indicated they would “monitor as recommended”, a detailed chart review revealed that only 35.5% (n=43) actually did. Providers sometimes reported that patients had already taken interacting medications together (15.7%, n=78), despite no evidence to confirm this.
Conclusions and Relevance
We found that providers continue to override important and useful alerts that are likely to cause serious patient injuries, even when relatively few false positive alerts are displayed.
Patient safety; decision support; data exchange
There is a pressing need to understand the challenges surrounding procurement of and business case development for hospital electronic prescribing systems, and to identify possible strategies to enhance the efficiency of these processes in order to assist strategic decision making.
Materials and Methods
We organized eight multi-disciplinary round-table discussions in the United Kingdom. Participants included policy makers, representatives from hospitals, system developers, academics, and patients. Each discussion was digitally audio-recorded, transcribed verbatim and, together with accompanying field notes, analyzed thematically with NVivo9.
We drew on data from 17 participants (approximately eight per roundtable), six hours of discussion, and 15 pages of field notes. Key challenges included silo planning with systems not being considered as part of an integrated organizational information technology strategy, lack of opportunity for interactions between customers and potential suppliers, lack of support for hospitals in choosing appropriate systems, difficulty of balancing structured planning with flexibility, and the on-going challenge of distinguishing “wants” and aspirations from organizational “needs”.
Discussion and conclusions
Development of business cases for major investments in information technology does not take place in an organizational vacuum. Building on previously identified potentially transferable dimensions to the development and execution of business cases surrounding measurements of costs/benefits and risk management, we have identified additional components relevant to ePrescribing systems. These include: considerations surrounding strategic context, case for change and objectives, future service requirements and options appraisal, capital and revenue implications, timescale and deliverability, and risk analysis and management.
While some published research indicates a fairly high frequency of Intravenous (IV) medication errors associated with the use of smart infusion pumps, the generalizability of these results are uncertain. Additionally, the lack of a standardized methodology for measuring these errors is an issue. In this study we iteratively developed a web-based data collection tool to capture IV medication errors using a participatory design approach with interdisciplinary experts. Using the developed tool, a prevalence study was then conducted in an academic medical center. The results showed that the tool was easy to use and effectively captured all IV medication errors. Through the prevalence study, violation errors of hospital policy were found that could potentially place patients at risk, but no critical errors known to contribute to patient harm were noted.
To determine whether HIT currently supports care transitions we interviewed clinicians from several healthcare settings. We learned about HIT tools to help nurses facilitate transitions, but discovered that there are few tools to promote high quality, safe transitions of care. We also found that HIT is rarely employed for patient-centered care coordination mechanisms. In conclusion, HIT tools are typically used within one healthcare setting to prepare for a transition, rather than across healthcare settings.
electronic health record; meaningful use; care coordination; care transitions
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.
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.
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.
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.
Clinical; decision support systems; medical order entry systems
Women with gestational diabetes (GDM) are at increased risk for type 2 diabetes (T2DM), but many do not receive recommended follow-up. We sought to identify barriers to follow-up screening.
We surveyed primary care (PCPs) and obstetric and gynecology care providers (OBCPs) in a large health system. We also assessed documentation of GDM history in the health care system’s electronic medical record.
478 clinicians were surveyed, among whom 207 responded. Most participants (81.1%) gave an accurate estimate of risk of progression to T2DM. PCPs were less likely than OBCPs to ask patients about history of GDM (OR 0.43, 95% CI 0.20–0.90), but they were far more likely to indicate that they order glucose screening for women with a known history (OR 4.31, 95% CI 2.01–9.26). Providers identified poor communication between OBCPs and PCPs as a major barrier to screening. Fewer than half (45.8%) of 450 women with GDM by GTT criteria had that history documented on their electronic problem list.
Clinicians are aware that women with GDM are at high risk of developing type 2 diabetes, but they do not routinely assess and screen patients, and communication between OBCPs and PCPs can be improved.
gestational diabetes; evidence-based practice; electronic medical record; type 2 diabetes
The complexity and rapid growth of genetic data demand investment in information technology to support effective use of this information. Creating infrastructure to communicate genetic information to health care providers and enable them to manage that data can positively affect a patient’s care in many ways. However, genetic data are complex and present many challenges. We report on the usability of a novel application designed to assist providers in receiving and managing a patient’s genetic profile, including ongoing updated interpretations of the genetic variants in those patients. Because these interpretations are constantly evolving, managing them represents a challenge. We conducted usability tests with potential users of this application and reported findings to the application development team, many of which were addressed in subsequent versions. Clinicians were excited about the value this tool provides in pushing out variant updates to providers and overall gave the application high usability ratings, but had some difficulty interpreting elements of the interface. Many issues identified required relatively little development effort to fix suggesting that consistently incorporating this type of analysis in the development process can be highly beneficial. For genetic decision support applications, our findings suggest the importance of designing a system that can deliver the most current knowledge and highlight the significance of new genetic information for clinical care. Our results demonstrate that using a development and design process that is user focused helped optimize the value of this application for personalized medicine.
clinical decision support; electronic health records; genomics; personalized medicine
Substantial resources are being invested in health information exchanges (HIE), community-based consortia that enable independent health-care organizations to exchange clinical data. However, under pressure to form accountable care organizations, medical groups may merge and support private HIE, reducing the potential utility of community HIEs. Simulations of “care transitions” based on data from 10 Massachusetts communities suggest that mergers would have to be considerable to substantially reduce the potential utility of an HIE. Nonetheless, simulations also suggest that HIEs will need to recruit a large proportion of the medical groups in a community, as hospitals and the largest groups account for only 10 to 20% of care transitions in communities.
To develop a set of high-severity, clinically significant drug–drug interactions (DDIs) for use in electronic health records (EHRs).
A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included 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. Candidate DDIs were assessed by the panel based on the consequence of the interaction, severity levels assigned to them across various medication knowledge bases, availability of therapeutic alternatives, monitoring/management options, predisposing factors, and the probability of the interaction based on the strength of evidence available in the literature.
Of 31 DDIs considered to be high risk, the panel approved a final list of 15 interactions. Panelists agreed that this list represented drugs that are contraindicated for concurrent use, though it does not necessarily represent a complete list of all such interacting drug pairs. For other drug interactions, severity may depend on additional factors, such as patient conditions or timing of co-administration.
The panel provided recommendations on the creation, maintenance, and implementation of a central repository of high severity interactions.
A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list.
Alerts; Medication-related decision support; electronic health records; alert fatigue; Office of the National Coordinator for health information Technology; drug-drug interaction; clinical decision support; medical informatics; knowledge bases; knowledge acquisition and knowledge management; knowledge representations; uncertain reasoning and decision theory; designing usable (responsive) resources and systems; personal health records and self-care systems; knowledge acquisition and knowledge management; demonstrating return on it investment; other specific EHR applications (results review); medication administration; disease progression; patient safety; decision support; data exchange
Despite mandates and incentives for electronic health record (EHR) adoption, little is known about factors predicting physicians’ satisfaction following EHR implementation.
To measure predictors of physician satisfaction following EHR adoption.
A total of 163 physicians completed a mailed survey before and after EHR implementation through a statewide pilot project in Massachusetts. Multivariable logistic regression identified predictors of physician satisfaction with their current practice situation in 2009 and generalized estimating equations accounted for clustering.
The response rate was 77% in 2005 and 68% in 2009. In 2005, prior to EHR adoption, 28% of physicians were very satisfied with their current practice situation compared to 25% in 2009, following EHR adoption (P < .001). In multivariate analysis, physician satisfaction following EHR adoption was correlated with self-reported ease of EHR implementation (adjusted odds ratio [OR] = 5.7, 95% CI 2.1 - 16), resources for practice improvement (adjusted OR = 2.6, 95% CI 1.2 - 6.1), pre-intervention satisfaction (adjusted OR = 4.8, 95% CI 1.5 - 15), and stress (adjusted OR = 5.3, 95% CI 1.1 - 25). Male physicians reported lower satisfaction following EHR adoption (adjusted OR = 0.3, 95% CI 0.2 - 0.6).
Interventions to expand EHR use should consider additional support for practices with fewer resources for improvement and ensure ease of EHR implementation. EHR adoption may be a factor in alleviating physicians’ stress. Addressing physicians’ satisfaction prior to practice transformation and anticipating greater dissatisfaction among male physicians will be essential to retaining the physician workforce and ensuring the quality of care they deliver.
electronic health record; physician satisfaction; implementation; Massachusetts eHealth collaborative
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.
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.
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).
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.
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.
Personal health record (PHR); perceptions; innovation; electronic health records (EHRs); meaningful use
Accurate patient problem lists are valuable tools for improving the quality of care, enabling clinical decision support, and facilitating research and quality measurement. However, problem lists are frequently inaccurate and out-of-date and use varies widely across providers.
Our goal was to assess provider use of an electronic problem list and identify differences in usage between medical specialties.
Chart review of a random sample of 100,000 patients who had received care in the past two years at a Boston-based academic medical center.
Counts were collected of all notes and problems added for each patient from 1/1/2002 to 4/30/2010. For each entry, the recording provider and the clinic in which the entry was recorded was collected. We used the Healthcare Provider Taxonomy Code Set to categorize each clinic by specialty.
We analyzed the problem list use across specialties, controlling for note volume as a proxy for visits.
A total of 2,264,051 notes and 158,105 problems were recorded in the electronic medical record for this population during the study period. Primary care providers added 82.3% of all problems, despite writing only 40.4% of all notes. Of all patients, 49.1% had an assigned primary care provider (PCP) affiliated with the hospital; patients with a PCP had an average of 4.7 documented problems compared to 1.5 problems for patients without a PCP.
Primary care providers were responsible for the majority of problem documentation; surgical and medical specialists and subspecialists recorded a disproportionately small number of problems on the problem list.
patient problem list; electronic medical records; primary care
It is uncertain if computerized physician order entry (CPOE) systems are effective at reducing adverse drug event (ADE) rates in community hospitals, where mainly vendor-developed applications are used.
To evaluate the impact of vendor CPOE systems on the frequency of ADEs.
DESIGN AND PATIENTS
Prospective before-and-after study conducted from January 2005 to September 2010 at five Massachusetts community hospitals. Participants were adults admitted during the study period. A total of 2,000 charts were reviewed for orders, medication lists, laboratory reports, admission histories, notes, discharge summaries, and flow sheets.
The primary outcome measure was the rate of preventable ADEs. Rates of potential ADEs and overall ADEs were secondary outcomes.
The rate of preventable ADEs decreased following implementation (10.6/100 vs. 7.0/100 admissions; p = 0.007) with a similar effect observed at each site. However, the associated decrease in preventable ADEs was balanced against an increase in potential ADEs (44.4/100 vs. 57.5/100 admissions; p < 0.001). We observed a reduction of 34.0% for preventable ADEs, but an increase of 29.5% in potential ADEs following implementation. The overall rate of ADEs increased (14.6/100 vs. 18.7/100 admissions; p = 0.03), which was driven by non-preventable events (4.0/100 vs. 11.7/100 admissions; p < 0.001).
Adoption of vendor CPOE systems was associated with a decrease in the preventable ADE rate by a third, although the rates of potential ADEs and overall ADEs increased. Our findings support the use of vendor CPOE systems as a means to reduce drug-related injury and harm. The potential ADE rate could be reduced by making refinements to the vendor applications and their associated decision support.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-012-1987-7) contains supplementary material, which is available to authorized users.
medication safety; adverse drug events; unintended consequences
Little is known about the frequency and types of prescribing errors in the ambulatory setting among community-based, primary care providers. Therefore, the rates and types of prescribing errors were assessed among community-based, primary care providers in two states.
Material and Methods
A non-randomized cross-sectional study was conducted of 48 providers in New York and 30 providers in Massachusetts, all of whom used paper prescriptions, from September 2005 to November 2006. Using standardized methodology, prescriptions and medical records were reviewed to identify errors.
9385 prescriptions were analyzed from 5955 patients. The overall prescribing error rate, excluding illegibility errors, was 36.7 per 100 prescriptions (95% CI 30.7 to 44.0) and did not vary significantly between providers from each state (p=0.39). One or more non-illegibility errors were found in 28% of prescriptions. Rates of illegibility errors were very high (175.0 per 100 prescriptions, 95% CI 169.1 to 181.3). Inappropriate abbreviation and direction errors also occurred frequently (13.4 and 4.2 errors per 100 prescriptions, respectively). Reviewers determined that the vast majority of errors could have been eliminated through the use of e-prescribing with clinical decision support.
Prescribing errors appear to occur at very high rates among community-based primary care providers, especially when compared with studies of academic-affiliated providers that have found nearly threefold lower error rates. Illegibility errors are particularly problematical.
Further characterizing prescribing errors of community-based providers may inform strategies to improve ambulatory medication safety, especially e-prescribing.
Trial registration number
Ambulatory; data exchange; decision support; electronic health records; health information technology; inappropriate prescribing; medication error; measuring/improving patient safety and reducing medical errors; patient safety; primary care; quality of care; veterans
Electronic health record (EHR) adoption is a national priority in the USA, and well-designed EHRs have the potential to improve quality and safety. However, physicians are reluctant to implement EHRs due to financial constraints, usability concerns, and apprehension about unintended consequences, including the introduction of medical errors related to EHR use. The goal of this study was to characterize and describe physicians' attitudes towards three consequences of EHR implementation: (1) the potential for EHRs to introduce new errors; (2) improvements in healthcare quality; and (3) changes in overall physician satisfaction.
Using data from a 2007 statewide survey of Massachusetts physicians, we conducted multivariate regression analysis to examine relationships between practice characteristics, perceptions of EHR-related errors, perceptions of healthcare quality, and overall physician satisfaction.
30% of physicians agreed that EHRs create new opportunities for error, but only 2% believed their EHR has created more errors than it prevented. With respect to perceptions of quality, there was no significant association between perceptions of EHR-associated errors and perceptions of EHR-associated changes in healthcare quality. Finally, physicians who believed that EHRs created new opportunities for error were less likely be satisfied with their practice situation (adjusted OR 0.49, p=0.001).
Almost one third of physicians perceived that EHRs create new opportunities for error. This perception was associated with lower levels of physician satisfaction.
Electronic medical records; medical errors; hospital information systems; unintended consequences; physician satisfaction; electronic health record; developing/using computerized provider order entry; knowledge representations; classical experimental and quasi-experimental study methods (lab and field); designing usable (responsive) resources and systems; statistical analysis of large datasets; health information technology; quality of care; electronic health records; veterans; primary care; patient safety; decision support; data exchange
Physicians are often unaware of the results of tests pending at discharge (TPADs). The authors designed and implemented an automated system to notify the responsible inpatient physician of the finalized results of TPADs using secure, network email. The system coordinates a series of electronic events triggered by the discharge time stamp and sends an email to the identified discharging attending physician once finalized results are available. A carbon copy is sent to the primary care physicians in order to facilitate communication and the subsequent transfer of responsibility. Logic was incorporated to suppress selected tests and to limit notification volume. The system was activated for patients with TPADs discharged by randomly selected inpatient-attending physicians during a 6-month pilot. They received approximately 1.6 email notifications per discharged patient with TPADs. Eighty-four per cent of inpatient-attending physicians receiving automated email notifications stated that they were satisfied with the system in a brief survey (59% survey response rate). Automated email notification is a useful strategy for managing results of TPADs.
Safety; quality; mobile; quality improvement; patient safety; clinical decision support; hospital medicine; medical informatics; decision support; healthcare information technology; communication; BICS; pending tests; automated alerts; discharge; email notification; decision support; data exchange
Little is known about physicians' perception of the ease or difficulty of implementing electronic health records (EHR). This study identified factors related to the perceived difficulty of implementing EHR. 163 physicians completed surveys before and after the implementation of EHR in an externally funded pilot program in three Massachusetts communities. Ordinal hierarchical logistic regression was used to identify baseline factors that correlated with physicians' report of difficulty with EHR implementation. Compared with physicians with ownership stake in their practices, physician employees were less likely to describe EHR implementation as difficult (adjusted OR 0.5, 95% CI 0.3 to 1.0). Physicians who perceived their staff to be innovative were also less likely to view EHR implementation as difficult (adjusted OR 0.4, 95% CI 0.2 to 0.8). Physicians who own their practice may need more external support for EHR implementation than those who do not. Innovative clinical support staff may ease the EHR implementation process and contribute to its success.
Data exchange; decision support; electronic health records; group practice; health information technology; implementation; ownership; patient safety; practice management; primary care; quality of care; veterans