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
Patient safety; decision support; data exchange
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
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
Although the adoption of health information technology (HIT) has advanced in Canada over the past decade, considerable challenges remain in supporting the development, broad adoption, and effective use of HIT in the public health system. Policy makers and practitioners have long recognized that improvements in HIT infrastructure are necessary to support effective and efficient public health practice. The objective of this study was to identify aspects of health information technology (HIT) policy related to public health in Canada that have succeeded, to identify remaining challenges, and to suggest future directions to improve the adoption and use of HIT in the public health system.
A qualitative case study was performed with 24 key stakeholders representing national and provincial organizations responsible for establishing policy and strategic direction for health information technology.
Identified benefits of HIT in public health included improved communication among jurisdictions, increased awareness of the need for interoperable systems, and improvement in data standardization. Identified barriers included a lack of national vision and leadership, insufficient investment, and poor conceptualization of the priority areas for implementing HIT in public health.
The application of HIT in public health should focus on automating core processes and identifying innovative applications of HIT to advance public health outcomes. The Public Health Agency of Canada should develop the expertise to lead public health HIT policy and should establish a mechanism for coordinating public health stakeholder input on HIT policy.
Health information technology; Electronic infrastructure; Informatics; Surveillance; Public health; Canada
To summarize the Canadian health information technology (HIT) policy experience and impart lessons learned to the US as it determines its policy in this area.
Qualitative analysis of interviews with identified key stakeholders followed by an electronic survey.
We conducted semi-structured interviews with 29 key Canadian HIT policy and opinion leaders and used a grounded theory approach to analyze the results. The informant sample was chosen to provide views from different stakeholder groups including national representatives and regional representatives from three Canadian provinces.
Canadian informants believed that much of the current US direction is positive, especially regarding incentives and meaningful use, but that there are key opportunities for the US to emphasize direct engagement with providers, define a clear business case for them, sponsor large scale evaluations to assess HIT impact in a broad array of settings, determine standards but also enable access to resources needed for mid-course corrections of standards when issues are identified, and, finally, leverage implementation of digital imaging systems.
Not all stakeholder groups were included, such as providers or patients. In addition, as in all qualitative research, a selection bias could be present due to the relatively small sample size.
Based on Canadian experience with HIT policy, stakeholders identified as lessons for the US the need to increase direct engagement with providers and the importance of defining the business case for HIT, which can be achieved through large scale evaluations, and of recognizing and leveraging successes as they emerge.
Health information technology; policy; electronic medical records; electronic health records; Canada; health care quality; patient safety; patient-centered care; patient satisfaction; patient safety; decision support; data exchange
Although robotically prepared antineoplastic and adjuvant medications did not reduce serious medication errors, both staff safety and accuracy of medication preparation were improved significantly.
Antineoplastic preparation presents unique safety concerns and consumes significant pharmacy staff time and costs. Robotic antineoplastic and adjuvant medication compounding may provide incremental safety and efficiency advantages compared with standard pharmacy practices.
We conducted a direct observation trial in an academic medical center pharmacy to compare the effects of usual/manual antineoplastic and adjuvant drug preparation (baseline period) with robotic preparation (intervention period). The primary outcomes were serious medication errors and staff safety events with the potential for harm of patients and staff, respectively. Secondary outcomes included medication accuracy determined by gravimetric techniques, medication preparation time, and the costs of both ancillary materials used during drug preparation and personnel time.
Among 1,421 and 972 observed medication preparations, we found nine (0.7%) and seven (0.7%) serious medication errors (P = .8) and 73 (5.1%) and 28 (2.9%) staff safety events (P = .007) in the baseline and intervention periods, respectively. Drugs failed accuracy measurements in 12.5% (23 of 184) and 0.9% (one of 110) of preparations in the baseline and intervention periods, respectively (P < .001). Mean drug preparation time increased by 47% when using the robot (P = .009). Labor costs were similar in both study periods, although the ancillary material costs decreased by 56% in the intervention period (P < .001).
Although robotically prepared antineoplastic and adjuvant medications did not reduce serious medication errors, both staff safety and accuracy of medication preparation were improved significantly. Future studies are necessary to address the overall cost effectiveness of these robotic implementations.
To evaluate the impact of a real-time computerized decision support tool in the emergency department that guides medication dosing for the elderly on physician ordering behavior and on adverse drug events (ADEs).
A prospective controlled trial was conducted over 26 weeks. The status of the decision support tool alternated OFF (7/17/06–8/29/06), ON (8/29/06–10/10/06), OFF (10/10/06–11/28/06), and ON (11/28/06–1/16/07) in consecutive blocks during the study period. In patients ≥65 who were ordered certain benzodiazepines, opiates, non-steroidals, or sedative-hypnotics, the computer application either adjusted the dosing or suggested a different medication. Physicians could accept or reject recommendations.
The primary outcome compared medication ordering consistent with recommendations during ON versus OFF periods. Secondary outcomes included the admission rate, emergency department length of stay for discharged patients, 10-fold dosing orders, use of a second drug to reverse the original medication, and rate of ADEs using previously validated explicit chart review.
2398 orders were placed for 1407 patients over 1548 visits. The majority (49/53; 92.5%) of recommendations for alternate medications were declined. More orders were consistent with dosing recommendations during ON (403/1283; 31.4%) than OFF (256/1115; 23%) periods (p≤0.0001). 673 (43%) visits were reviewed for ADEs. The rate of ADEs was lower during ON (8/237; 3.4%) compared with OFF (31/436; 7.1%) periods (p=0.02). The remaining secondary outcomes showed no difference.
Single institution study, retrospective chart review for ADEs.
Though overall agreement with recommendations was low, real-time computerized decision support resulted in greater acceptance of medication recommendations. Fewer ADEs were observed when computerized decision support was active.
Emergency; computerized decision support; patient safety; decision support; data exchange
Computerized Provider Order Entry (CPOE) can reduce medication errors; however, its benefits are only achieved when data are entered in a structured format and entries are properly coded. This paper aims to explore the incidence of free-text medication order entries involving hypoglycemic agents in an ambulatory electronic health record (EHR) system with CPOE. Our results showed that free-text order entry continues to be frequent. During 2010, 9.3% of hypoglycemic agents were entered as free-text for 2,091 patients. 17.4% of the entries contained misspellings. The highest proportion of free-text entries were found in urgent care clinics (49.4%) and among registered nurses (31.5%). Additionally, 92 drug-drug interaction alerts were not triggered due to free-text entries. Only 25.9% of the patients had diabetes recorded in their problem list. Solutions will require policy to enforce structured entry, ongoing improvement in user-interface design, improved training for users, and strategies for maintaining a complete medication list.
The electronic exchange of health information among healthcare providers has the potential to produce enormous clinical benefits and financial savings, although realizing that potential will be challenging. The American Recovery and Reinvestment Act of 2009 will reward providers for ‘meaningful use’ of electronic health records, including participation in clinical data exchange, but the best ways to do so remain uncertain.
We analyzed patient visits in one community in which a high proportion of providers were using an electronic health record and participating in data exchange. Using claims data from one large private payer for individuals under age 65 years, we computed the number of visits to a provider which involved transitions in care from other providers as a percentage of total visits. We calculated this ‘transition percentage’ for individual providers and medical groups.
On average, excluding radiology and pathology, approximately 51% of visits involved care transitions between individual providers in the community and 36%–41% involved transitions between medical groups. There was substantial variation in transition percentage across medical specialties, within specialties and across medical groups. Specialists tended to have higher transition percentages and smaller ranges within specialty than primary care physicians, who ranged from 32% to 95% (including transitions involving radiology and pathology). The transition percentages of pediatric practices were similar to those of adult primary care, except that many transitions occurred among pediatric physicians within a single medical group.
Care transition patterns differed substantially by type of practice and should be considered in designing incentives to foster providers' meaningful use of health data exchange services.
Health information policy; decision support; machine learning; confidentiality; Patient Safety; decision support; data exchange; editorial Office; health data standards; vocabulary; ontology; scientific information and health data policy; consumer health/patient education information; information retrieval; NLP; public health informatics; clinical trials; health information exchange; health information technology; meaningful use; care coordination
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.
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.
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.
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.
Problem list; clinical decision support; data mining; automated inference; methodology
To report the frequency, types, and causes of errors associated with outpatient computer-generated prescriptions, and to develop a framework to classify these errors to determine which strategies have greatest potential for preventing them.
Materials and methods
This is a retrospective cohort study of 3850 computer-generated prescriptions received by a commercial outpatient pharmacy chain across three states over 4 weeks in 2008. A clinician panel reviewed the prescriptions using a previously described method to identify and classify medication errors. Primary outcomes were the incidence of medication errors; potential adverse drug events, defined as errors with potential for harm; and rate of prescribing errors by error type and by prescribing system.
Of 3850 prescriptions, 452 (11.7%) contained 466 total errors, of which 163 (35.0%) were considered potential adverse drug events. Error rates varied by computerized prescribing system, from 5.1% to 37.5%. The most common error was omitted information (60.7% of all errors).
About one in 10 computer-generated prescriptions included at least one error, of which a third had potential for harm. This is consistent with the literature on manual handwritten prescription error rates. The number, type, and severity of errors varied by computerized prescribing system, suggesting that some systems may be better at preventing errors than others.
Implementing a computerized prescribing system without comprehensive functionality and processes in place to ensure meaningful system use does not decrease medication errors. The authors offer targeted recommendations on improving computerized prescribing systems to prevent errors.
Patient safety; quality of care; informatics; improving healthcare workflow and process efficiency; developing/using clinical decision support (other than diagnostic) and guideline systems; measuring/improving patient safety and reducing medical errors; decision support; data exchange; medical informatics; decision support; healthcare information technology
Medication errors in hospitals are a worldwide concern. The World Health Organization has recommended the implementation of basic applications in healthcare systems to improve medication safety, but it is largely unknown whether these recommendations are adhered to by hospitals. We assessed the presence of core medication safety practices in Saudi Arabian hospitals.
We developed and validated a survey to assess medication safety practices in hospitals. Major headings included Look-Alike Sound-Alike (LASA) medications, control of concentrated electrolyte solutions, transitions in care, information technology, drug information and other medication safety practices. Trained pharmacists visited samples of hospitals from all regions of Saudi Arabia.
Seventy-eight hospitals were surveyed. Only 30% of the hospitals had a medication safety committee and 9% of hospitals had a medication safety officer. Only 33% of hospitals had a list of LASA medications and 50% had a list of error-prone abbreviations. Concentrated electrolytes were available in floor stock in 60% of the hospitals. No hospital involved pharmacists in obtaining medication histories and only 37% of the hospitals provided a medication list to the patients at discharge. While 61% of hospitals used a computer system in their pharmacy to enter prescriptions, only 29% of these hospitals required entry of patient’s allergies before entering a drug order.
Core practices to improve medication safety were not implemented in many hospitals in Saudi Arabia. In developing countries, an effort must be made at the national level to increase the adoption of such practices.
Medication safety; Hospitals; Saudi Arabia
Clinical decision support systems can prevent knowledge-based prescription errors and improve patient outcomes. The clinical effectiveness of these systems, however, is substantially limited by poor user acceptance of presented warnings. To enhance alert acceptance it may be useful to quantify the impact of potential modulators of acceptance.
We built a logistic regression model to predict alert acceptance of drug–drug interaction (DDI) alerts in three different settings. Ten variables from the clinical and human factors literature were evaluated as potential modulators of provider alert acceptance. ORs were calculated for the impact of knowledge quality, alert display, textual information, prioritization, setting, patient age, dose-dependent toxicity, alert frequency, alert level, and required acknowledgment on acceptance of the DDI alert.
50 788 DDI alerts were analyzed. Providers accepted only 1.4% of non-interruptive alerts. For interruptive alerts, user acceptance positively correlated with frequency of the alert (OR 1.30, 95% CI 1.23 to 1.38), quality of display (4.75, 3.87 to 5.84), and alert level (1.74, 1.63 to 1.86). Alert acceptance was higher in inpatients (2.63, 2.32 to 2.97) and for drugs with dose-dependent toxicity (1.13, 1.07 to 1.21). The textual information influenced the mode of reaction and providers were more likely to modify the prescription if the message contained detailed advice on how to manage the DDI.
We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design.
Visualization of data and knowledge; knowledge representations; knowledge acquisition and knowledge management; distributed systems; agents; software engineering: architecture; developing and refining EHR data standards (including image standards); data models; data exchange; controlled terminologies and vocabularies; communication; integration across care settings (inter- and intra-enterprise); knowledge bases; electronic decision support; medication errors; patient safety; decision support
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/
Chronic kidney disease (CKD) causes substantial morbidity and mortality; however, there are limited data to comprehensively assess quality of care in this area.
To assess quality of care for CKD according to patient risk and identify correlates of improved care delivery.
Fifteen health centers within a multi-site group practice in eastern Massachusetts.
166 primary care physicians caring for 11,774 patients with stages 3 or 4 CKD defined as two estimated glomerular filtration rates (eGFR) between 15 and 60.
Two measures of kidney disease monitoring, five measures of cardiovascular disease management, four measures of metabolic bone disease and anemia management, and one measure of drug safety were extracted from the electronic health record. Primary care recognition of CKD was assessed as a problem list diagnosis, and nephrology co-management was assessed as at least one visit with a nephrologist in the prior 12 months.
Overall, 46% of patients were high risk for death based on the presence of diabetes, proteinuria, or an eGFR <45. Seventy percent of patients lacked annual urine protein testing, 46% had a blood pressure ≥130/80 mmHg and 25% were not receiving appropriate angiotensin blockade. Appropriate screening for anemia was common (76%), while screening rates for metabolic bone disease were low. Use of potentially harmful drugs was common (26%). Primary care physician recognition and nephrology co-management were both associated with improved quality of care, though rates of both were low (24% and 10%, respectively).
Significant deficiencies in the quality of CKD care exist. Opportunities for improvement include increasing physician recognition of CKD and improving collaborative care with nephrology.
chronic kidney disease; primary care; quality of care; performance measurement
Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study.
Three site visits were conducted at institutions across the USA to learn about CDS capabilities and processes from clinical, technical, and organizational perspectives. Based on the results of these visits, written questionnaires were sent to the three institutions visited and two additional sites. Together, these five organizations encompass a variety of academic and community hospitals as well as small and large ambulatory practices. These organizations use both commercially available and internally developed clinical information systems.
Characteristics of clinical information systems and CDS systems used at each site as well as governance structures and content management approaches were identified through extensive field interviews and follow-up surveys.
Six recommended practices were identified in the area of governance, and four were identified in the area of content management. Key similarities and differences between the organizations studied were also highlighted.
Each of the five sites studied contributed to the recommended practices presented in this paper for CDS governance. Since these strategies appear to be useful at a diverse range of institutions, they should be considered by any future implementers of decision support.
The epidemiology of adverse drug events (ADEs) and medication errors has received little evaluation outside the U.S. and Europe, and extrapolating from these data might not be valid, especially regarding selecting and prioritizing solutions.
To assess the incidence and preventability of ADEs and medication errors in Japan.
The Japan Adverse Drug Events (JADE) study was a prospective cohort study.
A cohort of 3,459 adults admitted to a stratified random sample of seven medical and eight surgical wards and three intensive care units in three tertiary care hospitals over 6 months.
We measured ADE and medication error rates from daily reviews of charts, laboratories, incident reports, and prescription queries by on-site reviewers; presence of a signal was considered an incident. Two independent physicians reviewed incidents to determine whether they were ADEs or medication errors and to assess severity and preventability.
We identified 1,010 ADEs and 514 medication errors (incidence: 17.0 and 8.7 per 1,000 patient-days, respectively) during the study period. Among ADEs, 1.6%, 4.9% and 33% were fatal, life-threatening and serious, respectively. Among ADEs, 14% were preventable. The rate per admission was 29 per 100 admissions, higher than in U.S. studies because associated with of the long length of hospital stay in Japan (mean, 17 days).
The epidemiology and nature of ADEs and medication errors in Japan were similar to other countries, although more frequent per admission. Solutions that worked in these countries might thus improve medication safety in Japan, as could shortening hospital length of stay.
adverse drug events; epidemiology; medication errors; patient safety
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.
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.
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.
Problem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement.
Problem list; clinical decision support; data mining; automated inference; meaningful use; quality of care; quality measurement; electronic health records; knowledge representations; classical experimental and quasi-experimental study methods (lab and field); designing usable (responsive) resources and systems; statistical analysis of large datasets
Personal health records (PHRs) remain a relatively new technology and concept in practice even though they have been discussed in the literature for more than 50 years. There is no consensus on the definition of a PHR or PHR system even within the professional societies of health information technology.
Our objective was to analyze and classify the opinions of health information professionals regarding the definitions of the PHR.
Q methodology was used to explore the concept of the PHR. A total of 50 Q-statements were selected and rated by 45 P-samples consisting of health information professionals. We analyzed the resulting data by using Q methodology-specific software and SPSS.
We selected five types of health information professionals’ opinions: type I, public interest centered; type II, health information standardization centered; type III, health consumer centered; type IV, health information security centered; and type V, health consumer convenience centered. The Q-statements with the highest levels of agreement were as follows: (1) the PHR is the lifetime record of personal health information, (2) the PHR is the representation of health 2.0, and (3) security is the most important requirement of the PHR. The most disagreed-with Q-statements were (1) the PHR is a paper-based system, and (2) it is most effective to carry the PHR information in USB storage.
Health information professionals agree that PHRs should be lifetime records, that they will be useful as more information is stored electronically, and that data security is paramount. To maximize the benefits of PHR, activation strategies should be developed and extended across disciplines and professionals so that patients begin to receive the benefits associate with using PHRs.
Personal health record; P-sample; Q-sample; Q-statement; qualitative research; self-efficacy