Erika L. Abramson

Electronic Prescribing Improves Medication Safety in Community-Based Office Practices

BACKGROUNDAlthough electronic prescribing (e-prescribing) holds promise for preventing prescription errors in the ambulatory setting, research on its effectiveness is inconclusive.OBJECTIVETo assess the impact of a stand-alone e-prescribing system on the rates and types of ambulatory prescribing errors.DESIGN, PARTICIPANTSProspective, non-randomized study using pre-post design of 15 providers who adopted e-prescribing with concurrent controls of 15 paper-based providers from September 2005 through June 2007.INTERVENTIONUse of a commercial, stand-alone e-prescribing system with clinical decision support including dosing recommendations and checks for drug-allergy interactions, drug-drug interactions, and duplicate therapies.MAIN MEASURESPrescribing errors were identified by a standardized prescription and chart review.KEY RESULTSWe analyzed 3684 paper-based prescriptions at baseline and 3848 paper-based and electronic prescriptions at one year of follow-up. For e-prescribing adopters, error rates decreased nearly sevenfold, from 42.5 per 100 prescriptions (95% confidence interval (CI), 36.7–49.3) at baseline to 6.6 per 100 prescriptions (95% CI, 5.1–8.3) one year after adoption (p < 0.001). For non-adopters, error rates remained high at 37.3 per 100 prescriptions (95% CI, 27.6–50.2) at baseline and 38.4 per 100 prescriptions (95% CI, 27.4–53.9) at one year (p = 0.54). At one year, the error rate for e-prescribing adopters was significantly lower than for non-adopters (p < 0.001). Illegibility errors were very high at baseline and were completely eliminated by e-prescribing (87.6 per 100 prescriptions at baseline for e-prescribing adopters, 0 at one year).CONCLUSIONSPrescribing errors may occur much more frequently in community-based practices than previously reported. Our preliminary findings suggest that stand-alone e-prescribing with clinical decision support may significantly improve ambulatory medication safety.TRIAL REGISTRATIONClinicalTrials.gov, Taconic Health Information Network and Community (THINC), NCT00225563, http://clinicaltrials.gov/ct2/show/NCT00225563?term=Kaushal&rank=6.

Unit-based clinical pharmacists’ prevention of serious medication errors in pediatric inpatients

PURPOSE Rates of serious medication errors in three pediatric inpatient units (intensive care, general medical, and general surgical) were measured before and after introduction of unit-based clinical pharmacists. METHODS Error rates on the study units and similar patient care units in the same hospital that served as controls were determined during six- to eight-week baseline periods and three-month periods after the introduction of unit-based clinical pharmacists (full-time in the intensive care unit [ICU] and mornings only on the general units). Nurses trained by the investigators reviewed medication orders, medication administration records, and patient charts daily to detect errors, near misses, and adverse drug events (ADEs) and determine whether near misses were intercepted. Two physicians independently reviewed and rated all data collected by the nurses. Serious medication errors were defined as preventable ADEs and nonintercepted near misses. RESULTS The baseline rates of serious medication errors per 1000 patient days were 29 for the ICU, 8 for the general medical unit, and 7 for the general surgical unit. With unit-based clinical pharmacists, the ICU rate dropped to 6 per 1000 patient days. In the general care units, there was no reduction from baseline in the rates of serious medication errors. CONCLUSION A full-time unit-based clinical pharmacist substantially decreased the rate of serious medication errors in a pediatric ICU, but a part-time pharmacist was not as effective in decreasing errors in pediatric general care units.

HEAL NY: Promoting Interoperable Health Information Technology In New York State

Through a novel, ambitious program called HEAL NY, New York State plans to invest

Physician experiences transitioning between an older versus newer electronic health record for electronic prescribing

250 million in health information technology (IT) that can be linked electronically to other health IT systems. In contrast to high rates of closure by other organizations attempting health information exchange (HIE), 100 percent of HEAL NY Phase 1 grantees still existed two years after awards were announced, 85 percent were still pursuing HIE, and 35 percent had actual users. The number of grantees meeting basic criteria for regional health information organizations (RHIOs) increased. Although it is early, lessons learned can inform state-based initiatives nationwide.

Electronic Prescribing Within an Electronic Health Record Reduces Ambulatory Prescribing Errors

PURPOSE Federal incentives to adopt interoperable, certified electronic health records (EHRs) with electronic prescribing (e-prescribing) are motivating providers using older EHRs to transition to newer EHRs. The objective of this study was to describe, from the perspective of experienced EHR users, the transition from an older, locally developed EHR with minimal clinical decision support (CDS) for e-prescribing to a newer, commercial EHR with more robust CDS for e-prescribing. METHODS This qualitative, case study consisted of observations and semi-structured interviews of adult internal medicine faculty members (n=19) at an academic-affiliated ambulatory care clinic from January through November 2009. All providers transitioned from the older, locally developed EHR to the newer, commercial EHR in April 2008. We analyzed field notes of observations and transcripts of semi-structured interviews using qualitative methods guided by a grounded theory approach. RESULTS We identified key themes describing physician experiences. Despite intensive effort by the information systems team to ease the transition, even these experienced e-prescribers found transitioning extremely difficult. The commercial EHR was not perceived as improving medication safety, despite having more robust CDS. Additionally, physicians felt the commercial EHR was too complex, reducing their efficiency. CONCLUSIONS This is among the first studies examining physician experiences transitioning between an older, locally developed EHR to a newer, commercial EHR with more robust CDS for e-prescribing. Understanding physician experiences with this type of transition and their general preferences for prescribing applications may lead to less disruptive system implementations and better designed EHRs that are more readily accepted by providers. In this way, productivity and safety benefits may be maximized while mitigating potential threats associated with transitions. TRIAL REGISTRATION ClinicalTrials.gov, Identifier: NCT00603070.

The Triangle Model for evaluating the effect of health information technology on healthcare quality and safety

BACKGROUND Health policy forces are promoting the adoption of interoperable electronic health records (EHRs) with electronic prescribing (e-prescribing). Despite the promise of EHRs with e-prescribing to improve medication safety in ambulatory care settings--where most prescribing occurs and where errors are common--few studies have demonstrated its effectiveness. A study was conducted to assess the effect of an e-prescribing system with clinical decision support, including checks for drug allergies and drug-drug interactions, that was integrated within an EHR on rates of ambulatory prescribing errors. METHODS In a prospective study using a nonrandomized, pre-post design with concurrent controls, 6 providers who used a commercial e-prescribing system were compared with 15 providers who remained paper-based from September 2005 through July 2008. Prescribing errors were identified by a standardized prescription and chart review. RESULTS Some 2,432 paper prescriptions at baseline and 2,079 prescriptions at one year were analyzed. Error rates for e-prescribing adopters decreased 1.5-fold--from 26.0 errors per 100 prescriptions at baseline (95% confidence interval [CI], 17.4-38.9) to 16.0 errors per 100 prescriptions at one year (95% CI, 12.7-20.2; p = .09). Error rates remained unchanged for nonadopters (37.3 per 100 prescriptions at baseline, 95% CI, 27.6-50.2, versus 38.4 per 100 prescriptions at one year, 95% CI 27.4-53.9; p = .54). Error rates for e-prescribing adopters were significantly lower than for nonadopters at one year (p < .001). Illegibility errors were high at baseline and eliminated by e-prescribing. CONCLUSIONS The preliminary findings from this small group of providers suggest that e-prescribing systems may decrease ambulatory prescribing errors, which are occurring at high rates among community-based providers.

Medication errors in paediatric outpatients

With the proliferation of relatively mature health information technology (IT) systems with large numbers of users, it becomes increasingly important to evaluate the effect of these systems on the quality and safety of healthcare. Previous research on the effectiveness of health IT has had mixed results, which may be in part attributable to the evaluation frameworks used. The authors propose a model for evaluation, the Triangle Model, developed for designing studies of quality and safety outcomes of health IT. This model identifies structure-level predictors, including characteristics of: (1) the technology itself; (2) the provider using the technology; (3) the organizational setting; and (4) the patient population. In addition, the model outlines process predictors, including (1) usage of the technology, (2) organizational support for and customization of the technology, and (3) organizational policies and procedures about quality and safety. The Triangle Model specifies the variables to be measured, but is flexible enough to accommodate both qualitative and quantitative approaches to capturing them. The authors illustrate this model, which integrates perspectives from both health services research and biomedical informatics, with examples from evaluations of electronic prescribing, but it is also applicable to a variety of types of health IT systems.

A Statewide Assessment of Electronic Health Record Adoption and Health Information Exchange among Nursing Homes

Background Medication errors are common in many settings and have important ramifications. Although there is growing research on rates and characteristics of medication errors in adult ambulatory settings, less is known about the paediatric ambulatory setting. Objective To assess medication error rates in paediatric patients in ambulatory settings. Methods The authors conducted a prospective cohort study of paediatric patients in six outpatient offices in Massachusetts. Data were collected using duplicate prescription review, two parental surveys and chart review. A research nurse classified all medication errors by stage and type of error. Results The authors identified 1205 medication errors with minimal potential for harm (rate: 68% of patients, 95% CI 64 to 72%; 53% of Rx, 95% CI 50 to 56%) and 464 potentially harmful medication errors (ie, near misses) (rate: 26% of patients, 95% CI 24 to 28%; 21% of Rx, 95% CI 19 to 22%). Overall, 94% of the medication errors with minimal potential for harm and 60% of the near misses occurred at the prescribing stage. The most common types of errors were inappropriate abbreviations followed by dosing errors. The most frequent cause of errors was illegibility. Conclusion With paper prescribing, half the prescriptions had medication errors, and one in five had a potentially harmful error. These rates are very high. Interventions targeting the ordering and administration stages have the greatest potential benefit.

A long-term follow-up evaluation of electronic health record prescribing safety

OBJECTIVE To determine rates of electronic health record (EHR) adoption and health information exchange (HIE) among New York State (NYS) nursing homes. DATA SOURCES/STUDY SETTING Primary data collected from a novel survey administered between November 2011 and March 2012 to all NYS nursing homes. STUDY DESIGN We used a cross-sectional study design to assess level of EHR implementation, automation of key functionalities, participation in HIE, and barriers to adoption. DATA COLLECTION/EXTRACTION METHODS We used descriptive statistics to characterize rates of EHR adoption and participation in HIE and logistic regression to identify nursing home characteristics associated with EHR adoption and HIE. PRINCIPAL FINDINGS We received responses from 375 of 632 nursing homes (59.3 percent). Of respondents, almost one in five (n=66, 18.0 percent) reported having a fully implemented and operational EHR and a majority (n=192, 54.4 percent) reported electronically exchanging information. Nursing homes with 100-159 beds were significantly less likely than other facilities to have implemented or be in the process of implementing an EHR (p=.011). CONCLUSIONS Our findings present an important systematic look at EHR adoption and HIE by NYS nursing homes. Although the nursing home sector has been reported to lag in health information technology adoption, our results are encouraging. However, they suggest much room for growth and highlight the need for targeted initiatives to achieve more widespread adoption in this important health care sector.

Computerized Provider Order Entry and Patient Safety

OBJECTIVE To be eligible for incentives through the Electronic Health Record (EHR) Incentive Program, many providers using older or locally developed EHRs will be transitioning to new, commercial EHRs. We previously evaluated prescribing errors made by providers in the first year following transition from a locally developed EHR with minimal prescribing clinical decision support (CDS) to a commercial EHR with robust CDS. Following system refinements, we conducted this study to assess the rates and types of errors 2 years after transition and determine the evolution of errors. MATERIALS AND METHODS We conducted a mixed methods cross-sectional case study of 16 physicians at an academic-affiliated ambulatory clinic from April to June 2010. We utilized standardized prescription and chart review to identify errors. Fourteen providers also participated in interviews. RESULTS We analyzed 1905 prescriptions. The overall prescribing error rate was 3.8 per 100 prescriptions (95% CI 2.8 to 5.1). Error rates were significantly lower 2 years after transition (p<0.001 compared to pre-implementation, 12 weeks and 1 year after transition). Rates of near misses remained unchanged. Providers positively appreciated most system refinements, particularly reduced alert firing. DISCUSSION Our study suggests that over time and with system refinements, use of a commercial EHR with advanced CDS can lead to low prescribing error rates, although more serious errors may require targeted interventions to eliminate them. Reducing alert firing frequency appears particularly important. Our results provide support for federal efforts promoting meaningful use of EHRs. CONCLUSIONS Ongoing error monitoring can allow CDS to be optimally tailored and help achieve maximal safety benefits. CLINICAL TRIALS REGISTRATION ClinicalTrials.gov, Identifier: NCT00603070.