Accuracy of electronically reported "meaningful use" clinical quality measures: a cross-sectional study.

BACKGROUND: The federal Electronic Health Record Incentive Program requires electronic reporting of quality from electronic health records, beginning in 2014. Whether electronic reports of quality are accurate is unclear. OBJECTIVE: To measure the accuracy of electronic reporting compared with manual review. DESIGN: Cross-sectional study. SETTING: A federally qualified health center with a commercially available electronic health record. PATIENTS: All adult patients eligible in 2008 for 12 quality measures (using 8 unique denominators) were identified electronically. One hundred fifty patients were randomly sampled per denominator, yielding 1154 unique patients. MEASUREMENTS: Receipt of recommended care, assessed by both electronic reporting and manual review. Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and absolute rates of recommended care were measured. RESULTS: Sensitivity of electronic reporting ranged from 46% to 98% per measure. Specificity ranged from 62% to 97%, positive predictive value from 57% to 97%, and negative predictive value from 32% to 99%. Positive likelihood ratios ranged from 2.34 to 24.25 and negative likelihood ratios from 0.02 to 0.61. Differences between electronic reporting and manual review were statistically significant for 3 measures: Electronic reporting underestimated the absolute rate of recommended care for 2 measures (appropriate asthma medication [38% vs. 77%; P < 0.001] and pneumococcal vaccination [27% vs. 48%; P < 0.001]) and overestimated care for 1 measure (cholesterol control in patients with diabetes [57% vs. 37%; P = 0.001]). LIMITATION: This study addresses the accuracy of the measure numerator only. CONCLUSION: Wide measure-by-measure variation in accuracy threatens the validity of electronic reporting. If variation is not addressed, financial incentives intended to reward high quality may not be given to the highest-quality providers. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

The effects of electronic prescribing by community-based providers on ambulatory medication safety.

BACKGROUND: US federal policies are incentivizing use of electronic prescribing (e-prescribing) to improve safety. However, little is known about e-prescribing's actual impact on medication safety over time. A study was conducted to assess the effect of implementing a commercial electronic health record (EHR) with e-prescribing on rates and types of prescribing errors. Understanding safety effects from e-prescribing will be important as providers increasingly e-prescribe. METHODS: Prescriptions written by 20 community-based primary care providers in the Hudson Valley region of New York from November 2008 to November 2009 were retrospectively studied. All providers adopted a commercial EHR with robust clinical decision support and extensive technical support to aid in prescribing. Errors were identified by standardized prescription and chart review. RESULTS: Some 1,629 prescriptions were analyzed at three months postimplementation, and 1,738 prescriptions were analyzed at one year postimplementation. Use of e-prescribing resulted in relatively low error rates (6.0 errors per 100 prescriptions). These rates were sustained over time but without further improvement (6.0 versus 4.5 errors per 100 prescriptions, p = .15). Antibiotics were the class of medications most frequently involved (12.7% of overall errors), and direction errors were most common (24% of errors). CONCLUSIONS: This study is the first, as far as known, to quantitatively evaluate prescribing errors early after EHR implementation and after sustained use among community-based primary care providers. Relatively low rates of errors with e-prescribing were found early and after prolonged use. Extensive support for providers before, during, and after implementation may mitigate potential safety threats from implementation of an EHR system and result in sustained safety benefits over the long-term.

Ambulatory prescribing errors among community-based providers in two states.

OBJECTIVE: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSIONS: Further characterizing prescribing errors of community-based providers may inform strategies to improve ambulatory medication safety, especially e-prescribing. TRIAL REGISTRATION NUMBER: http://www.clinicaltrials.gov, NCT00225576.

Electronic prescribing within an electronic health record reduces ambulatory prescribing errors.

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.

Electronic prescribing improves medication safety in community-based office practices.

BACKGROUND: Although electronic prescribing (e-prescribing) holds promise for preventing prescription errors in the ambulatory setting, research on its effectiveness is inconclusive. OBJECTIVE: To assess the impact of a stand-alone e-prescribing system on the rates and types of ambulatory prescribing errors. DESIGN, PARTICIPANTS: Prospective, 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. INTERVENTION: Use 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 MEASURES: Prescribing errors were identified by a standardized prescription and chart review. KEY RESULTS: We 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). CONCLUSIONS: Prescribing 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 REGISTRATION: ClinicalTrials.gov, Taconic Health Information Network and Community (THINC), NCT00225563, http://clinicaltrials.gov/ct2/show/NCT00225563?term=Kaushal&rank=6 .