An unintended consequence of electronic prescriptions: Prevalence and impact of internal discrepancies

Harvard Medical School, Boston, Massachusetts, USA.
Journal of the American Medical Informatics Association (Impact Factor: 3.5). 07/2010; 17(4):472-6. DOI: 10.1136/jamia.2010.003335
Source: PubMed


Many e-prescribing systems allow for both structured and free-text fields in prescriptions, making possible internal discrepancies. This study reviewed 2914 electronic prescriptions that contained free-text fields. Internal discrepancies were found in 16.1% of the prescriptions. Most (83.8%) of the discrepancies could potentially lead to adverse events and many (16.8%) to severe adverse events, involving a hospital admission or death. Discrepancies in doses, routes or complex regimens were most likely to have a potential for a severe event (p=0.0001). Discrepancies between structured and free-text fields in electronic prescriptions are common and can cause patient harm. Improvements in electronic medical record design are necessary to minimize the risk of discrepancies and resulting adverse events.

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Available from: Jonathan S Einbinder
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    • "From the studies assessed in this review, it appears that observational studies give us most insight into potential causes of adverse events or potential for patient harm. User-interface, faulty programming and erroneous information in the CDSS application were problems that lead to erroneous prescribing [67,74]. Adverse events were found to be concordant with non-adherence to CDSS suggestions [77]. "
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    ABSTRACT: The objective was to find evidence to substantiate assertions that electronic applications for medication management in ambulatory care (electronic prescribing, clinical decision support (CDSS), electronic health record, and computer generated paper prescriptions), while intended to reduce prescribing errors, can themselves result in errors that might harm patients or increase risks to patient safety. Because a scoping search for adverse events in randomized controlled trials (RCTs) yielded few relevant results, we systematically searched nine databases, including MEDLINE, EMBASE, and The Cochrane Database of Systematic Reviews for systematic reviews and studies of a wide variety of designs that reported on implementation of the interventions. Studies that had safety and adverse events as outcomes, monitored for them, reported anecdotally adverse events or other events that might indicate a threat to patient safety were included. We found no systematic reviews that examined adverse events or patient harm caused by organizational interventions. Of the 4056 titles and abstracts screened, 176 full-text articles were assessed for inclusion. Sixty-one studies with appropriate interventions, settings and participants but without patient safety, adverse event outcomes or monitoring for risks were excluded, along with 77 other non-eligible studies. Eighteen randomised controlled trials (RCTs), 5 non-randomised controlled trials (non-R, CTs) and 15 observational studies were included. The most common electronic intervention studied was CDSS and the most frequent clinical area was cardio-vascular, including anti-coagulants. No RCTS or non-R,CTS reported adverse event. Adverse events reported in observational studies occurred less frequently after implementation of CDSS. One RCT and one observational study reported an increase in problematic prescriptions with electronic prescribing CONCLUSIONS: The safety implications of electronic medication management in ambulatory care have not been established with results from studies found in this systematic review. Only a minority of studies that investigated these interventions included threats to patients' safety as outcomes or monitored for adverse events. It is therefore not surprising that we found little evidence to substantiate fears of new risks to patient safety with their implementation. More research is needed to focus on the draw-backs and negative outcomes that implementation of these interventions might introduce.
    Full-text · Article · Dec 2013 · BMC Medical Informatics and Decision Making
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    • "These studies offer limited evidence on how the electronic medication chart can support the collaborative process of medication management that spans multiple organisations [72] [77] [78]. Recent studies in healthcare contexts like hospitals and ambulatory care have identified unintended adverse consequences and a high incidence of errors related to electronic systems [79] [80] [81]. The prime reasons for adverse effects of electronic systems include their lack of alignment with the collaborative team based processes they intend to support [80] [82] [83]. "
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    Full-text · Article · Sep 2012 · International Journal of Medical Informatics
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    ABSTRACT: Health plans have implemented tiered copayment systems to incentivize members to use less expensive medications. However, members need drug price information to make comparisons among therapeutic alternatives. Many health plans and pharmacy benefit management companies have implemented online prescription drug price comparison tools to provide such information. There has been little published evaluation of these tools. To evaluate use of an online price comparison tool- MyPharmacyTools (MPT)- by the measures of (a) the extent to which the tool was used, (b) changes in use over the first year after implementation, and (c) the types of members who were most likely to use the tool. Data were provided by a 500,000-member integrated health plan with approximately 156,250 enrolled families. The sample included only families with continuous eligibility for all members from July 1, 2006, through June 30, 2008; use of 1 of 7 common copayment structures; and use of the pharmacy benefit in every quarter of the study period. Data collected on each member, using pharmacy claims for the time period July 1, 2007, through June 30, 2008, included annual drug costs (total, out-of-pocket, plan-paid, and mail order) and number of unique drugs and unique generic drugs taken during the third quarter of 2007. Data collected also included whether the member had each of several selected chronic diseases (as inferred from drug claims for the third quarter of 2007) and demographics. Age, gender, and family size were taken from eligibility files. Other demographic data were imputed to members from the demographics of the ZIP code in which they resided. MPT was made available to members on July 1, 2007. Use of MPT was measured as the number of times members logged into the site for each quarter during the subsequent year. Statistical analyses were conducted at the family rather than at the individual level, and families were defined as users if any family member used MPT at least once during the year. Between-group comparisons were evaluated with t-tests, Pearson chi-square tests, and analyses of variance. Data were analyzed for 8,909 families composed of 28,537 health plan members, of which 464 (5.2%) families used MPT at least once between July 2007 and June 2008. A total of 141 families used MPT in the first quarter it was available, 170 families used it in the second quarter, 185 families in the third quarter, and 182 families during the fourth quarter. Users had significantly higher mean [SD] total drug costs ($4,477 [$9,647] vs. $2,848 [$3,473], P < 0.001) and used significantly more unique drug products (7.7 [5.7] vs. 5.9 [4.5], P < 0.001) and unique generic drug products (5.0 [3.9] vs. 3.9 [3.2], P < 0.001) than did nonusers. Users were significantly more likely than nonusers to use drugs for behavioral diseases (47.0% vs. 39.7%, P = 0.002), hypercholesterolemia (35.8% vs. 27.0%, P < 0.001), gastric disorders (32.8% vs. 23.0%, P < 0.001), diabetes (18.3% vs. 12.8%, P < 0.001), epilepsy (21.1% vs. 10.6%, P < 0.001), cardiovascular problems (48.3% vs. 37.5%, P < 0.001), and asthma (14.0% vs. 10.7%, P = 0.025). Families that used MPT were less likely to have a female subscriber than were nonusers (39.7% vs. 49.0%, P < 0.001). Otherwise, here were no statistically significant demographic differences between users and nonusers. Families using MPT in more quarters of the year had higher out-of-pocket (P < 0.001) and mail order drug costs (P < 0.001), took a larger number of drugs (P = 0.003) and generic drugs (P = 0.019), were more likely to use drugs for diabetes (P = 0.049) and cardiovascular disease (P = 0.013), and used drugs for a greater number of chronic diseases (P = 0.049), compared with less frequent MPT users. About 5% of families in a sample from a large integrated health plan used an online prescription drug cost comparison tool during the first year it was available. Use increased over the year. Users were more likely to have several chronic diseases, took more prescription drugs, and had higher drug costs than nonusers. Further, users with more chronic diseases and more prescriptions were more likely to use the tool consistently throughout the year. These results indicate that the tool was successful in reaching health plan members who could most benefit from comparative prescription drug price information.
    Full-text · Article · Nov 2010 · Journal of managed care pharmacy: JMCP
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