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Communication failure: analysis of prescribers' use of an internal free-text field on electronic prescriptions.

ABSTRACT: Importance:Electronic prescribing promises to improve the safety and clarity of prescriptions. However, it also can introduce miscommunication between prescribers and pharmacists. There are situations where information that is meant to be sent to pharmacists is not sent to them, which has the potential for dangerous errors. Objective:To examine how frequently prescribers or administrative personnel put information intended for pharmacists in a field not sent to pharmacists, classify the type of information included, and assess the potential harm associated with these missed messages. Design, Setting, Participants:Medication record data from our legacy electronic health record were requested for ambulatory care patients seen at an academic medical center from January 1, 2000, to May 31, 2015 (20?123?881 records). From this database, 6?060?272 medication orders met our inclusion criteria. We analyzed a random sample of 10?000 medication orders with internal comments. Main Outcomes and Measures:Reviewers classified internal comments for intent. Comments intended for pharmacists were also sorted into descriptive categories and analyzed for the potential for patient harm. Results:We found that 11.7% of the prescriptions in our sample contained comments that were intended to be sent to pharmacists. Many comments contained information about the dose, route, or duration of the prescription (38.0%). Approximately a third of the comments intended for pharmacists contained information that had the potential for significant or severe harm if not communicated. Conclusion:We found undelivered comments that were clearly intended for pharmacists and contained important information for either pharmacists or patients. This poses a legitimate safety concern, as a portion of comments contained information that could have prevented severe or significant harm.

SUBMITTER: Ai A

PROVIDER: S-EPMC7647024 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Communication failure: analysis of prescribers' use of an internal free-text field on electronic prescriptions.

Ai Angela A Wong Adrian A Amato Mary M Wright Adam A

Journal of the American Medical Informatics Association : JAMIA 20180601 6

<h4>Importance</h4>Electronic prescribing promises to improve the safety and clarity of prescriptions. However, it also can introduce miscommunication between prescribers and pharmacists. There are situations where information that is meant to be sent to pharmacists is not sent to them, which has the potential for dangerous errors.<h4>Objective</h4>To examine how frequently prescribers or administrative personnel put information intended for pharmacists in a field not sent to pharmacists, classi ...[more]

PMID: 29474659

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Project description:BackgroundThe indication for prescribing a particular medication, or its reason for use (RFU) is a crucial piece of information for all those involved in the circle of care. Research has shown that sharing RFU information with physicians, pharmacists and patients improves patient safety and patient adherence, however RFU is rarely added on prescriptions by prescribers or on medication labels for patients to reference.MethodsQualitative interviews were conducted with 20 prescribers in Southern Ontario, Canada, to learn prescribers' current attitudes on the addition of RFU on prescriptions and medication labels. A trained interviewer used a semi-structured interview guide for each interview. The interviews explored how the sharing of RFU information would impact prescribers' workflows and practices. Interviews were recorded, transcribed and thematically coded.ResultsThe analysis yielded four main themes: Current Practice, Future Practice, Changing Culture, and Collaboration. Most of the prescribers interviewed do not currently add RFU to prescriptions. Prescribers were open to sharing RFU with colleagues via a regional database but wanted the ability to provide context for the prescribed medication within the system. Many prescribers were wary of the impact of adding RFU on their workflow but felt it could save time by avoiding clarifying questions from pharmacists. Increased interprofessional collaboration, increased patient understanding of prescribed medications, avoiding guesswork when determining indications and decreased misinterpretation regarding RFU were cited by most prescribers as benefits to including RFU information.ConclusionsPrescribers were generally open to sharing RFU and clearly identified the benefits to pharmacists and patients if added. Critically, they also identified benefits to their own practices. These results can be used to guide the implementation of future initiatives to promote the sharing of RFU in healthcare teams.

Project description:ImportanceThe receipt of overlapping opioid and benzodiazepine prescriptions is associated with increased overdose risk. It is unknown whether this increase in risk varies when overlapping prescriptions are written by multiple prescribers vs 1 prescriber.ObjectiveTo evaluate the association between receipt of overlapping opioid and benzodiazepine prescriptions from multiple prescribers and overdose risk.Design, setting, and participantsThis cohort study was conducted using 2017 to 2018 claims from the Optum deidentified Clinformatics Data Mart. Participants were patients with private insurance or Medicare Advantage aged 12 years or older with overlapping opioid and benzodiazepine prescriptions. Data were analyzed from March through November 2020.ExposuresFor each patient, person-days on which opioid and benzodiazepine prescriptions overlapped were identified. The exposure was whether these prescriptions were written by multiple prescribers vs 1 prescriber.Main outcomes and measuresThe outcome was a treated overdose, defined as the occurrence of 1 or more claims containing a diagnosis code for opioid or benzodiazepine poisoning on a person-day of opioid-benzodiazepine overlap. The association between exposure and outcome at the person-day level was estimated using logistic regression, controlling for opioid and benzodiazepine prescribing patterns, demographics, and comorbidities. The average marginal effect (AME) of the exposure, defined as the absolute difference in the probability of a treated overdose if all person-days of overlap involved prescriptions from multiple prescribers vs 1 prescriber, was calculated.ResultsAmong 529 053 patients, the mean (SD) age was 61.2 (15.6) years and 350 857 (66.3%) were female patients. Mean (SD) follow-up was 198.7 (249.8) days. During follow-up, overdose occurred on 1 or more person-days of opioid-benzodiazepine overlap for 2288 patients (0.4%, or 1 in 231 patients). There were 52 989 316 person-days of opioid-benzodiazepine overlap. Among 19 895 457 person-days (37.5%) involving prescriptions from multiple prescribers, there were 1390 overdoses (7.0 per 100 000 person-days), and among 33 093 859 person-days (62.5%) involving prescriptions from 1 prescriber, there were 1302 overdoses (3.9 per 100 000 person-days). Overdose risk was increased 1.8-fold (95% CI, 1.6-1.9) on person-days of overlap involving prescriptions from multiple prescribers vs 1 prescriber. The association between multiple prescribers and increased risk of overdose persisted in adjusted analyses (adjusted odds ratio, 1.20; 95% CI, 1.10-1.31; AME, 0.91 per 100 000 person-days of overlap; 95% CI, 0.46-1.37).Conclusions and relevanceThis study found that among patients already at increased risk of overdose owing to concurrent treatment with opioids and benzodiazepines, overdose risk was increased further when multiple prescribers were responsible for this treatment regimen compared with 1 prescriber. This increased risk was not fully accounted for by differences in prescribing patterns, demographics, or comorbidities. This finding suggests that other factors, such as poor care coordination, may be associated with the increase in risk.

Project description:BackgroundThe electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).MethodologyA manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis.Principal findingsAn adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.ConclusionStructured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties.

Dataset Information

Communication failure: analysis of prescribers' use of an internal free-text field on electronic prescriptions.

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Communication failure: analysis of prescribers' use of an internal free-text field on electronic prescriptions.

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