A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record.
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ABSTRACT: Objective
Incomplete and static reaction picklists in the allergy module led to free-text and missing entries that inhibit the clinical decision support intended to prevent adverse drug reactions. We developed a novel, data-driven, "dynamic" reaction picklist to improve allergy documentation in the electronic health record (EHR).Materials and methods
We split 3 decades of allergy entries in the EHR of a large Massachusetts healthcare system into development and validation datasets. We consolidated duplicate allergens and those with the same ingredients or allergen groups. We created a reaction value set via expert review of a previously developed value set and then applied natural language processing to reconcile reactions from structured and free-text entries. Three association rule-mining measures were used to develop a comprehensive reaction picklist dynamically ranked by allergen. The dynamic picklist was assessed using recall at top k suggested reactions, comparing performance to the static picklist.Results
The modified reaction value set contained 490 reaction concepts. Among 4 234 327 allergy entries collected, 7463 unique consolidated allergens and 469 unique reactions were identified. Of the 3 dynamic reaction picklists developed, the 1 with the optimal ranking achieved recalls of 0.632, 0.763, and 0.822 at the top 5, 10, and 15, respectively, significantly outperforming the static reaction picklist ranked by reaction frequency.Conclusion
The dynamic reaction picklist developed using EHR data and a statistical measure was superior to the static picklist and suggested proper reactions for allergy documentation. Further studies might evaluate the usability and impact on allergy documentation in the EHR.
SUBMITTER: Wang L
PROVIDER: S-EPMC7309236 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesDocumentation of allergies in a coded, non-free-text format in the electronic health record (EHR) triggers clinical decision support to prevent adverse events. Health system-wide patient safety initiatives to improve EHR allergy documentation by specifically decreasing free-text allergy entries have not been reported. The goal of this initiative was to systematically reduce free-text allergen entries in the EHR allergy module.MethodsWe assessed free-text allergy entries in a commercial EHR used at a multihospital integrated health care system in the greater Boston area. Using both manual and automated methods, a multidisciplinary consensus group prioritized high-risk and frequently used free-text allergens for conversion to coded entries, added new allergen entries, and deleted duplicate allergen entries. Environmental allergies were moved to the patient problem list.ResultsWe identified 242,330 free-text entries, which included a variety of environmental allergies (42%), food allergies (18%), contrast media allergies (13%), "no known allergy" (12%), drug allergies (2%), and "no contrast allergy" (2%). Most free-text entries were entered by medical assistants in ambulatory settings (34%) and registered nurses in perioperative settings (20%). We remediated a total of 52,206 free-text entries with automated methods and 79,578 free-text entries with manual methods.ConclusionsThrough this multidisciplinary intervention, we identified and remediated 131,784 free-text entries in our EHR to improve clinical decision support and patient safety. Additional strategies are required to completely eliminate free-text allergy entry, and establish systematic, consistent, and safe guidelines for documenting allergies.
| S-EPMC7704710 | biostudies-literature
Project description:ObjectiveTo assess novel dynamic reaction picklists for improving allergy reaction documentation compared to a static reaction picklist.Materials and methodsWe developed three web-based user interfaces (UIs) mimicking the Mass General Brigham's EHR allergy module: the first and second UIs (i.e., UI-1D, UI-2D) implemented two dynamic reaction picklists with different ranking algorithms and the third UI (UI-3S) implemented a static reaction picklist like the one used in the current EHR. We recruited 18 clinicians to perform allergy entry for 10 test cases each via UI-1D and UI-3S, and another 18 clinicians via UI-2D and UI-3S. Primary measures were the number of free-text entries and time to complete the allergy entry. Clinicians were also interviewed using 30 questions before and after the data entry.Results and discussionsAmong 36 clinicians, less than half were satisfied with the current EHR reaction picklists, due to their incomprehensiveness, inefficiency, and lack of intuitiveness. The clinicians used significantly fewer free-text entries when using UI-1D or UI-2D compared to UI-3S (p < 0.05). The clinicians used on average 51 s (15 %) less time via UI-1D and 50 s (16 %) less time via UI-2D in completing the allergy entries versus UI-3S, and there was not a statistically significant difference in documentation time for either group between the dynamic and static UIs. Overall, 15-17 (83-94 %) clinicians rated UI-1D and 13-15 (72-83 %) clinicians rated UI-2D as efficient, easy to use, and useful, while less than half rated the same for UI-3S. Most clinicians reported that the dynamic reaction picklists always or often suggested appropriate reactions (n = 30, 83 %) and would decrease the free-text entries (n = 26, 72 %); nearly all preferred the dynamic picklist over the static picklist (n = 32, 89 %).ConclusionWe found that dynamic reaction picklists significantly reduced the number of free-text entries and could reduce the time for allergy documentation by 15%. Clinicians preferred the dynamic reaction picklist over the static picklist.
| S-EPMC10167939 | biostudies-literature
Project description:BackgroundDetection, monitoring and treatment of adverse drug reactions (ADRs) are paramount to patient safety. The use of a comprehensive electronic health record (EHR) system has the potential to address inadequacies in ADR documentation and to facilitate ADR reporting to health agencies. However, effective methods to maintain the quality of documented ADRs within an EHR have not been well studied.ObjectiveTo evaluate the accuracy and effectiveness of ADR documentation transfer throughout the implementation of a comprehensive EHR system.MethodsRetrospective analysis of ADR documentation at a tertiary care pediatric hospital between January 2013 and June 2014. ADRs documented in the newly implemented ambulatory EHR, pharmacy system and hybrid health record system were extracted. Documentation inconsistencies and processes for managing ADR documentation within the EHR were reviewed.ResultsA total of 115 patients with 260 unique ADRs were identified. Only 155 (60 %) of the identified ADRs were found in the ambulatory EHR system. The remaining 105 ADRs (40 %) were missing from the EHR when it was compared with the other systems. Seventy-two patients (63 %) returned for a follow-up visit, and each had their ADR documentation reviewed in the ambulatory EHR. Following the visit, 44 % of these ambulatory EHR records still included incorrect information.ConclusionsWe identified discrepancies in ADR documentation within hospital systems, which need to be addressed as healthcare institutions transition to EHRs. Processes related to the transfer of ADR information into the EHR should be clearly defined. To improve the quality of ADR documentation, steps to force complete and continual ADR verification should be introduced at early stages of implementation of a new EHR, and all responsible providers should play a role.
| S-EPMC4914540 | biostudies-literature
Project description:The use of electronic cigarettes (e-cigarettes) can affect patient health and clinical care. However, the current documentation of e-cigarette use in the electronic health records (EHR) is inconsistent. This report outlines how the ambulatory clinical practices of a large U.S. hospital system optimized its electronic health records (EHR) framework to better record e-cigarettes used by patients. The new EHR section for e-cigarette information was implemented for outpatient appointments. During a 30-week evaluation period post-implementation, 638,804 patients (12 yrs and older) completed ambulatory appointments within the health system; of these, the new section contained e-cigarette use information for 37,906 (6%) patients. Among these patients, 1005 (2.7%) were identified as current e-cigarette users (current every day or current some day e-cigarette use), 941 (2.5%) were reported as former e-cigarette users, and 35,960 (94%) had never used e-cigarettes. A separate EHR section to document e-cigarette use is feasible within existing clinical practice models. Utilization of the new section was modest in routine clinical practice, indicating the need for more intensive implementation strategies that emphasize the health effects of e-cigarette use, and how consistent ascertainment could improve clinical practice.
| S-EPMC7460036 | biostudies-literature
Project description:Physicians who more intensively interact with electronic health records (EHRs) through their documentation style may pay greater attention to coded fields and clinical decision support and thus may deliver higher quality care. We measured the quality of care of physicians who used three predominating EHR documentation styles: dictation, structured documentation, and free text.We conducted a retrospective analysis of visits by patients with coronary artery disease and diabetes to the Partners Primary Care Practice Based Research Network. The main outcome measures were 15 EHR-based coronary artery disease and diabetes measures assessed 30 days after primary care visits.During the 9-month study period, 7000 coronary artery disease and diabetes patients made 18?569 visits to 234 primary care physicians of whom 20 (9%) predominantly dictated their notes, 68 (29%) predominantly used structured documentation, and 146 (62%) predominantly typed free text notes. In multivariable modeling adjusted for clustering by patient and physician, quality of care appeared significantly worse for dictators than for physicians using the other two documentation styles on three of 15 measures (antiplatelet medication, tobacco use documentation, and diabetic eye exam); better for structured documenters for three measures (blood pressure documentation, body mass index documentation, and diabetic foot exam); and better for free text documenters on one measure (influenza vaccination). There was no measure for which dictators had higher quality of care than physicians using the other two documentation styles.EHR-assessed quality is necessarily documentation-dependent, but physicians who dictated their notes appeared to have worse quality of care than physicians who used structured EHR documentation.ClinicalTrials.gov Identifier: NCT00235040.
| S-EPMC3534457 | biostudies-literature
Project description:ImportanceElectronic health records are a potentially valuable source of information for identifying patients with opioid use disorder (OUD).ObjectiveTo evaluate whether proxy measures from electronic health record data can be used reliably to identify patients with probable OUD based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria.Design, setting, and participantsThis retrospective cross-sectional study analyzed individuals within the Geisinger health system who were prescribed opioids between December 31, 2000, and May 31, 2017, using a mixed-methods approach. The cohort was identified from 16 253 patients enrolled in a contract-based, Geisinger-specific medication monitoring program (GMMP) for opioid use, including patients who maintained or violated contract terms, as well as a demographically matched control group of 16 253 patients who were prescribed opioids but not enrolled in the GMMP. Substance use diagnoses and psychiatric comorbidities were assessed using automated electronic health record summaries. A manual medical record review procedure using DSM-5 criteria for OUD was completed for a subset of patients. The analysis was conducted beginning from June 5, 2017, until May 29, 2020.Main outcomes and measuresThe primary outcome was the prevalence of OUD as defined by proxy measures for DSM-5 criteria for OUD as well as the prevalence of comorbidities among patients prescribed opioids within an integrated health system.ResultsAmong the 16 253 patients enrolled in the GMMP (9309 women [57%]; mean [SD] age, 52 [14] years), OUD diagnoses as defined by diagnostic codes were present at a much lower rate than expected (291 [2%]), indicating the necessity for alternative diagnostic strategies. The DSM-5 criteria for OUD can be assessed using manual medical record review; a manual review of 200 patients in the GMMP and 200 control patients identifed a larger percentage of patients with probable moderate to severe OUD (GMMP, 145 of 200 [73%]; and control, 27 of 200 [14%]) compared with the prevalence of OUD assessed using diagnostic codes.Conclusions and relevanceThese results suggest that patients with OUD may be identified using information available in the electronic health record, even when diagnostic codes do not reflect this diagnosis. Furthermore, the study demonstrates the utility of coding for DSM-5 criteria from medical records to generate a quantitative DSM-5 score that is associated with OUD severity.
| S-EPMC7489858 | biostudies-literature
Project description:Although complete and accurate clinical records do not guarantee the provision of excellent dental care, they do provide an opportunity to evaluate the quality of care provided. However, a lack of universally accepted documentation standards, incomplete record-keeping practices, and unfriendly electronic health care record (EHR) user interfaces are factors that have allowed for persistent poor dental patient record keeping.Using 2 different methods-a validated survey, and a 2-round Delphi process-involving 2 appropriately different sets of participants, we explored what a dental clinical record should contain and the frequency of update of each clinical entry.For both the closed-ended survey questions and the open-ended Delphi process questions, respondents had a significant degree of agreement on the "clinical entry" components of an adequate clinical record. There was, however, variance on how frequently each of those clinical entries should be updated.Dental providers agree that complete and accurate record keeping is essential and that items such as histories, examination findings, diagnosis, radiographs, treatment plans, consents, and clinic notes should be documented. There, however, does not seem to be universal agreement how frequently such items should be recorded.As the dental profession moves towards prevalent use of electronic health care records, the issue of standardization and interoperability becomes ever more pressing. Settling issues of standardization, including record documentation, must begin with guideline-creating dental professional bodies, who need to clearly define and disseminate what these standards should be and everyday dentists who will ultimately ensure that these standards are met and kept.
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Project description:ObjectiveUsing Failure Mode and Effects Analysis (FMEA) as an example quality improvement approach, our objective was to evaluate whether secondary use of orders, forms, and notes recorded by the electronic health record (EHR) during daily practice can enhance the accuracy of process maps used to guide improvement. We examined discrepancies between expected and observed activities and individuals involved in a high-risk process and devised diagnostic measures for understanding discrepancies that may be used to inform quality improvement planning.MethodsInpatient cardiology unit staff developed a process map of discharge from the unit. We matched activities and providers identified on the process map to EHR data. Using four diagnostic measures, we analyzed discrepancies between expectation and observation.ResultsEHR data showed that 35% of activities were completed by unexpected providers, including providers from 12 categories not identified as part of the discharge workflow. The EHR also revealed sub-components of process activities not identified on the process map. Additional information from the EHR was used to revise the process map and show differences between expectation and observation.ConclusionFindings suggest EHR data may reveal gaps in process maps used for quality improvement and identify characteristics about workflow activities that can identify perspectives for inclusion in an FMEA. Organizations with access to EHR data may be able to leverage clinical documentation to enhance process maps used for quality improvement. While focused on FMEA protocols, findings from this study may be applicable to other quality activities that require process maps.
| S-EPMC5391722 | biostudies-literature
Project description:ObjectiveTo compare the efficiency and safety of using speech recognition (SR) assisted clinical documentation within an electronic health record (EHR) system with use of keyboard and mouse (KBM).MethodsThirty-five emergency department clinicians undertook randomly allocated clinical documentation tasks using KBM or SR on a commercial EHR system. Tasks were simple or complex, and with or without interruption. Outcome measures included task completion times and observed errors. Errors were classed by their potential for patient harm. Error causes were classified as due to IT system/system integration, user interaction, comprehension, or as typographical. User-related errors could be by either omission or commission.ResultsMean task completion times were 18.11% slower overall when using SR compared to KBM (P = .001), 16.95% slower for simple tasks (P = .050), and 18.40% slower for complex tasks (P = .009). Increased errors were observed with use of SR (KBM 32, SR 138) for both simple (KBM 9, SR 75; P < 0.001) and complex (KBM 23, SR 63; P < 0.001) tasks. Interruptions did not significantly affect task completion times or error rates for either modality.DiscussionFor clinical documentation, SR was slower and increased the risk of documentation errors, including errors with the potential to cause clinical harm compared to KBM. Some of the observed increase in errors may be due to suboptimal SR to EHR integration and workflow.ConclusionUse of SR to drive interactive clinical documentation in the EHR requires careful evaluation. Current generation implementations may require significant development before they are safe and effective. Improving system integration and workflow, as well as SR accuracy and user-focused error correction strategies, may improve SR performance.
| S-EPMC7651984 | biostudies-literature
Project description:PurposeWe sought to evaluate sexual history documentation and corresponding Chlamydia trachomatis screening practices across a large pediatric primary care network in the context of patient and clinic characteristics.MethodsDemographic, chlamydia screening, and provider note data were collected via electronic health record and manual chart audit for females aged 15-19 years attending annual well-adolescent visits, from February 1 to 28, 2019. Inductive qualitative textual analysis evaluated sexual history documentation as informative (containing clear indication of patient as sexually active or not) or noninformative and identified documentation subtypes. We examined patient and clinic characteristics by sexual history documentation type (informative or noninformative) and chlamydia screening status and documentation subtypes across clinic types using chi-square and Fisher's exact tests. A multilevel logistic regression model considering clinic-specific random effects evaluated predictors of informative sexual history documentation.ResultsChart notes were examined for 1,062 patients across 31 unique clinics. Only 34.7% of chart notes were found to have informative sexual history documentation. Older patients (odds ratio: 1.51, 95% confidence interval: 0.99-2.31) and patients seen at clinics receiving U.S. Department of Health and Human Services Title-X funding (odds ratio: 11.05, 95% confidence interval: 1.34-90.86) had higher rates of informative documentation. The overall Chlamydia screening rate was 13.1%.ConclusionSexual history documentation varied widely across clinics, and the majority of chart notes were found to have noninformative documentation. Understanding and addressing barriers to informative sexual history documentation and comprehensive sexual health care is fundamental to improve adolescent sexual health outcomes, particularly given recently enacted federal electronic health record transparency policies.
| S-EPMC8860853 | biostudies-literature