Frank Y. Chang

Rising drug allergy alert overrides in electronic health records: an observational retrospective study of a decade of experience

OBJECTIVE There have been growing concerns about the impact of drug allergy alerts on patient safety and provider alert fatigue. The authors aimed to explore the common drug allergy alerts over the last 10 years and the reasons why providers tend to override these alerts. DESIGN Retrospective observational cross-sectional study (2004-2013). MATERIALS AND METHODS Drug allergy alert data (n = 611,192) were collected from two large academic hospitals in Boston, MA (USA). RESULTS Overall, the authors found an increase in the rate of drug allergy alert overrides, from 83.3% in 2004 to 87.6% in 2013 (P < .001). Alarmingly, alerts for immune mediated and life threatening reactions with definite allergen and prescribed medication matches were overridden 72.8% and 74.1% of the time, respectively. However, providers were less likely to override these alerts compared to possible (cross-sensitivity) or probable (allergen group) matches (P < .001). The most common drug allergy alerts were triggered by allergies to narcotics (48%) and other analgesics (6%), antibiotics (10%), and statins (2%). Only slightly more than one-third of the reactions (34.2%) were potentially immune mediated. Finally, more than half of the overrides reasons pointed to irrelevant alerts (i.e., patient has tolerated the medication before, 50.9%) and providers were significantly more likely to override repeated alerts (89.7%) rather than first time alerts (77.4%, P < .001). DISCUSSION AND CONCLUSIONS These findings underline the urgent need for more efforts to provide more accurate and relevant drug allergy alerts to help reduce alert override rates and improve alert fatigue.

A web-based, patient-centered toolkit to engage patients and caregivers in the acute care setting: a preliminary evaluation

We implemented a web-based, patient-centered toolkit that engages patients/caregivers in the hospital plan of care by facilitating education and patient-provider communication. Of the 585 eligible patients approached on medical intensive care and oncology units, 239 were enrolled (119 patients, 120 caregivers). The most common reason for not approaching the patient was our inability to identify a health care proxy when a patient was incapacitated. Significantly more caregivers were enrolled in medical intensive care units compared with oncology units (75% vs 32%; P < .01). Of the 239 patient/caregivers, 158 (66%) and 97 (41%) inputted a daily and overall goal, respectively. Use of educational content was highest for medications and test results and infrequent for problems. The most common clinical theme identified in 291 messages sent by 158 patients/caregivers was health concerns, needs, preferences, or questions (19%, 55 of 291). The average system usability scores and satisfaction ratings of a sample of surveyed enrollees were favorable. From analysis of feedback, we identified barriers to adoption and outlined strategies to promote use.

Building and Testing a Patient-Centric Electronic Bedside Communication Center

In this article, the authors describe the development and pilot testing of an electronic bedside communication center (eBCC) prototype to improve access to health information for hospitalized adults and their family caregivers. Focus groups were used to identify improvements for the initial eBCC prototype developed by the research team. Face-to-face bedside interviews and questions were presented while patients used the eBCC for usability testing to drive further development. Qualitative methods within an iterative, participatory approach supported the development of an eBCC prototype that was considered both easy to use and helpful for accessing tailored patient information during an inpatient hospitalization to receive acute care.

Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach

OBJECTIVE To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. METHODS We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. RESULTS Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. CONCLUSION The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping.

Prospective Evaluation of a Multifaceted Intervention to Improve Outcomes in Intensive Care: The Promoting Respect and Ongoing Safety Through Patient Engagement Communication and Technology Study*

Objectives: Studies comprehensively assessing interventions to improve team communication and to engage patients and care partners in ICUs are lacking. This study examines the effectiveness of a patient-centered care and engagement program in the medical ICU. Design: Prospective intervention study. Setting: Medical ICUs at large tertiary care center. Patients: Two thousand one hundred five patient admissions (1,030 before and 1,075 during the intervention) from July 2013 to May 2014 and July 2014 to May 2015. Interventions: Structured patient-centered care and engagement training program and web-based technology including ICU safety checklist, tools to develop shared care plan, and messaging platform. Patient and care partner access to online portal to view health information, participate in the care plan, and communicate with providers. Measurements and Main Results: Primary outcome was aggregate adverse event rate. Secondary outcomes included patient and care partner satisfaction, care plan concordance, and resource utilization. We included 2,105 patient admissions, (1,030 baseline and 1,075 during intervention periods). The aggregate rate of adverse events fell 29%, from 59.0 per 1,000 patient days (95% CI, 51.8–67.2) to 41.9 per 1,000 patient days (95% CI, 36.3–48.3; p < 0.001), during the intervention period. Satisfaction improved markedly from an overall hospital rating of 71.8 (95% CI, 61.1–82.6) to 93.3 (95% CI, 88.2–98.4; p < 0.001) for patients and from 84.3 (95% CI, 81.3–87.3) to 90.0 (95% CI, 88.1–91.9; p < 0.001) for care partners. No change in care plan concordance or resource utilization. Conclusions: Implementation of a structured team communication and patient engagement program in the ICU was associated with a reduction in adverse events and improved patient and care partner satisfaction.

Tailored Prevention of Inpatient Falls: Development and Usability Testing of the Fall TIPS Toolkit

Patient falls and fall-related injuries are serious problems in hospitals. The Fall TIPS application aims to prevent patient falls by translating routine nursing fall risk assessment into a decision support intervention that communicates fall risk status and creates a tailored evidence-based plan of care that is accessible to the care team, patients, and family members. In our design and implementation of the Fall TIPS toolkit, we used the Spiral Software Development Life Cycle model. Three output tools available to be generated from the toolkit are bed poster, plan of care, and patient education handout. A preliminary design of the application was based on initial requirements defined by project leaders and informed by focus groups with end users. Preliminary design partially simulated the paper version of the Morse Fall Scale currently used in hospitals involved in the research study. Strengths and weaknesses of the first prototype were identified by heuristic evaluation. Usability testing was performed at sites where research study is implemented. Suggestions mentioned by end users participating in usability studies were either directly incorporated into the toolkit and output tools, were slightly modified, or will be addressed during training. The next step is implementation of the fall prevention toolkit on the pilot testing units.

A value set for documenting adverse reactions in electronic health records

Objective To develop a comprehensive value set for documenting and encoding adverse reactions in the allergy module of an electronic health record. Materials and Methods We analyzed 2 471 004 adverse reactions stored in Partners Healthcares Enterprise-wide Allergy Repository (PEAR) of 2.7 million patients. Using the Medical Text Extraction, Reasoning, and Mapping System, we processed both structured and free-text reaction entries and mapped them to Systematized Nomenclature of Medicine - Clinical Terms. We calculated the frequencies of reaction concepts, including rare, severe, and hypersensitivity reactions. We compared PEAR concepts to a Federal Health Information Modeling and Standards value set and University of Nebraska Medical Center data, and then created an integrated value set. Results We identified 787 reaction concepts in PEAR. Frequently reported reactions included: rash (14.0%), hives (8.2%), gastrointestinal irritation (5.5%), itching (3.2%), and anaphylaxis (2.5%). We identified an additional 320 concepts from Federal Health Information Modeling and Standards and the University of Nebraska Medical Center to resolve gaps due to missing and partial matches when comparing these external resources to PEAR. This yielded 1106 concepts in our final integrated value set. The presence of rare, severe, and hypersensitivity reactions was limited in both external datasets. Hypersensitivity reactions represented roughly 20% of the reactions within our data. Discussion We developed a value set for encoding adverse reactions using a large dataset from one health system, enriched by reactions from 2 large external resources. This integrated value set includes clinically important severe and hypersensitivity reactions. Conclusion This work contributes a value set, harmonized with existing data, to improve the consistency and accuracy of reaction documentation in electronic health records, providing the necessary building blocks for more intelligent clinical decision support for allergies and adverse reactions.