Accuracy of Noninvasive Blood Pressure Monitoring in Critically Ill Adults.

Background: Blood pressure (BP) is routinely invasively monitored by an arterial catheter in the intensive care unit (ICU). However, the available data comparing the accuracy of noninvasive methods to arterial catheters for measuring BP in the ICU are limited by small numbers and diverse methodologies. Purpose: To determine agreement between invasive arterial blood pressure monitoring (IABP) and noninvasive blood pressure (NIBP) in critically ill patients. Methods: This was a single center, observational study of critical ill adults in a tertiary care facility evaluating agreement (≤10% difference) between simultaneously measured IABP and NIBP. We measured clinical features at time of BP measurement inclusive of patient demographics, laboratory data, severity of illness, specific interventions (mechanical ventilation and dialysis), and vasopressor dose to identify particular clinical scenarios in which measurement agreement is more or less likely. Results: Of the 1852 critically ill adults with simultaneous IABP and NIBP readings, there was a median difference of 6 mm Hg in mean arterial pressure (MAP), interquartile range (1-12), P < .01. A logistic regression analysis identified 5 independent predictors of measurement discrepancy: increasing doses of norepinephrine (adjusted odds ratio [aOR] 1.10 [95% confidence interval, CI 1.08-1.12] P = .03 for every change in 5 µg/min), lower MAP value (aOR 0.98 [0.98-0.99] P < .01 for every change in 1 mm Hg), higher body mass index (aOR 1.04 [1.01-1.09] P = .01 for an increase in 1), increased patient age (aOR 1.31 [1.30-1.37] P < .01 for every 10 years), and radial arterial line location (aOR 1.74 [1.16-2.47] P = .04). Conclusions: There was broad agreement between IABP and NIBP in critically ill patients over a range of BPs and severity of illness. Several variables are associated with measurement discrepancy; however, their predictive capacity is modest. This may guide future study into which patients may specifically benefit from an arterial catheter.

Proteomic Portraits Reveal Evolutionarily Conserved and Divergent Responses to Spinal Cord Injury.

Despite the emergence of promising therapeutic approaches in preclinical studies, the failure of large-scale clinical trials leaves clinicians without effective treatments for acute spinal cord injury (SCI). These trials are hindered by their reliance on detailed neurological examinations to establish outcomes, which inflate the time and resources required for completion. Moreover, therapeutic development takes place in animal models whose relevance to human injury remains unclear. Here, we address these challenges through targeted proteomic analyses of cerebrospinal fluid and serum samples from 111 patients with acute SCI and, in parallel, a large animal (porcine) model of SCI. We develop protein biomarkers of injury severity and recovery, including a prognostic model of neurological improvement at 6 months with an area under the receiver operating characteristic curve of 0.91, and validate these in an independent cohort. Through cross-species proteomic analyses, we dissect evolutionarily conserved and divergent aspects of the SCI response and establish the cerebrospinal fluid abundance of glial fibrillary acidic protein as a biochemical outcome measure in both humans and pigs. Our work opens up new avenues to catalyze translation by facilitating the evaluation of novel SCI therapies, while also providing a resource from which to direct future preclinical efforts.

Measurement of Trauma Caregiver Stress: Validation of Heart rate variability in a Real-World Surgical Setting.

BACKGROUND: Acute stress is a potentially modifiable risk-factor that contributes to errors in trauma care. Research on stress mitigation is limited by the lack of a validated objective measure of surgeon stress. We sought to validate HRV in a real-world surgical setting by comparison to the Subjective Units of Distress Score (SUDS), and correlation with self-reported peak stress moments. METHODS: Attending and resident surgeons on the trauma team at a Level I Trauma Center wore armbands to measure HRV. Stress-associated blunting of HRV was analyzed using the standard deviation of N-N intervals (SDNN) and the root mean square of successive differences . Perceived stress was measured with the SUDS at random intervals and at perceived stress peaks. SUDS and HRV metrics were compared with a mixed effect regression model. Correlation between binned SUDS quartiles and HRV was evaluated. HRV at reported peak-stress moments were compared to shift baseline values. RESULTS: Twelve participants were monitored for 340 h, producing 135 SUDS responses and 65 peak-stress time points. Regression analysis demonstrated no correlation between HRV and SUDS. With a binned approach, decreased SDNN was associated with an elevated SUDS (P = 0.03). The self-identified peak-stress moments correlated with decreases in both SDNN and root mean square of successive differences (P = 0.02; P < 0.01). CONCLUSIONS: HRV by SDNN analysis correlated with heightened perceived stress, supporting its validity as a measure. However, the wide, frequent variation of HRV tracings within subjects, the sensitivity of HRV to of analytic technique, and the impact of confounders may limit its utility as an education or research tool. LEVEL OF EVIDENCE: V Diagnostic test.

The Radiologist's Gaze: Mapping Three-Dimensional Visual Search in Computed Tomography of the Abdomen and Pelvis.

A radiologist's search pattern can directly influence patient management. A missed finding is a missed opportunity for intervention. Multiple studies have attempted to describe and quantify search patterns but have mainly focused on chest radiographs and chest CTs. Here, we describe and quantify the visual search patterns of 17 radiologists as they scroll through 6 CTs of the abdomen and pelvis. Search pattern tracings varied among individuals and remained relatively consistent per individual between cases. Attendings and trainees had similar eye metric statistics with respect to time to first fixation (TTFF), number of fixations in the region of interest (ROI), fixation duration in ROI, mean saccadic amplitude, or total number of fixations. Attendings had fewer numbers of fixations per second versus trainees (p < 0.001), suggesting efficiency due to expertise. In those cases that were accurately interpreted, TTFF was shorter (p = 0.04), the number of fixations per second and number of fixations in ROI were higher (p = 0.04, p = 0.02, respectively), and fixation duration in ROI was increased (p = 0.02). We subsequently categorized radiologists as "scanners" or "drillers" by both qualitative and quantitative methods and found no differences in accuracy with most radiologists being categorized as "drillers." This study describes visual search patterns of radiologists in interpretation of CTs of the abdomen and pelvis to better approach future endeavors in determining the effects of manipulations such as fatigue, interruptions, and computer-aided detection.

Identifying health information technology related safety event reports from patient safety event report databases.

OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model features. A feature-constraint model was developed and evaluated to support the analysis of PSE reports. METHODS: 5287 PSE reports manually coded as likely or unlikely related to HIT were used to train unigram, bigram, and combined unigram-bigram logistic regression and support vector machine models using five-fold cross validation. A difference-based scoring approach was used to prioritize and select unigram and bigram features by their relative importance to likely and unlikely HIT reports. A held-out set of 2000 manually coded reports were used for testing. RESULTS: Unigram models tended to perform better than bigram and combined models. A 300-unigram logistic regression had comparable classification performance to a 4030-unigram SVM model but with a faster relative run-time. The 300-unigram logistic regression model evaluated with the testing data had an AUC of 0.931 and a F1-score of 0.765. DISCUSSION: A difference-based scoring, prioritization, and feature selection approach can be used to generate simplified models with high performance. A feature-constraint model may be more easily shared across healthcare organizations seeking to analyze their respective datasets and customized for local variations in PSE reporting practices. CONCLUSION: The feature-constraint model provides a method to identify HIT-related patient safety hazards using a method that is applicable across healthcare systems with variability in their PSE report structures.

Emergency Physician Use of Cognitive Strategies to Manage Interruptions.

STUDY OBJECTIVE: The purpose of this study is to examine whether emergency physicians use strategies to manage interruptions during clinical work. Interruption management strategies include immediately engaging the interruption by discontinuing the current task and starting the interruption, continuing the current task while engaging the interruption, rejecting the interruption, or delaying the interruption. METHODS: An observational time and motion study was conducted in 3 different urban, academic emergency departments with 18 attending emergency physicians. Each physician was observed for 2 hours, and the number of interruptions, source of interruptions, type of task being interrupted, and use of interruption management strategies were documented. RESULTS: Participants were interrupted on average of 12.5 times per hour. The majority of interruptions were in person from other staff, including nurses, residents, and other attending physicians. When participants were interrupted, they were often working on their computer. Participants almost always immediately engaged the interruption task (75.4% of the time), followed by multitasking, in which the primary task was continued while the interrupting task was performed (22.2%). Physicians rejected or delayed interruptions less than 2% of the time. CONCLUSION: Our results suggest there is an opportunity to introduce emergency physicians to the use of interruption management strategies as a method of handling the frequent interruptions they are exposed to. Use of these strategies when high-risk primary tasks are performed may reduce the disruptiveness of some interruptions and improve patient safety.

Identifying influential individuals on intensive care units: using cluster analysis to explore culture.

AIM: The objective of this paper is to identify attribute patterns of influential individuals in intensive care units using unsupervised cluster analysis. BACKGROUND: Despite the acknowledgement that culture of an organisation is critical to improving patient safety, specific methods to shift culture have not been explicitly identified. METHODS: A social network analysis survey was conducted and an unsupervised cluster analysis was used. RESULTS: A total of 100 surveys were gathered. Unsupervised cluster analysis was used to group individuals with similar dimensions highlighting three general genres of influencers: well-rounded, knowledge and relational. CONCLUSIONS: Culture is created locally by individual influencers. Cluster analysis is an effective way to identify common characteristics among members of an intensive care unit team that are noted as highly influential by their peers. To change culture, identifying and then integrating the influencers in intervention development and dissemination may create more sustainable and effective culture change. Additional studies are ongoing to test the effectiveness of utilising these influencers to disseminate patient safety interventions. IMPLICATIONS FOR NURSING MANAGEMENT: This study offers an approach that can be helpful in both identifying and understanding influential team members and may be an important aspect of developing methods to change organisational culture.

Exploring methods for identifying related patient safety events using structured and unstructured data.

Most healthcare systems have implemented patient safety event reporting systems to identify safety hazards. Searching the safety event data to find related patient safety reports and identify trends is challenging given the complexity and quantity of these reports. Structured data elements selected by the event reporter may be inaccurate and the free-text narrative descriptions are difficult to analyze. In this paper we present and explore methods for utilizing both the unstructured free-text and structured data elements in safety event reports to identify and rank similar events. We evaluate the results of three different free-text search methods, including a unique topic modeling adaptation, and structured element weights, using a patient fall use case. The various search techniques and weight combinations tended to prioritize different aspects of the event reports leading to different search and ranking results. These search and prioritization methods have the potential to greatly improve patient safety officers, and other healthcare workers, understanding of which safety event reports are related.

Reading Room Interruptions are Less Disruptive When Using Asynchronous Communication Methods.

Radiologist interruptions, though often necessary, can be disruptive. Prior literature has shown interruptions to be frequent, occurring during cases, and predominantly through synchronous communication methods such as phone or in person causing significant disengagement from the study being read. Asynchronous communication methods are now more widely available in hospital systems such as ours. Considering the increasing use of asynchronous communication methods, we conducted an observational study to understand the evolving nature of radiology interruptions. We hypothesize that compared to interruptions occurring through synchronous methods, interruptions via asynchronous methods reduce the disruptive nature of interruptions by occurring between cases, being shorter, and less severe. During standard weekday hours, 30 radiologists (14 attendings, 12 residents, and 4 fellows) were directly observed for approximately 90-min sessions across three different reading rooms (body, neuroradiology, general). The frequency of interruptions was documented including characteristics such as timing, severity, method, and length. Two hundred twenty-five interruptions (43 Teams, 47 phone, 89 in-person, 46 other) occurred, averaging 2 min and 5 s with 5.2 interruptions per hour. Microsoft Teams interruptions averaged 1 min 12 s with only 60.5% during cases. In-person interruptions averaged 2 min 12 s with 82% during cases. Phone interruptions averaged 2 min and 48 s with 97.9% during cases. A substantial portion of reading room interruptions occur via predominantly asynchronous communication tools, a new development compared to prior literature. Interruptions via predominantly asynchronous communications tools are shorter and less likely to occur during cases. In our practice, we are developing tools and mechanisms to promote asynchronous communication to harness these benefits.

Developing a multimedia patient-reported outcomes measure for low literacy patients with a human-centered design approach.

INTRODUCTION: Almost all patient-reported outcomes measures (PROMs) are text-based, which impedes accurate completion by low and limited literacy patients. Few PROMs are designed or validated to be self-administered, either in clinical or research settings, by patients of all literacy levels. We aimed to adapt the Patient Reported Outcomes Measurement Information System Upper Extremity Short Form (PROMIS-UE) to a multimedia version (mPROMIS-UE) that can be self-administered by hand and upper extremity patients of all literacy levels. METHODS: Our study in which we applied the Multimedia Adaptation Protocol included seven phases completed in a serial, iterative fashion: planning with our community advisory board; direct observation; discovery interviews with patients, caregivers, and clinic staff; ideation; prototyping; member-checking interviews; and feedback. Direct observations were documented in memos that underwent rapid thematic analysis. Interviews were audio-recorded and documented using analytic memos; a rapid, framework-guided thematic analysis with both inductive and deductive themes was performed. Themes were distilled into design challenges to guide ideation and prototyping that involved our multidisciplinary research team. To assess completeness, credibility, and acceptability we completed additional interviews with member-checking of initial findings and consulted our community advisory board. RESULTS: We conducted 12 hours of observations. We interviewed 17 adult English-speaking participants (12 patients, 3 caregivers, 2 staff) of mixed literacy. Our interviews revealed two distinct user personas and three distinct literacy personas; we developed the mPROMIS-UE with these personas in mind. Themes from interviews were distilled into four broad design challenges surrounding literacy, customizability, convenience, and shame. We identified features (audio, animations, icons, avatars, progress indicator, illustrated response scale) that addressed the design challenges. The last 6 interviews included member-checking; participants felt that the themes, design challenges, and corresponding features resonated with them. These features were synthesized into an mPROMIS-UE prototype that underwent rounds of iterative refinement, the last of which was guided by recommendations from our community advisory board. DISCUSSION: We successfully adapted the PROMIS-UE to an mPROMIS-UE that addresses the challenges identified by a mixed literacy hand and upper extremity patient cohort. This demonstrates the feasibility of adapting PROMs to multimedia versions. Future research will include back adaptation, usability testing via qualitative evaluation, and psychometric validation of the mPROMIS-UE. A validated mPROMIS-UE will expand clinicians' and investigators' ability to capture patient-reported outcomes in mixed literacy populations.

Development and Evaluation of Patient Safety Interventions: Perspectives of Operational Safety Leaders and Patient Safety Organizations.

OBJECTIVES: The purpose of this study is to understand how patient safety professionals from healthcare facilities and patient safety organizations develop patient safety interventions and the resources used to support intervention development. METHODS: Semistructured interviews were conducted with patient safety professionals at nine healthcare facilities and nine patient safety organizations. Interview data were qualitatively analyzed, and findings were organized by the following: patient safety solutions and interventions, use of external databases, and evaluation of patient safety solutions. RESULTS: Development of patient safety interventions across healthcare facilities and patient safety organizations was similar and included literature searches, internal brainstorming, and interviews. Nearly all patient safety professionals at healthcare facilities reported contacting colleagues at other healthcare facilities to learn about similar safety issues and potential interventions. Additionally, less than half of patient safety professionals at healthcare facilities and patient safety organizations interviewed report data to publicly available patient safety databases. Finally, most patient safety professionals at healthcare facilities and patient safety organizations stated that they evaluate the effectiveness of patient safety interventions; however, they mentioned methods that may be less rigorous including audits, self-reporting, and subjective judgment. CONCLUSIONS: Patient safety professionals often utilize similar methods and resources to develop and evaluate patient safety interventions; however, many of these efforts are not coordinated across healthcare organizations and could benefit from working collectively in a systematic fashion. Additionally, healthcare facilities and patient safety organizations face similar challenges and there are several opportunities for optimization on a national level that may improve patient safety.

A natural language processing approach to categorise contributing factors from patient safety event reports.

OBJECTIVES: The objective of this study was to explore the use of natural language processing (NLP) algorithm to categorise contributing factors from patient safety event (PSE). Contributing factors are elements in the healthcare process (eg, communication failures) that instigate an event or allow an event to occur. Contributing factors can be used to further investigate why safety events occurred. METHODS: We used 10 years of self-reported PSE reports from a multihospital healthcare system in the USA. Reports were first selected by event date. We calculated χ2 values for each ngram in the bag-of-words then selected N ngrams with the highest χ2 values. Then, PSE reports were filtered to only include the sentences containing the selected ngrams. Such sentences were called information-rich sentences. We compared two feature extraction techniques from free-text data: (1) baseline bag-of-words features and (2) features from information-rich sentences. Three machine learning algorithms were used to categorise five contributing factors representing sociotechnical errors: communication/hand-off failure, technology issue, policy/procedure issue, distractions/interruptions and lapse/slip. We trained 15 binary classifiers (five contributing factors * three machine learning models). The models' performances were evaluated according to the area under the precision-recall curve (AUPRC), precision, recall, and F1-score. RESULTS: Applying the information-rich sentence selection algorithm boosted the contributing factor categorisation performance. Comparing the AUPRCs, the proposed NLP approach improved the categorisation performance of two and achieved comparable results with baseline in categorising three contributing factors. CONCLUSIONS: Information-rich sentence selection can be incorporated to extract the sentences in free-text event narratives in which the contributing factor information is embedded.

A text mining approach to categorize patient safety event reports by medication error type.

Patient safety reporting systems give healthcare provider staff the ability to report medication related safety events and errors; however, many of these reports go unanalyzed and safety hazards go undetected. The objective of this study is to examine whether natural language processing can be used to better categorize medication related patient safety event reports. 3,861 medication related patient safety event reports that were previously annotated using a consolidated medication error taxonomy were used to develop three models using the following algorithms: (1) logistic regression, (2) elastic net, and (3) XGBoost. After development, models were tested, and model performance was analyzed. We found the XGBoost model performed best across all medication error categories. 'Wrong Drug', 'Wrong Dosage Form or Technique or Route', and 'Improper Dose/Dose Omission' categories performed best across the three models. In addition, we identified five words most closely associated with each medication error category and which medication error categories were most likely to co-occur. Machine learning techniques offer a semi-automated method for identifying specific medication error types from the free text of patient safety event reports. These algorithms have the potential to improve the categorization of medication related patient safety event reports which may lead to better identification of important medication safety patterns and trends.

Symptom and Anatomical Phenotypes Provide Insights Into Interactions of Prolapse Symptoms and Anatomy.

IMPORTANCE: Women pursue treatment to relieve symptoms, while surgeons repair anatomy, underlining the importance of the relationship between symptoms and anatomy. OBJECTIVE: We hypothesized different anatomical and symptom phenotypes associated with pelvic organ prolapse (POP). Our objective was to investigate prevalence of phenotypes to explore associations of symptoms with anatomical defects. METHODS: We defined 420 anatomical phenotypes from combinations of POP Quantification parameters and 128 symptom phenotypes from symptoms described by condition-specific questionnaires (Pelvic Floor Disorders Inventory, Short Form of the Personal Experience Questionnaire). We applied these to an anonymized database of 719 subjects with symptomatic pelvic floor disorders. Bar graphs were used to illustrate the distribution of anatomical and symptom phenotypes, as well as anatomical phenotypes of patients with specific symptoms. We then used biclustering analysis with the multiple latent block model, to identify patterns of clustered groups of subjects and features. RESULTS: The most common symptom phenotypes have multiple (3-5) symptoms. A third of the theoretical anatomical phenotypes existed in our cohort. Bar graphs for specific symptom composites demonstrated unique distributions of anatomical phenotypes suggesting associations between anatomy and symptoms. Biclustering converged on 2 subject clusters (C1, C2) and 8 feature clusters. Cluster 1 (68%) represented a younger subpopulation with lower stage POP, more stress urinary incontinence and sexual dysfunction (P < 0.001 all). Cluster 2 had more protrusion (P < 0.001) and obstructed voiding (P = 0.001). Features that clustered together, such as stress urinary incontinence and sexual dysfunction, may represent underlying relationships. CONCLUSIONS: We demonstrated a relationship between locations of anatomical POP and certain symptoms, which may generate new hypotheses and guide clinical decision making.

HCV universal EHR prompt successfully increases screening, highlights potential disparities.

BACKGROUND & OBJECTIVES: Screening for hepatitis C virus is the first critical decision point for preventing morbidity and mortality from HCV cirrhosis and hepatocellular carcinoma and will ultimately contribute to global elimination of a curable disease. This study aims to portray the changes over time in HCV screening rates and the screened population characteristics following the 2020 implementation of an electronic health record (EHR) alert for universal screening in the outpatient setting in a large healthcare system in the US mid-Atlantic region. METHODS: Data was abstracted from the EHR on all outpatients from 1/1/2017 through 10/31/2021, including individual demographics and their HCV antibody (Ab) screening dates. For a limited period centered on the implementation of the HCV alert, mixed effects multivariable regression analyses were performed to compare the timeline and characteristics of those screened and un-screened. The final models included socio-demographic covariates of interest, time period (pre/post) and an interaction term between time period and sex. We also examined a model with time as a monthly variable to look at the potential impact of COVID-19 on screening for HCV. RESULTS: Absolute number of screens and screening rate increased by 103% and 62%, respectively, after adopting the universal EHR alert. Patients with Medicaid were more likely to be screened than private insurance (ORadj 1.10, 95% CI: 1.05, 1.15), while those with Medicare were less likely (ORadj 0.62, 95% CI: 0.62, 0.65); and Black (ORadj 1.59, 95% CI: 1.53, 1.64) race more than White. CONCLUSIONS: Implementation of universal EHR alerts could prove to be a critical next step in HCV elimination. Those with Medicare and Medicaid insurance were not screened proportionately to the national prevalence of HCV in these populations. Our findings support increased screening and re-testing efforts for those at high risk of HCV.

Atropine for the treatment of childhood myopia: safety and efficacy of 0.5%, 0.1%, and 0.01% doses (Atropine for the Treatment of Myopia 2).

PURPOSE: Our previous study, Atropine for the Treatment of Myopia 1 (ATOM1), showed that atropine 1% eyedrops were effective in controlling myopic progression but with visual side effects resulting from cycloplegia and mydriasis. The aim of this study was to compare efficacy and visual side effects of 3 lower doses of atropine: 0.5%, 0.1%, and 0.01%. DESIGN: Single-center, double-masked, randomized study. PARTICIPANTS: A total of 400 children aged 6-12 years with myopia of at least -2.0 diopters (D) and astigmatism of -1.50 D or less. INTERVENTION: Children were randomly assigned in a 2:2:1 ratio to 0.5%, 0.1%, and 0.01% atropine to be administered once nightly to both eyes for 2 years. Cycloplegic refraction, axial length, accommodation amplitude, pupil diameter, and visual acuity were noted at baseline, 2 weeks, and then every 4 months for 2 years. MAIN OUTCOME MEASURES: Myopia progression at 2 years. Changes were noted and differences between groups were compared using the Huber-White robust standard error to allow for data clustering of 2 eyes per person. RESULTS: The mean myopia progression at 2 years was -0.30±0.60, -0.38±0.60, and -0.49±0.63 D in the atropine 0.5%, 0.1%, and 0.01% groups, respectively (P=0.02 between the 0.01% and 0.5% groups; between other concentrations P > 0.05). In comparison, myopia progression in ATOM1 was -1.20±0.69 D in the placebo group and -0.28±0.92 D in the atropine 1% group. The mean increase in axial length was 0.27±0.25, 0.28±0.28, and 0.41±0.32 mm in the 0.5%, 0.1%, and 0.01% groups, respectively (P < 0.01 between the 0.01% and 0.1% groups and between the 0.01% and 0.5% groups). However, differences in myopia progression (0.19 D) and axial length change (0.14 mm) between groups were small and clinically insignificant. Atropine 0.01% had a negligible effect on accommodation and pupil size, and no effect on near visual acuity. Allergic conjunctivitis and dermatitis were the most common adverse effect noted, with 16 cases in the 0.1% and 0.5% atropine groups, and no cases in the 0.01% group. CONCLUSIONS: Atropine 0.01% has minimal side effects compared with atropine at 0.1% and 0.5%, and retains comparable efficacy in controlling myopia progression.

Improving presurgical pupil dilation for cataract surgery patients.

Insufficient pupil dilation, a common challenge in cataract surgery, may lead to surgical complications. After a quality improvement project was conducted, the proportion of patients with the desired pupil dilation of > or = 7 mm increased from 39.5% to 88.0% (Implementation phase) and then to 82.2% (Sustaining phase).

Using Community Detection Techniques to Identify Themes in COVID-19-Related Patient Safety Event Reports.

OBJECTIVES: The COVID-19 pandemic has transformed how healthcare is delivered to patients. As the pandemic progresses and healthcare systems continue to adapt, it is important to understand how these changes in care have changed patient care. This study aims to use community detection techniques to identify and facilitate analysis of themes in patient safety event (PSE) reports to better understand COVID-19 pandemic's impact on patient safety. With this approach, we also seek to understand how community detection techniques can be used to better identify themes and extract information from PSE reports. METHODS: We used community detection techniques to group 2082 PSE reports from January 1, 2020, to January 31, 2021, that mentioned COVID-19 into 65 communities. We then grouped these communities into 8 clinically relevant themes for analysis. RESULTS: We found the COVID-19 pandemic is associated with the following clinically relevant themes: (1) errors due to new and unknown COVID-19 protocols/workflows; (2) COVID-19 patients developing pressure ulcers; (3) unsuccessful/incomplete COVID-19 testing; (4) inadequate isolation of COVID-19 patients; (5) inappropriate/inadequate care for COVID-19 patients; (6) COVID-19 patient falls; (7) delays or errors communicating COVID-19 test results; and (8) COVID-19 patients developing venous thromboembolism. CONCLUSIONS: Our study begins the long process of understanding new challenges created by the pandemic and highlights how machine learning methods can be used to understand these and similar challenges. Using community detection techniques to analyze PSE reports and identify themes within them can help give healthcare systems the necessary information to improve patient safety and the quality of care they deliver.

Usability and Accessibility of Publicly Available Patient Safety Databases.

OBJECTIVES: The aims of the study were to identify publicly available patient safety report databases and to determine whether these databases support safety analyst and data scientist use to identify patterns and trends. METHODS: An Internet search was conducted to identify publicly available patient safety databases that contained patient safety reports. Each database was analyzed to identify features that enable patient safety analyst and data scientist use of these databases. RESULTS: Seven databases (6 hosted by federal agencies, 1 hosted by a nonprofit organization) containing more than 28.3 million safety reports were identified. Some, but not all, databases contained features to support patient safety analyst use: 57.1% provided the ability to sort/compare/filter data, 42.9% provided data visualization, and 85.7% enabled free-text search. None of the databases provided regular updates or monitoring and only one database suggested solutions to patient safety reports. Analysis of features to support data scientist use showed that only 42.9% provided an application programing interface, most (85.7%) provided batch downloading, all provided documentation about the database, and 71.4% provided a data dictionary. All databases provided open access. Only 28.6% provided a data diagram. CONCLUSIONS: Patient safety databases should be improved to support patient safety analyst use by, at a minimum, allowing for data to be sorted/compared/filtered, providing data visualization, and enabling free-text search. Databases should also enable data scientist use by, at a minimum, providing an application programing interface, batch downloading, and a data dictionary.