Artificial Intelligence Technology-Based Medical Information Processing and Emergency First Aid Nursing Management.

This study was aimed at exploring the new management mode of medical information processing and emergency first aid nursing management under the new artificial intelligence technology. This study will use the artificial intelligence algorithm to optimize medical information processing and emergency first aid nursing management process, in order to improve the efficiency of emergency department and first aid efficiency. The successful rescue rates of hemorrhagic shock, coma, dyspnea, and more than three organs injury were 96.7%, 92.5%, 93.7%, and 87.2%, respectively, after the emergency first aid nursing mode was used in the hospital emergency center. The success rates of first aid within three years were compared, which were 91.8%, 93.4%, and 94.2%, respectively, showing an increasing trend year by year. 255 emergency patients in five batches in June and five batches in July were selected as the research objects by convenience sampling method. Among them, 116 cases in June were taken as the experimental group, and 139 cases in July were taken as the control group, which was used to verify the efficiency of the design model in this study. The results showed that the triage time of the two groups was 8.16 ± 2.07 min and 19.21 ± 6.36 min, respectively, and the difference was statistically significant (P < 0.01). The triage coincidence rates were 96.35% and 90.04%, respectively, and the difference was statistically significant (P < 0.05). The research proved that the design of intelligent medical information processing and emergency first aid nursing management research model can effectively improve the triage efficiency of the wounded, assist the efficiency of emergency nursing of medical staff, and improve the survival rate of emergency patients, which is worthy of clinical promotion.

Trends in Health Information Technology Use Among the US Population With and Without Cardiovascular Risk Factors, 2012-2018: Evidence From the National Health Interview Survey.

BACKGROUND: The COVID-19 pandemic has required clinicians to pivot to offering services via telehealth; however, it is unclear which patients (users of care) are equipped to use digital health. This is especially pertinent for adults managing chronic diseases, such as obesity, hypertension, and diabetes, which require regular follow-up, medication management, and self-monitoring. OBJECTIVE: The aim of this study is to measure the trends and assess factors affecting health information technology (HIT) use among members of the US population with and without cardiovascular risk factors. METHODS: We used serial cross-sectional data from the National Health Interview Survey for the years 2012-2018 to assess trends in HIT use among adults, stratified by age and cardiovascular risk factor status. We developed multivariate logistic regression models adjusted for age, sex, race, insurance status, marital status, geographic region, and perceived health status to assess the likelihood of HIT use among patients with and without cardiovascular disease risk factors. RESULTS: A total of 14,304 (44.6%) and 14,644 (58.7%) participants reported using HIT in 2012 and 2018, respectively. When comparing the rates of HIT use for the years 2012 and 2018, among participants without cardiovascular risk factors, the HIT use proportion increased from 51.1% to 65.8%; among those with one risk factor, it increased from 43.9% to 59%; and among those with more than one risk factor, it increased from 41.3% to 54.7%. Increasing trends in HIT use were highest among adults aged >65 years (annual percentage change [APC] 8.3%), who had more than one cardiovascular risk factor (APC 5%) and among those who did not graduate from high school (APC 8.8%). Likelihood of HIT use was significantly higher in individuals who were younger, female, and non-Hispanic White; had higher education and income; were married; and reported very good or excellent health status. In 2018, college graduates were 7.18 (95% CI 5.86-8.79), 6.25 (95% CI 5.02-7.78), or 7.80 (95% CI 5.87-10.36) times more likely to use HIT compared to adults without high school education among people with multiple cardiovascular risk factors, one cardiovascular risk factor, or no cardiovascular risk factors, respectively. CONCLUSIONS: Over 2012-2018, HIT use increased nationally, with greater use noted among younger and higher educated US adults. Targeted strategies are needed to engage wider age, racial, education, and socioeconomic groups by lowering barriers to HIT access and use.

The relationship between health IT characteristics and organizational variables among German healthcare workers.

Health information technologies (HITs) are widely employed in healthcare and are supposed to improve quality of care and patient safety. However, so far, their implementation has shown mixed results, which might be explainable by understudied psychological factors of human-HIT interaction. Therefore, the present study investigates the association between the perception of HIT characteristics and psychological and organizational variables among 445 healthcare workers via a cross-sectional online survey in Germany. The proposed hypotheses were tested using structural equation modeling. The results showed that good HIT usability was associated with lower levels of techno-overload and lower IT-related strain. In turn, experiencing techno-overload and IT-related strain was associated with lower job satisfaction. An effective error management culture at the workplace was linked to higher job satisfaction and a slightly lower frequency of self-reported medical errors. About 69% of surveyed healthcare workers reported making errors less frequently than their colleagues, suggesting a bias in either the perception or reporting of errors. In conclusion, the study's findings indicate that ensuring high perceived usability when implementing HITs is crucial to avoiding frustration among healthcare workers and keeping them satisfied. Additionally healthcare facilities should invest in error management programs since error management culture is linked to other important organizational variables.

Health information technology interventions and engagement in HIV care and achievement of viral suppression in publicly funded settings in the US: A cost-effectiveness analysis.

BACKGROUND: The US National HIV/AIDS Strategy (NHAS) emphasizes the use of technology to facilitate coordination of comprehensive care for people with HIV. We examined cost-effectiveness from the health system perspective of 6 health information technology (HIT) interventions implemented during 2008 to 2012 in a Ryan White HIV/AIDS Program (RWHAP) Special Projects of National Significance (SPNS) Program demonstration project. METHODS/FINDINGS: HIT interventions were implemented at 6 sites: Bronx, New York; Durham, North Carolina; Long Beach, California; New Orleans, Louisiana; New York, New York (2 sites); and Paterson, New Jersey. These interventions included: (1) use of HIV surveillance data to identify out-of-care individuals; (2) extension of access to electronic health records (EHRs) to support service providers; (3) use of electronic laboratory ordering and prescribing; and (4) development of a patient portal. We employed standard microcosting techniques to estimate costs (in 2018 US dollars) associated with intervention implementation. Data from a sample of electronic patient records from each demonstration site were analyzed to compare prescription of antiretroviral therapy (ART), CD4 cell counts, and suppression of viral load, before and after implementation of interventions. Markov models were used to estimate additional healthcare costs and quality-adjusted life-years saved as a result of each intervention. Overall, demonstration site interventions cost $3,913,313 (range = $287,682 to $998,201) among 3,110 individuals (range = 258 to 1,181) over 3 years. Changes in the proportion of patients prescribed ART ranged from a decrease from 87.0% to 72.7% at Site 4 to an increase from 74.6% to 94.2% at Site 6; changes in the proportion of patients with 0 to 200 CD4 cells/mm3 ranged from a decrease from 20.2% to 11.0% in Site 6 to an increase from 16.7% to 30.2% in Site 2; and changes in the proportion of patients with undetectable viral load ranged from a decrease from 84.6% to 46.0% in Site 1 to an increase from 67.0% to 69.9% in Site 5. Four of the 6 interventions-including use of HIV surveillance data to identify out-of-care individuals, use of electronic laboratory ordering and prescribing, and development of a patient portal-were not only cost-effective but also cost saving ($6.87 to $14.91 saved per dollar invested). In contrast, the 2 interventions that extended access to EHRs to support service providers were not effective and, therefore, not cost-effective. Most interventions remained either cost-saving or not cost-effective under all sensitivity analysis scenarios. The intervention that used HIV surveillance data to identify out-of-care individuals was no longer cost-saving when the effect of HIV on an individual's health status was reduced and when the natural progression of HIV was increased. The results of this study are limited in that we did not have contemporaneous controls for each intervention; thus, we are only able to assess sites against themselves at baseline and not against standard of care during the same time period. CONCLUSIONS: These results provide additional support for the use of HIT as a tool to enhance rapid and effective treatment of HIV to achieve sustained viral suppression. HIT has the potential to increase utilization of services, improve health outcomes, and reduce subsequent transmission of HIV.

Nomogram to predict the risk of acute kidney injury in patients with diabetic ketoacidosis: an analysis of the MIMIC-III database.

BACKGROUND: This study aimed to develop and validate a nomogram for predicting acute kidney injury (AKI) during the Intensive Care Unit (ICU) stay of patients with diabetic ketoacidosis (DKA). METHODS: A total of 760 patients diagnosed with DKA from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included and randomly divided into a training set (70%, n = 532) and a validation set (30%, n = 228). Clinical characteristics of the data set were utilized to establish a nomogram for the prediction of AKI during ICU stay. The least absolute shrinkage and selection operator (LASSO) regression was utilized to identified candidate predictors. Meanwhile, a multivariate logistic regression analysis was performed based on variables derived from LASSO regression, in which variables with P < 0.1 were included in the final model. Then, a nomogram was constructed applying these significant risk predictors based on a multivariate logistic regression model. The discriminatory ability of the model was determined by illustrating a receiver operating curve (ROC) and calculating the area under the curve (AUC). Moreover, the calibration plot and Hosmer-Lemeshow goodness-of-fit test (HL test) were conducted to evaluate the performance of our newly bullied nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit. RESULTS: A multivariable model that included type 2 diabetes mellitus (T2DM), microangiopathy, history of congestive heart failure (CHF), history of hypertension, diastolic blood pressure (DBP), urine output, Glasgow coma scale (GCS), and respiratory rate (RR) was represented as the nomogram. The predictive model demonstrated satisfied discrimination with an AUC of 0.747 (95% CI, 0.706-0.789) in the training dataset, and 0.712 (95% CI, 0.642-0.782) in the validation set. The nomogram showed well-calibrated according to the calibration plot and HL test (P > 0.05). DCA showed that our model was clinically useful. CONCLUSION: The nomogram predicted model for predicting AKI in patients with DKA was constructed. This predicted model can help clinical physicians to identify the patients with high risk earlier and prevent the occurrence of AKI and intervene timely to improve prognosis.

Association between 30-day readmission rates and health information technology capabilities in US hospitals.

ABSTRACT: Health information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = -0.086; 95% Confidence Interval, -0.162 to -0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial - perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.

Age Differences in the Use of Health Information Technology Among Adults in the United States: An Analysis of the Health Information National Trends Survey.

Background: Despite significant advancements in the use of health information technologies (HITs) in health care, older adults' adoption of new technologies has consistently lagged behind that of younger adults. Objective: To compare ownership rates and preferences for utilizing technology for health information exchange among older and younger adults. Methods: Utilizing data from the 2017 and 2018 iterations of the Health Information National Trends Survey (n = 6789), we performed multivariable logistic regression while controlling for sociodemographic characteristics. Results: Older adults were less likely than younger adults to own technological devices such as smartphones, less likely to report finding these tools beneficial in monitoring their health, and less likely to use these tools in communicating with their health providers. However, these differences were substantially attenuated after adjustment for technology ownership. Discussion: Future research should aim to identify factors associated with access, usability, and adoption of HIT for managing care among older adults.

Outcomes of a health informatics technology-supported behavioral activation training for care managers in a collaborative care program.

INTRODUCTION: Health informatics-supported strategies for training and ongoing support may aid the delivery of evidence-based psychotherapies. The objective of this study was to describe the development, implementation, and practice outcomes of a scalable health informatics-supported training program for behavioral activation for patients who screened positive for posttraumatic stress disorder and/or bipolar disorder. METHOD: We trained 34 care managers in 12 rural health centers. They used a registry checklist to document the delivery of 10 behavioral activation skills for 4,632 sessions with 455 patients. Care managers received performance feedback based on registry data. Using encounter-level data reported by care managers, we described the implementation outcomes of patient reach and care manager skill adoption. We used cross-classified multilevel modeling to explore variation in skill delivery accounting for patient characteristics, provider characteristics, and change over time. RESULTS: Care managers engaged 88% of patients in behavioral activation and completed a minimum course for 57%. The average patient received 5.9 skills during treatment, with substantial variation driven more by providers (63%) than patients (29%). Care managers significantly increased the range of skills offered to patients over time. DISCUSSION: The registry-based checklist was a feasible training and support tool for community-based providers to deliver behavioral activation. Providers received data-driven performance feedback and demonstrated skill improvement over time, promoting sustainment. Future research will examine patient-level outcomes. Results underscore the potential public health impact of a simple registry-based skills checklist coupled with a scalable remote training program for evidence-based psychotherapy. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ontological representation, classification and data-driven computing of phenotypes.

BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term 'phenotype' has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimisation. In the context of a methodological use case 'phenotype pipeline' (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. RESULTS: In this article, we present a Core Ontology of Phenotypes (COP) and the software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model, classify and compute phenotypes from already available data. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated with selected phenotypes including SOFA score, socio-economic status, body surface area and WHO BMI classification based on available medical data. CONCLUSIONS: We developed a novel ontology-based method to model phenotypes of living beings with the aim of automated phenotype reasoning based on available data. This new approach can be used in clinical context, e.g., for supporting the diagnostic process, evaluating risk factors, and recruiting appropriate participants for clinical and epidemiological studies.

The Effects of Social Participation Restriction on Psychological Distress among Older Adults with Chronic Illness.

This study examined how restricted social participation mediates the relationship between chronic illness and psychological distress among community-dwelling older adults. Additionally, the use of the Internet for health care was tested as a moderator to examine whether the relationship between limited social participation and psychological distress differs. Using the multiple-group path analysis approach, 16,032 community-dwelling older adults (65+) from the National Health Interview Survey were analyzed. The findings show that 32.2% suffered from chronic illnesses that limited their daily activities, and 26% reported social participation restrictions to some degree. While having chronic illnesses was associated with greater psychological distress, the association was also through increased social participation restriction (mediation). Furthermore, differences in mediation were found between health information technology users and nonusers (moderated mediation). In contrast to the hypothesis, the adverse relationship between limited social participation and psychological distress was stronger among users, although chronic conditions were associated with greater social participation restrictions among nonusers. The findings suggest that with proper accommodations and interventions that aim to increase the social participation of community-dwelling older adults, the disadvantageous effects of chronic conditions on psychological distress could be ameliorated. Moreover, the importance of such interventions is greater among health information technology users.

Clinical informatics subspecialists: characterizing a novel evolving workforce.

BACKGROUND: The growing complexity of data systems in health care has precipitated increasing demand for clinical informatics subspecialists. The first board certification exam for the clinical informatics subspecialty was offered in 2013. Characterizing trends in this novel workforce is important to inform its development. METHODS: We conducted an exploratory analysis of American Board of Medical Specialties data on individuals certified in clinical informatics from 2013 to 2019 to review trends and demographic characteristics of current subspecialists. RESULTS: 2018 physicians were certified in clinical informatics from 2013 to 2019. The annual number of awarded certifications declined after 2016. The majority of primary certifications held by clinical informaticians were in broad-based medical specialties relative to primarily procedural specialties. CONCLUSIONS: Disparities may exist within the clinical informatics physician workforce with respect to primary specialty certifications and geographic distribution. There remains a need for the creation of fellowship programs to sustain the growth of this workforce.

Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals.

Given the severe and rapid impact of COVID-19, the pace of information sharing has been accelerated. However, traditional methods of disseminating and digesting medical information can be time-consuming and cumbersome. In a pilot study, the authors used social listening to quickly extract information from social media channels to explore what people with COVID-19 are talking about regarding symptoms and disease progression. The goal was to determine whether, by amplifying patient voices, new information could be identified that might have been missed through other sources. Two data sets from social media groups of people with or presumed to have COVID-19 were analyzed: a Facebook group poll, and conversation data from a Reddit group including detailed disease natural history-like posts. Content analysis and a customized analytics engine that incorporates machine learning and natural language processing were used to quickly identify symptoms mentioned. Key findings include more than 20 symptoms in the data sets that were not listed in online lists of symptoms from 4 respected medical information sources. The disease natural history-like posts revealed that people can experience symptoms for many weeks and that some symptoms change over time. This study demonstrates that social media can offer novel insights into patient experiences as a source of real-world data. This inductive research approach can quickly generate descriptive information that can be used to develop hypotheses and new research questions. Also, the method allows rapid assessments of large numbers of social media conversations that could be applied to monitor public health for emerging and rapidly spreading diseases such as COVID-19.

Problem-solving in technology-rich environments and cancer screening in later life.

Routine cancer screening is widely recognized as an effective preventive strategy to reduce cancer mortality - the second leading cause of death in the US. However, cancer screening requires a complex array of tasks such as seeking up-to-date guidelines, making appointments, planning hospital visits, and communicating with health care professionals. Importantly, modern health care largely relies on technology to disseminate the latest information and administer the system. Yet, little is known about the technology-related skills that are relevant to regular cancer screening. This study examined the association between problem-solving skills in the technology-rich environment and cancer screening in later life. Using 2012/2014 Program for International Assessment of Adult Competencies data, binary logistic regressions with survey weights were used to estimate the association between problem-solving skills in the technology-rich environment and four cancer screening behaviors among the corresponding target populations aged between 45 and 74 years old (n = 1374 for cervical screening; n = 1373 for breast screening; n = 1166 for prostate screening; n = 2563 for colon screening). Results showed that greater problem-solving skills in the technology-rich environment scores (0-500 points) were significantly and positively associated with prostate cancer screening (odds ratio = 1.005, P < 0.05) among men, but not with colon (men and women) or cervical or breast (women) cancer screenings. Improvement in problem-solving skills in the technology-rich environment may promote specific cancer screening behaviors. Our findings inform future policy discussions and interventions that seek to improve cancer screening among a vulnerable section of older populations.

Analysis of user behavior on the website of a university eye hospital in Germany.

Medical information websites are usually targeted toward patients, physicians, and medical students. Most of the latest studies researched the usability of such websites. However, reports on user numbers and behavior are rare.The goal of our study is to analyze the utility of a website of a large tertiary referral center in ophthalmology in terms of various target audiences (patients, applicants, medical students, referring ophthalmologists).The web access data from our institutional website was assessed with Google Analytics. Data collection started in 2016.From 2016 to 2018, we counted a total of 763,942 page views. The overall number of users dropped from 81,572 to 67,740. This drop's onset correlates with a change in the website structure. All target audience pages received constant traffic from 2016 to 2019, with the patients' and doctors' sites attracting the most traffic. The pages for medical students and job applicants, although not viewed often, revealed a long session duration.Our website is used by all our target audiences. The behavior and the user numbers of each target group differ. Changes to a website's structure can influence the number of users and their behavior. It is not possible to make a direct comparison to other institutions' websites as there are so few similar reports available. By adding more parameters to the analytics profile in a prospective setting, more detailed analyses of user behavior may be possible in the future.

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data.

Importance: Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged. Objective: To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system. Design, Setting, and Participants: This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018. Main Outcomes and Measures: Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved. Results: Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results. Conclusions and Relevance: This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.

Improving venous thromboembolism prophylaxis through critical thinking and health informatics.

Venous thromboembolism (VTE) is a leading cause of preventable morbidity and mortality in hospitalised patients. Mafraq Hospital, a 450-bed tertiary-level hospital in Abu Dhabi, United Arab Emirates, has identified VTE prevention as a critical patient safety measure and VTE prophylaxis as a key performance indicator (KPI). Mafraq Hospital VTE prevention policy states that all admitted adult patients 18 years and above should receive a VTE risk assessment, and all patients identified at risk of VTE with no contraindications should receive appropriate VTE prophylaxis within 24 hours of admission. In a move towards safer practices, our governing body, Abu Dhabi Health Services SEHA, has raised the VTE prophylaxis KPI target from 85% to 95% for all admitted adult patients within 24 hours of admission. Our average VTE prophylaxis rate was 87%, and achieving this new target was a challenge. We conducted this study on Mafraq Hospital Medical and Surgical wards. The study period was 12 months, from July 2018 to June 2019, and a total of 5475 patients were evaluated. Our aim was to improve VTE prophylaxis rates in order to ensure patient safety and reduce preventable harm. We used Caprini Model electronic VTE risk assessment computerised decision support tool to help identify VTE risk. A multidisciplinary task force team was formed and led this quality improvement project. The purpose of this publication was to indicate the quality improvement interventions implemented to enhance compliance with VTE prophylaxis using integrated critical thinking and health informatics and the outcomes of those interventions. Through implementing critical thinking and health informatics interventions, our VTE prophylaxis within 24 hours of admission rates improved from an average 87% in July 2018 to above 98%, and this improvement was sustained over the last 3 months of the study period April through June 2019.