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BackgroundElectronic health records (EHRs) are a central feature of care delivery in acute care hospitals; however, the financial and quality outcomes associated with system performance remain unclear. ObjectiveIn this study, we aimed to evaluate the association between the top 3 EHR vendors and measures of hospital financial and quality performance. MethodsThis study evaluated 2667 hospitals with Cerner, Epic, or Meditech as their primary EHR and considered their performance with regard to net income, Hospital Value–Based Purchasing Total Performance Score (TPS), and the unweighted subdomains of efficiency and cost reduction; clinical care; patient- and caregiver-centered experience; and patient safety. We hypothesized that there would be a difference among the 3 vendors for each measure. ResultsNone of the EHR systems were associated with a statistically significant financial relationship in our study. Epic was positively associated with TPS outcomes (R2=23.6%; β=.0159, SE 0.0079; P=.04) and higher patient perceptions of quality (R2=29.3%; β=.0292, SE 0.0099; P=.003) but was negatively associated with patient safety quality scores (R2=24.3%; β=−.0221, SE 0.0102; P=.03). Cerner and Epic were positively associated with improved efficiency (R2=31.9%; Cerner: β=.0330, SE 0.0135, P=.01; Epic: β=.0465, SE 0.0133, P

BackgroundThe Health Information Technology for Economic and Clinical Health Act (HITECH) allocated $19.2 billion to incentivize adoption of the electronic health record (EHR). Since 2009, Meaningful Use Criteria have dominated information technology (IT) strategy. Health care organizations have struggled to meet expectations and avoid penalties to reimbursements from the Center for Medicare and Medicaid Services (CMS). Organizational theories attempt to explain factors that influence organizational change, and many theories address changes in organizational strategy. However, due to the complexities of the health care industry, existing organizational theories fall short of demonstrating association with significant health care IT implementations. There is no organizational theory for health care that identifies, groups, and analyzes both internal and external factors of influence for large health care IT implementations like adoption of the EHR. ObjectiveThe purpose of this systematic review is to identify a full-spectrum of both internal organizational and external environmental factors associated with the adoption of health information technology (HIT), specifically the EHR. The result is a conceptual model that is commensurate with the complexity of with the health care sector. MethodsWe performed a systematic literature search in PubMed (restricted to English), EBSCO Host, and Google Scholar for both empirical studies and theory-based writing from 1993-2013 that demonstrated association between influential factors and three modes of HIT: EHR, electronic medical record (EMR), and computerized provider order entry (CPOE). We also looked at published books on organizational theories. We made notes and noted trends on adoption factors. These factors were grouped as adoption factors associated with various versions of EHR adoption. ResultsThe resulting conceptual model summarizes the diversity of independent variables (IVs) and dependent variables (DVs) used in articles, editorials, books, as well as quantitative and qualitative studies (n=83). As of 2009, only 16.30% (815/4999) of nonfederal, acute-care hospitals had adopted a fully interoperable EHR. From the 83 articles reviewed in this study, 16/83 (19%) identified internal organizational factors and 9/83 (11%) identified external environmental factors associated with adoption of the EHR, EMR, or CPOE. The conceptual model for EHR adoption associates each variable with the work that identified it. ConclusionsCommonalities exist in the literature for internal organizational and external environmental factors associated with the adoption of the EHR and/or CPOE. The conceptual model for EHR adoption associates internal and external factors, specific to the health care industry, associated with adoption of the EHR. It becomes apparent that these factors have some level of association, but the association is not consistently calculated individually or in combination. To better understand effective adoption strategies, empirical studies should be performed from this conceptual model to quantify the positive or negative effect of each factor.

BackgroundWebsites of many rogue sellers of medications are accessible through links in email spam messages or via web search engines. This study examined how well students enrolled in a U.S. higher education institution could identify clearly unsafe pharmacies. ObjectiveThe aim is to estimate these health consumers´ vulnerability to fraud by illegitimate Internet pharmacies. MethodsTwo Internet pharmacy websites, created specifically for this study, displayed multiple untrustworthy features modeled after five actual Internet drug sellers which the authors considered to be potentially dangerous to consumers. The websites had none of the safe pharmacy signs and nearly all of the danger signs specified in the Food and Drug Administration´s (FDA´s) guide to consumers. Participants were told that a neighborhood pharmacy charged US$165 for a one-month supply of Beozine, a bogus drug to ensure no pre-existing knowledge. After checking its price at two Internet pharmacies—$37.99 in pharmacy A and $57.60 in pharmacy B—the respondents were asked to indicate if each seller was a good place to buy the drug. Responses came from 1,914 undergraduate students who completed an online eHealth literacy assessment in 2005-2008. Participation rate was 78%. ResultsIn response to "On a scale from 0-10, how good is this pharmacy as a place for buying Beozine?" many respondents gave favorable ratings. Specifically, 50% of students who reviewed pharmacy A and 37% of students who reviewed pharmacy B chose a rating above the scale midpoint. When explaining a low drug cost, these raters related it to low operation costs, ad revenue, pressure to lower costs due to comparison shopping, and/or high sales volume. Those who said that pharmacy A or B was "a very bad place" for purchasing the drug (25%), as defined by a score of 1 or less, related low drug cost to lack of regulation, low drug quality, and/or customer information sales. About 16% of students thought that people should be advised to buy cheaper drugs at pharmacies such as these but the majority (62%) suggested that people should be warned against buying drugs from such internet sellers. Over 22% of respondents would recommend pharmacy A to friends and family (10% pharmacy B). One-third of participants supplied online health information to others for decision-making purposes. After controlling for the effects of education, health major, and age, these respondents had significantly worse judgment of Internet pharmacies than those who did not act as information suppliers. ConclusionsAt least a quarter of students, including those in health programs, cannot see multiple signs of danger displayed by rogue Internet pharmacies. Many more are likely to be misled by online sellers that use professional design, veil untrustworthy features, and mimic reputable websites. Online health information consumers would benefit from education initiatives that (1) communicate why it can be dangerous to buy medications online and that (2) develop their information evaluation skills. This study highlights the importance of regulating rogue Internet pharmacies and curbing the danger they pose to consumers.

Objective To assess college students' willingness to accept COVID-19 vaccines and the factors that influence their decisions. Participants: Traditional (aged 18-23) undergraduate students at a university in central Texas. Methods: An online survey was administered in fall 2020 to 614 students stratified by sex and race/ethnicity. Results: 40.9% of students planned to take the vaccine as soon as possible, 37.1% eventually, 11.4% only if required, and 10.6% did not intend to be vaccinated. Analyses indicated that gender, major/minor, political affiliation, receiving a flu shot in the preceding 12 months, perception of risk for COVID-19, and vaccine hesitancy were all associated with willingness to accept COVID-19 vaccines. Conclusion: Results confirm that no one-size-fits-all approach to promoting COVID-19 vaccination among college students is possible. Instead, administrators interested in increasing vaccine uptake should address concerns of specific groups, while also utilizing the prosocial beliefs of college students (e.g., being vaccinated will protect others).

Tobacco product waste (TPW) is one of the most ubiquitous forms of litter, accumulating in large amounts on streets, highways, sidewalks, beaches, parks, and other public places, and flowing into storm water drains, waste treatment plants, and solid waste collection facilities. In this paper, we evaluate the direct and indirect costs associated with TPW in the 30 largest U.S. cities. We first developed a conceptual framework for the analysis of direct and indirect costs of TPW abatement. Next, we applied a simulation model to estimate the total costs of TPW in major U.S. cities. This model includes data on city population, smoking prevalence rates, and per capita litter mitigation costs. Total annual TPW-attributable mean costs for large US cities range from US$4.7 million to US$90 million per year. Costs are generally proportional to population size, but there are exceptions in cities that have lower smoking prevalence rates. The annual mean per capita TPW cost for the 30 cities was US$6.46, and the total TPW cost for all 30 cities combined was US$264.5 million per year. These estimates for the TPW-attributable cost are an important data point in understanding the negative economic externalities created by cigarette smoking and resultant TPW cleanup costs. This model provides a useful tool for states, cities, and other jurisdictions with which to evaluate a new economic cost outcome of smoking and to develop new laws and regulations to reduce this burden.

Cigarette butts, whuch are also known as tobacco product waste (TPW), are the single most collected item in environmental trash cleanups worldwide. This study used an online survey tool (Qualtrics) to assess knowledge, attitudes, and perceptions regarding this issue among individuals representing the Framework Convention Alliance (FCA). The FCA has about 680 members on its listserv, including non-governmental tobacco control advocacy groups that support the implementation of the World Health Organization's (WHO) Framework Convention on Tobacco Control (FCTC). Respondents (n = 65) represented countries from all six WHO regions. The majority (82%) had heard the term TPW, and they all considered TPW as an environmental harm at some level. Additionally, 29% of respondents failed to identify that "cigarette filters make smoking easier". Most (73%) correctly identified TPW components; however, fewer (60%) correctly identified the composition of cigarette butts. The majority (57%) were unfamiliar with Extended Producer Responsibility (EPR) and Product Stewardship (PS) as possible environmental intervention strategies. Respondents expressing opinions concurred that adding a litter fee to fund TPW programs will aid in reducing tobacco use and reduce the environmental impacts of TPW (100%); that prevention, reduction, and mitigation of TPW could be an important part of international tobacco control programs (98%); and, that banning smoking in outdoor venues could reduce TPW (95%). Only 16% reported effective prevention or clean-up efforts in their countries. Weighted rankings revealed that respondents' saw the national government, the tobacco industry, and state governments as the most important in addressing TPW. The results of this research will inform continuing international discussions by the FCTC Conference of the Parties (COP) regarding environmental policies that may be addressed within FCTC obligations.

The focal point of this research is to compare two of the largest global organizations' sustainability indices and scores, namely Dow Jones Sustainability Indices (DJSIs) and Standard & Poor's Global (S&P Global) ESG scores (environmental, social, and governance), which rank companies based on their sustainability practices, and to learn if they correspond to each other. Considering that Germany is the hub of large companies from leading global industries, this research compares the ESG scores of the German companies that appear on the Dow Jones Sustainability Indices. Several statistical analyses are conducted to determine if the German companies on the DJSIs correspond with high ESG scores. The years under consideration are 2018 through 2023. The results of this research indicate that DJSIs and ESG scores do not tell the same story and there are discrepancies regarding the sustainability practices of the studied companies that are added to the DJSIs and the assigned high ESG scores by S&P Global. [ABSTRACT FROM AUTHOR]

In a three-group, gender-matched, preexisting knowledge-controlled, randomized experiment, we evaluated the effect of learner control over study pace on healthcare executives' performance in an online statistics course. Overall, frequent deadlines enhanced distribution of practice and improved learning. Students with less control over pace (in groups with weekly deadlines) spaced their study episodes to a greater extent than their peers with more control over pace (in groups with monthly and end-of-course deadlines). Online learning experience and technology self-efficacy did not explain practice distribution effects. Student perceptions of control over how, when and in which order they learn did not differ significantly across experimental groups. However, perceived control and spaced practice were positively and significantly related to performance on tests of short delayed retention and near transfer. In addition, perceived control and spaced practice predicted performance on a test of delayed retention and far transfer. Locus of control did not explain differences in performance. (Contains 6 tables.)

This manuscript discusses the common confusion between the terms probability and odds. To emphasize the importance and responsibility of being meticulous in the dissemination of information and knowledge, this manuscript reveals five cases of sources of inaccurate statistical language imbedded in the dissemination of information to the general public. The five cases presented are: Texas Lottery, Texas PowerBall, the Discovery Education Website, ScienceNews, and the Oregon State website. (Contains 4 tables and 4 figures.)

The number of COVID-19 fatalities fluctuated widely across United States (US) counties. The number of deaths is stochastic. When the average number of deaths is equal to the dispersion, the distribution is the usual Poisson. When the average number of deaths is higher than the dispersion, the distribution is an intervened Poisson. When the average number of deaths is lower than the dispersion, the distribution is an incidence-rate-restricted Poisson (IRRP) type. Because dispersion of COVID-19 fatalities in some counties is higher than the average number of fatalities, the underlying model for the chance-oriented mechanism might be IRRP. Understanding where this overdispersion or volatility exists and the implications of it is the topic of this research. In essence, this paper focuses on the number of COVID-19 fatalities that fluctuated widely across United States (US) counties and develops an incidence-rate-restricted Poisson (IRRP) to understand where this overdispersion or volatility exists and the implications of it. [ABSTRACT FROM AUTHOR]

Background: Health care data breaches are the most rapidly increasing type of cybercrime; however, the predictors of health care data breaches are uncertain. Objective: This quantitative study aims to develop a predictive model to explain the number of hospital data breaches at the county level. Methods: This study evaluated data consolidated at the county level from 1032 short-term acute care hospitals. We considered the association between data breach occurrence (a dichotomous variable), predictors based on county demographics, and socioeconomics, average hospital workload, facility type, and average performance on several hospital financial metrics using 3 model types: logistic regression, perceptron, and support vector machine. Results: The model coefficient performance metrics indicated convergent validity across the 3 model types for all variables except bad debt and the factor level accounting for counties with >20% and up to 40% Hispanic populations, both of which had mixed coefficient directionality. The support vector machine model performed the classification task best based on all metrics (accuracy, precision, recall, F 1-score). All the 3 models performed the classification task well with directional congruence of weights. From the logistic regression model, the top 5 odds ratios (indicating a higher risk of breach) included inpatient workload, medical center status, pediatric trauma center status, accounts receivable, and the number of outpatient visits, in high to low order. The bottom 5 odds ratios (indicating the lowest odds of experiencing a data breach) occurred for counties with Black populations of >20% and <40%, >80% and <100%, and >40% but <60%, as well as counties with ≤20% Asian or between 80% and 100% Hispanic individuals. Our results are in line with those of other studies that determined that patient workload, facility type, and financial outcomes were associated with the likelihood of health care data breach occurrence. Conclusions: The results of this study provide a predictive model for health care data breaches that may guide health care managers to reduce the risk of data breaches by raising awareness of the risk factors. [ABSTRACT FROM AUTHOR]