Exploring a model of skillful engagement in nursing practice

Prominent challenges facing nurse leaders are the growing shortage of nurses and the increasingly complex care required by acutely ill patients. In organizations that shortage is exacerbated by turnover and intent to leave. Unsatisfactory working conditions are cited by nurses when they leave their current jobs. Disengagement from the job leads to plateaued performance, decreased organizational commitment, and increased turnover. Solutions to these challenges include methods both to retain and to increase the effectiveness of each nurse. ^ The specific aim of this study was to examine the relationships among organizational structures thought to foster the clinical development of the nurse, with indicators of the development of clinical expertise, resulting in outcomes of positive job attitudes and effectiveness. Causal loop modeling is incorporated as a systems tool to examine developmental cycles both for an organization and for an individual nurse to look beyond singular events and investigate deeper patterns that emerge over time. ^ The setting is an academic specialty-care institution, and the sample in this cross-sectional study consists of paired data from 225 RNs and their nurse managers. Two panels of survey instruments were created based on the model's theoretical variables, one completed by RNs and the other by their Nurse Managers. The RN survey panel examined the variables of structural empowerment, magnet essentials, knowledge as identified by the Benner developmental stage, psychological empowerment, job stage, engagement, intent to leave, job satisfaction and the early recognition of patient complications. The nurse manager survey panel examined the Benner developmental stage, job stage, and overall level of nursing performance. ^ Four regression models were created based on the outcome variables. Each model identified significant organizational and individual characteristics that predicted higher job satisfaction, decreased intent to leave, more effectiveness as measured by early recognition and acting upon subtle patient complications, and better job performance. ^ Implications for improving job attitudes and effectiveness focus on ways that nursing leaders can foster a more empowering and healthy work environment. ^

The effect of African Americans' ethnographic paradigms and cultural explanatory model of breast cancer in framing the male partner's attitudes and behaviors about the woman's breast cancer diagnosis

The disparate burden of breast cancer-related morbidity and mortality experienced by African American women compared with women of other races is a topic of intense debate in the medical and public health arenas. The anomaly is consistently attributed to the fact that at diagnosis, a large proportion of African American women have advanced-stage disease. Extensive research has documented the impacts of cultural factors and of socioeconomic factors in shaping African American women's breast-health practices; however, there is another factor of a more subtle influence that might have some role in establishing these women's vulnerability to this disease: the lack of or perceived lack of partner support. Themes expressed in the research literature reflect that many African American breast cancer patients and survivors consider their male partners as being apathetic and nonsupportive. ^ The purpose of this study was to learn how African American couples' ethnographic paradigms and cultural explanatory model of breast cancer frame the male partners' responses to the women's diagnosis and to assess his ability to cope and willingness to adapt to the subsequent challenges. The goal of the study was to determine whether these men's coping and adaptation skills positively or negatively affect the women's self-care attitudes and behaviors. ^ This study involved 4 African American couples in which the woman was a breast cancer survivor. Participants were recruited through a community-based cancer support group and a church-based cancer support group. Recruitment sessions were held at regular meetings of these organizations. Accrual took 2 months. In separate sessions, each male partner and each survivor completed a demographic survey and a questionnaire and were interviewed. Additionally, the couples were asked to participate in a communications activity (Adinkra). This activity was not done to fulfill any part of the study purpose and was not included in the data analysis; rather, it was done to assess its potential use as an intervention to promote dialogue between African American partners about the experience of breast cancer. ^ The questionnaire was analyzed on the basis of a coding schema and the interview responses were analyzed on the principles of hermeneutic phenomenology. In both cases, the instruments were used to determine whether the partner's coping skills reflected a compassionate attitude (positive response) versus an apathetic attitude (negative response) and whether his adaptation skills reflected supportive behaviors (the positive response) versus nonsupportive behaviors (the negative response). Overall, the women's responses showed that they perceived of their partners as being compassionate, yet nonsupportive, and the partner's perceived of themselves likewise. Only half of the women said that their partners' coping and adaptation abilities enabled them to relinquish traditional concepts of control and focus on their own well-being. ^ The themes that emerged indicate that African American men's attitudes and behaviors regarding his female partner's diagnosis of breast cancer and his ability to cope and willingness to adapt are influenced by their ritualistic mantras, folk beliefs, religious teachings/spiritual values, existential ideologies, socioeconomic status, and environmental factors and by their established perceptions of what causes breast cancer, what the treatments and outcomes are, and how the disease affects the entire family, particularly him. These findings imply that a culturally specific intervention might be useful in educating African American men about breast cancer and their roles in supporting their female partners, physically and psychologically, during diagnosis, treatment, and recovery. ^

Roadmap for implementing the Chronic Care Model for weight management: Healthcare Institution's Response to Obesity (HIRO)

Background. Excess weight and obesity are at epidemic proportions in the United States and place individuals at increased risk for a variety of chronic conditions. Rates of diabetes, high blood pressure, coronary artery disease, stroke, cancer, and arthritis are all influenced by the presence of obesity. Small reductions in excess weight can produce significant positive clinical outcomes. Healthcare organizations have a vital role to play in the identification and management of obesity. Currently, healthcare providers do not adequately diagnose and manage excess weight in patients. Lack of skill, time, and knowledge are commonly cited as reasons for non-adherence to recommended standards of care. The Chronic Care Model offers an approach to healthcare organizations for chronic disease management. The model consists of six elements that work together to empower both providers and patients to have more productive interactions: the community, the health system itself, self-management support, delivery system design, decision support, and clinical information systems. The model and its elements may offer a framework through which healthcare organizations can adapt to support, educate, and empower providers and patients in the management of excess weight and obesity. Successful management of excess weight will reduce morbidity and mortality of many chronic conditions. Purpose. The purpose of this review is to synthesize existing research on the effectiveness of the Chronic Care Model and its elements as they relate to weight management and behaviors associated with maintaining a healthy weight. Methods: A narrative review of the literature between November 1998 and November 2008 was conducted. The review focused on clinical trials, systematic reviews, and reports related to the chronic care model or its elements and weight management, physical activity, nutrition, or diabetes. Fifty-nine articles are included in the review. Results. This review highlights the use of the Chronic Care Model and its elements that can result in improved quality of care and clinical outcomes related to weight management, physical activity, nutrition, and diabetes. Conclusions. Healthcare organizations can use the Chronic Care Model framework to implement changes within their systems to successfully address overweight and obesity in their patient populations. Specific recommendations for operationalizing the Chronic Care Model elements for weight management are presented.^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^

Adenosine induced pulmonary fibrosis and the contribution of the adenosine A2B receptor to the induction of osteopontin in a mouse model of pulmonary fibrosis

Pulmonary fibrosis is a devastating and lethal lung disease with no current cure. Research into cellular signaling pathways able to modulate aspects of pulmonary inflammation and fibrosis will aid in the development of effective therapies for its treatment. Our laboratory has generated a transgenic/knockout mouse with systemic elevations in adenosine due to the partial lack of its metabolic enzyme, adenosine deaminase (ADA). These mice spontaneously develop progressive lung inflammation and severe pulmonary fibrosis suggesting that aberrant adenosine signaling is influencing the development and/or progression of the disease in these animals. These mice also show marked increases in the pro-fibrotic mediator, osteopontin (OPN), which are reversed through ADA therapy that serves to lower lung adenosine levels and ameliorate aspects of the disease. OPN is known to be regulated by intracellular signaling pathways that can be accessed through adenosine receptors, particularly the low affinity A2BR receptor, suggesting that adenosine receptor signaling may be responsible for the induction of OPN in our model. In-vitro, adenosine and the broad spectrum adenosine receptor agonist, NECA, were able to induce a 2.5-fold increase in OPN transcripts in primary alveolar macrophages. This induction was blocked through antagonism of the A2BR receptor pharmacologically, and through the deletion of the receptor subtype in these cells genetically, supporting the hypothesis that the A2BR receptor was responsible for the induction of OPN in our model. These findings demonstrate for the first time that adenosine signaling is an important modulator of pulmonary fibrosis in ADA-deficient mice and that this is in part due to signaling through the A2BR receptor which leads to the induction of the pro-fibrotic molecule, otseopontin. ^

Homeless access to dental health care: Creation of a dental service model

This project involved developing a model for planning a dental emergency treatment center that could function as an embedded component of a shelter for the homeless population. The dental services provided by such a clinic should include treatment for tooth pain, dental caries or cavities, chipped or broken teeth, broken partials, abscessed teeth, emergency cleanings, periodontal disease or gum disease and fillings. These are the dental services that are most often sought by homeless people in hospital emergency rooms.^ The underlying assumption for this project was that the oral health needs of the homeless community can most effectively be addressed by implementing small dental clinics in existing facilities that provide shelter and other services for this population. The model described in this project identifies oral health care services that would be provided by the clinic, facility (physical plant) requirements and associated infrastructure to operate an embedded dental clinic, methods for obtaining funding, strategies of recruiting dental professionals to staff the facility, and methods to assess the outcomes of the embedded clinic strategy. As an example, this project describes a strategy for developing such an embedded clinic at San Antonio Metropolitan Ministries SAMM shelter based on recommendations from community health care leaders, managers of homeless shelters, members of the homeless community and dental professionals^

Concomitant Mycobacterium tuberculosis infection and type 2 diabetes: A descriptive model with global health implications

The type 2 diabetes (diabetes) pandemic is recognized as a threat to tuberculosis (TB) control worldwide. This secondary data analysis project estimated the contribution of diabetes to TB in a binational community on the Texas-Mexico border where both diseases occur. Newly-diagnosed TB patients > 20 years of age were prospectively enrolled at Texas-Mexico border clinics between January 2006 and November 2008. Upon enrollment, information regarding social, demographic, and medical risks for TB was collected at interview, including self-reported diabetes. In addition, self-reported diabetes was supported by blood-confirmation according to guidelines published by the American Diabetes Association (ADA). For this project, data was compared to existing statistics for TB incidence and diabetes prevalence from the corresponding general populations of each study site to estimate the relative and attributable risks of diabetes to TB. In concordance with historical sociodemographic data provided for TB patients with self-reported diabetes, our TB patients with diabetes also lacked the risk factors traditionally associated with TB (alcohol abuse, drug abuse, history of incarceration, and HIV infection); instead, the majority of our TB patients with diabetes were characterized by overweight/obesity, chronic hyperglycemia, and older median age. In addition, diabetes prevalence among our TB patients was significantly higher than in the corresponding general populations. Findings of this study will help accurately characterize TB patients with diabetes, thus aiding in the timely recognition and diagnosis of TB in a population not traditionally viewed as at-risk. We provide epidemiological and biological evidence that diabetes continues to be an increasingly important risk factor for TB.^

Process to develop a State Model Law to reduce prescription drug trafficking while protecting pain management

This paper will discuss the intersection of pill mills and the under-treatment of pain, while addressing the unintended consequence that cracking down on pill mills actually has on medical professionals' treatment of legitimate pain in clinical settings. Moreover, the impact each issue has on the spectrum of related policy, regulatory issues and legislation will be analyzed while addressing the national impact on medical care. Lastly, this paper will outline a process to develop a State Model Law on this subject. This process will include suggestions for the future and how we can move forward to adequately address public safety needs and how we can attempt to mitigate the unintended impact prescription drug trafficking has had on a patient's right to appropriate pain management. This balance is achievable and this paper will address ways we can find this elusive balancing point through the development of a State Model Law. ^

Assessment of the effect on statistical power of regression model misspecification by using techniques of mathematical statistics and simulation study

Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

Policy analysis of Texas Senate Bill 532 and the regulation of nurse practitioners in the convenience care model

Background. Retail clinics, also called convenience care clinics, have become a rapidly growing trend since their initial development in 2000. These clinics are coupled within a larger retail operation and are generally located in "big-box" discount stores such as Wal-mart or Target, grocery stores such as Publix or H-E-B, or in retail pharmacies such as CVS or Walgreen's (Deloitte Center for Health Solutions, 2008). Care is typically provided by nurse practitioners. Research indicates that this new health care delivery system reduces cost, raises quality, and provides a means of access to the uninsured population (e.g., Deloitte Center for Health Solutions, 2008; Convenient Care Association, 2008a, 2008b, 2008c; Hansen-Turton, Miller, Nash, Ryan, Counts, 2007; Salinsky, 2009; Scott, 2006; Ahmed & Fincham, 2010). Some healthcare analysts even suggest that retail clinics offer a feasible solution to the shortage of primary care physicians facing the nation (AHRQ Health Care Innovations Exchange, 2010). ^ The development and performance of retail clinics is heavily dependent upon individual state policies regulating NPs. Texas currently has one of the most highly regulated practice environments for NPs (Stout & Elton, 2007; Hammonds, 2008). In September 2009, Texas passed Senate Bill 532 addressing the scope of practice of nurse practitioners in the convenience care model. In comparison to other states, this law still heavily regulates nurse practitioners. However, little research has been conducted to evaluate the impact of state laws regulating nurse practitioners on the development and performance of retail clinics. ^ Objectives. (1). To describe the potential impact that SB 532 has on retail clinic performance. (2). To discuss the effectiveness, efficiency, and equity of the convenience care model. (3). To describe possible alternatives to Texas' nurse practitioner scope of practice guidelines as delineated in Texas Senate Bill 532. (4). To describe the type of nurse practitioner state regulation (i.e. independent, light, moderate, or heavy) that best promotes the convenience care model. ^ Methods. State regulations governing nurse practitioners can be characterized as independent, light, moderate, and heavy. Four state NP regulatory types and retail clinic performance were compared and contrasted to that of Texas regulations using Dunn and Aday's theoretical models for conducting policy analysis and evaluating healthcare systems. Criteria for measurement included effectiveness, efficiency, and equity. Comparison states were Arizona (Independent), Minnesota (Light), Massachusetts (Moderate), and Florida (Heavy). ^ Results. A comparative states analysis of Texas SB 532 and alternative NP scope of practice guidelines among the four states: Arizona, Florida, Massachusetts, and Minnesota, indicated that SB 532 has minimal potential to affect the shortage of primary care providers in the state. Although SB 532 may increase the number of NPs a physician may supervise, NPs are still heavily restricted in their scope of practice and limited in their ability to act as primary care providers. Arizona's example of independent NP practice provided the best alternative to affect the shortage of PCPs in Texas as evidenced by a lower uninsured rate and less ED visits per 1,000 population. A survey of comparison states suggests that retail clinics thrive in states that more heavily restrict NP scope of practice as opposed to those that are more permissive, with the exception of Arizona. An analysis of effectiveness, efficiency, and equity of the convenience care model indicates that retail clinics perform well in the areas of effectiveness and efficiency; but, fall short in the area of equity. ^ Conclusion. Texas Senate 532 represents an incremental step towards addressing the problem of a shortage of PCPs in the state. A comparative policy analysis of the other four states with varying degrees of NP scope of practice indicate that a more aggressive policy allowing for independent NP practice will be needed to achieve positive changes in health outcomes. Retail clinics pose a temporary solution to the shortage of PCPs and will need to expand their locations to poorer regions and incorporate some chronic care to obtain measurable health outcomes. ^

Effects of informative censoring on the hazard function: Application to the proportional hazards regression model

The standard analyses of survival data involve the assumption that survival and censoring are independent. When censoring and survival are related, the phenomenon is known as informative censoring. This paper examines the effects of an informative censoring assumption on the hazard function and the estimated hazard ratio provided by the Cox model.^ The limiting factor in all analyses of informative censoring is the problem of non-identifiability. Non-identifiability implies that it is impossible to distinguish a situation in which censoring and death are independent from one in which there is dependence. However, it is possible that informative censoring occurs. Examination of the literature indicates how others have approached the problem and covers the relevant theoretical background.^ Three models are examined in detail. The first model uses conditionally independent marginal hazards to obtain the unconditional survival function and hazards. The second model is based on the Gumbel Type A method for combining independent marginal distributions into bivariate distributions using a dependency parameter. Finally, a formulation based on a compartmental model is presented and its results described. For the latter two approaches, the resulting hazard is used in the Cox model in a simulation study.^ The unconditional survival distribution formed from the first model involves dependency, but the crude hazard resulting from this unconditional distribution is identical to the marginal hazard, and inferences based on the hazard are valid. The hazard ratios formed from two distributions following the Gumbel Type A model are biased by a factor dependent on the amount of censoring in the two populations and the strength of the dependency of death and censoring in the two populations. The Cox model estimates this biased hazard ratio. In general, the hazard resulting from the compartmental model is not constant, even if the individual marginal hazards are constant, unless censoring is non-informative. The hazard ratio tends to a specific limit.^ Methods of evaluating situations in which informative censoring is present are described, and the relative utility of the three models examined is discussed. ^

Development of a conceptual model for mass gatherings

In making the arrangements for the visit of Pope John Paul II to San Antonio, Texas, in September, 1987, it was discovered that no comprehensive documents or guidelines are available in the public sector for planning such an event. It was not clear which, if any, laws applied. The literature describes rock concerts, papal masses, and civil disorders. These events are held in stadia, and in the open. There was little agreement on what services, if any, were needed to protect the public's health and the environment; or if needed, how services should be provided, or by whom.^ A literature review and bibliography are given to provide greater understanding of the variety of mass gatherings and the many factors that impinge on temporary groups while away from their homes. Descriptions of past mass gatherings in terms of personnel ratios are provided. This study develops a conceptual model which delineates some of the known parameters necessary for successfully conducting a mass gathering. A study of one such site is given.^ Provisions for public wellness and freedom from disease at a mass gathering include adequate water (fluids), food, sanitary facilities, security, transportation, and medical services. The determination of adequacy of these provisions is discussed. Methods of determining the use of provided facilities are given. ^