A Simple Model of Credit Rationing with Information Externalities

Credit-rationing model similar to Stiglitz and Weiss [1981] is combined with the information externality model of Lang and Nakamura [1993] to examine the properties of mortgage markets characterized by both adverse selection and information externalities. In a credit-rationing model, additional information increases lenders ability to distinguish risks, which leads to increased supply of credit. According to Lang and Nakamura, larger supply of credit leads to additional market activities and therefore, greater information. The combination of these two propositions leads to a general equilibrium model. This paper describes properties of this general equilibrium model. The paper provides another sufficient condition in which credit rationing falls with information. In that, external information improves the accuracy of equity-risk assessments of properties, which reduces credit rationing. Contrary to intuition, this increased accuracy raises the mortgage interest rate. This allows clarifying the trade offs associated with reduced credit rationing and the quality of applicant pool.

Impact of a modified dietary plan on the health related quality of life of minority participants in the Women's Healthy Eating and Living (WHEL) Study

Advances in medical technology, in genetics, and in clinical research have led to early detection of cancer, precise diagnosis, and effective treatment modalities. Decline in cancer incidence and mortality due to cancer has led to increased number of long-term survivors. However, the ethnic minority population has not experienced this decline and still continues to carry a disparate proportion of the cancer burden. Majority of the clinical research including survivorship studies have recruited and continue to recruit a convenient sample of middle- to upper-class Caucasian survivors. Thus, minorities are underrepresented in cancer research in terms of both clinical studies and in health related quality of life (HRQOL) studies. ^ Life style and diet have been associated with increased risk of breast cancer. High vegetable low fat diet has been shown to reduce recurrence of breast cancer and early death. The Women's Healthy Eating and Living Study is an ongoing multi-site randomized controlled trial that is evaluating the high-vegetable low fat diet in reducing the recurrence of breast cancer and early death. The purpose of this dissertation was to (1) compare the impact of the modified diet on the HRQOL during the first 12-month period on specific Minorities and matched Caucasians; (2) identify predictors that significantly impact the HRQOL of the study participants; and (3) using the structural equation modeling assess the impact of nutrition on the HRQOL of the intervention group participants. Findings suggest that there are no significant differences in change in HRQOL between Minorities and Caucasians; between Minorities in the intervention group and those in the comparison group; and between women in the intervention group and those in the comparison group. Minority indicator variable and Intervention/Comparison group indicator variable were not found to be good predictors of HRQOL. Although the structural equation models suggested viable representation of the relationship between the antecedent variables, the mediating variables and the two outcome variables, the impact of nutrition was not statistically significant to be included in the model. This dissertation, by analyzing the HRQOL of minorities in the WHEL Study, attempted to add to the knowledge base specific to minority cancer survivors. ^

Airliner cabin air quality exposure assessment

The airliner cabin environment and its effects on occupant health have not been fully characterized. This dissertation is: (1) A review of airliner environmental control systems (ECSs) that modulate the ventilation, temperature, relative humidity (RH), and barometric pressure (PB) of the cabin environment---variables related to occupant comfort and health. (2) A review and assessment of the methods and findings of key cabin air quality (CAQ) investigations. Several significant deficiencies impede the drawing of inferences about CAQ, e.g., lack of detail about investigative methods, differences in methods between investigations, limited assessment of CAQ variables, small sample sizes, and technological deficiencies of data collection. (3) A comprehensive evaluation of the methods used in the subsequent NIOSH-FAA Airliner CAQ Exposure Assessment Feasibility Study (STUDY) in which this author participated. A number of problems were identified which limit the usefulness of the data. (4) An analysis of the reliable 10-flight STUDY data. Univariate and multivariate methods applied to CO2 (a surrogate for air contaminants), temperature, RH, and PB, in association with percent passenger load, ventilation system, flight duration, airliner body type, and measurement location within the cabin, revealed neither the measured values nor their variability exceeded established health-based exposure limits. Regression analyses suggest CO2, temperature, and RH were affected by percent passenger load. In-flight measurements of CO2 and RH were relatively independent of ventilation system type or flight duration. Cabin temperature was associated with percent passenger load, ventilation system type, and flight duration. (5) A synthesis of the implications of the airliner ECS and cabin O2 environment on occupant health. A model was developed to predict consequences of the airliner cabin pressure altitude 8,000 ft limit and resulting model-estimated PO2 on cardiopulmonary status. Based on the PB, altitude, and environmental data derived from the 10 STUDY flights, the predicted PaO2 of adults with COPD, or elderly adults with or without COPD, breathing ambient cabin air could be < 55 mm Hg (SaO2 < 88%). Reduction in cabin PB found in the STUDY flights could aggravate various medical conditions and require the use of in-flight supplemental O2. ^

Interrelationships between the structural and functional aspects of social relationships, comorbidity and health related quality of life in breast cancer survivors

It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

Federally regulated institutional review boards: The aspects of a "model" IRB---Is the current system in need of a tune up or complete overhaul?

Institutional Review Boards (IRBs) are the primary gatekeepers for the protection of ethical standards of federally regulated research on human subjects in this country. This paper focuses on what general, broad measures that may be instituted or enhanced to exemplify a "model IRB". This is done by examining the current regulatory standards of federally regulated IRBs, not private or commercial boards, and how many of those standards have been found either inadequate or not generally understood or followed. The analysis includes suggestions on how to bring about changes in order to make the IRB process more efficient, less subject to litigation, and create standardized educational protocols for members. The paper also considers how to include better oversight for multi-center research, increased centralization of IRBs, utilization of Data Safety Monitoring Boards when necessary, payment for research protocol review, voluntary accreditation, and the institution of evaluation/quality assurance programs. ^ This is a policy study utilizing secondary analysis of publicly available data. Therefore, the research for this paper focuses on scholarly medical/legal journals, web information from the Department of Health and Human Services, Federal Drug Administration, and the Office of the Inspector General, Accreditation Programs, law review articles, and current regulations applicable to the relevant portions of the paper. ^ Two issues are found to be consistently cited by the literature as major concerns. One is a need for basic, standardized educational requirements across all IRBs and its members, and secondly, much stricter and more informed management of continuing research. There is no federally regulated formal education system currently in place for IRB members, except for certain NIH-based trials. Also, IRBs are not keeping up with research once a study has begun, and although regulated to do so, it does not appear to be a great priority. This is the area most in danger of increased litigation. Other issues such as voluntary accreditation and outcomes evaluation are slowing gaining steam as the processes are becoming more available and more sought after, such as JCAHO accrediting of hospitals. ^ Adopting the principles discussed in this paper should promote better use of a local IRBs time, money, and expertise for protecting the vulnerable population in their care. Without further improvements to the system, there is concern that private and commercial IRBs will attempt to create a monopoly on much of the clinical research in the future as they are not as heavily regulated and can therefore offer companies quicker and more convenient reviews. IRBs need to consider the advantages of charging for their unique and important services as a cost of doing business. More importantly, there must be a minimum standard of education for all IRB members in the area of the ethical standards of human research and a greater emphasis placed on the follow-up of ongoing research as this is the most critical time for study participants and may soon lead to the largest area for litigation. Additionally, there should be a centralized IRB for multi-site trials or a study website with important information affecting the trial in real time. There needs to be development of standards and metrics to assess the performance of the IRBs for quality assurance and outcome evaluations. The boards should not be content to run the business of human subjects' research without determining how well that function is actually being carried out. It is important that federally regulated IRBs provide excellence in human research and promote those values most important to the public at large.^

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

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.^

A qualitative analysis of leadership styles and the selection of quality improvement in primary care practice

In the Practice Change Model, physicians act as key stakeholders, people who have both an investment in the practice and the capacity to influence how the practice performs. This leadership role is critical to the development and change of the practice. Leadership roles and effectiveness are an important factor in quality improvement in primary care practices.^ The study conducted involved a comparative case study analysis to identify leadership roles and the relationship between leadership roles and the number and type of quality improvement strategies adopted during a Practice Change Model-based intervention study. The research utilized secondary data from four primary care practices with various leadership styles. The practices are located in the San Antonio region and serve a large Hispanic population. The data was collected by two ABC Project Facilitators from each practice during a 12-month period including Key Informant Interviews (all staff members), MAP (Multi-method Assessment Process), and Practice Facilitation field notes. This data was used to evaluate leadership styles, management within the practice, and intervention tools that were implemented. The chief steps will be (1) to analyze if the leader-member relations contribute to the type of quality improvement strategy or strategies selected (2) to investigate if leader-position power contributes to the number of strategies selected and the type of strategy selected (3) and to explore whether the task structure varies across the four primary care practices.^ The research found that involving more members of the clinic staff in decision-making, building bridges between organizational staff and clinical staff, and task structure are all associated with the direct influence on the number and type of quality improvement strategies implemented in primary care practice.^ Although this research only investigated leadership styles of four different practices, it will offer future guidance on how to establish the priorities and implementation of quality improvement strategies that will have the greatest impact on patient care improvement. ^

Health information exchange: Using metrics to address quality of care and return on investment

Health Information Exchange (HIE) will play a key part in our nation’s effort to improve healthcare. The evidence of HIEs transformational role in healthcare delivery systems is quite limited. The lack of such evidence led us to explore what exists in the healthcare industry that may provide evidence of effectiveness and efficiency of HIEs. The objective of the study was to find out how many fully functional HIEs are using any measurements or metrics to gauge impact of HIE on quality improvement (QI) and on return on investment (ROI).^ A web-based survey was used to determine the number of operational HIEs using metrics for QI and ROI. Our study highlights the fact that only 50 percent of the HIEs who responded use or plan to use metrics. However, 95 percent of the respondents believed HIEs improve quality of care while only 56 percent believed HIE showed positive ROI. Although operational HIEs present numerous opportunities to demonstrate the business model for improving health care quality, evidence to document the impact of HIEs is lacking. ^

Can accreditation work as a tool for quality improvement in public health? A critical review

Public health departments play an important role in promoting and preserving the health of communities. The lack of a system to ensure their quality and accountability led to the development of a national voluntary accreditation program by Public Health Accreditation Board (PHAB). The concept that accreditation will lead to quality improvement in public health which will ultimately lead to healthy communities seems intuitive but lacks a robust body of evidence. A critical review of literature was conducted to explore if accreditation can lead to quality improvement in public health. The articles were selected from publically available databases using a specific set of criteria for inclusion, exclusion, and appraisal. To understand the relationship between accreditation and quality improvement, the potential strengths and limitations of accreditation process were evaluated. Recommendations for best practices are suggested so that public health accreditation can yield maximum benefits. A logic model framework to help depict the impact of accreditation on various levels of public health outcomes is also discussed in this thesis. The literature review shows that existing accreditation programs in other industries show limited but encouraging evidence that accreditation will improve quality and strengthen the delivery of public health services. While progress in introducing accreditation in public health can be informed by other accredited industries, the public health field has its own set of challenges. Providing incentives, creating financing strategies, and having a strong leadership will allow greater access to accreditation by all public health departments. The suggested recommendations include that continuous evaluation, public participation, systems approach, clear vision, and dynamic standards should become hallmarks of the accreditation process. Understanding the link between accreditation, quality improvement, and health outcomes will influence the successful adoption and implementation of the public health accreditation program. This review of literature suggests that accreditation is an important step in improving the quality of public health departments and in ultimately improving the health of communities. However, accreditation should be considered in an integrated system of tools and approaches to improve the public health practice. Hence, it is a means to an end - not an end unto itself.^

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. ^

Distribution of quality adjusted life expectancy: A systems approach

Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

The role of a nursing home administrator's education in influencing quality of care in US nursing homes

Nursing home literature links poor management practices to poor quality of care and resident outcomes. Since Nursing Home Administrators (NHAs) require an array of skills to perform their role, it is important to explore what makes a NHA effective. This research fills a gap in the literature and provides a possible option to improve the quality of care in nursing homes. Purpose of the study. The study examines whether NHAs with advanced education (defined as a Masters degree or more) are associated with better quality of care in licensed nursing homes (NHs). Design and Methods. Data was derived from the CDC’s 2004 National Nursing Home Survey, which is a representative sample of NHs across the US. A Donabedian- inspired structure-process-outcomes study model was created to explain how education relates to quality of care. Quality of care was defined as onsite oral care, employee influenza vaccination rates and staff recognition programs. Statistical analyses included multivariate logistic regression; covariates included facility-level variables used in similar peer-reviewed research but also included select measures from the Area Resource File to control for county-level factors. Results. Descriptive and analytical analyses confirm that NHAs with a Bachelor’s degree, Associate degree or high school diploma perform less well than NHAs with a Masters degree or more. NHAs with advanced education are more likely to have onsite dental care and recognition programs for staff than NHAs with a Bachelor’s degree (or less). Also NHAs with less than graduate education are more likely to provide off-site dental care. Employee vaccination rates are not impacted by education. Adding certification, tenure or years of experience to a NHA with advanced education gives them an advantage. In fact, certification and experience alone do not have a positive relationship to care indicators; however adding these to advanced education produces a significant result. Implications. This research provides preliminary evidence that advanced education for the NHA is associated with better quality of care. If future research can confirm these findings, there is merit in revisiting the qualifications. Education can be a legitimate option to support quality improvement efforts in US nursing homes. ^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^