WGU D514 Analytical Methods of Healthcare Leaders Detailed Guide Exam 2026

WGU D514 Analytical Methods of Healthcare Leaders Detailed Guide Exam 2026 ANOVA test - -Analysis of variance (ANOVA) may be used in research studies where there are two or more groups to compare. Chi-square tests - -Chi-square tests determine if an association exists between two categorical variables. Control group - -In a healthcare environment, this group of patients does not receive the treatment that is being studied. Experimental group - -This group of patients receives the treatment being studied with follow-up observation to determine the effect of the treatment. F-test - -The F-test is designed to test if two population variances are equal. The ratio of the two variances is compared. If they are equal, the ratio of the variances will be 1. Frequency - -Frequencies measure how often a particular value occurs to assess the importance of a value or check the variation of the values in a study. Hypothesis - -A proposed explanation for an observation that leads to a prediction. Through investigation and the use of statistical data, those doing the study will either confirm or reject the hypothesis. Testing the hypothesis will show if there is a link (or not) between two or more variables. Integrity - -Research always makes some assumptions, depending on the type of method used. Research assumptions must be identified to determine possible breaches of integrity. Interval data - -Interval data includes units of equal size, such as IQ results. There is no zero point. An example of interval scale is time: Time is measured in 24 hours in each day; the time between each hour is the same, 60 minutes. Mean - -Mean is the arithmetic average. Divide the sum of all scores by the total number of scores. WGU D514 WGU D514 Median - -Median is the midpoint of the distribution of values, or the point above or below which 50 percent of the values fall. Methods section components - -When analyzing the quality of a study, a careful evaluation of the research methods can reveal critical details about population and sample, covariables and hypothesis, data presentation, statistical analysis, and study limitations. Misleading statistics - -Interpreting and presenting the results of data analysis affords many opportunities for accidental or deliberate misrepresentations of data. Common examples include implying causation, extrapolating beyond the reasonable, relying on a biased or incomplete sample, and using inappropriate graphical representations. Mode - -Mode is the value that occurs most frequently in the data. Multivariate regression analyses - -Multivariate regression analyses can be used to analyze and adjust risk. This analysis model contrasts each measured factor to the patient's risk of a particular outcome. Nominal data - -Nominal data can be measured as a frequency or percentage, and the mean of these data cannot be calculated. Nominal data in healthcare might include demographic information about patients. The word nominal means "pertaining to a name." Ordinal data - -Ordinal data can be measured as a frequency, and the mean of ordinal data is often calculated. Ordinal data in healthcare might include patient satisfaction surveys using a Likert scale. The word ordinal means to "put in order." Parametric and nonparametric tests - -Parametric tests are based on probability distributions. Nonparametric tests are used when data are not normally distributed. Pearson's correlation - -Pearson's correlation is used with interval and ordinal scale data and determines the extent to which a change in one variable tends to be associated with a change in another. Qualitative research methods - -Qualitative research is aimed at understanding perceptions, perspectives, interpretations, and opinions. Qualitative research methods often include questionnaires, interviews, written documents, observations, and focus groups. Ratio data - -Divide one quantity by another, and you have a value. You will have a proportion, a percentage or a rate. Reliability, validity, and analysis of questionnaires - -Questionnaires can be evaluated for reliability based on their consistency (stability) or repeatability over time; questionnaires are valid if they measure or record what they purport to measure. Data WGU D514 WGU D514 from questionnaires may then be grouped according to nominal, ordinal, or interval or ratio data. Research - -Research can inform decisions regarding the development and efficacy of new processes, systems, technologies, environments, and organizational structures to support operations. Research platform - -Research is built on a platform of previous knowledge, the scientific method. Risk adjustment - -Risk adjustment is essential for comparing data across systems, especially among patients with varying comorbid diseases and complex treatment modalities. Multivariate regression analyses can be used to analyze and adjust risk. This analysis model looks at each measured factor to the patient's risk of a particular outcome. Risk of error and harm - -Studies should include an analysis of any sources of error as well as a thorough explanation of the consequences associated with a particular study treatment. Sample size - -The design of the study provides insight into an appropriate number and volume of each variable. The calculation of statistical confidence factors informs the validity testing of the study sample size. Standard Deviation - -Standard deviation determines the amount of variance in a set of data and evaluates the degree to which each case deviates from the average, or mean. Statistical significance - -The observation is statistically significant if the null hypothesis is rejected. In a research study, the null hypothesis states there is no association between the independent and dependent variables in a study. t-test - -The t-test helps the researcher to compare whether two groups have different average values. A paired t-test is used when each observation in one group is paired with a related observation in another. Variables - -The independent variable is the factor that is directly manipulated by the researchers. The dependent variable is the measurable variable that depends on the independent variable. Master Population/Patient Index (MPI) - -Assigns specific medical record number to avoid duplicate patient records. Includes patient's demographic information and dates of encounters. Disease Registries - -Secondary data gathered on patient diagnosis, condition, and procedure. Used for public health purposes and documenting disease prevalence. WGU D514 WGU D514 Length of Stay/Average Length of Stay (ALOS) - -Average number of days a patient spends in the hospital. Tracked to gauge the efficiency of a healthcare facility. Center for Medicare and Medicaid Services (CMS) - -Responsible for developing U.S. healthcare policy; administers the Medicare program and federal portion of Medicaid program. HRRP - -Affordable Care Act (ACA) added a section to Social Security Act in 2012, requiring CMS to reduce payments to hospitals with excessive readmissions. Data gathered is response to the Hospital Readmissions Reduction Program (HRRP), which is a Medicare value-based purchasing program. Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Scores - -An effective indicator that measures quality provided, communication from providers, and other aspects of care delivery. It affects clinical outcomes, patient retention, and medical malpractice claims. Mortality after acute MIs (myocardial infarctions) - -Reflects the health status of cardiac patients and effectiveness of services. Central Line Associated Bloodstream Infections (CLABSI) - -Data tracked to ensure best practices in treating patients receiving repeated IV medication or fluids. Catheter can become infected over time if guidelines preventing bacterial contamination are not followed. Pain Management - -Tracking this data helps providers understand why certain patients improve faster than others, and why some are more vulnerable to depression due to chronic pain or addiction. Hospital Quietness & Cleanliness - -Measured in patient satisfaction surveys as a subjective indicator of hospital environment. Post-Op Infections - -This data useful as a quality measurement to improve care during and after surgery. Pressure Ulcer Rates - -Data tracked on incidence, prevalence, and facility-acquired rates to improve quality of care and develop best practices to address skin breakdown. Catheter Associated Urinary Tract Infection Rates (CAUTI) - -This hospital-acquired infection is tracked and reported to Medicare. One of the first hospital-acquired conditions selected for nonpayment by Medicare. Staff Performance, Turnover, Absenteeism - -Organizations track this human resource data to optimize employee skill sets and build a stronger organizational culture. WGU D514 WGU D514 Accounts Receivable and Cost Data - -Tracking this data ensures adequate resources for long- and short-term goals and financial planning. HRSA Data: Health Resources and Services Administration - -It is the primary federal agency for improving healthcare to the geographically isolated, and economically or medically vulnerable. Health Payment Systems data - -Data pulled from coding/billing departments. MEPS data from CMS: The Medical Expenditure Panel Survey (MEPS) - -Administered by Centers for Medicare & Medicaid Services (CMS). Surveys families, individuals, providers, employers in the U.S. Gathers data on cost, use of healthcare services, and health insurance coverage. NIH data: The National Institutes of Health (NIH) - -U.S. Medical Research Agency is part of the Department of Health and Human Services. The Joint Commission (TJC) data - -Through its accreditation process it requires the gathering and reporting of specific data to demonstrate safety, quality care, and performance improvement in healthcare organizations. Surveillance records - -These records are kept and reviewed to maintain health history on employees who may be exposed to hazardous materials, eliminate causes of exposure and prevent medical issues from developing. Contribute to worksite health and safety programs. Medicare Provider Analysis and Review (MEDPAR) - -Acute care and skilled nursing facility claim data on Medicare patients. National Practitioner Data Bank (NPDB) - -Database queried as part of physician credentialing process when applying for medical staff privileges and every two years afterward. It contains data on medical malpractice, adverse licensure actions, suspensions, and professional review actions. Public Health databases - -Holds data on incidence and prevalence of diseases; survival statistics; high-risk populations; and tracks trends over time. Data is gathered from medical records, surveys, and interviews. National Center for Health Statistics (NCHS) is responsible for these databases. National Center for Health Statistics (NCHS) - -Operates through the Center for Disease Control (CDC); includes vital statistics data such as birth, death, marriages, divorces, and fetal deaths. National Healthcare Survey - -Answer key questions of interest to healthcare policy makers, public health professionals, and researchers. Topics include quality care, resources, safety, and disparities. WGU D514 WGU D514 Relational Databases - -This is the most common of all the different types of databases. Data in a relational database is stored in various data tables. Each table has a key field that is used to connect it to other tables. Hence all the tables are related to each other through several key fields. Relational databases have advantages because the data is entered one time, which improves the consistency and quality of data. Searching can be done across data tables, making it easier to connect information. The relational database allows the data administrator to control access to certain tables in order to provide security for the data in the database. Flat File Database - -A flat file database is a database designed around a single table. The flat file design puts all database information in one table, or list, with fields to represent all parameters. A flat file may contain many fields, often with duplicate data that are prone to data corruption. If you decide to merge data between two flat files, you need to copy and paste relevant information from one file to the other. There is no automation between flat files. This opens the possibility of data error when moving data among files. Hierarchical Database Model - -This type of database structures data similar to the layout of an organizational chart. It is good for data storage but not versatile. There is a one-to-many relationship of data. In a hierarchical data model, access to data starts at the top of the hierarchy and moves downward. Object-Oriented Database - -Object-oriented databases handle text, images, audio, video, and other objects. In this model, images and other nontext items are stored as objects with hierarchy and a navigational programming style. De-Identified Database - -You may see this term. It refers to removing all identifying patient information. No information can be connected back to a specific patient. It may be used in research to protect participants and human subjects. Network Database Model - -Data is connected through pointers, and unlike the hierarchical model that has one "parent" to one "child," a "child" can have multiple "parents." Multiple records can be linked to the same owner. This model is more difficult to implement and maintain but more flexible than the hierarchical model. It allows many to-many relationships. Multidimensional Database - -This is a hybrid between hierarchical and relational, capturing the benefits of both so that large amounts of data can be processed quickly. You have the ability to process various data attributes at a time, including within various hierarchies and levels. If you need large amounts of data in a short time, this database would be useful to you. Transactional Database - -This is a database management system that has the capability to roll back or undo a database transaction or operation if it is not completed WGU D514 WGU D514 appropriately. Although this was a unique capability several decades ago, today, the majority of relational database systems support transactional database operations. Data Warehouses - -But, they want to be able to share their data among all of their facilities. They would have a data warehouse into which all of these different technologies could be loaded, and a common language standard would be used in order for all of these different systems to "talk" to each other, to "translate" the data into a common language. By doing this, data could be pulled from all sources for reports and stats. Data warehouses are critical to the success of analytics, because they hold huge amounts of data to be used, and having the common language allows that. It is all very techy on that end, but makes analytics possible for managers and others running reports at the operational level. Rollup Query - -It is not a type of database; a rollup query is a process that drills down into data at many levels, giving the researcher a higher-level view of the data. This would be very beneficial when performing data analytics and looking at huge amounts of data. Data Warehouse - -A business intelligence analyst at a multistate healthcare system is developing reports for clinical quality-improvement projects and best practice guideline development. The best practice guidelines will be used across the entire multistate system. Which type of database should be used to gather and analyze data for the reports needed? Trauma registry - -The chief medical officer of emergency services is investigating the number of gunshot victims seen in their emergency department in the past two years, for their hospital. Which type of database should be used to locate this data? Object oriented - -A group of speech pathologists from several facilities within the same large healthcare system is doing a research study on children who stutter. They want to share their audio files across their interoperable databases as they work on this study together. Which database should they use? True - -If you were constructing a database for a research project, de-identifying patient information would be an important consideration in protecting patient privacy. True or False Research identified - -A clinical research associate is comparing data on study patients and their response to a clinical-trial drug for patients with fibromyalgia. The patients were enrolled six months ago. The associate is comparing data from when the patients were first enrolled in the study to today. Which type of database is the associate using? WGU D514 WGU D514 Current lengths of stay for patients after CABG; this data will provide a baseline trend of current practice. Number of providers providing direct care for patients post CABG per day; knowledge of the extent of human resources used for this patient population will be used to analyze current provider service patterns - -The vice president of operations of a medical facility in Jackson, Mississippi, seeks to improve the efficiency, effectiveness, equity, and timeliness of patient care at the facility. Over the past month, 150 patients have undergone coronary artery bypass graft (CABG) surgery. These patients require significant resources and are occupying the majority of beds in the facility, on average, with an eight-day post-procedure length of stay. Currently, the facility has no established standardized protocol guiding physicians on postoperative care. The chief medical officer (CMO) is concerned about the situation and sees this as an opportunity to perform data analysis and make recommendations based on the results. The vice president, CMO, and Operations Team are meeting to determine what types of data to gather and analyze to develop recommendations to present to their cardiothoracic surgeons. Their goal is to develop standardized protocols for the care management of this patient population and benchmark the results over time with external standards. The following web link is an additional reference in determining types of data to be considered: "Patient Education: Recovery After Coronary Artery Bypass Graft Surgery (CABG) (Beyond the Basics)" Calculate the descriptive statistics of the presented values and consider a course of action based on the results. Dental check-ups should be scheduled in tandem with physician visits. Americans do not view oral care as important as taking care of other parts of the body. - -The Centers for Disease Control and Prevention (CDC) has a division of oral health. Its website offers numerous resources, reports, and data-gathering tools for any community or agency interested in developing a more comprehensive oral healthcare plan. The community wellness coordinator for a primary care network wants to determine whether initial education programs for pediatricians and staff will have an impact on oral hygiene. This project includes a coordinated patent education program about the importance of regular dental and physician visits. Based on a review of the research studies, which of the following statements are relevant to the community wellness coordinator? Categorical variables - -The value is in the name or label. Types of cancers (breast, skin, lung, etc.) are categorical variables. Confounding Variable - -It obscures the effect of another variable. The researcher may initially believe the variable will influence the research, but findings show it does not. As WGU D514 WGU D514 a researcher, you may not be able to control its influence on the result of the research, but you should have an awareness that it is impacting your results and not allow it to skew your data. Continuous variable - -This is also known as an interval variable. There is a meaningful difference between values. An example is body temperature. Databases - -A well-designed healthcare database captures data to support the organization's analysis and comparison of safety, quality, effectiveness, efficiency, timeliness, and efficacy of actual care and services delivered to the patient over time. Data warehouses - -These assimilate data from multiple transaction systems. Data warehouses can be used to distinguish larger trends in data from multiple sources Dichotomous variable - -This is also called a binary variable. It occurs in one of two possible states, for example, male or female. The patient has cancer or does not. Disease registries - -These are a hybrid between transaction systems and data warehouses. They are designed for tracking explicitly defined data at a case-specific level. Some examples are trauma registries to track emergency department data, cancer registries, immunizations registries, and numerous others. Errors - -Incorrect application of a statistical test can result in a type I error, which occurs when a null hypothesis is rejected when it should have been accepted. A type II error is experienced when the alternative hypothesis is rejected when it should have been accepted. Measurement and decision support - -Measurement is used within an organization to monitor improvements in systems and processes through analysis of current performance trends, identify key opportunities, and consider leading practices informed by new research-based knowledge. Decision support provides an information platform to evaluate leading, lagging, and real-time performance measures. Outcome evaluation - -An outcome evaluation focuses on the end result of a specific program or initiative, generally clinically measured by improvements in morbidity, mortality, or vital measures of symptoms, signs, or physiologic indicators. Quality improvement - -Quality improvement is measured internally and externally using various benchmarks and indicators. These indicators are quantified by proportions, percentages, ratios, means, medians, and counts to measure processes, perspectives, and outcomes aligned with a certain initiative or decision. Quality measures - -In today's healthcare environment, administrators receive numerous quality reports on a regular basis. These reports are generated for internal quality improvement projects, for mandated external reports to government agencies, and for compliance with accrediting body requirements. As a value-based purchasing WGU D514 WGU D514 model evolves in healthcare, quality measures become pivotal operational "pulse checks" to administrators. Statistical testing and treatment - -The basis of statistical testing is whether or not the study results have a proven relationship to a change in processes or care modalities. Results that are statistically significant do not automatically indicate clinical significance. Transaction systems - -Transaction systems divide data according to individual operations. The data stored by transaction systems is granular and based on specialized systems. Risk adjustment is used in all major public programs offering health coverage in the United States—including Medicare Advantage (MA), Medicare Part D, and state Medicaid managed-care programs. Multivariate regression is a statistical technique that produces an equation or model measuring the statistical relationship between patient characteristics and the cost of care. For population health initiatives, you may use a data warehouse to compare care outcomes on separate cohorts of patients and evaluate healthcare and costs. Changes to regression models do as much or more to increase explanatory power as do additional data sources. Adding more risk factors, using a different time frame, changes to the treatment of the highest-cost cases, and including prior use or expenditures are examples of changing the regression model. - -Risk adjustment refers to using statistical methods to account for patient factors associated with a greater vulnerability of certain outcomes. Statistical risk adjustment is often used for performance measures. Numerous data sources are used for risk adjustment, such as demographic data, self reported health status of patients, laboratory and clinical data, and previous healthcare expenditures. A formula is developed to calculate risk scores based on consequences (e.g., clinical or financial outcomes) expected in one cohort of patients compared to another with similar factors. Risk adjustment may also be used for process measurements, such as subsets of patients that should all receive certain lab tests. Several types of research methods are used for risk adjustment, the most common being multivariate regression. Based on the reading, which statements convey risk adjustment? Risk adjustment is intended to counteract the incentive for plans to make their plan more attractive to patients who are low-risk and less attractive to patients with greater healthcare needs, among both potential enrollees and current members. - -Risk adjustment refers to using statistical methods to account for patient factors associated with a greater vulnerability of certain outcomes. Statistical risk adjustment is often used for performance measures. WGU D514 WGU D514 Numerous data sources are used for risk adjustment, such as demographic data, self reported health status of patients, laboratory and clinical data, and previous healthcare expenditures. A formula is developed to calculate risk scores based on consequences (e.g., clinical or financial outcomes) expected in one cohort of patients compared to another with similar factors. Risk adjustment may also be used for process measurements, such as subsets of patients that should all receive certain lab tests. Several types of research methods are used for risk adjustment, the most common being multivariate regression. Based on the reading, which statements convey risk adjustment? Nonmaleficence Beneficence - -You are a physician working in a large, private radiology practice, and one of your senior partners who has been an invaluable mentor (this partner hired you originally), colleague, and friend, has been showing subtle signs of forgetfulness and minor lapses when interpreting scans. You ask him if there is anything going on, and he tells you that he has been a little tired lately, and a little time off will do wonders. You let it go, and several weeks later, he misses an obvious mass on a lung scan that results in a delay in diagnosis and treatment of a pulmonary malignancy. What could be the ethical issues here, if you choose to say or do nothing? Two may apply. Plagiarism Avoidance - -A small rural clinic is applying for a grant to fund a program to address the methamphetamine problem they are experiencing in their community. The research proposal must be original and include a literature review that cites previous research findings and details the benefits anticipated for this research study. Which ethical consideration is described in this situation? Justice - -An endocrinologist is asked to refer patients for inclusion in a clinical trial of a new drug for diabetic patients. This is a national study, and the endocrinologist has been asked to refer 25 patients. There are more than 25 patients who would be appropriate for the study. The endocrinologist knows the patients personally and feels they may be biased in selecting them. The endocrinologist asks the risk management manager at the hospital, who frequently performs research studies for reports, to review the patients that meet the criteria and select 25 for the study. Which ethical principle is the endocrinologist exhibiting by asking the risk management manager to make this decision? Nonmaleficence Beneficence - -A busy case manager for a multistate insurance company retrieves voice mails at the beginning of the workday, and one of them is from a patient whose care the case manager has managed for several months. WGU D514 WGU D514 The case manager believes the patient is a malingerer, based on conversations with this patient's physical therapist and conversations the case manager has had with the patient. The case manager decides to call the patient back at the end of the eight-hour workday, as the case manager tells themselves that the patient's call is most likely unnecessary and unimportant. Which ethical principle is described in this situation? Autonomy - -In research, this principle is the right for a person to participate as a human subject or not. In healthcare, it refers to a patient having the right to make their own choices, unless they have been legally deemed unable to do so. Beneficence - -This is a concept that concerns the welfare of a research participant, but it can also apply to the treatment of patients. The opposite term, "maleficence," describes opposing the welfare of a research participant. You may also see a term, "malfeasance," which is intentional conduct outside the law. Databases - -A well-designed healthcare database captures data to support the organization's analysis and comparison of safety, quality, effectiveness, efficiency, timeliness, and efficacy of actual care and services delivered to the patient over time. Data warehouses - -These assimilate data from multiple transaction systems. Data warehouses can be used to distinguish larger trends in data from multiple sources. Disease registries - -A hybrid between transaction systems and data warehouses, these are designed for tracking explicitly defined data at a case-specific level. Evidence-based practice - -Healthcare administrators must have a working knowledge of statistics in order to make sound, effective decisions when using research to inform treatment and processes. Studies show that using analytical skills to make decisions based on quality data will result in increased patient satisfaction and improved outcomes (Scott & Mazhindu, 2014). In order to discern the highest-quality research, administrators must have the expertise necessary to objectively analyze statistics for validity. For both professionals and patients, a basic understanding of research and statistics in healthcare fosters improved health literacy and informed decisions. Fidelity - -this principle requires loyalty, fairness, truthfulness, advocacy, and dedication to patients (and others). It involves an agreement to keep promises, to keep a commitment, and is based on the virtue of caring. This principle would include patient advocacy. Forecasting - -Forecasting is the process of predicting outcomes and needs to create systems and models with the highest financial and operational safety and efficiency; it can be used to determine the potential use of services and patient demand, or to expand service lines and markets. WGU D514 WGU D514 Health disparities - -Health disparities are defined as "differences in the incidence, prevalence, mortality, and burden of diseases;" they are frequently seen in subpopulations based on socioeconomic status, geography, race, ethnicity, sexual orientation, or special needs. Justice - -in research, it pertains to the fair selection of research participants. Justice is the ideal distribution of risks and benefits when conducting clinical research and recruiting volunteer research participants to participate in clinical trials. One example of the principle of justice seen in the United States is when citizens turn 65 years of age, they are eligible for Medicare, no matter who they are or their socioeconomic level. Market segmentation - -Market or population segmentation is used to divide the defined community, group, or cohort into aggregate domains of shared traits. The intent is to optimally understand specific needs and further customize care and services. Measurement and decision support - -Measurement is used to monitor quality improvement in systems and processes, analyze current trends, evaluate performance, and—when results are gathered—to place accountability. New knowledge is built on research. Decision support provides an information platform to evaluate leading, lagging, and real-time performance measures. Measuring effectiveness of treatments - -Statistics are necessary to measure and compare treatment outcomes. Statistically analyzing the effectiveness of treatments is the optimal method to determine validity for adoption. Multiple regression - -The purpose of multiple regression is to determine the relationship between several independent or predictor variables and a dependent variable. Needs assessment - -A needs assessment is the process of collecting and analyzing information about a specific population, enterprise, or cohort to gain stakeholder insight into cultural engagement. It may also identify coalition strengths, weaknesses, opportunities, issues, available resources, and constraints or barriers. The needs assessment supports clear direction for decisions involving development of a specific health initiative or program. Outcome evaluation - -An outcome evaluation focuses on the end result of a specific program or initiative, generally clinically measured by improvements in morbidity, mortality, or vital measures of symptoms, signs, or physiologic indicators. Plagiarism Avoidance - -Plagiarism is the uncredited use of someone else's words or ideas. A charge of plagiarism to a researcher may have serious consequences, including loss of a job or expulsion from a university, and will result in loss of standing in the professional community. WGU D514 WGU D514 Research - -Research can inform decisions regarding the development and efficacy of new processes, systems, technologies, environments, and organizational structures to support operations. Quality improvement - -Quality improvement is measured internally and externally, using various benchmarks and indicators. These indicators are quantified by proportions, percentages, ratios, means, medians, and counts to measure processes, perspectives, and outcomes aligned with a certain initiative or decision. Transaction systems - -Divide data according to individual operations. The data stored by transaction systems is granular and based on specialized systems. True - -True or False: Healthcare prices have historically driven health services spending growth, but utilization is now the primary driver of health services spending. False - -True or False: Healthcare consumers are spending more money out of pocket for their healthcare services than any time since the 1970s. False - -True or False. Public and private spending have both grown substantially, but private spending has grown much faster. True - -True or False. Health spending growth is now more on pace with economic growth. California - -Review the "State Facts" Data provided by the Henry J. Kaiser Foundation. Use the data from January 2018 to compare state Medicaid and CHIP Enrollment, when comparing the pre-Affordable Care Act average monthly enrollment to the total monthly Medicaid and CHIP enrollment. Select the correct answers to the following questions. Which state has the highest enrollment? Wyoming - -Review the "State Facts" Data provided by the Henry J. Kaiser Foundation. Which state has the lowest enrollment? Kentucky - -Review the "State Facts" Data provided by the Henry J. Kaiser Foundation. Which state had the greatest percentage increase, when comparing pre-ACA to January 2018? Wyoming - -Review the "State Facts" Data provided by the Henry J. Kaiser Foundation. Which state had the lowest percentage increase, when comparing pre-ACA to January 2018? Predictive Modeling - -State whether each statement is an example of predictive modeling or statistical modeling. A hospital administrator in Kentucky is comparing outcomes on patients using Medicaid and CHIP to patients using other insurers, to determine the need for stronger case management. WGU D514 WGU D514 Statistical Modeling - -A quality improvement manager in Alaska is comparing facility data on the enrollment of patients using Medicaid and CHIP, from before the passage of the Affordable Care Act to current data on Medicaid and CHIP enrollment. Statistical Modeling - -A hospital CFO in California is examining reimbursement data from their five-hospital system to compare which hospitals are incurring debt from services to patients using Medicaid and CHIPS. Predictive Modeling - -A hospital in Colorado is launching an initiative to decrease the use of their emergency department by the homeless population. This homeless population uses Medicaid for their healthcare. The plan for achieving this aim is to send mobile healthcare units into certain sections of the community. They are forecasting this will save them over a million dollars in healthcare expenditures over the next few years. Forecasting - -The process of predicting outcomes and needs to create systems and models with the highest financial and operational safety and efficiency; it can be used to determine the potential use of services and patient demand or to expand service lines and markets. Modeling questions - -These questions include "What are you predicting and why? How accurate is your prediction and what actions are taken based on the prediction?" Predictive modeling - -This modeling relies on mathematical algorithms to predict the probability of an outcome. Predictive analytics - -When used in the healthcare environment, it provides a predictive score (probability) for each patient or groups of patients in order to determine, inform, and influence organizational processes that pertain to large numbers of individuals. Histogram - -A histogram is a tool to plot the frequency and number of cases and is useful to identify areas of high variance. Distribution and deviations - -Normal distribution visually reflects a well-formed bell curve. Variation may appear to be skewed outside the normal distribution and require additional testing for statistical significance. Standard error - -The standard error reflects how close a sample mean is to the true population mean. This calculation is essential for identifying variation that is a result of chance. Z-score - -The z-score measures the distance along the x-axis of a normal distribution measured in units of standard deviation. The z-score is a unit that can simplify the measurement of variation. Complete and Close Review