Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page
Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page
Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Getting StartedAfter the prior activities, the analysis section can be written for each of the research reports. Since there are three analyses to perform, this is a partial assignment for the analysis section. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page In order to successfully complete this assignment, you should be able to: Write part of the analysis section for two data sets. Resources File: Research Report Patients Your most recent research reports Background InformationThis is one of the more detailed assignments in this course. You will write your third analysis up for each of the reports. Instructions Study the Research Report Patients file. In each of your reports, fill out the third analysis section, including any statistics and graphs and interpretation on the analysis. When you have completed your assignment, save copies for yourself and submit a copy of each research report to your instructor by the end of the workshop. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Professors comments 5.4: I recommend showing more of these tables, similar to those shown in the WS5 Practice Excel Spreadsheet (which shows the level of significance, critical value, the test statistic, and the p-value). Also regarding the P-Value, I recommend changing the exponential notation to a real decimal number. That will make the results clear. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page If you have additional questions, please let me know. .4_categoral_hypothesis_prof_comments_request.docx copy_of_ws5practice.xls research_report_patients.docx NC Births Chi-Square Analysis Is weight and gained interdependent variables? Total Observed Gained Weight Total 29507 7101 36608 29507 7101 36608 Expected 29507 7101 29507 7101 Total p 36608 36608 1 The table shows a Chi-square analysis of Gained and weight to test for their independence. Since the p-value which is 1 is higher than the level of significance, we fail to reject the null hypothesis and therefore both gained and weight are both interdependent variables. Impeach Chi-Square Analysis Republican Democrat Total Observed Degree of Conservatism 1998 Population Estimate Total 2720 239366898 239369618 2011 300086256 300088267 4731 539453154 539457885 Republican Democrat Total Expected Degree of Conservatism 1998 Population Estimate Total 2099.251293 239367518.7 239369618 2631.748707 300085635.3 300088267 4731 539453154 539457885 p 9.73817E-74 The chi-square analysis is based on the sum of Degree of Conservatism and 1998 Population Estimate in relation to the party. The level of significance used in the study is 0.05 and since the p-value is less than the level of significance, the two variables are independent and do not depend on each other. MAG (Richter scale) DEPTH (km) 0.70 6.6 0.74 2.0 0.64 15.3 0.39 17.2 0.70 3.2 2.20 2.2 1.98 14.8 0.64 5.6 1.22 6.1 0.20 9.1 1.64 18.5 1.32 8.1 2.95 10.0 0.90 1.76 1.01 1.26 0.00 0.65 1.46 1.62 1.83 0.99 1.56 0.40 1.28 0.83 1.34 0.54 1.25 0.92 1.00 0.79 0.79 1.44 1.00 2.24 2.50 1.79 1.25 1.49 0.84 1.42 1.00 1.25 1.42 1.35 0.93 0.40 1.39 10.0 10.0 10.0 10.0 10.0 10.0 10.0 13.7 4.5 8.3 6.0 14.2 5.4 17.7 9.9 17.3 5.1 5.3 15.9 13.7 4.2 5.7 5.9 15.1 8.5 14.7 16.4 4.7 8.6 8.2 15.2 10.1 14.5 5.2 7.9 3.3 6.4 Place your pivot table here: This is what the pivot table should look like: This is STEP 1 of the process to create the pivot table. Chi-Square Test Is depth of earthquake independent of the magnitude? Use .01 level of significance and quake raw data in worksheet RawData to summarize into c Observed Frequencies Depth (km) Magnitude (Richter) 0-10 10-20 Total 0-1 >1 Total 0 0 0 Expected Frequencies Depth (km) Magnitude (Richter) 0-10 10-20 0-1 #DIV/0! #DIV/0! >1 #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! Data Level of Significance Number of Rows Number of Columns Degrees of Freedom 0.01 0 0 1 Results Critical Value Chi-Square Test Statistic p -Value Do not reject the null hypothesis 6.6349 0.0000 1.0000 0 0 Total #DIV/0! #DIV/0! #DIV/0! ata in worksheet RawData to summarize into counts. Notice that >1 takes into account 2 lines of the pivot. NOTE: Your counts will come from the RawDat when you create the pivot table there. This is step 2 of the process. Entering values correctly into table: Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page (10 points) Access this helpful video: Video DO NOT touch the non-blue areas of the tables. This is what the rows 33 through 43 should look like: Entering correct alpha value (10 points) from the RawData tab REPORT ON GERIATRICS By Professor of Course STAT 535 A paper submitted in partial fulfillment of the requirements for the degree of Masters of Business Administration INDIANA WESLEYAN UNIVERSITY January 2020 Report on Geriatrics 1 Contents PROJECT BACKGROUND . 2 Purpose of the Study . 2 Context of the Problem, Challenge Opportunity or Issue . 2 Objectives of the Study .. 2 Limitations of the Study . 2 Assumptions of the Study . 3 Significance of the Study 3 What are the goals of the Study . 3 Significance of the Topic to the Writer .. 3 Significance of the Topic to Stakeholders 3 Broader Implications of the Topic 4 Information and Literature Review 4 Brief Summary of the Literature on the Subject 4 Systematic Review of the Literature 5 Descriptive Statistics 6 Descriptive graphs 8 PROJECT ANALYSIS .. 12 Analysis of the Literature Review Research Findings .. 12 Simple Linear Regression Analysis .. 12 Single Sample Hypothesis Test of the MeanIndiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page 13 Chi-Square Analysis of Age and Principal Payer .. 14 PROJECT SUMMARY . 16 Conclusions . 16 Specific Recommendations . 16 Suggestions for Future Research . 16 Ethical considerations 16 References . 17 Appendices 18 Appendix A: Data Set 19 Appendix B: Pictures of Analysis 22 Report on Geriatrics 2 PROJECT BACKGROUND Purpose of the Study Context of the Problem, Challenge Opportunity or Issue Healthcare is currently a major fiscal problem. If this trend continues to 2010 and beyond then corporation managers will stop offering healthcare (some already have) to employees, or they will keep passing along premium increases to employees as many currently do (Chandra, Kumar & Ghildayal, 2011, p.315). The cost of inpatient hospital care is under scrutiny, from patients to insurance providers to government officials. With costs continuing to skyrocket, it is more important than ever to understand the relationships between an inpatient hospital stay and the costs associated the patient care. The effective management of hospitals is an increasingly political and social issue as demographic trends in the USA indicate that the issues associated with better hospital management will only become increasingly important as the domestic population continues to age (Stock & McDermott, 2009, p. 142). Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Objectives of the Study By analyzing raw data collected in the hospital setting, we are able to describe the data in terms of statistics and a visual exploration through graphs. We can also test hypothetical statements and claims using the sample data. Limitations of the Study In the dataset from Freedom Hospital Geriatric Patients there appear to be anomalies. Geriatric is defined as a branch of medicine that deals with the problems and diseases of old age and aging people (Merriam-Webster, 2016). Once the dataset is sorted, twelve patients do not fit the geriatric definition. If the dataset is a sample of all patients in the hospital and not specifically geriatric patients, the information should be noted on the description for the dataset. Report on Geriatrics 3 The data also included a patient who was not identified as either male or female. Assumptions of the Study It is assumed that the data in the spreadsheet used in the analysis for this report was honest and truthful. It is assumed that any blank information provided is not due to privacy concerns. It is assumed that no private identifying information was collected. Significance of the Study What are the goals of the Study Goals of this study are to analyze age, charges, gender, length of stay, and principal payer in terms of central tendency and variation, and specific visual explorations and hypothesis tests on the data. Based on performing this analysis the interpretations and judgments allow for business decisions to be made. For instance, based on the typical length of stay a business can strive to lower that value and look for ways to improve evidence of outcomes. Significance of the Topic to the Writer The significance to this writer is personally having friends and family in ages greater than 50 years and in a hospital setting. It would be advantageous to anyone who cares about loved ones and friends to attain care that is efficient and effective. Measuring for the purpose of improvement is therefore of significance to this writer. Significance of the Topic to Stakeholders Stakeholders could be patients, payers, and the government in this context. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page All three would be interested in the results of a medical study on people over 50 years of age. Patients would be informed of trends of costs. Payers would know the breakdown by percentage by various payers. The government would benefit from research to know how to legislate. Report on Geriatrics 4 There are political consequences to lack of efficiency and effectiveness. If people spend all their money in retirement on medical bills, then that can translate into votes for candidates that specialize in health care legislation. In current times, Medicare for all is being hotly debated on its merits and costs. Broader Implications of the Topic Industry implications. The significance to the hospital industry as a whole is to treat patients with utmost care and concern, while not bankrupting the patient in the process. Health care costs have been a significant part of employee benefit packages and the costs have been going up faster than inflation and certainly faster that wages. Global implications. Worldwide we have different ways of paying for medical care. Which is the correct option for a country? The facts should drive the decisions for a given country. This is not a one size fits all so data analysis should include data from many countries. Research should be funded and then used to make decisions and considered important due to the cost ramifications. Information and Literature Review Brief Summary of the Literature on the Subject Rising costs are at the heart of the cost challenges that are prevalent in health care. Healthcare reform was designed, in part to help alleviate this persistent cost problem, but much work still needs to be done to fully understand the true costs of health care (Richmond, 2013, p. 90). This section, will analyze the costs associated with an inpatient hospital stay. The total charges along with the individual department charges will be analyzed. Report on Geriatrics 5 There are different ways for hospitals to estimate the costs involved in a hospital stay. According to Richmond (2013), ratios of costs to charges is one of the ways a hospital can estimate patient costs. Richmond discusses the use of ratios and highlights the use of ratios can cause hospitals to overestimate the profitability of specific services, for example, orthopedic procedures. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page In the article, the author shares a four step process for hospitals to use to better estimate patient costs. The process takes time and the ability to utilize analytical data to better project costs. Using data can help a hospital determine whether a physician is efficiently using resources, which directly impacts the cost of care to the patient. Systematic Review of the Literature Summary and Relevance of the Literature to the problem or questions The research involves 137 patients at a geriatric hospital. The sex (gender) and principal payer are categorical with values having text values, and the age, length of stay, and total charges are numeric variables, and can be used for hypothesis testing and regression scatterplots. The analysis being proposed in this paper is one of looking at length of stay and charges. The impact of gender is being analyzed. As discusses earlier in the paper, costs are high and growing, which makes it essential to measure and analyze to improve efficiency and effectiveness. Thematic Findings in Literature as Applied to the Topic Costs are high and increasing for health care. It is important to reduce costs while maintaining quality. There is a balance. It is important to monitor length of stay to minimize it. Key definitions. Length of Stay (LOS) is a key measure and bed census is affected when we cant manage LOS effectively. Report on Geriatrics 6 Ethical consideration from the literature review. Gathering data involves a lot of work to capture, clean, and store the data in a usable format. We know that people can be overcharged for services. Many people have experienced this on a personal level. Even paying 20% of the service charges can effect a household and be an ethical dilemma to resolve when deciding what services to provide and at what cost. Do you pay for new equipment knowing that care would improve but so would costs? Descriptive Statistics Type of variables in the data set. Table 1: Variable list Variable Variable Type Length of Stay in Days Numerical, Discrete, Ratio Scale Patient Age Numerical, Discrete, Ratio Scale Sex Categorical, Nominal Scale Principal Payer Categorical, Nominal Scale Total Charges during Hospital Stay Numerical, Continuous, Ratio Scale This section will analyze the following questions: What is the breakdown by age of males and females? Do men or women spend more time (length in days) in the hospital? Do men or women pay more for their stay in the hospital? Do men and women use the same principal payers? To describe the raw data our attention turns to some statistics related to the variables being used in the research (Length of Stay in Days, Patient Age, Sex, and Principal Report on Geriatrics 7 Payer). The following table will present the descriptive statistics on the variables being researched (Table 2). Table 2: Descriptive statistics Variable Gender Mean Median Standard Deviation Length of Stay in Days Patient Age Total Charges during Hospital Stay M 4.92 5 2.31 F 5.31 5 2.39 M 78.1 80 8.94 F 77.6 78.5 9.38 M 8978.08 8907 885 F 8789.93 8794 729 Table 2 shows that the mean length of stay in days for women is slightly higher. Patient age has a mean of 77.6-78.1 for females and males.Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page The minimum amount of time spent in the hospital was zero days up to the maximum of twelve days. Prior research has shown that ALOS [average length of stay] is related to cost, efficiency, quality of care, and speed in service delivery (Ashby et al., 2000; Glick et al., 2003; Thomas et al., 1997; Burns et al., 1994) (as cited in Stock & McDermott, 2009, p. 144). Total charges averages $8,978.08 for men and $8,789.93 for women which is slightly lower. The standard deviation for length of stay is 2.31 for men and 2.39 for women. Rising costs are at the heart of the cost challenges that are prevalent in health care. Healthcare reform was designed, in part to help alleviate this persistent cost problem, but much work still needs to be done to fully understand the true costs of health care (Richmond, 2013, p. 90). This section, Report on Geriatrics 8 will analyze the costs associated with an inpatient hospital stay. The total charges along with the individual department charges will be analyzed. The standard deviation for the age is about one eighth of the mean for both men and women, and total charges about one tenth for men and a little less for women. There is not a big difference in variation between men and women. Descriptive graphs Figure 1. Length of Stay by Gender Figure 1 shows that the shape of the column charts is similar for men and women but more females stay 7-8 days and less on 1-2 days than men. Both distributions are heavily loaded towards the front, indicating right skewness. The majority of the values are eight days or under for length of stay. Report on Geriatrics Figure 2. Age by Gender Figure 2 shows that the shape of the column charts is similar for men and women but with only a slight difference being higher for females. Both distributions are heavily loaded towards the higher end, indicating left skewness. The majority of the age values are 60 and up. This makes total sense for a geriatric hospital study set of data. 9 Report on Geriatrics 10 Figure 3. Total Charges by Gender Figure 3 shows that the shape of the column charts is similar for men and women but with some charges for males existing in the 8,500 to 11,000 range. Both distributions are heavily loaded towards the lower end, indicating right skewness. The majority of the charges are 1,000 to 11,000 dollars. Figure 4. Primary Payer percentages Figure 4 shows that most of the payments are through Medicare for all patients. For people over 60 that makes sense, sense they become eligible for those benefits as the patients age. Medicaid and Blue Cross are the other percentages that make up the largest portion of the payments. Table 3 shows there is not much difference by gender on which payers are used other than SELF and INS and HMO. Report on Geriatrics 11 Table 3: Count of Primary Payers by Gender Gender F M Grand Total BC CAID 13 3 3 22 16 25 Grand CARE HMO INS OGVT OTHR SELF Total 31 9 1 1 16 74 16 15 8 64 47 9 16 1 8 16 138 Report on Geriatrics 12 PROJECT ANALYSIS Analysis of the Literature Review Research Findings Simple Linear Regression Analysis The research question that will be answered using simple linear regression is below: Is there a correlation between drug charges and age? Figure 5. Scatterplot of Drug Charges based on Age Figure 5 shows a slightly upward slope. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page The slope is calculated to be -3.8068 and a relationship strength measured by r-squared is .0064. The plot points on the scatterplot look random and the r-squared value of .0064 is extremely low. This means there is almost no relationship (correlation) between drug charges and age. Report on Geriatrics 13 Single Sample Hypothesis Test of the Mean The research claim that will be answered using one sample hypothesis testing is below: The population mean for total charges is $10,000 Table 4: Hypothesis test using a t test for the mean The hypothesis analysis in Table 4 shows the sample input values of the hypothesis value of $10,000 for the mean of total charges, the sample mean of $8,882.64, sample standard de Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10
Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page
Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Getting StartedAfter the prior activities, the analysis section can be written for each of the research reports. Since there are three analyses to perform, this is a partial assignment for the analysis section. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page In order to successfully complete this assignment, you should be able to: Write part of the analysis section for two data sets. Resources File: Research Report Patients Your most recent research reports Background InformationThis is one of the more detailed assignments in this course. You will write your third analysis up for each of the reports. Instructions Study the Research Report Patients file. In each of your reports, fill out the third analysis section, including any statistics and graphs and interpretation on the analysis. When you have completed your assignment, save copies for yourself and submit a copy of each research report to your instructor by the end of the workshop. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Professors comments 5.4: I recommend showing more of these tables, similar to those shown in the WS5 Practice Excel Spreadsheet (which shows the level of significance, critical value, the test statistic, and the p-value). Also regarding the P-Value, I recommend changing the exponential notation to a real decimal number. That will make the results clear. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page If you have additional questions, please let me know. .4_categoral_hypothesis_prof_comments_request.docx copy_of_ws5practice.xls research_report_patients.docx NC Births Chi-Square Analysis Is weight and gained interdependent variables? Total Observed Gained Weight Total 29507 7101 36608 29507 7101 36608 Expected 29507 7101 29507 7101 Total p 36608 36608 1 The table shows a Chi-square analysis of Gained and weight to test for their independence. Since the p-value which is 1 is higher than the level of significance, we fail to reject the null hypothesis and therefore both gained and weight are both interdependent variables. Impeach Chi-Square Analysis Republican Democrat Total Observed Degree of Conservatism 1998 Population Estimate Total 2720 239366898 239369618 2011 300086256 300088267 4731 539453154 539457885 Republican Democrat Total Expected Degree of Conservatism 1998 Population Estimate Total 2099.251293 239367518.7 239369618 2631.748707 300085635.3 300088267 4731 539453154 539457885 p 9.73817E-74 The chi-square analysis is based on the sum of Degree of Conservatism and 1998 Population Estimate in relation to the party. The level of significance used in the study is 0.05 and since the p-value is less than the level of significance, the two variables are independent and do not depend on each other. MAG (Richter scale) DEPTH (km) 0.70 6.6 0.74 2.0 0.64 15.3 0.39 17.2 0.70 3.2 2.20 2.2 1.98 14.8 0.64 5.6 1.22 6.1 0.20 9.1 1.64 18.5 1.32 8.1 2.95 10.0 0.90 1.76 1.01 1.26 0.00 0.65 1.46 1.62 1.83 0.99 1.56 0.40 1.28 0.83 1.34 0.54 1.25 0.92 1.00 0.79 0.79 1.44 1.00 2.24 2.50 1.79 1.25 1.49 0.84 1.42 1.00 1.25 1.42 1.35 0.93 0.40 1.39 10.0 10.0 10.0 10.0 10.0 10.0 10.0 13.7 4.5 8.3 6.0 14.2 5.4 17.7 9.9 17.3 5.1 5.3 15.9 13.7 4.2 5.7 5.9 15.1 8.5 14.7 16.4 4.7 8.6 8.2 15.2 10.1 14.5 5.2 7.9 3.3 6.4 Place your pivot table here: This is what the pivot table should look like: This is STEP 1 of the process to create the pivot table. Chi-Square Test Is depth of earthquake independent of the magnitude? Use .01 level of significance and quake raw data in worksheet RawData to summarize into c Observed Frequencies Depth (km) Magnitude (Richter) 0-10 10-20 Total 0-1 >1 Total 0 0 0 Expected Frequencies Depth (km) Magnitude (Richter) 0-10 10-20 0-1 #DIV/0! #DIV/0! >1 #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! Data Level of Significance Number of Rows Number of Columns Degrees of Freedom 0.01 0 0 1 Results Critical Value Chi-Square Test Statistic p -Value Do not reject the null hypothesis 6.6349 0.0000 1.0000 0 0 Total #DIV/0! #DIV/0! #DIV/0! ata in worksheet RawData to summarize into counts. Notice that >1 takes into account 2 lines of the pivot. NOTE: Your counts will come from the RawDat when you create the pivot table there. This is step 2 of the process. Entering values correctly into table: Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page (10 points) Access this helpful video: Video DO NOT touch the non-blue areas of the tables. This is what the rows 33 through 43 should look like: Entering correct alpha value (10 points) from the RawData tab REPORT ON GERIATRICS By Professor of Course STAT 535 A paper submitted in partial fulfillment of the requirements for the degree of Masters of Business Administration INDIANA WESLEYAN UNIVERSITY January 2020 Report on Geriatrics 1 Contents PROJECT BACKGROUND . 2 Purpose of the Study . 2 Context of the Problem, Challenge Opportunity or Issue . 2 Objectives of the Study .. 2 Limitations of the Study . 2 Assumptions of the Study . 3 Significance of the Study 3 What are the goals of the Study . 3 Significance of the Topic to the Writer .. 3 Significance of the Topic to Stakeholders 3 Broader Implications of the Topic 4 Information and Literature Review 4 Brief Summary of the Literature on the Subject 4 Systematic Review of the Literature 5 Descriptive Statistics 6 Descriptive graphs 8 PROJECT ANALYSIS .. 12 Analysis of the Literature Review Research Findings .. 12 Simple Linear Regression Analysis .. 12 Single Sample Hypothesis Test of the MeanIndiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page 13 Chi-Square Analysis of Age and Principal Payer .. 14 PROJECT SUMMARY . 16 Conclusions . 16 Specific Recommendations . 16 Suggestions for Future Research . 16 Ethical considerations 16 References . 17 Appendices 18 Appendix A: Data Set 19 Appendix B: Pictures of Analysis 22 Report on Geriatrics 2 PROJECT BACKGROUND Purpose of the Study Context of the Problem, Challenge Opportunity or Issue Healthcare is currently a major fiscal problem. If this trend continues to 2010 and beyond then corporation managers will stop offering healthcare (some already have) to employees, or they will keep passing along premium increases to employees as many currently do (Chandra, Kumar & Ghildayal, 2011, p.315). The cost of inpatient hospital care is under scrutiny, from patients to insurance providers to government officials. With costs continuing to skyrocket, it is more important than ever to understand the relationships between an inpatient hospital stay and the costs associated the patient care. The effective management of hospitals is an increasingly political and social issue as demographic trends in the USA indicate that the issues associated with better hospital management will only become increasingly important as the domestic population continues to age (Stock & McDermott, 2009, p. 142). Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page Objectives of the Study By analyzing raw data collected in the hospital setting, we are able to describe the data in terms of statistics and a visual exploration through graphs. We can also test hypothetical statements and claims using the sample data. Limitations of the Study In the dataset from Freedom Hospital Geriatric Patients there appear to be anomalies. Geriatric is defined as a branch of medicine that deals with the problems and diseases of old age and aging people (Merriam-Webster, 2016). Once the dataset is sorted, twelve patients do not fit the geriatric definition. If the dataset is a sample of all patients in the hospital and not specifically geriatric patients, the information should be noted on the description for the dataset. Report on Geriatrics 3 The data also included a patient who was not identified as either male or female. Assumptions of the Study It is assumed that the data in the spreadsheet used in the analysis for this report was honest and truthful. It is assumed that any blank information provided is not due to privacy concerns. It is assumed that no private identifying information was collected. Significance of the Study What are the goals of the Study Goals of this study are to analyze age, charges, gender, length of stay, and principal payer in terms of central tendency and variation, and specific visual explorations and hypothesis tests on the data. Based on performing this analysis the interpretations and judgments allow for business decisions to be made. For instance, based on the typical length of stay a business can strive to lower that value and look for ways to improve evidence of outcomes. Significance of the Topic to the Writer The significance to this writer is personally having friends and family in ages greater than 50 years and in a hospital setting. It would be advantageous to anyone who cares about loved ones and friends to attain care that is efficient and effective. Measuring for the purpose of improvement is therefore of significance to this writer. Significance of the Topic to Stakeholders Stakeholders could be patients, payers, and the government in this context. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page All three would be interested in the results of a medical study on people over 50 years of age. Patients would be informed of trends of costs. Payers would know the breakdown by percentage by various payers. The government would benefit from research to know how to legislate. Report on Geriatrics 4 There are political consequences to lack of efficiency and effectiveness. If people spend all their money in retirement on medical bills, then that can translate into votes for candidates that specialize in health care legislation. In current times, Medicare for all is being hotly debated on its merits and costs. Broader Implications of the Topic Industry implications. The significance to the hospital industry as a whole is to treat patients with utmost care and concern, while not bankrupting the patient in the process. Health care costs have been a significant part of employee benefit packages and the costs have been going up faster than inflation and certainly faster that wages. Global implications. Worldwide we have different ways of paying for medical care. Which is the correct option for a country? The facts should drive the decisions for a given country. This is not a one size fits all so data analysis should include data from many countries. Research should be funded and then used to make decisions and considered important due to the cost ramifications. Information and Literature Review Brief Summary of the Literature on the Subject Rising costs are at the heart of the cost challenges that are prevalent in health care. Healthcare reform was designed, in part to help alleviate this persistent cost problem, but much work still needs to be done to fully understand the true costs of health care (Richmond, 2013, p. 90). This section, will analyze the costs associated with an inpatient hospital stay. The total charges along with the individual department charges will be analyzed. Report on Geriatrics 5 There are different ways for hospitals to estimate the costs involved in a hospital stay. According to Richmond (2013), ratios of costs to charges is one of the ways a hospital can estimate patient costs. Richmond discusses the use of ratios and highlights the use of ratios can cause hospitals to overestimate the profitability of specific services, for example, orthopedic procedures. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page In the article, the author shares a four step process for hospitals to use to better estimate patient costs. The process takes time and the ability to utilize analytical data to better project costs. Using data can help a hospital determine whether a physician is efficiently using resources, which directly impacts the cost of care to the patient. Systematic Review of the Literature Summary and Relevance of the Literature to the problem or questions The research involves 137 patients at a geriatric hospital. The sex (gender) and principal payer are categorical with values having text values, and the age, length of stay, and total charges are numeric variables, and can be used for hypothesis testing and regression scatterplots. The analysis being proposed in this paper is one of looking at length of stay and charges. The impact of gender is being analyzed. As discusses earlier in the paper, costs are high and growing, which makes it essential to measure and analyze to improve efficiency and effectiveness. Thematic Findings in Literature as Applied to the Topic Costs are high and increasing for health care. It is important to reduce costs while maintaining quality. There is a balance. It is important to monitor length of stay to minimize it. Key definitions. Length of Stay (LOS) is a key measure and bed census is affected when we cant manage LOS effectively. Report on Geriatrics 6 Ethical consideration from the literature review. Gathering data involves a lot of work to capture, clean, and store the data in a usable format. We know that people can be overcharged for services. Many people have experienced this on a personal level. Even paying 20% of the service charges can effect a household and be an ethical dilemma to resolve when deciding what services to provide and at what cost. Do you pay for new equipment knowing that care would improve but so would costs? Descriptive Statistics Type of variables in the data set. Table 1: Variable list Variable Variable Type Length of Stay in Days Numerical, Discrete, Ratio Scale Patient Age Numerical, Discrete, Ratio Scale Sex Categorical, Nominal Scale Principal Payer Categorical, Nominal Scale Total Charges during Hospital Stay Numerical, Continuous, Ratio Scale This section will analyze the following questions: What is the breakdown by age of males and females? Do men or women spend more time (length in days) in the hospital? Do men or women pay more for their stay in the hospital? Do men and women use the same principal payers? To describe the raw data our attention turns to some statistics related to the variables being used in the research (Length of Stay in Days, Patient Age, Sex, and Principal Report on Geriatrics 7 Payer). The following table will present the descriptive statistics on the variables being researched (Table 2). Table 2: Descriptive statistics Variable Gender Mean Median Standard Deviation Length of Stay in Days Patient Age Total Charges during Hospital Stay M 4.92 5 2.31 F 5.31 5 2.39 M 78.1 80 8.94 F 77.6 78.5 9.38 M 8978.08 8907 885 F 8789.93 8794 729 Table 2 shows that the mean length of stay in days for women is slightly higher. Patient age has a mean of 77.6-78.1 for females and males.Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page The minimum amount of time spent in the hospital was zero days up to the maximum of twelve days. Prior research has shown that ALOS [average length of stay] is related to cost, efficiency, quality of care, and speed in service delivery (Ashby et al., 2000; Glick et al., 2003; Thomas et al., 1997; Burns et al., 1994) (as cited in Stock & McDermott, 2009, p. 144). Total charges averages $8,978.08 for men and $8,789.93 for women which is slightly lower. The standard deviation for length of stay is 2.31 for men and 2.39 for women. Rising costs are at the heart of the cost challenges that are prevalent in health care. Healthcare reform was designed, in part to help alleviate this persistent cost problem, but much work still needs to be done to fully understand the true costs of health care (Richmond, 2013, p. 90). This section, Report on Geriatrics 8 will analyze the costs associated with an inpatient hospital stay. The total charges along with the individual department charges will be analyzed. The standard deviation for the age is about one eighth of the mean for both men and women, and total charges about one tenth for men and a little less for women. There is not a big difference in variation between men and women. Descriptive graphs Figure 1. Length of Stay by Gender Figure 1 shows that the shape of the column charts is similar for men and women but more females stay 7-8 days and less on 1-2 days than men. Both distributions are heavily loaded towards the front, indicating right skewness. The majority of the values are eight days or under for length of stay. Report on Geriatrics Figure 2. Age by Gender Figure 2 shows that the shape of the column charts is similar for men and women but with only a slight difference being higher for females. Both distributions are heavily loaded towards the higher end, indicating left skewness. The majority of the age values are 60 and up. This makes total sense for a geriatric hospital study set of data. 9 Report on Geriatrics 10 Figure 3. Total Charges by Gender Figure 3 shows that the shape of the column charts is similar for men and women but with some charges for males existing in the 8,500 to 11,000 range. Both distributions are heavily loaded towards the lower end, indicating right skewness. The majority of the charges are 1,000 to 11,000 dollars. Figure 4. Primary Payer percentages Figure 4 shows that most of the payments are through Medicare for all patients. For people over 60 that makes sense, sense they become eligible for those benefits as the patients age. Medicaid and Blue Cross are the other percentages that make up the largest portion of the payments. Table 3 shows there is not much difference by gender on which payers are used other than SELF and INS and HMO. Report on Geriatrics 11 Table 3: Count of Primary Payers by Gender Gender F M Grand Total BC CAID 13 3 3 22 16 25 Grand CARE HMO INS OGVT OTHR SELF Total 31 9 1 1 16 74 16 15 8 64 47 9 16 1 8 16 138 Report on Geriatrics 12 PROJECT ANALYSIS Analysis of the Literature Review Research Findings Simple Linear Regression Analysis The research question that will be answered using simple linear regression is below: Is there a correlation between drug charges and age? Figure 5. Scatterplot of Drug Charges based on Age Figure 5 shows a slightly upward slope. Indiana University of Pennsylvania STAT 535 Creating Categorical Hypothesis Web Page The slope is calculated to be -3.8068 and a relationship strength measured by r-squared is .0064. The plot points on the scatterplot look random and the r-squared value of .0064 is extremely low. This means there is almost no relationship (correlation) between drug charges and age. Report on Geriatrics 13 Single Sample Hypothesis Test of the Mean The research claim that will be answered using one sample hypothesis testing is below: The population mean for total charges is $10,000 Table 4: Hypothesis test using a t test for the mean The hypothesis analysis in Table 4 shows the sample input values of the hypothesis value of $10,000 for the mean of total charges, the sample mean of $8,882.64, sample standard de Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10
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