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Foundation Skills in Business Analysis

Table of Contents

Executive Summary.

Introduction.

Data analysis.

Conclusion.

Bibliography.

Executive Summary of Medical Malpractice Claim Data Analysis

This is a descriptive report of data analysis that will provide the proper structuration of the business as considering all the fundamental extensions. With a presentation of excel sheet all the data which are provided and needed to analyse further are discussed in this report. With the presentation of a report, it can be cleared that foundation skill and the business analysis will be designed in an appropriate formation by using several charts. Regarding the medical hospitality system proper insourcing for. At including with the age according to the claimed amount and as follows by their gender and divided into various groups is very much essential. This whole report will contain the bereft of data analysis as presented in the excel sheet. To state a proper formation of data that has been taken as the insurance malfunctioning of that respective organization includes all the different information regarding every patient.

 There is 200 number of clients taken for this study or data analysis. In this below report including the age and gender of each of the patients is also mentioned. Because after analysis of the age and the specialization regarding the stage of the disease only then the insurance company will ensure the amount of money that they are ready to provide that claimants. After focusing on the severity that has been divided into three several parts as mild, medium, and severe after following those and the specialization only the claimed money will be declared. Age is very much essential to be followed cause the child and the 60 years above the candidate's insurance claiming amount must not be the same. On the other hand of this data analysis sheet, it is being elaborated about all the averages based on age and gender.

This report is being represented by the use of a designed bar graph and pie chart and also pivot chart and the presentation of the table. The average age and the claimed insurance as per the last year and this year are also being statistically examined. It is a system or process which provides the cleansing of unnecessary data or transforming or sometimes to manipulate data from one division to another. A report regarding a business data analysis always helps to identify the development structure of the business further in a better way. With the projection of proper data analysis, the system of the business can be more moderate than before and it will give a proper design in the overall database system of the insurance management system with following the information which is already provided through the excel sheet. with the help of manipulate those data and use them in a more specific method will discover the report in a more presentable format. With the preparation of proper average as the number of the male and female or the serenity candidate, it is easy to eradicate.

Introduction to Medical Malpractice Claim Data Analysis

This report is presenting a proper data analysis of the provided excel sheet as per the hospitality is needed to be managed and to develop their process. Analysis of a database mainly helps to draw a proper line in the description of the management system.

Data Analysis of Medical Malpractice Claim Data Analysis

As have already mentioned that this report is going to discuss the various data which are provided in the excel sheet. Several visualizations of that information through charts, bar graphs, and tables are represented as a data analysis of the given data. To describe the data analysis in a proper way and relevant format by using regular useful techniques is the only possible way to present a proper analysis result. Followed by this analysis result many decisions used to be taken for business development and welfare purpose. Data analysis has various facets and ways of approaches that encompass several techniques and formats which mostly depend on the type of business and their domains.

Data mining is one of the particular data analysis techniques which always focus on the statistical model which needs to be prepared on the base of the following excel datasheet. Forecasting or the classification of the text analysis applied by the statistical and linguistic and also referred to the classification of the information from all mentioned textual resources.

Data always can be collected from several sources. Though all the requirements are always communicated or mostly interrelated to each other such as the organization, data collection always represents each other though presenting the business and its development. All the mentioned data are mostly obtained from the source of the particular business or the communication with the targeted customer. Involving data are always placed in either in a separate column or divided into rows mostly represented by the excel sheet.

Q1. For this report as per the data are expanding from a hospital database. This excel sheet has the claimant id which refers to every individual claimant with a unique id. All the allotted insurance prices are also claimed as an amount column. Continuing with the amount the next column is added in the name of severity which describes the seriousness of the patient. That condition can always be differentiated into three parts such as MILD, MEDIUM, and SEVERE. Where mild is representing minor issues like a skin condition, mild acne, cough and cold, constipation, or piles, including fever and allergies are also in this section. Medium is referencing the particular person if the mild disease spreads on a large scale. On the other hand, severe is identified when the patient is in the critical condition or completely unable to continue anything on his own may be the patient can be in comma also. This condition always considered the age of the patients and based on that they allotted the money. Whether the claimant is applied from the private or the non-private attorney is also being mentioned in the next column. Though everything is already mentioned to complete all the claimant information their marital status also needs to be concluded in the data analysis part of the excel sheet. A proper representation of the specialization is essential to provide because on behalf of the insurance company has decided if they will align the insurance and the amount height also marked for the specific patient. To claim the treatment amount with the help of proper insurance it is very much important to recognize the type of insurance. This will provide the knowledge if the patient has insurance or not or what is the type of that insurance. It will consider whether the insurance will cover the total amount of the treatment or not. 

Q2. In the below as the total amount of the claim, payment has been asked to be presented in dollars will be a cost of $14,691,498.71 after the summation of the total amount of the insurance claimed. Sum of the total 200 candidates’ total amount and also represented by the help of a pivot chart. 

Q3. In the next analysis, where the severity rating of damage to the patient has been asked where the analysis of the total mild, medium, and severe is needed to be recognized. Here, in the excel sheet the calculation addresses that the count of “MILD is 26, MEDIUM is 128 and SEVERE is 46.” The serenity chart is represented with the help of a bar graph that presents the damage of the patient in a clearer method.

Q4. This way all the analysis is providing the representation including the severity damage rating including the total number of mild, medium, and severe as per the division of gender male and female. In the three upper mentioned zones 80, 14, and 27 is the number of female claimants. Where male claimants are 48, 12, and 19 respectively all these amounts have already been described elaborately and the data file has been attached with the documents where both values have been given and elaborated.

Q5. Besides, the excel file has also included in question no 2 b, the age range of claimant amount are already been given in the excel and a few filters have been developed which has been concluded with four filters such as 0-20, 21-40, 41-60 and above 60 filters. Here, the summation of each age filtered has been calculated which addressed that 0-20 level age average of the claimant amount is $1,466,580.06 while age 21-40 age average amount is $4,435,071.26 included also the 41-40 level age average amount is $6,050,374.52 and above 60 age level average amount is $2,739,472.87. The last year's amount average was $64,000.00 which is counted with the help of a chart this year as $73,457.49. The average claimant is running within 30%-48% in this datasheet.

All the claimed payments which have been shown in the excel sheet are as well as the severity damage rating and also all the average regarding the asked formation of patients party have also been highlighted there. Data has been extracted as per the given excel file that has been already provided where at least 200 fields of data have been taken for analysis. As per the rate of severe damages. Also, the severe damage rating has been shown as percentages. variable. Besides, the analysis of this question has also included several numerical datasets and an investigation has been made thoroughly for these two variables.

With the addition, the average age of claimant is also being deducted between 23-55 while the claim proportion is between 9%-65% also. In this section, the average amount of claimants has been extracted from the excel file. In the file, the age column has already been given in this section and the average of the age regarding the claimant amount has been calculated here and the average is 44.49. In the excel sheet, one pie chart has been presented to mention its proper structure.

In this data analysis, several types of data charts and grapes are provided to get a proper design of severe claimant amounts, their age, their demand, and other all the information. To claims, the average of dollars of 4,000 dollars per year to take accurately will be the proper estimation for the data analysis.

Conclusion on Medical Malpractice Claim Data Analysis

After a brief analysis of this whole report, this is very much essential to form a proper format of data analysis which always helps to encourage development and involve every crucial data and being analysed in the chart. As per the insurance is already discussed on supporting many points such as the age and the gender of the claimants this will be the specification of the company will claim those patients a proper amount of insurance or not. A proper data analysis of a system is crucial to represent the whole database of that respective company in a proper fundamental physical presentation. Through this many encapsulated information can be recovered and also helps to discover the new provided the structural formation of data. 

Bibliography for Medical Malpractice Claim Data Analysis

Agresti, A. (2018). An introduction to categorical data analysis. John Wiley & Sons.

Bledzki, L. A., & Rybak, J. I. (2016). Freshwater Crustacean Zooplankton of Europe: Cladocera & Copepoda (Calanoida, Cyclopoida) Key to species identification, with notes on ecology, distribution, methods and introduction to data analysis. Springer.

Chazal, F., & Michel, B. (2017). An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists. arXiv preprint arXiv:1710.04019. Vasishth, S., Nicenboim, B., Beckman, M. E., Li, F., & Kong, E. J. (2018). Bayesian data analysis in the phonetic sciences: A tutorial introduction. Journal of phonetics71, 147-161.

Friese, S. (2019). Qualitative data analysis with ATLAS. ti. SAGE Publications Limited.

Ghilani, C. D. (2017). Adjustment computations: spatial data analysis. John Wiley & Sons.

Heeringa, S. G., West, B. T., & Berglund, P. A. (2017). Applied survey data analysis. CRC press.

Heeringa, S. G., West, B. T., & Berglund, P. A. (2017). Applied survey data analysis. CRC press.

Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Routledge.

Sgouralis, I., & Pressé, S. (2017). An introduction to infinite HMMs for single-molecule data analysis. Biophysical journal112(10), 2021-2029.

Tierny, J. (2017). Introduction to topological data analysis.

Washington, S., Karlaftis, M. G., Mannering, F., & Anastasopoulos, P. (2020). Statistical and econometric methods for transportation data analysis. CRC press.

Wickham, H. (2016). ggplot2: elegant graphics for data analysis. springer.

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