Foundations in Analytics

Alpha release

Test release of a product that is typically for internal circulation only and is passed among a select group of mock users

Assembler

A program that translates an assembly-language program into machine code

For this discussion we will be reviewing qualitative versus quantitative analysis and the applicability of either/or, or both types of variables being utilized in regression testing and framework appropriate for regression modeling. With that, let's jump right in! According to SAS, it is possible that qualitative and quantitative variables can be utilized for regression testing, however the preference lies within the type of regression testing and analysis being performed. For example, Analysis of Variance uses qualitative independent variables only within the regression testing whereas Analysis of Covariance utilizes both qualitative and quantitative variables to account for correlation (SAS, n.d). The type of testing and regression analysis performs can dictate the preference of which variable to utilize. While it is important to note that correlation in regression testing does not always equate to causation, the need for measuring qualitative and quantitative cases can be seen in specific cases.

As we read earlier in the discussion that simple linear regression models prefer to analysis a dependent and independent quantitative variable, more complex methodologies such as logistic regression modeling utilize and leverage qualitative variables when a simple linear regression model cannot be leveraged. For example, logistic regression may be utilized/leveraged over simple linear regression when the response variable is categorical (such as yes/no or student status like full time and part-time). Cumulatively, the type of variable leveraged and utilized is often dependent on the response variable being received to perform the regression analysis. In some unique circumstances as annotated above, Analysis of Covariance leverages both types of variables to accommodate for correlation in the data.

clinical

extremely objective and realistic; dispassionately analytic; unemotionally critical

Hypertension

high blood pressure

ulcer

open sore

Fall prevention

screenings, elements of focused history, physical examination, functional assessment. adaption of the environment, minimization of psychoactive medications, management of foot problems and footwear, exercise that emphasize balance, strength and gait training.

benchmark

standard of measure

Data plays an important role in any business, allowing businesses to improve targeting, optimize internal operations, and successfully drive innovation. As businesses look to adopt the latest technologies, the accuracy, and quality of data become important for business growth.

Poor data quality negatively impacts business creating both long and short-term issues which impact your ROI.

assembly

A group of machined or handmade parts that fit together to form a self-contained unit.

excerpt

A passage taken from a book

delegate

A person appointed or elected to represent others

Regression is a broad term that encompasses a wide variety of models. Regression is a great tool that an analyst can use in many situations. Regression is used in forecasting, examining relationships and their degree, analyzing key variables, and is used in binary problems. When thinking of quantitative and qualitative analysis different methodologies of regression can be used. In linear regression, it can be used to analyze numerical values. However, it is not possible to use categorical variables with linear regression. Instead there is a workaround to instead use dummy variables. Logistic regression is used for binary problems 1, 0, yes or no, etc. With these models categorical variables can be used. It is important to also follow the list of assumptions before running these models as well. This means checking for multicollinearity, normal distribution, and others depending on the method of regression. There are also other types of regression such as ordinal, stepwise, and multivariate.

Each has a situation where that type is the best to use. It is important when developing regression models to start with the basics of descriptive statistics, aggregations, and correlations. Then, make sure that the data passes each of the assumptions. It is important to remove variables that are highly correlated and to keep the model as simple as possible. If a simple linear regression model can solve the problem, it is going to be better to use that over a fancy neural network or machine learning model.

The alternative hypothesis is the one you would believe if the null hypothesis is concluded to be untrue. The evidence in the trial is your data and the statistics that go along with it. All hypothesis tests ultimately use a p-value to weigh the strength of the evidence (what the data are telling you about the population). The p-value is a number between 0 and 1 and interpreted in the following way: A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis. A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis. p-values very close to the cutoff (0.05) are considered to be marginal (could go either way). Always report the p-value so your readers can draw their own conclusions.

For example, suppose a pizza place claims their delivery times are 30 minutes or less on average but you think it's more than that. You conduct a hypothesis test because you believe the null hypothesis, Ho, that the mean delivery time is 30 minutes max, is incorrect. Your alternative hypothesis (Ha) is that the mean time is greater than 30 minutes. You randomly sample some delivery times and run the data through the hypothesis test, and your p-value turns out to be 0.001, which is much less than 0.05. In real terms, there is a probability of 0.05 that you will mistakenly reject the pizza place's claim that their delivery time is less than or equal to 30 minutes. Since typically we are willing to reject the null hypothesis when this probability is less than 0.05, you conclude that the pizza place is wrong; their delivery times are in fact more than 30 minutes on average, and you want to know what they're gonna do about it! (Of course, you could be wrong by having sampled an unusually high number of late pizza deliveries just by chance.)

Skewness is a measure of the symmetry in a distribution. ... It measures the amount of probability in the tails. The value is often compared to the kurtosis of the normal distribution, which is equal to 3.

If the kurtosis is greater than 3, then the dataset has heavier tails than a normal distribution (more in the tails).

Analysts help make sense of what happened, what is happening, how often it happens on average, and what is the likelihood of something happening in the future. Furthermore, with some modeling techniques, an analyst can recommend what should happen in the future. Statistics help an analyst develop a picture of the past and the present, and predict the likelihood of some event to happen in the future. The average, or mean, is just one measurement of central tendency that analysts use to make sense of some phenomenon or pattern. Others are variability and measures of position.

In this unit, you focus on descriptive statistics, confidence intervals, and hypothesis tests, with an eye toward predictive analytics. OBJECTIVES To successfully complete this learning unit, you will be expected to: Discuss descriptive statistics and assertions. Explain elementary data mining methods. Discuss the use of variables in regression-type analysis and database solutions.

pressure ulcer

Inflammation, sore, or ulcer in the skin over a bony prominence.

Key Performance Indicators INTRODUCTION The complicated path of modern business projects reflects a business environment that is continuously growing in complexity. Factors impacting a project's progress, such as new advancements in computer technology, an unpredictable economy, and the increase in stakeholder involvement make metrics and key performance indicators (KPIs) for project management important focal points. KPI measures are commonly used to help a business define and evaluate how successful it is, typically in terms of meeting the milestones and objectives toward its long-term organizational goals. TOGGLE DRAWERREAD FULL INTRODUCTION OBJECTIVES To successfully complete this learning unit, you will be expected to: Identify key performance indicators for professional domains. Compare and contrast qualitative and quantitative research methods. Suggest improvement strategies related to KPI measures. Discuss best practices related to use of facility indicators. LEARNING ACTIVITIES Collapse All Toggle Drawer[u04s1] Unit 4 Study 1 Studies Required Resources Access the following reading: In Parmenter's 2015 Key Performance Indicators (KPI): Developing, Implementing, and Using Winning KPIs (3rd. ed.).Read Chapter 1, "The Great KPI Misunderstanding," pages 3-23.Refer to Appendix E: Performance Measures Database for examples of KPIs. Multimedia You may view the following walkthrough to help you understand key performance indicators: Key Performance Indicators Walkthrough. Industry Certification Track The following SAS lessons are recommended in this unit. Access the e-courses at SAS. Log in to the site and go to My Training to find the following course: SAS® Programming 2: Data Manipulation Techniques.Lesson 7: Using Iterative DO Loops.Lesson 8: Accessing Observations.Lesson 9: Combining SAS Data Sets. Qualifying for Your Exam Voucher In addition to academic credit, Capella provides an opportunity to earn an exam voucher to current learners who meet specific criteria. If you follow this certification track throughout the duration of the course and complete all of the necessary tasks each week, you can qualify for an exam voucher to take your SAS certification at no additional cost. See the Campus IT Industry Certifications page for qualifying criteria details. Toggle Drawer[u04s2] Unit 4 Study 2 Analytics Internship: ETL and Data Warehousing Analytics Internship: ETL and Data Warehousing Transcript In this Vila Health activity, you will have the opportunity to speak with key stakeholders from Clarion Court in order to learn more about the data you will need to complete your assignments. The Vila Health director of IT will also be available to provide insight into the structure of the Vila Health data warehouse. Toggle Drawer[u04s3] Unit 4 Study 3 Study Group Tasks The recommendations that your group agrees to this week need to be included as part of the midpoint review and final report and will contribute to your final group report grade. It is critical, therefore, that you do not skip any of these discussions. You will be able to make changes to your recommendations at any time during the course but skipping a topic will negatively impact your grade. Review Analytics Internship: Data Types and Sources and Analytics Internship: ETL and Data Warehousing, provided in the Resources. Consider the topics for discussion as you watch the scenarios. Search for details that are specific to these topics and that will help you make recommendations to Vila Health. This week's topics for discussion: What KPIs are currently used in the health care industry related to pressure ulcers and falls in nursing homes and skilled nursing facilities? What data and calculations are required to create and report on these KPIs? Do you currently have sufficient data available to create reports on these KPIs for Clarion Court? If yes, what fields or variables will you use to do so? If no, what additional or different data do you need? Keep in mind the role you are playing in your group. You may find that some information is more useful to your role than others. Your group will need to choose an area to meet outside of the courseroom to discuss these topics and formulate your recommendations. See the Unit 1 discussion, Planning Your Group, for more information on roles and social media. Resources Analytics Internship: Data Types and Sources | Transcript. Analytics Internship: ETL and Data Warehousing | Transcript. Toggle Drawer[u04a1] Unit 4 Assignment 1 Data Sources and KPIs Overview KPIs usually do not emerge from source systems directly as they are. They are usually a calculation, or series of calculations, made on a combination of variables from a variety of sources. When first identifying a KPI, you need to figure out how to measure it, where the data will be sourced, and how to manipulate the data to translate it into a meaningful indicator. By doing this assignment, you will gain an understanding of what work is needed "behind the scenes" to build KPIs and related reporting. Since KPIs are often the main point of contact an executive has with the organization's data, it is important for analysts to understand what the KPIs are composed of, and what factors might contribute to the change in value for a particular KPI. Analysts can then answer the "why" questions asked by executives regarding the degradation or improvement in performance on a particular KPI. Instructions Use the industry and the industry-specific KPI from your Unit 4 Discussion 1 initial post as you complete the following tasks and analysis: Identify the potential source systems for the data you need to calculate this KPI, including definitions of the data source(s) and the variables from those data sources you will need to calculate the KPI. Create a sample data set in SAS that includes the variables identified above as inputs to the KPI calculation/manipulation, and 10 sample records. Calculate the identified KPI using the sample data set and included variables. Use the SAS Data Step and any other SAS procedures needed to prepare the sample data set. Based on your work in this assignment, create a step-by-step guide for identifying, sourcing, and calculating a new key performance indicator, and make recommendations for best practices related to these steps. Include your code, output, and a screenshot of the data set in your submission. Your assignment will be graded on the following criteria: Identify key performance indicators relevant to a professional domain. Identify data sources to use in calculating a KPI. Create a SAS data set from scratch. Identify calculations and manipulations needed for translating source data into a KPI. Recommend best practices to stakeholders clearly and succinctly. Refer to the Data Sources and KPIs Scoring Guide for more details. Additional Requirements Written communication: Written communication is free of errors that detract from the overall message. APA formatting: Resources and citations are formatted according to APA current edition style and formatting. Number of resources: Include a list of any articles or readings you reference or use to complete your assignment. Length of paper: Four to six (4-6) typed double-spaced pages. Font and font size: Arial, 10 point. Resources Data Sources and KPIs Scoring Guide. APA Style and Format. Toggle Drawer[u04d1] Unit 4 Discussion 1

KPI Measures and Improvement Strategies For this discussion, you will select an industry that is familiar or of interest to you and analyze its key performance indicators. Use the Capella University Library and the Internet to find key performance indicators commonly used in your selected industry, and provide an overview of a minimum of 3-5 of them. Select one KPI to focus on for the remainder of this KPI analysis. Define the business problem that is being measured by your selected KPI, and select a goal, or optimal value, for the KPI, along with references supporting that goal. Identify the data types and data sources that would be required to analyze and report on your selected KPI. Compare and contrast the quantitative and qualitative research methods that might be used to assist in improving your selected KPI and identify the advantages of each method with supporting references. Response Guidelines Respond to at least two other learners and share with them the information in their initial posts that best helped you in understanding the concepts. Resources

Inbox - (1) Susskind, RickTeam Project Details Team Project Details From: Rick Susskind, Data Analytics Mentor To: Mohammad Bangoura I have another project for you and your team - and this time, you're going to start getting your feet wet in terms of working with data. Come see me as soon as you're settled in and I'll give you the details. CLOSE Use your Vila Health notebook to reflect on what you have learned about the situation. Enter notes here... CLOSE Progress Panel Total Progress: 0% Introduction Read Interview with Rick Susskind Documents Read Introduction After completing the activity, you will be prepared to: Familiar with the context for the group project assignments. Able to apply the case study information to the details of your group project assignments. Able to discuss potential data sources and attributes relevant to the case study and the group project. Analytics Internship: Data Types and Sources The virtual internship is intended to help you develop the skills needed to be a knowledgeable data analyst and a collaborative member of a working group or team. In each course, you and your teammates will be given a new business problem to address through the creative use of analytic methods, tools, and strategies. In this course, you will work with your team to determine how descriptive analytics can shed light on some key performance metrics. NOTE: If you are taking classes concurrently, you should always complete the Analytics Internship module in the earlier course in the sequence. For example, if you are taking ANLT5002 and ANLT5010 concurrently, complete the first Virtual Internship module in ANLT5002 before starting the first Virtual Internship module in ANLT5010. Data Types and Sources Welcome back to your internship with Vila Health's Data Analytics team. As part of their efforts to better utilize the vast amounts of data generated within their organization, Vila Health's leaders want to look at how they are using KPIs to address real objectives and goals. Your mentor has a project for your team that will involve looking at two key metrics for Clarion Court in order to identify ways to improve the facility's performance in these two areas. CLOSE Vila Health Logo Welcome Mohammad Bangoura HOMENEWSABOUTLEADERSHIP Transforming lives through Science, Education, & Exceptional Care. Health Care Informatic Professionals. RECENT NEWS & ANNOUNCEMENTS DELAWARE COUNTY HOSPITAL OFFERS FREE FALLS PREVENTION SCREENINGS FOR SENIORS MANCHESTER, Iowa. 09/02/2015 - For many seniors, falls can mean the difference between remaining in their own homes and the need to enter a long term faci... Read More » VILA HEALTH FORMS TEAM TO EXPLORE MEASURES TO AVOID UNNECESSARY HOSPITAL READMISSIONS In an effort to reduce the number of unnecessary hospital readmissions, Vila Health is forming a multi-disciplinary task-force to address this issue. An estimated one in... Read More » RICHARD HOLMES TAKES THE REINS AS NEW MARKETING DIRECTOR Richard Holmes recently joined St. Anthony Medical Center's strategic team as marketing director. Richard brings his strate... Read More » AWARDS & RECOGNITION: Twin Cities Monthly Deems St. Anthony's "Most Trusted Hospital" in People's Choice Survey. St. Anthony's Labor and Delivery Unit Wins Fifth Nursing Excellence Award From APNA. FEATURED FACT: The first participants of Vila Health's Business Analytics Internship partnership with Capella University will begin their internship in October 2015. RECENT NEWS & ANNOUNCEMENTS Delaware County Hospital Offers Free Falls Prevention Screenings for Seniors MANCHESTER, Iowa. 09/02/2015 - For many seniors, falls can mean the difference between remaining in their own homes and the need to enter a long term facility. As part of national Rehabilitation Awareness Week (Sept. 21-25), specialists from the Delaware County Sports Medicine Center in Thorpe and Delaware County Hospital will offer free falls prevention screenings to anyone concerned about their fall risk. According to the Iowa Department of Health and Human Services, falls are the leading cause of accidental death among people aged 65-plus in Iowa. "A fall can result in a significant change in lifestyle and the cost - personal and financial - to a person can be considerable," said Kent Kerheim, PT, manager of the Delaware County Sports Medicine Center in Thorpe. "By coming to this screening, someone may learn a few easy adjustments they could make to their home situation or daily routine and ultimately, potentially prevent a fall." The free screenings take five to 10 minutes and involve two short tests of a person's physical abilities. If someone is identified as at-risk, follow-up referrals can be scheduled on the spot. Referral appointments will consist of meeting with a physical therapist to address issues and identify possible solutions. Although the screenings, available at Delaware County Sports Medicine Center on Thursday, 9 a.m.-3 p.m. are free, appointments are limited and reservations are requested. Please call 851-370-6060 to reserve a spot. Vila Health Forms Team to Explore Measures to Avoid Unnecessary Hospital Readmissions In an effort to reduce the number of unnecessary hospital readmissions, Vila Health is forming a multi-disciplinary task-force to address this issue. An estimated one in five elderly patients in the U.S. is readmitted to the hospital within 30 days after leaving, and about 90 percent of the readmissions are unplanned according to a 2013 analysis of Medicare claims data in Health Affairs. Areas being examined by the task force include: Transition conferences with care givers to identify resources needed for at-risk patients. Follow-up appointment procedures. Standardizing discharge communications. The team is expected to recommend a strategy to decrease expected 30-day, all-cause readmissions at St. Anthony Medical Center, Mercy Hospital, Independence Medical Center and Valley City Regional Hospital by 15 percent. Richard Holmes Takes the Reins as New Marketing Director Richard Holmes recently joined St. Anthony Medical Center's strategic team as marketing director. Richard brings his strategic vision, multi-faceted background, and hospital industry experience to the marketing team, where he is responsible for the strategic direction of hospital communications, brand recognition, and social media marketing. Richard holds an MBA from Stanford Business School. For five years prior to joining St. Anthony's, Richard developed a successful targeted, revenue-enhancing marketing plan for a major hospital system based in Omaha, Nebraska. In his spare time, Richard enjoys spending time with his wife and two dogs, travelling, and home brewing. We welcome you to St. Anthony's, Richard! VILA HEALTH HOSPITALS Hilding-Long Memorial Hospital (Park Rapids, MN) Mercy Hospital (Bloomington, MN) Queens Hospital (Alexandria, MN) (Psychiatric Hospital) St. Anthony Medical Center (Minneapolis, MN) Vila Health Ambulatory Medical Center (Eden Prairie, MN) Superior-Parkland Hospital (Parkland, WI) Oxbow Regional Hospital (Eau Claire, WI) Delaware County Hospital (Manchester, IA) Independence Medical Center (Waterloo, IA) Valley City Regional Hospital (Valley City, ND) VILA HEALTH STRATEGIC GOALS Vila Health will transform lives and provide quality health care through a nationally recognized, patient-centered system of care that includes: A comprehensive system of health care delivery that spans the entirety of our service area. Consistent, holistic patient care that meets patients and their families where they are physically and emotionally, while providing the best options in the best manner possible. An enhanced patient encounter that leverages health information technologies to deliver a positive, engaging, and consistent experience with every interaction. The best practitioners and healthcare professionals, working together to create a culture of excellence and performance. OUR MISSION, VISION, AND VALUES Mission Vision Values Vila Health is a comprehensive system of health dedicated to preventing and treating illness and improving the health of the people it serves through innovative and compassionate care. Vila Health aspires to transform lives through science, education and exceptional care, locally and globally. Vila Health is dedicated to providing quality health care by creating a system of care that promotes compassion, integrity, and accountability in all its dealings with patients, staff, and other partners. LEADERSHIP Name Position Department Ronald Bennett President and Chief Executive Officer Executive Leadership View Profile » Cassie Woo Chief Financial Officer Executive Leadership View Profile » Nicholas Martinez Chief Administrative Officer Executive Leadership View Profile » Merrill Kirk Executive Vice President Vila Health Group View Profile » Scott Patterson Executive Vice President Hospitals and Specialty Services View Profile » Malcolm Moore Executive Vice President Strategy and Business Development View Profile » Dwayne Hanson Senior Vice President Southwest Region (Delaware County Regional Health System President) View Profile » Melinda Gibson Senior Vice President Northwest Region (Red River Rural Health System President) View Profile » Malcolm Knowles Senior Vice President Northeast Region (Wisconsin Assets President) View Profile » Ruby Young Senior Vice President General Counsel and Secretary to Vila Health Board of Directors View Profile » Geoffrey Vaughn Senior Vice President Central Region (St. Anthony Medical Center President) View Profile » Close x All rights reserved © Vila Health Activity Log INTERVIEWS Rick Susskind Rick Susskind Portrait Interview Q & A Rick Susskind Interview Interview Good! There you are! Evidently, we didn't scare you off with the last problem. I know it was somewhat open-ended, and I'm glad to see that you can handle some degree of ambiguity. Let's get started. I have a lot to cover with you today and not a lot of time, so let's jump right in. The last project you worked on here at Vila Health involved identifying ways that data analytics could have been used to help us make strategic decisions about one of our facilities - the Clarion Court long-term care facility. You didn't work with actual data, but instead you were asked to consider what data and what kind of analytics processes would have helped stakeholders make a more informed decision. Well, we're asking you to look at Clarion Court again. This time, your group will need to work with data in order to identify useful pieces of information. First, though, let's review some of the basic concepts you'll need to understand in order to tackle this project. We should recap the analytics lifecycle, examine the various types of data you might encounter, and then broadly address how descriptive analytics are applied in a healthcare setting. I know! It's a lot to cover, so let's go. Oh... feel free to use your notebook to capture any thoughts or questions that occur to you. We've spoken before about the analytic life cycle. The previous group task focused on the first step - identifying the business problem. The next steps in the process focus on the data itself - determining what data is available, what condition that data might be in, determining how to prepare or otherwise transform that data, and (and this is no small matter) determining how to acquire the data for analysis. As you are exploring the business problem, you should ask yourself 'what data is available? What is the quality of the data and how could poor quality data affect the analytical process?' In addition, the level to which you understand the business problem and the stakeholders' objectives will affect your ability to determine how useful the available data will be. A good analyst needs to understand the data - the overall quality of the data, the source or sources of the data, and the inter-relationships between data from a variety of sources - before attempting to create a solution. So... when we're talking about health care, data is everywhere. There's clinical data - this would include information collected in the electronic health record, lab results, images from radiology, and so forth. There's operational data such as schedules and other staffing data, training records, suppliers, and so forth. There's also strategic data such as benchmark data, information about competitors, or population health data. As you can see, we're talking about internal and external sources of data. It's important, too, to remember that the form of the data we're looking at can vary - you might have structured data, which could be transactional data or time-phased data... you could have unstructured data not only in terms of clinical data such as provider notes, but also in the form of social media, warranty data, customer service feedback, and so forth. Then there's data generated by medical equipment or sensors. RFID, QR codes... even GPS. And all the while there are new forms of data - images, video, voice records, and, as I mentioned, GPS. The key thing to remember is that data analytics in the healthcare industry is a fast-moving field. There's a lot going on. In terms of what we do with that data, healthcare isn't all that different than other industries. The starting point for most data analytics would be descriptive analytics. We need to use data to understand what's been happening in order to make informed decisions. Descriptive analytics provides methods that can help take the raw data - which isn't telling anyone anything for the most part - and convert it into useful information that leaders can use to make informed decisions about how we do our work. Converting the raw data produces charts and reports that could illustrate trends and insights. Let me give you an example of how descriptive analytics has helped us improve efficiency and quality of care. There's significant interest in reducing disparities between African American and White patients in regard to hypertension control. Using descriptive analytics, we were able to identify patterns in the screening, treatment, and follow-up care we were providing in all our clinics and physician practices. The knowledge we gained from this analysis has allowed us to create targeted goals in our hypertension control programs. As a result, we've seen a significant narrowing in the disparity in this area over the last two years. Several clinics report no disparity at all. Case Study: Persistent Performance Issues at Clarion Court So... let's move on to the specific task for your group project. We're going to be looking at what's going on with Clarion Court again, but this time we're going to look at how we can use data to provide more insight into specific questions. As was mentioned last time, Clarion Court has struggled with performance issues for some time. Two areas of particular concern are fall and pressure ulcer prevention - and, knowing that you are data experts and not health care providers, I've put some basic materials about both these issues in your documents folder, which you can review later. The bottom line, though, is that both fall prevention and pressure ulcer prevention are important measures of quality of care. Unfortunately, despite the fact that there is a lot of attention around these metrics, Clarion Court has not been able to make much headway in reducing the incidence of falls or pressure ulcers. What I would like your group to do is to identify what data is available and useful to understanding these two problems. Using the data, apply analytics to the problem to identify a potential solution. When looking at the problem and the available data, try not to limit yourself with assumptions about the problem. Instead, try to consider how data might shed light on the issue. Your group may want to work on generating questions about the issues that could be explored through data analysis. For example... when do falls occur? Are there patterns to be found? Where do they occur? [calendar notification sound] Oh, there's my phone - I need to take this call. In addition to the materials I mentioned earlier, I also posted a write-up of the case study in your documents folder. Go ahead and take a look at them all. I'll see you soon. NOTES SESSION 1 100% Introduction Read Interview with Rick Susskind Documents Read You can now download the record of your decisions or you can go through the activity again and download a cumulative log when you are ready. Download My Activity Log Relevant Documents: Help Panel Progress Your progress and percentage of completion is stored here. Email Email gives you guidance about what you should be accomplishing in the Vila Health activities or provides additional information necessary for your course discussions or assignments. Intranet The Vila Health intranet is a rich source of information about the company and the people who work there. You may be expected to analyze not only what is being communicated on the intranet, but also what isn't being communicated with that resource. Documents In some activities, company documents, newspaper clippings, and other documents will be made available for your analysis. Notes In some activities, you may be provided a tool for taking notes and recording your impressions and questions about the activity. Transcript The transcript provides a text only version of the content contained in the activity. In some activities, portions of the transcript will be populated based on your decisions. Capella University logo Help make Vila Health a better place! Your feedback is important to us. Please take two minutes to complete the survey. Give us your feedback »

Licensed under a Creative Commons Attribution 3.0 License. Activity Complete! In this activity, you met with your mentor and he provided you with some basic information about your group project. That information and any notes you took are available in your activity log. You can review the activity log now, within this Vila Health activity, and you can also download a PDF file of the log for later review. Later in the course, you will return to Vila Health to gather more information about the project. In the meantime, you are expected to form a group with several of your classmates and to discuss various aspects of the case as it relates to your assignments. Resources to help you with these tasks are available in the courseroom. The choices you make in each internship activity are captured in the Activity Log. You will be able to view and download that log at the end of each Virtual Internship activity. View My Activity Log Repeat the Activity

disparities

Marked differences or distinctions.

metrics

Measurements that evaluate results to determine whether a project is meeting its goals

Quartiles. Quartiles divide the data into four groups, each containing an equal number of values. Quartiles are divided by the 25th, 50th, and 75th percentile, also called the first, second and third quartile.

One quarter of the values are less than or equal to the 25th percentile.

Unit 3 PRINT Phase I - Stakeholder Analysis and Milestones INTRODUCTION Stakeholders can have a positive or negative effect on the project, and vice-versa: the project can have a beneficial or detrimental effect on the stakeholders. Recognize that stakeholders are critical to the success or failure of your project and stakeholder analysis is a critical part of project management. To better manage expectations of all participants, this analysis is next on the list of team tasks to perform. TOGGLE DRAWERHIDE FULL INTRODUCTION In this unit your team is asked to use the work done in Unit 2 and expand your examination of the significant stakeholders. Your team is performing this project exercise because a stakeholder analysis will help to determine the "wants and needs" of the stakeholders of your project. Understand that stakeholders are all those who have a vested interest in a project. This can consist of individuals, organizations, and professional bodies. They can be part of the organization working on the project, customer organizations, or outside of these organizations: government and regulatory bodies, trades unions, etc. Use your Communication Plan from Unit 2 in the Stakeholder Analysis. After stakeholder analysis is completed, the team can better plan and bring about communication across the project among the significant stakeholders. For example: What kind of narratives need to be sent to each type of stakeholders? What is the level of detail and how frequently the communication should occur? Who are the demanding stakeholders, and how should we address their needs? LEARNING ACTIVITIESCollapse All Toggle Drawer [u03s1] Unit 3 Study 1 Studies Readings Use your course file, ITEC5900 Project Plan, to read the following section: Stakeholder Analysis. Use the Internet to complete the following: Young Upstarts. (2015). 9 best practices for consultants to improve their client relationships. Retrieved from http://www.youngupstarts.com/2015/03/19/9-best-practices-for-consultants-to-improve-their-client-relationships/ SkillsYouNeed (n.d.) Top tips for effective presentations. Retrieved from https://www.skillsyouneed.com/present/presentation-tips.html Research Use the Capella library, the Internet, and other scholarly resources to perform scholarly research on the issues that your project is facing at this point and determine the appropriate response to those issues or concerns. Multimedia Complete the following: Cambridge Educational (Producer). (2015). Information technology consultant—Career Q&A;: Professional advice and insight [Video file]. Retrieved from https://fod.infobase.com/PortalPlaylists.aspx?wID=107300&xtid;=93222 (18 mins) Toggle Drawer [u03a1] Unit 3 Assignment 1 Stakeholder Analysis Instructions Refer to the course file, ITEC5900 Project Plan, for more information about stakeholder analysis and milestones. While not all stakeholders can be identified at this stage, project leaders need to identify the significant project stakeholders to determine their needs and expectations of the project. A stakeholder analysis does not preclude the interests of the stakeholders overriding the interests of the other stakeholders involved, but it ensures that all affected will be contemplated. Stakeholder analysis is the activity of identifying the individuals or groups that are likely to affect or be affected. Stakeholder analysis is a key part of stakeholder management and expectations. Effective communication between stakeholders is critical for the project to be successful and that everyone is on the same page. Write 2-3 pages that: Identifies primary stakeholders. Captures and records stakeholders' expectations. Explains if expectations are feasible and manageable. Offer examples of how the team can keep the client and other stakeholders committed to the project. What is the plan to make this happen? Are all stakeholders in consensus? In addition, the team will produce a PowerPoint presentation with goals, objectives, requirements, and expectations for the client consultation assignment in this unit.​ Deliverable to the assignment area: Paper with stakeholder analysis. Deliverable to your client: Presentation on goals, objectives, requirements, and expectations. Review the scoring guide prior to developing and submitting your assignment to ensure you meet all evaluation criteria. Additional Requirements Your assignment should also meet the following requirements: Written communication: Written communication is free of errors that detract from the overall message. Suggested length: 2-3 pages, typed and double-spaced, not including the title page and reference list. Font and font size: Times New Roman, 12 point. Resources Stakeholder Analysis Scoring Guide. ITEC5900 Project Plan. Toggle Drawer [u03a2] Unit 3 Assignment 2 Client Consultation Instructions The status meeting with the client is intended to provide them with an update on the progress of the project. It gives an opportunity for the team and stakeholders to make sure that the project is proceeding as expected. If any issues, risk, or other concerns should arise, now is the time to address them. Moreover, this can establish greater trust and confidence that the project team is performing as expected. Be prepared and professional in all aspects of conducting this meeting. For this assignment, meet with your client to get confirmation of vision and objectives of project. Purpose of Meeting: Present goals, objectives, and requirements to the client. To reach agreement and consensus on goals, objectives, and requirements. Logistics of Meeting: Set up Adobe Connect meeting with the client. Send out meeting invitations to the client, the team, and other stakeholders. Conduct the meeting and be sure to record it. Submit the recording of the meeting. Review the scoring guide prior to developing and submitting your assignment to ensure you meet all evaluation criteria. Reference Young Upstarts. (2015). 9 Best Practices for Consultants to Improve Their Client Relationships. Retrieved from http://www.youngupstarts.com/2015/03/19/9-best-practices-for-consultants-to-improve-their-client-relationships/ Resources Client Consultation Scoring Guide. 9 Best Practices for Consultants to Improve Their Client Relationships. Toggle Drawer [u03d1] Unit 3 Discussion 1 Preliminary Milestones Performing a stakeholder analysis is intended to reinforce the team's understanding of the project needs. Once this is done, the team can begin to identify the significant deliverables needed to complete their objectives, stimulating team discussion on what challenges may come. While you will continue to identify milestones as you move forward, take time now to review the milestones up to this point. Discuss what you view as a "milestone" and any you have already identified. Be clear and descriptive. Are the milestones you selected specific, measurable, attainable, relevant, and timely (SMART)? Response Guidelines Read the posts of your peers and respond to a minimum of two. More is better. Expand on the concepts covered in their initial posts. The quantity and quality of your posts will determine the value of the group's learning experience. Resources Discussion Participation Scoring Guide. Toggle Drawer [u03d2] Unit 3 Discussion 2 Team Discussion Scholars have determined that students achieve more progress if they are engaged in their own appraisal. To enrich the learning environment please take some time to reflect on yourself and your peers. Team evaluation and reflection are important aspects of this process. Examine your participation and contributions and that of your colleagues. This can help students to develop their understanding of managing expectations.

Post in the discussion area your feedback for other learners. You are strongly encouraged to do this by Tuesday so that there is opportunity for others to comment. If others were to read this, they should be able to get an idea of who you are, what kind of leader you are, and how you fit into the overall project. This is not the time or the place for a complaint or gripe session. A good leader will motivate and inspire others. How can you help make this happen? For this discussion exercise, consider the following: Using a scale of 0-5, rate your personal contributions to the team project. Discuss how you can enhance active engagement with this project. Explain how to increase the amount of feedback your colleagues can receive from each other. Describe how your teammates can better understand what is considered good work and explain why. Put in plain words, what is needed to expand team participation and contribution. Anything else you think will influence the success of your project. Response Guidelines Respond to the peers on your project team or other project teams as needed. Resources

Hello Class, In this discussion we'll be focusing on KPI's and diving into one specific KPI in-particular for the remainder of the analysis. Let's get started! For this discussion I'd like to focus on three distinct KPI measures within the healthcare industry; per member per month (PMPM) cost, readmission rates (RA), and ER Visits total (ER). Each of these KPI measures plays a direct impact on overall healthcare costs (or per member costs per month) for a healthcare delivery organization. PMPM costs can be derived as a total cost per member per month. Regarding either costs or savings attributed, PMPM rates are an excellent KPI to determine overall costs or savings per member. Readmission rates are a numerical count of all 30-day (CMS) standardized readmissions (all-cause or specific) which can attribute directly to increased healthcare costs. For ER visits, these function similar to readmission rates, but for admissions into an ER or emergency department. Both readmission rates and ER visits can be affected through various initiatives, but attribute directly to increased overall healthcare costs. For this discussion, I'd like to focus on PMPM measures as a KPI. Say for example, Hospital "A" is looking at measuring the total PMPM costs for members over the course of a program for ER Reduction, and is interested in examining this KPI after program implementation. Let's say reducing total PMPM costs from $20.00 to $15.00 in a congestive heart failure patient sample (or by 25%). In order to measure the PMPM costs, Hospital "A" will need to pull total healthcare costs for all members in the sample and divide this total cost by remaining member months in the year. Once complete, a numerical (quantitative) value can be assigned as the PMPM metric. Data sources for total cost would most-likely be claims-specific and therefore will induce a significant lag as a measure and therefore is not a realistic KPI to measure in near-real time. Data sources for this information can be a claims processing software.

Quantitative research analysis has proven to be an effective method for monitoring and controlling PMPM rates for many organizations. As an example, a coordinated care organization (CCO) was able to effectively monitor and track PMPM costs. By drilling into focus areas of how providers, members, and specialty modalities (ex. congestive heart failiure) are driving up costs, the CCO could focus and drill down on ways to intervene on cost factors (such as ER visits or readmits) (Health Catalyst, 2018). Quantitative research analysis, such as a correlational design or a descriptive design could be leveraged to build a hypothesis or case for increasing healthcare costs per member from an objective approach. Ideally, a quantitative design would be leveraged as the output value of PMPM is quantitative by-nature. However, it should be noted that a qualitative analysis may prove beneficial if-drilling into specific modalities impacting overall PMPM costs.

In the real world, I have only assisted two organizations that were very much so linked together. I was contacted by an MSP to advise and assist in recovering their customers electronic assets which were infected with the WannaCry malware that was infamously known years ago and was a big deal. I thought it ironic that we were consulted to assist what was basically our competition but money is money so we assisted in the entire recovery process as cybersecurity is one of our many specialties. What happened really made me question the competency of some of these smaller IT companies as there were problems everywhere, from physically where the servers were located to the nonexistent protection their systems had in place during the time of the attack. Fortunately, my business has an excellent track record of a grand total of zero breaches in the course of the 7 years it has been running. I am sure this is due to a combination of our diligence in protecting our customers, tools we and patching systems in a timely, organized manner. The last part was where the problems began. I got the feeling that the company that was consulting with us had no real system for patching systems. I remember thinking it strange how I was able to seamlessly patch all 130 ish systems we had at the time in less than an hour while this company was running around like chickens with their heads cut off to patch the 20 ish systems they were responsible for.

Secondly, the servers were literally stored in the owner of this companies house if I remember correctly, something I would highly recomend against as you are not guaranteed that someone at the house wouldn't accidentally plug in an infected USB drive or someone walks by and trips over a power cord. To get back to the breach, we ended up assisting the company in patching the non infected systems, isolating the systems by preventing dial backs to the malicious servers (which can be done with one of our tools which filters malicious traffic at the DNS level), and restoring systems back to normal when backups were available. I was frustrated with the main contact I had because he ended up making his customer buy antivirus software for their computers when our comapny provides this at no additional cost to our customers. This lack of foresight really was the responsibility of this MSP to begin with and I thought it was wrong to have them charged for such a huge oversight on their part. Eventually their customer moved the servers into a datacenter but I can't help but notice how little some of these IT service providers know or do to actually protect their customers. Oh, and the backups that this company made weren't even tested so many of them failed. I feel like banging my head against the wall as I type this thinking about how frustrating that was.

An organisation's most important asset is its people. And critical to an organisation's success is the extent to which its people interact effectively - both with each other as team members and with the wider organisation. This is why managing teams has become a key area for a growing number of organisations around the world. While many organisations are world-class at managing their materials and machinery, they fall short in managing the human side of their activities.This book outlines the challenges faced by both team leaders and team members in 21st-century workplaces. It proposes 13 key performance or "team health" indicators for highly effective teams based on research data collected from a large range of industry sectors, team sizes and organisations in the UK. It contributes to the understanding of the nature and functioning of team cohesiveness by describing teamwork as a multi-component variable and identifying the factors that impact on teams and the implications of teamwork for organisations.The book sets out to aid organisations by introducing a Team Performance Diagnostic (TPD) tool. The TPD enables organisations to gain an accurate and detailed insight into the real-time performance of their teams, helps team managers to understand the underlying 'people' issues within the team and how to reach higher levels of team performance quickly. The TPD has been widely used in major multinationals and the UK public sector to pinpoint hard-to-find opportunities to achieve rapid improvements. The research suggests that the use of TPD contributes to more free-flowing feedback both within the team and in the organisation as a whole, and that successful teams are indicative of a healthy organisational culture.This book is an essential guide for senior managers and policy-makers dealing with team effectiveness, and will be highly useful for students of business and management. There are many factors that may contribute to the successful delivery of a simulation project. To provide a structured approach to assessing the impact various factors have on project success. A KPI is a measurable value used by an organization to keep track of and determine progress on a specific business objective. KPIs allow organization's to evaluate how well they're performing, and if current behaviors should be continued or if a change of strategy is needed. IT departments are often measured by the solutions they provide and how effectively they tackle challenges for an organization, some process and solution driven KPIs are as follow Quality Assurance, Project Delivery Time, Service Level Agreements (SLAs), Measuring Agility. SLAs is quite a specific way to measure and present both performance (time) and quality. The numbers are agreed and measured monthly or quarterly to identify if the agreed level of service is being delivered. Consequently SLAs often get a bad rap because they often show an IT team is not as good as hoped, but on the flipside, they can present transparency and set realistic expectations if used positively. A telecom company's SLA, for example, may promise network availability of 99.999 percent (for the mathematically disinclined, that works out to about five and a quarter minutes of downtime per year, which, believe it or not, can still be too long for some businesses), and allow the customer to reduce their payment by a given percentage if that is not achieved, usually on a sliding scale based on the magnitude of the breach. Best practice when setting service standards is to first establish the needs of your customers. Both qualitative research as well as quantitative research are methods that can be used to clarify what is important to customers. Depending on the service, the types of metric to monitor may include:

Service availability: the amount of time the service is available for use. This may be measured by time slot, with, for example, 99.5 percent availability required between the hours of 8 a.m. and 6 p.m., and more or less availability specified during other times Defect rates: Counts or percentages of errors in major deliverables. Production failures such as incomplete backups and restores, coding errors/rework, and missed deadlines may be included in this category. Technical quality: in outsourced application development, measurement of technical quality by commercial analysis tools that examine factors such as program size and coding defects. Security: In these hyper-regulated times, application and network security breaches can be costly. Measuring controllable security measures such as anti-virus updates and patching is key in proving all reasonable preventive measures were taken, in the event of an incident.

Revolution

The movement of an object around another object

KPIs

The quantifiable metrics a company uses to evaluate progress toward critical success factors Key performance indicators

But in situations where you just observe and record data, a large standard deviation isn't necessarily a bad thing; it just reflects a large amount of variation in the group that is being studied. For example, if you look at salaries for everyone in a certain company, including everyone from the student intern to the CEO, the standard deviation may be very large. On the other hand, if you narrow the group down by looking only at the student interns, the standard deviation is smaller, because the individuals within this group have salaries that are less variable. The second data set isn't better, it's just less variable.

The standard deviation can never be a negative number, due to the way it's calculated and the fact that it measures a distance (distances are never negative numbers). The smallest possible value for the standard deviation is 0, and that happens only in contrived situations where every single number in the data set is exactly the same (no deviation). The standard deviation is affected by outliers (extremely low or extremely high numbers in the data set). That's because the standard deviation is based on the distance from the mean. And remember, the mean is also affected by outliers. The standard deviation has the same units as the original data.

Regression is a broad term that encompasses a wide variety of models. Regression is a great tool that an analyst can use in many situations. Regression is used in forecasting, examining relationships and their degree, analyzing key variables, and is used in binary problems. When thinking of quantitative and qualitative analysis different methodologies of regression can be used. In linear regression, it can be used to analyze numerical values. However, it is not possible to use categorical variables with linear regression. Instead there is a workaround to instead use dummy variables. Logistic regression is used for binary problems 1, 0, yes or no, etc. With these models categorical variables can be used. It is important to also follow the list of assumptions before running these models as well. This means checking for multicollinearity, normal distribution, and others depending on the method of regression.

There are also other types of regression such as ordinal, stepwise, and multivariate. Each has a situation where that type is the best to use. It is important when developing regression models to start with the basics of descriptive statistics, aggregations, and correlations. Then, make sure that the data passes each of the assumptions. It is important to remove variables that are highly correlated and to keep the model as simple as possible. If a simple linear regression model can solve the problem, it is going to be better to use that over a fancy neural network or machine learning model.

benchmark data

Use of foundational data within a social media campaign. By benchmarking, a social media entity may set and track longer-term goals and objectives, as well as effectiveness of tactics.

headway

progress toward a destination or goal

descriptive analytics

the use of data to understand past and current business performance and make informed decisions