Mary Greenley Medical Center: Business Model Evaluation

Background Information
Mary Greenley Medical Center (MGMC) was gifted to Ames, Iowa in 1916 by a Union Army officer in the Civil War named Captain Wallace Greeley. He gifted the hospital in memory of his wife Mary Greenley. MGMC is a public, nonprofit hospital and is the largest independent medical center in its primary and secondary markets. The hospital supplies 220 beds offering a wide range or medical services such as cancer care, surgery, mental health service and rehabilitation. MGMC provides health care to residents of a 13-county area in central Iowa (“About Mary Greeley Medical Center”, 2020).

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Critical Evaluation
A company’s strategy is the set of actions that its managers take to outperform the company’s competitors and achieve superior profitability (Thompson, Gamble, Peteraf, & Strickland, 2018). The strategic decision that led MGMC to winning the Baldrige Performance Excellence award was making their mission, vision, and values a huge foundation in their strategic plan. MGMC focuses on four goals which are serious safety events, employee engagement, patient engagement, and net operation margin. Another strategy of MGMC was by offering different programs within the hospital, focusing on the patient’s needs, and having patient access. A wide range of programs like cancer care offered patients to seek medical support for MGMC because not only could they get everyday medical care there but also had specialty care that is harder to find.
Business Model
A company’s business model sets forth the logic for how its strategy will create value for customers and at the same time generate revenues sufficient to cover costs and realize a profit (Thompson, Gamble, Peteraf, & Strickland, 2018). MGMC focuses on making the community that surrounds them as their primary stakeholder. They also include the community in their strategic planning. This gives them an advantage over their competition because the community believes in their vision. One of the missions of MGMC is to provide the most cost-effective health care services while still making sure all the needs of the patient is met.
Competitive Advantage
MGMC has maintained competitive advantage over their competition. Competitive advantage whenever it has some type of edge over rivals in attracting buyers and coping with competitive forces. (Thompson, Gamble, Peteraf, & Strickland, 2018). MGMC differentiates itself from other hospital in a number of ways. Above all MGMC focuses on their patients. More than 75% of inpatients and outpatients would recommend MGMC to others and has also outperformed local competitors in top-of-mind hospital recall, preferred hospital, and brand power index (“About Mary Greeley Medical Center”, 2020). They also outperform in the areas of hospice care, and home health care. One reason they maintain this advantage is by believing and focusing on the vision of “Doing What’s Right”. MGMC also focuses on adjustments in financial decisions over time. They have sustained Medicare spending per beneficiary at or close to the CMS top decile for four years. The maintain under budget for cost per adjusted admission and net revenue has remained stable over six year even with a tight labor market.
Sustainable Competitive Advantage
MGMC develops a sustainable competitive advantage by being a low-cost provider, a broad differentiation,
Vision, Mission, and Values
MGMC has a strong mission, vision and values that is Mission: To advance health through specialized care and personal touch. Vision: To be the best. Values: PRIDE in the quality of care we provide to our patients, visitors and families – People-oriented Respectful Innovative Dedicated Effective. These mission, vision and value statement works for MGMC because it is believe my everyone from the top leaders of the company to the employees and ever throughout the community.
References

About Mary Greeley Medical Center. (n.d.). Retrieved from https://www.mgmc.org/about/
Thompson, A. A., Gamble, J. E., Peteraf, M. A., & Strickland, A. J. (2018). Crafting and executing strategy: the quest for competitive advantage: concepts and cases. New York, NY: McGraw-Hill Education.

 

Improving Resource Allocation for Data Center Overbooking

Abstract
Overbooking becomes feasible because user applications tend to overestimate their resources and requirements, that tends to utilize only a fraction of the allocated resources. Overbooking has to be carefully planned in order not to impact application performance. Resource utilization and Data centres utilization can be used in this overbooking scheduler. Data send can send from sources to destination via node. Resource utilization and allocated capacity can be increased by 50% with acceptable performance degradation. Fuzzy logic functions are used to check each overbooking decisions and estimate it. Changing the acceptable level of risk is depending on the current status of the cloud data centres. The suggested approach is extensively evaluated using a combination of simulations and experiments executing real cloud applications with real-life available workloads. Our results show a 50% increment at both resource utilization and capacity allocated with acceptable performance degradation and more stable resource utilization over time.
Keywords: Proportional Integral Derivative (PID), Mitigation algorithm, Greedy algorithm

Introduction
Authors Data set for overbooking levels. It is collections of some Services and work loading data. The data that represents the collection of fields that will be returned when the data set query runs on the data source. Dataset fields represent the data from a data connection. A field can represent either numeric or non-numeric data. Main features provided by cloud is elasticity, allows users to dynamically adjust resources allocations depending on their current needs. The objective is to make an efficient use of available resources, overestimating the required capacity results in poor resource utilization. Factors contributing to lower the Data Centre Utilization: cloud provides predefined VM Sizes, which have fixed amount of CPU, memory Disk Etc.

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A set of distributed PID controllers are implemented to avoid performance degradation and to increase and keep the utilization evenly distributed among the servers. Overbooking addresses the utilization problems that cloud data centres face due to the elastic nature of cloud services. Overbooking has to be carefully planned in order not to impact application performance. It present an overbooking framework that performs admission control decisions based on fuzzy logic risk assessments of each incoming service deployment request. If delay beyond slack on critical path is initiated, then the completion time of the project may get delayed. Resource levelling is a method for smoothing a schedule that attempts to minimize the fluctuations in requirements for resources when the project completion time is fixed. Users are usually bad at estimating the requirements of their applications. This low resource utilization is a big concern for cloud data centred providers as data centres consume lot of energy and are being used in a rather inefficient way. Energy consumption does not decrease linearly with resource usage. One way cloud providers can mitigate these resource utilization problems is by overbooking. The overbooking techniques always expose the infrastructure to a risk of resource congestion upon unexpected situations and consequently to SLA violations.
This leads to:

Overestimating the required capacity results in poor resource utilization.
Lower income from consumers.
The contrary, underestimating may lead to performance degradation and/or crashes.

Overbooking is to address the utilization problems that cloud data centres face due to the elastic nature of cloud services. Overbooking has to be carefully planned in order not to impact application performance. It present an overbooking framework that performs admission control decisions based on fuzzy logic risk assessments of each incoming service deployment request. A set of distributed PID controllers are implemented to avoid performance degradation and to increase and keep the utilization evenly distributed among the servers.

Overbooking within cloud data centres to increase resource utilization in a safe and balanced way.
The cloud paradigm also introduces new obstacles for efficient resource management.
The very large scale and multi-tenant nature of cloud infrastructures offers great potential for efficient multiplexing of different services.

Our initial work on this problem include scheduling for better server utilization and admission control for capacity planning, getting an initial understanding of the overbooking problem and the risk evaluation, respectively. Cloud applications do not use the same amount of hardware resources all the time. This low resource utilization is a big concern for cloud data centred providers as data centres consume lot of energy and are being used in a rather inefficient way. One way cloud providers can mitigate these resource utilization problems is by overbooking.

Figure 1 Overbooking Fuzzy Risk Assessment
Mitigation Algorithm for Reducing Service Level
Mitigation method is used to avoid sun expected misbehaviors, such as reducing the service level of some services to avoid performance degradation. This Algorithm is used to collocate, reducing the performance degradation when overbooking. This algorithm also clear traffics for data center overbooking utilization. Proportional Integral Derivative (PID) controller is a generic control loop feedback mechanism. PID calculates the differences between the measured and desired set points attempts to minimize it by reading the control input.PID involves three parameter, Present error(P), Accumulated error(I), Prediction of error may occur (D).
1. Data Collection
Dataset for overbooking levels is a collection of some Services and work loading data. The data that representing the collection of fields that will return when the dataset queries runs on the data source. Dataset fields represent the data from a data connection. A field can represent either numeric or non-numeric data.
2. Overbooking
Overbooking is techniques used as a solution to poor resource utilization in cloud data centres. Overbooking is mainly used to handle the data centred resource utilization problems and overbooking. An implemented an autonomic overbooking framework. An autonomic framework that provides better application performance, avoiding over passing total capacity at any of the dimensions will be provided.
3. Resources Utilizations
It determines the shortest project schedule with the limited resources available.
4. Schedule with collocation
It presents a greedy approach that perform traffic-aware VM placement to increase the rate of accepted requests. It avoid repeating poor performance and to increase the chances of good collocations. VMs are suitable to be collocated for improved utilization and stable performance.
5. Prediction method
The prediction step calculates a rough approximation of the desired quantity. The corrector step refines the initial approximation using another means. Overbooking system as well as admission control techniques when dealing with elastic services need insight in future resource usage. Service requirements to avoid performance degradation due to overloaded physical resources.
Distribution of PID Controller
PID controlled this fact motivates the use of feedback to adjust the level of risk that the overbooking system is willing to face over time. We also evaluate the distributed controller approach when the data centre size is reduced to 128 cores. Furthermore, choosing an acceptable risk threshold has an impact on data centred utilization and performance. High thresholds result in higher utilization but the expense of exposing the system to performance degradation, whilst using lower values leads to lower but safer resource utilization. When overbooking CPU and I/O capacity, and a more realistic approach for the memory. The rationale for this is that problems resulting from CPU or I/O congestion are less critical than the ones coming from running out of memory. Therefore, the different risk degrees presented can be combined according to the situation, considered capacity dimensions, knowledge about the incoming service, etc. The risk assessment module gets no feedback about the current status and behaviour of the system, the current workload mixture, the data centre size, etc. In order to address this issue, we propose here a control theory approach that dynamically (re)adjusts risk thresholds depending on the system behaviour and the desired utilization n levels, allowing the admission control to learn over time depending on current system behaviour. PID Controller works properly if the performance is measured at the data centre level, obtaining a smooth utilization fluctuations (close enough to the target one) for each congested capacity dimension. However, the utilization of each server may vary from the accumulated utilization – even after applying load balancing techniques. This effect cannot be totally avoided as load imbalance is also caused by the current workload characteristics. To reduce load imbalance we propose a distributed controller approach where each physical server has its own PID controllers, one for each capacity dimension.
Related Techniques
Mathematical models for SaaS providers to satisfy customers by leasing Cloud resources from multiple IaaS providers. It proposes three innovative admission control and scheduling algorithms for profit maximization by minimizing cost and maximizing customer satisfaction level. It demonstrates effectiveness of the proposed models and algorithms through an extended evaluation study by varying customer and provider side parameters to analyze which solution suits best in which scenario to maximize SaaS providers profit using actual IaaS data from Amazon and Go Grid. An extensive evaluation to study and analyze which solution suits best in which scenario to maximize SaaS provider’s profit. In-house hosting can increase administration and maintenance costs whereas renting from an IaaS provider can impact the service quality due to its variable performance.
Dynamic consolidation of virtual machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in cloud data centres. The problem of host overload detection by maximizing the mean inter migration time under the specified QoS goal based on a Markov chain model. Through simulations with workload traces from more than a thousand Planet Lab VMs, we show that our approach outperforms the best benchmark algorithm and provides approximately 88 percent of the performance of the optimal offline algorithm. The data center efficiency is been improved and more enterprises are been to consolidate the existing system. All system resources and centralizing resource management allow increasing overall utilization and lowering management costs.
Server consolidation has emerged as a promising technique to reduce the data centre energy cost. We also present a distinguished analysis of an enterprise server workload from the perspective of consolidation and finding characteristics for it. Then observing a significant inherent for power savings if consolidation is performed using off-peak values for application demand. An implementation of the methodologies in a consolidation planning tool and provide a comprehensive evaluation study of the proposed methodologies. The size applications by an off-peak metric and place correlated applications together; there is a high risk of SLA capacity violation. If consolidation is performed by reserving the maximum utilization for each application, the application may require capacity equal to the size of its current entitlements.
As per the size of the cloud increases, the anticipation that all workloads paralyze scale up to their maximum demands. In this observation multiplexing is allowed to access cloud resources among multiple workloads, resource information have been improved. Hosting virtualized loads such that available physical capacity is smaller than the sum of maximal demands of the workloads is referred to as over-commit or over-subscription. It computationally and storage efficiently, while maintaining sufficient accuracy. It is simple method of estimating total effective nominal demand of a cloud and uses it for capacity sizing and placement reservation plan that is compliant with SLA.
Conclusion
Overbooking has to be carefully planned in order not to impact application performance. A set of distributed PID controllers are implemented to avoid performance degradation and to increase and keep the utilization evenly distributed among the servers. Feedback control is used to adapt the level of overbooking (risk threshold) that the cloud data centre has tolerating capacity. The utilization technique of data centre is not only increased in overall but also harmonized across hardware capacity dimensions and servers. A set of distributed PID controllers are implemented to avoid performance degradation and to increase and keep the utilization evenly distributed among the servers.
References
[1] A. Ali-Eldin, J. Tordsson, and E. Elmroth, “An adaptive hybrid elasticity controller for cloud infrastructures,” in Proc. of Network Operations and Management Symposium (NOMS), 2012, pp. 204–212.
[2] A. Sulistio, K. H. Kim, and R. Buyya, “Managing cancellations and no-shows of reservations with overbooking to increase resource revenue,” in Proc. of Intl. Symposium on Cluster Computing and the Grid (CCGrid), 2008, pp. 267–276.
[3] X. Meng, C. Isci, J. Kephart, L. Zhang, E. Bouillet, and D. Pendarakis,“Efficient resource provisioning in compute clouds via VM multiplexing,” in Proc. Intl. Conference of Autonomic Computing (ICAC), 2010, pp. 11–20.
[4] Y. C. Lee and A. Y. Zomaya, “Energy efficient utilization of resources in cloud computing systems,” The Journal of Supercomputing, vol. 60, no. 2, pp. 268–280, 2012.
[5] L. A. Barroso and U. Holzle, “The case for energy-proportional computing,” Computer, vol. 40, no. 12 pp. 33–37, 2007.
[6] C. Mastroianni, M. Meo, and G. Papuzzo, “Probabilistic consolidationof virtual machines in self-organizing cloud data centers,” IEEE Transactions on Cloud Computing, vol. 1, no. 2, pp. 215–228, 2013.
[7] T. Wo, Q. Sun, B. Li, and C. Hu, “Overbooking-based resource allocation in virtualized data center,” in Proc of 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW), 2012, pp. 142–149.
[8] L. Larsson, D. Henriksson, and E. Elmroth, “Scheduling and monitoring of internally structured services in cloud federations,” in Proc. of IEEE Intl. Symposium on Computers and Communications (ISCC), 2011, pp. 173–178.
[9] D. Breitgand, Z. Dubitzky, A. Epstein, O. Feder, A. Glikson, I. Shapira, and G. Toffetti, “Pulsar: An adaptive utilization accelerator for iaas clouds,” in IEEE International Conference on Cloud Engineering (IC2E), 2014.
[10] M. Dobber, R. van der Mei, and G. Koole, “A prediction method for job runtimes on shared processors: Survey, statistical analysis and new avenues,” Performance Evaluation, vol. 64, no. 7-8, pp. 755–781, 2007.

M. Ponmani Bharathi, currently studying B.E. computer science and engineering in ultra college of Engineering and Technology for women at Madurai

C sindhuja, currently studying B.E. computer science and engineering in ultra college of Engineering and Technology for women at Madurai

S.vaishnavi, currently studying B.E. computer science and engineering in ultra college of Engineering and Technology for women at Madurai

Ms.A.Judith Arockia Gladies received her bachelor’s degree (B.Tech-Bachelor of Information Technology) from Raja College of engineering and Technology, Madurai, and affiliated to Anna University, Chennai, and then did her Master Degree in computer science and engineering from Raja College Of Engg and Tech, Madurai. She is currently working as an Asst Prof in Ultra College of Engg & Tech for Women, Madurai.
 

Center for Diabetes Care Strategic and Business Plan

“Make no little plans; they have no magic to stir men’s blood and probably will themselves not be realized. Make big plans; aim high in hope and work, remembering that a noble, logical diagram once recorded will not die” – Daniel Burnham

Executive Summary

 According to the Centers for Disease Control and Prevention’s (CDC) (2018) statistics report, in the United States more than 30 million people have diabetes. The report states that in 2014 a total of 7.2 million hospital discharges and 14.2 million emergency visits were reported with diabetes as any listed diagnosis among adults aged 18 years or older, and diabetes was the 7th leading cause of death in 2015 (CDC, 2018). The problem of diabetes in Lowertown is even more significant. According to the community health needs assessment (CHNA) done in order to comply with the Patient Protection and Affordable Care Act (PPACA), diabetes prevalence is 14% among Latinos and African Americans. This is 6% higher than the national average of 8%.

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 Creating the Center for Diabetes care will offer comprehensive care of complex cases of diabetes and preventive management for patients with diabetes and pre‐diabetic conditions, aligning it with the core competencies of the Institute of Medicine (2001) and the goals of Healthy People 2020 (2018). The Center will offer evidence-based services in endocrinology, case management and education, and nutrition counseling. A collaborative effort will be developed to improve diabetes patient management with multi‐specialty care such as physical/occupational therapy, prosthetic/orthotics, mental health, vascular surgery, wound care, optometry, and nephrology.

 Western Hospital must carefully balance mission and money considerations when deciding the direction that will best serve the people of the Lowertown community. A proactive approach to treating complex diabetes on an outpatient basis will lessen the costs due to hospitalization for these patients and shorten lengths of stay for those individuals who are admitted. Given that the payer mix of the primary service area is not favorable for costly care, strategic action to reduce the cost of diabetes care is required. In addition, the Center for Diabetes Care strategically positions Western Hospital to take better advantage of pay for performance or pay for outcome reimbursement models (Beck, Kelly-Aduli, & Sanderson, 2018).

 Based on financial analysis and non‐financial considerations, Western Hospital should proceed with the creation of the Center for Diabetes Care. The consideration of spillover revenue is an issue that is admittedly difficult to quantify and trace back to the Center. Without the consideration of spillover revenue, the Center is not particularly viable based solely on financial considerations. However, conceptually, the Center for Diabetes Care addresses the issue of emerging patients with diabetes who may not seek preventative services or who may go to the emergency room for care. This puts the Center in line with the mission and vision of the organization.

Strategic Plan

 This document is intended as a start. It is meant as a living, changing, ever evolving instrument to empower the Center for Diabetes Care to create, imagine, and build the organization in new and innovative ways. This document is meant as a framework to guide growth and progress and shall be revisited annually to ensure there is consistency with the Mission and Vision set forth.

Mission:

 Deliver safe, high-quality, cost-effective, patient- and family-centered care, regardless of one’s ability to pay, with the goal of improving the health of the community it serves.

Vision:

 Provide patient- and family-centric care in a highly efficient manner with exceptional quality and safety outcomes for the benefit of the residents of the community.

Values: ICARE

 The Center for Diabetes Care values apply across the entire Western Hospital’s organization. These core organizational values are the foundation of our culture and support our mission to provide the best care and services to patients, their families, and communities (adapted from: University of Iowa Hospitals & Clinics, 2018).

 Innovation.  We seek creative ways to solve problems.

 Collaboration.  We believe teamwork, guided by compassion and commitment is the best way to work.

 Accountability.  We behave ethically and with integrity in all that we do.

 Respect.  We honor diversity, recognize the dignity of every person, and strive to earn the trust of all those we serve.

 Excellence.  We strive to achieve excellence in all that we do.

SWOT Analysis

 It quickly became clear that reinforcing and advancing diabetes care in the Lowertown community is our priority. We have an overarching strategic imperative to invest, align, and integrate clinical and educational activities; establish a clear plan of economic interdependency; and prepare our workforce for evolving healthcare. Understanding our capabilities and barriers is crucial to being successful (see Appendix A for the SWOT analysis).

Company Strengths

 Western Hospital has recognized the need to enhance diabetes care by offering specialized diabetes outpatient services. At the community level, Western Hospital has shown generous support of the Jefferson County Community Benefit Coalition which formed collaborative efforts with eight affiliated hospitals to identify ten specific community health needs. Diabetes care was chosen as the top priority to address.

 Western Hospital has a unique opportunity to change the health of Jefferson County by creating a Center for Diabetes Care and offering comprehensive outpatient diabetes care for the most complex cases. Many of Western Hospital’s previously established service delivery lines such as cardiac, stroke, and wound care, could benefit from spillover effects from the establishment of the Center for Diabetes Care. Collaborative efforts could easily be established and all service lines would be enhanced.

Opportunities

 The Center for Diabetes Care has a huge opportunity to make a significant difference in the lives of Jefferson County residents that have 8% diabetes prevalence, specifically in the Lowertown neighborhood where the Latino and African American diabetes prevalence is 14%. Finally, as reported in the CHNA, drivers of diabetes rates include poor nutrition and lack of exercise, and physical environment, such as availability of fresh foods and fast food. This data demonstrates a remarkable need for these services and underscores Western Hospital’s focus on improving the lives of those in Jefferson County.

Product Strategy

 People with diabetes want a partnership with their healthcare provider. They want the convenience of having their care in one place and they want superior quality. The services being offered will be developed in two phases. The initial phase is to establish the primary medical and education components of diabetes care and establish collaboration between secondary support services (See appendix B for the project timeline). The long term goal will be to create a larger, all-inclusive multispecialty center.

Short Term Goal

 This phase will establish the core primary medical and education components which include an endocrinologist, a nurse practitioner, a receptionist, and four community health workers to monitor and build relationships with patients. Along with these services, a collaborative effort will be developed between supporting services to improve patient management with multi‐specialty care. These key support services include preventative services and complication services. Preventative services can include general practitioners, additional endocrinologists, lab services, pharmacy, and dieticians. Also, patients with complex diabetes will encounter complications and need coordination of these additional services. These complication services can include cardiology, ophthalmology, obstetrics and gynecology, podiatry, and physical therapy.

Long Term Goal

 In the next 5-10 years, the goal is to create a centralized multispecialty center with primary and specialty clinics, lab, pharmacy, podiatry, mental health, and other therapies. In addition, pursue a multi‐site expansion by replicating the model throughout a multi-county service area. This multisite expansion would extend access to quality diabetes care in the greater target market, thereby having a widespread impact on the objectives of the organization.

 Through these services, this center will meet many of the patient’s needs. Functionally, the Center for Diabetes Care will meet their needs with specialized diabetes care and by offering collaborating services. Receiving services at the center will result in fewer office visits due to reduced complications, fewer co‐pays, less medication, less expensive hospitalizations, and less time away from work. Freedom will be gained through convenience of receiving services in one central location. Emotionally, this will provide a feeling of partnership and a sense of ownership over this disease, creating a feeling of being healthier and also improving their quality of life (See Appendix C for the goals balanced scorecard).

Pricing Strategy

 Pricing will be dictated by current reimbursement rates. Clinical visits will be routinely billed and reimbursed. Diabetes care supplies will be set at market standard prices for self-pay or insurance reimbursement. Education will not be reimbursed, but the regulations will be monitored closely for changes (See appendix D for patient-generated revenue by payer).

 Western’s current discharge rate for the Hispanic population 65 and older with diabetes is 386 per 1,000. The goal is to reduce this to 310 per 1,000 by the third year of operation. The average cost of an inpatient stay is $2000 a day and the patients with diabetes as the first-listed diagnosis stay for an average of five days. Simple math shows a significant savings to Western’s bottom line just by reducing the number of patients admitted with diabetes (See appendix E for the financial data summary).

Place Strategy

 The location of the Center for Diabetes Care will be on site of the Western Hospital’s urgent care in Lowertown with its own proper signage and logo display. This is critical because the space will be convenient for Lowertown residents. Having the center in Lowertown will facilitate home visits for those residents that cannot or will not visit the clinic.

 Western Hospital will provide the required start‐up resources through the capital budgeting process and grant funding (See appendix F for grant funding and projected capital costs). Thus, an initial capital cost is projected to total $175,181. The majority of these costs involves remodeling the existing office space to meet the needs of the center but also includes funds needed to upgrade this space to allow connection to Western Hospital’s data mainframe and electronic medical records (EMR).

Marketing Strategy

 The strategy is to promote awareness within the target market. The steering committee anticipates that the marketing budget will be in the range of $40,000. There are two groups that the marketing must reach. The first group is healthcare providers in the community who will refer patients to the Center for Diabetes Care. The second is the Hispanic population, 65 years of age or older, in Lowertown diagnosed with Type II diabetes and their primary caregivers.

 Marketing tactics to reach providers will include: hosting a lunch for key general practitioners and specialists at a popular local restaurant, where they will serve a healthy Mexican lunch while Dr. Novak explains the program; and deliver the Center for Diabetes Care brochures to the staff of general practitioners and specialists likely to refer patients.

 Marketing tactics to reach diabetes patients and their families will include: hosting ribbon cutting by Rosa Sanchez, State Senator, followed by press release and news stories in local papers; arrange a lunch hosted by Rosa Sanchez for church leaders and other key influencers; conduct radio spots on Spanish language radio; target online ads to primary caregivers; and print ads in the local Spanish paper.

Management and Organization

 Employees will include a Program Director. This person will be coordinating many of the startup tasks including overseeing the remodel of the facility, working with the marketing staff to assist and supplement the marketing plan implementation, coordinating new staff training, and developing operations optimization for the center. Being an endocrinologist, the Program Director will also consult on complex cases.

 Also included in the initial organizational staffing model are: a nurse practitioner to provide clinic support for less complex cases and to supervise the community health educators; four community health educators that will serve as bridges between the healthcare system and people living with and at risk for diabetes; and a receptionist to manage the office (See appendix G for staff salary projections).

Operations Plan

 The Center for Diabetes care will be located in the urgent care clinic in Lowertown. Facilities will be leased for a 3 year term. The location of the center will be convenient with parking and visible signage with displayed logos. The hours of operation will be Monday through Friday 8:00 until 17:00. During these times the center will offer two main services: diabetes care provided by the endocrinologist, nurse practitioner, and community health workers; and diabetes education classes. Additional education classes will be offered in the patient’s home if necessary.

 The space will include a waiting room, a class room, space for the receptionists, four consultation rooms, and an administrative area for the staff. The center will utilize the existing electronic health record at Western Hospital; so medical records storage will not be required. Initially, the center will lease the space to be utilized and staffed by one Endocrinologist and one Nurse Practitioner (See appendix H for projected non-staffing costs).

 In addition to direct medical care, the center will provide patient education and nutrition counseling. Critical to this service will be the educational classroom where the group education sessions will be conducted. Group diabetes education has been shown to have equal or slightly greater outcomes in improving knowledge, body-mass index (BMI), health‐related quality of life, attitudes, and HbA1c, as compared to individual diabetes education (Rickheim, Weaver, Flader, & Kendall, 2002). Therefore, the focus on group education will allow for more efficient and cost‐effective methods in the delivery of diabetes education programs.

  Other equipment necessary for the center will include exam tables, blood pressure cuffs, thermometers, scales, otoscopes, glucometers, pulse oximeters, stools, computers, desks, office chairs, a copy machine, a fax machine, and telephones. The educational center will include tables, chairs, computer, LCD projector, sound system, and a screen. The waiting room will include furniture and a wide screen HDTV. As a wholly owned and operated division of Western Hospital, many of the aspects of business startup are simplified.

Insurance for the facility, including business liability, worker’s compensation, and medical malpractice limits will be provided Western Hospital.

Western Hospital employee benefits.

Access to group purchasing vendors that provide discounted medical supplies and equipment

Facility maintenance will be provided by Western Hospital maintenance staff.

Technology support will be provided through Western Hospital Information Technology Department.

Recruitment and Training

 A big challenge is to get the right individuals in the community health worker roles. Individuals with a combination of language skills, cultural competency, the ability to collaborate with the entire care team, and appropriate clinical knowledge will be needed. The nurse practitioner will have to have the same skill set as the community health workers. They will also have to be flexible and innovative. Human Resources (HR) will be utilized to find the right candidates for the roles. HR will also assist in developing policies and procedures for the center.

 It is expected that the community health workers will have some education in healthcare or nursing. They will also need language skills. The success of this program rests on the community health workers’ ability to relate to patients. All of the staff, including the receptionist, will go through an intensive 3-week training program. The training will address cultural competency and diabetes care and prevention. They will also learn basic first aid.

Every year, there will be an annual formal training for the staff.

Social Responsibility

 The Center for Diabetes Care is being established to make an impact on the critical problem of diabetes in Lowertown. This is a major healthcare need in the community that is not being adequately addressed. Through the design and availability of services, as well as community involvement, the center will help lead the community to significantly improve diabetes health. In addition, all members of the center’s staff will be expected to be ambassadors of the center’s mission within the community. The center will focus strategies to address the disparities in diabetes care and mortality, such as reaching out to Latinos through community churches and organizations. The community will be engaged through employer and community health initiatives, as well as large community events such as diabetes fundraisers, awareness walks and diabetes camps. Through effective implementation of the business plan, the center will realize success in improving diabetes health in the community. This will be measured by the overall objectives of increased diabetes testing, increased screenings for patients with diabetes, reduced need for emergency care and readmissions, and decreased diabetes mortality rate disparities in Lowertown.

References

Beck, W. E., Kelly-Aduli, C., & Sanderson, B. B. (2018). protecting revenue at risk: Healthcare organization leaders should be familiar with and create strategies for effective performance under Medicare’s new “pay-for-value” quality programs. Healthcare Financial Management, (4), 62. Retrieved from https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edsgea&AN=edsgcl.537405342&site=eds-live&scope=site

Centers for Disease Control and Prevention (CDC). (2018). Retrieved from https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf

Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/PDF%20O/PDF%20OpenDoorFinancialAnalysis.pdf

Committee on Quality of Health Care in America, & Institute of Medicine. (2001). Crossing the Quality Chasm : A New Health System for the 21st Century. Washington, D.C.: National Academies Press. Retrieved from https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=86916&site=eds-live&scope=site

HealthyPeople.gov. (2018). Retrieved from https://www.healthypeople.gov/2020/About-Healthy-People

Rickheim, P. L., Weaver, T. W., Flader, J. L., & Kendall, D. M. (2002). Assessment of group versus individual diabetes education: a randomized study. Diabetes Care, 25(2), 269–              274. Retrieved from https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=mnh&AN=11815494&site=eds-live&scope=site

University of Iowa Hospitals & Clinics. (2018). Retrieved from https://uihc.org/about-us

Appendix A

SWOT Analysis for the Center for Diabetes Care

Strengths

Space is available in desired community

Strong leadership/Program Director

New EHR system

Support of HR for staffing

Weaknesses

Space needs significant remodel

Limited marketing budget

15 month timeline

EHR may need customizing to interface with iPads for billing

Opportunities

Lowertown demographics support the program

PPHF grant funds available

Strong community support

Lack of access to healthcare in the county

Lack of Spanish speaking providers

Can be a model for other chronic disease centers

Threats

Finding staff with the right skills and education

Short timeline for remodel construction

Dependent on outside provider referrals

Cannot bill for education

PPHF grant funds only available for three years

Appendix B

Project Timeline

Project

Months

0

1-3

3-6

6-9

9-12

12-15

15-36

Marketing

Referrals

Opening

Post Opening

Operations

Board Approval

Space Converted

Purchase Office Equipment

Policies & Procedures Implemented

Recruitment

Evaluation

Evaluate KPI’s Monthly

Evaluate Program Viability

Appendix C

Goals Balanced Scorecard

Objectives

Measures

Targets

Initiatives

Results

Financial

To operate at breakeven without grant funding

Reduce healthcare costs through preventative care

Operating budget

Key metrics about attitudes toward the healthcare system

Operating at breakeven by year 3 without grant funding

Statistically significant improvement year-over-year

Use best practice for documenting to ensure billing for all services

Empower Hispanic patients through education and advocacy

Customer

Slowing or stopping disease progression

Optimizing and reducing all risk factors associated with micro and macrovascular disease complications

Reduction in average HbA1c levels

8.5 in 2 years

Increase patient compliance and education about diabetes treatments and care

Internal Process

Reduce hospital admission and readmission

Reduce emergency room visits

The “all-cause” hospitalization for patients in the target population or the rate of overall discharge for patients with diabetes as an “any-listed” diagnosis

Third year goal is 310 per 1,000

Increase patient compliance and education about diabetes treatments and care

Network with local providers to provide culturally competent diabetes care to target population

Learning & Growth

Frequency of contacts with patient

Staff engagement

Number of check-ups per patient in a year

Retention rates and employee satisfaction surveys

6 check-ups in a year

Increases in retention and satisfaction annually

Identify patients to enroll in center

Utilize best practices and lesson learned items for education and growth

 

Appendix D

Projected Patient-Generated Revenue by Payer

Adapted from: Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/PDF%20O/PDF%20OpenDoorFinancialAnalysis.pdf

Appendix E

Financial Data Summary

Year 1

Income

Patient-generated Revenue

$95,141

Grant Funding

$175,000

Non-staffing Costs

(311,520)

Staffing Costs

(596,094)

Capital Costs

(175,181)

Reduce Diabetes discharges by 25 per 1000 (This calculation only shows a reduction of the first 25 patients)

$250,000

(562,654)

Year 2

Income

Patient-generated Revenue

$120,425

Grant Funding

$150,000

Non-staffing Costs

(285,533)

Staffing Costs

(618,287)

Capital Costs

    (3,500)

Reduce Diabetes discharges by 50 per 1000 (This calculation only shows a reduction of the first 50 patients)

$500,000

(136,895)

Year 3

Income

Patient-generated Revenue

$100,214

Grant Funding

$100,000

Non-staffing Costs

(315,659)

Staffing Costs

(641,371)

Capital Costs

    (3,500)

Reduce Diabetes discharges by 76 per 1000 (This calculation only shows a reduction of the first 76 patients)

$760,000

       (316)

Appendix F

Grant Funds and Projected Capital Costs

Adapted from Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/O/PDF%20OpenDoorFinancialAnalysis.pdf     

Adapted from Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/O/PDF%20OpenDoorFinancialAnalysis.pdf     

Appendix G

Projected Staffing Costs

Adapted from Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/O/PDF%20OpenDoorFinancialAnalysis.pdf     

Appendix H

Projected Non-staffing Costs

Adapted from Chelius, L., Hook, J., & Rodriguez, M. (2010). Financial analysis of Open Door Community Health Centers’ telehealth experience. Retrieved from http://www.chcf.org/~/media/MEDIA%20LIBRARY%20Files/PDF/O/PDF%20OpenDoorFinancialAnalysis.pdf     
 

The Center for Transforming Lives: History and Police Impact

Provide A Brief History of The Organization Program and Its Mission Statement. Include A Brief Overview of Some of The Organizational Programs And Services

 The Center for Transforming Lives (CTL) started out as the first YWCA in Texas. The program provided housing for the homeless and other services for women in need. Funding sources and name changes through the years, eventually settled on the title, Center for Transforming Lives and the program’s primary focus is providing services that promote anti-poverty for women and children (Transforming Lives, 2017). The following programs/services have been designed to fulfill the overall mission for Center for Transforming Lives which is to to elevate women and children out of poverty.  Their Mission statement is “Center for Transforming Lives lifts women with children from poverty to possibility through: Safe Homes – an on-site homeless shelter for women and off-site homes for families. Early Childhood Education – providing free or subsidized early childhood education to impoverished and homeless families. Financial Stability – individual financial coaching and other programs to promote financial self-sufficiency” (Transforming Lives, 2017).

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 The homeless service is called Rapid Housing for Families. In the program, emergency shelter is available for victims of abuse and crime then the service is extended to help women and children secure safe, permanent housing (Transforming Lives, 2017).  The early childhood development program offers free child care and access to the development program to homeless families. Low income families are also able to take advantage of the early childhood development program on a sliding scale pay basis. This means that they pay a small fee that is based on their income (Transforming Lives, 2017).  The financial empowerment program focuses on training/coaching mothers on how to manage their money responsibly (Transforming Lives, 2017).  The counseling service is provided a program named Healers of the Broken” (Transforming Lives, 2017).  The therapist in this program provide inhouse and off-site services that address many issues including but not limited to trauma and substance abuse(Transforming Lives, 2017).

Analyze Current Trends That Influence Social Policy And Social Change Relative To The Program/ Include A Description Of Current Trends That Impact The Program

 In Tarrant county Texas, 14,981 children in experience homelessness every year (Transforming Lives, 2017).  According to CTL. This problem will become worse over time due to a link between homelessness and trauma, and poor education, which lead to poor employment opportunities (Transforming Lives, 2017).    CTL seeks to change this trend providing what they describe as a two generational approach. They believe that this approach will ultimately break the cycle of poverty.  The cycle of poverty is that the hardships that the parent experience causes stress, and other financial issues. This in turn affects the children. They experience inadequate education, lack of health care and other issues (Transforming Lives, 2017).  Basically, the parent’s issues affect the children who then grow up maladjusted and experience that same hardships as their parents and so forth. The two generational model is designed to meet the needs of child and parent at the same time. The desired result being to stop this trend.

Describes How Those Trends Will Influence Social Policy And Social Change

These trends affect social policy and change by providing that conditions needed to intervene in the social problem. Kettner et. al., explains that if we want to change the problem we must modify or remove the factors that link to the condition. We must remove the cause that created a negative effect (Kettner et. al., 2017). This task can only be accomplished as a result of policy changes.

Center For Transforming Lives Part II

Describe Three Examples of Program Hypotheses

 Program hypothesis are statements that describe what you think will be the end product as a result of a certain action (Kettner et. al., 2017). For example, I hypothesize that if I apply pressure to a full balloon, it will pop. I then test my hypothesis by applying pressure to a full balloon to see if it indeed, does pop. In practice, this will look like “If I provide more food vouchers then we will eliminate food insecurity issues in our community”. Three examples of program hypothesis that are in play for CTL are:

If we provide free/subsidized early childhood education then parents will be free to work and become more self-sufficient.

If we provide classes on how to be financially stable then we will help eliminate homelessness caused by poverty.

If we provide trauma based counseling then we will eliminate homelessness due to abuse.

Provide A Thorough Description of One of The Researched Trends

Trauma is something that has cause major pain, distress, and fear. This can be mental, physical, or both (Bowen and Murshid, 2016). Service approach based on trauma realizes that trauma has a profound effect on many health and social issues. Though it is a sensitive subject, counselors understand that to focus on a client’s underlying trauma is important in the healing and recovery process. Social Policy regarding trauma based care has outlined the following categories or principles as the most important aspects of care: Trustworthiness, Safety, and Transparency (Bowen and Murshid, 2016). These three principles are paramount in the success of the Center for Transforming Lives Program.

Develop A Program Hypotheses for The Program You Selected.

CTL acknowledges that their homeless shelter is NOT a domestic violence shelter. If we establish a domestic violence shelter, then we will be able to fill that gap in services for women and children that find themselves homeless as a result of domestic violence. According to CTL, domestic violence and poverty go hand-in-hand (Transforming Lives, 2017).  The set of services needed, though similar, may be focused on victim services like protective orders, and developing escape plans. The facilities will be more secure and clients would have access to victim assistance funds to help with the transition. If we highlight these domestic violence services, then more victims will seek help through this program

References

Bowen, E. A., Murshid, N.S. (2016). Trauma-Informed Social Policy: A Conceptual Framework for Policy Analysis and Advocacy

Center For Transforming Lives (2017).  Retrieved from https://www.transforminglives.org/

Kettner, P., Robert, M., & martin, L. (2017). Designing and Managing Programs: An Effectiveness- Based Appoach. (5th ed.) Sage Publications