Fresenius Medical Care Needs Assessment and Gap Analysis

Fresenius Medical Care: Description 

Fresenius medical care is one of the leading healthcare facilities in America . The facility offers treatment for chronic kidney diseases and related health problems. Though the c entre offers treatment of other diseases , the primary focus is on kidney and associated diseases or health problems . The hospital is also recognized for offering quality service related to its specialty ( Fresenius Medical Care, 2017 ) . The hospital serve s approximatel y 19,000 patients per year with the majority being those suffer ing from kidney problems. Both inpatient and outpatient services are the offered by 6,700 employees who work in approximately 2200 dialysis clinics in different regions. The healthcare facility was started in the 15th century and subsequently boasts unprecedented experience in treating patients with renal and other chronic diseases. The facility started as a pharmacy shop but has grown to become a well-recognized medical c entre for renal and chronic diseases. Over the years, the hospital has experienced immense growth and currently projects that the number of patients will increase considerably moving into the future.

The facility’s vision is to improve the quality of life of every patient every day. To achieve this , it has continuously adopted measures and strategies that can help the treat and serve patients better (Fresenius Medical Care, 2017). Principal among these strategies is the adopti on of artificial intelligence ( Niel et al . , 2018 ; Barbieri et al., 2016; Brier & Gaweda, 2016 ). Secondly, the medical care has sought collaboration with the Renal Research Institute. This collaboration has helped the to hospital grow its capacity and subsequently offer better service to its patients. In line with this, the hospital is committed to investing in continuous growth so as to gain a competitive advantage in the industry.

N eed s Assessment/ Gap Analysis 

The number of patients with CKD has increased in recent years. This has creat ed an enormous demand for hemodialysis services to cater to the se patients. Globally, the number of patients currently stands at 3.2 million. By the year 2025, this number is expected to rise to 4.9 million (Fresenius Medical Care, 2017). These figures point towards the increasing demand for dialysis products and services mainly in such emerging markets as India and China. Fresenius Medical Care is among the largest providers of products and services for patients undergoing dialysis. Subsequently, the medical care offers a complete solution for individuals with chronic kidney failure. This entails research and development; manufacture of dialysis products; and the provision of full therapy options (Fresenius Medical Care, 2017). The company' uniqueness is informed by the fact that it seeks to offer comprehensive solutions to patients irrespective of their location. Given the demand for hemodialysis services , the company is faced with the challenge of developing an efficient and effective mechanism of serving the growing number of patients. This problem is exacerbated by the fact that the medical facility is recognized widely in the treatment of renal diseases. Th e growth in demand for hemodialysis services implies that the hospital needs to invest in measures that build the capacity of the hospital to handle the additional demand. For instance, the number of patients attended to by the facility rose from 308,471 in 2016 to 320, 960 in 2017 (Fresenius Medical Care, 2017). This upward trend justifies the need for the medical care facility to prepare for the rising demand for its services and products. It is due to this that the facility increased the number of dialysis centers from 3,624 to 3,752 within the same period (Fresenius Medical Care, 2017). 

The medical care is also operating in a volatile, uncertain, complex and often ambiguous business environment. There is, therefore, the need for the hospital to seek and invest in better ways of serv ing its patients and offer ing higher quality services. One of the key trend s in t he treat ment of renal diseases that Fresenius Medical Care has sought to pursue is the use of artificial intelligence ( Niel et al . , 2018 ; Barbieri et al., 2016) . Artificial intelligence is currently aiding health care facilities to make better decisions, offer prediction s and achieve both effectiveness and efficiency. For instance, artificial intelligence enables the se facilities to make deeper and broader organizational analysis to obtain accurate and reliable insight that support the ir overall performance. Artificial intelligence can also be applied to specific areas of an organization’s operation s . In the Fresenius medical care clinic, artificial intelligence is being used with the aim of improving the quality of treatment services offered to the patient s suffering from kidney diseases.

Artificial intelligence is used in developing an artificial kidney that can help clean a patient’s blood during the hemodialysis sessions (Kooman et al., 201 5 ) . This technology offers real-time monitoring of the changes in the kidney thus allowing the doctors to instantaneously change prescription when there is a need. For example, the artificial neural network has been used to predict anemia, total body water thus making it is easy to monitor and manage the health condition. Artificial intelligence is also applied in patient monitoring prediction model and medical image analysis. However, numerous gaps have been cited i n the use of artificial intelligence . Notably, the safety measures associated with this technology have not been adequately addressed ( Hueso et al., 2018). T o fully achieve all the dialysis parameters, the hospital requires data analysis techniques from the area of machine learning to make better decision s that would result in better services being offered to the customers ( Makino et al., 2018) . This necessitates fresh training of the personnel. 

While the facility has invested in adopting artificial intelligence, a significant percentage of its doctors and nurses do not fully understand how to use the technology and integrate it into their daily medical activities . This implies that the medical care is not likely to maximize on this technology to offer better services to its patients. Such technologies are aimed at enabling the medical staff to offer better services by reducing the time spent in carrying out procedural activities, image analysis among others. Therefore, there is a need for Fresenius medical care clinic to empower its personnel on how to fuse this technology into their day-to-day activities.

Proposed Intervention: System-wide Capacity Building 

To help t he medical care personnel to integrate artificial intelligence into their daily activities and to become more productive, the facility needs to equip them with the technical skills, information as well as necessary support. In this case , the most recommendable intervention is to carry out a system-wide capacity building program . Th is training and empowerment can be offered using different techniques. Firstly, t he doctors and the nurses need to be exposed to as much information as possible about how artificial intelligence is being used to treat chronic kidney diseases and related health problems. This means that the hospital will be required to provide publication s , peer-reviewed journals and other material that can offer as much information to the doctors and nurses as possible. The hospital also needs to offer specialized training sessions to the doctors and nurses. The training can be offered by key experts in the field or technical personnel from the companies offering the artificial intelligence solutions. Th is training will equip the personnel with the necessary skills and information on how to operate and integrate the technologies in their day-to-day operations; how to deal with technical challenges that may arise ; and to what extent the devices can be used. T raining should also adopt a coaching model so as to offer practical sessions to the trainees. This will boost their confidence in using the devices and addressi ng any issue that may arise. Such sessions will also provide the trainees with an opportunity to express their concern s and the difficulties they have experienced when using the devices and other systems adopted by the hospital.

T raining can be supplemented with other interventions to ensure that the need gap has been fully closed. The hospital can establish coordinated alliances with such institutions as the Renal Research Institute and those that offer technology-driven solutions in healthcare and business operation s to ensure that there is continuous learning. In addition to this, the hospital should provide access to repositories of information.

Overall, the hospital must offer training to the doctors and nurses and then create a culture that allows for continuous learning. T his is because the functionality of the artificial intelligence system is continuously improved. The culture should thus support and empower the doctors and nurses in adopting artificial intelligence to increase the productivity and profitability of the hospital ( Kooman et al . , 201 5 ) . A culture of c ontinuous learning is necessary because once the hospital has invested in artificial intelligence devices and systems and the personnel is trained, there is a need for follow up strategies so as to make sure that the knowledge and skills gained are effectively translated in to increased productivity and enhanced care provision .

Justification of th e Proposed Intervention 

The presence of a s kills gap is likely to affect Fresenius Medical Care negatively in various ways. Firstly , poor skills lead to reduced productivity from the employees’ perspective . T h is is because the employees are not able to fully maximize on the resources available to them (Updyke et al . , 2016) owing to lack of knowledge o n how to operate the technical devices and the high rates of error associated with this . Ultimately, t his results in low productivity and wastage of resources. This is in contrast to the goal of maximizing the use of availab le resources . Equally , an organization is expected to operate at the lowest cost possible so as to yield the maximum profit possible. Failure to do t his results in financial losse s for the company. Employees’ support is also very critical in ensuring that productivity is achieved. One of the main concerns is that when the employees are not well trained on how to handle new technology , their confidence level is low and this leads to low job satisfaction ( Hayes & Allinovi, 2018 ). This is also likely to lead to job-related stress especially when employees are under pressure to perform and offer high-quality services to the customers.

Any b usiness is expected to operate at the lowest cost possible. This, therefore, implies that there is a need to reduce any form of wastage within an organization. Waste can be symboli zed by the time wasted as the employees attempt to use the devices or operat e the complex systems, inventories wasted due to errors among others. All the business operation s must be carried out in a manner that leads to enhanced productivity of a company . Thus, minimum cost of operation is one of the parameters of high productivity . According to state health regulations, it is an ethical requirement that a health care facility maintains the safety of a patient as a priority in all its endeavors ( Runciman et al., 2017) . Injury to the patient due to negligence and human error can attract legal suits for the company or individual caregiver . The health institution is therefore required to invest in measures that ensure that the safety of all patient s is achieved. All these concern s justify the need to train doctors and nurses on how to integrate artificial intelligence into their daily activities as they attend to various patients suffering from kidney diseases.

At Fresenius medical care, three factor s justify the need to offer training and empowerment support to the doctors and nurses. First ly, from a social perspective, the hospital is operating in a n environment that demands a high quality of the services offered . To gain a competitive advantage and attract patients in this environment, the facility has to prove that it is interested in providing high-quality services to the patients . This can be achieved by developing and adopting new and improved ways of treating the patients. A rtificial intelligence has emerged as an avenue for ensuring effectiveness and efficiency in heal th care . This technology is aimed at t he overall achievement of business goals which are increased productivity and profitability. From the regulatory perspective, the hospital is expected to prioritize patients’ safety in all its operations. It is also a legal requirement for hospitals to ensure that patients don’t suffer any form of harm due to human error and negligence. E rrors are likely to occur due to lack of skills in operating the artificial intelligence devices. This is likely to be intensified if the medical personnel lack the confiden ce needed in dealing with the technical issues that may arise. From an economics perspective, investing in the capacity building of doctors and nurses is likely to improve the operation s of the facility . In this regard , the hospital seeks to strengthen its operations by adopting better technologies to solve problems and help offer better services within a shorter time and with reduced errors. Capacity building improves this in two significant ways. First ly , errors are reduced and the quality of service suffered to the patients will be increased. Second ly , the confidence of employee s will be improved and job-related stress reduced. 

I mplement ation Plan 

The medical care facility should invest in both short - term and long - term plans to achieve effectiveness in capacity building. The short-term plan may include scheduled training of doctors and nurses on how to integrate artificial intelligence into their daily operations. The training session would also help them understand why they need to positively adapt and advance their skills in using artificial intelligence to perform their duties ( Hueso et al., 2018). The trainers would include industry experts, technicians among others. The long-term plan would consist of creating a structure for how the culture of continuous learning would be implemented. This implies that facilities such as a research center or hospital library can be established to provide support to the doctors and the nurses. 

To implement this plan, a multi-disciplinary committee needs to be set up. The committee may comprise of the technical manager, quality manager, finance manager, renal department manager, human resource manager, public relations manager. This team may be tasked with the responsibilit y of developing the implementation schedule and sourcing for all the resources needed. The team w ould also ensure that the plan is implemented in the long - term to ensure that all the goals have been effectively achieved. The quality manager is tasked with the responsibility of overseeing that the plan has been implemented and all the steps from planning to re-evaluation have been adequately followed. The budget to be used in the implementation of the plan is dependent on the details that are included in the final implementation plan. For example, this would depend on the number of facilitators per training session, the number of training sessions, materials to be used in the training session, training venue, frequency of the training sessions among others. In the long-term, it would also be dependent on the cost of establishing such facilities as the research center and library. Moreover, more employees can be engaged for example, if the hospital decide s to create a resource c entre. E qually, this is subject to the centre’s areas of focus and skills required. To reduce the cost, some of the se roles can be allocated to the already existing employees.

Communication Plan 

Effective communication will play a key role in ensuring that all the set goals are achieved. In this respect , a clear communication channel should be adopted ( Shockley-Zalabak, 2014 ) . For example, both the technical and human resource manager should assess the specific issues that the doctors and nurses need training or empowerment on. With the support of the quality manager, they should develop performance indicator s as expected. They would then decide on the best activity to undertake so as to achieve the goals . This plan , once approved , would be taken to the finance manager for funding. The technical and human resource manager would be tasked with the role of implementation, monitoring and feedback. This clarity would ensure that every detail of the plan is taken into consideration thus leading to effectiveness.

Inclusivity must be adopted as a communication principle ( Shockley-Zalaba k, 2014 ; Christensen & Cornelissen, 2013). The end goal is to empower the nurses and doctors who interact and offer care to the patients . This aimed at enabling them to offer better services to the patients. In this case, therefore, the patients are the end users of artificial intelligence. A lot of focus must be given to the medical personnel’s experience and feedback as they use the skills and knowledge gained. They must thus be included in the feedback analysis otherwise the goals will not be achieved. Regular feedback analysis from both end users and the selected committee would help continuously monitor the progress thus ensuring that success has been achieved. Different collaboration tools can be used for feedback and support when face - to - face meetings are hard to plan. This is to ensure that there is no delay when the end users face any form of challenge or difficulty. The tools should also have ways of capturing data that can be used to make better decisions on how to support the nurses and the doctors. Overall, open, transparent and inclusive communication should be ensured before, during and after training has been conducted. This would ensure that the plan proceeds smoothly. 

M easur ing the Intervention’s E ffectiveness 

Training to facilitate e ffective integration of artificial intelligence by the medical personnel a t Fresenius medical care in their daily activities would result in five key benefits. These benefits can be used as the key performance indicators of the intervention’s effectiveness. T he team must monitor the quality of services offered to the patients. T his includes early diagnosis of any health problem before it becomes worse. Better medication strategies and reduced errors would indicate that the quality of the services has been improved after the training . Quality indicators include time spent in image analysis and diagnostic process ; the accuracy of the diagnosis ; timeliness of diagnosis ; reduction in negligence ; and human errors among others. 

The second indicator is a reduction in operating cost s . This will be as a result of the decrease in errors and wastage resulting from lack of capacity . Equally , increased efficiency would reduce the operating cost s . Over time , the cost of training will also significantly reduce owing to effective integration of the new technologies, 

Patient feedback will also be used as an indicator of whether or not success has been achieved. Positive feedback and customer satisfaction will indicate that the patients are receiving better services following the training. Customer referral and positive compliment s are also indicators of successful implementation of the plan. Further, an i ncrease in the level of confidence in employees will be an indicator that the capacity building efforts have born positive fruits. The employees should feel confident using artificial intelligence systems and devices because their skills and knowledge have been impro ved . The reduction errors also significantly boost the medical personnel’s confidence. Indicators of employee confidence may include fewer challenges in using the devices ; positive feedback from the nurses and doctors ; positive anticipation of improved devises and systems. Another indicator of success in the implementation of the intervention is i ncreased revenues. Satisfied customers and quality services attract are likely to attract more customers leading to increased profits for the medical facility . Overall , the business operations will be improved significantly owing to improved skills and knowledge.

Conclusion 

The increase in the number of patients with CKD in recent year has generated an unprecedented demand for hemodialysis services. Being a vital provider of these services, Fresenius medical care is tasked with the responsibility of improving its services. In the attempt to increase productivity and offer higher quality services in treating patients with renal problems, the medical care facility seeks to adopt artificial intelligence. This necessitates the need for capacity building through training to ensure that all the personnel are well prepared to deal with the new technolog y. 

References 

Barbieri, C., Molina, M., Ponce, P., Tothova, M., Cattinelli, I., Titapiccolo, J. I., ... & Stuard, S. (2016). An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.  Kidney international ,  90 (2) : 422-429. 

Brier, M. E., & Gaweda, A. E. (2016). Artificial intelligence for optimal anemia management in end-stage renal disease.  Kidney international ,  90 (2), 259-261. 

Christensen, L. T., & Cornelissen, J. (2013). Bridging corporate and organizational communication: Review, development and a look to the future. In  Organisationskommunikation und Public Relations  (pp. 43-72). Springer VS, Wiesbaden. 

Fresenius Medical Care (2017). Creating Added Value. Fresenius Medical Care Annual Report. Retrieved from https://www.freseniusmedicalcare.com/fileadmin/data/com/pdf/investors/News___Publications/Annual_Reports/2017/FME_Annual_Report_2017.pdf 

Hayes, W., & Allinovi, M. (2018). Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing.  Pediatric Nephrology , 1-3. 

Hueso, M., Vellido, A., Montero, N., Barbieri, C., Ramos, R., Angoso, M., ... & Jonsson, A. (2018). Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.  Kidney Diseases ,  4 (1), 1-9. 

Kooman, J. P., Joles, J. A., & Gerritsen, K. G. (2015). Creating a wearable artificial kidney: where are we now? Expert Rev Med Device , 12 (4): 373- 37 6. 

Makino, M., Ono, M., Itoko, T., Katsuki, T., Koseki, A., Kudo, M., ... & Suzuki, A. (2018). Artificial Intelligence Predicts Progress of Diabetic Kidney Disease-Novel Prediction Model Construction with Big Data Machine Learning.

Niel, O., Bastard, P., Boussard, C., Hogan, J., Kwon, T., & Deschênes, G. (2018). Artificial intelligence outperforms experienced nephrologists to assess dry weight in pediatric patients on chronic hemodialysis.  Pediatric Nephrology , 1-5. 

Runciman, B., Merry, A., & Walton, M. (2017).  Safety and ethics in healthcare: a guide to getting it right . CRC Press. 

Shockley-Zalabak, P. (2014).  Fundamentals of organizational communication . Boston, MA: Pearson.