D031 Evidence-Based Innovation Proposal
Disruptive Innovation in Healthcare Examples
The delivery of healthcare and the procedures that take place are both significantly impacted by innovation. Disruptive innovation could be an idea, a product, or a modification that transforms a process. There have been several ground-breaking technologies that have contributed to positive transformation and results in the healthcare industry. This idea has begun to spread throughout the medical field.
The utilization of telemedicine is currently among the most widespread examples of disruptive innovation. The delivery of medical care has been revolutionized through telemedicine, which became increasingly important following the COVID-19 pandemic.
It caused many parts of healthcare to be interrupted. Telehealth remotely delivers healthcare services to patients through networking technologies (Finley & Shea, 2019). It has emerged as one of the most prominent disruptive innovations in healthcare and has allowed more individuals in high-risk populations to seek medical attention. Because of this, healthcare has been forced to collaborate in previously unimaginable ways before the COVID-19 pandemic.
Using electronic medical records (EMR) is another game-changing breakthrough within the healthcare industry. The EMR enables various healthcare professionals to obtain rapid access to essential sections of a patient’s record, irrespective of where the record was initially created or kept.
The EMR can even alert the appropriate medical staff members when it is time for patients to undergo routine health checks and management. It has applications in research to enhance medical care and develop new commercial prospects. Young healthcare workers have shown more predilection for using the EMR than older healthcare workers (Janett & Yeracaris, 2020).
Nurse Innovator Role
Innovation refers to introducing a novel concept or method for carrying out a process, paving the way for enhancing a practice (Snow, 2019). A new system that delivers comprehensive medical attention centered on each patient’s requirements can be influenced by the role of disruptive innovation and the nurses.
The nurse innovator is responsible for performing the functions of a nurse scientist, nurse manager of the healing environment, and nurse detective (Snow, 2019). They investigate the causes of diseases, the efficacy of various treatments, and the implications of advances in medical technology to enhance the quality of life for patients and shape the nursing field (Snow, 2019).
To implement methods potentially affecting health care, those aspiring to become nurse scientists need to develop advanced leadership qualities and fundamental competencies such as analytical and research abilities.
The context in which healing occurs is global and considers social, cultural, political, and economic factors. In light of this reality, as a part of the interprofessional network, the nurse exerts influence over public policy and works to advance social justice in public health.
The nurses gather and interpret information, make informed evaluations, and cooperate with others. By doing so, they can help guarantee that clients receive the appropriate therapy at the proper time, ultimately leading to improved results and superior quality of life for the individual.
Using Big Data for Innovation
Big Data refers to large amounts of data that are complicated, dynamic, and uncertain enough that they defy processing by conventional means such as algorithms or processing techniques. The use of big data in healthcare can assist healthcare practitioners in influencing evidence-based practice and care by enabling the prediction of patterns and events (Wang, 2019).
Collecting and applying large amounts of data in the healthcare industry can take different forms. The use of mobile phones and other electronic gadgets, particularly smartphones, has been increasingly widespread in recent years. All of these technologies are capable of collecting, analyzing, and managing large amounts of data.
Big Data comprises data from machines such as sensor networks, X-ray and scanning equipment, and data consumers generate through social media (Wang, 2019). Healthcare organizations constantly seek methods to reduce expenses or, at the very least, find ways to avoid incurring additional costs wherever possible. Increasing one’s financial and human resources is traditionally considered an essential component of innovation.
When utilizing big data, these firms can at least verify that they are making investments where necessary because it expedites the innovation process, which leads to quicker research outcomes with reduced use of time and resource allocation (Wang, 2019).
For instance, when examining a substantial amount of data across a specific target population in preparation for the launch of a new service, they can undertake modifications at initial phases than if they delay the trial of the service after its implementation in the market. This allows them to save time and money.
They can predict how the market will react to their new product or service far beforehand instead of waiting to observe after its launch. As a result, new products are brought to market more quickly, and the chance of obsolete services is considerably reduced due to the shorter time between the idea’s conception and its launch.
The explosive growth of healthcare information has led to new difficulties as big data has developed. Many challenges arise when attempting to analyze, store, and recover massive amounts of data due to the dynamic nature of big data (Awrahman et al., 2022).
Because of their immense size and vast volume, traditional or standard database management systems cannot handle, store, and receive big data (Awrahman et al., 2022). Since a great deal of big clinical data consists of unstructured sources like handwritten notes and natural language, analyzing, integrating, and storing it presents a fair amount of challenge (Awrahman et al., 2022).
Sharing structured data is inadequate for agencies, and communicating complex data among organizations is more complicated. How to efficiently mine a massive amount of unstructured data presents a formidable challenge. The confidentiality of healthcare data is essential due to the potentially vital and delicate information about independent healthcare providers.
In the past, security and privacy issues associated with big data rendered its application controversial. Protecting healthcare information from hackers requires making it inaccessible to the general public (Awrahman et al., 2022). As a result, ensuring safety is the top priority, despite the difficulty it presents.
Ethical Use of Big Data
The ANA’s Code of Nursing Ethics influences contemporary nursing practices. Article 6 requires that the nurse, through individual and collective effort, builds, sustains, and enhances the ethical atmosphere of the work setting and work circumstances favorable to delivering safe and high-quality medical care (Ferretti et al., 2021).
The codes guide how nurses should conduct themselves ethically and what they should do if they are confronted with impediments that prohibit them from meeting their commitments. To be effective, an ethical code for nursing practice needs to offer direction on dealing with ethical issues on both the social and organizational levels.
Ethical concerns emerge when fields within healthcare, like nursing, grapple with issues of informed consent, privacy, data ownership, and the data’s potential applications (Ferretti et al., 2021).
The ANA discusses the rights of each patient to decide how, where, and for what purpose their data is gathered, used, and disseminated. It is not safe to presume that simply because a person’s identity has been removed from any link with the information collected regarding them, this permits the data to be used or shared (Schaefer, 2019).
Whether or not to communicate one’s findings to others ultimately rests with the individual. Because of this, the existence of regulatory committees to defend patients’ rights regarding the dissemination and circulation of big data is of the utmost importance.
Using New Technology for Innovation
In today’s society, new technologies and information technologies (ICT) have evolved as a sign of development, improvement, and quality, all essential factors in determining our lives. The majority of innovations are driven, either directly or indirectly, by new technologies; this includes innovations in marketing strategies and changes in consumer habits (Sounderajah et al., 2020).
Introducing new technologies has a significant bearing on the markets and the dynamics of the markets. It is occurring at a rate that is faster than in the past. When technological innovation becomes widespread in our society, it not only drives people to engage in new behaviors but also changes how they view their role as consumers; consequently, these changes give rise to the possibility of new markets (Sounderajah et al., 2020).
Tinkering and experimentation are both encouraged by technology, which speeds up the innovation process. Not long ago, the only entities that could research and develop emerging technologies were multinational firms or research institutions supported by the government.
The availability of relatively inexpensive technology has made it possible for most healthcare organizations, both large and small, to explore concepts and ideas in entirely new ways and the real world, as opposed to just in test labs (Shetty, 2020). It is now easy, for instance, to test out upgrades, adjustments, and refinements online for minimal cost.
Incredibly simple-to-use software and the advent of 3D printing have made prototyping accessible to everyone. AI is capable of simulating multiple market scenarios by using big data that is already accessible. Because virtual reality makes it possible to generate whole new blueprints, these designs can bring services and products to reality, making it possible to assess them before they are built or manufactured.
Proposed Disruptive Innovation
The utilization of continuous glucose monitoring (CGM) linked to a healthcare professional or advanced practice provider is an example of an emerging disruptive innovation that can be adopted. The measurements will allow the caregivers to monitor patients’ blood sugar levels, determine the fluctuations that occur every day, and view the most recent HgbA1c values.
This will enable the caregivers to create a tailored plan for each patient to match their needs, such as administering medications or insulin injections, an additional workup for complicated diabetes, or additional teaching regarding diet.
It is anticipated that patients will grow more conscious of their condition if they use the CGM since it will boost treatment adherence by testing blood sugar levels. It will also teach patients how to care for their illnesses and other health problems that may arise adequately.
Additionally, it will be of assistance in the process of enhancing health results within an organization. Those that utilize the healthcare services provided will be in better health, leading to an overall decrease in disease rates. It has the potential to cut down on admissions caused by diabetes complications.
Continuous Glucose Monitoring (CGM) can help healthcare organizations improve patient health outcomes. By keeping track of their patient’s glucose levels in real-time, healthcare workers can better tailor their care to each individual’s needs (Awrahman et al., 2022).
Improved glycemic control, fewer complications, and superior health, in general, can result from this (Kant et al., 2022). Reduced hospitalizations and emergency room visits are achieved by using CGM to detect hypoglycemic and hyperglycemic episodes long before they occur.
Healthcare providers may see cost savings as a result of this, and the level of satisfaction may increase. Patients with diabetes can benefit significantly from the information provided by CGM about their blood sugar levels. The patients may be more invested in their care and more likely to follow instructions, increasing patient engagement. CGM can assist healthcare organizations in identifying individuals who need extra focused monitoring and intervention, resulting in better resource allocation and utilization.
Proposed Healthcare Organization
In general, CGM can be utilized in a wide range of healthcare facilities to track the blood sugar levels in diabetic individuals, regardless of the degree of their disease or the location where they receive care. The Intermountain Medical Center in Murray, Utah, can benefit from CGM; this renowned medical facility provides numerous healthcare care, including diabetes care.
People living with type 1, type 2, and gestational diabetes can benefit from the use of CGM at this facility. It will be necessary for persons who need intensive insulin therapy, face challenges regulating their sugars within normal levels, or have experienced hypoglycemia.
Diabetic individuals can track their glucose levels more frequently and make more knowledgeable decisions regarding their nutrition, fitness, and treatment because CGM delivers real-time blood sugar levels (Awrahman et al., 2022). As the CGM gadget constantly monitors glucose levels, patients with diabetes can reduce the frequency of fingerstick tests (Tang et al., 2020). Users can be warned of impending hypoglycemia and take preventative measures promptly before complications occur.
Goal
The goal of the healthcare organization is to decrease the complications associated with diabetes; the application of CGM can help to achieve this goal. CGM can aid in better glycemic control since it allows for more frequent glucose tests and notifies users of variations in their glucose levels. As a result, diabetic retinopathy, neuropathy and nephropathy can be reduced.
Furthermore, CGM will assist medical professionals in making more informed therapeutic decisions by providing more specific data on patients’ blood sugar levels. Healthcare practitioners can lessen the likelihood of diabetes complications by creating individualized treatment strategies. In the same way, it can help those with diabetes better control their disease, ultimately leading to better patient self-management.
Relevant Sources Summary Table
| Scholarly Peer-Reviewed Sources Published in the Past 5 Years that Support the Proposed Innovation | Summary of Findings Relevant to Proposed Innovation
| Evidence StrengthLevel I–VII
| EvidenceHierarchy
| |
| APA formatted scholarly reference with a DOI or retrievable link. | Present a detailed summary of the findings and how the findings support the proposed innovation. | Refer toWGU Levels of Evidence | ||
| SCHOLARLY SOURCE 1 | Kant, R., Antony, A., Geurkink, D., Gilreath, N., Chandra, L., Zipprer, E., Munir, M., Chandra, R., Parker, G., & Verma, V. (2022). Real-time continuous glucose monitoring improves glycemic control and reduces hypoglycemia: Real-world data. Primary Care Diabetes. https://doi.org/10.1016/j.pcd.2022.09.005 | This research set out to evaluate the effects of continuous glucose monitoring on a real-time basis on various measures of glucose control in people with diabetes. This research examined 91 persons already using the Dexcom continuous blood sugar monitoring. This allowed them to compare two HbA1c readings taken, one right after the other, before and after use for at least three months. 31 people used the Freestyle Libre in a user-blinded CGM test lasting 5-14 days. Patients with diabetes receiving SQ insulin infusions continuously were also employed in this investigation. With their CGM readings, these patients could fine-tune their insulin dosages.HbA1c values in this study’s participants dropped significantly from their starting points. When real-time CGM was utilized for at least three months in diabetic individuals, the results showed a marked decrease in lab values with consistent glycemic control without raising the likelihood of hypoglycemia. This provides further evidence for the requirement and significance of continuous glucose monitoring. | Level IV | Non-experimental |
| SCHOLARLY SOURCE 2 | Tang, L., Chang, S. J., Chen, C. J., & Liu, J. T. (2020). Non-Invasive Blood Glucose Monitoring Technology: A Review. Sensors (Basel, Switzerland), 20(23), 6925. https://doi.org/10.3390/s20236925 | Based on the detection principle, this research classifies current non-invasive blood glucose measurement methods into three categories: optical, microwave, or electrochemistry. The advantages and limits of non-invasive and invasive technology, in addition to electrochemistry and optics in non-invasives, are contrasted in this paper. In addition, the current research successes and limits of non-invasive electrochemical glucose sensing devices in continuous monitoring, point-of-care and clinical contexts are discussed. | Level V | Non-experimental |
| SCHOLARLY SOURCE 3 | Rotondi, A., Wong, O., Riddell, M., & Perkins, B. (2022). Population-level impact and cost-effectiveness of continuous glucose monitoring and intermittently scanned continuous glucose monitoring technologies for adults with type 1 diabetes in Canada: A modeling study. Diabetes Care. https://doi.org/10.2337/dc21-2341 | A Markov cost-effectiveness model was employed in this research. They used a sample size of 180000 patients with Type 1 Diabetes and a mean HgbA1c of 8.1% at baseline. The importance of keeping glucose levels within a normal range in managing Type 1 diabetes is the driving force behind this research. Constant glucose monitoring revealed a notable variation. Researchers discovered that those who employed continuous glucose monitoring or intermittent scanning glucose monitoring had a decreased mortality rate. According to the study’s findings, using CGM or isCGM in the management of diabetes should reduce the incidence of diabetes-related complications as well as mortality. | Level IV | Non-experimental |
| SCHOLARLY SOURCE 4 | Pica, S., Morano, C., & Díez, R. (2022). A role for the diabetes nurse educator to telemedically support children with type 1 diabetes on continuous glucose monitoring? The COVID-19 lockdown experience. Primary Care Diabetes. https://doi.org/10.1016/j.pcd.2022.03.011 | The value of CGM for children with type 1 diabetes is outlined in this article. Evidence that nurse educators can successfully manage their patients’ glucose levels. Researchers monitored data from 59 children with Type 1 diabetes daily.As the eA1c was less trustworthy than the hgbA1c, the fact that it dropped much was a drawback.Nonetheless, the results demonstrated that DNE ensured adequate hypoglycemia control when telemedicine was used. Continuous monitoring has been shown to enhance glycemic control while decreasing healthcare costs.According to this study, telemedicine and continuous monitoring have helped diabetes educators better manage their patients’ blood sugar levels. | Level IV | Non-experimental |
| SCHOLARLY SOURCE 5 | Milne, N. (2022). How to initiate and support continuous glucose monitoring. Diabetes & Primary Care, 24(5), 139–143. Accessed on March 6th from https://diabetesonthenet.com/diabetes-primary-care/how-to-cgm | This article provides a detailed description of continuous glucose monitors and the methodology behind their blood sugar measurements.The research article compared and contrasted the various treatment options open to patients. The possible advantages of using CBG monitors were also discussed. This journal aims to encourage patients to adhere to treatment plans so they can benefit from them. This means the patient will have to stick their finger less often. Alarms can be set to indicate high or low blood glucose levels before symptoms appear, allowing for timely and safe medication modifications.Patients benefit from CGMs by feeling more informed and engaged in their care. In addition to improving their quality of life, all of this information may be uploaded and shared online with healthcare practitioners. | Level VII | Expert opinion |
Synthesis of Literature
In inpatient care settings, the use of CGMs is becoming increasingly common. Evidence shows that CGM delivers several advantages to the patient’s health. These benefits include the client becoming more conscious of how they feel, how to take medications based on blood glucose, and how to regulate their condition to avoid complications.
The articles examined different options that focused on measuring glucose levels in physiological fluids apart from blood. Non-experimental research shows a decline in the patient’s hgbA1c when health providers continually monitor their client’s sugar levels, leading to a lower incidence of deaths caused by diabetes (Rotondi et al., 2022). This resulted in a decrease in the number of people who suffered from diabetes-related complications; this result is congruent with findings from Kant et al. (2022) studies
Wearable monitors can have a vital role in the management of patients; however, the exploitation of telemedicine will imply that optimal hypoglycemia control will be guaranteed (Pica et al., 2022). CGM is a non-invasive monitoring method that encourages individuals to adhere more to their care and helps improve their overall health.
Literature supports the necessity and significance of CGM because when real-time CGM was employed for at least three months, there was a significant decrease in lab thresholds with stable glycemic regulation without increasing the risk of hypoglycemia.
This finding indicates that CGM is necessary and effective. Studies by Tang et al. (2020) concluded that the use of non-invasive glucose monitoring methods significantly reduces the rates of fingersticks, decreasing trauma to the patients.
The journal Diabetes and Primary Care provides an overview of CGMs and how they monitor the level of blood sugars. This article compares a variety of products for the benefit of patients. The possible advantages of CGM are discussed in this research article. This illustrates that patients are more likely to have fewer fingerstick tests if they follow these guidelines.
Patients may detect elevated or decreased blood glucose levels before they become ill, and therapy can be adjusted securely and efficiently accordingly. By reading this journal, patients can better grasp their conditions and learn how to participate in their care actively. Giving providers access to a patient’s continuous blood sugar levels will inform the care they deliver.
Patients with diabetes can learn more about controlling their condition by using these monitoring systems with their healthcare providers. Undoubtedly, positive health outcomes can be achieved due to CGM as it justifies the cost of disruptive innovation.
Evidence for the Innovation
The evidence presented in the chart above has been evaluated and supports the use of CGM in diabetic patients. The evaluated evidence demonstrates that the disruptive innovation of CGM can benefit care delivery. Each of the studies shows a decrease in lab levels, indicating an enhancement in their wellness or providing advantages to the usage of this technique. The suggested innovation employs CGM to allow for individualized care. This improvement is supported by evidence of increased care adherence and the provider’s capacity for bettering health outcomes.
Reflection on the Role
The application of technology in medical care is undergoing continuous development. Advanced professional nurses can provide superior and much more up-to-date care owing to the use of technology in the healthcare industry. This increases the likelihood of enhanced medical results, leading to better patient-centered care. Research based on evidence serves as a source of motivation for healthcare innovation.
As a nurse with advanced professional training, they have experience and knowledge that allows them to identify reliable data sources that support the need for transformation. My comprehension of the function of the APN has increased due to my participation in launching a disruptive innovation to enhance diabetes care.
As highly trained professionals, furthering our education and being abreast of the latest advances in our field will enable us to provide enhanced and more supportive service. I am now positioned to improve the health of communities and the quality of care they receive.
Strategies
As a nurse innovator, one of the primary responsibilities should be to promote an atmosphere that encourages disruptive innovation. One of the strategies that could be used is to promote more autonomy in the workplace. If employees, clients, and other nursing professionals can share their insights and opinions regarding how change can be fostered, they will be more receptive to innovations.
Service users are allowed to take an active role in their care, which should lead to increased adherence to their prescribed healthcare regimens. Imagination can result in the production of novel ideas that, once implemented, may appear to be risky.
In healthcare, encouraging teamwork can be a potent source of new ideas. Together, people with different backgrounds, skill sets, and experiences can solve complex issues in novel ways through collaboration (Day-Duro et al., 2020).
Collaboration between healthcare specialists from different fields allows for increased knowledge sharing, better utilization of resources, and the development of new approaches to patient care (Day-Duro et al., 2020). There are various ways to work together, such as in interdisciplinary teams or stakeholder partnerships.
Professionals in the healthcare industry can better meet the requirements of their patients if they pool their resources, share what works, and brainstorm new approaches to old problems (Day-Duro et al., 2020). Furthermore, collaboration can boost healthcare innovation by creating an environment where people feel safe trying new things and taking calculated risks.
Collaborative workplaces foster an atmosphere where healthcare professionals are more open to new ideas and willing to offer their opinions and expertise. Also, they can learn from one another’s past mistakes and work together on initiatives neither of them would have thought of on their own.
The entire healthcare system must adopt these approaches to implement new ideas successfully. There has been a significant increase in healthcare accessibility, a drop in disease transmission, and a cut in hospitalization rates. Better, more efficient methods of providing quality care to patients are essential as healthcare continues to develop and innovations emerge. Improving working conditions and implementing more flexible organizational structures can foster transformation.
References
Awrahman, J., Aziz , C., & Hamaamin, Y. (2022). A review of the role and challenges of big data in healthcare informatics and analytics. Computational Intelligence and Neuroscience, 2022, 1–10. https://doi.org/10.1155/2022/5317760
Day-Duro, E., Lubitsh, G., & Smith, G. (2020). Understanding and investing in healthcare innovation and collaboration. Journal of Health Organization and Management, Ahead-of-print (ahead-of-print). https://doi.org/10.1108/jhom-07-2019-0206
Ferretti, A., Ienca, M., Sheehan, M., Blasimme, A., Nebeker, C., Samuel, G., Shabani, M., Rivas Velarde, M., & Vayena, E. (2021). Ethics review of big data research: What should stay and what should be reformed? BMC Medical Ethics, 22(1). https://doi.org/10.1186/s12910-021-00616-4
Finley, A., & Shea, D. (2019). Telehealth. Nursing Administration Quarterly, 43(3), 256–262. https://doi.org/10.1097/naq.0000000000000357
Janett, S., & Yeracaris, P. (2020). Electronic medical records in the American health system: Challenges and lessons learned. Ciencia & Saude Coletiva, 25(4), 1293–1304. https://doi.org/10.1590/1413-81232020254.28922019
Kant, R., Antony, A., Geurkink, D., Gilreath, N., Chandra, L., Zipprer, E., Munir, M., Chandra, R., Parker, G., & Verma, V. (2022). Real-time continuous glucose monitoring improves glycemic control and reduces hypoglycemia: Real-world data. Primary Care Diabetes. https://doi.org/10.1016/j.pcd.2022.09.005
Milne, N. (2022). How to initiate and support continuous glucose monitoring. Diabetes & Primary Care, 24(5), 139–143.
Pica, S., Morano, C., & Díez, R. (2022). A role for the diabetes nurse educator to telemedically support children with type 1 diabetes on continuous glucose monitoring? The COVID-19 lockdown experience. Primary Care Diabetes. https://doi.org/10.1016/j.pcd.2022.03.011
Rotondi, A., Wong, O., Riddell, M., & Perkins, B. (2022). Population-level impact and cost-effectiveness of continuous glucose monitoring and intermittently scanned continuous glucose monitoring technologies for adults with type 1 diabetes in Canada: A modeling study. Diabetes Care. https://doi.org/10.2337/dc21-2341
Schaefer, O. (2019). Ethics in the era of big data. Asian Bioethics Review, 11(2), 169–171. https://doi.org/10.1007/s41649-019-00092-4
Shetty, N. (2020). Technology and innovation: The game changer of the next decade. Indian Journal of Orthopaedics, 54(2), 107–108. https://doi.org/10.1007/s43465-020-00081-y
Snow, F. (2019). Creativity and innovation. Nursing Administration Quarterly, 43(4), 306–312. https://doi.org/10.1097/naq.0000000000000367
Sounderajah, V., Patel, V., Varatharajan, L., Harling, L., Normahani, P., Symons, J., Barlow, J., Darzi, A., & Ashrafian, H. (2020). Are disruptive innovations recognized in the healthcare literature? A systematic review. BMJ Innovations, bmjinnov-2020-000424. https://doi.org/10.1136/bmjinnov-2020-000424
Tang, L., Chang, J., Chen, J., & Liu, T. (2020). Non-invasive blood glucose monitoring technology: A review. Sensors, 20(23), 6925. https://doi.org/10.3390/s20236925
Wang, C. (2019). The strengths, weaknesses, opportunities, and threats analysis of big data analytics in healthcare. International Journal of Big Data and Analytics in Healthcare, 4(1), 1–14. https://doi.org/10.4018/ijbdah.2019010101
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