Business: Applicares SWOT Analysis

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Business: Applicares SWOT Analysis

Table of Contents

Executive Summary
Strengths
Weaknesses
Opportunities
Threats
Recommendations
References

Executive Summary

Although Applicare is in the early stages of developing software as a medical device (SaMD), this product is projected to provide laboratories, insurance payers, and pharmaceutical companies with evidence-based solutions to manage or prevent diabetes. Based on the SWOT analysis, the companys strengths emanate from leveraging artificial intelligence (AI) tools to develop predictive models and provide a Clinical Decision Support System (CDSS) to help the target market solve health complications. Still, the report offers recommendations based on the companys perceived weaknesses and threats prevalent in the digital solution market. In this case, obtaining regulatory approval from necessary organizations is needed for the software programs launch and future growth. In addition, for the company to reach its target market, a robust internet presence is essential to allow prospective businesses to learn about Applicare and its product. Furthermore, clinical valuation is needed to provide evidence that SaMD will function properly or improve health outcomes. Nevertheless, the market analysis also highlights immediate areas of opportunity, which Applicare can exploit or focus on to strengthen its competitiveness.

Artificial intelligence (AI) has various implications for the provision of healthcare services. Data collection and analysis, clinical decision support, patient monitoring, healthcare intervention and prediction of incidences of infections are major areas where AI can be applied. Predictive modeling is a proactive approach that can help identify individuals at risk of disease or adverse health outcomes. As Applicare AI envisions to effectively serve its customers by offering evidence-based solutions driven by software to manage, prevent, or treat chronic diseases, market analysis can provide insights and help the company make better decisions. The report uses the SWOT framework to understand Applicares internal strengths, limitations, external prospects and threats within the market in which it operates. The companys SWOT model involves the following.

Strengths

Applicare possesses capabilities that are integral in competing in the software market. The companys software can leverage experience-based knowledge in Artificial Intelligence (AI) and expertise in the research advance in Machine Learning (ML) approaches for time series data (Abid, 2022). Applicares AI tools can extract and analyze information to gain insights to augment healthcare providers complex decision-making processes. For example, through computer-based programs, Clinical Decision Support System (CDSS) is expected to improve hospitals efficiency by sending actionable real-time insights (Abid, n.d.). In addition, Applicares value proposition is based on a technology-agnostic approach (Abid, 2022). Therefore, the companys software program design is intended to be compatible across the most common systems, such as proprietary wearable and patient-generated health data (PGHD) (Velmovitsky et al., 2021). In this case, AI incorporates multiple smart technologies for investigating complex patient data (Cappiello et al., 2020). Thus, such systems will help Applicare be at the forefront in uncovering patterns, facilitating data analysis, and forming new hypotheses to improve decision-making to manage life-threatening health complications (Cao, 2018). Applicares product will enhance effective patient management, personalized medicine plans, and drug discovery.

Since Applicare provides business-to-business services (B2B), predictive analytics allows it to use existing data to formulate patterns and predict future trends in diabetes, which will help healthcare providers to deliver quality care. In this regard, the predictive analytics model may be crucial in improving business efficiency (Martin et al., 2019). Whether it is assisting hospitals in providing personalized treatments or identifying individuals at risk of hospitalization to avoid exacerbation and complications of existing conditions, predictive models help understand diabetes patient data (Nibareke & Laassiri, 2020). Through its software program, the company will be able to determine the diabetes numbers, monitor the current trends of the infection, and detect patterns or what is going to happen in the future (Abid, n.d.). Applicare recognizes that now, more than ever, healthcare providers must rely on scientific-based data to strategically compete in a rapidly evolving health environment, shifting from volume-based care to a value-based system (Dagliati et al., 2018). Therefore, AI tools combined with ML may give Applicare a competitive advantage by delivering high-quality services to healthcare providers to prevent the disease, which is more cost-effective than treatment, reducing operational costs.

Weaknesses

Weaknesses are internal factors in Applicare and evaluating them can help identify areas of improvement. Hence, it needs to consider some factors that may hinder its operations. According to the companys details, one of its goals is getting Food and Drug Administrations (FDA) clearance (Abid, n.d.). The lack of regulatory approval may limit Applicares capability to adapt and provide software as a medical device (SaMD) to its potential clients. The FDA is an international body mandated to review and authorize many medical devices (Mittelstadt, 2017). The organization has various guidelines for legally placing medical software on the market. The approval may be granted when the software program creates a solution for healthcare providers and does not present a risk to consumers or if the product passes rigorous clinical trials for efficacy. Therefore, in order to provide a system that will help prevent diabetes and other related health complications, Applicare will have to obtain permission from the regulatory authorities.

Applicares limited online presence or Google Search may negatively influence its brand. The inadequate information about the company can make it lose out to competitors providing CDSS and predictive analytics services. In this regard, a prominent internet presence may help laboratories, insurance payers, and pharmaceutical companies get familiar with the digital solutions Applicare intends to offer before mass adoption. Thus, the data provided on various digital platforms can assist prospective businesses in reviewing the results of clinical trials before recommending the product to their clients (Sazu & Jahan, 2022). Therefore, increased digital visibility may allow the brand to build its credibility, maintain its reputation, and boost its engagement with the target market. Thus, a lack of awareness about the company can make Applicare fail to attract a huge market share to provide digital solutions. The company may not provide customers with quick information even if it has what they need. This implies that if healthcare providers cannot easily locate Applicare online, they will likely use services provided by other companies with a stronger brand presence.

Another obstacle that may impede Applicares operations is the lack of clinical validation. Although this is among its goals, the validation process aims to ensure that the SaMD meets users needs. In this case, Applicare may achieve this through real-world data (RWD), which is essential in demonstrating to regulators that its devices or system will work as intended for target healthcare providers. The companys software program, which is at the proof of concept and prototype development stage, must undergo a validation process (Abid, 2022). This can provide evidence on whether SaMD will function properly or analyze data relating to patients with diabetes from various sources using AI and be able to develop trustworthy predictive models for better clinical outcomes (Applicare AI solutions, n.d.). Thus, clinical validation may determine whether the RWD, which may come from multiple sources, can help better understand the adverse impacts of diabetes and prevent other conditions and comorbidities associated with the disease.

Opportunities

The major opportunity that Applicare has is establishing its global footprint and operations in emerging markets, which would undoubtedly give it an edge in the market. Significant growth is expected, primarily due to the high incidence of diabetes mellitus and the increasing demand for evidence-based models driven by high-quality software programs. This is needed to help healthcare providers prevent, manage, or treat chronic diseases (Nibareke & Laassiri, 2020). An epidemiological study indicates that between 2010 and 2030, the number of patients with diabetes in developing nations is projected to increase by 69% (Liu et al., 2022). This is more than thrice the number predicted in developed countries. In this case, emerging economies in Africa, the Middle East, and Asia represent growth opportunities for Applicare to penetrate or expand its operations because these regions show high incidence rates of this chronic disease. Thus, implementing predictive models to manage diabetes using high-quality software programs will help healthcare professionals provide personalized care.

Emerging markets in developed and developing countries can create a demand for Applicares products. Although developers of digital solutions are obligated to create safe and effective products without waiting for government approval, sometimes international regulatory statutes significantly impact these software companies. Thus, obtaining FDA or other regulatory approval is one of the main challenges that Applicare may face. However, various developing markets in countries that lack government regulations for digital health solutions may provide a potential opportunity for startups that cannot meet stringent standards set by the FDA (Crisafulli et al., 2022). Therefore, such a regulatory landscape may allow Applicare to introduce its software programs in the market and serve clients while continuing to innovate.

Threats

Using AI to develop predictive models for chronic disease complications based on data collected from Biometric Monitoring Technologies (BioMets) is an easily imitable business model. Therefore, if the business can be copied, this may increase the number of new entrants with a similar digital solution in the market. Thus, many startups in the industry can change the competitive environment and significantly impact Applicares customer base, which includes laboratories, insurance payers, and pharmaceutical companies (Abid, 2022). As more software programs enter the marketplace, their prices may decrease to compete for clients. Similarly, although other companies focus on a different niche (complication or disease), Applicare may face aggressive competition from Biofourmis, Oxitone, and Bioconscious (Abid, n.d.). These companies are more likely to expand their AI-based virtual care service to monitor other complex chronic conditions, such as diabetes. With more sophisticated programs, Applicare competitors platforms may span the entire care continuum, shrinking the available market base, especially if the demand is limited.

A robust software program cybersecurity system is integral to protecting users sensitive information and meeting regulatory requirements. Thus, some of the threats to Applicares software may include cyber-attacks, contributing to illegal access, data theft, and damage through malware. Consequently, unauthorized access can lead to the manipulation of the digital solution or its primary information and jeopardize patient care and product confidence. Lastly, government regulations for digital health solutions may act as a barrier to startups that cannot meet stringent standards set by FDA and other regulatory bodies (Mittelstadt, 2017). This can significantly impact Applicares ability to obtain the necessary approval required to operate. In this case, the regulatory landscape is dynamic, and various guidelines differ by country and are product-specific. As a result, this can lead to substantial delays in introducing the software program in the market.

Recommendations

The SWOT analysis demonstrates Applicares current standing; therefore, a few necessary improvements are needed to strengthen its market position. Firstly, the company requires a strong online presence to reach a broader market audience. Therefore, a more substantial online presence frees the company from the limits of physical borders and improves user engagement. This also may signify that Applicare is reliable and earn credibility to attract more business partnerships. Similarly, to establish a robust cybersecurity system, Applicare will have to secure the assistance of a security expert with a track record in guiding digital solution development. Popular companies in the industry may have the infrastructure to support patient data confidentiality and safety, whereas small startups may require a responsible third party to execute the task. In addition, for a small-sized company with a limited budget coupled with a lack of in-house professionals, meeting the markets requirements will demand close cross-functional collaboration throughout the software development cycle. Thus, Applicare needs to form partnerships with programmers, clinical trial design professionals, data scientists, and regulatory experts. These strategies can ensure that the company successfully introduces its software program in the market.

References

Abid, M. (2022, November 25). Answers from Dr. Abid [Interview].

Abid, M. (n.d.). Applicare AI: where we are? Where we want to go? [PDF Document].

Applicare AI solutions inc. (n.d.). Riipen. Web.

Cao, L. (2018). Data science. ACM Computing Surveys, 50(3), 142. Web.

Cappiello, C., Meroni, G., Pernici, B., Plebani, P., Salnitri, M., Vitali, M., Trojaniello, D., Catallo, I., & Sanna, A. (2020). Improving health monitoring with adaptive data movement in fog computing. Frontiers in Robotics and AI, 7, 96. Web.

Crisafulli, S., Santoro, E., Recchia, G., & Trifirò, G. (2022). Digital therapeutics in perspective: From regulatory challenges to post-marketing surveillance. Frontiers in Drug Safety and Regulation, 2. Web.

Dagliati, A., Tibollo, V., Sacchi, L., Malovini, A., Limongelli, I., Gabetta, M., Napolitano, C., Mazzanti, A., De Cata, P., Chiovato, L., Priori, S., & Bellazzi, R. (2018). Big data as a driver for clinical decision support systems: A learning health systems perspective. Frontiers in Digital Humanities, 5. Web.

Liu, J., Bai, R., Chai, Z., Cooper, M. E., Zimmet, P. Z., & Zhang, L. (2022). Low- and middle-income countries demonstrate rapid growth of type 2 diabetes: An analysis based on global burden of disease 19902019 data. Diabetologia, 65(8), 13391352. Web.

Martin, C. M., Sturmberg, J. P., Stockman, K., Hinkley, N., & Campbell, D. (2019). Anticipatory care in potentially preventable hospitalizations: Making data sense of complex health journeys. Frontiers in Public Health, 6(376), 1-15. Web.

Mittelstadt, B. (2017). Designing the health-related internet of things: Ethical principles and guidelines. Information, 8(3), 77. Web.

Nibareke, T., & Laassiri, J. (2020). Using big data-machine learning models for diabetes prediction and flight delays analytics. Journal of Big Data, 7(1), 78. Web.

Sazu, M. H., & Jahan, S. A. (2022). Big data analytics & artificial intelligence in the management of healthcare: Impacts & current state. Management of Sustainable Development, 14(1), 3642. Web.

Velmovitsky, P. E., Bevilacqua, T., Alencar, P., Cowan, D., & Morita, P. P. (2021). Convergence of precision medicine and public health into precision public health: Toward a big data perspective. Frontiers in Public Health, 9. Web.