Revolutionizing Healthcare: The Impact of Digital Health and Big Data Analytics on Spire Healthcare

Question

How is Spire Healthcare harnessing the power of digital health and big data analytics to improve patient outcomes, operational efficiency, and quality of care in the ever-evolving healthcare landscape?

Answer

Introduction

Digital health is the combination of digital technologies with healthcare and has brought several benefits to human society.  These benefits are growing exponentially, partly due to accelerating change in the technological sector and quicker adoption of innovative solutions in the healthcare sector. Digital health has undoubtedly brought a transformative change to the healthcare sector, and this is often labeled as disruptive innovation. It can provide access to remote and advanced care and help in designing health innovations more accurately. Accuracy and efficiency in the services can also be considered as the benefits of digital health which can be considered as a disruptive innovation. Spire Healthcare Group PLC is the second biggest contributor of private healthcare listed on the London Stock Exchange in the United Kingdom. The organisation operates a network of ten clinics and thirty-eight private hospitals in the UK. The chief aim of this assessment is to evaluate the significance of health data for quality improvement in the organisation of Spire Healthcare Group PLC.

Overview

Spire Healthcare Plc is one of the leading independent healthcare service providers in the UK which has about 39 hospitals, 33 clinics, and medical centers along with consulting rooms across England, Scotland, and Wales. The company also operates the sports medicine and physiotherapy rehabilitation center named Perform under the brand name Spire Plc. The company is associated with services related to integrated surgery, medical, and diagnostic services. Spire was formed from the sales of Bupa Hospitals to the private equity company Civen in the year 2007. The company has also opened two state-of-the-art hospitals in Manchester and Nottingham in 2017 and has also made significant investments in the capital estate (Spire Healthcare Plc., 2022). The company delivers excellent patient care with leading clinical outcomes which lead to satisfied patients across the country. Healthcare data in the company is one of the most prioritized factors within the industry.

Critical Evaluation

The selected theme for the critical evaluation is the significance of health data for quality improvement. The growth of biomedical big data analytics in the extended field of healthcare data collection is a significant factor that has led to the overall growth of the organization in the country. The utilization of AI-enabled machine learning has provided a new direction for organizations like Spire Healthcare Plc. as they can process relevant healthcare data for the benefit of the patients and the overall organization. AI and machine learning have provided substantial benefits in analysing healthcare data which has brought benefits and advantages like improved healthcare outcomes, reduction in healthcare costs, and advancements in clinical research (Bohr and Memarzadeh, 2020). AI has provided many benefits to the healthcare sector by reducing inefficiency and improving the flow of patients in hospital settings.

The healthcare organization has made significant capital investments in the research and development wing by implementing AI and machine learning which can provide significant benefits in the future and can make the organization smarter (Sharma et al., 2022).  AI implementation can help in enabling better treatment protocols for the patients and expect better outcomes. Enhancement of the digital capabilities of the organization through machine learning and AI can provide significant improvements in overall data quality assurance and quality improvement (NHS, 2023). Enabling health data through the use of AI can also help in enhancing the quality of the services provided which can ensure a targeted treatment and intervention plan for the patients.

Lewin’s Organisational Development (OD) theory regards procedures as having the aim to transfer skills and knowledge to an enterprise with the procedure to mainly enhance problem-solving skills and to handle any type of future changes (Sabharwal and Miah, 2021). The theory mainly proposes that individuals or groups are influenced by the restraining forces that can drive change in the healthcare sector. The implementation of new and innovative technological changes within the surgical technology and radiology elements within the healthcare organization can be considered the models for change management according to the Organizational Development theory proposed by Lewin (Smith et al., 2022). The development of AI and machine learning through the implementation of digital strategies has significantly helped patients obtain clear quotes faster and swiftly make informed decisions. However, there are certain limitations in the evidence which need to be further analyzed by considering alternative perspectives and interpretations.

AI can help in retrieving patient data within seconds which can ease the overall functioning of the administrative and management systems. It can significantly reduce the manual load of employees and utilize the benefits of machine learning and integrated management information systems (Licholai, 2019). The rollout of the new pricing engine by the hospital administration and management has enabled the consultants to gain a secure position in terms of offering patients streamlined and uninterrupted healthcare facilities and services. This factor has provided clear visibility and control to the company over the prices across the healthcare facilities in the country. Analysis and evaluation of patient data across the country through the help of the NHS is also considered instrumental in the overall development of the organization. The digital portals developed with the help of machine learning automation and AI have benefited both the patients and the partners which consist of the consultants and the PMI providers (Feng et al., 2022).

Spire Healthcare Plc has also applied and implemented the electronic preoperative assessment tool or ePOA which is enabled by machine learning and robotic assistance. The digital implementation of AI-based tools in surgical procedures has immensely benefited patients by providing them with an enhanced experience and helped the healthcare authorities monitor the quality of treatment and interventions (Bajwa et al., 2021). AI has also been significantly used in the healthcare data perspectives like analyzing X-ray images, and mammograms and supporting the radiologist in making assessments and health evaluations of the patients. AI artificial intelligence and machine learning have also created a positive impact on the healthcare industry and its digital perspectives. It has significantly reduced inefficiency in the healthcare sector and improved the flow of patients and their overall experiences. Digitalization through AI has also improved the experiences of the caregivers and enhanced patient safety which can be considered as the main benefits of implementing digital inputs through AI in healthcare settings (Bajwa et al., 2021).  Big data is also a significant beneficial factor in the case of the healthcare industry as it can provide more opportunities for companies like Spire Healthcare to understand the experiences of the patients. It can provide medical researchers a wider access to a large volume of data and methods of collecting them.

Healthcare challenges such as intricate care episodes, high occurrence of prolonged infection, decreasing resources, snowballing costs, and increasing patient anticipations have shown the insufficiency of the conventional authoritarian tactic for quality development. Policymakers progressively believe that the capability to enhance the quality of care and manage control costs will necessitate an efficient association with engaged and informed patients. High-quality care can be characterized as one that is equal, efficient, effective, knowledge-based, and safe along functional and technical dimensions (Kumah et al., 2020).

Challenges of disruptive innovation in healthcare through digital healthcare can also affect companies like Spire Healthcare. Access to healthcare-oriented data can become complicated as technical experts need to be appointed to check the proper implementation of the information in healthcare settings. Maintaining a consistent approach to the healthcare data retrieval process is also considered a challenge of digitalization in the healthcare industry which should be prioritized by the company. Privacy-related issues and security concerns can also affect the healthcare industry due to the transformation into digitalization. Digitalization can also create budgetary restrictions for development within the healthcare sector (Exworthy et al., 2021).

Healthcare systems generally operate at three interrelated levels: micro, meso, and macro and according to evidence an enterprise through its leadership and strategies can bridge these levels to enhance the quality of care distributed at the front line. Organisations like Spire Healthcare can utilise several processes and levers to translate external inputs such as regulatory and policy incentives and internal inputs like local assurance systems facilitating data on capacity and performance to assist quality improvement. In the UK the reorganisation of acute strokes demonstrates how leadership can play a crucial role in handling organisational and professional resistance to changes that aim to enhance the quality of care. Leaders, in this case, cited that external company's public consultation and priorities responses held a line against local conflict to change (Fulop and Ramsay, 2019).

Fundamental the prevalence of public commentary in health schemes is an array of cultural and socio-political vicissitudes. At first trust in medical professionals has been minimised by a range of disgraces that have often rotated around the management of health routine. As a consequence, doctors in several healthcare organisations are no longer in individual custody of evaluating their performance principles, monitoring those principles and monitoring those principles and taking relevant action to reward good or cure poor practice (Enticott, Johnson and Teede, 2021). Along with that, the development of a commercial culture has invigorated clients to become more informed and proactive about the selections they make concerning their fitness by retrieving autonomous information.

Some of the key methods that have established the capability to interpret the large-scale databases that are accumulated in healthcare systems are machine learning and more currently deep learning. The usage of machine learning facsimiles tends to enhance client well-being and lead to better clinical outcomes. Machine learning has a significant capacity to augment clinicians' work by processing through millions of client data and information points which are accumulated in electronic health records. This model has been successfully integrated into several clinical solicitations such as identifying early signs of lung cancer, detecting respirational circumstances through X-rays, and detecting abusive and deceitful health insurance prerogatives (Waring, Lindvall and Umeton, 2020).

While there are different approaches to enhancing the quality and safety of healthcare, continuous quality improvement or CQI has received significant attention within the sectors of healthcare systems. CQI has been built on five chief principles: an emphasis on corporate systems and processes rather than on individuals within the organisation, the use of methodologically and statistically sturdy problem-solving tactics, empowerment of workers to help recognise actions and issues in improvement opportunities, the usage of multi-disciplinary teams and a focus on clients through ensuring the best potential patient outcomes and experience (Hill et al., 2020). Currently, the National Health Services (NHS) faces significant operational and financial pressures with services struggling to uphold standards of care. It is therefore crucial for NHS leaders and leaders of healthcare systems to emphasize improving the effectiveness, safety experience, and quality of care (Alderwick et al., 2017).

The association between big data analytics and value creation and assistance for healthcare companies states that organizations facility with processes, techniques, and tools that facilitate an organization to analyse, process, visualize and organize data in that way generating comprehensions that facilitate data-driven decision-making, functioning preparation, and implementation. By the year 2025, the market of big data is anticipated to touch a record high of 70$ billion a massive 568% growth in ten years (Cozzoli et al., 2022). Indeed big data analytics must be utilised by managers to derive crucial patient data and leverage positive patient outcomes. However, the implementation of the big data approach must be linked with the application of precise and personalized medicine based on private evidence tailored to the individual patient, delivered in real-time. The concept of big data has evolved constantly and presently, it does not emphasize the massive volume of data but rather the procedure of generating value from these records (Batko and ?l?zak, 2022).

Conclusion

The organization is focused on the implementation of digital strategies for enhancing the overall outcome of the patient experience and systemic development. AI and machine learning implementation is common in the areas of operating procedures, radiology, and scanning technologies which can provide the company with a comprehensive overview and evaluation of the data structure and procedure. The implementation of new technologies in the healthcare settings by the organization can create a competitive atmosphere within the healthcare sector which can lead the other players to adopt the new AI-implementing tools in surgery, radiology, imaging, scanning, and other areas to gain a competitive advantage.

The adoption of the procedure can help in resolving the issues faced by other healthcare organizations in the UK. Digital tools can provide healthcare providers an increased exposure to various types of health data and give patients better control over their health. Increased efficiency and improved medical outcomes can be considered as the significant benefits that can be provided by the digitalization of healthcare in the future.