The Digital Transformation of Healthcare

As we stood at the start of this decade, it became clear that the tumultuous events from COVID-19 precipitated a rapid acceleration of changes through worldwide healthcare delivery. However, affirming that these changes were already gathering pace over the last five years is noteworthy.

However, the transformation has significantly magnified through the last few years global pandemic.

In addition, a concentration of progressive technological advancements is combined to catalyse this next normal. This refers to the impending widespread uptake of 5G, improved machine learning capabilities in extensive data analysis and further developments in real-time human biosensor data acquisition.

Whilst these components all focus on one point- individual human health, we are required to carefully analyse the various features to maximise the smooth transition and implementation within healthcare.

As mobile biosensors, available in skin patches and smartwatches, are also quickly improving in accuracy and reliability, human biomarker information is significantly increasing. Thus, secure data analysis and storage have become a central requirement and possible cause of concern in global healthcare re-imagining. This concern is, first and foremost, articulated by the User.

The potential for data hacks, cybersecurity missteps and inappropriate sharing of identified data sharing are readily apparent. Many platforms and technologies fail to provide the level of data privacy that is the required minimum standard in this field. Market research confirms that data governance and safeguards are the most front-of-mind concerns for the patient (or User).

Thus, any considered new healthcare platform must comprehensively tackle this issue. How is this done? Firstly, the tenements of data protection, data storage and secure transfer, as articulated in the HIPAA and GDPR recommendations, must form the bedrock of all subsequent designs. With these provisions developing the blueprint, any health platform and mobile applications incorporate "privacy by design."

This refers to the highest standard" being comprehensively and thoroughly implemented before writing the "first line of code". In addition, "ore any mobile app "action or platform offered to the general public, thorough Independent data security auditing and penetration testing must be enacted by external accredited organisations.

A comprehensive system of quality assurance and quality management must be implemented across all organisational levels to ensure transparency and reproducibility of design to the highest regulatory standards. Anything less than this will not be appropriate. Nor will it develop sophisticated levels of trust, crucial to interchange personal human data.

The bar needs to be set much higher than is currently exhibited by many large multinational companies providing smartwatches. In healthcare, we must always strive to achieve this high water mark.

In short, adopting all of these standards is mandatory in any new platform that functions in the Software as a medical device class- SaMD. These standards should include external software audits and the careful ultimate protection of all personal data. Users' data should never be shared inUsers'dentifiable way.

However, a platform could enable secure data transfer if and only if the User / patient desires, requests and requires. For instance, this would be specific re-application programming interfaces to their family medical practitioner, medical specialist, hospital or pharmacist. The control and segmentation of this transfer would only be in the hands of the User. Their data, the power, is the required mantra. This is the standard that all should follow.

The Healthcare Landscape in 2020's

Rise of On-demand Health 2020's
Patients seek healthcare delivery and availability on their terms, time and schedule. 52% of all web- browsing in 2018 was performed on a mobile device.

77% of all US residents own a mobile device. As a result, consumers are increasingly going online to procure medical information or services- such as appointments, advice or diagnosis. This has been termed the rise in consumerism.

A shift has also been observed towards a value-based service model from a fee-for-service.

Medical wearable devices
Improve / Aid preventative healthcare programs. For example, 33% of US consumers in 2018 regularly used smartwatches and fitness trackers.

Real-time Data
Real-time data gives patients more significant insight into their daily health and thus improves compliance, behavioural changes and compliance. For example, think of 24 blood pressure patches or sensors (via photoplethysmography, PPG) that give much more immediate feedback on the effectiveness of the anti-hypertensive medication.

Pulse oximeters(PPG)aid screening with nocturnal sleep apnoea or hypopnea.

The implementation of PPG for identifying these metrics and heart rate variability, resting heart rate and sleep cycle analysis has been extensively covered in the literature. In addition, these noise and movement artifact reduction techniques and algorithmic overlay are repeatedly shown to be within 3% of in-hospital delivered devices.

Personalise the Healthcare Experience - provides patients with ownership of their data and thus can take more direct responsibility for their health outcomes. This is also facilitated by machine learning backend data analysis.

Big data insights via AI
Physicians and Hospital providers are increasingly using significant big data insights via Artificial Intelligence (AI) in the vast field of Bioinformatics.

AI's real power is in precision personalised medicine, medical imaging, drug discovery, and genomics.

1. The real power of AI can be best observed in areas such as precision personalised medicine, medical imaging, drug discovery, and genomics.
2. Lowered rates of medical errors through better cross-data analysis.
3. Lowered rates of medication errors.
4. Identify the presentation of patients to the emergency departments and give them specific information. Up to 28% of visits may be from recurring patients that do not require emergency care.
5. Permits more accurate staffing allowances and better management of human workforce capital. We are treating patients with Virtual Reality (VR). This market is estimated to reach 51 B by 2025 in the US alone. VR is used in pain management programs, treatment of anxiety, and post-traumatic stress disorder. In addition, task-related or operative simulations and preparative educational training are being improved with VR. This has demonstrably lowered error rates and speed up task completion.

Predictive Healthcare

• Big data market share in the US has reached over 14.9 B by 2022.
• Understanding current biometrics and psychometrics with extensive big data analysis may allow future health patterns and disorders to be predicted.
• May allow more predictive future staff requirements and fine-tune staff deployment.

The need for digital transformation is, therefore, absolute. However, for the human condition, multiple benefits will accrue if effective planning and execution are carefully considered and widely consulted throughout society, institutions and governmental organisations.

References\

1. Virtual Reality Training Improves Operating Room Performance\
2. Patient perceptions of receiving test results via online portals: a mixed-methods study\
3. Mckinsey & Company - The consumer sector in 2030: Trends and questions to consider\
4. Virtual reality gives doctors, patients 3D look at hearts\
5. Forbes - 10 Charts That Will Change Your Perspective On Artificial Intelligence's Growth\
6. Healthcare Artificial Intelligence Market to Top $34B by 2025