Trends, Challenges, and Solutions for Healthcare’s Digital Transformation

Sanjay Singh
Digital-Transformation-in-Healthcare

Introduction

In order to remain relevant and flourish in the market, it is imperative that companies embrace technology. Digital transformation has changed the face of many industries, and healthcare is not exempt either. Personalized medicine, advanced telehealth, and streamlined clinical operations would all be within reach if a digital transformation was to be implemented in healthcare.

To take full advantage of the digital transformation’s potential, the healthcare industry must, however, address some unique challenges.

Consequently, healthcare has been lagging behind other industries in adopting technology due to these challenges. A recent report from the State of Digital Transformation indicates that 80.8% of respondents plan to increase technology spending in healthcare.

Post-COVID-19The result is that a significant portion of the healthcare industry is still lagging behind in terms of utilizing technology to its fullest potential.

As well as discussing strategies to overcome the obstacles hindering digital disruption in the healthcare sector, the article analyzes the impediments and solutions.

Digital Transformation in Healthcare: What are the Benefits?

A number of benefits can be derived from digital transformation in healthcare, including:

  • Managing data related to patients and staff automatically
  • Maintaining competitiveness in healthcare
  • Patients, healthcare providers, and other partners of the ecosystem can interact better through improved communication channels
  • Providers should be encouraged to use remote care options to offer continuity of care in cases where there is difficulty coming to the office and patients should be able to receive on-demand services
  • The ability to diagnose and treat patients quickly results in high levels of satisfaction and retention of patient records
  • Patient care was improved and human errors were reduced
  • Utilization of big data analytics to personalize prognostic and diagnostic claims

The following technologies might be developed:

  • With advancements in telehealth, information from various sources can be integrated into medical reports to assist physicians in better understanding patient conditions (e.g., Fitbits, body composition scales, virtual reality tools, etc.).
  • A user-friendly platform that facilitates the seamless transfer of data between patients and providers as well as the scheduling of appointments between providers
  • Increasing the speed at which clinicians make clinical decisions and perform risk assessments (e.g., sorting MRIs quickly so physicians see patients with the highest risk at the beginning of the procedure).
  • A personalized and precision approach to medicine

Digital Transformation Challenges in the Healthcare Industry

  • There are a lot of obstacles to accessing healthcare data
  • There is no consistency among providers or centers when it comes to healthcare data
  • Data privacy concerns related to patients
  • Technologies that pose a security threat
  • Development budget constraints
  • There are not yet laws in place that would address organizational concerns surrounding liability and patient autonomy. There is a lack of organizational preparedness on the front line

A Consistent, Accessible, and Privacy-Protective Approach to Healthcare Data

The potential benefits listed above depend on the availability and interoperability of data across organizations. The digital health transformation can only take place when electronic health records are accessible and interoperable, despite the fact that many centers have adopted systems to keep electronic health records.

As stated by the department of Health and Human Services (HHS), “providers and payers will not be able to benefit from the value of using modern computing tools – such as machine learning and artificial intelligence – to identify trends and inform care decisions without the capability to access multiple records across a population of patients.”

As a result, patients are unable to easily transfer information between providers within their insurance networks and shop for lower-cost care within the network.

In the absence of efficient electronic access to patient records, providers have limited access to information they can use to treat patients. In addition, secure systems must be used to transfer patient data in order to protect privacy, particularly for longitudinal data that has been stored across multiple centers and IT systems.

By transferring such data remotely, doctors would be able to offer remote, telehealth services to their patients. This can limit the availability of real-time, 24/7 data from smartwatches to after-the-fact patient reports.

As a result, researchers cannot utilize the power of artificial intelligence and machine learning (AI/ML) when they lack access to data that is interoperable across centers. Developing technologies able to help with clinical decision making through prognostic, diagnostic, and optimized treatment strategy predictions requires aggregating datasets suitable for AI/ML application.

Ideally, these AI/ML technologies should provide us with the ability to learn from all past patients rather than just a single provider or center’s very narrow scope. As a result of a lack of standardization between centers regarding clinical decision making, interoperability across centers is further complication, as there is inconsistency in the types and amounts of data available across centers.

Solution possibilities:

Healthcare adoption of blockchain

In 2023, the healthcare-related blockchain application market will exceed $890 million, according to Precision and Strategic Intelligence.

Data accessibility issues hampering healthcare’s digital transformation may be resolved with blockchain, the digital transaction technology characterized by a decentralized network of computers.

Blockchain technology could be useful in healthcare for:

  • Analyze patient data for inaccuracies or repetitions
  • Ensure that private information is not leaked through security breaches
  • A distributed ledger can be used to store, share, and access patient health records
  • By sharing model parameters on the ledger and continuously updating them, researchers can access and aggregate datasets suitable for AI/ML

In an effort to solve fragmented medical records, medicalchain is implementing blockchain technology.

Standardization and access to data are being improved through consortium efforts

The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study involves 18 hospital systems across the country collecting detailed clinical data on thousands of patients with brain injuries. TRACK-TBI standardizes data sources and how they are recorded across centers. The dataset is also available for researchers to analyze.

A similar approach is being used to generate large, publicly accessible datasets for other disorders and diseases; however, because of their siloed nature, there may be concerns about time and budget inefficiency. By adopting blockchain technology to address the fragmented nature of health records, we might be able to relieve some of the strain that is generated by these consortium studies, which are currently brute force.

Consortia efforts could serve the following purposes in healthcare:

  • Methods for collecting data should be standardized
  • Achieve AI/ML success by aggregating and curating datasets
  • Make data more accessible

Trends and Best Practices in Technology Development

The healthcare industry needs to develop a digital strategy to accelerate its transformation and prepare staff for the upcoming changes after data accessibility, privacy, and security concerns have been addressed. Healthcare will require massive investments in technology and hiring digitally savvy minds to implement digital transformation. Digital transformation goes beyond buying the latest IT system.

Health-related businesses would have to invest more and strategize more carefully.

It is possible to create influential healthcare technologies by following a few simple steps:

Development using agile methods

Iterative and incremental approaches allow new additions and changes to be accommodated even later in the development process thanks to agile software development.

Agile Development or outsourcing to a team that implements this process should be considered when creating software that bridges the gap between healthcare and digital transformation.

Big data analytics can also add value to the healthcare industry if the right Agile Development team is working on it.

  • Adjusting staff availability to meet surges in patient demand
  • Reporting patient records that contain inconsistencies or incompatibilities, such as prescriptions that may be risky for some patients given their health histories
  • Making clinical decision-making easier using AI/ML-enabled technologies

Customers can take advantage of digital services

Various industries, including travel, banking, and entertainment, have successfully adopted digitization today. Consumers expect the same level of digital service delivery in healthcare systems as they do in other industries, as the impact of these digital transformations has integrated into their lives.

Consumers expect omnichannel experiences across all touchpoints, according to a survey from McKinsey.

Digital-healthcare-is-popular-with-most-consumers

Using digital identities as a means to provide consumers with more personalized services and build trust is crucial for healthcare leaders.

A look at the latest trends in healthcare related to digital transformation

Among the newest healthcare technology trends for 2020 are the following:

HealthcareWhile digital transformation in healthcare offers many benefits, patients still have a considerable gap between expectations and how healthcare is actually delivered. There is no doubt that consumers want their demands met, but they also do not want their privacy to be compromised.

Security, liability, and incentives in governance

Rewards

Digital transformation of the healthcare industry needs to be promoted and invested by governments across the globe. Many are working in this direction. The US government, for example, has subsidized healthcare centers for using electronic health records, according to a McKinsey report.

There is, however, room for improvement. Legislative bodies should also reevaluate laws and regulations that currently limit the accessibility and interoperability of healthcare data in addition to providing incentives for adopting digital systems and funding mechanisms for developing disruptive healthcare technologies.

Liability and autonomy

AI-enabled devices may soon be able to offer treatment strategy predictions. It is imperative that healthcare setups adopt these technologies in accordance with clear legislation that protects patients’ privacy and defines medical liability. In other words, patients must be informed about the technology and what role it plays in their care.

The liability for a mistake made by the predictive system is also important. For instance, if a mistake is made, the responsible party should be understood (e.g., physician, group implementing the technology, developers of the technology).

Safety

The technology’s developers must also follow best practices for security, especially for AI/ML-enabled devices that constantly update with new patient information. In spite of the importance of continuous updating for generalizability and addressing data drift concerns, a data breach or alteration could affect model performance.

The healthcare organization may not know of the security concern for a period of time after model performance is affected.

Mentality, culture, and trust: Organizational Readiness

Technology modernization will not be implemented immediately and effectively in the healthcare industry, as there is a resistance to change (both culturally and mentally).

Healthcare sector respondents to the State of Digital Transformation report believe that lack of organizational readiness is preventing healthcare from transforming effectively.

The digital transformation in healthcare can be accelerated in several ways by addressing this resistance.

Develop skills that are lacking

In order to address the concerns described above, healthcare systems need to train their employees in technological solutions.

A digital strategy at the organizational level can address this challenge since this type of training is both expensive and time consuming.

Developing a trusting mindset

The privacy and security of patients’ personal information are at the heart of technological advancements in healthcare; if there are too many leaks (of PII and other sensitive information), mistrust among stakeholders will develop.

In the healthcare space, where data-trained systems are not able to capture physician-patient interaction, that influences treatment outcomes, there is a widespread concern that artificial intelligence-enabled devices will replace humans.

The healthcare/technology fraternity needs to run awareness campaigns highlighting the benefits a tech revolution can bring to healthcare in order to mitigate these concerns and shift the mindset in favor of digital transformation.

Assisting clinicians and decision makers with technology

In an effort to reduce staff fatigue and turnover, a socially intelligent robot, Moxi, is being tested in the supply room to assist with tasks such as retrieving and delivering items.

By applying AI to images, radiologists can detect diseases like cancer even before they are visible to the human eye, which allows them to detect them earlier. By utilizing this technology, doctors can ensure they reach the most vulnerable patients first by sorting scans based on risk.

The idea that technology can be a powerful assistant in healthcare is further cemented with the use of human and machine hybrid approaches.

Choosing between machines and humans isn’t the only topic of debate in Artificial Intelligence, as Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School demonstrated in a joint study.

Pathology images were interpreted using a deep learning algorithm trained to identify metastatic breast cancer. 92.5% of the algorithm’s accuracy was achieved, whereas 97% of the accuracy was achieved by pathologists. However, when they were combined, they achieved approximately 99.5% of detection accuracy.

Clinical-Duties-andDecision-Making

Healthcare's future lies in digital health?

When it comes to adopting the digital transformation, healthcare is learning, evolving, and growing as many other industries have. The healthcare industry understands that technology needs to become a crucial part of its operations in order to adapt and focus on a customer-centric vision that leads to better patient outcomes.

It is important that healthcare leaders consider more sophisticated ways of delivering technological solutions to the issues limiting advancement, while investments in social, cloud, and analytics are progressing and adding value.

To accelerate this incredibly important digital transformation, organizations still relying on decades-old legacy systems must develop strategies today for the post-digital age.

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Sanjay Singh
Article written by

Sanjay Singh

Sanjay Singh holds a Bachelor's degree in MCA from JNU University. Sanjay Singh is an experienced WordPress developer with over 6 years of experience. He specializes in PHP programming, HTML, CSS, and JavaScript, along with strong web development ski... read more

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