The data leads to better medical practice. Here’s how.

The data leads to better medical practice.  Here's how.

Data can save lives when it is standardized, organized, and secure. Photo: Canva.

What does quality health care mean for every stakeholder? For patients, this can mean short waiting times and positive interactions with health care professionals, especially when the person is at their most vulnerable. For nurses, that may mean providing the best hands-on care until patients get better again. For clinicians, this may mean accurate diagnoses and prescriptions that ensure patients recover quickly and completely.

But for nurse-turned-healthcare transformation specialist Alexis Edwards, quality healthcare means comprehensively addressing all of these needs and reinventing healthcare systems through digitalisation. This means developing healthcare strategies for the population and recommending digitally enabled care strategies so that patients, nurses, and physicians alike benefit from more improved healthcare systems.

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Edwards joins IBM as a co-partner on IBM’s UK-based Watson Health Consulting team to harness the power of data science, analytics and artificial intelligence to help healthcare organizations advance their digital journeys. “I was really inspired by the profound opportunity we have to responsibly disrupt healthcare through system modernization and healthcare redesign, which I believe is integral to the current and future needs of a healthy population,” she says.

Edwards talks to GovInsider about how governments in the UK, US and Singapore are using digital tools to improve patient experiences with more accurate and standardized patient data.

Data saves lives

Powerful data analytics platforms, along with standardized patient data, can support healthcare organizations such as hospitals in responding to healthcare crises as they arise.

When the 2020 COVID-19 pandemic hit, hospitals around the world struggled to cope with an influx of patients, many of whom required urgent and immediate attention. In Ontario, Canada, North York General Hospital chose to respond to this healthcare management crisis with data analytics that provided doctors and nurses with real-time data that was easy to understand.

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“As a member of the Incident Management Team, the information on the Covid-19 dashboard gave me real-time access to important information such as the ICU and acute care unit admissions for Covid-19, the number of patients undergoing ventilation, and the number of tests completed in D., clinical director of the NYGH Mental Health Program, formerly the “Covid-19 Assessment Center.”

But the hospital’s digital transformation journey didn’t happen overnight, or just in response to an unexpected and acute healthcare crisis. Instead, it began in 2017, when NYGH deployed AI-powered IBM Cognos Analytics to develop a real-time patient dashboard that replaced at least 100 different static reports. This enabled doctors and nurses to see if a patient’s vitals were incorrect, and to provide them with critical and timely responses.

Such a visionary investment in future data management technologies puts NYGH in good standing when the Covid-19 pandemic strikes, potentially saving countless lives.

Elsewhere, Edwards highlights how the US federal health insurance program, Medicare, adopts data-driven quality measures when providing health care. “This includes reviewing patient-reported experiences, allowing for a feedback loop that ensures that we can qualify and define the way care is delivered in a patient-centered manner,” she says.

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“There is a dire need to standardize, organize, and integrate data – because data as we know saves lives. It allows us to look at the bigger picture, automate leadership, and personalize medicine, which is certainly something we will see as an increasing need in the future,” Edwards adds.

Consolidation of health systems

Consolidated data can support agencies in better serving patient needs at the population level, as population health strategies take off worldwide.

As the population ages, care delivery must be reorganized in favor of team-based care. This means shifting much of the health care delivery from hospitals to general practitioners located within neighborhoods, such as polyclinics.

Decentralized healthcare is shifting the focus from physician-directed acute diagnoses to long-term patient monitoring by allied health professionals – a key requirement for older patients who often deal with chronic rather than acute conditions.

The Singapore Ministry of Health, which is home to one of the world’s rapidly aging population, has announced its intention to put connectivity at the heart of healthcare transformation as part of its broader healthcare strategy, Healthier SG. This means standardizing patient databases across primary, secondary and private healthcare institutions to ensure seamless patient experiences.

For this to happen, healthcare institutions can no longer operate in silos. “The Department of Health will study how we can provide better data support to family physicians, such as giving them access to patients’ medical records and tools such as clinical dashboards to better track patients’ conditions and health trends over time,” the Department of Health announced last March. general.

As part of this journey, the Department of Health’s Office of Healthcare Transformation has already begun offering home care modalities, such as the Home Ambulatory Inpatient Care Program. This is supported by an increase in telehealth vendors such as Speedoc, which are using cloud-based systems and automated process automation (RPA) to ensure that the quality of patient experiences does not decline, even when delivered remotely.

In the UK’s parallel journey towards the integration of its healthcare systems, the country’s national health system has sought to link clinical data sets – from local to national level datasets, across both primary and secondary sources.

Edwards says this approach to using the overall social determinants of health is exemplary. “By using multiple deprivation indicators that monitor income, employment, health, disability, crime and housing factors, the NHS is able to prioritize resource allocation within England,” she says. Only when these needs are properly identified can the government then rely on a wide range of societal factors to improve overall health care outcomes.

User centralization is the core of shared solutions

The three main stages of the IBM Garage method are co-creation, co-implementation, and collaboration. Photo: IBM.

Finally, Edwards stresses the importance of user-centered design thinking, which can ensure that healthcare meets patients’ needs from the start. One such process is IBM’s garage method.

This method is at the heart of IBM’s approach to designing solutions that truly benefit end users across industries. It involves designing technologies together with end users, followed by multiple rounds of beta testing before scaling and implementing them.

“Often, when we design [healthcare] Solutions, we can fall into the pattern of not really being sure that these solutions have been tested…but it is critical to make sure that the solutions we create meet and exceed the expectations of our end users.”

With a solid understanding of the place of data in transforming healthcare, governments will be on a path to taking deliberate and informed steps to improve overall health outcomes at the national level.

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