Health data management has the potential to reduce costs, improve care delivery, and solve many complex challenges plaguing the industry. With the help of advanced technology and data analytics tools, health care organizations can reap the benefits of efficient data management.
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The Importance of Health Data Management
While every health care institution collects data, many do not have a firm grasp on health data management, which is the systematic organization of health data in a digital format. According to a Deloitte analysis, “Very few organizations use non-health data sources that can be used to augment formal medical data, such as patient lifestyle information, remote monitoring and wearable devices, and survey data about patient experience.”
The Three M’s of Health Care Data
In his book Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage, Douglas Laney discusses the three M’s of health care data. The first M, data measurement, concerns data that’s generated and collected through normal daily activities like the billing system, electronic health records (EHRs), and prescription writing software. To fully grasp the data’s value, it’s important for organizations to understand how much data is stored, where it’s collected, how it can reduce costs, and how much can improve care quality. Investing in data management infrastructure can help attain this understanding.
The second M, data management, requires an understanding of data sources and storage. It also requires an ability to obtain data that can be analyzed and managed. Health care organizations need a data operating system to have a foundation for obtaining data from a centralized location, to know what data’s available, and to know the data source and its implications.
The third M is data monetization. This represents an organization’s ability to leverage information assets. In health care, data monetization refers to metrics like improvements in care quality and patient experience, reduced care costs, and finding new revenue streams.
According to PwC and the Business-Higher Education Forum, health care organizations are in most need of functional analysts and data-driven decision-makers to fill analytics-enabled and data science jobs. Data engineers, data analysts, and data scientists are also needed, albeit in a less urgent capacity.
Benefits and Challenges of Health Data Management
Though engaging in effective health data management entails numerous challenges, the benefits are worth the effort.
Benefits of Efficient Health Data Management
There are several benefits that could be experienced through efficient data management. For instance, it can provide health care workers with a more comprehensive view of patients, households, and patient groups and greater insights into physician activity. This could lead to improved patient engagement, improved health outcomes, and informed decision-making.
Challenges to Efficient Health Data Management
One of the primary challenges to efficient health data management involves fragmented data, which could stem from structured data located in spreadsheets and digital documents or data in specialized formats used by imaging equipment. Another challenge concerns changes to data, such as name changes or treatment advances. A third challenge involves issues concerning regulations and compliance.
Health Data Management Tools
One of the prominent providers of health data management tools comes from Blue Health Intelligence, whose tools offer “transparent, in-depth, and detailed analytics.” Their tools can help organizations close care gaps, discover opportunities for care interventions, and identify at-risk patient populations.
A second company specializing in health data management tools is Information Builders. The company’s software tools help organizations redefine enterprise analytics and empower employees to make data-driven decisions. They also use artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to foster business innovation.
Another company, Prealize, provides solutions that help health plans, employers, and providers identify the drivers of future risk. Their tools can also define which procedures are most important to strategy.
The Role of Data in a Pandemic
Data usage can be an essential component to helping health care professionals determine pandemic strategies. Data can help them develop real-time forecasts, track the movement of infected individuals, identify outbreaks, and predict progression and disease hotspots.
This form of data usage can yield many benefits. Some of these include the acceleration of the notification process, improved resource allocation, improved local response to an outbreak, and supporting faster development of medical treatments.
Complex Challenges During a Health Crisis
There are numerous hurdles health care professionals may have to clear during a pandemic. These include challenges linked to respecting individual privacy while considering population health and well-being, effectively sharing data, and building an interdisciplinary team to foster collaboration.
Data Analytics Solutions Used During Pandemics
One of the solutions that’s emerged during the coronavirus pandemic is the COVID Symptom Tracker. Developed by scientists at King’s College London in collaboration with health company Zoe Global, the app allows users to voluntarily share data from their smartphones, fitness trackers, and other mobile devices.
Another analytics solution is the use of the BlueDot model, which was built by the analytics firm BlueDot. This model successfully predicted the spread of Zika to the U.S. by combining worldwide flight itineraries, ecological data for the carrying mosquitos, and gridded global population datasets.
There are other advanced tools that can provide assistance during the pandemic. These include free analytics tools from Amazon Web Services and Google Cloud, artificial intelligence, and natural language processing.
Driving Invaluable Insights
Effective health data management requires the use of advanced tools, the efforts of a multidisciplinary team, and a shared commitment to uncovering and implementing actionable insights – insights that can promote public health and help save lives.
Blue Health Intelligence, Analytic Tools: Models That Simplify and Accelerate Visibility Into Quality and Cost Dimensions
Cloudian, Health Data Management: Benefits, Challenges and Storage
The Economist, From Chaos to Coherence: Managing Pandemics with Data
Forbes, The Vital Role of Big Data In the Fight Against Coronavirus
HealthCatalyst, Healthcare Data Management: Three Principles of Using Data to its Full Potential
Health IT Analytics, Understanding the COVID-19 Pandemic as a Big Data Analytics Issue
IBI, Home Page
Nature Machine Intelligence, Pandemic Data Challenges
NCBI, Significant Applications of Big Data in COVID-19 Pandemic
Prealize Health, Solutions
PWC, What’s Next For the Data Science and Analytics Job Market?