Healthcare Data Management: What Is It and Why Does It Matter?

Health informatics is an emerging practice that is rapidly expanding. Today, there are numerous colleges that provide degrees in health information. Healthcare Data Management (HDM) of healthcare data, information, and knowledge for decision support by care providers, teaching hospitals, research centers, and pharmaceutical and biotech companies is at the heart of healthcare Information management. Healthcare data management is evolving and improving medical treatment delivery and support.

Making sense of healthcare data and managing patient outcomes are driving today’s healthcare practice. We can see this today in the management of the global response to COVID. The response is heavily data-driven in order to make decisions about an appropriate global response to the virus.

What is Healthcare Data Management?

The Process of managing the lifecycle of health data is known as healthcare data management. Data is generated, collected, stored, organized, processed, archived, and destroyed. Furthermore, data is kept secure and protected to ensure strict confidentiality and integrity, and it is only accessible to those who need it. All of this and more is possible with healthcare database management systems, which can analyze disparate and diverse datasets from multiple internal and external sources to provide operational and decision support to applications, devices, and people. Healthcare data management is increasingly focused on digital data, whether on-premises, in the cloud, or at the network’s edge for mobile and telehealth, as well as medical devices and instrumentation.

Healthcare data management, also known as digital healthcare data management, includes population health records, other clinical records for drug efficacy, and even medical instrumentation logs and RF-ID tags on various physical assets ranging from beds to bedpans that are required for supply chain management. Data management also includes all operational and financial records for healthcare providers and payers, including public, national, and state healthcare programs such as Medicare and Medicaid, as well as private insurers.

Benefits of Healthcare Data Management

From a basic standpoint, the benefits of healthcare data management are obvious. The more accurate the data, the better decisions can be made, and the outcomes of patients’ healthcare can be improved. Aside from the crucial aspect of providing healthcare to patients.

Other benefits of healthcare data management include:

• Health data analytics — It can be used to make predictions about patients’ health in order to provide better treatment and a more proactive approach to health care — the overall improvement of health outcomes for the patient and, in some cases, the general public.
• Better alignment and communication — Communication improves patients, providers, and other stakeholders, especially when digital records are available. A comprehensive view of the patient can help doctors collaborate more effectively. This is also useful across national and geographic boundaries.
• Improved patient engagement with healthcare — This entails greater visibility in patient records to better understand treatments, trends, and proactive care. When necessary, the patient can easily access their health records at any time and from any location.
• Data-driven choices — Historical data, real-time data, and other data can help providers and patients make better decisions. Instead of relying on hunches, data can improve both the provider’s and the patient’s diagnostic abilities.
• Integration with the patient’s personal health activities — Individual patient-monitored activity with sensors, in particular, can be fed into the Health Record Management system to improve treatments. Many mobile applications now allow data from sensors or other applications to be integrated with or shared with healthcare data management systems.
• Integration with emerging technologies — Improved integration with artificial intelligence to assist in diagnosing illness without requiring a physical doctor visit — better integration with medical chatbots that use medical knowledge management systems with health data and knowledge integration for self-service.

Challenges of Healthcare Data Management

Over the last four years, medical data has evolved from purely paper-based tracking to digitized information. Many types of medical data have yet to be digitized or integrated into health data management systems, even today.

Here are a few of the most pressing issues confronting health data professionals today:

• Fragmented data — Medical data can be structured in spreadsheets or databases, images or video files, digital documents, scanned paper documents or stored in specialized formats like the DICOM format used for MRI scans. Data is frequently duplicated, collected multiple times, and stored in multiple versions by healthcare providers, public health organizations, insurance companies, pharmacies, and patients. There is no single source of truth about the well-being of patients.
• Changes in data — Medical data, as well as the names, professions, locations, and conditions of patients and physicians, are constantly changing. Over time, patients are subjected to a variety of tests and treatments, and medications themselves evolve. New medical treatment models, such as telehealth models, generate new types of data.
• Regulations and compliance — Medical data is sensitive and must comply with government regulations such as the USA Health Insurance Portability and Accountability Act (HIPAA). Data discovery challenges and poor data quality make it much more difficult to perform required audits and meet regulatory requirements, as well as limit the diversity of data available to medical professionals so that patients may benefit.

Use Cases of Blockchain in Healthcare

Many healthcare organizations and blockchain firms are developing blockchain-enabled systems and blockchain in healthcare is improving healthcare services for both patients and healthcare professionals. Blockchain technology is all set to revolutionize the healthcare industry by decentralizing patient medical histories, improving payment methods, and tracking pharmaceuticals.

Here are some examples of blockchain use cases in healthcare:

• Patient Data Management

Patient data management is one of the most popular blockchain use cases in healthcare. Healthcare organizations typically separate patients’ medical records, making it possible to identify a patient’s medical history without having to contact previous healthcare providers. It takes a significant amount of time and may result in mistakes due to human error.

• Overcoming counterfeit drugs

Tens of thousands of people are expected to die each year as a result of counterfeit drugs. Blockchain provides complete visibility into the medical supply chain, allowing for the tracking of when a medicine has been altered or changed while in transit. As a result, drug recalls are simplified, and counterfeiting is reduced.

• EHR accessibility

EHRs are difficult to manage. EHRs provided by one healthcare provider for a patient differ from those provided by another healthcare provider for the same patient. Blockchain solves the interoperability problem by allowing healthcare professionals to store data in one place that can be distributed to all network nodes.

Healthcare Data Management decision support systems

All stakeholders, from providers to patients, can benefit from healthcare data. Data is everywhere and must be available in real-time to support timely decision-making. Data can be used to measure anything healthcare-related, manage decisions, and monetize actions using integrated, secure collaborative systems. Various providers can create healthcare service catalogs of information, which can then be combined with factual, real-time data to determine the availability of services and products.

Emerging technologies such as artificial intelligence, machine learning, and others can benefit from the use of health data on social, mobile, and cloud platforms to support a wide range of use cases in healthcare Information management. Clinical decision support systems can examine evidence-based data collected in a health care management system at any point of care, whether routine or emergency.

When a healthcare provider can do their job better and the patient has more knowledge about care, it benefits both parties. Healthcare data management systems increase the efficiency and effectiveness of health care.

Some real-world examples of Blockchain in Healthcare?

Here are four real-world examples of blockchain technology in healthcare:

• BurstIQ
• Medicalchain
• Patientory

Let’s find out more about them.

BurstIQ

BurstIQ, based in Colorado, USA, uses blockchain to improve the way medical information is shared and used. BurstIQ’s platform enables healthcare organizations to securely manage a large amount of patient data while ensuring strict HIPAA compliance and enabling:

• Safekeeping data
• Selling data
• Sharing data
• Licensing data

Since the platform keeps complete and up-to-date patient health information, it has aided in the control of prescription drugs and opioid abuse.

Medicalchain

Medicalchain’s blockchain-based platform is located in London.

• Protects patients’ identities from outside sources.
• Ensures the accuracy of records
• Keeps track of origin records.

In 2018, Medicalchain also launched its telemedicine platform, allowing patients to consult physicians and specialists via video calls and pay in “MedTokens.”

Patientory

Patientory’s blockchain platform, located in Atlanta, Georgia, allows for the secure storage and transfer of medical information. It supports end-to-end encryption, ensuring the secure exchange of all patient data. It also allows patients and providers to use blockchain to access, store, and transfer all critical information.

Closing thoughts,

We hope you now have a better understanding of how blockchain technology, when combined with AI and IoT, can be unstoppable in the healthcare industry. AI-enabled automated health checks that save money and time; patients’ immutable health records securely stored on the blockchain; and millions of devices performing precise diagnoses and finding better — the future of healthcare data management is near.