How Healthcare Data Management Overcomes Challenges for Hospitals

The evolution of healthcare technology is driving the evolution of the industry. Modern healthcare systems need effective means to manage health data capable of providing care providers and professionals with fully integrated and complete medical records.

What is Health Data Management

Have you ever wondered how much data a health organization uses each day? All that patient data, lab test data, images from MRTs and X-rays, administrative data, and financial data form huge silos of information that must be processed and analyzed to be of any use.

There are some types of data management systems that are already accessible to medical practitioners. Electronic Health Records (EHRs), the use of which is mandated by the Health Information Technology for Economic and Clinical Health Act (HITECH), and Health Information Technology (HIT) are used to securely manage and protect data, though healthcare systems still have some difficulties to overcome to ensure “meaningful use” of healthcare data.

The statistics of the Office of the National Coordinator for Health Information Technology show that more than 90% of U.S. hospitals are using EHRs.

Though the initiatives in healthcare systems supported by the government foster the creation of more unified and commonly used data management systems, they have also led to a torrent of unstructured data from disparate systems. For now, at least 50% of the patient content is generated outside the Electronic Medical Records system. The health information is collected from various sources like paper, clinical images from different locations and machines, nurse notes, remote monitoring systems, etc. All this information must be effectively integrated and managed to unlock the value of this data and let physicians and clinicians get important information to use for patient care.

According to Meaningful Use Objectives, the meaningful use of certified electronic health record (EHR) technology should:

• Improve quality, safety, efficiency, and reduce health disparities
• Engage patients and families
• Improve care coordination, and population and public health
• Maintain the privacy and security of patient health information

The three stages of meaningful EHR use set specific objectives that eligible professionals (EPs) and hospitals must achieve to qualify for Centers for Medicare & Medicaid Services (CMS) Incentive Programs. Those objectives are data capture and sharing, advanced clinical processes, and improved outcomes. This means that providers now must not only collect data and put it into EHRs but use this data in a meaningful way, i.e. to get insights out of the data and apply the findings. Starting in 2017, Medicare eligible clinicians will report to the Quality Payment Program. According to Centers for Medicare and Medical Services, beginning on January 2, 2018, eligible hospitals and critical access hospitals (CAHs) attesting to CMS will submit their 2017 meaningful use attestations to the QualityNet Secure Portal (QNet).

All these prerequisites mean that healthcare organizations need a unified approach to data management to turn their data assets into data insights. Let’s consider what pitfalls are hidden on the way to the creation of a full and meaningful picture of a patient’s journey.

Healthcare Data Management Challenges

Healthcare providers have to manage the data they obtain, and data management solutions for this market should integrate, measure, analyze, and form reports on a broad variety of data. The goal of any such system is to provide insights for better administrative, clinical, and financial decisions. And the ultimate goal is to improve patient care, reduce costs, and improve patient engagement.

Here we should remember that the provider environment is complex, and has many interrelated components. Therefore, healthcare organizations have extract data from various sources and have to integrate those heterogeneous sources of data. Even when using EHR protocols actively, healthcare data management for hospitals poses some distinct challenges to overcome. Let’s find out what are those challenges for data management in healthcare.

HIPAA compliance is the challenge that is most obvious. The Health Insurance Portability and Accountability Act (HIPAA) requires a specific set of data security measures for EHRs to make sharing Protected Health Information (PHI) safe. Adequate security is a concern for the organizations used to store data in hospital information systems (HIS) which are usually closed-network ones, because comparatively new but very popular technologies of data storing and sharing, such as cloud computing, require implementing shared data access and HIPAA compliant security protocols. The compliance issue is very important as the cost of a data breach in the healthcare industry is very high.

Mobile computing is another introduced by technology developments. Patients and doctors now have more opportunities to collect and share data using smartphones, wearables, tablets, and handheld data entry systems. Access to data becomes faster and more efficient, but this also means that secure wireless access is a must. It also means that new security and compliance protocols both for doctors and patients must be developed.

Patient data sharing is another concern. Besides HIPAA Security Rule compliance, there’s another challenge. Centralized data management systems are effective for dealing with records of patients treated in a medical facility, but when it is necessary to share the data with practitioners outside the facility, the problem of integrating different data storage standards can arise. So it is necessary to adopt EHR data storage standards and protocols to allow meaningful use of data between various providers.

Integration between clinical and administration systems is necessary to avoid the gap between patient care and medical facility administration. Here, the core of the problem is adequate coordination between physician records, insurance claims, and patient billing. The treatment codes of the data management system must match the codes used for administrative purposes and analytics.

Integration of legacy systems with any new data management system adopted by a healthcare facility is also important, both for government regulation compliance and efficiency of all medical facility departments (medical, administrative, and financial).

Providing relevant data for operational analytics is another challenge for today’s health data management. Efficient healthcare data collection, including EHRs, and practical use of big data insights are necessary for measuring operational efficiency. It is clear enough that new strategies to mine healthcare data should be adopted for efficiency and profitability analytics to find the areas that need to be improved and to make informed decisions.

What can we do to achieve consistency in a patient, provider, procedure, and facility information?

Healthcare Data Management Solutions – Best Practices

Besides government incentives, there are tangible benefits of healthcare data management both for care providers and their patients. And first of all, a qualified approach to data management allows healthcare organizations to achieve meaningful use of data assets. It can improve financial analytics and operational performance analytics making it easier to identify best practices of in-network professionals and to replicate those practices throughout the facility, thus improving the quality of patient care.

When considering a health data management solution for a hospital, keep these key elements in mind:

• You should start with a data governance strategy to capture only the right information necessary for your organization.
• The developer of a health data management system must design a seamless and complete EMR system based upon standards and compliant with all state and national regulations.
• There should be a secure centralized data repository built on a relational database. This database must be capable of getting information from multiple disparate systems, integrating, sorting, and analyzing the health data necessary for your organization.
• Your system must provide access to the necessary data and visualize it in a user-friendly and comprehensive way.
• Your data management solution must use and provide only quality data. Accurate data allows for efficient analysis. This is why data must be checked for accuracy, consistency, and thoroughness.

The final goal of any health data management solution is to make sure critical information reaches patients, hospital administrators, and physicians. To improve patient engagement and satisfaction, a healthcare facility must be able to turn insights obtained from the data into action.

A 360-degree picture of financial, operational, and clinical performance based on the right information provides healthcare organizations with the data to conduct in-depth analyses. Based on those analyses you can build successful processes in the areas of opportunity that are discovered.