Across industries, digitization and the resulting increase in the access to data is changing the way organizations are serving their clients by reduced costs. Healthcare has been a serious contender in the digitization revolution, and as the health records shift from paper to electronic, the amount of available healthcare data has proliferated rapidly. Healthcare data management is the process of storing, protecting, and the analysing of data pulled from diverse sources. Managing the available healthcare information allows health systems to create holistic views of patients, personalize treatments, improve communication and enhance health outcomes.
This article covers the different approaches to data management, current trends, opportunities, and unique challenges in healthcare database management.
The healthcare sector has been snowballing in the last 30 years. Historically, the healthcare industry has generated large volumes of data, which is driven by record keeping, compliance and regulatory requirements, and patient care.[i] In current healthcare scenario, more than 75% of patient data is unstructured and comes from digital devices and sensors, emails, doctors’ and nurses’ notes, laboratory tests, and third-party sources outside the hospital.[ii] While most data is stored in hard copy form, the current trend is the digitization of these data.i
Every healthcare organization in the world is using digital patient-data management system for ensuring the availability of patient data to healthcare providers in a hospital/clinic/physician’s office/contract research organizations. Since patient-related sensitive data are being stored electronically, new strategies should be adopted by health information technology (HIT) professionals in order to securely manage and protect that data and to be sure that healthcare data management protocols comply with government regulations such as the Health Insurance Portability and Accountability Act (HIPAA).[iii]
Approaches to Data Management
Healthcare data is managed by using technologies like Electronic Health Records (EHR) and Healthcare Customer Relationship Management (HCRM).
An EHR is a digital version of a patient’s paper chart. EHRs allow the physicians to store and record the patient information electronically, thus, simplifying the medical recording process for authorized users. This tool helps healthcare organizations to consolidate, centralize, and securely access patient medical data.
HCRM is a customer relationship management system designed specifically for use by healthcare organizations. It can integrate, measure, analyse, and present the data from different sources into one data hub. HCRM allows consolidating the user and patient data from EHRs, engagement centers, social media, and many other sources. With HCRM technology in place, healthcare organizations can develop a 360‑degree view of patients that helps to portray patient lifecycle along with their profiles, preferences, and behaviors.[iv]
Due to the latest advancements in analytics and big data technologies, the healthcare industry is on the verge of a major transformation.
- Value-based patient-centric care: A significant change in the healthcare industry’s approach to providing care is by putting the patient at the center of care. The goal is to improve patient satisfaction scores and engagement. Modern healthcare systems promote the meaningful use of HIT to reduce healthcare costs, improve patient outcomes, and provide support for reformed payment structures.
- The healthcare Internet of Things (IoT): The IoT is described as a network of internet-connected objects/devices which enables the collection and exchange of data. These devices monitor a wide range of patient behavior including glucose levels, heart function, blood pressure, etc. Combination of machine learning with the smart devices could transform the entire process, could lower the cost, and improve patient care. For example, smart medicine dispensers that can detect if the medicines are being taken as per the prescription, and if not, then a phone call can be initiated to remind them.ii
- Reducing fraud, waste, and abuse: Skyrocketing healthcare costs are mainly due to fraud, waste, and abuse in the healthcare industry, but data analytics can be a game-changer for healthcare fraud.[v] The key to identifying the fraud is by using artificial intelligence to detect the abnormalities and patterns in large unstructured datasets. Healthcare organizations can analyse patient records and billing to detect anomalies such as a hospital’s overutilization of services, patients receiving simultaneous treatments from different locations, or filing of similar prescription for the same patient in different locations.
- Predictive analytics to improve outcomes: As the application of EHR accelerates, the amount of patient data also increases. Being able to analyse the structured and unstructured data across multiple sources helps in the accuracy of diagnosing patient conditions, matching treatments with outcomes, and predicting patients at risk for disease or readmission. Using predictive modelling on EHR data enables the earlier diagnosis of a variety of illnesses, significantly reducing mortality rates.
- Real-time monitoring of patients: Healthcare organizations proactively monitor patients vital signs and this data gets analysed in a real-time health monitoring system. This system instantly alerts the healthcare provider if patients condition is changing. The use of machine learning algorithms provides more information about the patient to the physicians which helps them in making lifesaving decisions. Wearable sensors and devices make healthcare process more convenient and resolute by assisting healthcare providers to interact with patients in different ways. ii
Opportunities in Healthcare Data Management
- Promotes research and innovation: Data analytics provides the current health status of patients, which gives them insights to take more ownership of their healthcare. The information-sharing mechanism increases productivity and reducing overlapping of data, which enhances the coordination of care.
- Personalized medicine: Personalized medicine is a new kind of approach for treatment and prevention of diseases in which variability in genes, environment, and lifestyle of each patient is taken into consideration.
- Strengthens the preventive care: Prevention is always better than cure. Following this thumb of rule, with the advent of data analytics, it is easy to capture, analyse, and compare patient symptoms in advance, to offer preventive care in a better way.
- Health trend analysis: Health trend analysis and complete information on patient management is much easier to obtain by using data analytic techniques such as data mining and text mining.i
Unique Challenges from Healthcare Data Management
- HIPAA compliance: Meeting HIPAA compliance requires a specific set of security measures for EHRs that have to be shared among practitioners and made accessible to patients. This is a challenging balancing act for many healthcare providers. For the hospital information system (HIS) managers who are used to operating a closed-network system, implementing shared data access and security protocols using technologies such as cloud computing is new territory. Adequate security is a particular concern, even without HIPAA regulations, because the cost of a data breach in the healthcare industry is significantly higher than in other industries.
- Mobile computing: Healthcare has become more efficient by the digitization of patient records. Physicians and nurses prefer to use smart systems to access patient records and to make data entries rather than noting on medical charts. Direct data entry removes steps and reduces errors, but it also means that HIS managers have to provide secure wireless access throughout the care facility with enough bandwidth to support a growing number of handheld workstations. It also means that they have to develop new security and compliance protocols for physicians who want to use their own mobile computing hardware.
- Sharing patient data: Centralizing patient records within a medical organization is certainly effective because of the standardized environment but sharing of patient’s complete medical records with external healthcare providers and integrating different medical data management systems is an ongoing challenge because they may use different systems and protocols.
- Lack of integration between clinical and administration systems: Often there is an integration gap between patient care and administration. Medical records maintained by hospital staff should reflect accurately in insurance claims and patient billing. The data management system should be configured to ensure that treatment codes and treatment provided to the patient is accurately tracked for both administrative purposes and analytics.
- Operational analytics: Healthcare data, including EHRs, has become an essential part of measuring operational efficiency. Healthcare workforce management, for example, is largely measured using patient care and healthcare data. HIS managers are looking for new strategies to mine healthcare data to perform productivity and profitability analytics to isolate profit centres and areas of practice that need to be reviewed and revised.
- Lack of analytics talent: As with data analytics for other industries, healthcare providers are struggling to find the right analytics experts to help them get the most out of their databases. There is a dearth of data scientists, especially those with a healthcare background, who can apply big data analytics to assess healthcare operations.iii
- Data Aggregation: The data available in the healthcare industry is in an unstructured form. These unstructured data are in the form of images, graphs, notes of other healthcare provider’s and many. Natural language processing and free-text software could help in the compilation of theses unstructured data into a structured form.i
Benefits of Healthcare Data Management
Healthcare data management creates 360-degree views of patients and includes personalized interactions by integrating patient data from all available sources. Health data management can also lead to lower costs in areas that are related to and affect patient care. With the help of data analytics, doctors are able to detect serious and potentially life‑threatening health conditions in advance. Quality of overall care has increased, and the patients that can benefit the most from more proactive intervention can be correctly identified through big data analytics.
On a larger scale, population health can also benefit greatly from health data management as the use of data provides doctors and healthcare administrators with improved tools and the increased ability to anticipate patient needs. For example, mobile health tools and e-health applications can make it possible for patients to transmit information on their health status to their doctor’s office or hospital while at home. Overall, these benefits of strong health data management clearly outweigh the costs of implementation for healthcare organizations of all kinds.iv
The purpose of healthcare data management is to ensure that the entire critical information is present at one place and can be easily accessed by patients, hospital administrators, and physicians. A healthcare facility should be able to take actions from the insights obtained from these data to improve patient engagement and satisfaction. 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. Before considering any healthcare data management solution for a hospital, a flawless and complete Electronic Medical Record system must be designed which should be centralized and follows all the standards and is compliant with all state and national regulations. This system should be secure and capable of obtaining information from different sources, integrating and sorting the data, and analyzing the data necessary for the organization and must provide access to necessary data and visualize it in a user-friendly and comprehensive way.
|EHR||Electronic Health Record|
|HCRM||Healthcare Customer Relationship Management|
|HIPAA||Health Insurance Portability and Accountability Act|
|HIS||Hospital Information System|
|HIT||Health Information Technology|
|IoT||Internet of Things|
- Patel S, Patel A. A big data revolution in health care sector: Opportunities, challenges and technological advancements. Intern Journal of Inform Sci and Tech. 2016;6(1/2):155-162.
- McDonald C. Five big data trends in healthcare. Spectra. 2017. Available from: https://www.itproportal.com/features/five-big-data-trends-in-healthcare/.
- Big data. The Top Six Challenges of Healthcare Data Management. Available from: http://www.ingrammicroadvisor.com/data-center/the-top-six-challenges-of-healthcare-data-management.
- What is Healthcare Data Management and Why is it Important? Evariant. Available from: https://www.evariant.com/faq/why-is-healthcare-data-management-important.
- Five big data trends in healthcare for 2017. MAPR. Available from: https://mapr.com/blog/5-big-data-trends-healthcare-2017/.
Sunil Singam, Executive – Pharmacovigilance at FMD K&L
Sunil is a Pharmacovigilance professional with 2 years of experience in in organizing the scientific/medical support information for specific claims platforms, claims studies, claims substantiation support, scientific resources, data mining, literature search, literature review, and claims intelligence for beauty care, baby care, wound care, hair care, and oral care products.
Goutam Hanje, Executive- Clinical Safety at FMD K&L
Goutam is a trained pharmacologist having more than 3 years of work experience in conducting, Monitoring and Data reviewing of phase 1 Clinical trials and BA/BE (Bio Availability & Bio equivalent) clinical studies. Clinical Safety, data management and Claims Reviewer for Cosmetics and OTC products.