Data can change lives. It is a vital part of daily living, with businesses also relying on data sets to improve product offerings and customer experience.
The growth in data consumption worldwide is proof. Research suggests the amount of data worldwide grew by 5000% between 2010 and 2020. Such is the consumption and importance of data that its total amount generated has doubled every three years.
And it is set to increase: the total installed global data storage capacity base could increase to approximately 13.2 zettabytes (2024) from 6.8 zettabytes (2020). The total amount of data in utilised storage will reach 8.9 zettabytes by 2024.
From manufacturing to aviation, every industry relies on data sets and analytics to derive results. The healthcare sector is no different, using raw data to find better diagnoses and treatment methods.
Introduction to Data in Healthcare
Data is invaluable in healthcare. Pharma and healthcare companies use data sets to improve their financials as well as produce products and solutions to improve healthcare facilities.
Health data collated from health information systems and technological tools help healthcare professionals, insurance companies, and government organisations understand what troubles people.
Data from diagnosis and surgeries provide a holistic view of patients’ health and is used to find trends, basis location, socioeconomic status, race, and other factors. Healthcare organisations form datasets and research ways to address the lingering health problems.
Electronic Health Records (EHRs), Master Patient Indexes (MPI), and Health-Related Smartphone Apps are tools used to collect, store, and analyse data. While each step is equally vital to find better health outcomes, data analysis requires special care.
Data Analytics in Healthcare
The healthcare industry is always in demand. As a result, public and private companies engaged in healthcare directly or indirectly generate a tremendous amount of data.
It is challenging to analyse it manually and find trends and solutions. Data analytics in healthcare is a sound solution, helping organisations overcome obstacles and build solutions that matter.
With data analytics, colleagues and external partners can effectively share data amongst themselves, making it easier to visualise for public consumption. It can also provide accurate data-driven forecasts in real-time, ensuring healthcare providers respond quickly to changing healthcare markets and environments.
Thanks to data analytics tools, companies can innovate faster by converting analytics-ready data into business-ready information.
Key Benefits of Data in Healthcare
Data in healthcare has massive scope. It can improve every aspect of the industry, including research and improving health outcomes. Still, a few benefits stand out for their impact on patients, employees, and the industry.
1. Improved Medical Research
Data analytics techniques have already revolutionised research efforts in health-related fields, gathering and analysing clinical data. Electronic Health Records (EHRs) are one example.
Electronic Health Records (EHRs) are one of the most significant sources of clinical information. They store patients’ X-rays, medical images, diagnoses, treatment plans, allergies, and test results in standard digital formats.
However, EHRs bring privacy and regulatory compliance requirements that restrict data use. Electronic Medical Records (EMRs) are like EHRs, but they only contain information from patients’ paper charts created in medical offices, clinics, and hospitals. EMRs are used for diagnosis and treatment and track patients’ healthcare over many visits and screenings.
Data analytics can also revolutionise personal health records (PHRs). PHRs maintain a patient’s health treatment history that the patient manages instead of healthcare providers. While PHRs do not legally replace the medical records maintained by healthcare providers, they assist patients in managing their health.
Public health records, such as the Cancer Research Data Commons, are promising health data sources for medical research. They serve as cloud-based data science platforms linking data analytics tools with data repositories storing genomic, proteomic, comparative oncology, and other data types.
2. Better Health Outcomes
Better health outcomes are one of the key goals of healthcare organisations and personnel. Doctors, surgeons, and nurses aspire to treat patients safely and effectively while minimising the trauma that comes with their treatment.
An analytics system can help healthcare professionals collect and analyse patient data in real time. Examples of patient data used for analysis include blood sugar level, temperature, and blood test results.
Analysing these with a system can help professionals better understand complex healthcare environments, develop systematic approaches to improve patient outcomes, and continuously enhance healthcare processes. Thanks to health data management systems, professionals see lower readmission rates, reduce errors, and better identify at-risk populations.
However, challenges exist. Healthcare professionals often struggle with choice as data-backed systems factor in and monitor several health parameters. One way to avoid the problem is to focus on key performance measures and collect the minimum data needed to track those measures.
3. Actionable Operational Insights
Healthcare providers directly impact the quality of care patients receive and the likelihood of positive outcomes through their work processes and organisational structures. Analysing healthcare provider data related to these processes in complex healthcare environments is crucial for measuring the effect of process changes on outcomes and operational efficiencies.
To improve the quality and efficiency of healthcare, healthcare providers conduct an organisation-wide assessment of current conditions, followed by aligning the institution’s strategies and goals for improvement. Employee scheduling, charting, emergency preparation, administration, financial management, and compliance are among the operational areas that benefit the most from data analytics.
Healthcare providers adopt various approaches to enhance operational efficiencies and maintain a high standard of care. These include reducing waste, tech integration to reduce costs, increasing hospital capacity, improving project management, and sustaining outcome improvements.
To cost-effectively implement data analytics, organisations measure and improve those operations that help the most for improved outcomes.
4. Efficient Staffing
Staffing is vital in healthcare as employees engage with several patients daily. Finding the right employees can help healthcare organisations build better connections with patients and understand their needs deeply.
Many companies rely on data analytics to address staffing issues and facilitate recruitment, hiring, training, and retention of healthcare workers. Data analytics tools help healthcare providers balance costs, efficiency, and patient outcomes with the growing scarcity of qualified medical professionals.
Intelligent data systems help manage labour costs in healthcare settings while boosting the quality of care patients receive and the efficiency of service delivery.
On the Growth Curve
Data analytics and healthcare have a promising future, per a report by Allied Market Research. The study estimates the global healthcare analytics market size will touch $96.90 billion by 2030 from $23.51 billion in 2020, indicating a 15.3% CAGR growth.
Several factors, including the need for laboratory automation and the increased prevalence of chronic diseases, have pushed healthcare companies to integrate big data into their thinking.
It is also essential as intelligent health data management improves patient care and health outcomes. Collecting and analysing health data can help healthcare providers diagnose illnesses, develop treatment plans, and improve the quality of care for patients.
Data in healthcare can also push public health policymakers to adapt quickly to problems and provide better care. While challenges exist, the potential benefits of data in healthcare are significant.
Smile Foundation and Healthcare
Smile Foundation’s comprehensive and community-centric health programme takes primary healthcare services to the doorsteps of underserved communities in both rural and urban India. Following a two-pronged approach, our health programme provides curative as well as preventive services, addressing the gaps in the availability, accessibility, and affordability of healthcare.