Healthcare Analytics Software Solutions

Clinical researchers and other professionals in medicine and academia utilise advanced healthcare analytics solutions to collect, manage and share data related to clinical trials and medical research. With access to increasingly powerful digital technology, healthcare providers have more data at their disposal than ever, and can now combine and share it globally. They can also take advantage of new digital tools to drive operational efficiencies, reduce costs and improve safety. Despite this, few healthcare providers exploit the full potential of cutting-edge healthcare analytics software.

How do organisations leverage healthcare analytics platform software?

Digital healthcare analytics solutions are utilised across the research sector to facilitate safe, effective and accurate clinical trials, manage health samples and data, and create valuable healthcare databases. In respect, healthcare organisations leverage digital analytics platforms in three core areas.

Clinical trials

Healthcare analytics software plays a critical role in collecting, managing and analysing clinical trial data. From helping to identify suitable trial candidates and streamlining data entry methods to monitoring adherence to trial protocols and helping to visualise results, healthcare analytics platforms are central to modern clinical research.

Quality registries

Quality registries typically feature data collected from diverse sources. Advanced digital solutions standardise the data, help identify discrepancies and improve the reliability and accuracy of the information collected. They will also often feature tools for displaying, monitoring and analysing data, and allow for easy extraction by relevant healthcare professionals.

Biobanks

With biobanks, sample integrity is a key consideration. Organisations require a robust system for cataloguing, storing and tracking biomaterial samples, as well as a means of facilitating quick retrieval. Healthcare analytics solutions incorporate a range of functionalities that ensure these processes are more efficient and less exposed to human error.

Core features of advanced healthcare analytics software

To meet the needs of clinical researchers and healthcare providers, digital health analytics platforms should integrate the following features and functionalities.

1. Intuitive data entry and automated data capture

Health analytics platforms can streamline and simplify time and resource-intensive data collection, reducing costs for healthcare organisations and the administrative burden on clinical researchers. They achieve this by implementing intuitive data-entry mechanisms, including streamlined forms, automated data capture from external sources and auto-population. Effective digital solutions must be built according to researchers’ needs, allowing for customisation where possible and providing a degree of flexibility.

2. Facilitate patient-reported outcome and experience measures

Patient-reported data is an integral aspect of most clinical trials, complementing medical metrics gathered by clinicians. Collecting patient-reported outcomes requires a unique approach, as does integrating that data into other scientific databases to enable use by other researchers and healthcare professionals. Digital solutions optimise these processes and simplify critical data collection, integration, management and display.

3. Advanced data analysis capabilities

Digital health analytics platforms should also include a comprehensive suite of analytics, statistics and visualisation tools, enabling researchers to better understand the collected data and present it in a more comprehensible manner. This can include real-time statistical dashboards, graphing capabilities and customisable reports. These tools must be user-focused and easy to use.

4. Real-time data validation to guarantee quality

In clinical trials and medical research, accuracy and reliability are essential. Health analytics solutions enhance reliability by incorporating validation protocols that eliminate opportunities for human error. They can also improve accuracy by utilising auto-population techniques that reduce the amount of data users enter manually.

5. Performance measurement and benchmarking

Specialist analytics platforms allow healthcare organisations to measure performance in particular facilities and regions, enabling organisations to identify strengths and weaknesses and improve processes. Benchmarking against regional, national and international standards helps providers maintain a high level of care and acts as an early-warning indicator if performance is declining.

6. Access and integration with quality registries

Organisations use quality registries to improve healthcare delivery, support clinical research and inform health policy. To achieve this, quality registries must standardise data arriving via diverse data pipelines, enabling comparison and reliable analysis. Health analytics platforms facilitate the effective management of quality registries, improving access to the information contained within. This results in superior knowledge sharing and data-based decision-making.

7. Comprehensive access management

Data collected for clinical trials is often highly sensitive and organisations must handle it with care and consideration. Solutions should incorporate effective data security measures that guarantee the integrity of participants’ personal information. At the same time, access management features ensure approved users can access data while blocking those without the necessary permissions.

8. Complete traceability

Accountability and transparency improve clinical trials and healthcare research by enabling medical professionals to identify issues in processes and rectify them. A complete record of how samples are submitted, managed and stored improves our understanding of how and why errors occur. At the same time, it enables organisations to account for their actions and justify their decision-making.

9. Evidence-based decision support

In modern healthcare systems, data drives decision-making. Consequently, health analytics software must support decision-makers by providing them with the information and evidence they need to optimise resource allocation, develop treatment strategies and evaluate the effect of new drugs and their side effects.

10. Built-in compliance

Healthcare data is subject to significant regulation and all healthcare organisations are concerned with compliance. Falling foul of ever-evolving healthcare legislation can be disastrous. Digital technology providers can build compliance into their solutions, promoting compliant collection, management and sharing of data and preventing improper use. As regulations differ from market to market, compliance functionality must be customisable and tailored to the customer’s needs.

Omda Healthcare Analytics solutions

With more than 20 years of experience in the Healthcare Analytics sector, Omda has been at the centre of digital development, delivering groundbreaking solutions and driving innovation. Currently, our Analytics portfolio consists of two principal products – Omda Research and Omda Health Intelligence.

Omda Research supports research and facilitates accurate and reliable data collection, management and analysis in clinical trials. Emphasising streamlined data entry, real-time validation and customisable reporting, it also acts as a complete online platform for hosting and managing quality registries and includes a web-based system for cataloguing, storing and tracking biomaterial sample data.

Omda Healthcare Intelligence is a versatile digital solution for electronic data capture and decision support that enables researchers, healthcare professionals and organisations to leverage their data to improve healthcare outcomes, operational efficiency and resource allocation.

Learn more about Omda Health Analytics solutions.