Cloud Based Healthcare is Slow to Change, but it's Happening!

November 01, 2016

Recently, cloud technology has evolved from a mere concept to the innovative reality of this century. It is extensively benefiting biobanks in managing their patient and sample data. Slowly yet steadily, cloud technology is now becoming part of diagnostics, clinical, research and testing laboratories worldwide.

Recent healthcare reports show that approximately 80% of global healthcare data will be stored in the cloud at some point in time in its life cycle by 2018. This shift is seen as a part of third-platform technologies dominating the future, which includes the cloud, big data analytics, mobile internet access, and social media tools.

Some hotspots for recent advancements include the developmental lab of University of Pittsburgh Medical Centre (UPMC), where radiologists are learning to work with a new cloud-enabled system for managing image files produced by CT scanners. This proves that tapping of cloud resources has just begun. Its true potential is not only limited to biobanks and clinical labs, it also includes radiology units for data management.

GE Health Cloud is planning to commercialize a medical imaging platform to store, share, and analyze their imaging data while supporting other imaging platforms, and not just to their machines and devices.

The usage of cloud technology in clinical and research laboratories is gaining popularity day-by-day. However, data security and information sharing remain as some of the biggest concerns in its adaptation. These concerns have lead to significant breakthroughs in security algorithms such as 256-bit encryption HTTPS protocol being deployed for transmitting data from a customer's PC to the server. The layering of databases has made viewing/ accessing of data by any third party almost impossible.

Hybrid cloud, which is a blend of traditional and modern cloud solutions, could be a trend in the coming decade. Organizations like academic medical centers and biobanks engaged in massive data-mining and analyses, especially for genomics and personalized medicine applications, will utilize the hybrid cloud infrastructure. This, however, would be a costly affair for small biobanks, hospitals, labs running on tight budgets. Companies such as CloudLIMS are proving to be a windfall for these small-to medium-sized organizations. Their SaaS-based Pay-As-You-Go payment model allows them to embrace the benefits of using the cloud platform, at an affordable price. CloudLIMS utilizes Amazon Web Services (AWS) which provides a rich experience to a user in terms of data backup, storage, networking, audit compliances, etc. Recently, Amazon and Google have inked HIPAA business associate agreements addressing several cloud-based security & regulatory aspects of healthcare. Additionally, CloudLIMS is also developing innovative solutions on its own to provide robust security measures to protect and safeguard sensitive data for its customers. It is just a matter of time until the percentage of cloud-based platform users will outgrow the ones using primitive, in-house IT managed platforms.

Need for Laboratory Automation

February 01, 2016

Today many research and development laboratories generate an unprecedented amount of data. With increasing data volumes and sample throughput along with advances in technology, labs seeking to streamline their operations and cut costs must modernize their laboratory management approach leading to efficient managing, tracking, and centralizing of data.

An automated laboratory reduces the risk of human error and allows personnel to be deployed for core laboratory jobs, thereby saving time and money, in addition to improving work efficiency. It also helps in presenting the lab in a more professional manner to various collaborators and granting authorities by enabling end-to-end sample and workflow management, assuring traceability of results and maintaining data integrity by following standard laboratory practices.

Laboratories using sample management software tools increase their efficiencies in primarily two ways:

  1. Results are achieved faster, are far more accurate, reproducible and reliable

  2. Data is easier to store, trace, and assess over time and across experiments so that laboratory processes can be monitored and improved to increase operational efficiency

Recent trends in providing software solutions have drastically changed scientific research perspectives and methodologies for data storage. Be it a small biobank or a large biorepository, automated management is a prerequisite determining their success in effectively managing the sample data.

Prerequisites of a Good Sample Management software

  1. It should allow 360° sample traceability such as unique identification, barcode based tracking, sample genealogy, chain of custody and audit trails etc.

  2. The system should provide role based access privileges grounded on the accountability of the person in lab operations

  3. Provide end-to-end information management of samples, tests, and results for biobanks, pharma and clinical trial labs

  4. Offer the ability to create custom and standard reports

  5. Enable a lab to get up and running quickly on its preferred instrumentation

  6. Every sample management system should be in compliant with HIPAA regulations, 21 CFR part 11 regulations and GLPs

  7. Be easy for lab staff to configure and customize, without the need to spend on costly customization. It should allow users to create custom workflows, applications, and reports easily

  8. Enterprise Grade Security to their clients with 256-bit data encryption level and their data centers should be AICPA developed SOC compliant

Parameters to be Considered for Purchasing a Sample Management Software

Parameters such as setup costs, license price, implementation time, customization, training, maintenance, design and ease of use, statutory compliances such as HIPAA, GLP, CFR 21 Part 11 support, audit trails, electronic signatures, validation and report import/export should be taken into consideration before selecting a new laboratory automation system.

Software security

Many modern laboratories and production units are required to meet regulatory guidelines. Traceability is the key component of solving many technical challenges. Working with a software with traceability options offers huge benefits when solving technical issues and complying with documentation demands. The sample management software compliant with HIPAA regulations facilitates masking of sensitive information based on the role of the user. The software system should be compliant with 21 CFR part 11 regulations and GLPs (Good Laboratory Practices). Electronic signatures can further be configured for steps taken by the user and the software also maintains an audit trail along with a date and time stamp. CloudLIMS, a user friendly, web based sample management offering from CloudLIMS is one of such tools. The tool is compliant with HIPAA, 21 CFR part 11 regulations and GLPs, making it essential for any laboratory wanting to automate their systems in a secure and reliable environment.

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