As technology advances, laboratories are becoming more sophisticated in the range and quality of services they offer. Automation and modern machinery promise to expedite patient care and enhance laboratory efficiency.
Precise, patient-centric testing and analysis enabled by a range of complex connected instruments and devices that provide data from both inside and outside of the lab. Delivery robots handle several fetch-and-deliver tasks and locate specimens in real-time. Physicians can review medical images more quickly and precisely with digital medical imaging systems.
Point-of-care (POC) devices enable testing from the comfort of your sofa and produce round-the-clock data.
The challenge for labs is to effectively integrate and manage point-of-care devices and the resulting data they produce to facilitate accuracy, data flow, and laboratory performance. An advanced cloud-based, SaaS solution, integrated laboratory information system (LIS) with an open architecture and in-built data management tools facilitate successful data management.
Open API for interoperability
A predecessor to streamlining machines and instruments is the LIS’s ability to interface with devices in a scalable manner and enable information exchange. This ability is just as important for clinical decision-making tools, patient information tools (such as electronic medical records, EMRs), or external test devices (such as POC devices). It is also true for robotic lines, artificial intelligence, and machine learning tools often used in labs. For example, to receive samples, identify or move samples, and re-run tests. The LIS must also be able to scale integrations to support new technologies so that information flows seamlessly. A LIS product with an open and standard architecture best supports interoperability, as it ensures integration with all devices, and minimizes integration challenges.
Cloud for flexible data storage
A cloud-based LIS is a natural facilitator for data management. Its flexible data hold means that laboratories can receive, and hold data from anywhere – be it EHRs, instrumentation, or POC devices. With cloud computing, laboratories can easily scale and add new modules or machines, which would have previously required massive overhead.
A Software-as-a-Service (SaaS) model offers minimal overheads and drastic reduction of maintenance fees. Everything, from hosting to upgrades, becomes the responsibility of the hosting provider. Similarly, providers are responsible for providing expert security levels that comply with HIPAA and other data privacy regulations in the healthcare field.
Point-of-Care devices for round the clock care
With Point-of-Care (POC) devices gaining momentum and spearheading a more patient-centric approach is easy and fast. Especially with chronically ill patients, doctors can use POC devices while the patients are tested in hospitals or in the comfort of their own homes.
The challenge with POC devices is collecting and making use of this data to offer fully integrated patient care. Currently, some LIS systems can integrate this patient data into a patient’s records and disseminate it to doctors looking after that patient. Again, the interoperability of devices is a pre-requisite for this, but integrated patient data from multiple sources will become natural over the next few years. With the technological advances, 5G, and digital transformations, it won’t be long before all devices are connected. So, it is important to consider innovative and scalable solutions to collect and make use of these large amounts of disparate data.
Another challenge with POC devices is the connectivity between the devices and the lab. If a laboratory is to use POC device-generating data it must control the quality of the device. An option is to use third-party software (such as Bio-Rad) which gives labs an indication of the device’s performance to other identical devices. LISs must be able to interface with such software for this process to be effective. More sophisticated LISs will offer inbuilt quality control (QC), such as the ability to assess a moving average. As the integration of POC devices to LIS becomes more established, both these options will have to integrate as standard.
Centralized data management for a holistic view
The limited-time medical decision-makers have in making a diagnosis sometimes leads to missed or inaccurate diagnoses. Indeed, diagnostic errors affect approximately 12 million U.S. adult patients each year, resulting in patient harm, as well as lawsuits. Errors in diagnostics may be caused by misreading clinical studies, focusing on the wrong conditions, not assessing a patient’s condition, or relying too heavily on a previous diagnosis. Incorporating diagnostic decision tools into a LIS, such as those that analyze a patient’s medical history, current symptoms, and compute a list of likely diagnoses based on previous cases, has shown to aid diagnosis by expanding the number of possibilities a physician will consider. To do this, a LIS must be capable of presenting the decision-maker with all relevant information simultaneously. LIS systems that gather data from diverse sources will fail labs, as even with complicated middleware, it will remain problematic for physicians to understand the whole picture in a snapshot.
A united LIS built off one database with centralized data storage, along with a unified reporting system gives physicians a leg up in their demanding diagnostic decisions.
Mobile health (mHealth) initiatives
Mobile devices play an integral role in the creation and transfer of data. Mobile outreach programs, that are an intrinsic extension of a LIS, allow patients and physicians to use tablets, smartphones, and other mobile devices to view and record information anytime and anywhere. As a type of POC device, LIS must store and manage the data it receives from mobile devices. Mobile health encourages more direct and instant doctor-patient communication and a more patient-centric approach. Mobile outreach programs also enable laboratories and phlebotomists to track samples on the road or between sites, change orders, or create add-ons for better patient care.
Compliance
Laboratories must be especially mindful of how they implement data-informed decision-making. Regulations like HIPAA and HITRUST compliance require data to be kept secure, private, and anonymized for those who do not require access to patient data. To comply with these and other regulatory requirements concerning data security, such as a complete audit trail, batch records, signatures, permission management, etc., laboratories should employ a LIS with built-in data management tools, effectively delivering compliance out of the box.