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Streamlining the Management of Machine and Data

Through technology, laboratories are becoming more sophisticated in the range and quality of services they offer. Automation and novel machinery promise to expedite patient care and enhance laboratory efficiency.

Precise, patient-centric testing and analysis is aided by a variety 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. Digital medical imaging systems make the process of reviewing medical images by physicians, as well as other medical professionals involved in medical decisions, so much faster and more precise. Point-of-care (POC) devices, enable testing in locations that are comfortable for the patient and produce round the clock data.

The challenge for labs is to effectively integrate and manage novel machinery and the resulting data they produce, in order to facilitate accuracy, data flow, and laboratory performance. An advanced integrated LIS with an open architecture and in-built data management tools facilitates successful management of data in the following ways:

Open API for interoperability

A predecessor to streamlining machines and instruments is a LIS’s ability to interface with devices in a scalable manner and enable information exchange. This 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 to re-run tests. The LIS must also be able to scale integrations in order 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 accept and hold data from anywhere – be it EHRs, instrumentation, or POC devices. Laboratories can easily scale and add new modules, or machinery, something that would previously have required massive overheads.

A Software-as-a-Service (SaaS) model offers ease of use, minimal overheads, and a drastic reduction of maintenance fees, as everything from hosting to upgrades becomes the responsibility of the host provider. Similarly, providers are responsible for providing expert security levels that comply with HIPAA and other data privacy regulations in the healthcare field.

POC devices for round the clock care

With POC devices gaining momentum, and spearheading a more patient-centric approach, especially in the care of chronically ill patients, doctors can make use of POC telehealth—patients can be tested in hospitals, or in the comfort of their own homes. A major challenge with POC devices is collecting and making use of this data to offer fully integrated patient care. Currently, there are some LIS systems that are able to 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. It won’t be long before all devices are connected, so it is important to consider innovative solutions to collect and make use of these large amounts of disparate data.

Another challenge with POC devices is the connectivity of the instruments themselves, and how the lab can control the quality of the information it receives from instruments. If a laboratory is to use POC device-generated data it must have control over 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 in relation to other identical devices. LISs must be able to interface with such software for this to be effective. More sophisticated LISs will offer inbuilt quality control (QC), such as being able to assess a moving average. As the integration of POC devices to LIS becomes more established, both these options will have to be integrated 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. Diagnostic errors may stem from misinterpretation of clinical studies, narrow diagnostic focus, inadequate or inappropriate testing, failure to adequately assess a patient’s condition and overreliance 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. In order to do this, a LIS must be capable of presenting the decision maker with all relevant information simultaneously. LIS systems that comprise of separate components for different disciplines will let labs down, in that even with complicated middleware to pull data from different sources, it will be difficult for physicians to understand the full picture in a snapshot. A united LIS built off one database, and with centralized data storage and unified reporting gives physicians a leg up in their demanding diagnostic decisions.

Mobile health (mHealth) initiatives

Mobile devices play an important role in the creation and transfer of data. Mobile outreach programs, that are an intrinsic extension of a LIS allow patients and physicians to make use of tablets, smartphones and other mobile devices to view and record information anytime and anywhere. As a form of POC device, again a LIS must be able to store and manage the data it receives from mobile devices. Mobile health is encouraging more direct and instant communication between patient and doctor, and a more patient-centric approach. Mobile outreach programs also enable laboratories and phlebotomists to track samples en route, or between sites, and to changes 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 don’t 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.

Originally written by Netlims for InsightsSuccess

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