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Broad feature set of a pathology information management solution

A pathology information management solution (PIMS) ...

• automated reflex testing: Some PIMS vendors include pre-loaded, customizable lists of reflex tests associated with certain pathology procedures and their associated diagnoses. Optimally, these reflex texts are automatically suggested at specimen reception, based on specimen and/or pathology test type. Examples of pathology-driven reflex testing in use today include testing for additional biomarkers for non-small-cell lung carcinoma (NSCLC) adenocarcinoma, HPV testing in addition to cervical cytology examination (discussed further in "adjunctive testing"), and additional automatic testing based off routine coagulation assays at hemostasis labs.

• adjunctive testing: Adjunctive testing is testing "that provides information that adds to or helps interpret the results of other tests, and provides information useful for risk assessment." A common adjunctive test performed in cytopathology is HPV testing. The FDA described this as such in 2003, specifically in regards to expanding the use of the Digene HC2 assay as an adjunct to cytology:

In women 30 years and older, the HC2 High-Risk HPV DNA test can be used with Pap to adjunctively screen to assess the presence or absence of high-risk HPV types. This information, together with the physician’s assessment of cytology history, other risk factors, and professional guidelines, may be used to guide patient management.

Some PIMS vendors allow users to manually add an adjunctive test to a primary pathology test, or in some cases this may be enabled as part of an automated reflex testing process. However, ensure that any such solution is capable of feeding any adjunctive test results into the final report (see the subsection on this topic).

• demand management: Similar to test optimization or clinical decision support, demand management mechanisms help laboratories reduce the amount of unnecessary and duplicate testing they perform. The idea of using demand management to reduce unnecessary pathology testing has been around since at least the beginning of the twenty-first century, if not well before, in the form of decision support systems and order request menus of informatics systems. Lang described what the process of demand management would look like in a system like a laboratory information management system (LIMS) in 2013:

When implementing a demand management tool it is important that the system used to manage a laboratory workload can correctly identify the patient and match requests with the patient’s medical record. Ideally there should be one unique identifier used (e.g., NHS number in the UK), which will allow the LIMS to interrogate the patient’s previous pathology result to allow identification of duplicate or inappropriate requests. If a subsequent request is blocked, then it is also important that there is real-time notification of a potential redundant test so that the requestor can make an informed choice on the clinical need of the test and if it is required to override the rule. It is important that there is a facility whereby the laboratory or requestor can record the reason for blocking a request or overriding the rule.

Today, some PIMS are designed to allow configurable rules and parameters to check for duplicate and unnecessary tests at various levels (e.g., by test ID or catalog type, activity type, or some other order level).

• consent management: In clinical medicine, patients typically must sign a form indicating informed consent to medical treatment. Biobanking facilities, which store biospecimens, also must collect consent forms regarding how a patient's biospecimens may be used. In all cases, these consent documents drive how and when certain actions take place. Though not common, some LIMS like LabVantage Pathology by Software Point provide consent management mechanisms within their PIMS, giving pathologists the ability to quickly verify consent details electronically. In biobanking solutions, this consent management process may be more rigorous to ensure biospecimen donors' preferences and regulatory requirements are being carefully followed. For example, the system may need to be able to prevent further use of a biospecimen and trigger sample and data deletion protocols when a donor withraws their consent to use.

• case management and review: Case history

• speech recognition and transcription management:

• storage and tissue bank management: Biorepositories and pathology laboratories go hand-in-hand. A significant example can be found with the relationship medical school biorepositories have with their pathology labs and departments, as with, for example, Duke University, University of Illinois Chicago, and the Icahn School of Medicine at Mount Sinai. However, even small pathology laboratories must also responsibly store and track their specimens, blocks, and slides, as well as the storage variables affecting them. Any reputable laboratory informatics solution will be able to track the location of such items through barcode or RFID support, as well as allowing for the creation of named storage locations in the system. However, some informatics solutions like AgileBio's LabCollector go a step further, providing data logging modules that are capable of connecting to data logger hardware and other sensors that capture environmental storage information such as temperature, humidity, light level, carbon dioxide level, and pressure. When a variable is out of range, an alert can be sent and logged. And full-fledged biorepository management LIMS may have all the bells and whistles, including randomized biospecimen location auditing.

• task management: Case assignment

• billing management with code support: Support for CPT, ICD-10, SNOMED, etc. codes, auto-generation of those codes based on specimen/slide code, automated billing, user-defined billing rules

• reflex and adjunctive test reporting: Ensure that a PIMS is capable of feeding any adjunctive test results into the final report, along with the results from the primary tests. Using adjunctive HPV test results as an example, the report should optimally include details such as assay name, manufacturer, the HPV types it covers, results, and any applicable educational notes and suggestions. Be careful with simple color-coding of results for interpretation, as they can be easily misinterpreted, including by the colorblind. A combination of symbol with color will help limit such misinterpretation.

• correlation reporting:

• structured data entry: The concept of structured data entry (SDE) is relatively simple, but it may still get taken for granted. At its core, SDE is all about ensuring that entered data is based on a set of predefined conditions or rules, usually implemented through standardized forms with pre-determined drop-down and auto-populated fields. This typically confers numerous advantages, including easier data entry, easier and more standardized reporting, decrease costs, improve translational research, and ensure better compatibility and integration across different information systems. As such, some PIMS vendors like NovoPath and Orchard Software describe their solutions as having SDE elements such as enabling intelligent auto-loading of diagnosis and billing codes during case loading, allowing input fields to be required, and synoptic reporting support.

• synoptic reporting:

• consultive reporting:

• CAP Cancer Reporting Protocol support:

• annotated organ mapping:

• stain panel and unstained/control slide support:

• grossing support:

• testing protocol and workflow design:

• high-risk patient follow-up:

• research animal support: