BK251188 · MAK-SYSTEM Group Ltd. London United Kingdom · MMH · Jun 11, 2025 · Hematology
Device Facts
Record ID
BK251188
Device Name
Patient Health Software (P.H.S) v11.0.0.0
Applicant
MAK-SYSTEM Group Ltd. London United Kingdom
Product Code
MMH · Hematology
Decision Date
Jun 11, 2025
Decision
SESE
Regulation
21 CFR 864.9165
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The eTraceLine / Patient Health Software (P.H.S) application is a modular, stand-alone blood transfusion, testing laboratory software dedicated to blood centers or community blood banks with transfusion services centers, hospitals transfusion services, reference labs, testing laboratories. eTraceLine/P.H.S is designed to aid and assist qualified and trained personnel to support the operations within their facilities. eTraceLine/P.H.S software supports single, centralized multi-sites and multi-organizations to be used centrally or in standalone. eTraceLine/P.H.S undertakes process controls for laboratory testing and transfusion service operations, manages, tracks and determines the suitability of the blood components and blood derivatives to reduce human error and contribute to patient safety. eTraceLine/P.H.S is intended to address all phases of laboratory activities and/or transfusion services operations at the laboratory department, transfusion service departments, hospital wards, and patient bedside. Functionality is provided for: - Patient identification at bedside and patient record management; - Supporting Patient immunohematology, virology, histocompatibility laboratory testing used for suitability and including reagent quality control; - Supporting HLA, HNA, and HPA laboratory testing; - Blood components preparation, release, and labelling (ISBT 128); - Blood components selection, testing, and issue of blood components under normal and emergency conditions, including serological crossmatch, electronic crossmatch, and remote crossmatch of blood components; - Tracking of blood components inventory, transformation, disposition, record transfusion details and related outcomes, and record-keeping of patient transfusion history for lookback; - Supporting therapeutic bleed orders. eTraceLine/P.H.S interfaces with Hospital Information Systems (HIS), laboratory testing instruments, BECS, Laboratory Information Systems (LIS), and blood storage devices.
Device Story
P.H.S is a modular, stand-alone software system for blood transfusion and laboratory testing management. It integrates with HIS, LIS, and laboratory instruments to manage patient records, immunohematology/virology/histocompatibility testing, blood component inventory, and transfusion tracking. Operated by trained personnel in clinical and laboratory settings, it supports bedside patient identification and electronic crossmatching. The system aids in reducing human error by automating process controls and tracking blood component suitability. It functions as a centralized or standalone platform, supporting multi-site operations via web-based architecture. Output includes test results, inventory status, and transfusion records, which assist clinicians in blood component selection and transfusion decision-making, ultimately enhancing patient safety.
Clinical Evidence
No clinical testing was performed. Evidence consists of software verification and validation, including Alpha and Beta (user site) testing to demonstrate performance under specified use conditions.
Technological Characteristics
Modular, stand-alone software using JAVA technology and 3-tier web architecture. Supports on-premise and cloud deployment. Interfaces with HIS, LIS, and laboratory instruments via standard network connections. Complies with ISBT 128 labeling standards. Software classification: Blood Establishment Computer Software (Enhanced Documentation).
Indications for Use
Indicated for use by qualified personnel in blood centers, community blood banks, hospital transfusion services, reference labs, and testing laboratories to manage laboratory testing, transfusion operations, blood component inventory, and patient transfusion history.
Regulatory Classification
Identification
Blood establishment computer software (BECS) is a device used in the manufacture of blood and blood components to assist in the prevention of disease in humans by identifying ineligible donors, by preventing the release of unsuitable blood and blood components for transfusion or for further manufacturing into products for human treatment or diagnosis, by performing compatibility testing between donor and recipient, or by performing positive identification of patients and blood components at the point of transfusion to prevent transfusion reactions. This generic type of device may include a BECS accessory, a device intended for use with BECS to augment the performance of the BECS or to expand or modify its indications for use.
Special Controls
*Classification.* Class II (special controls). The special controls for these devices are:(1) Software performance and functional requirements including detailed design specifications (
*e.g.,* algorithms or control characteristics, alarms, device limitations, and safety requirements).(2) Verification and validation testing and hazard analysis must be performed.
(3) Labeling must include:
(i) Software limitations;
(ii) Unresolved anomalies, annotated with an explanation of the impact on safety or effectiveness;
(iii) Revision history; and
(iv) Hardware and peripheral specifications.
(4) Traceability matrix must be performed.
(5) Performance testing to ensure the safety and effectiveness of the system must be performed, including when adding new functional requirements (
*e.g.,* electrical safety, electromagnetic compatibility, or wireless coexistence).
Predicate Devices
Patient Health Software (P.H.S) Version 2.0 (BK180232)
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
