SafeTrace Tx®
Transfusion Management Software System

Designed by blood bank experts – just like you Request Information

As a transfusion management system designed by experienced blood bankers, the SafeTrace Tx Software was built with patient safety in mind and works the way you do. Its patented safety and multi-facility features help protect patients and guard against mistakes while robust interfaces enable seamless data exchange across the hospital network.

Continuously updated to meet the needs of our customers, markets and regulations, the SafeTrace Tx Software is the transfusion management system-of-choice for hundreds of hospitals, including 6 of the top 10 hospitals in the US.1

Powered by the latest technologies and standards

SafeTrace Tx Software now features a sleek new look and enhanced user experience. This premier Transfusion Management Software Solution includes:

  • Browser-based platform with user friendly Blood Bank centric workflows
  • Straightforward, easy-to-enforce safety and compatibility checks
  • Patented Patient-at-a-Glance Bar® to access all patient details on one screen2
  • Complete patient testing and transfusion history for continuity-of-care across locations
  • Integration with BloodTrack® Software for closed-loop transfusion safety
  • Link to InstaMatch® Software to find and reserve the best-matched platelet product

Elevate transfusion safety with proven integration

Using an open architecture and the latest HL7® standards, the SafeTrace Tx Transfusion Management Software seamlessly exchanges data with Electronic Medical Record (EMR) systems, lab systems, positive patient ID (PPID) systems, bedside transfusion administration systems, BloodTrack® Software and instruments from a wide range of suppliers. We have over a decade of experience interfacing with hospital information system (HIS) providers including: Allscripts®, Cerner®, Epic®, Meditech®, SCC Soft®, Sunquest® and more.

If your hospital is using Epic or another hospital information system, then SafeTrace Tx should be your preferred Transfusion Management System.

InstaMatch®
Product Matching and Reservation Software

InstaMatch Software helps clinicians select the best-matched platelet product for a patient, based upon a grade and site-configurable compatibility score, using a patient’s HLA-type, blood attributes and special needs, and reserve it in SafeTrace Tx.

InstaMatch automates your searching, matching and reservation process, providing a consistent matching approach and streamlined record-keeping and audit history.

Click here to learn more about our SafeTrace Tx Software.

Request Information

Resources

References

  • Brad Johnston, J and Kinney, S . (2019), Autoverification in a Pediatric Transfusion Service. Transfusion. Sep. 2019,59:S3. AABB Abstract P-TS-58. .
  • Bahr, T.M., DuPont, T.L., Christensen, T.R., Rees, T., O'Brien, E.A., Ilstrup, S.J. and Christensen, R.D.. (2019), Evaluating emergency‐release blood transfusion of newborn infants at the Intermountain Healthcare hospitals. Transfusion, 59: 3113-3119. doi: 10.1111/trf.15495.
  • Cushing, M.M., DeSimone, R.A., Goel, R., Hsu, Y.‐M.S., Parra, P., Racine‐Brzostek, S.E., Degtyaryova, D., Lo, D.T., Morrison, M., Crowley, K.M., Rossi, A. and Vasovic, L.V. . (2019), The impact of Daratumumab on transfusion service costs. Transfusion, 59: 1252-1258. doi: 10.1111/trf.15134.
  • Tsang, H.C., Garcia, A., Scott, R., Lancaster, D., Geary, D., Nguyen, A.‐T., Shankar, R., Buchanan, L. and Pham, T.D.. (2018), Streamlining a blood center and hospital transfusion service supply chain with an informatics vendor‐managed inventory solution: development, implementation, and 3‐month follow‐up. Transfusion, 58: 1718-1725. doi: 10.1111/trf.14766.
  • Staples, S., Staves, J., Davies, J., Polley, N., Boyd, J.S., Lukas, M., Popovsky, M.A., Frank, S.M., Ness, P.M. and Murphy, M.F. . (2019), Electronic remote blood issue supports efficient and timely supply of blood and cost reduction: evidence from five hospitals at different stages of implementation. Transfusion, 59: 1683-1691. doi: 10.1111/trf.15231.
  • Badjie KS, Rogers JC, Jenkins SM, Bundy KL, Stubbs JR, Cima RR.. (2015), Safe transition to surgery: working differently to make blood transfusion process safer for elective surgery. Transfusion. 2015 Apr 9. doi: 10.1111/trf.13108. [Epub ahead of print]..
  • Lin DM, Goldfinger D, Lu Q, Wallace B, Kosaka-Nguyen D, Wood A, Porter B, Bumerts P, Jeffery R, Fang A, Stalcup I, Penaflorida T, Ziman A. . (2014), Measuring trade-offs that matter: assessing the impact of a new electronic cross-match policy on the turnaround time and the cross-match workload efficiency. Transfusion. 2014 Dec;54(12):3075-9. doi: 10.1111/trf.12725. Epub 2014 May 27..
  • Shafi H, Abumuhor I, Klapper E. . (2014), How we incorporate molecular typing of donors and patients into our hospital transfusion service. Transfusion. 2014 May;54(5):1212-9. doi: 10.1111/trf.12582. Epub 2014 Mar 13..
  • Harm SK, Yazer MH, Monis GF, Triulzi DJ, Aubuchon JP, Delaney M.. (2014), A Centralized Recipient Database Enhances the Serologic Safety of RBC Transfusions for Patients With Sickle Cell Disease. Am J Clin Pathol. 2014 Feb;141(2):256-61. doi: 10.1309/AJCP47QAAXTOZEKJ..
  • Delaney M, Dinwiddie S, Nester TN, Aubuchon JA. . (2013), The immunohematologic and patient safety benefits of a centralized transfusion database. Transfusion. 2013 Apr;53(4):771-6. doi: 10.1111/j.1537-2995.2012.03789.x. Epub 2012 Jul 15..
  • MacIvor D, Triulzi DJ, Yazer MH.. (2009), Enhanced detection of blood bank sample collection errors with a centralized patient database. Transfusion. 2009 Jan;49(1):40-3. doi: 10.1111/j.1537-2995.2008.01923.x. Epub 2008 Sep 16..
  • DeSimone, R.A., Nowak, M.D., Lo, D.T., Crowley, K.M., Parra, P., Cushing, M.M. and Hsu, Y.‐M.S.. (2018), Logistical and safety implications of temperature‐based acceptance of returned red blood cell units. Transfusion, 58: 1500-1505. doi:10.1111/trf.14615
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  • Lin DM, Goldfinger D, Lu Q, Wallace B, Kosaka-Nguyen D, Wood A, Porter B, Bumerts P, Jeffery R, Fang A, Stalcup I, Penaflorida T, Ziman A. . (2014), Measuring trade-offs that matter: assessing the impact of a new electronic cross-match policy on the turnaround time and the cross-match workload efficiency.  Transfusion. 2014 Dec;54(12):3075-9. doi: 10.1111/trf.12725. Epub 2014 May 27.
    .
  • Bahr, T.M., DuPont, T.L., Christensen, T.R., Rees, T., O'Brien, E.A., Ilstrup, S.J. and Christensen, R.D.. Evaluating emergency‐release blood transfusion of newborn infants at the Intermountain Healthcare hospitals. Transfusion, 59: 3113-3119. doi:
    .
  • Johnston B, Kinney S . (2019) Autoverification in a Pediatric Transfusion Service. Transfusion, Oct. 2019,59: 111A. AABB Abstract P-TS-38
    .
  • Forest S., Shirazi M., Wu-Gall C., Stotler B. . (2017) The Impact of an Electronic Ordering System on Blood Bank Specimen Rejection Rates, American Journal of Clinical Pathology. 147:105–109, https://doi.org/10.1093/ajcp/aqw204
    .
  • Hulse, W., Bahr, T.M., Morris, D.S., Richards, D.S., Ilstrup, S.J. and Christensen, R.D. . (2020), Emergency‐release blood transfusions after postpartum hemorrhage at the Intermountain Healthcare hospitals. Transfusion, 60: 1418-1423. doi:10.1111/trf.15903
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  • Tan BT, Fralick J, Flores W, et al.. Implementation of Epic Beaker Clinical Pathology at Stanford University Medical Center. Am J Clin Pathol. 2017;147(3):261-272. doi:10.1093/ajcp/aqw221
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  • Royal Bournemouth Hospital. (2012), NHS Blood and Transplant pilot scheme comes to Royal Bournemouth Hospital. Press Release: Royal Bournemouth Hospital. 2012 Nov 15.
  • Malvik, N., Leon, J., Schlueter, A.J., Wu, C. and Knudson, C.M. . (2020), ABO‐incompatible platelets are associated with increased transfusion reaction rates. Transfusion, 60: 285-293. doi:10.1111/trf.15655
    .
  • Tsang, H.C., Garcia, A., Scott, R., Lancaster, D., Geary, D., Nguyen, A.‐T., Shankar, R., Buchanan, L. and Pham, T.D. . (2018), Streamlining a blood center and hospital transfusion service supply chain with an informatics vendor‐managed inventory solution: https://pubmed.ncbi.nlm.nih.gov/19437613/.
  • Staves J, Davies A, Kay J, Pearson O, Johnson T, Murphy MF. (2008), Electronic remote blood issue: a combination of remote blood issue with a system for end-to-end electronic control of transfusion to provide a "total solution" for a safe and timely hospital blood transfusion service. Transfusion. 2008 Mar;48(3):415-24. Epub 2007 Dec 7.
  • Davies A, Staves J, Kay J, Casbard A, Murphy MF. (2006), End-to-end electronic control of the hospital transfusion process to increase the safety of blood transfusion: strengths and weaknesses. Transfusion. 2006 Mar;46(3):352-64.
  • Virk, M.S., Lancaster, D., Quach, T., Lim, A., Shu, E., Belanger, G. and Pham, T.D.. (2020), Optimizing O-negative RBC utilization using a data-driven approach. Transfusion, 60: 739-746. doi:10.1111/trf.15713
    .
  • Cushing, M.M., DeSimone, R.A., Goel, R., Hsu, Y.‐M.S., Parra, P., Racine‐Brzostek, S.E., Degtyaryova, D., Lo, D.T., Morrison, M., Crowley, K.M., Rossi, A. and Vasovic, L.V.. (2019), The impact of Daratumumab on transfusion service costs. Transfusion, 59: 1
    .

Notes

1 According to U.S. News & World Report: Best Hospitals 2018-19 Honor Roll.
2 US Patent #7363167, 8229675.
HL7 is a trademark of Health Level Seven International, Inc.
Epic is a trademark of Epic Systems Corporation.
AllScripts is a trademark of AllScripts.
Cerner is a trademark of Cerner Industries, Inc.
Meditech is a trademark of Meditech, LLC.
SCC Soft is a trademark of SCC Soft.
Sunquest is a trademark of Sunquest Information Systems.