Journal:Building a newborn screening information management system from theory to practice

Full article title	Building a newborn screening information management system from theory to practice
Journal	International Journal of Neonatal Screening
Author(s)	Pluscauskas, Michael; Henderson, Matthew; Milburn, Jennifer; Chakraborty, Pranesh
Author affiliation(s)	Children’s Hospital of Eastern Ontario, University of Ottawa
Primary contact	Email: mplus at cheo dot on dot ca
Year published	2019
Volume and issue	5 (1)
Page(s)	9
DOI	10.3390/ijns5010009
ISSN	2409-515X
Distribution license	Creative Commons Attribution 4.0 International
Website	https://www.mdpi.com/2409-515X/5/1/9/htm
Download	https://www.mdpi.com/2409-515X/5/1/9/pdf (PDF)

Abstract

Information management systems are the central process management and communication hub for many newborn screening programs. In late 2014, Newborn Screening Ontario (NSO) undertook an end-to-end assessment of its information management needs, which resulted in a project to develop a flexible information systems (IS) ecosystem and related process changes. This enabled NSO to better manage its current and future workflow and communication needs. An idealized vision of a screening information management system (SIMS) was developed that was refined into enterprise and functional architectures. This was followed by the development of technical specifications, user requirements, and procurement. In undertaking a holistic full product lifecycle redesign approach, a number of change management challenges were faced by NSO across the entire program. Strong leadership support and full program engagement were key for overall project success. It is anticipated that improvements in program flexibility and the ability to innovate will outweigh the efforts and costs.

Keywords: newborn screening, neonatal screening, laboratory information management system, laboratory information system, LIMS, LIS, screening information management

Introduction

Dating back to the early days of computers, a variety of software programs have been utilized to automate numerous laboratory workflows, processes, and related activities. In newborn screening labs, a screening information management system (SIMS)—a set of integrated software components which may or may not be from a single vendor that can be used to automate screening workflows—has become a useful tool for automation. In addition, a SIMS can be used to manage other aspects of overall laboratory management and programmatic aspects, such as case reporting and follow-up.

Population-based newborn screening began appearing in many North American and European countries over 50 years ago. Due to the low number of tests per patient, many programs were initially able to handle their testing and reporting functions using manual workflows, paper-based lab logs, and patient reports. Labs initially employed simple computer functions such as using word processing to create mailing lists/labels and basic reports. Eventually, usage evolved into managing basic lab workflows and quality metrics using standard software such as spreadsheets and databases.

In the late 1990s and early 2000s, the shift to complex equipment such as tandem mass spectrometers (MS/MS), that could test for dozens of target diseases and related follow-ups, necessitated the development of a more complex information technology infrastructure to manage newborn screening programs. This shift required the development of new, often integrated, software programs to manage the new challenges that were created by these changes. Also, a number of new target disorders required very quick turnaround times (TATs) in order to locate infants who were at risk of early decompensation that could cause severe morbidity or even death. This meant that neonatal screening labs required information systems that could process large batches of results quickly in order to ensure that infants who tested positive for these disorders could be identified in a timely manner.

The current shift into new paradigms for newborn screening, including molecular (DNA-based) screening, is pushing the limits of the original software architectural approaches of these integrated packages. The ability of decision support tools such as Collaborative Laboratory Integrated Reports (CLIR) to be linked, potentially in real time via application program interfaces (APIs), also stretches the limits of current SIMS functionality. In addition, the potential of new point-of-care technologies and the possibility of screening for certain time-critical disorders prenatally have stretched these new paradigms even further. As these needs evolve, a more comprehensive information ecosystem approach to newborn screening SIMS architectures will be required to support the expanding needs of newborn screening.

In their paper “The Ideal Laboratory Information System,” Sepulveda and Young described a set of processes and technology modules that they considered key for the development of an “ideal” comprehensive clinical laboratory information system (LIS). An approach to developing an “ideal” SIMS in a newborn screening context is described in this paper. The experiences of Newborn Screening Ontario (NSO) are used to illustrate the various technical and administrative approaches that are involved in undertaking such a project. The potential benefits, impacts, and risks of taking this approach are discussed and key lessons are highlighted.

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In several cases the PubMed ID was missing and was added to make the reference more useful.