The Newfoundland and Labrador Geriatric Health Index (NLGHI): Design, Implementation, and Clinical Workflow-Oriented Features for Community Geriatrics
DOI:
https://doi.org/10.52609/jmlph.v6i2.266Abstract
Background: Primary care and community-based settings often face time limitations that make detailed, repeatable geriatric assessment difficult. There is a need for a practical, clinic-oriented tool that supports longitudinal tracking while remaining easy to interpret, transparent, and straightforward to use in routine workflows.
Aims: This paper introduces NLGHI, a desktop-based application designed to support structured multi-domain data entry, automated composite scoring, longitudinal visualization, rapid report generation, and basic administrative functions within a single system.
Methods: The application was developed in Python using a Qt-based interface, with established libraries such as NumPy and Matplotlib supporting computation and visualization. It records impairment levels across 27 predefined clinical and social domains and calculates a normalized composite score for each visit based on fixed weightings. Data are stored locally in JSON format to allow portability and direct inspection without dependence on external systems. Additional components include a symptom-lexicon module for advisory input and a patient workspace that supports notes, attachments, follow-ups, and timeline exports.
Results: Implementation produces consistent scoring outputs and clear visual summaries, including trend graphs, across visits. Reports can be generated quickly, and patient records remain auditable within a single workstation. Basic validation checks help identify inconsistencies during data entry, while dashboards allow clinicians to review longitudinal changes without requiring server infrastructure.
Conclusion: NLGHI offers a transparent and adaptable approach to geriatric data capture in small-scale clinical environments. It is intended to complement, rather than replace, established tools such as the Clinical Frailty Scale, Charlson and Elixhauser indices, and the Katz ADL, providing a practical option for ongoing monitoring in primary care and community settings.
References
Nightingale G, Burhenn PS, Puts M, Stolz-Baskett P, Haase KR, Sattar S, et al. Integrating nurses and allied health professionals in the care of older adults with cancer: a report from the International Society of Geriatric Oncology Nursing and Allied Health Interest Group. J Geriatr Oncol. 2020;11(2):187-190. doi:10.1016/j.jgo.2019.06.012.
Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, et al. Array programming with NumPy. Nature. 2020;585:357-362. doi:10.1038/s41586-020-2649-2.
Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods. 2020;17(3):261-272. doi:10.1038/s41592-019-0686-2.
Hunter JD. Matplotlib: a 2D graphics environment. Comput Sci Eng. 2007;9(3):90-95. doi:10.1109/MCSE.2007.55.
Bray T. The JavaScript object notation (JSON) data interchange format. RFC 8259. RFC Editor; 2017. doi:10.17487/RFC8259.
Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173(5):489-495. doi:10.1503/cmaj.050051.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8.
Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. doi:10.1097/00005650-199801000-00004.
Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The Index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185(12):914-919. doi:10.1001/jama.1963.03060120024016.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Mirza Niaz Zaman Elin
This work is licensed under a Creative Commons Attribution 4.0 International License.
The Creative Commons Attribution 4.0 International License (CC BY 4.0) is a flexible and commonly used license that allows others to share, remix, adapt, and build upon the work even for commercial purposes, as long as they follow the requirements outlined by the license.
