Locating Parkinson Assessment Services to Reduce Patient Travel: A Reproducible Analysis of Average Cost, Remote Access, and Service Constraints

Abstract

Abstract Travel expenditure can limit access to Parkinson assessment even when the assessment itself carries a modest charge. Service location therefore deserves evaluation alongside the price and technical performance of a test. This study develops a reproducible hypothetical location analysis that separates patient travel from diagnostic performance and total health-system cost. Twelve fictional demand locations and twelve candidate sites are connected by straight-line round-trip distances. Exhaustive enumeration identifies configurations minimizing demand-weighted mean travel, while a second objective minimizes the longest journey. A targeted narrative selection of primary access, telemedicine, economic, and geographical studies informs interpretation of the model. The fixed central-site scenario produces a mean round trip of 11.32 km. Allowing one site to relocate reduces the mean to 9.31 km but increases the longest journey from 24.33 to 32.25 km. Two freely located sites reduce the mean to 5.80 km. A two-site configuration chosen to minimize the longest journey instead has a mean of 8.82 km and a maximum of 15.62 km, illustrating a substantive trade-off between average and remote access. All locations, demand weights, and travel calculations are fictional; no real communities or patients are represented. The analysis shows why an average saving can conceal a worsening journey for a small group and why geographical optimization cannot establish earlier diagnosis, clinical equivalence, or affordability without information on transport, capacity, referral pathways, and household resources. A proposed evaluation framework reports these outcomes separately and makes the service objective explicit before implementation. Article details NeuralCipherai; Kadir Tamrak; Salih Yaldız; Feride Yaldız; Ömer Ağyol; Yavuz Selim Silay; Hasan Randa Hypothetical service-location analysis Exhaustive site enumeration demonstrating that lower average travel can worsen remote access. Project: NeuralCipher. Bibliographic records are supplied in BibTeX and RIS formats for reference-management software, including Zotero. Reproducible calculations and figure data accompany the article. References Beck, C. A., Beran, D. B., Biglan, K. M., Boyd, C. M., Dorsey, E. R., Schmidt, P. N., Simone, R., Willis, A. W., Galifianakis, N. B., Katz, M., Tanner, C. M., Dodenhoff, K., Aldred, J., Carter, J., Fraser, A., Jimenez-Shahed, J., Hunter, C., Spindler, M., Reichwein, S., . . . Zhu, W. (2017). National randomized controlled trial of virtual house calls for Parkinson disease. Neurology, 89(11), 1152-1161. https://doi.org/10.1212/wnl.0000000000004357 Canoro, V., Picillo, M., Cuoco, S., Pellecchia, M. T., Barone, P., & Erro, R. (2024). Development of the Digital Inclusion Questionnaire (DIQUEST) in Parkinson’s Disease. Neurological Sciences, 45(3), 1063-1069. https://doi.org/10.1007/s10072-023-07090-3 Collins, G. S., Moons, K. G. M., Dhiman, P., Riley, R. D., Beam, A. L., Van Calster, B., Ghassemi, M., Liu, X., Reitsma, J. B., van Smeden, M., Boulesteix, A.-L., Camaradou, J. C., Celi, L. A., Denaxas, S., Denniston, A. K., Glocker, B., Golub, R. M., Harvey, H., Heinze, G., . . . Logullo, P. (2024). TRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ, 385, Article e078378. https://doi.org/10.1136/bmj-2023-078378 Crighton, E. J., Ouédraogo, A. M., Sawada, M., & Mestre, T. A. (2024). Patterns and determinants of health care utilization among people with Parkinson’s disease: A population-based analysis in Ontario, Canada. PLOS ONE, 19(6), e0305062. https://doi.org/10.1371/journal.pone.0305062 Dorsey, E. R., Venkataraman, V., Grana, M. J., Bull, M. T., George, B. P., Boyd, C. M., Beck, C. A., Rajan, B., Seidmann, A., & Biglan, K. M. (2013). Randomized Controlled Clinical Trial of “Virtual House Calls” for Parkinson Disease. JAMA Neurology, 70(5), 565. https://doi.org/10.1001/jamaneurol.2013.123 Goh, Z. H. K., Cheong, J. L. Y., Marras, C., Tanner, C. M., Kasten, M., Korczyn, A. D., Chahine, L., Lo, R., Noyce, A. J., & on behalf of the Movement Disorders Society Epidemiology Study Group (2022). Surveying Global Availability of Parkinson’s Disease Treatment. Journal of Parkinson’s Disease, 12(3), 1023-1034. https://doi.org/10.3233/jpd-213006 Jimenez-Shahed, J., Malaty, I. A., Soileau, M., Yan, C. H., Kandukuri, L., Schinkel, J., Teigland, C., Shah, M. B., Kukreja, P., Hambrick, A., & Fernandez, H. H. (2025). Association of patient characteristics, social drivers of health, and geographic location on access to device-aided therapies among medicare beneficiaries with advanced Parkinson's disease. Parkinsonism & Related Disorders, 133, 107322. https://doi.org/10.1016/j.parkreldis.2025.107322 Lu, Y., Sun, Y., Yu, H., Ma, B., Hu, C., Wang, W., Jiang, C., Cai, X., Cui, Z., Chen, L., Chen, W., Chen, L., Chen, Z., Geng, X., Guo, Y., Huang, W., Li, W., Li, D., Ling, Z., . . . Li, L. (2026). Real-world clinical and economic evaluation of remote programming for deep brain stimulation in Parkinson’s disease. Nature Health. https://doi.org/10.1038/s44360-026-00131-z Maclagan, L. C., Emdin, A., Fu, L., Guan, J., de Oliveira, C., Marras, C., & Bronskill, S. E. (2025). Net Health System Costs of Parkinson Disease. Neurology Clinical Practice, 15(1), e200371. https://doi.org/10.1212/cpj.0000000000200371 Mantri, S., & Mitchell, K. T. (2021). Falling down the digital divide: A cautionary tale. Parkinsonism & Related Disorders, 93, 33-34. https://doi.org/10.1016/j.parkreldis.2021.10.032 Mokaya, J., Dotchin, C. L., Gray, W. K., Hooker, J., & Walker, R. W. (2016). The Accessibility of Parkinson's Disease Medication in Kenya: Results of a National Survey. Movement Disorders Clinical Practice, 3(4), 376-381. https://doi.org/10.1002/mdc3.12294 Moons, K. G. M., Damen, J. A. A., Kaul, T., Hooft, L., Andaur Navarro, C., Dhiman, P., Beam, A. L., Van Calster, B., Celi, L. A., Denaxas, S., Denniston, A. K., Ghassemi, M., Heinze, G., Kengne, A. P., Maier-Hein, L., Liu, X., Logullo, P., McCradden, M. D., Liu, N., . . . van Smeden, M. (2025). PROBAST+AI: An updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods. BMJ, 388, Article e082505. https://doi.org/10.1136/bmj-2024-082505 Pearson, C., Hartzman, A., Munevar, D., Feeney, M., Dolhun, R., Todaro, V., Rosenfeld, S., Willis, A., & Beck, J. C. (2023). Care access and utilization among medicare beneficiaries living with Parkinson’s disease. npj Parkinson's Disease, 9(1), 108. https://doi.org/10.1038/s41531-023-00523-y Postuma, R. B., Berg, D., Stern, M., Poewe, W., Olanow, C. W., Oertel, W., Obeso, J., Marek, K., Litvan, I., Lang, A. E., Halliday, G., Goetz, C. G., Gasser, T., Dubois, B., Chan, P., Bloem, B. R., Adler, C. H., & Deuschl, G. (2015). MDS clinical diagnostic criteria for Parkinson's disease. Movement Disorders, 30(12), 1591–1601. https://doi.org/10.1002/mds.26424 Ramadhan, M., Stott, J., & Schrag, A. (2025). The barriers to receiving health care for people with Parkinson’s from predominantly Asian backgrounds in the UK. npj Parkinson's Disease, 11(1), 131. https://doi.org/10.1038/s41531-025-00946-9 Sahar, H., Pintér, D., Pintér, E., Balás, I., Janszky, J., & Kovács, N. (2025). Travel distance may have a negative impact on the outcome of deep brain stimulation in Parkinson’s disease. Scientific Reports, 15(1), 29992. https://doi.org/10.1038/s41598-025-14519-6 Saiyed, M., Hill, A. J., Russell, T. G., Theodoros, D. G., & Scuffham, P. (2022). Cost analysis of home telerehabilitation for speech treatment in people with Parkinson’s disease. Journal of Telemedicine and Telecare, 28(7), 524-529. https://doi.org/10.1177/1357633x20948302 Shivkumar, V., Subramanian, T., Agarwal, P., Mari, Z., & Mestre, T. A. (2021). Uptake of telehealth in Parkinson's disease clinical care and research during the COVID-19 pandemic. Parkinsonism & Related Disorders, 86, 97-100. https://doi.org/10.1016/j.parkreldis.2021.03.032 Theodoros, D. G., Hill, A. J., & Russell, T. G. (2016). Clinical and Quality of Life Outcomes of Speech Treatment for Parkinson's Disease Delivered to the Home Via Telerehabilitation: A Noninferiority Randomized Controlled Trial. American Journal of Speech-Language Pathology, 25(2), 214-232. https://doi.org/10.1044/2015_ajslp-15-0005 Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., Denniston, A. K., Faes, L., Geerts, B., Ibrahim, M., Liu, X., Mateen, B. A., Mathur, P., McCradden, M. D., Morgan, L., Ordish, J., Rogers, C., Saria, S., Ting, D. S. W., . . . the DECIDE-AI expert group. (2022). Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nature Medicine, 28(5), 924–933. https://doi.org/10.1038/s41591-022-01772-9 von Campenhausen, S., Winter, Y., Rodrigues e Silva, A., Sampaio, C., Ruzicka, E., Barone, P., Poewe, W., Guekht, A., Mateus, C., Pfeiffer, K. P., Berger, K., Skoupa, J., Bötzel, K., Geiger-Gritsch, S., Siebert, U., Balzer-Geldsetzer, M., Oertel, W. H., Dodel, R., & Reese, J. P. (2011). Costs of illness and care in Parkinson's Disease: An evaluation in six countries. European Neuropsychopharmacology, 21(2), 180-191. https://doi.org/10.1016/j.euroneuro.2010.08.002 von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & for the STROBE Initiative. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Medicine, 4(10), Article e296. https://doi.org/10.1371/journal.pmed.0040296 Willis, A. W., Schootman, M., Evanoff, B. A., Perlmutter, J. S., & Racette, B. A. (2011). Neurologist care in Parkinson disease. Neurology, 77(9), 851-857. https://doi.org/10.1212/wnl.0b013e31822c9123 Yang, W