507
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 332-356 | Received 28 Mar 2021, Accepted 24 Jan 2023, Published online: 16 Feb 2023

References

  • Abernathy, W. J., & Hershey, J. C. (1972). A spatial-allocation model for regional health- services planning. Operations Research, 20(3), 629–642. https://doi.org/10.1287/opre.20.3.629
  • Ahmadi-Javid, A., & Ramshe, N. (2020). A stochastic location model for designing primary healthcare networks integrated with workforce cross-training. Operations Research for Health Care, 24, 100226. https://doi.org/10.1016/j.orhc.2019.100226
  • Altschuler, J., Margolius, D., Bodenheimer, T., & Grumbach, K. (2012). Estimating a reasonable patient panel size for primary care physicians with team-based task delegation. Annals of Family Medicine, 10(5), 396–400. https://doi.org/10.1370/afm.1400
  • Baum, M. A., Bergwall, D. F., & Reeves, P. N. (1975). Planning health care delivery systems. American Journal of Public Health, 65(3), 272–279. https://doi.org/10.2105/AJPH.65.3.272
  • Brabyn, L., & Skelly, C. (2002). Modeling population access to New Zealand public hospitals. International Journal of Health Geographics, 1(1), 1–9. https://doi.org/10.1186/1476-072X-1-3
  • Bullen, N., Moon, G., & Jones, K. (1996). Defining localities for health planning: A GIS approach. Social Science & Medicine, 42(6), 801–816. http://www.sciencedirect.com/science/article/pii/0277953695001808
  • Butler, D. C., Petterson, S., Bazemore, A., & Douglas, K. A. (2010). Use of measures of socioeconomic deprivation in planning primary health care workforce and defining health care need in australia. The Australian Journal of Rural Health, 18(5), 199–204. https://doi.org/10.1111/j.1440-1584.2010.01154.x
  • Cao, K., Batty, M., Huang, B., Liu, Y., Yu, L., & Chen, J. (2011). Spatial multi-objective land use optimization: Extensions to the non-dominated sorting genetic algorithm-ii. International Journal of Geographical Information Science, 25(12), 1949–1969. https://doi.org/10.1080/13658816.2011.570269
  • Caparros-Midwood, D., Barr, S., & Dawson, R. (2017). Spatial optimization of future urban development with regards to climate risk and sustainability objectives. Risk Analysis, 37(11), 2164–2181. https://doi.org/10.1111/risa.12777
  • Casalino, L. P., Devers, K. J., Lake, T. K., Reed, M., & Stoddard, J. J. (2003). Benefits of and barriers to large medical group practice in the United States. Archives of Internal Medicine, 163(16), 1958–1964. https://doi.org/10.1001/archinte.163.16.1958
  • Church, R. L. (2002). Geographical information systems and location science. Computers & Operations Research, 29(6), 541–562. http://www.sciencedirect.com/science/article/pii/S0305054899001045
  • Crooks, V. A., & Schuurman, N. (2012). Interpreting the results of a modified gravity model: Examining access to primary health care physicians in five Canadian provinces and territories. BMC Health Services Research, 12(1), 1–13. https://doi.org/10.1186/1472-6963-12-230
  • Dahrouge, S., Hogg, W., Younger, J., Muggah, E., Russell, G., & Glazier, R. H. (2016). Primary care physician panel size and quality of care: A population-based study in Ontario, Canada. Annals of Family Medicine, 14(1), 26–33. https://doi.org/10.1370/afm.1864
  • Daskin, M. S., & Dean, L. K. (2005). Location of health care facilities. In Margaret, Brandeau, François, Sainfort, William, Pierskalla (Eds.), Operations Research and Health Care A Handbook of Methods and Applications. International Series in Operations Research & Management Science (pp. 43–76). New York: Springer.
  • Duckett, S., Breadon, P., & Ginnivan, L. (2013). Access all areas: New solutions for gp shortages in rural australia (Tech. Rep).
  • Elkabalawy, M., & Al-Sakkaf, A. (2021). Decision support NSGA-ii optimization method for resource-constrained schedule compression with allowed activity splitting. Journal of Physics: Conference Series. In (Vol. 1900, p. 012016).
  • Exeter, D. J., Zhao, J., Crengle, S., Lee, A., & Browne, M. (2017). The New Zealand indices of multiple deprivation (imd): A new suite of indicators for social and health research in Aotearoa, New zealand. Plos One, 12(8), e0181260. https://doi.org/10.1371/journal.pone.0181260
  • Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7), 1689–1709. http://www.sciencedirect.com/science/article/pii/S0307904X09003242
  • Foley, R. (2002). Assessing the applicability of GIS in a health and social care setting: Planning services for informal carers in East Sussex, England. Social Science & Medicine, 55(1), 79–96. https://doi.org/10.1016/S0277-9536(01)00208-8
  • Foley, R., & Darby, N. (2002). Placing the practice: GP service location planning using GIS in Brighton & Hove. In Geohealth 2002. December 3-5th 2022. Victoria University of Wellington.
  • Goodyear-Smith, F., & Janes, R. (2008). New Zealand rural primary health care workforce in 2005: More than just a doctor shortage. The Australian Journal of Rural Health, 16(1), 40–46. https://doi.org/10.1111/j.1440-1584.2007.00949.x
  • Gordon, A., & Womersley, J. (1997). The use of mapping in public health and planning health services. Journal of Public Health, 19(2), 139–147. https://doi.org/10.1093/oxfordjournals.pubmed.a024601
  • Graber-Naidich, A., Carter, M. W., & Verter, V. (2015). Primary care network development: The regulator’s perspective. The Journal of the Operational Research Society, 66(9), 1519–1532. https://doi.org/10.1057/jors.2014.119
  • Griffin, P. M., Scherrer, C. R., & Swann, J. L. (2008). Optimization of community health center locations and service offerings with statistical need estimation. IIE Transactions, 40(9), 880–892. https://doi.org/10.1080/07408170802165864
  • Guagliardo, M. F. (2004). Spatial accessibility of primary care: Concepts, methods and challenges. International Journal of Health Geographics, 3(1), 3. https://doi.org/10.1186/1476-072X-3-3
  • Güneş, E. D., Melo, T., & Nickel, S. (2019). Location problems in healthcare. In Gilbert, Laporte, Stefan, Nickel, Francisco, Saldanha-da-Gama (Eds.), Location science (pp. 657–686). Springer.
  • Güneş, E. D., Yaman, H., Çekyay, B., & Verter, V. (2014). Matching patient and physician preferences in designing a primary care facility network. The Journal of the Operational Research Society, 65(4), 483–496. https://doi.org/10.1057/jors.2012.71
  • Hillsman, E. L. (1980). Multiobjective location planning for primary medical services in rural iowa (Tech. Rep.). Oak Ridge National Lab., TN (USA).
  • Hodgson, M. J., Laporte, G., & Semet, F. (1998). A covering tour model for planning mobile health care facilities in Suhum District, Ghana. Journal of Regional Science, 38(4), 621–638. https://doi.org/10.1111/0022-4146.00113
  • Jaeggi, D. M., Parks, G. T., Kipouros, T., & Clarkson, P. J. (2008). The development of a multi-objective tabu search algorithm for continuous optimisation problems. European Journal of Operational Research, 185(3), 1192–1212. https://doi.org/10.1016/j.ejor.2006.06.048
  • Kelly, E., & Stoye, G. (2014). Does gp practice size matter? gp practice size and the quality of primary care (No. R101). IFS Report.
  • Lapierre, S. D., Myrick, J. A., & Russell, G. (1999). The public health care planning problem: A case study using geographic information systems. Journal of Medical Systems, 23(5), 401–417. https://doi.org/10.1023/A:1020585302393
  • Leitch, S., Dovey, S. M., Samaranayaka, A., Reith, D. M., Wallis, K. A., Eggleton, K. S., McMenamin, A. W., Cunningham, W. K., Williamson, M. I., Lillis, S., & Tilyard, M. W. (2018). Characteristics of a stratified random sample of New Zealand general practices. Journal of Primary Health Care, 10(2), 114–124. https://doi.org/10.1071/HC17089
  • Lopane, F. D., Barr, S., James, P., & Dawson, R. (2019). Optimization of resource storage location for managing flood emergencies [Conference Paper]. ICONHIC 2019 Proceedings. https://iconhic.com/2019/2019/10/id-58-f-d-lopane-s-barr-p-james-r-dawson/
  • Luo, W., & Qi, Y. (2009). An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians. Health & Place, 15(4), 1100–1107. https://doi.org/10.1016/j.healthplace.2009.06.002
  • Luo, W., & Wang, F. (2003). Measures of spatial accessibility to health care in a GIS environment: Synthesis and a case study in the Chicago region. Environment and Planning B: Planning & Design, 30(6), 865–884. https://doi.org/10.1068/b29120
  • Mazumdar, S., Bagheri, N., Konings, P., Chong, S., Jalaudin, B., Girosi, F., & McRae, I. (2019). Measuring relationships between doctor densities and patient visits: A dog’s breakfast of small area health geographies. Applied Spatial Analysis and Policy, 12(3), 631–645. https://doi.org/10.1007/s12061-018-9261-y
  • Mazumdar, S., Butler, D., Bagheri, N., Konings, P., Girosi, F., Feng, X., & McRae, I. (2016). How useful are primary care service areas? Evaluating PCSAs as a tool for measuring primary care practitioner access. Applied Geography, 72, 47–54. https://doi.org/10.1016/j.apgeog.2016.05.005
  • Mazumdar, S., Feng, X., Konings, P., McRae, I., & Girosi, F. (2014). A brief report on primary care service area catchment geographies in New South Wales, Australia. International Journal of Health Geographics, 13(1), 38. https://doi.org/10.1186/1476-072X-13-38
  • McGrail, M. R., & Humphreys, J. S. (2009). Measuring spatial accessibility to primary care in rural areas: Improving the effectiveness of the two-step floating catchment area method. Applied Geography, 29(4), 533–541. http://www.sciencedirect.com/science/article/pii/S0143622809000034
  • McGrail, M. R., & Humphreys, J. S. (2015). Spatial access disparities to primary health care in rural and remote australia. Geospatial Health, 10(2), 358. https://doi.org/10.4081/gh.2015.358
  • McLafferty, S. L. (2003). GIS and health care. Annual Review of Public Health, 24(1), 25–42. https://doi.org/10.1146/annurev.publhealth.24.012902.141012
  • Ministry of Health NZ. (2021a). Retrieved January 14, 2021, from https://www.health.govt.nz
  • Ministry of Health NZ. (2021b). Retrieved January 14, 2021, from https://www.health.govt.nz/your-health/services-and-support/health-care-services/visiting-doctor-or-nurse
  • Mitropoulos, P., Mitropoulos, I., & Giannikos, I. (2013). Combining dea with location analysis for the effective consolidation of services in the health sector. Computers & Operations Research, 40(9), 2241–2250. http://www.sciencedirect.com/science/article/pii/S0305054812000202
  • Murad, A. (2004). Creating a GIS application for local health care planning in Saudi Arabia. International Journal of Environmental Health Research, 14(3), 185–199. https://doi.org/10.1080/0960312042000218606
  • Parker, B. R., & Srinivasan, V. (1976). A consumer preference approach to the planning of rural primary health-care facilities. Operations Research, 24(5), 991–1025. https://doi.org/10.1287/opre.24.5.991
  • Rahman, S. -U., & Smith, D. K. (2000). Use of location-allocation models in health service development planning in developing nations. European Journal of Operational Research, 123(3), 437–452. https://doi.org/10.1016/S0377-2217(99)00289-1
  • Raith, A., & Ehrgott, M. (2009, Apr). A comparison of solution strategies for biobjective shortest path problems. Computers & Operations Research, 36(4), 1299–1331. https://doi.org/10.1016/j.cor.2008.02.002
  • Reuter-Oppermann, M., Nickel, S., & Steinhäuser, J. (2019). Operations research meets need related planning: Approaches for locating general practitioners’ practices. Plos One, 14(1), e0208003. https://doi.org/10.1371/journal.pone.0208003
  • Reuter-Oppermann, M., Rockemann, D., & Steinhäuser, J. (2017). A GIS-based decision support system for locating primary care facilities. In S. Za, M. Dra˘goicea, & M. Cavallari (Eds.), Exploring services science (pp. 210–222). Springer International Publishing.
  • Ribeiro, A., & Antunes, A. P. (2002). A GIS-based decision-support tool for public facility planning. Environment and Planning B: Planning & Design, 29(4), 553–569. https://doi.org/10.1068/b1281
  • Rosero-Bixby, L. (2004). Spatial access to health care in Costa Rica and its equity: A GISbased study. Social Science & Medicine, 58(7), 1271–1284. https://doi.org/10.1016/S0277-9536(03)00322-8
  • Schröder, L., Flägel, K., Goetz, K., & Steinhäuser, J. (2018). Mobility concepts and access to health care in a rural district in Germany: A mixed methods approach. BMC Family Practice, 19(1), 47. https://doi.org/10.1186/s12875-018-0733-6
  • Schuurman, N., Berube, M., & Crooks, V. A. (2010). Measuring potential spatial access to primary health care physicians using a modified gravity model. The Canadian Geographer/Le Geographe Canadien, 54(1), 29–45. https://doi.org/10.1111/j.1541-0064.2009.00301.x
  • Scott, K. M., Marwick, J. C., & Crampton, P. R. (2003). Utilization of general practitioner services in New Zealand and its relationship with income, ethnicity and government subsidy. Health Services Management Research, 16(1), 45–55. https://doi.org/10.1258/095148403762539130
  • Shortt, N. K., Moore, A., Coombes, M., & Wymer, C. (2005). Defining regions for locality health care planning: A multidimensional approach. Social Science & Medicine, 60(12), 2715–2727. https://doi.org/10.1016/j.socscimed.2004.11.016
  • Southern Health. (2021). Retrieved January 14, 2021, from https://www.southernhealth.nz
  • Standridge, C. R., Alan, A., Pritsker, B., & Delcher, H. (1978). Issues in the development of a model for planning health manpower. Simulation, 31(1), 9–13. https://doi.org/10.1177/003754977803100102
  • Steiner, M. T. A., Datta, D., Neto, P. J. S., Scarpin, C. T., & Figueira, J. R. (2015). Multi-objective optimization in partitioning the healthcare system of Parana State in Brazil. Omega, 52, 53–64. https://doi.org/10.1016/j.omega.2014.10.005
  • Tien, J. M., & El-Tell, K. (1984). A quasihierarchical location-allocation model for primary health care planning. IEEE Transactions on Systems, Man, and Cybernetics, 3(3), 373–380. https://doi.org/10.1109/TSMC.1984.6313229
  • Verter, V., & Lapierre, S. D. (2002). Location of preventive health care facilities. Annals of Operations Research, 110(1–4), 123–132. https://doi.org/10.1023/A:1020767501233
  • Walsh, S. J., Page, P. H., & Gesler, W. M. (1997). Normative models and healthcare planning: Network-based simulations within a geographic information system environment. Health Services Research, 32(2), 243–260.
  • Worldometer. (2021). Retrieved January 14, 2021, from https://www.worldometers.info/world-population/new-zealand-population/
  • Yanık, S., & Bozkaya, B. (2020). A review of districting problems in health care. In R. Z. RíosMercado (Ed.), Optimal districting and territory design (pp. 31–55). Springer International Publishing.
  • Yin, H., Xiao, Y., Wen, G., & Fang, H. (2017). Design optimization of a new w-beam guardrail for enhanced highway safety performance. Advances in Engineering Software, 112, 154–164. https://doi.org/10.1016/j.advengsoft.2017.05.002
  • Zhang, Y., Berman, O., Marcotte, P., & Verter, V. (2010). A bilevel model for preventive healthcare facility network design with congestion. IIE Transactions, 42(12), 865–880. https://doi.org/10.1080/0740817X.2010.491500
  • Zhang, Y., Berman, O., & Verter, V. (2009). Incorporating congestion in preventive healthcare facility network design. European Journal of Operational Research, 198(3), 922–935. https://doi.org/10.1016/j.ejor.2008.10.037
  • Zhang, Y., Berman, O., & Verter, V. (2012). The impact of client choice on preventive healthcare facility network design. OR spectrum, 34(2), 349–370. https://doi.org/10.1007/s00291-011-0280-1
  • Zhang, W., & Fujimura, S. (2010). Improved vector evaluated genetic algorithm with archive for solving multiobjective pps problem. 2010 International Conference on E-Product E-Service and E-Entertainment Henan, China, 1–4.
  • Zhao, J., Ameratunga, S., Lee, A., Browne, M., & Exeter, D. J. (2019). Developing a new index of rurality for exploring variations in health outcomes in Auckland and northland. Social Indicators Research, 144(2), 955–980. https://doi.org/10.1007/s11205-019-02076-1

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.