Modeling the Impact of Community First Responders

References

• Ata B, Lee D, Sönmez E (2019) Dynamic volunteer staffing in multicrop gleaning operations. Oper. Res. 67(2):295–314.Abstract, Google Scholar
• Bandara D, Mayorga ME, McLay LA (2012) Optimal dispatching strategies for emergency vehicles to increase patient survivability. Inernat. J. Oper. Res. 15(2):195–214.Crossref, Google Scholar
• Barbour AD, Holst L, Janson S (1992) Poisson Approximation. Oxford Studies in Probability, vol. 2 (Clarendon Press, Oxford, UK).Crossref, Google Scholar
• Berdowski J, Berg RA, Tijssen JG, Koster RW (2010) Global incidences of out-of-hospital cardiac arrest and survival rates: Systematic review of 67 prospective studies. Resuscitation 81(11):1479–1487.Crossref, Google Scholar
• Bomze IM, Rinaldi F, Zeffiro D (2020) Active set complexity of the away-step Frank–Wolfe algorithm. SIAM J. Optim. 30(3):2470–2500.Crossref, Google Scholar
• Boutilier JJ, Brooks SC, Janmohamed A, Byers A, Buick JE, Zhan C, Schoellig AP, Cheskes S, Morrison LJ, Chan TCY (2017) Optimizing a drone network to deliver automated external defibrillators. Circulation 135(25):2454–2465.Crossref, Google Scholar
• Boutilier JJ, Chan TCY (2022) Drone network design for cardiac arrest response. Manufacturing Service Oper. Management 24(5):2407–2424.Link, Google Scholar
• Brandweer Amsterdam-Amstelland (2021) Beleidsplan 2021–2024. https://openresearch.amsterdam/image/2021/7/7/eindconcept_vraa_beleidsplan_brandweer.pdf.Google Scholar
• Brooks SC, Simmons G, Worthington H, Bobrow BJ, Morrison LJ (2016) The PulsePoint Respond mobile device application to crowdsource basic life support for patients with out-of-hospital cardiac arrest: Challenges for optimal implementation. Resuscitation 98:20–26.Crossref, Google Scholar
• Chan TC, Demirtas D, Kwon RH (2016) Optimizing the deployment of public access defibrillators. Management Sci. 62(12):3617–3635.Link, Google Scholar
• Chan TC, Shen ZJM, Siddiq A (2018) Robust defibrillator deployment under cardiac arrest location uncertainty via row-and-column generation. Oper. Res. 66(2):358–379.Link, Google Scholar
• Chu J, Leung KB, Snobelen P, Nevils G, Drennan IR, Cheskes S, Chan TC (2021) Machine learning-based dispatch of drone-delivered defibrillators for out-of-hospital cardiac arrest. Resuscitation 162:120–127.Crossref, Google Scholar
• Cont R, Kotlicki A, Xu R (2021) Modelling COVID-19 contagion: Risk assessment and targeted mitigation policies. R. Soc. Open Sci. 8(3):201535.Crossref, Google Scholar
• Daskin M (1983) A maximum expected location model: Formulation, properties and heuristic solution. Transportation Sci. 7:48–70.Link, Google Scholar
• De Maio V, Stiell I, Wells G, Spaite D (2003) Optimal defibrillation for maximum out-of-hospital cardiac arrest survival rates. Ann. Emergency Medicine 42:242–250.Crossref, Google Scholar
• Dicker B, Garrett N, Wong S, McKenzie H, McCarthy J, Jenkin G, Smith T, et al. (2019) Relationship between socioeconomic factors, distribution of public access defibrillators and incidence of out-of-hospital cardiac arrest. Resuscitation 138:53–58.Crossref, Google Scholar
• Erkut E, Ingolfsson A, Erdoğan G (2008) Ambulance location for maximum survival. Naval Res. Logist. 55(1):42–58.Crossref, Google Scholar
• Facebook Data For Good (2021) Colocation maps. Accessed August 24, 2021, https://dataforgood.facebook.com/dfg/tools/colocation-maps.Google Scholar
• Folke F, Lippert FK, Nielsen SL, Gislason GH, Hansen ML, Schramm TK, Sørensen R, et al. (2009) Clinical perspective. Circulation 120(6):510–517.Crossref, Google Scholar
• Global Resuscitation Alliance (2019) GoodSAM—A smart phone application to crowdsource CPR in New Zealand. Accessed June 6, 2023, https://www.globalresuscitationalliance.org/wp-content/uploads/2019/12/St_John_NZ_Smart_Tech.pdf.Google Scholar
• GoodSAM Platform (2020) GoodSAM. Accessed February 29, 2020, https://www.goodsamapp.org/.Google Scholar
• HartslagNu (2020) HartslagNu. Accessed December 14, 2020, https://hartslagnu.nl/.Google Scholar
• Henderson SG, Berg PL, Jagtenberg CJ, Li H (2022) How should volunteers be dispatched to out-of-hospital cardiac arrest cases? Queueing Systems 100:437–439.Crossref, Google Scholar
• Jansma T (2014) Extending the emergency medical services network for out-of-hospital cardiac arrest victims: An explorative study for the province of Drenthe. Master’s thesis, University of Groningen, Groningen, Netherlands.Google Scholar
• Johari R, Kamble V, Kanoria Y (2021) Matching while learning. Oper. Res. 69(2):655–681.Link, Google Scholar
• Kingman JFC (1993) Poisson Processes (Oxford University Press, Oxford, UK).Google Scholar
• Larson RC, Odoni AR (1981) Urban Operations Research (Prentice Hall, Englewood Cliffs, NJ).Google Scholar
• Liu W, Sun Q, Ching Tang L, Ye Z (2022) Robust data-driven design of a smart cardiac arrest response system. Preprint, submitted October 2, http://dx.doi.org/10.2139/ssrn.4590433.Google Scholar
• Lives. Emergency responders. Accessed October 24, 2022, https://www.lives.org.uk/what-we-do/emergency-responders/.Google Scholar
• Manshadi V, Rodilitz S (2022) Online policies for efficient volunteer crowdsourcing. Management Sci. 68(9):6572–6590.Link, Google Scholar
• Matinrad N, Granberg TA, Angelakis V (2021) Modeling uncertain task compliance in dispatch of volunteers to out-of-hospital cardiac arrest patients. Comput. Indust. Engrg. 159:107515.Crossref, Google Scholar
• Matinrad N, Granberg T, Ennab Vogel N, Angelakis V (2019) Optimal dispatch of volunteers to out-of-hospital cardiac arrest patients. Proc. 52nd Hawaii Internat. Conf. System Sci. (Association for Information Systems, Atlanta), 4088–4097.Google Scholar
• McElfresh DC, Kroer C, Pupyrev S, Sodomka E, Sankararaman KA, Chauvin Z, Dexter N, Dickerson JP (2020) Matching algorithms for blood donation. Proc. 21st ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 463–464.Google Scholar
• McLay LA (2009) Emergency medical service systems that improve patient survivability. Cochran JJ, Cox LA, Keskinocak P, Kharoufeh JP, Smith JC, eds. Wiley Encyclopedia of Operations Research and Management Science (John Wiley & Sons, Hoboken, NJ).Google Scholar
• Ministry of Health (2020) Emergency ambulance service national performance report. Accessed May 12, 2021, https://www.health.govt.nz/system/files/documents/pages/naso-march-report-2019-2020.pdf.Google Scholar
• Nazarian A (2018) Optimizing the deployment of automated external defibrillators by a data-driven algorithmic approach. Master’s thesis, University of Twente, Enschede, Netherlands.Google Scholar
• NHS North West Ambulance Service. Community first responders (CFR). Accessed October 24, 2022, https://www.nwas.nhs.uk/get-involved/volunteering/community-first-responder/.Google Scholar
• Nichol G, Stiell IG, Laupacis A, Pham B, De Maio VJ, Wells GA (1999) A cumulative meta-analysis of the effectiveness of defibrillator-capable emergency medical services for victims of out-of-hospital cardiac arrest. Ann. Emergency Medicine 34(4):517–525.Crossref, Google Scholar
• Nisingizwe MP, Ndishimye P, Swaibu K, Nshimiyimana L, Karame P, Dushimiyimana V, Musabyimana JP, Musanabaganwa C, Nsanzimana S, Law MR (2022) Effect of unmanned aerial vehicle (drone) delivery on blood product delivery time and wastage in Rwanda: A retrospective, cross-sectional study and time series analysis. Lancet Global Health 10(4):564–569.Crossref, Google Scholar
• Northern Ireland Ambulance Service Health and Social Care Trust. Community first responder scheme. Accessed April 9, 2024, https://nias.hscni.net/calling-999/who-will-treat-you/first-responders/.Google Scholar
• Oving I, Masterson S, Tjelmeland IB, Jonsson M, Semeraro F, Ringh M, Truhlar A, et al. (2019) First-response treatment after out-of-hospital cardiac arrest: A survey of current practices across 29 countries in Europe. Scandinavian J. Trauma Resuscitation Emergency Medicine 27(1):112.Crossref, Google Scholar
• Özkan E, Ward AR (2020) Dynamic matching for real-time ride sharing. Stochastic Systems 10(1):29–70.Link, Google Scholar
• Phung VH, Trueman I, Togher F, Orner R, Siriwardena AN (2017) Community first responders and responder schemes in the United Kingdom: Systematic scoping review. Scandinavian J. Trauma Resuscitation Emergency Medicine 25(1):58.Crossref, Google Scholar
• Pijls RW, Nelemans PJ, Rahel BM, Gorgels AP (2016) A text message alert system for trained volunteers improves out-of-hospital cardiac arrest survival. Resuscitation 105:182–187.Crossref, Google Scholar
• Pijls RW, Nelemans PJ, Rahel BM, Gorgels AP (2019) Characteristics of a novel citizen rescue system for out-of-hospital cardiac arrest in the Dutch province of Limburg: Relation to incidence and survival. Netherlands Heart J. 27(2):100–107.Crossref, Google Scholar
• PulsePoint (2020) PulsePoint. Accessed February 29, 2020, https://www.pulsepoint.org/.Google Scholar
• Qin Z, Tang X, Jiao Y, Zhang F, Xu Z, Zhu H, Ye J (2020) Ride-hailing order dispatching at DiDi via reinforcement learning. INFORMS J. Appl. Anal. 50(5):272–286.Link, Google Scholar
• Ridler S (2020) Emergency medical services research at the University of Auckland, Department of Engineering Science. Accessed April 9, 2024, https://github.com/uoa-ems-research.Google Scholar
• Ridler S, Mason AJ, Raith A (2017) A simulation package for emergency medical services. Proc. 51st Annual Conf. ORSNZ (Operations Research Society of New Zealand, Hamilton, New Zealand).Google Scholar
• Ridler S, Mason AJ, Raith A (2022) A simulation and optimisation package for emergency medical services. Eur. J. Oper. Res. 298(3):1101–1113.Crossref, Google Scholar
• Ringh M, Fredman D, Nordberg P, Stark T, Hollenberg J (2011) Mobile phone technology identifies and recruits trained citizens to perform CPR on out-of-hospital cardiac arrest victims prior to ambulance arrival. Resuscitation 82(12):1514–1518.Crossref, Google Scholar
• Safegraph (2021) Safegraph. Accessed March 14, 2023, https://www.safegraph.com/.Google Scholar
• Sasson C, Rogers MA, Dahl J, Kellermann AL (2010) Predictors of survival from out-of-hospital cardiac arrest: A systematic review and meta-analysis. Circulation Cardiovascular Quality Outcomes 3(1):63–81.Crossref, Google Scholar
• Serfling RJ (1980) Approximation Theorems of Mathematical Statistics. Wiley Series in Probability and Mathematical Statistics (Wiley, New York).Crossref, Google Scholar
• Shin J, Marla L, Boutilier JJ (2022) Heterogeneous facility location under coordination and collaboration: The case of ambulance-bystander-drone coordination. Preprint, submitted June 6, https://ssrn.com/abstract=3519243.Google Scholar
• Slaa G (2020) Increasing cardiac arrest survival by improving the volunteer alerting algorithm. Accessed November 30, 2023, http://essay.utwente.nl/80432/.Google Scholar
• Smith CM, Wilson MH, Ghorbangholi A, Hartley-Sharpe C, Gwinnutt C, Dicker B, Perkins GD (2017) The use of trained volunteers in the response to out-of-hospital cardiac arrest–The GoodSAM experience. Resuscitation 121:123–126.Crossref, Google Scholar
• Stats New Zealand Geographic Data Service (2015) Age by meshblock (2013 census). Accessed October 25, 2021, https://datafinder.stats.govt.nz/layer/8447-age-by-meshblock-2013-census/.Google Scholar
• Stats New Zealand Geographic Data Service (2016) Area units 2013. Accessed October 28, 2020, https://datafinder.stats.govt.nz/layer/25743-area-unit-2013/.Google Scholar
• Stats New Zealand Geographic Data Service (2020) 2018 census main means of travel to work by statistical area 2. Accessed October 25, 2021, https://datafinder.stats.govt.nz/table/104720-2018-census-main-means-of-travel-to-work-by-statistical-area-2/.Google Scholar
• Stieglis R, Zijlstra JA, Riedijk F, Smeekes M, van der Worp WE, Koster RW (2020) AED and text message responders density in residential areas for rapid response in out-of-hospital cardiac arrest. Resuscitation 150:170–177.Crossref, Google Scholar
• Tafreshian A, Masoud N, Yin Y (2020) Frontiers in service science: Ride matching for peer-to-peer ride sharing: A review and future directions. Service Sci. 12(2–3):44–60.Link, Google Scholar
• Valenzuela TD, Roe DJ, Cretin S, Spaite DW, Larsen MP (1997) Estimating effectiveness of cardiac arrest interventions: A logistic regression survival model. Circulation 96(10):3308–3313.Crossref, Google Scholar
• Waalewijn RA, de Vos R, Tijssen JG, Koster RW (2001) Survival models for out-of-hospital cardiopulmonary resuscitation from the perspectives of the bystander, the first responder, and the paramedic. Resuscitation 51(2):113–122.Crossref, Google Scholar
• Wikipedia (2020) Burgerhulpverlening. Accessed December 14, 2020, https://nl.wikipedia.org/wiki/Burgerhulpverlening.Google Scholar
• Yan S, Gan Y, Jiang N, Wang R, Chen Y, Luo Z, Zong Q, Chen S, Lv C (2020) The global survival rate among adult out-of-hospital cardiac arrest patients who received cardiopulmonary resuscitation: A systematic review and meta-analysis. Critical Care 24(1):61.Crossref, Google Scholar
• Zaffar MA, Rajagopalan HK, Saydam C, Mayorga M, Sharer E (2016) Coverage, survivability or response time: A comparative study of performance statistics used in ambulance location models via simulation optimization. Oper. Res. Health Care 11:1–12.Crossref, Google Scholar
• Zijlstra JA, Stieglis R, Riedijk F, Smeekes M, Van der Worp WE, Koster RW (2014) Local lay rescuers with AEDs, alerted by text messages, contribute to early defibrillation in a Dutch out-of-hospital cardiac arrest dispatch system. Resuscitation 85(11):1444–1449.Crossref, Google Scholar