The Future of Hospitals: A Systematic Review in the Field of Architectural Design with a Disruptive Research and Development Approach

Authors: María Araya Léon, Ainoa Abella, Aura Murillo, Ricardo Guasch, Laura Clèries

Abstract:

This article aims to examine scientific theory framed within the term hospitals of the future from a multidisciplinary and cross-sectional perspective. To understand the connection that the various cross-sectional areas, we studied have with architectural spaces and to determine the future outlook of the works examined and how they can be classified into the categories of need/solution, evolution/revolution, collective/individual, and preventive/corrective. The changes currently taking place within the context of healthcare demonstrate how important these projects are and the need for companies to face future changes. A systematic review has been carried out focused on what will the hospitals of the future be like in relation to the elements that form part of their use, design, and architectural space experience, using the WOS database from 2016 to 2019. The large number of works about sensoring & big data and the scarce amount related to the area of materials is worth highlighting. Furthermore, no growth concerning future issues is envisaged over time. Regarding classifications, the articles we reviewed address evolutionary and collective solutions more, and in terms of preventive and corrective solutions, they were found at a similar level. Although our research focused on the future of hospitals, there is little evidence representing this approach. We also detected that, given the relevance of the research on how the built environment influences human health and well-being, these studies should be promoted within the context of healthcare. This article allows to find evidence on the future perspective from within the domain of hospital architecture, in order to create bridges between the productive sector of architecture and scientific theory. This will make it possible to detect R&D opportunities in each analyzed cross-section.

Keywords: Hospitals, trends, architectural space, disruptive approach.

References:

[1] Art & Architecture Thesaurus, (n.d.). Retrieved on August 3, 2022, at https://www.aatespanol.cl/
[2] Health Science Descriptor, (n.d). Retrieved on August 3, 2022, at http://decs.bvs.br/E/homepagee.htm
[3] Farmer, J., Bigby, C., Davis, H., Carlisle, K., Kenny, A., & Huysmans, R. (2018). The state of health services partnering with consumers: evidence from an online survey of Australian health services. BMC Health Services Research 2018 18:1, 18(1), 1–13. https://doi.org/10.1186/S12913-018-3433-Y
[4] Okoroh, J. S., Uribe, E. F., & Weingart, S. (2017). Racial and ethnic disparities in patient safety. Journal of Patient Safety, 13(3), 153–161. https://doi.org/10.1097/PTS.0000000000000133
[5] Suarez, T., & Lopez Canto, L. E. (2016). Cultural differences in a public hospital in Mexico. Management Research: The Journal of the Iberoamerican Academy of Management, 14(1), 85–102. https://doi.org/10.1108/MRJIAM-07-2015-0601
[6] Hamadi, H., Moody, L., Apatu, E., Vossos, H., Tafili, A., & Spaulding, A. (2019). Impact of hospitals’ Referral Region racial and ethnic diversity on 30-day readmission rates of older adults. Https://Doi.Org/10.1080/20009666.2019.1613882, 9(3), 181–188.
[7] Valtorta, N. K., Moore, D. C., Barron, L., Stow, D., & Hanratty, B. (2018). Older Adults’ Social Relationships and Health Care Utilization: A Systematic Review. Https://Doi.Org/10.2105/AJPH.2017.304256, 108(4), e1–e10.
[8] Noordman, J., van Vliet, L., Kaunang, M., van den Muijsenbergh, M., Boland, G., & van Dulmen, S. (2019). Towards appropriate information provision for and decision-making with patients with limited health literacy in hospital-based palliative care in Western countries: a scoping review into available communication strategies and tools for healthcare providers. BMC Palliative Care 2019 18:1, 18(1), 1–10. https://doi.org/10.1186/S12904-019-0421-X
[9] Bennett, M., Cartwright, J., & Young, J. (2017). Is the speech-language pathology profession prepared for an ageing population? An Australian survey. Https://Doi.Org/10.1080/17549507.2017.1413135, 21(2), 153–162.
[10] Capozza, D., Falvo, R., & Boin, J. (2016). Dehumanization in medical contexts: an expanding research field. https://doi.org/10.4473/TPM23.4.8
[11] Roe, B., McCormick, S., Lucas, T., Gallagher, W., Winn, A., & Elkin, S. (2014). Coffee, Cake & Culture: Evaluation of an art for health programme for older people in the community: Http://Dx.Doi.Org/10.1177/1471301214528927, 15(4), 539–559.
[12] Threatt, A. L., Merino, J., Brooks, J. O., Healy, S., Truesdail, C., Manganelli, J., Walker, I., & Green, K. E. (2017). The Design, Prototyping, and Formative Evaluation of an Assistive Robotic Table (ART) for Stroke Patients: Https://Doi.Org/10.1177/1937586716687802, 10(3), 152–169.
[13] Shajahan, A., Culp, C. H., & Williamson, B. (2019). Effects of indoor environmental parameters related to building heating, ventilation, and air conditioning systems on patients’ medical outcomes: A review of scientific research on hospital buildings. Indoor Air, 29(2), 161–176. https://doi.org/10.1111/INA.12531
[14] Kipnis, P., Turk, B. J., Wulf, D. A., LaGuardia, J. C., Liu, V., Churpek, M. M., Romero-Brufau, S., & Escobar, G. J. (2016). Development and validation of an electronic medical record-based alert score for detection of inpatient deterioration outside the ICU. Journal of Biomedical Informatics, 64, 10–19. https://doi.org/10.1016/J.JBI.2016.09.013
[15] Ghezeljeh, T. N., Nasari, M., Haghani, H., & Rezaei Loieh, H. (2017). The effect of nature sounds on physiological indicators among patients in the cardiac care unit. Complementary Therapies in Clinical Practice, 29, 147–152. https://doi.org/10.1016/J.CTCP.2017.09.010
[16] Smith, S. W., Ortmann, A. J., & Clark, W. W. (2018). Noise in the Neonatal Intensive Care Unit: A New Approach to Examining Acoustic Events. Noise & Health, 20(95), 121. https://doi.org/10.4103/NAH.NAH_53_17
[17] Willis, V. (2017). The Relationship Between Hospital Construction and High-Risk Infant Auditory Function at NICU Discharge: A Retrospective Descriptive Cohort Study: Https://Doi.Org/10.1177/1937586717742123, 11(2), 124–136.
[18] Sehmi, S. K., Allan, E., MacRobert, A. J., & Parkin, I. (2016). The bactericidal activity of glutaraldehyde-impregnated polyurethane. MicrobiologyOpen, 5(5), 891–897. https://doi.org/10.1002/MBO3.378
[19] Clark, A., Ng, J. Q., Morlet, N., & Semmens, J. B. (2016). Big data and ophthalmic research. Survey of Ophthalmology, 61(4), 443–465. https://doi.org/10.1016/J.SURVOPHTHAL.2016.01.003
[20] Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of Medical Informatics, 114, 57–65. https://doi.org/10.1016/J.IJMEDINF.2018.03.013
[21] Oliver, B. J., Nelson, E. C., & Kerrigan, C. L. (2019). Turning Feed-forward and Feedback Processes on Patient-reported Data into Intelligent Action and Informed Decision-making: Case Studies and Principles. Medical Care, 57, S31–S37. https://doi.org/10.1097/MLR.0000000000001088
[22] Radiya-Dixit, E., Zhu, D., & Beck, A. H. (2017). Automated Classification of Benign and Malignant Proliferative Breast Lesions. Scientific Reports 2017 7:1, 7(1), 1–8. https://doi.org/10.1038/s41598-017-10324-y
[23] Rush, B., Celi, L. A., & Stone, D. J. (2018). Applying machine learning to continuously monitored physiological data. Journal of Clinical Monitoring and Computing 2018 33:5, 33(5), 887–893. https://doi.org/10.1007/S10877-018-0219-Z
[24] Saxe, G. N., Ma, S., Ren, J., & Aliferis, C. (2017). Machine learning methods to predict child posttraumatic stress: a proof of concept study. BMC Psychiatry 2017 17:1, 17(1), 1–13. https://doi.org/10.1186/S12888-017-1384-1
[25] Knezović, J., Žagar, M., & Mlinarić, H. (2019). Software System for Efficient Lossless Compression of Medical Images. Tehnički Vjesnik, 26(4), 995–1000. https://doi.org/10.17559/TV-20180407110315
[26] Helgheim, B. I., Maia, R., Ferreira, J. C., & Martins, A. L. (2019). Merging Data Diversity of Clinical Medical Records to Improve Effectiveness. International Journal of Environmental Research and Public Health 2019, Vol. 16, Page 769, 16(5), 769. https://doi.org/10.3390/IJERPH16050769
[27] Reiz, A. N., Sagasti, F. M., González, M. Á., Malpica, A. B., Benítez, J. C. M., Cabrera, M. N., Ramírez, Á. D. P., Perdomo, J. M. G., Alonso, J. P., Celi, L. A., de la Hoz, M. Á. A., Deliberato, R., Paik, K., Pollard, T., Raffa, J., Torres, F., Mayol, J., Chafer, J., Ferrer, A. G., … Sánchez García, M. (2019). Big data and machine learning in critical care: Opportunities for collaborative research. Medicina Intensiva, 43(1), 52–57. https://doi.org/10.1016/J.MEDIN.2018.06.002
[28] Norvang, O. P., Hokstad, A., Taraldsen, K., Tan, X., Lydersen, S., Indredavik, B., & Askim, T. (2018). Time spent lying, sitting, and upright during hospitalization after stroke: a prospective observation study. BMC Neurology 2018 18:1, 18(1), 1–8. https://doi.org/10.1186/S12883-018-1134-0
[29] Kang, M., Park, E., Cho, B. H., & Lee, K.-S. (2018). Recent Patient Health Monitoring Platforms Incorporating Internet of Things-Enabled Smart Devices. International Neurourology Journal, 22(Suppl 2), S76. https://doi.org/10.5213/INJ.1836144.072
[30] de Jong, M., van der Meulen-de Jong, A., Romberg-Camps, M., Degens, J., Becx, M., Markus, T., Tomlow, H., Cilissen, M., Ipenburg, N., Verwey, M., Colautti-Duijsens, L., Hameeteman, W., Masclee, A., Jonkers, D., & Pierik, M. (2017). Development and Feasibility Study of a Telemedicine Tool for All Patients with IBD: MyIBDcoach. Inflammatory Bowel Diseases, 23(4), 485–493. https://doi.org/10.1097/MIB.0000000000001034
[31] Murphy, M. (2018). Telehealth Factors for Predicting Hospital Length of Stay. Journal of Gerontological Nursing, 44(10), 16–20. https://doi.org/10.3928/00989134-20180305-01
[32] Schougaard, L. M. V., Mejdahl, C. T., Petersen, K. H., Jessen, A., de Thurah, A., Sidenius, P., Lomborg, K., & Hjollund, N. H. (2017). Effect of patient-initiated versus fixed-interval telePRO-based outpatient follow-up: study protocol for a pragmatic randomised controlled study. BMC Health Services Research 2017 17:1, 17(1), 1–11. https://doi.org/10.1186/S12913-017-2015-8
[33] Wade, V. A., Taylor, A. D., Kidd, M. R., & Carati, C. (2016). Transitioning a home telehealth project into a sustainable, large-scale service: a qualitative study. BMC Health Services Research 2016 16:1, 16(1), 1–10. https://doi.org/10.1186/S12913-016-1436-0
[34] Hanna, Thylén, I., Ågren, S., Liljeroos, M., & Strömberg, A. (2019). Perceptions of Information and Communication Technology as Support for Family Members of Persons with Heart Failure: Qualitative Study. J Med Internet Res 2019;21(7):E13521 Https://Www.Jmir.Org/2019/7/E13521, 21(7), e13521. https://doi.org/10.2196/13521
[35] Chen, C., Garrod, O. G. B., Zhan, J., Beskow, J., Schyns, P. G., & Jack, R. E. (2018). Reverse engineering psychologically valid facial expressions of emotion into social robots. Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018, 448–452. https://doi.org/10.1109/FG.2018.00072
[36] Hung, L., Liu, C., Woldum, E., Au-Yeung, A., Berndt, A., Wallsworth, C., Horne, N., Gregorio, M., Mann, J., & Chaudhury, H. (2019). The benefits of and barriers to using a social robot PARO in care settings: a scoping review. BMC Geriatrics 2019 19:1, 19(1), 1–10. https://doi.org/10.1186/S12877-019-1244-6
[37] Athavipach, C., Pan-ngum, S., & Israsena, P. (2019). A Wearable In-Ear EEG Device for Emotion Monitoring. Sensors 2019, Vol. 19, Page 4014, 19(18), 4014. https://doi.org/10.3390/S19184014
[38] Hueso, M., Vellido, A., Montero, N., Barbieri, C., Ramos, R., Angoso, M., Cruzado, J. M., & Jonsson, A. (2018). Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy. Kidney Diseases, 4(1), 1–9. https://doi.org/10.1159/000486394
[39] Tonsaker, T., Law, S., Ormel, I., Nease, C., & Bartlett, G. (2017). Engaging caregivers: exploring perspectives on web-based health information. Family practice, 34(4), 479-484.
[40] Abdul-Razzak, A., Sherifali, D., You, J., Simon, J., & Brazil, K. (2016). ‘Talk to me’: a mixed methods study on preferred physician behaviours during end-of-life communication from the patient perspective. Health Expectations, 19(4), 883–896. https://doi.org/10.1111/HEX.12384
[41] Omilion-Hodges, L. M., & Swords, N. M. (2015). Communication that heals: mindful communication practices from palliative care leaders. Http://Dx.Doi.Org/10.1080/10410236.2014.953739, 31(3), 328–335.
[42] Jennings, B. (2018). Solidarity and care as relational practices. Bioethics, 32(9), 553–561. https://doi.org/10.1111/BIOE.12510
[43] Calvo, P. (2019). Bioethics of Things: on the algorithmization of moral deliberation in clinical practice. Filosofia Unisinos / Unisinos Journal of Philosophy, 20(2), 155–162. https://doi.org/10.4013/FSU.2019.202.05
[44] Guthrie, E. A., Dickens, C., Blakemore, A., Watson, J., Chew-Graham, C., Lovell, K., Afzal, C., Kapur, N., & Tomenson, B. (2016). Depression predicts future emergency hospital admissions in primary care patients with chronic physical illness. Journal of Psychosomatic Research, 82, 54–61. https://doi.org/10.1016/J.JPSYCHORES.2014.10.002
[45] Zarotti, N., Fletcher, I., & Simpson, J. (2019). New Perspectives on Emotional Processing in People with Symptomatic Huntington’s Disease: Impaired Emotion Regulation and Recognition of Emotional Body Language. Archives of Clinical Neuropsychology, 34(5), 610–624. https://doi.org/10.1093/ARCLIN/ACY085
[46] Khalid, I., Khalid, T. J., Qabajah, M. R., Barnard, A. G., & Qushmaq, I. A. (2016). Healthcare Workers Emotions, Perceived Stressors and Coping Strategies During a MERS-CoV Outbreak. Clinical Medicine & Research, 14(1), 7–14. https://doi.org/10.3121/CMR.2016.1303
[47] Ruitenburg, M. M., Frings-Dresen, M. H. W., & Sluiter, J. K. (2016). Current and future healthcare needs of future hospital physicians. Occupational Medicine, 66(2), 122–127. https://doi.org/10.1093/OCCMED/KQV146
[48] Adamson, K., Sengsavang, S., Charise, A., Wall, S., Kinross, L., & Balkaran, M. (2018). Narrative Training as a Method to Promote Nursing Empathy Within a Pediatric Rehabilitation Setting. Journal of Pediatric Nursing, 42, e2–e9. https://doi.org/10.1016/J.PEDN.2018.06.011
[49] Black, A., McGlinchey, T., Gambles, M., Ellershaw, J., & Mayland, C. R. (2018). The ‘lived experience’ of palliative care patients in one acute hospital setting – a qualitative study. BMC Palliative Care 2018 17:1, 17(1), 1–10. https://doi.org/10.1186/S12904-018-0345-X
[50] Corradi-Dell’Acqua, C., Foerster, M., Sharvit, G., Trueb, L., Foucault, E., Fournier, Y., Vuilleumier, P., & Hugli, O. (2019). Pain management decisions in emergency hospitals are predicted by brain activity during empathy and error monitoring. British Journal of Anaesthesia, 123(2), e284–e292. https://doi.org/10.1016/J.BJA.2019.01.039
[51] Norman, V., Rossillo, K., & Skelton, K. (2016). Creating Healing Environments Through the Theory of Caring. AORN Journal, 104(5), 401–409. https://doi.org/10.1016/J.AORN.2016.09.006
[52] Meesala, A., & Paul, J. (2018). Service quality, consumer satisfaction and loyalty in hospitals: Thinking for the future. Journal of Retailing and Consumer Services, 40, 261–269. https://doi.org/10.1016/J.JRETCONSER.2016.10.011
[53] Pevec, T., & Pisnik, A. (2018). Empirical Evaluation of a Conceptual Model for the Perceived Value of Health Services. Slovenian Journal of Public Health, 57(4), 175. https://doi.org/10.2478/SJPH-2018-0022
[54] Irons, J. Y., Petocz, P., Kenny, D. T., & Chang, A. B. (2019). Singing as an adjunct therapy for children and adults with cystic fibrosis. Cochrane Database of Systematic Reviews, 2019(7). https://doi.org/10.1002/14651858.CD008036.PUB5
[55] Isenberg, S. R., Aslakson, R. A., Dionne-Odom, J. N., Clegg Smith, K., Singh, S., Larson, S., Bridges, J. F. P., Smith, T. J., Wolff, J. L., & Roter, D. L. (2018). Family companions’ involvement during pre-surgical consent visits for major cancer surgery and its relationship to visit communication and satisfaction. Patient Education and Counseling, 101(6), 1066–1074. https://doi.org/10.1016/J.PEC.2018.01.011
[56] Sinclair, S., Beamer, K., Hack, T. F., McClement, S., Bouchal, S. R., Chochinov, H. M., & Hagen, N. A. (2016). Sympathy, empathy, and compassion: A grounded theory study of palliative care patients’ understandings, experiences, and preferences: Https://Doi.Org/10.1177/0269216316663499, 31(5), 437–447.
[57] Blackwell, R. W. née, Lowton, K., Robert, G., Grudzen, C., & Grocott, P. (2017). Using Experience-based Co-design with older patients, their families and staff to improve palliative care experiences in the Emergency Department: A reflective critique on the process and outcomes. International Journal of Nursing Studies, 68, 83–94. https://doi.org/10.1016/J.IJNURSTU.2017.01.002
[58] Mokhtar, A. M. (2017). The Future Hospital: A Business Architecture View. The Malaysian Journal of Medical Sciences: MJMS, 24(5), 1. https://doi.org/10.21315/MJMS2017.24.5.1
[59] Vogus, T. J., & McClelland, L. E. (2016). When the customer is the patient: Lessons from healthcare research on patient satisfaction and service quality ratings. Human Resource Management Review, 26(1), 37–49. https://doi.org/10.1016/J.HRMR.2015.09.005
[60] Sade, R. M., & Kavarana, M. N. (2017). Surgical ethics: today and tomorrow. Https://Doi.Org/10.2217/Fca-2017-0057, 13(6), 567–578.
[61] Syafiqah Abd Mutalib, N., Chiau Ming, L., Mei Yee, S., Lee Wong, P., & Chang Soh, Y. (2016). Pharmaceutical Education Medical Tourism: Ethics, Risks and Benefits. Indian Journal of Pharmaceutical Education and Research |, 50. https://doi.org/10.5530/ijper.50.2.6
[62] Chesterton, L., Stephens, M., Clark, A., & Ahmed, A. (2019). A systematic literature review of the patient hotel model. Https://Doi.Org/10.1080/09638288.2019.1628314, 43(3), 317–323.
[63] Barnes, S., Hamrock, E., Toerper, M., Siddiqui, S., & Levin, S. (2016). Real-time prediction of inpatient length of stay for discharge prioritization. Journal of the American Medical Informatics Association, 23(e1), e2–e10. https://doi.org/10.1093/JAMIA/OCV106
[64] Cai, X., Perez-Concha, O., Coiera, E., Martin-Sanchez, F., Day, R., Roffe, D., & Gallego, B. (2016). Real-time prediction of mortality, readmission, and length of stay using electronic health record data. Journal of the American Medical Informatics Association, 23(3), 553–561. https://doi.org/10.1093/JAMIA/OCV110
[65] Hussain, M., Ajmal, M. M., Gunasekaran, A., & Khan, M. (2018). Exploration of social sustainability in healthcare supply chain. Journal of Cleaner Production, 203, 977-989. https://doi.org/10.1016/j.jclepro.2018.08.157
[66] Nyrud, A. Q., Bringslimark, T., & Bysheim, K. (2014). Benefits from wood interior in a hospital room: a preference study. Http://Dx.Doi.Org/10.1080/00038628.2013.816933, 57(2), 125–131.
[67] Connellan, K., Gaardboe, M., Riggs, D., Due, C., Reinschmidt, A., & Mustillo, L. (2013). Stressed Spaces: Mental Health and Architecture: Https://Doi.Org/10.1177/193758671300600408, 6(4), 127–168.
[68] Watson, K. J., Evans, J., Karvonen, A., & Whitley, T. (2014). Re-conceiving building design quality: A review of building users in their social context: Http://Dx.Doi.Org/10.1177/1420326X14557550, 25(3), 509–523.
[69] Laursen, J., Danielsen, A., & Rosenberg, J. (2014). Effects of Environmental Design on Patient Outcome: A Systematic Review: Https://Doi.Org/10.1177/193758671400700410, 7(4), 108–119.
[70] Rahimi, N., & Dabagh, A. M. (2018). Study the mental effect of color in the interior architecture of the hospital spaces and effect on the patient tranquility. Amazonia Investiga, 7(13), 5–16. https://amazoniainvestiga.info/index.php/amazonia/article/view/489
[71] Van Hoof, J., Rutten, P. G., Struck, C., Huisman, E. R., & Kort, H. S. (2015). The integrated and evidence-based design of healthcare environments. Architectural Engineering and Design Management, 11(4), 243-263.
[72] Salingaros, N. (2016). Teoría de la arquitectura unificada - Capítulo 9: Fisiología humana y diseño basado en la evidencia (Parte 2) | Plataforma Arquitectura. Retrieved April 6, 2020, from https://www.plataformaarquitectura.cl/cl/791780/teoria-de-la-arquitectura-unificada-capitulo-9-fisiologia-humana-y-diseno-basado-en-la-evidencia-parte-2