Recapitulating the Bayesian framework for neurosurgical outpatient care and a cost-benefit analysis of telemedicine for socioeconomically disadvantaged patients in the Philippines during the pandemic
Open accessAbstract
OBJECTIVE: In the Philippines during recent months, a neurosurgical center that caters primarily to socioeconomically disadvantaged patients has encountered unprecedented changes in practice patterns brought about by the COVID-19 pandemic. In particular, the usual task of outpatient care has shifted to the telemedicine format, bringing along all of its attendant advantages and gargantuan challenges. The authors sought to determine the responsiveness of this telemedicine setup to the needs of their disadvantaged patients and explored the application of Bayesian inference to enhance the use of teleconsultation in daily clinical decision-making. METHODS: The authors used the following methods to assess the telemedicine setup used in a low-resource setting during the pandemic: 1) a cross-sectional survey of patients who participated in a medical consultation via telemedicine during the 16-week period from March 16, 2020, to July 15, 2020; 2) a cost-benefit analysis of the use of telemedicine by patients; and 3) a case illustration of a Bayesian approach application unique to the teleconsultation scenario. RESULTS: Of the 272 patient beneficiaries of telemedicine in a 16-week period, 57 responded to the survey. The survey responses regarding neurosurgical outpatient care through telemedicine yielded high ratings of utility for the patients and their caregivers. According to 64% of respondents, the affordability of the telemedicine setup also prevented them from borrowing money from others, among other adverse life events prevented. There were realized financial gains on the part of the patients in terms of cost savings and protection from further impoverishment. The benefit-cost ratio was 3.51 for the patients, signifying that the benefits outweighed the costs. An actual teleconsultation case vignette was reported that is meant to be instructive and contributory to the preparedness of the neurosurgeon on the provider end of the service delivery. CONCLUSIONS: Telemedicine holds promise as a viable and safe method for health service delivery during the pandemic. In the setting of a health system that is continually challenged by shortages of resources, this study shows that an effective telemedicine setup can come with high benefit-cost ratios and quality of care, along with the assurance of patient satisfaction. The potential for high-quality care can be enhanced by the inclusion of the Bayesian framework to the basic toolkit of remote clinical assessment. When confronted with choices in terms of differential diagnosis and tests, the rigor of a simple application of the Bayesian framework can minimize costs arising from uncertainties.
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Cites
Crossing the Quality Chasm: A New Health System for the 21st Century
Committee on Quality of Health Care in America (2002) · Journal for Healthcare Quality · doi:10.1111/j.1945-1474.2002.tb00463.x · Cited by 8,508 · see citing works
Global Surgery 2030: evidence and solutions for achieving health, welfare, and economic development
Meara, J. G., Leather, A. J. M., Hagander, L., Alkire, B. C., Alonso, N., Ameh, E. A., Bickler, S. W., Conteh, L., Dare, A. J., Davies, J., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(15)60160-x · Cited by 3,851 · see citing works
Crossing the Quality Chasm: A New Health System for the 21st Century
Bloom, B. S. (2002) · JAMA · doi:10.1001/jama.287.5.646-a · Cited by 3,732 · see citing works
Household catastrophic health expenditure: a multicountry analysis
Xu, K., EVANS, D. B., Kawabata, K., Zeramdini, R., Klavus, J., & Murray, C. J. L. (2003) · The Lancet · doi:10.1016/s0140-6736(03)13861-5 · Cited by 2,322 · see citing works
(1975) · New England Journal of Medicine · doi:10.1056/nejm197507312930513 · Cited by 1,017 · see citing works
Tuberculous meningitis: more questions, still too few answers
Thwaites, G. E., van Toorn, R., & Schoeman, J. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70168-6 · Cited by 482 · see citing works
Diagnosis of adult tuberculous meningitis by use of clinical and laboratory features
Thwaites, G. E., Chau, T., Stepniewska, K., Phu, N. H., Chuong, L. V., Sinh, D. X. T., White, N. J., Parry, C., & Farrar, J. (2002) · The Lancet · doi:10.1016/s0140-6736(02)11318-3 · Cited by 396 · see citing works
Why clinicians are natural bayesians
Gill, C. J., Sabin, L., & Schmid, C. H. (2005) · BMJ · doi:10.1136/bmj.330.7499.1080 · Cited by 270 · see citing works
Clinical Decision Rules to Rule Out Subarachnoid Hemorrhage for Acute Headache
Perry, J. J., Stiell, I. G., Sivilotti, M. L. A., Bullard, M. J., Hohl, C. M., Sutherland, J., Émond, M., Worster, A., Lee, J. S., Mackey, D., et al. (2013) · JAMA · doi:10.1001/jama.2013.278018 · Cited by 237 · see citing works
Global Monitoring Report on Financial Protection in Health 2021
World Health Organization, & Bank, W. (2021) · doi:10.1596/36723 · Cited by 221 · see citing works
Smith, W. R., Atala, A., Terlecki, R. P., Kelly, E. E., & Matthews, C. A. (2020) · Journal of the American College of Surgeons · doi:10.1016/j.jamcollsurg.2020.04.030 · Cited by 196 · see citing works
Jean, W. C., Ironside, N. T., Sack, K. D., Felbaum, D. R., & Syed, H. R. (2020) · Acta Neurochirurgica · doi:10.1007/s00701-020-04342-5 · Cited by 166 · see citing works
Telemedicine in the Era of Coronavirus Disease 2019 (COVID-19): A Neurosurgical Perspective
Blue, R., Yang, A. I., Zhou, C., De Ravin, E., Teng, C. W., Arguelles, G. R., Huang, V., Wathen, C., Miranda, S. P., Marcotte, P., et al. (2020) · World Neurosurgery · doi:10.1016/j.wneu.2020.05.066 · Cited by 136 · see citing works
The Role of Neurosurgery in Countries with Limited Facilities: Facts and Challenges
Servadei, F., Rossini, Z., Nicolosi, F., Morselli, C., & Park, K. B. (2018) · World Neurosurgery · doi:10.1016/j.wneu.2018.01.047 · Cited by 113 · see citing works
Financing Global Health: Mission Unaccomplished
Schieber, G. J., Gottret, P. E., Fleisher, L. K., & Leive, A. A. (2007) · Health Affairs · doi:10.1377/hlthaff.26.4.921 · Cited by 109 · see citing works
Can economic evaluation in telemedicine be trusted? A systematic review of the literature
Bergmo, T. S. (2009) · Cost Effectiveness and Resource Allocation · doi:10.1186/1478-7547-7-18 · Cited by 103 · see citing works
Ahmed, S. N., Mann, C., Sinclair, D. B., Heino, A., Iskiw, B., Quigley, D., & Ohinmaa, A. E. (2007) · Epilepsia · doi:10.1111/j.1528-1167.2007.01464.x · Cited by 97 · see citing works
Cost–Benefit Analysis and Health Care Evaluations
Brent, R. J. (2003) · Edward Elgar Publishing eBooks · doi:10.4337/9781843766988 · Cited by 93 · see citing works
THE CLINICAL APPLICATION OF BAYES' THEOREM
Hall, G. (1967) · The Lancet · doi:10.1016/s0140-6736(67)90514-4 · Cited by 90 · see citing works
Challenges in the diagnosis of tuberculous meningitis
Palacios, C. F., & Saleeb, P. G. (2020) · Journal of Clinical Tuberculosis and Other Mycobacterial Diseases · doi:10.1016/j.jctube.2020.100164 · Cited by 66 · see citing works
Thakar, S., Rajagopal, N., Mani, S., Shyam, M., Aryan, S., Rao, A. S., Srinivasa, R., Mohan, D., & Hegde, A. S. (2018) · Neurosurgical FOCUS · doi:10.3171/2018.2.focus17543 · Cited by 60 · see citing works
Dadlani, R., Mani, S., Jai Ganesh, A. U., Mohan, D., Rajgopalan, N., Thakar, S., Aryan, S., & Hegde, A. S. (2014) · World Neurosurgery · doi:10.1016/j.wneu.2014.05.027 · Cited by 59 · see citing works
Weir, B. (1994) · Cephalalgia · doi:10.1046/j.1468-2982.1994.1402079.x · Cited by 55 · see citing works
CSF spectrophotometry in the diagnosis and exclusion of spontaneous subarachnoid haemorrhage
Wood, M. J., Dimeski, G., & Nowitzke, A. M. (2005) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2004.05.009 · Cited by 53 · see citing works
Ragonnet, R. R., Trauer, J. M., Geard, N. L., Scott, N., & McBryde, E. S. (2019) · BMC Medicine · doi:10.1186/s12916-019-1452-0 · Cited by 40 · see citing works
Ferraris, K. P., Matsumura, H., Wardhana, D. P. W., Vesagas, T. S., Seng, K., Ali, M. R. M., Ishikawa, E., Matsumura, A., Rosyidi, R. M., Mahadewa, T. G. B., et al. (2020) · Neurosurgical FOCUS · doi:10.3171/2019.12.focus19814 · Cited by 38 · see citing works
Self-citationDiagnostic features of tuberculous meningitis: a cross-sectional study
Pasco, P. M. D. (2012) · BMC Research Notes · doi:10.1186/1756-0500-5-49 · Cited by 32 · see citing works
Greven, A. C. M., Rich, C. W., Malcolm, J. G., Bray, D. P., Rodts, G. E., Refai, D., & Gary, M. F. (2020) · Neurosurgery · doi:10.1093/neuros/nyaa165 · Cited by 26 · see citing works
Cost–benefit analysis and health care evaluations
Birch, S. (2004) · Social Science & Medicine · doi:10.1016/j.socscimed.2003.11.020 · Cited by 25 · see citing works
A Sampler of International Media and Communication Statistics 2010
Leckner, S., & Facht, U. (2011) · Diva portal (Dalarna University Library) · Cited by 22 · see citing works
Which methods for bedside Bayes?
Glasziou, P. (2001) · BMJ Evidence-Based Medicine · doi:10.1136/ebm.6.6.164 · Cited by 20 · see citing works
Snyder, S. R. (2018) · Neurosurgical FOCUS · doi:10.3171/2018.2.focus1889 · Cited by 20 · see citing works
Basil, G. W., Eichberg, D. G., Perez-Dickens, M., Menendez, I., Ivan, M. E., Urakov, T. M., Komotar, R. J., Wang, M. Y., & Levi, A. D. (2020) · Neurosurgery · doi:10.1093/neuros/nyaa215 · Cited by 20 · see citing works
Letter: Telemedicine in Neurosurgery—A Timely Review
LoPresti, M. A., McDeavitt, J. T., Wade, K. R., Jahn, L. K., Viswanathan, A., Fordis, M., & Yoshor, D. (2020) · Neurosurgery · doi:10.1093/neuros/nyaa175 · Cited by 19 · see citing works
The Bayesian Approach to Decision Making and Analysis in Nutrition Research and Practice
Gleason, P., & Harris, J. E. (2019) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2019.07.009 · Cited by 16 · see citing works
Clinical Reasoning and Risk in the Intensive Care Unit
Connors, G. R., & Siner, J. M. (2015) · Clinics in Chest Medicine · doi:10.1016/j.ccm.2015.05.016 · Cited by 13 · see citing works
Telemedicine: Providing Access to Care in Pediatric Neurosurgery to Underserved Communities
Simko, A. P., Han, S. H., & Aldana, P. R. (2020) · World Neurosurgery · doi:10.1016/j.wneu.2020.03.181 · Cited by 13 · see citing works
Fever characteristics in tuberculosis--clinical observation in 597 cases.
Tsao, T. C. Y., Tsai, Y. H., Lan, R. S., Wb, S., & Lee, C. H. (1989) · PubMed · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Telemedicine in surgical care in low- and middle-income countries: a scoping review
Owolabi, E. O., Mac Quene, T., Louw, J., Davies, J. I., & Chu, K. M. (2022) · World Journal of Surgery · doi:10.1007/s00268-022-06549-2 · Cited by 70 · see citing works
The Role of Telemedicine in Surgical Specialties During the COVID‐19 Pandemic: A Scoping Review
Gachabayov, M., Latifi, L. A., Parsikia, A., & Latifi, R. (2022) · World Journal of Surgery · doi:10.1007/s00268-021-06348-1 · Cited by 41 · see citing works
Eslami Jahromi, M., & Ayatollahi, H. (2023) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocac250 · Cited by 30 · see citing works
Silva, A. B., Síndico, S. R. F., Carneiro, A. C., Henrique, S. M., Fernandes, A. G., Gomes, J. P., Marinho, T. P., & Fernandes, V. R. (2021) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2021.0145 · Cited by 24 · see citing works
Telemedicine in Southeast Asia: A Systematic Review
Pengput, A., & Schwartz, D. G. (2022) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2021.0516 · Cited by 27 · see citing works
Ferraris, K. P., Yap, M. E., Bautista, M. C. G., Wardhana, D. P. W., Maliawan, S., Wirawan, I. M. A., Rosyidi, R. M., Seng, K., & Navarro, J. E. (2021) · Frontiers in Surgery · doi:10.3389/fsurg.2021.690851 · Cited by 12 · see citing works
Self-citationSavoldelli, A., Landi, D., & Rizzi, C. (2024) · Sustainability · doi:10.3390/su16062438 · Cited by 11 · see citing works
Nie, J. Z., Karras, C. L., Texakalidis, P., Trybula, S. J., & Dahdaleh, N. S. (2022) · World Neurosurgery · doi:10.1016/j.wneu.2022.08.145 · Cited by 9 · see citing works
Impact of COVID-19 on the Neurosurgical Resident Training Program: An Early Experience
Omer, M., Al–Afif, S., Machetanz, K., Bettag, C., Tatagiba, M. S., Rohde, V., & Krauss, J. K. (2022) · Journal of Neurological Surgery Part A Central European Neurosurgery · doi:10.1055/s-0042-1743108 · Cited by 7 · see citing works
The COVID-19 Pandemic and Global Neurosurgery: The Situation in Japan and the Philippines
Matsumura, H., Ferraris, K. P., & Tsurumi, A. (2021) · World Neurosurgery · doi:10.1016/j.wneu.2021.01.083 · Cited by 3 · see citing works
Self-citationKarasik, D., Cabrera, C. I., Shammassian, B. H., Wright, J. M., III, Bambakidis, N. C., & D’Anza, B. (2024) · World Neurosurgery · doi:10.1016/j.wneu.2024.06.099 · Cited by 2 · see citing works
Patel, S., Shlobin, N. A., & Rosenow, J. M. (2021) · World Neurosurgery · doi:10.1016/j.wneu.2021.07.028
Truong, T. B. (2025) · medRxiv · doi:10.1101/2025.05.25.25328225
Cost analysis for telemedicine services: A scoping review of literature on the cost-benefit approach
Bene, L. D., & Menegon, C. (2026) · MANAGEMENT CONTROL · doi:10.3280/maco2025-003007
Sierra, N. M., Rincón, E. H. H., Bejarano, V. N., & Ghotme, K. A. (2026) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2026.112121
Valenzuela, J. F., Verdeprado, M. D., Tan, A., Carandang, K. A., Dorosan, M., & Alis, C. (2026) · npj Health Systems · doi:10.1038/s44401-026-00141-9
- Authors
- Ferraris, K. P., Golidtum, J. P., Zuñiga, B. K. W., Bautista, M. C. G., Alcazaren, J. C., Seng, K., & Navarro, J. E.
- Affiliations
- José R. Reyes Memorial Medical Center (PH)
- Ateneo de Manila University (PH)
- Philippine General Hospital (PH)
- Venue
- Neurosurgical Focus
- Published
- 2020-12
- Volume
- 49
- Issue
- 6
- Pages
- E14
- ISSN
- 1092-0684 (ISSN-L)
- OpenAlex
- W3107295310
- Cited by
- 16
- References
- 39
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 2 · 2022: 5 · 2021: 5
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Neurosurgical FOCUS (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Keywords
- telemedicine, teleconsultation, COVID-19 pandemic, Bayesian inference, clinical decision-making, cost-benefit analysis, resource-limited settings, patient satisfaction, differential diagnosis, Philippines, health care delivery, remote clinical assessment
- MeSH terms
- COVID-19, Adult, Ambulatory Surgical Procedures, Bayes Theorem, Child, Cost-Benefit Analysis, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Philippines, Surveys and Questionnaires, Social Class, Telemedicine, Neurosurgical Procedures, Vulnerable Populations
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