Abstract
There is an increasing emphasis on digital health. However, success of digital health depends on voluntary adoption, which requires good product–market fit for a wide range of users. A national-level survey through snowball sampling was conducted from November 2020 to March 2021 among all MBBS doctors willing to participate. A total of 1010 doctors from different sectors, locations, qualifications with wide range of experience and patient load participated. Doctors from across the board felt going digital would entail long learning curves, additional workload, more screen time and that they do not improve overall quality of care. Majority feel digital solutions do not help in increasing net revenue and consequently prefer free-of-cost digital solutions. Among those willing to pay, onetime investment for hardware/equipment (38%) followed by annual subscription for software licenses (34%) are the preferred modalities. Seventy-four percent of doctors expressed not being comfortable with government providing digital solutions or controlling the data. In order to make the findings more practical and relevant, digital health adoption curve and market intelligence grid have been proposed. Digital health companies can use the adoption curve to understand how adoption can fluctuate with cost, ease of use and data policy. The grid can help companies identify the requirements of their target segment of doctors and therefore achieve better product–market fit.
Similar content being viewed by others
Data availability
All relevant data is part of the manuscript and detailed data analysis sheets have been included in supplementary material. All data is being shared.
References
Choudhury M, Datta P (2019) Private hospitals in health insurance network in India a reflection for implementation of Ayushman Bharat. Working Papers 254: 1–22
Feldman K, Johnson RA, Chawla NV (2018) The state of data in healthcare: path towards standardization. J Healthc Inf Res 2018:1–24
Gowda NR, Kumar A, Arya SK, Ha V (2020) The information imperative: to study the impact of informational discontinuity on clinical decision making among doctors. BMC Med Inf Decis Mak 20(1):1–10
Gowda NR, Khare A, Vikas H, Singh AR, Sharma DK, Poulose R et al (2021) More from less: study on increasing throughput of COVID-19 screening and testing facility at an apex tertiary care hospital in New Delhi using discrete-event simulation software. Digit Health 7:1–8
R Gowda N, Satpathy S, Singh AR, Behera SD (2022) The Holy grail of healthcare analytics: what it takes to get there? BMJ Leader. leader-2021-000527
Kaipio J, Lääveri T, Hyppönen H, Vainiomäki S, Reponen J, Kushniruk A et al (2017) Usability problems do not heal by themselves: national survey on physicians’ experiences with EHRs in Finland. Int J Med Inform 97:266–281
Kruse CS, Kothman K, Anerobi K, Abanaka L (2016a) Adoption factors of the electronic health record: a systematic review. JMIR Med Inform 4(2):1–13
Kruse CS, Kristof C, Jones B, Mitchell E, Martinez A (2016b) Barriers to electronic health record adoption: a systematic literature review. J Med Syst 40:1–7
Mudavadi C, Hogaboam L, Daim TU (2017) A hierarchical decision model (HDM) for exploring the adoption of electronic health records. In: PICMET 2016-Portland International Conference on Management of Engineering and Technology: Technology Management for Social Innovation, Proceedings. pp 2770–81.
Panch T, Mattie H, Celi LA (2019) The inconvenient truth about AI in healthcare. NPJ Digit Med 2(1):4–6
Ramaswamy A, Gowda NR, Vikas H, Prabhu M, Sharma DK, Gowda PR et al (2022) It’s the data, stupid: inflection point for artificial intelligence in Indian healthcare. Artif Intell Med 128(April):102300
Ranabhat CL, Jakovljevic M (2023) Sustainable health care provision worldwide: is there a necessary trade-off between cost and quality? Sustainability 15(2):1372
Raskin L (2012) Grading on a curve. Archit Rec 200(1):121–123
Romanova I, Kudinska M (2016) Banking and fintech: a challenge or opportunity? Contemp Stud Econ Financ Anal 98:21–35
Sahoo PM, Rout HS, Jakovljevic M (2023) Consequences of India’s population aging to its healthcare financing and provision. J Med Econ 26:308–315
Shah R, Basu D (2010) Coercion in psychiatric care: global and Indian perspective. Indian J Psychiatr 52(3):203–206
Acknowledgements
None.
Funding
This work received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Author information
Authors and Affiliations
Contributions
The study was conceptualized by Dr NRG, Dr VH under the guidance of Dr SS. Study design was created and methodology was planned by Dr NRG, Dr VH, Dr SS, Dr ARS, Dr AK and Dr DKS. Mr PRG, Mr SV and Mr NG being engineers and experts on software systems & artificial intelligence, played a vital role while designing the questionnaire and then during the interpretation of results and writing discussion. Dr AR, Dr MP, Dr DD, Dr JBS, Dr RK, Dr BG, Dr CH, Dr SKP, Dr DTK and Dr KW being clinicians and experts from different fields played a key role in designing the questionnaire and validating it. They also contributed during data interpretation and in writing discussion. Dr AR, Dr AK and Mr DCJ helped in creating visualization like charts and tables. Dr NRG, Dr VH and Dr AR prepared the first draft of the manuscript which was reviewed and approved by all other authors.
Corresponding author
Ethics declarations
Conflict of interest
None.
Ethical approval
Approval has been obtained from All India Institute of Medical Sciences (AIIMS) Ethics Committee vide Ref No. 1043/03.10.2020.
Consent to participation
Consent obtained at the time of participation and only those willing have participated in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Gowda, N.R., Vikas, H., Satpathy, S. et al. Digital elixir for healthcare: market intelligence and policy implications. Decision 50, 489–500 (2023). https://doi.org/10.1007/s40622-023-00370-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40622-023-00370-z