Year : 2022 | Volume
: 66 | Issue : 4 | Page : 399--400
Digital technology for improving health
Jayashree Sachin Gothankar1, Prakash Prabhakarrao Doke2, Sujata Kapil Murarkar3,
1 Professor and Head, Department of Community Medicine, Bharati Vidyapeeth DTU Medical College, Pune, Maharashtra, India
2 Chairperson-CRPU, Bharati Vidyapeeth DTU Medical College and Medical Foundation, Pune, Maharashtra, India
3 Associate Professor Department of Community Medicine, Bharati Vidyapeeth DTU Medical College, Pune, Maharashtra, India
Jayashree Sachin Gothankar
Professor and Head, Department of Community Medicine, Bharati Vidyapeeth DTU Medical College, Pune, Maharashtra
|How to cite this article:|
Gothankar JS, Doke PP, Murarkar SK. Digital technology for improving health.Indian J Public Health 2022;66:399-400
|How to cite this URL:|
Gothankar JS, Doke PP, Murarkar SK. Digital technology for improving health. Indian J Public Health [serial online] 2022 [cited 2023 Jan 31 ];66:399-400
Available from: https://www.ijph.in/text.asp?2022/66/4/399/366573
The concept of digital health in the form of images and telemedicine has been used for the last 100 years. However, since the 1990s, the U. S. National Academy of Medicine began recommending the complete digitization of health data; since then, digital technology in health care has become more evident. The rapid expansion of the Internet and digital technology in the last 15 years has changed the social, educational, and therapeutic space in many ways. The World Health Assembly Resolution on Digital Health, approved by WHO in 2018, indicates the importance of digital technologies (DTs) to achieve universal health coverage and other health indicators of sustainable development goals. Later, the movement got more impetus when the World Health Organization also published a global strategy on digital health. The COVID-19 pandemic further expedited the need for digital advancement. DTs in health are used to facilitate clinical support in disciplines such as radiology, ophthalmology, and oncology, thereby improve and monitor patient care quality.,, In the public health domain, DT is used at the primary prevention level to improve immunization uptake, encourage and help people to adopt healthier lifestyles, and monitor the environment. At the next level, it can help deliver medicines to remote clinics and improve registration under the Birth and Death Registration Act. It can detect and respond to emerging infectious disease threats earlier than official notifications., Analysis of various syndrome surveillance can be done through web queries. Computational modeling helps to understand the role of mobility patterns in the progression of epidemics. Climate change and vector activity can be monitored using remote sensing technology. Using climatologic parameters, vegetation, and soil indices data in mathematical modeling could generate early warnings for epidemic mitigation. DTs used in the COVID-19 pandemic were digital epidemiological surveillance through machine learning, survey app, and websites; rapid case identification through the connected diagnostic device and machine learning; interruption of community transmission using smartphone apps and mobile phone data location; public communication through social media platform, online search engine, and chat box; and clinical care through teleconferencing. DT enables public health programs to reach more beneficiaries.
There are two critical drivers for digitization in the health field: the nonavailability of health resources and the differential health status at various levels: national, state, district, and community. There is a heightened need for collaboration between institutions, organizations, scientists, and public health networks for the success of DT in improving health.
Every new change comes with challenges. The most crucial challenge for the universal use of the DT is suboptimal Internet connectivity in tribal and hilly areas. There is a need to have a robust and uniform system across the country to avoid duplication, expenditure, and better understanding. Poor health literacy leads to poor health outcomes and higher health systems costs. Challenges related to cybersecurity threats, privacy, and challenging misinformation should be tackled. Digital wellness gadgets may provide multifaceted and understandable information that can worry the patient; often, these gadgets are expensive; hence, their usage is restricted and require regular upgrades. DT may help reduce health inequities, but the existing “digital divide” may further widen the gap in health achievements between different societal groups. This division is likely to happen due to varying levels of technical and literacy skills, differences in access, cultural and social barriers, and lack of sufficient knowledge and confidence about its use which exists considerably between different socioeconomic and sociodemographic groups. Thus, only evaluation studies to determine the extent to which DTs may create, reduce, or exacerbate health inequalities are required.
The Government of India has launched the National Digital Health Mission (NDHM) to strengthen health systems by applying digital health technologies. The health management information system gives block-wise information on selected RCH indicators. The nationwide rollout of the digitization pilot project was renamed “Ayushman Bharat Digital Mission” (ABDM). Honorable Prime Minister Shri Narendra Modi launched ABDM on September 27, 2021. It is a descendant of what was formerly known as the NDHM and further gives impetus to the drive for health-care digitization in India. The ABDM strives to boost the four key spheres for measuring health-care delivery: quality, transparency, accessibility, and affordability.
ABDM presently has the following components: (1) Ayushman Bharat Health Account (ABHA) number is a 14-digit number linked with an Aadhaar card, enabling the person to participate by sharing and receiving data from impaneled health-care service providers; (2) The health-care professional registry includes practitioners from modern medicine and AYUSH systems; (3) The health facility registry is a comprehensive system matrix that envisages the empanelment of public/private, clinic/hospital, and diagnostic/imaging centers; (4) ABHA mobile app is an electronic personal health record. It is expected to be under the control of the user; and (5) A unified health interface between patients and health service providers enables varied digital health services such as appointments, teleconsultation, review of reports, and admissions whenever needed. The use of DT requires adequate education and training of health-care providers. Keeping in mind the above fact, the Indian Public Health Association, therefore, decided to address the importance of digital technology for improving health through their national conference held from 23 to September 5, 2022, at Pune to foster and harness existing and new partnerships among the stakeholders for developing strategies to address public health issues using innovative techniques.
The authors sincerely thank faculty from Community Medicine Department B. J. Medical College, Pune. We also thank the management and faculty of Bharati Vidyapeeth Deemed University Medical College, Pune, for extending full support. We are grateful to the Central Council of the Indian Public Health Association for allowing us to hold the 66th Annual National Conference of the Indian Public Health Association at Pune.
|1||Cummins N, Schuller BW. Five crucial challenges in digital health. Front Digit Health 2020;2:536203.|
|2||World Health Organization. WHO Guideline: Recommendations on Digital Interventions for Health System Strengthening; 2019. Available from: http://apps.who.int/iris/bitstream/handle/10665/311941/9789241550505-eng.pdf?ua=1. [Last Assessed on 15th November 2022].|
|3||World Health Organization. Global Strategy on Digital Health 2020-2025. World Health Organization; 2021. Available from https://www.who.int/publications/i/item/9789240020924.|
|4||Cheng PM, Montagnon E, Yamashita R, Pan I, Cadrin-Chênevert A, Perdigón Romero F, et al. Deep learning: An update for radiologists. Radiographics 2021;41:1427-45.|
|5||Aggarwal R, Sounderajah V, Martin G, Ting DS, Karthikesalingam A, King D, et al. Diagnostic accuracy of deep learning in medical imaging: A systematic review and meta-analysis. NPJ Digit Med 2021;4:65.|
|6||Cui M, Zhang DY. Artificial intelligence and computational pathology. Lab Invest 2021;101:412-22.|
|7||Chauvin J, Lomazzi M. The digital technology revolution and its impact on the public's health. Eur J Public Health 2017;27:947.|
|8||European Centre for Disease Prevention and Control. Digital Technologies for Infectious Disease Surveillance, Prevention and Control – A Scoping Review of the Research Literature 2015-2019. Stockholm: European Centre for Disease Prevention and Control; 2021.|
|9||Christaki E. New technologies in predicting, preventing and controlling emerging infectious diseases. Virulence 2015;6:558-65.|
|10||Budd J, Miller BS, Manning EM, Lampos V, Zhuang M, Edelstein M, et al. Digital technologies in the public-health response to COVID-19. Nat Med 2020;26:1183-92.|
|11||Mackert M, Mabry-Flynn A, Champlin S, Donovan EE, Pounders K. Health literacy and health information technology adoption: The potential for a new digital divide. J Med Internet Res 2016;18:e264.|
|12||Ricciardi W, Pita Barros P, Bourek A, Brouwer W, Kelsey T, Lehtonen L, et al. How to govern the digital transformation of health services. Eur J Public Health 2019;29:7-12.|
|13||National Health Mission, Government of India. Health Management Information System. Available from: https://hmis.nhp.gov.in/#!/standardReports. [Last Assessed on 15th November 2022].|