Journal of Education and Health Promotion

Assessing the implementation of a mobile App‑based electronic health record: A mixed‑method study from South India

Document Type : Original Article

Authors

. D.M. Shilpa 1
. Poonam Ramesh Naik 2
. Hemant Deepak Shewade 3
. H Sudarshan 1

1 Karuna Trust, Bengaluru

2 Department of Community Medicine, Yenepoya Medical College, Yenepoya (Deemed to be University), Mangalore, Karnataka

3 Karuna Trust, Bengaluru, The Union South‑East Asia Office, New Delhi, India, International Union Against Tuberculosis and Lung Diseases (The Union), Paris, France

Abstract
BACKGROUND: Government of India recognizes the use of “information, communication, and
technology” in the provision of comprehensive primary healthcare. In 2014–2015, Karuna Trust,
a nongovernmental organization, Bengaluru, India, introduced an electronic health record (EHR)
innovation, namely “Comprehensive Public Health Management” application (CPHM App). Data
could be entered in an offline mode followed by syncing with cloud. The CPHM App was piloted in
primary health center (PHC) Gumballi, in Karnataka, with focus on household survey and maternal
and child health (MCH) services.
OBJECTIVES: To compare the consistency of selected MCH process indicators for Health
Management Information System [HMIS] available from paper‑based records and those generated
through the CPHM App (2016–2017). We also explored the implementation enablers, barriers, and
suggested solutions from the user perspective.
METHODS: A sequential mixed‑method study design was followed. Quantitative phase involved
aggregate data analysis looking into the consistency of selected MCH process indicators available
from paper‑based records and those generated through the CPHM App (2016–2017) followed by
thematic analysis of in‑depth interviews of healthcare providers. Consistency was defined as a
percentage where the numerator was the HMIS‑related process indicator data from CPHM App and
denominator was the data from paper‑based records.
RESULTS: Three out of 12 selected MCH indicators had consistency of  >80%. The quarterly
consistency reduced over the 2 years. Dual burden of entry and regular monitoring of paper‑based
records by district health and family welfare department were the reasons why more importance was
given to entry in paper‑based records. Ability to generate aggregate indicators with CPHM App, easy
to use and retrieve data in the field, and reminder facility for planned health activities were some
of the factors facilitating CPHM implementation. The key barriers were limited technical expertise
and support from the technical team and no internet connectivity in the field and traveling to PHC
to sync the data. Provision of real‑time technical support and availability of data connectivity in the
field were some of the solutions suggested.
CONCLUSION: There should be a minimum of 1–2  years of simultaneous use of EHR and
paper‑based records after which one must shift to EHR.

Keywords

Comprehensive Public Health Management App
electronic health records
health system research
maternal and child health services
Structured Operational Research and Training Initiative
  1. World Health Organization. Declaration. World Health
    Organization; 2019. [cited on 10 December 2019]. Available
    from: https://www.who.int/primary‑health/conference‑phc/
    declaration.
    2. WHO Global Diffusion of eHealth: Making Universal. Report
    of the third Global Survey on eHealth Global Observatory for
    eHealth Global Diffusion of eHealth: Making Universal Health
    Coverage Achievable; 2016.
    3. Bodavala R. Evaluation of Health Management Information
    System in India Need for Computerized Databases in HMIS; 2012.
    4. National Health Mission, Ministry of Health and Family
    Welfare – Government of India. Infrastructure. Available from:
    https://nhm.gov.in/index1.php?lang=1&level=2&sublinkid=1
    220&lid=190. [Last accessed 2019 Dec 10].
    5. Ministry of Statistics and Program Implementation. Government
    of India. Records and Reports Maintained at Sub Health Centre
    Level; Available from: http://www.mospi.gov.in/91-recordsand-reports-maintained-sub-health-centre-level. [Last accessed
    on 2019 Dec 10].
    6. National Health Mission. Ministry of Health and Family Welfare,
    Government of India. Health Management Information System;
    2019.
    7. Ministry of Health and Family Welfare. e‑Health and Telemedicine,
    Government of India. Available from: https://www.nhp.gov.in/
    telemedicine_pg. [Last accessed on 2019 Dec 10].
    8. Creswell J, Plano Clark V. Designing and Conducting Mixed
    Methods Research, Organizational Research Methods. Vol. 12.
    London (United Kingdom): SAGE Publications; 2009. p. 801‑4.
    Available from: https://doi.org/10.1177/1094428108318066.
    [Last accessed on 2019 Dec 10].
    9. Karuna Trust; 2019. Available from: http://www.karunatrust.
    com/. [Last accessed on 2019 Dec 10].
    10. National Health Systems Resource Centre. Ayushman Bharat:
    Comprehensive Primary Health Care through Health and
    Wellness Centers‑Operational Guidelines. National Health
    Systems Resource Centre; 2019. p. 96.
    11. Sanjari M, Bahramnezhad F, Fomani FK, Shoghi M, Cheraghi MA.
    Ethical challenges of researchers in qualitative studies: The
    necessity to develop a specific guideline. J Med Ethics Hist Med
    2014;7:14.
    12. Kvale S. Doing Interviews. United Kingdom: SAGE
    Publications; 2007. p. 157. Available from: https://dx.doi.
    org/10.4135/9781849208963. [Last accessed on 2019 Dec 10].
    13. Saldana J. The Coding Manual for Qualitative Researchers. Los
    Angeles, CA, USA: SAGE Publications; 2009.
    14. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting
    qualitative research (COREQ): A 32‑item checklist for interviews
    and focus groups. Int J Qual Health Care 2007;19:349‑57.
    15. Rothstein JD, Jennings L, Moorthy A, Yang F, Gee L, Romano K,
    et  al. Qualitative assessment of the feasibility, usability, and
    acceptability of a mobile client data app for community‑based
    maternal, neonatal, and child care in rural Ghana. Int J Telemed
    Appl 2016;2016:2515420. doi: 10.1155/2016/2515420.
    16. Agarwal S, Perry HB, Long LA, Labrique AB. Evidence on
    feasibility and effective use of mHealth strategies by frontline
    health workers in developing countries: Systematic review. Trop
    Med Int Health 2015;20:1003‑14.
    17. Bogan M, van Esch J, Derenzi B, Mushi C, Wakabi T, Lesh N,
    et al. Improving Standards of Care with Mobile Applications in
    Tanzania Gayo Mhila D‑tree International Presented at the W3C
    Workshop on the Role of Mobile Technologies in Fostering Social
    and Economic Development in Africa; 2009.
    18. Alam M, Khanam T, Khan R, Raihan A, Chowdhury M. Assessing
    the Scope for use of Mobile Based Solution to Improve Maternal
    and Child Health in Bangladesh: A Case Study on Efficiency of
    Community Health Workers, Automated risk Assessment of
    Patients and web Based data Collection (Working Paper for ICTD
    London Conference) [2013-04-22].
    19. Rotheram‑Borus MJ, Richter L, Van Rooyen H, van Heerden A,
    Tomlinson M, Stein A, et al. Project masihambisane: A cluster
    randomised controlled trial with peer mentors to improve
    outcomes for pregnant mothers living with HIV. Trials 2011;12:2.
    20. Asiki G, Newton R, Kibirige L, Kamali A, Marions L, Smedman L.
    Feasibility of using smartphones by village health workers for
    pregnancy registration and effectiveness of mobile phone text
    messages on reduction of homebirths in rural Uganda. PLoS One
    2018;13:e0198653.
    21. Rajput ZA, Mbugua S, Amadi D, Chepngeno V, Saleem JJ,
    Anokwa Y, et al. Evaluation of an Android‑based mHealth system
    for population surveillance in developing countries. J Am Med
    Inform Assoc 2012;19:655‑9.
    22. McNabb M, Chukwu E, Ojo O, Shekhar N, Gill CJ, Salami H, et al.
    Assessment of the quality of antenatal care services provided by
    health workers using a mobile phone decision support application
    in northern Nigeria: A pre/post‑intervention study. PLoS One
    2015;10:e0123940.
    23. Chib A. The aceh besar midwives with mobile phones project:
    Design and evaluation perspectives using the information and
    communication technologies for healthcare development model.
    J Comput Commun 2010;15:500‑25. Available from: https://doi.
    org/10.1111/j. 1083‑6101.2010.01515.x. [Last accessed on 2019 Dec 10].
    24. Lund S, Hemed M, Nielsen BB, Said A, Said K, Makungu MH,
    et al. Mobile phones as a health communication tool to improve
    skilled attendance at delivery in Zanzibar: A cluster‑randomised
    controlled trial. BJOG 2012;119:1256‑64.
  2. 25. Blank A, Prytherch H, Kaltschmidt J, Krings A, Sukums F,
    Mensah N, et al. “Quality of prenatal and maternal care: Bridging
    the know‑do gap” (QUALMAT study): An electronic clinical
    decision support system for rural Sub‑Saharan Africa. BMC Med
    Inform Decis Mak 2013;13:44.
    26. Chaiyachati KH, Loveday M, Lorenz S, Lesh N, Larkan LM,
    Cinti S, et al. A pilot study of an mHealth application for healthcare
    workers: Poor uptake despite high reported acceptability at a rural
    South African community‑based MDR‑TB treatment program.
    PLoS One 2013;8:e64662.
    27. Cole‑Ceesay R, Cherian M, Sonko A, Shivute N, Cham M,
    Davis M, et al. Strengthening the emergency healthcare system
    for mothers and children in The Gambia. Reprod Health
    2010;7:21.
Journal of Education and Health Promotion
Volume 10, Issue 4
April 2020
Pages 1-10

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