mWELLCARE:An Integrated mHealth System for the Prevention and Care of Chronic Disease (mWELLCARE)

Major barriers to controlling cardiovascular diseases (CVDs) in India and elsewhere are: low detection rates, inadequate use of evidence based interventions and low adherence with these interventions. Primary health care is the appropriate setting for improving the prevention and management of these chronic conditions. The investigators will develop and evaluate an innovative mobile health (mHealth) software application -'m-WELLCARE'- which provides a patient health profile, decision support for clinical care, monitoring and feedback for use in Indian Community Health Centers (CHCs). The investigators will conduct this research following the steps proposed by the medical research council (MRC) for evaluation of complex interventions. Technical development of m-WELLCARE will be conducted, user acceptability appraised and potential barriers overcome. m-WELLCARE will be evaluated in CHCs of two states, Haryana and Karnataka. The use made of m-WELLCARE, its impact on patterns of health care received and changes in risk factors achieved will be evaluated.

Study Overview

• Status: Completed
• Conditions: Depression; Hypertension; Diabetes; Alcohol Use Disorder
• Intervention / Treatment: Other: mWELLCARE; Other: Usual Care

Detailed Description

Cardiovascular disease (CVD) and diabetes are the leading causes of premature (<60 years) adult deaths in India with projections indicating an almost 3-fold increase to 18 million premature years of life lost by 2030. CVD and diabetes will result in $336.6 billion in lost national income in India over the next decade. The major barriers to the control of these conditions in India are the low detection rates early in the course of the condition, inadequate use of evidence based interventions and low adherence with these interventions. After detection of these conditions, the long-term health outcomes of persons affected is heavily dependent on adherence with care guidelines and is a major priority.

Harnessing the potential of Smartphone technology would be a solution for addressing these challenges at the community level by improving the quality of care. There are several advantages for Smartphone technology that makes it an ideal tool for improving the quality care at the government facilities. Smartphones/tablet computers are low-cost, requires less investment in infrastructure and are ubiquitous used by the masses.

Primary health care settings are best suited to address the prevention and management of hypertension/diabetes and its risk factors. Given these reasons, the Government of India, is planning to scale-up the National Program on prevention and control of cancer, diabetes, cardiovascular diseases and stroke (NPCDCS) giving a major thrust to screening, diagnosis and management of hypertension and diabetes at community level by starting NCD clinics at the Community Health Centres and assigning new roles to the Health Workers at the sub-centers.

In the above context, the investigators plan to develop a tablet computer application for the Medical Officers and Nurse enabling them to deliver high quality care at Community Health Centres (CHCs). The tablet computer application will be capable of running clinical risk scores for identifying people at high risk of diabetes, cardiovascular disease, and computing personalized management plan using evidence-based clinical management guidelines. The feasibility and effectiveness of such a novel application is to be formally evaluated in order to develop a robust clinical decision support system for the Nurses and Medical Officers at the public health facilities.

In brief, the investigators plan to implement the research project in the 20 CHCs each in 2 states in India i.e.Haryana and Karnataka. Out of these, 10 CHCs will receive the mWellcare interventions. In the intervention arm, the NPCDCS Nurses will register 30 years+ patient diagnosed with hypertension and diabetes using tablet computer based Decision Support Software (DSS). For the patients identified with hypertension/diabetes or at high risk, the software will provide individual tailored management plan that would include treatment plan, lifestyle advice and follow up schedule. Thus, Medical Officers at CHCs will be able to prescribe a guideline based management plan for these patients with the help of DSS. The software will store relevant health parameters of patients at local database (tablet computer) and central server that could be accessed during the follow-up visits of the patients or whenever required.

To make meaningful comparison on the impact of the new technology enabled services in improving the quality of care of diabetes and hypertension at the CHCs, the investigators will collect data from 10 more CHCs that provide routine/usual care to the patients. A structured training will be conducted for Medical Officers and Nurse at CHCs (both from the intervention & usual care arm) on evidence based management of hypertension and diabetes prior to the start of the project.

The intervention will be carried out for a period of 1 year that would include regular follow up. The effect of the intervention will be assessed at six and twelve month comparing the blood pressure and blood glucose values of the patients in two groups.

This project has considerable importance because of the fact that the utility of tablet computer based clinical decision support systems in the management of hypertension and diabetes at the public health facilities has not been evaluated in developing countries so far. If found successful, the technology has the potential to be upscale not only in Haryana and Karnataka but across the country in government and private healthcare settings.

• Study Type: Interventional
• Enrollment (Actual): 3702
• Phase: Not Applicable

Contacts and Locations

Study Locations

• India
  • Haryana
    • Assandh, Haryana, India, 132039
      • CHC Assandh
    • Ballah, Haryana, India, 132040
      • CHC Ballah
    • Brara, Haryana, India, 133201
      • CHC Brara
    • Chauramastpur, Haryana, India, 134003
      • CHC Chauramastpur
    • Gharaunda, Haryana, India, 132114
      • CHC Gharaunda
    • Indri, Haryana, India, 132041
      • CHC Indri
    • Jhansa, Haryana, India, 136130
      • CHC Jhansa
    • Ladwa, Haryana, India, 136132
      • CHC Ladwa
    • Mathana, Haryana, India, 136131
      • CHC Mathana
    • Mullana, Haryana, India, 133207
      • CHC Mullana
    • Mustafabad, Haryana, India, 133103
      • CHC Mustafabad
    • Naharpur, Haryana, India, 135001
      • CHC Naharpur
    • Nilokheri, Haryana, India, 132116
      • CHC Nilokheri
    • Nissing, Haryana, India, 132024
      • CHC Nissing
    • Pehowa, Haryana, India, 136128
      • CHC Pehowa
    • Radaur, Haryana, India
      • CHC Radaur
    • Sadhaura, Haryana, India, 133204
      • CHC Sadhaura
    • Shahbad, Haryana, India, 136135
      • CHC Shahbad
    • Shahzadpur, Haryana, India, 134202
      • CHC Shahzadpur
    • Taraori, Haryana, India, 132116
      • CHC Taraori
  • Karnataka
    • Anandapuram, Karnataka, India, 577412
      • CHC Anandapuram
    • Anavatti, Karnataka, India, 577413
      • CHC Anavatti
    • Aynur, Karnataka, India, 577221
      • CHC Aynur
    • Bhadravathi, Karnataka, India, 577301
      • Taluk Hospital Bhadravathi
    • CN Halli, Karnataka, India, 572214
      • CHC CN Halli
    • Gubbi, Karnataka, India, 572216
      • CHC Gubbi
    • Holehonnuru, Karnataka, India, 577227
      • CHC Holehonnuru
    • Hosanagara, Karnataka, India, 577418
      • Taluk Hospital Hosanagara
    • Kannangi, Karnataka, India, 577226
      • CHC Kannangi
    • Koratagere, Karnataka, India, 572129
      • General Hospital Koratagere
    • Kunigal, Karnataka, India, 572130
      • General Hospital Kunigal
    • M.N.Kote, Karnataka, India, 572222
      • CHC M.N.Kote
    • Madhugiri, Karnataka, India, 572132
      • General Hospital Madhugiri
    • Pavagada, Karnataka, India, 561202
      • General Hospital Pavagada
    • Sagar, Karnataka, India, 577401
      • Taluk Hospital Sagar
    • Shiralkoppa, Karnataka, India, 577428
      • CHC Shiralkoppa
    • Sira, Karnataka, India, 572137
      • General Hospital Sira
    • Thirthahalli, Karnataka, India, 577432
      • CHC Kannangi
    • Tiptur, Karnataka, India, 572201
      • General Hospital Tiptur
    • Turuvekere, Karnataka, India, 572227
      • CHC Turuvekere

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 30 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Adults aged 30 yrs+ diagnosed with hypertension and /or diabetes who are able to give written consent (or verbal witnessed consent for illiterate patients).

Exclusion Criteria:

1. Patient requiring immediate referral to tertiary care due to accelerated hypertension, diabetic complications.
2. Patients with learning difficulties or vision/ hearing impairments but without a care giver making it impossible to use mobile phone.
3. Pregnant and lactating women.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: mWELLCARE software arm; The doctor and nurse care coordinators (NCCs) in the mWELLCARE intervention arm will be trained on the use of mWELLCARE software loaded on a tablet computer. Patients diagnosed with hypertension and/or diabetes will be registered by the nurse using mWellcare application. The nurse will record patient parameters, medical history, medication etc and generate a management plan (including drug recommendation, lifestyle advise) using the mWellcare application based on standard treatment guidelines. The doctor will review the recommendation and agree or disagree giving reasons. Patient will be followed up using SMS.	Other: mWELLCARE; mWELLCARE intervention arm will include a software application loaded on a tablet computer that will be used by Nurse Care Coordinators (posted in community health centers) in the course of their jobs to register patients with hypertension or diabetes, to generate clinical decision support recommendations, to track these patients over time and to improve follow-up care. Decision support recommendations will be printed and given to a doctor, who will make the final call on the management plan that will be used for the patient. Registered patients will also receive customized messages on their mobile phone. In addition, at sites where network connectivity permits, the doctor may also be equipped with a doctor's app on a tablet that will be largely the same as the NCC app.; Other Names: Software application loaded on a tablet computer
Active Comparator: Usual care arm; In the control arm or the usual care arm CHCs, the doctor and Nurse will get "refresher" training in the detection, management and follow up of hypertension and diabetes patients based on standard guidelines. They will be provided with charts for quick reference to standard treatment guidelines. Patients diagnosed with hypertension and/or diabetes will be managed by the doctor at the CHC. The nurse will assist in recording blood pressure, height, weight etc, providing lifestyle advise and follow up advice to patients.	Other: Usual Care; Usual care at the community health centers

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Systolic blood Pressure	Difference in mean change in systolic blood pressure between the two treatment arms	Baseline and 12 months
Glycated haemoglobin (HbA1c)	Difference in mean change in glycated haemoglobin(HbA1c) between the two treatment arms	Baseline and 12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Depression	Proportion of patients with moderate and severe depression measured using PHQ-9 score	Baseline and 12 months
Smoking	proportion of smokers	Baseline and 12 months
Body Mass Index (BMI)	Difference in BMI	Baseline and 12 months
Alcohol use	Change in alcohol use to be measured using WHO- AUDIT questionnaire	Baseline and 12 months
Fasting blood sugar	Difference in mean change in fasting blood sugar	Baseline and 12 months
Total cholesterol	Difference in mean change in total cholesterol	Baseline and 12 months
CVD risk	Difference in mean change in predicted 10 year risk of cardiovascular disease using re-caliberated Framingham Risk Score	Baseline and 12 months
Cost	Costs associated with delivering intervention compared to usual care	Baseline and 12 months

Collaborators and Investigators

• Sponsor: Public Health Foundation of India
• Collaborators: London School of Hygiene and Tropical Medicine; Wellcome Trust
• Investigators: Principal Investigator: Dorairaj Prabhakaran, Public Health Foundation of India; Principal Investigator: Vikram Patel, London School of Hygeine and Tropical Medicine

Publications and helpful links

General Publications

• D'Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008 Feb 12;117(6):743-53. doi: 10.1161/CIRCULATIONAHA.107.699579. Epub 2008 Jan 22.
• Krishna S, Boren SA, Balas EA. Healthcare via cell phones: a systematic review. Telemed J E Health. 2009 Apr;15(3):231-40. doi: 10.1089/tmj.2008.0099.
• Chalkidou K, Levine R, Dillon A. Helping poorer countries make locally informed health decisions. BMJ. 2010 Jul 16;341:c3651. doi: 10.1136/bmj.c3651. No abstract available.
• Wee HL, Loke WC, Li SC, Fong KY, Cheung YB, Machin D, Luo N, Thumboo J. Cross-cultural adaptation and validation of Singapore Malay and Tamil versions of the EQ-5D. Ann Acad Med Singap. 2007 Jun;36(6):403-8.
• Prabhakaran D, Jha D, Prieto-Merino D, Roy A, Singh K, Ajay VS, Jindal D, Gupta P, Kondal D, Goenka S, Jacob P, Singh R, Kumar BGP, Perel P, Tandon N, Patel V; Members of the Research Steering Committee,Investigators,Members of the Data Safety and Monitoring Board. Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial. Circulation. 2019 Jan 15;139(3):380-391. doi: 10.1161/CIRCULATIONAHA.118.038192. Epub 2018 Nov 10.
• Jindal D, Gupta P, Jha D, Ajay VS, Goenka S, Jacob P, Mehrotra K, Perel P, Nyong J, Roy A, Tandon N, Prabhakaran D, Patel V. Development of mWellcare: an mHealth intervention for integrated management of hypertension and diabetes in low-resource settings. Glob Health Action. 2018;11(1):1517930. doi: 10.1080/16549716.2018.1517930.
• Jha D, Gupta P, Ajay VS, Jindal D, Perel P, Prieto-Merino D, Jacob P, Nyong J, Venugopal V, Singh K, Goenka S, Roy A, Tandon N, Patel V, Prabhakaran D. Protocol for the mWellcare trial: a multicentre, cluster randomised, 12-month, controlled trial to compare the effectiveness of mWellcare, an mHealth system for an integrated management of patients with hypertension and diabetes, versus enhanced usual care in India. BMJ Open. 2017 Aug 11;7(8):e014851. doi: 10.1136/bmjopen-2016-014851.

Helpful Links

• Curioso, W., New technologies and public health in developing countries: the Cell PREVEN project, in The Internet and health care: theory, research and practice, M. Murero and R. Rice, Editors. 2006, Lawrence Erlbaum Associates: Mahwah (NJ).
• Curioso, W. and P. Mechael, Enhancing 'M-Health' With South-To-South Collaborations. Health Affairs, 2010(29): p. 264-267.
• Vital Wave Consulting, mHealth for Development: The Opportunity of Mobile Technology for Healthcare in the Developing World. . 2009, UN Foundation-Vodafone Foundation Partnership: Washington, D.C. and Berkshire, UK.
• Hanson, K., et al., Expanding access to priority health interventions: a framework for understanding the constraints to scaling-up. J of International Development, 2003. 15(1): p. 1-14.
• Kaplan, W., Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries? . Global Health, 2006(2): p. 9.
• Rigby, M., Impact of telemedicine must be defined in developing countries. bmj, 2002. 324(7328): p. 47.
• Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, et al. No health without mental health. Lancet. 2007; 370:859-77
• http://www.whoindia.org/LinkFiles/NMH_Resources_CVD_RISK_MANAGEMENT_BOOKLET.pdf
• mhGAP Intervention Guide for mental, neurological and substance use disorders in non-specialist health settings. ver 1.0. World Health Organisation Geneva, 2010.
• Free C, Phillips G, Watson L, Gallo L, Lambert F, Patel V, Edwards P. The Effectiveness Of Mobile Health Technologies for Improving Health and Health Services: A Systematic Review. Report for Department of Health, England (in preparation)

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2016
• Primary Completion (Actual): September 1, 2017
• Study Completion (Actual): September 1, 2017

Study Registration Dates

• First Submitted: May 26, 2015
• First Submitted That Met QC Criteria: June 19, 2015
• First Posted (Estimate): June 24, 2015

Study Record Updates

• Last Update Posted (Actual): October 2, 2017
• Last Update Submitted That Met QC Criteria: September 28, 2017
• Last Verified: September 1, 2017

More Information

Terms related to this study

• Keywords: Primary Health Care; mHealth; Decision Support System; Non-communicable diseases
• Additional Relevant MeSH Terms: Mental Disorders; Chemically-Induced Disorders; Pathologic Processes; Alcohol-Related Disorders; Substance-Related Disorders; Disease Attributes; Alcoholism; Chronic Disease
• Other Study ID Numbers: mWELLCARE 107/11