Evidence map›Paper›PMID 34654431›Full record

ArticleBMC health services research2021

A model for national assessment of barriers for implementing digital technology interventions to improve hypertension management in the public health care system in India.

Shivani A Patel, Kushagra Vashist, Prashant Jarhyan, Hanspria Sharma, Priti Gupta, Devraj Jindal, Nikhil Srinivasapura Venkateshmurthy, Lisa Pfadenhauer, Sailesh Mohan, Nikhil Tandon

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Cross fertilisation of Public Health and Translational Research.Journal of the Indian Institute of Science · 2022
    Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Shivani A PatelDepartment of Global Health and Epidemiology, Emory University, Atlanta, USA. s.a.patel@emory.edu.ORCID http://orcid.org/0000-0003-0082-5857
Kushagra VashistDepartment of Global Health and Epidemiology, Emory University, Atlanta, USA.
Prashant JarhyanCentre for Chronic Disease Control, New Delhi, India.
Hanspria SharmaAll India Institute of Medical Sciences, New Delhi, India.
Priti GuptaCentre for Chronic Disease Control, New Delhi, India.
Devraj JindalCentre for Chronic Disease Control, New Delhi, India.
Nikhil Srinivasapura VenkateshmurthyCentre for Chronic Disease Control, New Delhi, India.
Lisa PfadenhauerDepartment of Global Health and Epidemiology, Emory University, Atlanta, USA.
Sailesh MohanCentre for Chronic Disease Control, New Delhi, India.
Nikhil TandonAll India Institute of Medical Sciences, New Delhi, India.
Centre for Chronic Disease Control · INEmory University · USAll India Institute of Medical Sciences · IN

Funding

Integrated Tracking, Referral, and Algorithmic Management (I-TREC) System for Hypertension and DiabetesU01HL138635 · NHLBI · ALL-INDIA INSTITUTE OF MEDICAL SCIENCES · PI TANDON, NIKHIL · 2017 to 2021
$1.3M
NHLBI NIH HHS 5U01HL138635NHLBI NIH HHS U01 HL138635
6 · The paper itself

Abstract

backgroundThere is substantial interest in leveraging digital health technology to support hypertension management in low- and middle-income countries such as India. The potential for healthcare infrastructure and broader context to support such initiatives in India has not been examined. We evaluated existing healthcare infrastructure to support digital health interventions and examined epidemiologic, socioeconomic, and geographical contextual correlates of healthcare infrastructure in 544 districts covering 29 states and union territories across India.

methodsThe study was a cross-sectional analysis of India's Fourth District Level Household and Facility Survey (DLHS-4; 2012-2014), the most up-to-date nationally representative district-level healthcare infrastructure data. Facilities were the unit of analysis, and analyses accounted for clustering within states. The main outcome was healthcare system infrastructural context to implement hypertension management programs. Domains included diagnostics (functional BP instrument), medications (anti-hypertensive medication in stock), essential clinical staff (e.g., staff nurse, medical officer, pharmacist), and IT specific infrastructure (regular power supply, internet connection, computer availability). Descriptive analysis was conducted for infrastructure indicators based on the Indian Public Health Standards, and logistic regression was conducted to estimate the association between epidemiologic and geographical context (exposures) and the composite measure of healthcare system.

resultsData from 32,215 government facilities were analyzed. Among lowest-tier subcenters, 30% had some IT infrastructure, while at the highest-tier district hospitals, 92% possessed IT infrastructure. At mid-tier primary health centres and community health centres, IT infrastructure availability was 28 and 51%, respectively. For all but sub-centres, the availability of essential staff was lower than the availability of IT infrastructure. For all but district hospitals, higher levels of blood pressure, body mass index, and urban residents were correlated with more favorable infrastructure. By region, districts in Western India tended towards having the best prepared health facilities.

conclusionsIT infrastructure to support digital health interventions is more frequently lacking at lower and mid-tier healthcare facilities compared with apex facilities in India. Gaps were generally larger for staffing than physical infrastructure, suggesting that beyond IT infrastructure, shortages in essential staff impose significant constraints to the adoption of digital health interventions. These data provide early benchmarks for state- and district-level planning.

Indexed as

Digital TechnologyHypertensionCross-Sectional StudiesDelivery of Health CareHumansIndiaDigital technologyHypertensionIndiaInfrastructureManagementPublic healthcare system

Identifiers

PMID34654431
PMCPMC8517936
OpenAlexW3205174347

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.