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Cited by 89Mobile Health and mHealth ApplicationsICT in Developing CommunitiesElectronic Health Records Systems

Engineering a mobile health tool for resource-poor settings to assess and manage cardiovascular disease risk: SMARThealth study

Open access
Raghu, Arvind, Praveen, Devarsetty, Peiris, David, Tarassenko, Lionel, Clifford, Gari·2015·BMC Medical Informatics and Decision Making
DOI 10.1186/s12911-015-0148-4PMC PMC4430914
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Abstract

BACKGROUND: The incidence of chronic diseases in low- and middle-income countries is rapidly increasing both in urban and rural regions. A major challenge for health systems globally is to develop innovative solutions for the prevention and control of these diseases. This paper discusses the development and pilot testing of SMARTHealth, a mobile-based, point-of-care Clinical Decision Support (CDS) tool to assess and manage cardiovascular disease (CVD) risk in resource-constrained settings. Through pilot testing, the preliminary acceptability, utility, and efficiency of the CDS tool was obtained. METHODS: The CDS tool was part of an mHealth system comprising a mobile application that consisted of an evidence-based risk prediction and management algorithm, and a server-side electronic medical record system. Through an agile development process and user-centred design approach, key features of the mobile application that fitted the requirements of the end users and environment were obtained. A comprehensive analytics framework facilitated a data-driven approach to investigate four areas, namely, system efficiency, end-user variability, manual data entry errors, and usefulness of point-of-care management recommendations to the healthcare worker. A four-point Likert scale was used at the end of every risk assessment to gauge ease-of-use of the system. RESULTS: The system was field-tested with eleven village healthcare workers and three Primary Health Centre doctors, who screened a total of 292 adults aged 40 years and above. 34% of participants screened by health workers were identified by the CDS tool to be high CVD risk and referred to a doctor. In-depth analysis of user interactions found the CDS tool feasible for use and easily integrable into the workflow of healthcare workers. Following completion of the pilot, further technical enhancements were implemented to improve uptake of the mHealth platform. It will then be evaluated for effectiveness and cost-effectiveness in a cluster randomized controlled trial involving 54 southern Indian villages and over 16000 individuals at high CVD risk. CONCLUSIONS: An evidence-based CVD risk prediction and management tool was used to develop an mHealth platform in rural India for CVD screening and management with proper engagement of health care providers and local communities. With over a third of screened participants being high risk, there is a need to demonstrate the clinical impact of the mHealth platform so that it could contribute to improved CVD detection in high risk low resource settings.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper reports the agile, user-centred development and pilot testing of SMARThealth, a mobile clinical decision support tool for assessing and managing cardiovascular disease (CVD) risk in rural India. In the pilot, 11 village health workers and 3 primary health centre doctors screened 292 adults, with 34% identified as high CVD risk and 57% of ASHA-screened participants referred to a physician.

Key findings

  • A total of 292 adults were screened: 227 by 11 ASHAs (mean age 51.4 ± 13.1 years) and 65 in-patients by 3 PHC physicians (mean age 55.3 ± 11.7 years); 34% of screened participants had a CVD risk score >30% or clinically high risk/CVD or both.
  • Among 227 participants screened by ASHAs, the CDS tool identified 57% (n = 128) for physician referral, either for high CVD risk (n = 88) or impaired fasting glucose (n = 40).
  • Median complete CVD risk assessment time was 00:21:10 (IQR 00:14:08); Step 3 (risk factor acquisition) took longest, median 00:10:33 (IQR 00:11:22), and completion time decreased as ASHAs performed more procedures.
  • Usability: over 72% of screening procedures were rated easy to use, no user rated the application below 3 on a 4-point scale, and manual blood glucose entry errors occurred in 14/227 patients (median error 9.55 mg/dL, IQR 35.75 mg/dL); overall Bluetooth BP device usage rate was 55%.

Methods

  • The CDS tool was developed using agile development and user-centred design, incorporating WHO/ISH 10-year CVD risk charts and guideline-based management recommendations, with a server-side OpenMRS electronic medical record and Android tablets.
  • Field testing involved 11 ASHAs performing door-to-door screening of 227 community participants in 3 rural Andhra Pradesh villages, plus 3 PHC physicians screening 65 in-patients; detailed usage analytics focused on 3 ASHAs (npB1, npM1, npL1) who performed 28, 20, and 16 assessments.
  • An analytics framework logged clicks and timestamps; bootstrapping estimated mean procedure times and 95% CIs; manually entered glucose values were compared with glucometer readings; a four-point Likert scale assessed usability after every risk assessment.

Limitations

  • Stated: the main limitation was the limited sample size, and the pilot was not designed to be representative; infrastructural barriers included power supply limited to fixed times of day, requiring frequent tablet charging.
  • Evident: the paper focuses on ASHA usage and does not report clinical outcomes or effectiveness; physician usage data are not analysed in detail; only 3 ASHAs were selected for detailed usage analysis; usability was assessed at the end of each procedure and may be subject to social desirability bias despite the authors’ efforts to minimise it.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s12911-015-0148-4

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 15 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    At the end of the pilot study, npM1 had an estimated mean procedure time of 00:24:42 with 95% CI [00:21:01, 00:28:27].

    “npM1, having completed 5 more procedures since the last milestone, finishes with a slightly lower estimated mean procedure time 00:24:42 with narrower 95% CI [00:21:01, 00:28:27].”
    Quote in the paperNot a substantial claim
  • Findingcitation

    Some participants did not know their date or year of birth accurately.

    “It was found that some of the participants did not know their date or even year of birth accurately.”
    Quote in the paperSubstantial claim
  • Findingown data

    The usage of the risk projection meter was much lower in comparison to the other sections for the three ASHAs.

    “It can be observed that the usage of the risk projection meter was much lower in comparison to the other sections for the three ASHAs.”
    Quote in the paperNot a substantial claim
  • Findingown data

    In the initial stages of the pilot study, at the end of 5 procedures completed by each ASHA, the bootstrapped estimates of mean procedure times for all ASHAs were high with wide CIs.

    “In the initial stages of the pilot study (for instance, at the end of 5 procedures completed by each ASHA), the bootstrapped estimate of the mean procedure times for all ASHAs are high with wide CIs.”
    Quote in the paperNot a substantial claim
  • Findingown data

    34% of screened participants had a CVD risk score greater than 30% or had CHR or CVD or both.

    “34% of screened participants had a CVD risk score greater than 30% or had CHR or CVD or both.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 18
  • May combine two claims. 36
  • The quote only partly states this claim. 3

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    A total of 227 individuals were screened by 11 ASHAs, while 3 PHC physicians independently used the mobile application HealthTracker to screen 65 in-patients, giving a total N of 292.

    “A total of 227 individuals (mean age of 51.4 ±13.1 years) were screened by 11 ASHAs, while 3 PHC physicians independently used the mobile application (HealthTracker) as a clinical decision support tool to screen 65 in-patients (mean age of 55.3 ± 11.7 years) who visited their clinic (total N=292).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    At the end of 5 procedures, ASHA npL1 had the largest estimate of mean procedure time, 00:53:02, with 95% CI [00:32:36, 01:24:35].

    “ASHA npL1 has the largest estimate with mean time 00:53:02, 95% CI [00:32:36, 01:24:35].”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    At the end of 10 procedures, the estimated mean time and CI continued to decrease: npL1 mean 00:43:31, 95% CI [00:31:05, 01:04:19]; npM1 mean 00:26:28, 95% CI [00:21:50, 00:30:29]; npB1 mean 00:35:18, 95% CI [00:24:34, 00:55:45].

    “At the end of 10 procedures (or approximately mid-way through the assigned target of 20 assessments for the ASHAs), the estimated mean time and CI continues to decrease (npL1 - mean time 00:43:31, 95% CI [00:31:05, 01:04:19]; npM1 - mean time 00:26:28, 95% CI [00:21:50,00:30:29]; npB1 - mean time 00:35:18, 95% CI [00:24:34, 00:55:45]).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Median step times were: Step 1 Demographics 00:02:37 (IQR 00:02:16), Step 2 Medical History 00:01:08 (IQR 00:01:35), Step 3 Risk factor acquisition 00:10:33 (IQR 00:11:22), and Step 4 Decision support 00:01:30 (IQR 00:01:53).

    “Step 1- Demographics with median time of 00:02:37 (IQR 00:02:16), Step 2- Medical History with median time of 00:01:08 (IQR 00:01:35), Step 3 - Risk factor acquisition with median time of 00:10:33 (IQR 00:11:22), and Step 4 - Decision support 00:01:30 (IQR 00:01:53).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Step 3 (risk factor acquisition) took the longest during data collection and showed large variation between ASHAs, with an IQR of 00:11:22.

    “Step 3 (risk factor acquisition) took the longest during data collection and its extensive spread observed from the distribution shows a large variation (IQR 00:11:22) between ASHAs in completing that step.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    At the end of 5 procedures, npM1 had mean time 00:30:33 with 95% CI [00:26:30, 00:32:45], and npB1 had mean time 00:35:45 with 95% CI [00:20:00, 01:03:28].

    “ASHAs npM1 and npB1 have comparable estimate of mean times but the latter has a much wider 95% CI (npM1 - mean time 00:30:33, 95% CI [00:26:30, 00:32:45]; ASHA npB1 - mean time 00:35:45, 95% CI [00:20:00, 01:03:28]).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    npM1 had the narrowest CI [00:21:01, 00:28:27] and npL1 had the widest CI [00:31:58, 00:57:58] for estimated mean procedure time towards the end of the study.

    “From Figure 8, we observe that npM1 is consistent and has the most narrow CI [00:21:01, 00:28:27] while npL1 has the widest CI [00:31:58, 00:57:58] for the estimated mean procedure time towards the end of the study.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    When 15 procedures had been completed by the ASHAs, the estimated mean stabilized while the CI continued to become narrower: npL1 mean 00:41:05, 95% CI [00:30:56, 00:56:24]; npM1 mean 00:26:18, 95% CI [00:22:34, 00:30:22]; npB1 mean 00:34:43, 95% CI [00:25:07, 00:52:08].

    “When 15 procedures have been completed by the ASHAs, the estimated mean stabilizes while CI continues to become narrower (npL1 - mean time 00:41:05, 95% CI [00:30:56, 00:56:24]; npM1 - mean time 00:26:18, 95% CI [00:22:34,00:30:22]; npB1 - mean time 00:34:43, 95% CI [00:25:07, 00:52:08]).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    ASHA npB1 had a Bluetooth usage rate of 61% (17/28 procedures) with mean BP acquisition time 00:05:20; npM1 had a usage rate of 50% (10/28) with mean BP acquisition time 00:07:06; npL1 had a usage rate of 37% (6/16) with mean BP acquisition time 00:08:24.

    “ASHA npB1 had a usage rate of 61% (17/28 procedures) with mean BP acquisition time of 00:05:20 (σ = 00:03:36) while npM1 had a usage rate of 50% (10/28) with mean BP acquisition time of 00:07:06 (σ = 00:02:36). ASHA npL1 had a usage rate of 37% (6/16) with mean BP acquisition time of 00:08:24 (σ = 00:02:56).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given

    The end users had little or no experience with using information and communication technology and could not drive the design.

    “However, our approach differed from conventional practice since the end users had little or no experience with using information and communication technology and could not drive the design.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The three ASHAs npB1, npM1, and npL1 had 3, 7, and 4 years of experience working as an ASHA and performed 28, 20, and 16 risk assessments respectively.

    “We shall refer to the three ASHAs as npB1, npM1, and npL1 and they had 3, 7, and 4 years of experience working as an ASHA and performed 28 (highest number in this study), 20 (median number of assessments in this study), and 16 (lowest number of assessments amongst ASHAs in our study) risk assessments respectively.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    Touch errors were common and frequent among end users.

    “Since the end user base had little or no experience, touch errors were common and frequent.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Infrastructural barriers observed in the pilot study included power constraints, as power supply was limited to fixed times of the day, so low-cost tablets had to be charged frequently or would not function optimally.

    “Infrastructural barriers observed in our pilot study included power constraints as power supply was limited to fixed times of the day, and so the low-cost tablets had to be charged frequently or would not function optimally.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    npL1 performed the fewest assessments, had the highest estimated mean time with a wide 95% CI, low dissemination rate of management recommendations, and the lowest usage rate of the automated Bluetooth feature.

    “npL1 performed the fewest assessments, had the highest estimated mean time with a wide 95% CI, low dissemination rate of management recommendations, and the lowest usage rate of the automated Bluetooth feature.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Overall Bluetooth BP device usage rate was 55% and overall median acquisition time was 00:06:50 (IQR 00:02:33).

    “Overall Bluetooth BP device usage rate was 55% and overall median acquisition time was 00:06:50 (IQR of 00:02:33).”
    Quote in the paperSubstantial claim

  • May combine two claims. The quote only partly states this claim.

    Findingown data

    The CDS tool was field-tested by 11 ASHAs and 3 Primary Health Centre doctors in 3 villages in rural Andhra Pradesh, screening a total of 292 adults aged 40 years and above.

    “The system was field-tested with eleven village healthcare workers and three Primary Health Centre doctors, who screened a total of 292 adults aged 40 years and above.”
    • Also stated in: § Field testing · plain
      “The mobile based CDS tool was field tested by 11 ASHAs who performed door-to-door screening of community participants in 3 villages in rural Andhra Pradesh, India.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Before the 10th procedure, Bluetooth usage rates were 40% for npB1, 50% for npM1, and 10% for npL1; after the 10th procedure, the usage rates were 65%, 44%, and 80% respectively.

    “Before the 10th procedure, Bluetooth usage rate was 40% for npB1, 50% for npM1, and 10% for npL1 while after the 10th procedure (midway between their ‘assigned’ target of 20 procedures as previously described in Section ‘Field testing’), the usage rates were 65%, 44%, and 80% respectively.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Only 81% of participants screened by ASHA npL1 were told about their next visit for follow-ups, while ASHA npB1 disseminated the information to 93% of her participants.

    “Also only 81% participants screened by ASHA npL1 were told about their next visit for follow-ups while in contrast, ASHA npB1 disseminated the information to 93% of her participants.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Out of 227 patients assessed, 14 had an erroneous value of glucose level entered; the median error was 9.55 mg/dL with IQR 35.75 mg/dL (0.53 mmol/L with IQR 1.99 mmol/L).

    “Out of 227 patients assessed, 14 patients had an erroneous value of glucose level entered. The median error was 9.55 mg/dL with IQR 35.75 mg/dL (0.53 mmol/L with IQR 1.99 mmol/L).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The three ASHAs chosen for detailed usage analysis had a mean age of 29 ± 2 years and had experience using a mobile phone at the time of the study.

    “The three distinct ASHAs chosen for detailed usage analysis had a mean age of 29 ± 2 years and had the experience of using a mobile phone at the time of this study.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    ASHAs npB1, npM1, and npL1 took 00:27:28 (IQR 00:14:05), 00:24:20 (IQR 00:12:12), and 00:33:53 (IQR 00:32:41) respectively.

    “ASHAs npB1, npM1, and npL1 took 00:27:28 (IQR 00:14:05), 00:24:20 (IQR 00:12:12), and 00:33:53 (IQR 00:32:41) respectively.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductcitation

    A validated Blood Pressure device (Stabil-O-Graph) was used, which could interface with the tablet via Bluetooth and send three BP measurements to the tablet.

    “Furthermore, a validated Blood Pressure (BP) device (Stabil-O-Graph [25]) was used, which could interface with the tablet via Bluetooth and send three BP measurements to the tablet.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [25] Westhoff T, Schmidt S, Zidek W, Van der Giet M. Validation of the Stabil-O-Graph blood pressure self-measurement device. J Hum Hypertens. 2007; 22(3):233–5. source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductnone given

    The main limitation in this pilot study was the limited sample size, and the study was not designed to be representative.

    “The main limitation in this pilot study was the limited sample size. However, this was not designed to be representative.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The decrease in median completion time with more procedures indicated the ASHA's increased familiarity with the process and provided evidence for expected or optimal usage and actual usage.

    “There was a decrease in median completion time with more number of procedures performed. This indicated the ASHA’s increased familiarity with the process as well as provides evidence for expected or optimal usage and actual usage.”
    Quote in the paperNot a substantial claim

  • May combine two claims. The quote only partly states this claim.

    Study design and conductown data

    The prediction and management applications were stringently validated in two stages: code validation against an external dataset from the Andhra Pradesh Rural Health Initiative, and manual assessment by an independent physician on 100 randomly selected individuals.

    “The prediction and management applications were stringently validated in two stages.”
    • Also stated in: § Computing 10-year absolute CVD risk · plain
      “In the second stage, the same dataset was used where 100 individuals were randomly selected by a physician not involved in the algorithm development.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [17] Chow C, Cardona M, Raju PK, Iyengar S, Sukumar A, Raju R, et al. Cardiovascular disease and risk factors among 345 adults in rural India- the Andhra Pradesh Rural Health Initiative. Int J Cardiol. 2007; 116(2):180–5. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    ASHA npM1 was the most consistent performer, with the lowest estimated mean time and smallest 95% CI and an approximately average rate of disseminating management recommendations.

    “With the lowest estimated mean time and smallest 95% CI as well as an approximately average rate of disseminating management recommendations, ASHA npM1 was the most consistent performer.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The in-depth design strategies resulted in a tool that could be easily integrated within the workflow of the ASHAs, as reflected by the majority agreeing with its ease of use, usefulness, and increased speed of assessments over time.

    “The in-depth design strategies resulted in a tool that could be easily integrated within the workflow of the ASHAs, as reflected by the majority agreeing with its easy of use, usefulness, and increased speed of assessments over time.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The design thinking process cohesively involved local community participants and end-users, and therefore differs from global health projects which push solutions onto the community.

    “Another key aspect of our study is the design thinking process that has cohesively involved the local community participants and end-users, and therefore differs from global health projects which ’push’ solutions onto the community.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The errors reported from manual data entry during blood glucose measurement demonstrate that transcription and transposition errors were likely and that the erroneous values had a wide range.

    “The errors reported from manual data entry during blood glucose measurement demonstrate that transcription and transposition errors were likely and the erroneous values had a wide range.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    For npL1, Bluetooth usage increased from 10% before her 10th procedure to 80% thereafter, which may indicate a longer learning curve and need for additional attention or performance monitoring.

    “However, with regard to Bluetooth usage, we observe that even though only a single attempt (or 10%) was made before her 10th procedure, her usage rate increased to 80% thereafter. Though this may indicate a longer learning curve, ASHA npL1 may be identified as one that would need additional attention or performance monitoring.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    An important factor in the success of any technology-based intervention depends on how well it can fit within the needs of the users and the environment.

    “An important factor in the success of any technology-based intervention depends on how well it can fit within the needs of the users and the environment [20].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [20] Nuseibeh B, Easterbrook S. Requirements engineering: A roadmap. In: Proceedings of the Conference on The Future of Software Engineering. ICSE ’00, New York, NY, USA: ACM: 2000. p. 35–46. http://doi.acm.org/10.1145/336512.336523 .

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Ali et al. highlight the need for well-designed investigations on the feasibility of using technology in clinical decision support.

    “Other studies in LMICs, such as that by Ali et al. [15] who reviewed electronic CDS tools for diabetes care, highlight the need for well-designed investigations on the feasibility of using technology in clinical decision support.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [15] Ali MK, Shah S, Tandon N. Review of electronic decision-support tools for diabetes care: a viable option for low- and middle-income countries?J Diabetes Sci Technol. 2011; 5(3):553–70. source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    In India, approximately 70% of the total population live in rural areas, and the doctor to patient ratio is lesser in rural areas (1:20000) as compared to urban areas (1:2000).

    “In developing countries like India, even though approximately 70% of the total population live in rural areas, the doctor to patient ratio is lesser in rural areas (1:20000) as compared to the urban areas (1:2000) [4].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [4] PriceWaterhouseCoopers. Report on health infrastructure and services financing in india. 2012.

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Communication through the risk meter found the lowest adoption in Table 4, possibly due to difficulties in the ASHA's understanding of the risk projection feature.

    “With regard to POC decision support, communication through the risk meter found the lowest adoption in Table 4 and this is possibly due to difficulties in the ASHA’s understanding of the risk projection feature.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    By recording user interactions with the mobile application, the study could gauge the end-user's behaviour and the effectiveness of the tool's features such as the rate of dissemination of point-of-care CVD management recommendations.

    “By recording user interactions with the mobile application, we could thus gauge the end-user’s behaviour and effectiveness of the tool’s features such as the rate of dissemination of point-of-care CVD management recommendations.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The colour-coded ranges in the WHO risk charts indicated five levels of CVD risk for different values of risk factors.

    “The colour-coded ranges in the WHO risk charts indicated five levels of CVD risk for different values of risk factors [16].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [16] World Health Organization/International Society for Hypertension. Pocket guidelines for Assessment and Management of Cardiovascular Risk with WHO/ISH Cardiovascular Risk Prediction Charts for WHO epidemiological Sub-regions SEAR-D. 2013.

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    The tool was developed using an agile development approach with iterative prototyping and user feedback, because requirements could not be gauged thoroughly through a needs assessment.

    “The requirements of our end-users compounded with the uncertainties in technical infrastructure (such as the availability of uninterrupted 2G/3G internet connectivity) could not be gauged thoroughly through a needs assessment. Therefore, the agile development approach was followed in our study to iteratively design prototypes and elicit feedback from the end-users.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims. The quote only partly states this claim.

    Study design and conductreasoning

    A multidisciplinary team and phases of prototyping and user assessment were employed to balance system and user requirements.

    “firstly we employed a multidisciplinary team comprising an engineer, local physician, sociologist, and an expert physician to balance system requirements”
    • Also stated in: § CDS tool design · plain
      “Secondly, we performed phases of prototyping and user assessment”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    To assess the extent of errors, blood glucose values stored in the glucometers were downloaded and compared with values entered by the ASHA in the tablet during risk assessment, with care taken to ensure the compared readings were taken at the same time.

    “However, to assess the extent of errors, the blood glucose values stored in the glucometers were downloaded and compared with those values entered by the ASHA in the tablet during risk assessment. Care was taken to ensure that the glucose readings being compared were taken at the same time.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The estimate of 95% CI and mean procedure time was obtained using a bootstrapped sample that included risk assessments performed up until and including that time period, to account for uneven sampling bias.

    “The estimate of 95% CI and mean procedure time was obtained using a bootstrapped sample that included risk assessments performed up until and including that time period in the study. This was performed to account for uneven sampling bias (for example, at the 5th procedure, procedure 1 till 5 were taken as samples and bootstrapped).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Four out of 219 procedures were not considered because the risk assessments were performed non-sequentially by the ASHAs.

    “Four out of 219 procedures were not considered as the risk assessments were performed non-sequentially by the ASHAs.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Field evaluation found the mHealth platform to be acceptable and feasible for use.

    “Field evaluation found the platform to be acceptable and feasible for use.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The study was approved by the ethics committee of Centre for Chronic Disease and Control, India and the University of Sydney, Australia, and informed written consent was obtained from all participants contributing data.

    “The study was approved by the ethics committee of Centre for Chronic Disease and Control, India and the University of Sydney, Austrlia (registration: CTRI/2013/06/003753). Informed, written consent was obtained from all participants contributing data in the study.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationcitation

    The analytics framework was beneficial to understand learnability, an indicator of how easily the ASHAs performed tasks, and efficiency, an analysis of the ASHA's ability to quickly perform the task they had learnt.

    “This was beneficial to understand learnability [32], which is an indicator of how easily the ASHAs performed tasks as well as efficiency [33], which is an analysis of the ASHA’s ability to quickly perform the task they have learnt.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [32] Abran A, Khelifi A, Suryn W, Seffah A. Usability meanings and interpretations in ISO standards. Software Qual J. 2003; 11(4):325–38. source

      Not checked in the free run.

    • cites [33] Frøkjær E, Hertzum M, Hornbæk K. Measuring usability: Are effectiveness, efficiency, and satisfaction really correlated?. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI ’00, New York, NY, USA: ACM: 2000. p. 345–52.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The CDS tool was designed and developed using the agile development methodology with close engagement of the ASHAs and physicians.

    “The CDS tool was designed and developed using the agile development methodology with the close engagement of the ASHAs and physicians.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    Detailed usage patterns could be gauged from analysing the interaction pattern of ASHAs with the mobile application.

    “Detailed usage patterns could be gauged from analysing the interaction pattern of ASHAs with the mobile application.”
    Quote in the paperNot a substantial claim
46 of 46

  • The paper relies on this without support.

    Access to prevention and control of CVD at the primary care level is poor in these communities.

    “Access to prevention and control of CVD at the primary care level is poor in these communities.”

  • The paper relies on this without support.

    The existing physician-centric, western style care is unsustainable in these regions.

    “The existing physician-centric, western style care is therefore unsustainable in these regions and there is a need for more innovative solutions.”

  • The paper relies on this without support.

    The three selected ASHAs represent all ASHAs in performance.

    “Data from the three ASHAs, representing all the ASHAs in performance, were analysed individually to obtain an estimate of their mean procedure time over the course of the pilot study.”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • npM1's Bluetooth usage fraction does not equal 50%

    Minor

    Ten uses in 28 procedures is 35.7%, not 50%. The paper also states that npM1 performed 20 assessments, for which 10 uses would equal 50%.

    Reported 50 · recomputed 35.714286

  • Risk-meter usage was not lower for all three ASHAs

    Minor

    The text says risk-meter usage was much lower than usage of the other sections for all three ASHAs, but Table 4 gives npL1 the same 81% usage for all three sections.

2 of 2

Cites

Flagged first, then by citations

Research works printed but not linked: 5

  1. Nuseibeh B, Easterbrook S. Requirements engineering: A roadmap. In: Proceedings of the Conference on The Future of Software Engineering. ICSE ’00, New York, NY, USA: ACM: 2000. p. 35–46. http://doi.acm.org/10.1145/336512.336523 . · DOI
  2. Cheng BHC, Atlee JM. Research directions in requirements engineering. In: 2007 Future of Software Engineering. FOSE ’07, Washington, DC, USA: IEEE Computer Society: 2007. p. 285–303.
  3. Raghu A, Praveen D, Peiris D, Tarassenko L, Clifford G. Lessons from the evaluation of a clinical decision support tool for cardiovascular disease risk management in rural india. In: UNESCO Tech4Dev 2014 conference. Lausanne, Switzerland: Springer: 2014.
  4. Frøkjær E, Hertzum M, Hornbæk K. Measuring usability: Are effectiveness, efficiency, and satisfaction really correlated?. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI ’00, New York, NY, USA: ACM: 2000. p. 345–52.
  5. Tourangeau R, Rips LJ, Rasinski K. The Psychology of Survey Response. New York: Cambridge University Press; 1998.

Cited by

Sorted by citations

Authors
Raghu, A., Praveen, D., Peiris, D., Tarassenko, L., & Clifford, G.
Affiliations
  • University of Oxford (GB)
  • The University of Sydney (AU)
  • Georgia Institute of Technology (US)
Corresponding author
Raghu, Arvind
ORCID
Venue
BMC Medical Informatics and Decision Making
Publisher
Springer Science and Business Media LLC
Published
2015-04-29
Volume
15
Issue
1
Pages
36-36
ISSN
1472-6947 (ISSN-L)
DOI
10.1186/s12911-015-0148-4
PMC
PMC4430914
OpenAlex
W2011947769
Cited by
89
References
19
Citations by year
2026: 2 · 2025: 11 · 2024: 8 · 2023: 6 · 2022: 17 · 2021: 8 · 2020: 6 · 2019: 9 · 2018: 4 · 2017: 8 · 2016: 7 · 2015: 3
FWCI
13.37
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • United States Agency for International Development
  • Wellcome Trust (WT 088877/Z/09/Z, 088877/Z/09/Z)
  • University of Oxford
  • Australian Agency for International Development
  • Medical Research Council
  • Engineering and Physical Sciences Research Council
  • National Health and Medical Research Council (1040147)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords
cardiovascular risk, clinical decision support, mobile health, electronic health records, primary health centers, resource-limited settings, cardiovascular screening, user-centered design, system usability, manual data entry errors, rural India
MeSH terms
Adult, Cardiovascular Diseases, Community Health Services, Humans, India, Telemedicine, Point-of-Care Systems, Decision Support Systems, Clinical, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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