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Farmer AJ, Allen J, Bartlett YK, Bower P, Chi Y, French DP, Gudgin B, Holmes E, Horne R, Hughes DA, Jones L, Kenning C, Locock L, McSharry J, Miles L, Newhouse N, Rea R, Robinson S, Tarassenko L, Velardo C, Williams N, Yu LM. Supporting people with type 2 diabetes in effective use of their medicine through mobile health technology integrated with clinical care (SuMMiT-D pilot): results of a feasibility randomised trial. Pilot Feasibility Stud 2024; 10:15. [PMID: 38273420 PMCID: PMC10809651 DOI: 10.1186/s40814-023-01429-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 12/19/2023] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND The purpose of this 6-month intervention pilot feasibility randomised trial was to test sending brief messages using mobile phones to promote self-management through taking medication as prescribed to people with type 2 diabetes. This was to inform the design and conduct of a future large-scale United Kingdom-based clinical trial and establish the feasibility of recruitment, the technology used, follow-up, and data collection. METHODS A multicentre individually randomised, controlled parallel group trial in primary care, recruiting adults (≥ 35 years) with type 2 diabetes in England. Consenting participants were randomly allocated to receive short message system text messages up to four times a week, or usual care, for a period of 6 months; messages contained behavioural change techniques targeting medication use. The primary outcome was the rate of recruitment to randomisation of participants to the trial with a planned rate of 22 participants randomised per month. The study also aimed to establish the feasibility of follow-up at 6 months, with an aim of retaining more than 80% of participants. Data, including patient-reported measures, were collected at baseline and the end of the 6-month follow-up period, and a notes review was completed at 24 months. RESULTS The trial took place between 26 November 2018 and 30 September 2019. In total 209 participants were randomly allocated to intervention (n = 103) or usual care (n = 106). The maximum rate of monthly recruitment to the trial was 60-80 participants per month. In total, 12,734 messages were sent to participants. Of these messages, 47 were identified as having failed to be sent by the service provider. Participants sent 2,864 messages to the automated messaging system. Baseline data from medical records were available for > 90% of participants with the exception of cholesterol (78.9%). At 6 months, a further HbA1c measurement was reported for 67% of participants. In total medical record data were available at 6 months for 207 (99.0%) of participants and completed self-report data were available for 177 (84.7%) of participants. CONCLUSION The feasibility of a large-scale randomised evaluation of brief message intervention for people with type 2 diabetes appears to be high using this efficient design. Failure rate of sending messages is low, rapid recruitment was achieved among people with type 2 diabetes, clinical data is available on participants from routine medical records and self-report of economic measures was acceptable. TRIAL REGISTRATION ISCTRN ISRCTN13404264. Registered on 10 October 2018.
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Affiliation(s)
- Andrew J Farmer
- University of Oxford, Oxford, UK.
- Nuffield Department of Primary Care Health Sciences, Woodstock Road, Oxford, OX2 6GG, UK.
| | | | | | | | - Yuan Chi
- University of Oxford, Oxford, UK
| | | | | | | | | | | | | | | | | | | | - Lisa Miles
- University of Manchester, Manchester, UK
| | | | - Rustam Rea
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
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Rouyard T, Leal J, Salvi D, Baskerville R, Velardo C, Gray A. An Intuitive Risk Communication Tool to Enhance Patient-Provider Partnership in Diabetes Consultation. J Diabetes Sci Technol 2022; 16:988-994. [PMID: 33655766 PMCID: PMC9264433 DOI: 10.1177/1932296821995800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
INTRODUCTION This technology report introduces an innovative risk communication tool developed to support providers in communicating diabetes-related risks more intuitively to people with type 2 diabetes mellitus (T2DM). METHODS The development process involved three main steps: (1) selecting the content and format of the risk message; (2) developing a digital interface; and (3) assessing the usability and usefulness of the tool with clinicians through validated questionnaires. RESULTS The tool calculates personalized risk information based on a validated simulation model (United Kingdom Prospective Diabetes Study Outcomes Model 2) and delivers it using more intuitive risk formats, such as "effective heart age" to convey cardiovascular risks. Clinicians reported high scores for the usability and usefulness of the tool, making its adoption in routine care promising. CONCLUSIONS Despite increased use of risk calculators in clinical care, this is the first time that such a tool has been developed in the diabetes area. Further studies are needed to confirm the benefits of using this tool on behavioral and health outcomes in T2DM populations.
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Affiliation(s)
- Thomas Rouyard
- Nuffield Department of Population
Health, Health Economics Research Centre, University of Oxford, Oxford, UK
- Research Center for Health Policy and
Economics, Hitotsubashi University, Tokyo, Japan
- Thomas Rouyard, DPhil, Adjunct Assistant
Professor, Research Center for Health Policy and Economics, Hitotsubashi
University, 2-1 Naka, Kunitachi, Tokyo, 186-8601, Japan.
| | - José Leal
- Nuffield Department of Population
Health, Health Economics Research Centre, University of Oxford, Oxford, UK
| | - Dario Salvi
- Department of Engineering Science,
Institute of Biomedical Engineering, University of Oxford, Oxford, UK
- School of Arts, Culture and
Communication, Malmö University, Malmö, Sweden
| | - Richard Baskerville
- Nuffield Department of Primary Care
Health Sciences, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- Department of Engineering Science,
Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Alastair Gray
- Nuffield Department of Population
Health, Health Economics Research Centre, University of Oxford, Oxford, UK
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Chappell LC, Tucker KL, Galal U, Yu LM, Campbell H, Rivero-Arias O, Allen J, Band R, Chisholm A, Crawford C, Dougall G, Engonidou L, Franssen M, Green M, Greenfield S, Hinton L, Hodgkinson J, Lavallee L, Leeson P, McCourt C, Mackillop L, Sandall J, Santos M, Tarassenko L, Velardo C, Wilson H, Yardley L, McManus RJ. Effect of Self-monitoring of Blood Pressure on Blood Pressure Control in Pregnant Individuals With Chronic or Gestational Hypertension: The BUMP 2 Randomized Clinical Trial. JAMA 2022; 327:1666-1678. [PMID: 35503345 PMCID: PMC9066282 DOI: 10.1001/jama.2022.4726] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 03/11/2022] [Indexed: 01/02/2023]
Abstract
Importance Inadequate management of elevated blood pressure is a significant contributing factor to maternal deaths. The role of blood pressure self-monitoring in pregnancy in improving clinical outcomes for the pregnant individual and infant is unclear. Objective To evaluate the effect of blood pressure self-monitoring, compared with usual care alone, on blood pressure control and other related maternal and infant outcomes, in individuals with pregnancy hypertension. Design, Setting, and Participants Unblinded, randomized clinical trial that recruited between November 2018 and September 2019 in 15 hospital maternity units in England. Individuals with chronic hypertension (enrolled up to 37 weeks' gestation) or with gestational hypertension (enrolled between 20 and 37 weeks' gestation). Final follow-up was in May 2020. Interventions Participants were randomized to either blood pressure self-monitoring using a validated monitor and a secure telemonitoring system in addition to usual care (n = 430) or to usual care alone (n = 420). Usual care comprised blood pressure measured by health care professionals at regular antenatal clinics. Main Outcomes and Measures The primary maternal outcome was the difference in mean systolic blood pressure recorded by health care professionals between randomization and birth. Results Among 454 participants with chronic hypertension (mean age, 36 years; mean gestation at entry, 20 weeks) and 396 with gestational hypertension (mean age, 34 years; mean gestation at entry, 33 weeks) who were randomized, primary outcome data were available from 444 (97.8%) and 377 (95.2%), respectively. In the chronic hypertension cohort, there was no statistically significant difference in mean systolic blood pressure for the self-monitoring groups vs the usual care group (133.8 mm Hg vs 133.6 mm Hg, respectively; adjusted mean difference, 0.03 mm Hg [95% CI, -1.73 to 1.79]). In the gestational hypertension cohort, there was also no significant difference in mean systolic blood pressure (137.6 mm Hg compared with 137.2 mm Hg; adjusted mean difference, -0.03 mm Hg [95% CI, -2.29 to 2.24]). There were 8 serious adverse events in the self-monitoring group (4 in each cohort) and 3 in the usual care group (2 in the chronic hypertension cohort and 1 in the gestational hypertension cohort). Conclusions and Relevance Among pregnant individuals with chronic or gestational hypertension, blood pressure self-monitoring with telemonitoring, compared with usual care, did not lead to significantly improved clinic-based blood pressure control. Trial Registration ClinicalTrials.gov Identifier: NCT03334149.
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Affiliation(s)
- Lucy C. Chappell
- Department of Women and Children’s Health, King’s College London, London, United Kingdom
| | - Katherine L. Tucker
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ushma Galal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Helen Campbell
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Oliver Rivero-Arias
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rebecca Band
- Department of Psychology, University of Southampton, Southampton, United Kingdom
| | - Alison Chisholm
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carole Crawford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Greig Dougall
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lazarina Engonidou
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Marloes Franssen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Marcus Green
- Action on Pre-eclampsia, The Stables, Evesham, Worcestershire, United Kingdom
| | - Sheila Greenfield
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Lisa Hinton
- The Healthcare Improvement Studies Institute, University of Cambridge, Cambridge, United Kingdom
| | - James Hodgkinson
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Layla Lavallee
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Paul Leeson
- Cardiovascular Clinical Research Facility, Division of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
| | - Christine McCourt
- Centre for Maternal and Child Health Research, City, University of London, London, United Kingdom
| | - Lucy Mackillop
- Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Jane Sandall
- Department of Women and Children’s Health, King’s College London, London, United Kingdom
| | - Mauro Santos
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Hannah Wilson
- Department of Women and Children’s Health, King’s College London, London, United Kingdom
| | - Lucy Yardley
- Department of Psychology, University of Southampton, Southampton, United Kingdom
- School of Psychological Science, University of Bristol, Bristol, United Kingdom
| | - Richard J. McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Tucker KL, Mort S, Yu LM, Campbell H, Rivero-Arias O, Wilson HM, Allen J, Band R, Chisholm A, Crawford C, Dougall G, Engonidou L, Franssen M, Green M, Greenfield S, Hinton L, Hodgkinson J, Lavallee L, Leeson P, McCourt C, Mackillop L, Sandall J, Santos M, Tarassenko L, Velardo C, Yardley L, Chappell LC, McManus RJ. Effect of Self-monitoring of Blood Pressure on Diagnosis of Hypertension During Higher-Risk Pregnancy: The BUMP 1 Randomized Clinical Trial. JAMA 2022; 327:1656-1665. [PMID: 35503346 PMCID: PMC9066279 DOI: 10.1001/jama.2022.4712] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
IMPORTANCE Inadequate management of elevated blood pressure (BP) is a significant contributing factor to maternal deaths. Self-monitoring of BP in the general population has been shown to improve the diagnosis and management of hypertension; however, little is known about its use in pregnancy. OBJECTIVE To determine whether self-monitoring of BP in higher-risk pregnancies leads to earlier detection of pregnancy hypertension. DESIGN, SETTING, AND PARTICIPANTS Unblinded, randomized clinical trial that included 2441 pregnant individuals at higher risk of preeclampsia and recruited at a mean of 20 weeks' gestation from 15 hospital maternity units in England between November 2018 and October 2019. Final follow-up was completed in April 2020. INTERVENTIONS Participating individuals were randomized to either BP self-monitoring with telemonitoring (n = 1223) plus usual care or usual antenatal care alone (n = 1218) without access to telemonitored BP. MAIN OUTCOMES AND MEASURES The primary outcome was time to first recorded hypertension measured by a health care professional. RESULTS Among 2441 participants who were randomized (mean [SD] age, 33 [5.6] years; mean gestation, 20 [1.6] weeks), 2346 (96%) completed the trial. The time from randomization to clinic recording of hypertension was not significantly different between individuals in the self-monitoring group (mean [SD], 104.3 [32.6] days) vs in the usual care group (mean [SD], 106.2 [32.0] days) (mean difference, -1.6 days [95% CI, -8.1 to 4.9]; P = .64). Eighteen serious adverse events were reported during the trial with none judged as related to the intervention (12 [1%] in the self-monitoring group vs 6 [0.5%] in the usual care group). CONCLUSIONS AND RELEVANCE Among pregnant individuals at higher risk of preeclampsia, blood pressure self-monitoring with telemonitoring, compared with usual care, did not lead to significantly earlier clinic-based detection of hypertension. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03334149.
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Affiliation(s)
- Katherine L. Tucker
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sam Mort
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Helen Campbell
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Oliver Rivero-Arias
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Hannah M. Wilson
- Department of Women and Children’s Health, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rebecca Band
- Department of Psychology, University of Southampton, Southampton, United Kingdom
| | - Alison Chisholm
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carole Crawford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Greig Dougall
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lazarina Engonidou
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Marloes Franssen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Marcus Green
- Action on Pre-eclampsia, The Stables, Evesham, Worcestershire, United Kingdom
| | - Sheila Greenfield
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Lisa Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- The Healthcare Improvement Studies Institute, University of Cambridge, Cambridge, United Kingdom
| | - James Hodgkinson
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Layla Lavallee
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Paul Leeson
- Cardiovascular Clinical Research Facility, RDM Division of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
| | - Christine McCourt
- Centre for Maternal and Child Health Research, City, University of London, London, United Kingdom
| | - Lucy Mackillop
- Nuffield Department of Women’s and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Jane Sandall
- Department of Women and Children’s Health, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Mauro Santos
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Lucy Yardley
- Department of Psychology, University of Southampton, Southampton, United Kingdom
- School of Psychological Science, University of Bristol, Bristol, United Kingdom
| | - Lucy C. Chappell
- Department of Women and Children’s Health, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Richard J. McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Farmer A, Jones L, Newhouse N, Kenning C, Williams N, Chi Y, Bartlett YK, Plumpton C, McSharry J, Cholerton R, Holmes E, Robinson S, Allen J, Gudgin B, Velardo C, Rutter H, Horne R, Tarassenko L, Williams V, Locock L, Rea R, Yu LM, Hughes D, Bower P, French D. Supporting People With Type 2 Diabetes in the Effective Use of Their Medicine Through Mobile Health Technology Integrated With Clinical Care to Reduce Cardiovascular Risk: Protocol for an Effectiveness and Cost-effectiveness Randomized Controlled Trial. JMIR Res Protoc 2022; 11:e32918. [PMID: 35188478 PMCID: PMC8902673 DOI: 10.2196/32918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/12/2021] [Accepted: 11/17/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Type 2 diabetes is a common lifelong condition that affects over 400 million people worldwide. The use of effective medications and active self-management can reduce the risk of serious complications. However, people often have concerns when starting new medications and face difficulties in taking their medications regularly. Support provided by brief messages delivered through mobile phone-based SMS text messages can be effective in some long-term conditions. We have identified promising behavior change techniques (BCTs) to promote medication adherence in this population via a systematic review and developed SMS text messages that target these BCTs. Feasibility work has shown that these messages have fidelity to intended BCTs, are acceptable to patients, and are successful in changing the intended determinants of medication adherence. We now plan to test this intervention on a larger scale in a clinical trial. OBJECTIVE The aim of this trial is to determine the effectiveness and cost-effectiveness of this intervention for reducing cardiovascular risk in people with type 2 diabetes by comparing it with usual care. METHODS The trial will be a 12-month, multicenter, individually randomized controlled trial in primary care and will recruit adults (aged ≥35 years) with type 2 diabetes in England. Consenting participants will be randomized to receive short SMS text messages intended to affect a change in medication adherence 3 to 4 times per week in addition to usual care. The aim is to test the effectiveness and cost-effectiveness of the intervention when it is added to usual care. The primary clinical outcome will be a composite cardiovascular risk measure. Data including patient-reported measures will be collected at baseline, at 13 and 26 weeks, and at the end of the 12-month follow-up period. With 958 participants (479 in each group), the trial is powered at 92.5% to detect a 4-percentage point difference in cardiovascular risk. The analysis will follow a prespecified plan. A nested quantitative and qualitative process analysis will be used to examine the putative mechanisms of behavior change and wider contextual influences. A health economic analysis will be used to assess the cost-effectiveness of the intervention. RESULTS The trial has completed the recruitment phase and is in the follow-up phase. The publication of results is anticipated in 2024. CONCLUSIONS This trial will provide evidence regarding the effectiveness and cost-effectiveness of this intervention for people with type 2 diabetes. TRIAL REGISTRATION ISRCTN Registry ISRCTN15952379; https://www.isrctn.com/ISRCTN15952379. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/32918.
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Affiliation(s)
- Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Louise Jones
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Nikki Newhouse
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Cassandra Kenning
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom
| | - Nicola Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Yuan Chi
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Y Kiera Bartlett
- Manchester Centre for Health Psychology, University of Manchester, Manchester, United Kingdom
| | - Catrin Plumpton
- Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, United Kingdom
| | - Jenny McSharry
- Health Behaviour Change Research Group, School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Rachel Cholerton
- Manchester Centre for Health Psychology, University of Manchester, Manchester, United Kingdom
| | - Emily Holmes
- Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, United Kingdom
| | - Stephanie Robinson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Bernard Gudgin
- Patient Advocate, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
- Sensyne Health plc, Oxford, United Kingdom
| | - Heather Rutter
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Rob Horne
- Centre for Behavioural Medicine, University College London, London, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | | | - Louise Locock
- Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom
| | - Rustam Rea
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Dyfrig Hughes
- Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, United Kingdom
| | - Peter Bower
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom
| | - David French
- Manchester Centre for Health Psychology, University of Manchester, Manchester, United Kingdom
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Armitage L, Chi Y, Santos M, Lawson B, Areia C, Velardo C, Watkinson P, Tarassenko L, Costa M, Farmer A. Monitoring activity of Hip Injury Patients (MoHIP): A sub-study of the World Hip Trauma Evaluation Observational Cohort Study. Physiotherapy 2021. [DOI: 10.1016/j.physio.2021.10.140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Chi Y, Velardo C, Allen J, Robinson S, Riga E, Judge D, Tarassenko L, Farmer AJ. Correction: System Architecture for "Support Through Mobile Messaging and Digital Health Technology for Diabetes" (SuMMiT-D): Design and Performance in Pilot and Randomized Controlled Feasibility Studies. JMIR Form Res 2021; 5:e29451. [PMID: 33835933 PMCID: PMC8065563 DOI: 10.2196/29451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 04/07/2021] [Indexed: 11/13/2022] Open
Abstract
[This corrects the article DOI: 10.2196/18460.].
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Affiliation(s)
- Yuan Chi
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Stephanie Robinson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Evgenia Riga
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - David Judge
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Chi Y, Velardo C, Allen J, Robinson S, Riga E, Judge D, Tarassenko L, Farmer AJ. System Architecture for "Support Through Mobile Messaging and Digital Health Technology for Diabetes" (SuMMiT-D): Design and Performance in Pilot and Randomized Controlled Feasibility Studies. JMIR Form Res 2021; 5:e18460. [PMID: 33769299 PMCID: PMC8034865 DOI: 10.2196/18460] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 08/20/2020] [Accepted: 12/17/2020] [Indexed: 02/06/2023] Open
Abstract
Background Diabetes is a highly prevalent long-term condition with high morbidity and mortality rates. People with diabetes commonly worry about their diabetes medicines and do not always take them regularly as prescribed. This can lead to poor diabetes control. The Support Through Mobile Messaging and Digital Health Technology for Diabetes (SuMMiT-D) study aims to deliver brief messages as tailored interventions to support people with type 2 diabetes in better use of their diabetes medicines and to improve treatment adherence and health outcomes. Objective This paper describes the overall architecture of a tailored intervention delivery system used in the pilot and randomized controlled feasibility studies of SuMMiT-D and reports its performance. Methods The SuMMiT-D system includes several platforms and resources to recruit participants and deliver messages as tailored interventions. Its core component is called the clinical system and is responsible for interacting with the participants by receiving and sending SMS text messages from and to them. The personalization and tailoring of brief messages for each participant is based on a list of built-in commands that they can use. Results For the pilot study, a total of 48 participants were recruited; they had a median age of 64 years (first quartile, third quartile [Q1, Q3: 54.5, 69]). For the feasibility study, a total of 209 participants were recruited and randomly assigned to either the control or intervention group; they had a median age of 65 years (Q1, Q3: 56, 71), with 41.1% (86/209) being female. The participants used the SuMMiT-D system for up to 6 months (26 weeks) and had a wide range of different interactions with the SuMMiT-D system while tailored interventions were being delivered. For both studies, we had low withdrawal rates: only 4.2% and 5.3% for the pilot and feasibility studies, respectively. Conclusions A system was developed to successfully deliver brief messages as tailored health interventions to more than 250 people with type 2 diabetes via SMS text messages. On the basis of the low withdrawal rates and positive feedback received, it can be inferred that the SuMMiT-D system is robust, user-friendly, useful, and positive for most participants. From the two studies, we found that online recruitment was more efficient than recruitment via postal mail; a regular SMS text reminder (eg, every 4 weeks) can potentially increase the participants’ interactions with the system. Trial Registration ISRCTN Registry ISRCTN13404264; http://www.isrctn.com/ISRCTN13404264
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Affiliation(s)
- Yuan Chi
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Stephanie Robinson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Evgenia Riga
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - David Judge
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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9
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Velardo C, Clifton D, Hamblin S, Khan R, Tarassenko L, Mackillop L. Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation. J Med Internet Res 2021; 23:e21435. [PMID: 33688832 PMCID: PMC7991989 DOI: 10.2196/21435] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/17/2020] [Accepted: 01/17/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Successful management of gestational diabetes mellitus (GDM) reduces the risk of morbidity in women and newborns. A woman's blood glucose readings and risk factors are used by clinical staff to make decisions regarding the initiation of pharmacological treatment in women with GDM. Mobile health (mHealth) solutions allow the real-time follow-up of women with GDM and allow timely treatment and management. Machine learning offers the opportunity to quickly analyze large quantities of data to automatically flag women at risk of requiring pharmacological treatment. OBJECTIVE The aim of this study is to assess whether data collected through an mHealth system can be analyzed to automatically evaluate the switch to pharmacological treatment from diet-based management of GDM. METHODS We collected data from 3029 patients to design a machine learning model that can identify when a woman with GDM needs to switch to medications (insulin or metformin) by analyzing the data related to blood glucose and other risk factors. RESULTS Through the analysis of 411,785 blood glucose readings, we designed a machine learning model that can predict the timing of initiation of pharmacological treatment. After 100 experimental repetitions, we obtained an average area under the receiver operating characteristic curve of 0.80 (SD 0.02) and an algorithm that allows the flexibility of setting the operating point rather than relying on a static heuristic method, which is currently used in clinical practice. CONCLUSIONS Using real-time data collected via an mHealth system may further improve the timeliness of the intervention and potentially improve patient care. Further real-time clinical testing will enable the validation of our algorithm using real-world data.
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Affiliation(s)
- Carmelo Velardo
- Sensyne Health, plc, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - David Clifton
- Sensyne Health, plc, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | | | - Rabia Khan
- Sensyne Health, plc, Oxford, United Kingdom
| | - Lionel Tarassenko
- Sensyne Health, plc, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Lucy Mackillop
- Sensyne Health, plc, Oxford, United Kingdom
- Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Nuffield Department of Women's Reproductive Health, University of Oxford, Oxford, United Kingdom
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10
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Whelan M, Biggs C, Areia C, King E, Lawson B, Newhouse N, Ding X, Velardo C, Bafadhel M, Tarassenko L, Watkinson P, Clifton D, Farmer A. Recruiting patients to a digital self-management study whilst in hospital for a chronic obstructive pulmonary disease exacerbation: A feasibility analysis. Digit Health 2021; 7:20552076211020876. [PMID: 34104470 PMCID: PMC8165816 DOI: 10.1177/20552076211020876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 05/09/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Patients with chronic obstructive pulmonary disease (COPD) are often hospitalised with acute exacerbations (AECOPD) and many patients get readmitted. Intervening with hospitalised patients may be optimal timing to provide support. Our previous work demonstrated use of a digital monitoring and self-management support tool in the community. However, we wanted to explore the feasibility of recruiting patients whilst hospitalised for an AECOPD, and to identify the rate of dropout attrition around admission for AECOPD. METHODS Patients were recruited to the EDGE2 study between May 2019 and March 2020. Patients were identified by the clinical teams and patients were recruited by members of the clinical research team. Participants were aged 40 years or older, had a diagnosis of COPD and were attending or admitted to hospital for an AECOPD. Participants were given a tablet computer, Bluetooth-linked pulse oximeter and wrist-worn physical activity monitor to use until 6 months post-discharge. Use of the system aimed to support COPD self-management by enabling self-monitoring of vital signs, COPD symptoms, mood and physical activity, and access to multi-media educational resources. RESULTS 281 patients were identified and 126 approached. The main referral source was the specialist respiratory nursing and physiotherapist team (49.8% of patients identified). Twenty-six (37.1%) patients were recruited. As of 21 April 2020, 14 (53.8%) participants withdrew and 11 (of 14; 78.6%) participants withdrew within four weeks of discharge. The remaining participants withdrew between one and three months follow-up (1 of 14; 7.1%) and between three and six months follow-up (2 of 14; 14.3%). CONCLUSION A large number of patients were screened to recruit a relatively small sample and a high rate of dropout was observed. It does not appear feasible to recruit patients with COPD to digital interventional studies from the hospital setting when they have the burden of coping with acute illness.
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Affiliation(s)
- Maxine Whelan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Centre for Intelligent Healthcare, Coventry University, Coventry, UK
| | - Christopher Biggs
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Carlos Areia
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Elizabeth King
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Beth Lawson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Nikki Newhouse
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Xiaorong Ding
- Department of Engineering, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- Department of Engineering, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Mona Bafadhel
- Department of Respiratory Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- Department of Engineering, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Peter Watkinson
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - David Clifton
- Department of Engineering, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
- Oxford-Suzhou Centre for Advanced Research, Suzhou, China
| | - Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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11
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Rai T, Morton K, Roman C, Doogue R, Rice C, Williams M, Schwartz C, Velardo C, Tarassenko L, Yardley L, McManus RJ, Hinton L. Optimizing a digital intervention for managing blood pressure in stroke patients using a diverse sample: Integrating the person-based approach and patient and public involvement. Health Expect 2020; 24:327-340. [PMID: 33316120 PMCID: PMC8077154 DOI: 10.1111/hex.13173] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/10/2020] [Accepted: 11/12/2020] [Indexed: 01/12/2023] Open
Abstract
Background Having a stroke or transient ischaemic attack increases the risk of a subsequent one, especially with high blood pressure (BP). Home‐based BP management can be effective at maintaining optimal BP. Objective To describe the optimization of a digital intervention for stroke patients and the value of participant diversity, using the person‐based approach (PBA) and integral patient and public involvement (PPI). Setting and participants Stroke patients recruited from primary care and community settings, and health‐care professionals in primary care, in England and Ireland. Design Three linked qualitative studies conducted iteratively to develop an intervention using the PBA, with integral PPI. Intervention The BP: Together intervention, adapted from existing BP self‐monitoring interventions, is delivered via mobile phone or web interface to support self‐monitoring of BP at home. It alerts patients and their clinicians when a change in antihypertensive medication is needed. Findings Feedback from a diverse range of participants identified potential barriers, which were addressed to improve the intervention accessibility, feasibility and persuasiveness. Easy‐to‐read materials were developed to improve usability for patients with aphasia and lower literacy. The importance of including family members who support patient care was also highlighted. Feedback messages regarding medication change were refined to ensure usefulness for patients and clinicians. Discussion Input from PPI alongside qualitative research with a diverse study sample allowed the creation of a simple and equitable BP management intervention for stroke patients. Patient involvement Two PPI co‐investigators contributed to design, conduct of study, data interpretation and manuscript preparation; community PPI sessions informed early planning. Study participants were stroke patients and family members.
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Affiliation(s)
- Tanvi Rai
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Kate Morton
- School of Psychology, University of Southampton, Southampton, UK
| | - Cristian Roman
- Department of Engineering Science, University of Oxford, UK
| | - Roisin Doogue
- Graduate Entry Medical School, University of Limerick, Limerick, Ireland
| | - Cathy Rice
- Public and Patient Involvement (PPI) Contributor, Bristol, UK
| | - Marney Williams
- Public and Patient Involvement (PPI) Contributor, Bristol, UK
| | - Claire Schwartz
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | | | - Lucy Yardley
- School of Psychology, University of Southampton, Southampton, UK.,Department of Experimental Psychology, Institute of Biomedical Engineering, University of Bristol, Bristol, UK
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lisa Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.,The Healthcare Improvement Studies Institute, University of Cambridge, Cambridge, UK
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12
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Armitage LC, Chi Y, Santos M, Lawson BK, Areia C, Velardo C, Watkinson PJ, Tarassenko L, Costa ML, Farmer AJ. Monitoring activity of hip injury patients (MoHIP): a sub-study of the World Hip Trauma Evaluation observational cohort study. Pilot Feasibility Stud 2020; 6:70. [PMID: 32477588 PMCID: PMC7243330 DOI: 10.1186/s40814-020-00612-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 04/27/2020] [Indexed: 11/25/2022] Open
Abstract
Background Hip fracture is common, affecting 20% of women and 10% of men during their lifetime. The trajectory of patients’ recovery as they transition from the acute hospital setting to their usual residence is poorly understood. Recently, the use of activity trackers to monitor physical activity during recovery has been investigated as a way to explore this trajectory. Methods This prospective observational cohort study followed patients from hospital to home as they recovered from a hip fracture. Participants were recruited from a single centre and provided with a 3-axis logging accelerometer worn as a pendant, for 16 weeks from recruitment. Participants received monthly follow-up visits which included questions about wearing the monitor. Monthly activity monitor data were also downloaded. Participant activity was estimated from the monitor data using the calibrated “Euclidean Norm Minus One” (ENMO) metric. Polynomial mixed-effects modelling was used to evaluate the difference between the weekly activity trends of 2 groups of participants: those with and without independent mobility at 16 weeks (defined by whether aids or personal assistance were required to mobilise). Results Twenty-nine participants from 125 eligible patients were recruited. Of these, 19 (66%) reported being aware of wearing the monitor at least some of the time. Fourteen (48%) participants withdrew before study completion. Data for thirteen (45%) participants were of sufficient quantity to be included in the activity modelling procedure. Of these, 8 reported independent mobility at 16 weeks post-surgery, and 5 did not. By week 7, the weekly predicted mean ENMO (\documentclass[12pt]{minimal}
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\begin{document}$$ {\overline{ENMO}}_W $$\end{document}ENMO¯W) values were significantly different between the two participant groups, demonstrating feasibility of the model’s ability to predict which patients will report independent mobility at 16 weeks. Conclusions This is the first study to our knowledge to investigate acceptability and feasibility of a pendant-worn activity monitor in this patient cohort. Acceptability of wearing the monitor and feasibility of recruitment and retention of participants were limited. Future research into the use of activity monitors in this population should use minimally intrusive devices which are acceptable to this population. Study registration MoHIP is a sub-study of the World Hip Trauma Evaluation (WHiTE) Study (ISRCTN 63982700).
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Affiliation(s)
- Laura C Armitage
- 1Nuffield Department of Primary Care Health Sciences, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, University of Oxford, Woodstock Road, Oxford, OX2 6GG UK
| | - Yuan Chi
- 2Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Mauro Santos
- 2Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Beth K Lawson
- 1Nuffield Department of Primary Care Health Sciences, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, University of Oxford, Woodstock Road, Oxford, OX2 6GG UK
| | - Carlos Areia
- 3Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- 2Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Peter J Watkinson
- 3Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- 2Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Matthew L Costa
- 4Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Andrew J Farmer
- 1Nuffield Department of Primary Care Health Sciences, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, University of Oxford, Woodstock Road, Oxford, OX2 6GG UK
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13
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O'Donnell J, Smith-Byrne K, Velardo C, Conrad N, Salimi-Khorshidi G, Doherty A, Dwyer T, Tarassenko L, Rahimi K. Self-reported and objectively measured physical activity in people with and without chronic heart failure: UK Biobank analysis. Open Heart 2020; 7:e001099. [PMID: 32153787 PMCID: PMC7046950 DOI: 10.1136/openhrt-2019-001099] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 10/18/2019] [Accepted: 11/27/2019] [Indexed: 01/06/2023] Open
Abstract
Objective The impact of heart failure (HF) on perceived and objectively measured levels of physical activity (PA) can inform risk stratification and treatment recommendation. We aimed to compare self-reported and objectively measured PA levels in a large sample of participants with and without HF. Methods A validated PA questionnaire was used to estimate self-reported weekly PA among 1600 participants with HF and 387 580 participants without HF. Accelerometer data were studied in 596 participants with HF and 96 105 participants without HF for a period of 7 days. Using multivariable linear regression models, we compared the PA levels between participants with HF and without HF, focusing on both the average daily PA levels and the intensity of PAs throughout the day. Results PA levels were significantly lower in participants with HF using both self-report (excess metabolic equivalent of task hours per week of 26.5 (95% CI 24.7 to 28.4) vs 34.7 (95% CI 34.5 to 34.9), respectively (p<0.001)) and accelerometer measures (mean accelerations of 23.7 milligravity (95% CI 23.1 to 24.4) vs 28.1 milligravity (95% CI 28.0 to 28.1), respectively (p<0.001)). Findings were consistent across different PA intensities. Hour-by-hour comparisons showed that accelerometer-derived PA levels of patients with HF were reduced throughout the day. Conclusion Perceived and objectively recorded PA levels of patients with chronic HF are significantly lower than those of individuals without HF. This difference is continuous throughout the different hours of the day, with individuals with HF being on average 16% less active than individuals without HF. In patients with HF, increases in everyday activity may be a potential alternative to structured exercise programmes.
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Affiliation(s)
- Johanna O'Donnell
- George Institute for Global Health, University of Oxford, Oxford, Oxfordshire, UK.,Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Karl Smith-Byrne
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Nathalie Conrad
- George Institute for Global Health, University of Oxford, Oxford, Oxfordshire, UK
| | | | - Aiden Doherty
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Terence Dwyer
- George Institute for Global Health, University of Oxford, Oxford, Oxfordshire, UK
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Kazem Rahimi
- George Institute for Global Health, University of Oxford, Oxford, Oxfordshire, UK
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14
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Dougall G, Franssen M, Tucker KL, Yu LM, Hinton L, Rivero-Arias O, Abel L, Allen J, Band RJ, Chisholm A, Crawford C, Green M, Greenfield S, Hodgkinson J, Leeson P, McCourt C, MacKillop L, Nickless A, Sandall J, Santos M, Tarassenko L, Velardo C, Wilson H, Yardley L, Chappell L, McManus RJ. Blood pressure monitoring in high-risk pregnancy to improve the detection and monitoring of hypertension (the BUMP 1 and 2 trials): protocol for two linked randomised controlled trials. BMJ Open 2020; 10:e034593. [PMID: 31980512 PMCID: PMC7044851 DOI: 10.1136/bmjopen-2019-034593] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
INTRODUCTION Self-monitoring of blood pressure (BP) in pregnancy could improve the detection and management of pregnancy hypertension, while also empowering and engaging women in their own care. Two linked trials aim to evaluate whether BP self-monitoring in pregnancy improves the detection of raised BP during higher risk pregnancies (BUMP 1) and whether self-monitoring reduces systolic BP during hypertensive pregnancy (BUMP 2). METHODS AND ANALYSES Both are multicentre, non-masked, parallel group, randomised controlled trials. Participants will be randomised to self-monitoring with telemonitoring or usual care. BUMP 1 will recruit a minimum of 2262 pregnant women at higher risk of pregnancy hypertension and BUMP 2 will recruit a minimum of 512 pregnant women with either gestational or chronic hypertension. The BUMP 1 primary outcome is the time to the first recording of raised BP by a healthcare professional. The BUMP 2 primary outcome is mean systolic BP between baseline and delivery recorded by healthcare professionals. Other outcomes will include maternal and perinatal outcomes, quality of life and adverse events. An economic evaluation of BP self-monitoring in addition to usual care compared with usual care alone will be assessed across both study populations within trial and with modelling to estimate long-term cost-effectiveness. A linked process evaluation will combine quantitative and qualitative data to examine how BP self-monitoring in pregnancy is implemented and accepted in both daily life and routine clinical practice. ETHICS AND DISSEMINATION The trials have been approved by a Research Ethics Committee (17/WM/0241) and relevant research authorities. They will be published in peer-reviewed journals and presented at national and international conferences. If shown to be effective, BP self-monitoring would be applicable to a large population of pregnant women. TRIAL REGISTRATION NUMBER NCT03334149.
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Affiliation(s)
- Greig Dougall
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Marloes Franssen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lisa Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Oliver Rivero-Arias
- National Perinatal Epidemiology Unit (NPEU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lucy Abel
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Rebecca Jane Band
- Academic Unit of Psychology, University of Southampton, Southampton, UK
| | - Alison Chisholm
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Carole Crawford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Sheila Greenfield
- Primary Care Clinical Sciences, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - James Hodgkinson
- Primary Care Clinical Sciences, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Paul Leeson
- Cardiovascular Clinical Research Facility, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK
| | - Christine McCourt
- Centre for Maternal & Child Health Research, School of Health Sciences, City University, London, UK
| | - Lucy MacKillop
- Nuffield Department of Women's & Reproductive Health, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Alecia Nickless
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jane Sandall
- Department of Women and Children's Health, Kings College, London, London, UK
| | - Mauro Santos
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Hannah Wilson
- Department of Women and Children's Health, Kings College, London, London, UK
| | - Lucy Yardley
- Academic Unit of Psychology, University of Southampton, Southampton, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Lucy Chappell
- Department of Women and Children's Health, Kings College, London, London, UK
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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15
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Farmer A, Allen J, Bartlett K, Bower P, Chi Y, French D, Gudgin B, Holmes EA, Horne R, Hughes DA, Kenning C, Locock L, McSharry J, Miles L, Newhouse N, Rea R, Riga E, Tarassenko L, Velardo C, Williams N, Williams V, Yu LM. Supporting people with type 2 diabetes in effective use of their medicine through mobile health technology integrated with clinical care (SuMMiT-D Feasibility): a randomised feasibility trial protocol. BMJ Open 2019; 9:e033504. [PMID: 31888938 PMCID: PMC6937131 DOI: 10.1136/bmjopen-2019-033504] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 10/30/2019] [Accepted: 12/04/2019] [Indexed: 01/12/2023] Open
Abstract
INTRODUCTION Type 2 diabetes is common, affecting over 400 million people worldwide. Risk of serious complications can be reduced through use of effective treatments and active self-management. However, people are often concerned about starting new medicines and face difficulties in taking them regularly. Use of brief messages to provide education and support self-management, delivered through mobile phone-based text messages, can be an effective tool for some long-term conditions. We have developed messages aiming to support patients' self-management of type 2 diabetes in the use of medications and other aspects of self-management, underpinned by theory and evidence. The aim of this trial is to determine the feasibility of a large-scale clinical trial to test the effectiveness and cost-effectiveness of the intervention, compared with usual care. METHODS AND ANALYSIS The feasibility trial will be a multicentre individually randomised, controlled trial in primary care recruiting adults (≥35 years) with type 2 diabetes in England. Consenting participants will be randomised to receive short text messages three times a week with messages designed to produce change in medication adherence or non-health-related messages for 6 months. The aims are to test recruitment methods, retention to the study, the feasibility of data collection and the mobile phone and web-based processes of a proposed definitive trial and to refine the text messaging intervention. The primary outcome is the rate of recruitment to randomisation of participants to the trial. Data, including patient reported measures, will be collected online at baseline and the end of the 6-month follow-up period. With 200 participants (100 in each group), this trial is powered to estimate 80% follow-up within 95% CIs of 73.8% to 85.3%. The analysis will follow a prespecified plan. ETHICS AND DISSEMINATION Ethics approval was obtained from the West of Scotland Research Ethics Committee 05. The results will be disseminated through conference presentations, peer-reviewed journals and will be published on the trial website: www.summit-d.org (SuMMiT-D (SUpport through Mobile Messaging and digital health Technology for Diabetes)). TRIAL REGISTRATION NUMBER ISRCTN13404264.
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Affiliation(s)
- Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Julie Allen
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Kiera Bartlett
- The Division of Psychology and Mental Health, The University of Manchester, Manchester, UK
| | - Peter Bower
- Division of Population Health, Health Services Research & Primary Care, The University of Manchester, Manchester, UK
| | - Yuan Chi
- The Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - David French
- The Division of Psychology and Mental Health, The University of Manchester, Manchester, UK
| | | | - Emily A Holmes
- School of Health Sciences, Bangor University, Bangor, UK
| | - Robert Horne
- UCL School of Pharmacy, University College London, London, UK
| | - Dyfrig A Hughes
- Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, UK
| | - Cassandra Kenning
- Institute of Population Health, The University of Manchester, Manchester, UK
| | - Louise Locock
- Health Service Research, University of Aberdeen, Aberdeen, UK
| | - Jenny McSharry
- Health Behaviour Change Research Group, School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Lisa Miles
- Division of Psychology and Mental Health, The University of Manchester, Manchester, UK
| | | | - Rustam Rea
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Evgenia Riga
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- The Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Carmelo Velardo
- The Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Nicola Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Veronika Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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16
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Band R, Hinton L, Tucker KL, Chappell LC, Crawford C, Franssen M, Greenfield S, Hodgkinson J, McCourt C, McManus RJ, Sandall J, Santos MD, Velardo C, Yardley L. Intervention planning and modification of the BUMP intervention: a digital intervention for the early detection of raised blood pressure in pregnancy. Pilot Feasibility Stud 2019; 5:153. [PMID: 31890265 PMCID: PMC6925434 DOI: 10.1186/s40814-019-0537-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 11/28/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Hypertensive disorders in pregnancy, particularly pre-eclampsia, pose a substantial health risk for both maternal and foetal outcomes. The BUMP (Blood Pressure Self-Monitoring in Pregnancy) interventions are being tested in a trial. They aim to facilitate the early detection of raised blood pressure through self-monitoring. This article outlines how the self-monitoring interventions in the BUMP trial were developed and modified using the person-based approach to promote engagement and adherence. METHODS Key behavioural challenges associated with blood pressure self-monitoring in pregnancy were identified through synthesising qualitative pilot data and existing evidence, which informed guiding principles for the development process. Social cognitive theory was identified as an appropriate theoretical framework. A testable logic model was developed to illustrate the hypothesised processes of change associated with the intervention. Iterative qualitative feedback from women and staff informed modifications to the participant materials. RESULTS The evidence synthesis suggested women face challenges integrating self-monitoring into their lives and that adherence is challenging at certain time points in pregnancy (for example, starting maternity leave). Intervention modification included strategies to address adherence but also focussed on modifying outcome expectancies, by providing messages explaining pre-eclampsia and outlining the potential benefits of self-monitoring. CONCLUSIONS With an in-depth understanding of the target population, several methods and approaches to plan and develop interventions specifically relevant to pregnant women were successfully integrated, to address barriers to behaviour change while ensuring they are easy to engage with, persuasive and acceptable.
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Affiliation(s)
- Rebecca Band
- Academic unit of psychology, University of Southampton, Southampton, SO17 1BJ UK
| | - Lisa Hinton
- Nuffield Department of Primary Care Health Sciences, Radcliffe Infirmary Quarter University of Oxford, Oxford, OX2 6GG UK
| | - Katherine L. Tucker
- Nuffield Department of Primary Care Health Sciences, Radcliffe Infirmary Quarter University of Oxford, Oxford, OX2 6GG UK
| | - Lucy C. Chappell
- Division of Women and Children’s Health, King’s College London, London, SE1 7EH UK
| | - Carole Crawford
- Nuffield Department of Primary Care Health Sciences, Radcliffe Infirmary Quarter University of Oxford, Oxford, OX2 6GG UK
| | - Marloes Franssen
- Nuffield Department of Primary Care Health Sciences, Radcliffe Infirmary Quarter University of Oxford, Oxford, OX2 6GG UK
| | - Sheila Greenfield
- Institute of Applied Health, University of Birmingham, Birmingham, B15 2TT UK
| | - James Hodgkinson
- Institute of Applied Health, University of Birmingham, Birmingham, B15 2TT UK
| | - Christine McCourt
- Centre for Maternal and Child Health, School of Health Sciences, City University, London, EC1R IUW UK
| | - Richard J. McManus
- Nuffield Department of Primary Care Health Sciences, Radcliffe Infirmary Quarter University of Oxford, Oxford, OX2 6GG UK
| | - Jane Sandall
- Division of Women and Children’s Health, King’s College London, London, SE1 7EH UK
| | - Mauro Dala Santos
- Institute of Biomedical Engineering, Department of Engineering Science, Building, University of Oxford, Oxford, OX3 7DQ UK
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, Building, University of Oxford, Oxford, OX3 7DQ UK
| | - Lucy Yardley
- Academic unit of psychology, University of Southampton, Southampton, SO17 1BJ UK
- School of Psychological Science, University of Bristol, Bristol, UK
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Whelan ME, Velardo C, Rutter H, Tarassenko L, Farmer AJ. Mood Monitoring Over One Year for People With Chronic Obstructive Pulmonary Disease Using a Mobile Health System: Retrospective Analysis of a Randomized Controlled Trial. JMIR Mhealth Uhealth 2019; 7:e14946. [PMID: 31755872 PMCID: PMC6898889 DOI: 10.2196/14946] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 08/11/2019] [Accepted: 08/31/2019] [Indexed: 01/23/2023] Open
Abstract
Background Comorbid anxiety and depression can add to the complexity of managing treatment for people living with chronic obstructive pulmonary disease (COPD). Monitoring mood has the potential to identify individuals who might benefit from additional support and treatment. Objective We used data from the sElf-management anD support proGrammE (EDGE) trial to examine: (1) the extent to which the mood-monitoring components of a mobile health system for patients with COPD were used by participants; (2) the levels of anxiety and depression symptoms among study participants; (3) the extent to which videos providing advice about coping with low mood were viewed; and (4) the characteristics of participants with differing levels of mood and utilization of mood monitoring. Methods A total of 107 men and women with a clinical diagnosis of COPD, aged ≥40 years old, were recruited to the intervention arm of the EDGE trial. Participants were invited to complete the Patient Health Questionnaire-8 and the Generalized Anxiety Disorder-7 test every four weeks using a tablet computer. Mood disturbance based on these measures was defined as a score ≥5 on either scale. Participants reporting a mood disturbance were automatically directed (signposted) to a stress or mood management video. Study outcomes included measures of health status, respiratory quality of life, and symptoms of anxiety and depression. Results Overall, 94 (87.9%) participants completed the 12-month study. A total of 80 participants entered at least one response each month for at least ten months. On average, 16 participants (range 8-38 participants) entered ≥2 responses each month. Of all the participants, 47 (50%) gave responses indicating a mood disturbance. Participants with a mood disturbance score for both scales (n=47) compared with those without (n=20) had lower health status (P=.008), lower quality of life (P=.009), and greater anxiety (P<.001) and increased depression symptoms (P<.001). Videos were viewed by 64 (68%) people over 12 months. Of the 220 viewing visualizations, 70 (34.7%) began after being signposted. Participants signposted to the stress management video (100%; IQR 23.3-100%) watched a greater proportion of it compared to those not signposted (38.4%; IQR 16.0-68.1%; P=.03), whereas duration of viewing was not significantly different for the mood management video. Conclusions Monitoring of anxiety and depression symptoms for people with COPD is feasible. More than half of trial participants reported scores indicating a mood disturbance during the study. Signposting participants to an advisory video when reporting increased symptoms of a mood disturbance resulted in a longer view-time for the stress management video. The opportunity to elicit measures of mood regularly as part of a health monitoring system could contribute to better care for people with COPD.
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Affiliation(s)
- Maxine E Whelan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Heather Rutter
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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OrDonnell J, Velardo C, Shah SA, Khorshidi GS, Salvi D, Rahimi K, Tarassenko L. Physical Activity and Sleep Analysis of Heart Failure Patients using Multi-sensor Patches. Annu Int Conf IEEE Eng Med Biol Soc 2019; 2018:6092-6095. [PMID: 30441725 DOI: 10.1109/embc.2018.8513594] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Traditional heart failure markers fail to reliably predict heart-failure related hospitalisations and deaths. Multi- sensor patch data can provide an objective insight into activity and sleep patterns of patients and may therefore improve the performance of current risk-quantification algorithms. This work aimed to establish the feasibility of collecting multi-sensor patch data from heart failure patients and to perform an initial analysis of activity and sleep patterns of heart failure patients in relation to disease severity. 13 heart failure patients from the SUPPORT-HF study were provided with chest-worn multisensor patches and asked to wear the devices continuously for up to seven consecutive days. Using a combination of impedance, heart rate and accelerometer data participants' sleep and wakefulness information were extracted and analyzed in relation to self-reported symptom scores. Patch data for eleven patients were of high enough quality to be included in the analysis, accounting for 63 patient days worth of data. The heart failure patients slept for an average of 8.3 hours a night and experienced 2.8 sleep interruptions. Potential differences in sleep angle, heart rate and wake-time activity were found for patients with different heart failure severity. Larger studies are necessary to create a more coherent picture of the potential of activity and sleep as a markers for heart failure deterioration.
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19
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Finnegan E, Villarroel M, Velardo C, Tarassenko L. Automated method for detecting and reading seven-segment digits from images of blood glucose metres and blood pressure monitors. J Med Eng Technol 2019; 43:341-355. [PMID: 31679409 DOI: 10.1080/03091902.2019.1673844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
There is an increasing need for fast and accurate transfer of readings from blood glucose metres and blood pressure monitors to a smartphone mHealth application, without a dependency on Bluetooth technology. Most of the medical devices recommended for home monitoring use a seven-segment display to show the recorded measurement to the patient. We aimed to achieve accurate detection and reading of the seven-segment digits displayed on these medical devices using an image taken in a realistic scenario by a smartphone camera. A synthetic dataset of seven-segment digits was developed in order to train and test a digit classifier. A dataset containing realistic images of blood glucose metres and blood pressure monitors using a variety of smartphone cameras was also created. The digit classifier was evaluated on a dataset of seven-segment digits manually extracted from the medical device images. These datasets along with the code for its development have been made public. The developed algorithm first preprocessed the input image using retinex with two bilateral filters and adaptive histogram equalisation. Subsequently, the digit segments were automatically located within the image by two techniques operating in parallel: Maximally Stable Extremal Regions (MSER) and connected components of a binarised image. A filtering and clustering algorithm was then designed to combine digit segments to form seven-segment digits. The resulting digits were classified using a Histogram of Orientated Gradients (HOG) feature set and a neural network trained on the synthetic digits. The model achieved 93% accuracy on digits found on the medical devices. The digit location algorithm achieved a F1 score of 0.87 and 0.80 on images of blood glucose metres and blood pressure monitors respectively. Very few assumptions were made of the locations of the digits on the devices so that the proposed algorithm can be easily implemented on new devices.
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Affiliation(s)
- E Finnegan
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - M Villarroel
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - C Velardo
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - L Tarassenko
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
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20
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Warner BE, Velardo C, Salvi D, Lafferty K, Crosbie S, Herrington WG, Haynes R. Feasibility of Telemonitoring Blood Pressure in Patients With Kidney Disease (Oxford Heart and Renal Protection Study-1): Observational Study. JMIR Cardio 2018; 2. [PMID: 30596204 PMCID: PMC6309686 DOI: 10.2196/11332] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Background Blood pressure (BP) is a key modifiable risk factor for patients with chronic kidney disease (CKD), with current guidelines recommending strict control to reduce the risk of progression of both CKD and cardiovascular disease. Trials involving BP lowering require multiple visits to achieve target BP, which increases the costs of such trials, and in routine care, BP measured in the clinic may not accurately reflect the usual BP. Objective We sought to assess whether a telemonitoring system for BP (using a Bluetooth-enabled BP machine that could transmit BP measurements to a tablet device installed with a bespoke app to guide the measurement of BP and collect questionnaire data) was acceptable to patients with CKD and whether patients would provide sufficient BP readings to assess variability and guide treatment. Methods A total of 25 participants with CKD were trained to use the telemonitoring equipment and asked to record BP daily for 30 days, attend a study visit, and then record BP on alternate days for the next 60 days. They were also offered a wrist-worn applanation tonometry device (BPro) which measures BP every 15 minutes over a 24-hour period. Participants were given questionnaires at the 1- and 3-month time points; the questionnaires were derived from the System Usability Scale and Technology Acceptance Model. All eligible participants completed the study. Results Mean participant age was 58 (SD 11) years, and mean estimated glomerular filtration rate was 36 (SD 13) mL/min/1.73m2. 13/25 (52%) participants provided >90% of the expected data and 18/25 (72%) provided >80% of the expected data. The usability of the telemonitoring system was rated highly, with mean scores of 84.9/100 (SE 2.8) after 30 days and 84.2/100 (SE 4.1) after 90 days. The coefficient of variation for the variability of systolic BP telemonitoring was 9.4% (95% CI 7.8-10.9) compared with 7.9% (95% CI 6.4-9.5) for the BPro device, P=.05 (and was 9.0% over 1 year in a recently completed trial with identical eligibility criteria), indicating that most variation in BP was short term. Conclusions Telemonitoring is acceptable for patients with CKD and provides sufficient data to inform titration of antihypertensive therapies in either a randomized trial setting (comparing BP among different targets) or routine clinical practice. Such methods could be employed in both scenarios and reduce costs currently associated with such activities. Trial Registration International Standard Randomized Controlled Trial Number ISRCTN13725286; http://www.isrctn.com/ISRCTN13725286 (Archived by WebCite at http://www.webcitation.org/74PAX51Ji).
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Affiliation(s)
- B E Warner
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - C Velardo
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - D Salvi
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - K Lafferty
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - S Crosbie
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - W G Herrington
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.,Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - R Haynes
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.,Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Salvi D, Velardo C, Brynes J, Tarassenko L. An Optimised Algorithm for Accurate Steps Counting From Smart-Phone Accelerometry. Annu Int Conf IEEE Eng Med Biol Soc 2018; 2018:4423-4427. [PMID: 30441333 DOI: 10.1109/embc.2018.8513319] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Step counting from smart-phones allows a wide range of applications related to fitness and health. Estimating steps from phones' accelerometers is challenging because of the multitude of ways a smart-phone can be carried. We focus our work on the windowed peak detection algorithm, which has previously been shown to be accurate and efficient and thus suitable for mobile devices. We explore and optimise further the algorithm and its parameters making use of data collected by three volunteers holding the phone in six different positions. In order to simplify the analysis of the data, we also built a novel device for the detection of the ground truth steps. Over the collected data set, the algorithm reaches 95% average accuracy. We implemented the algorithm for the Android OS and released it as an open source project. A separate dataset was collected with the algorithm running on the smart-phone for further validation. The validation confirms the accuracy of the algorithm in real-time conditions.
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22
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Bhatia M, Mackillop LH, Bartlett K, Loerup L, Kenworthy Y, Levy JC, Farmer AJ, Velardo C, Tarassenko L, Hirst JE. Clinical Implications of the NICE 2015 Criteria for Gestational Diabetes Mellitus. J Clin Med 2018; 7:E376. [PMID: 30360376 PMCID: PMC6209967 DOI: 10.3390/jcm7100376] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/11/2018] [Accepted: 10/17/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND In response to concerns that the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria labeled too many women with gestational diabetes mellitus (GDM) without evidence of clinical or economic benefit, NICE recommended a change in diagnostic criteria in 2015. AIM To compare diabetes associated maternal and neonatal complications in pregnancies complicated by GDM diagnosed using IADPSG criteria only, to those with GDM diagnosed using both IADPSG and NICE 2015 criteria. GDM screening was risk factor based. METHODS This was a secondary analysis of a trial of women with GDM diagnosed by the IADPSG criteria (fasting blood glucose (BG) ≥ 5.1 mmol/L, 1 h ≥ 10.0 mmol/L and 2 h ≥ 8.5 mmol/L). Outcomes were compared for two groups: NICE + IADPSG defined as those with GDM diagnosed by both the NICE 2015 and IADPSG criteria (fasting BG ≥ 5.6 mmol/L, 2 h ≥ 8.5 mmol/L); and IADPSG-ONLY (fasting BG 5.1 mmol/L to 5.5 mmol/L, and/or 1-hour ≥10.0 mmol/L, and 2 h ≥ 8.5 mmol/L). We were not able to obtain data for women with a 2-h value between BG 7.8⁻8.4 mmol/L (i.e., NICE-ONLY; NICE 2015 positive and IADPSG negative). All women were treated for GDM using targets of fasting BG < 5.3 mmol/L and 1-h post prandial BG < 7.8 mmol/L respectively. RESULTS Of 159 women, 65 (40.9%) were NICE + IADPSG and 94 (59.1%) IADPSG-ONLY. Hypoglycaemic medication use was similar in both groups: 52.3% NICE + IADPSG, 46.8% IADPSG-ONLY, OR 1.0 (0.5⁻1.9). The IADPSG-ONLY group delivered later than the NICE + IADPSG group; 39.0 weeks (sd 1.4) compared to 38.2 weeks (sd 2.5), p value 0.02. Fewer caesarean sections occurred in IADPSG-ONLY group 30.9% vs. 52.3%, OR 0.4 (0.2⁻0.9). Birthweight, large for gestational age, and other neonatal complications were not significantly different between groups. CONCLUSIONS Gestational diabetes-associated perinatal complications were similar in both groups. The IADPSG criteria detect women with evidence of ongoing hyperglycaemia who may benefit from treatment during pregnancy.
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Affiliation(s)
- Meena Bhatia
- Oxford University Hospitals NHS Foundation Trust, Headington OX3 9DU, UK.
| | - Lucy H Mackillop
- Oxford University Hospitals NHS Foundation Trust, Headington OX3 9DU, UK.
- Nuffield Department of Women's Reproductive Health, University of Oxford, Oxford OX3 9DU, UK.
| | - Katy Bartlett
- Oxford University Hospitals NHS Foundation Trust, Headington OX3 9DU, UK.
| | - Lise Loerup
- Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7DQ, UK.
| | - Yvonne Kenworthy
- Nuffield Department of Women's Reproductive Health, University of Oxford, Oxford OX3 9DU, UK.
| | - Jonathan C Levy
- The Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals NHS Trust, Oxford OX3 7LE, UK.
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK.
| | - Carmelo Velardo
- Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7DQ, UK.
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7DQ, UK.
| | - Jane E Hirst
- Nuffield Department of Women's Reproductive Health, University of Oxford, Oxford OX3 9DU, UK.
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Hartmann-Boyce J, Aveyard P, Piernas C, Koshiaris C, Velardo C, Salvi D, Jebb SA. Cognitive and behavioural strategies for weight management in overweight adults: Results from the Oxford Food and Activity Behaviours (OxFAB) cohort study. PLoS One 2018; 13:e0202072. [PMID: 30096203 PMCID: PMC6086460 DOI: 10.1371/journal.pone.0202072] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 07/29/2018] [Indexed: 11/29/2022] Open
Abstract
Background Though many overweight and obese adults attempt to lose weight without formal support, little is known about the strategies used in self-directed weight loss attempts. We set out to assess cognitive and behavioural strategies for weight loss and their associations with weight change. Methods Prospective, web-based cohort study of overweight UK adults (BMI≥25kg/m2) trying to lose weight through behaviour change. Strategy use was assessed using the OxFAB questionnaire and evaluated (1) at the domain level, (2) through exploratory factor analysis, and (3) in a model of strategies deemed a priori to be “essential” to weight management. Associations with weight change at 3 months were tested using linear regression. Results 486 participants answered all questions; 194 reported weight at baseline and at 3 months (mean weight change -3.3kg (SD 4.1)). Greater weight loss was significantly associated with the motivational support domain (-2.4kg, 95% CI -4.4 to -0.4), dietary impulse control (from factor analysis) (-0.6kg, 95% CI -1.1 to -0.03), and weight loss planning and monitoring (from factor analysis) (-1.3kg, 95% CI -2.0 to -0.5). Higher scores in the model of essential behavioural strategies were significantly associated with greater weight loss (compared to participants using 6 or fewer of the 9 strategies, using 7 or more of the 9 strategies was associated with a 2.13kg greater weight loss (SE 0.58, p<0.001)). Conclusions Despite heterogeneity in the strategies employed for weight loss, coherent patterns of behaviours emerged for individual participants, some of which were associated with greater weight loss, including strategies relating to dietary impulse control, weight loss planning and monitoring, motivational support, information seeking and self-monitoring. Trials could test the effect of promoting use of these patterns on weight loss.
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Affiliation(s)
- Jamie Hartmann-Boyce
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford, United Kingdom
- * E-mail:
| | - Paul Aveyard
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford, United Kingdom
| | - Carmen Piernas
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford, United Kingdom
| | - Constantinos Koshiaris
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Sciences, Old Road Campus Research Building, University of Oxford, Headington, Oxford, United Kingdom
| | - Dario Salvi
- Institute of Biomedical Engineering, Department of Engineering Sciences, Old Road Campus Research Building, University of Oxford, Headington, Oxford, United Kingdom
| | - Susan A. Jebb
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford, United Kingdom
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Cairns AE, Tucker KL, Leeson P, Mackillop LH, Santos M, Velardo C, Salvi D, Mort S, Mollison J, Tarassenko L, McManus RJ. Self-Management of Postnatal Hypertension: The SNAP-HT Trial. Hypertension 2018; 72:425-432. [PMID: 29967037 DOI: 10.1161/hypertensionaha.118.10911] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 02/15/2018] [Accepted: 05/18/2018] [Indexed: 12/24/2022]
Abstract
Hypertension affects 1 in 10 pregnancies, often persisting postpartum, when antihypertensive requirements may vary substantially. This unmasked, randomized controlled trial evaluated the feasibility and effects on blood pressure (BP) of self-management of postpartum hypertension. Women with gestational hypertension or preeclampsia, requiring postnatal antihypertensive treatment, were randomized to self-management or usual care. Self-management entailed daily home BP monitoring and automated medication reduction via telemonitoring. Women attended 5 follow-up visits during 6 months. The primary outcome was feasibility: specifically recruitment, retention, and compliance with follow-up rates. Secondary outcomes included BP control and safety, analyzed on an intention-to-treat basis. Forty-nine percent (91/186) of those women approached were randomized (45 intervention, 46 control), and 90% (82/91) finished follow-up. The groups had similar baseline characteristics. After randomization, BP was lower in the intervention group, most markedly at 6 weeks: intervention group mean (SD), systolic 121.6 (8.7)/diastolic 80.5 (6.6) mm Hg; control group, systolic 126.6 (11.0)/diastolic 86.0 (9.7) mm Hg; adjusted differences (95% confidence interval), systolic -5.2 (-9.3 to -1.2)/diastolic -5.8 (-9.1 to -2.5) mm Hg. Diastolic BP remained significantly lower in those self-managing to 6 months: adjusted difference -4.5 (-8.1 to -0.8) mm Hg. This is the first randomized evaluation of BP self-management postpartum and indicates it would be feasible to trial this intervention in larger studies. Self-management resulted in better diastolic BP control to 6 months, even beyond medication cessation. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT02333240.
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Affiliation(s)
- Alexandra E Cairns
- From the Nuffield Department of Primary Care Health Sciences (A.E.C., K.L.T., S.M., J.M., R.J.M.)
| | - Katherine L Tucker
- From the Nuffield Department of Primary Care Health Sciences (A.E.C., K.L.T., S.M., J.M., R.J.M.)
| | - Paul Leeson
- Cardiovascular Clinical Research Facility (P.L.)
| | | | - Mauro Santos
- Institute of Biomedical Engineering (M.S., C.V., D.S., L.T.), University of Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering (M.S., C.V., D.S., L.T.), University of Oxford, United Kingdom
| | - Dario Salvi
- Institute of Biomedical Engineering (M.S., C.V., D.S., L.T.), University of Oxford, United Kingdom
| | - Sam Mort
- From the Nuffield Department of Primary Care Health Sciences (A.E.C., K.L.T., S.M., J.M., R.J.M.)
| | - Jill Mollison
- From the Nuffield Department of Primary Care Health Sciences (A.E.C., K.L.T., S.M., J.M., R.J.M.)
| | - Lionel Tarassenko
- Institute of Biomedical Engineering (M.S., C.V., D.S., L.T.), University of Oxford, United Kingdom
| | - Richard J McManus
- From the Nuffield Department of Primary Care Health Sciences (A.E.C., K.L.T., S.M., J.M., R.J.M.)
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Rouyard T, Leal J, Baskerville R, Velardo C, Salvi D, Gray A. Nudging people with Type 2 diabetes towards better self-management through personalized risk communication: A pilot randomized controlled trial in primary care. Endocrinol Diabetes Metab 2018; 1:e00022. [PMID: 30815556 PMCID: PMC6354823 DOI: 10.1002/edm2.22] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 06/01/2018] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES To assess the feasibility in routine primary care consultation and investigate the effect on risk recall and self-management of a new type of risk communication intervention based on behavioural economics ("nudge-based") for people with Type 2 diabetes mellitus (T2DM). METHODS Forty adults with poorly controlled T2DM (HbA1c > 7.5%) were randomized to receive a personalized, nudge-based risk communication intervention (n = 20) or standard care (n = 20). Risk recall and self-management were evaluated at baseline and 12 weeks after the intervention. RESULTS Both in terms of feasibility and acceptability, this new risk communication intervention was very satisfactory. Study retention rate after 12 weeks was very high (90%) and participants were highly satisfied with the intervention (4.4 out of 5 on the COMRADE scale). Although not powered to identify significant between-group effects, the intervention significantly improved risk recall after 12 weeks and intentions to make lifestyle changes (dietary behaviour) compared to standard care. CONCLUSIONS This pilot study provides the first evidence of the feasibility of implementing in primary care a nudge-based risk communication intervention for people with T2DM. Based on the promising results observed, an adequately powered trial to determine the effectiveness of the intervention on long-term self-management is judged feasible. As a result of this feasibility study, some minor adaptations to the intervention and study methods that would help to facilitate a definitive trial are also reported.
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Affiliation(s)
- Thomas Rouyard
- Health Economics Research CentreNuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Jose Leal
- Health Economics Research CentreNuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Richard Baskerville
- Nuffield Department of Primary Care Health SciencesUniversity of OxfordOxfordUK
| | - Carmelo Velardo
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordOxfordUK
| | - Dario Salvi
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordOxfordUK
| | - Alastair Gray
- Health Economics Research CentreNuffield Department of Population HealthUniversity of OxfordOxfordUK
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Mackillop L, Hirst JE, Bartlett KJ, Birks JS, Clifton L, Farmer AJ, Gibson O, Kenworthy Y, Levy JC, Loerup L, Rivero-Arias O, Ming WK, Velardo C, Tarassenko L. Comparing the Efficacy of a Mobile Phone-Based Blood Glucose Management System With Standard Clinic Care in Women With Gestational Diabetes: Randomized Controlled Trial. JMIR Mhealth Uhealth 2018; 6:e71. [PMID: 29559428 PMCID: PMC5883074 DOI: 10.2196/mhealth.9512] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 01/31/2018] [Accepted: 02/17/2018] [Indexed: 12/15/2022] Open
Abstract
Background Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits. Objective We conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance. Methods Women with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study. Results A total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (–0.16 mmol/L in the intervention and –0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of –£1044 (95% CI –£2186 to £99). There were no unexpected adverse outcomes. Conclusions Remote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world. Trial Registration ClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ)
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Affiliation(s)
- Lucy Mackillop
- Oxford University Hospitals NHS Foundation Trust, Headington, United Kingdom.,Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Jane Elizabeth Hirst
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Katy Jane Bartlett
- Oxford University Hospitals NHS Foundation Trust, Headington, United Kingdom
| | | | - Lei Clifton
- Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Oliver Gibson
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Yvonne Kenworthy
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Jonathan Cummings Levy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Lise Loerup
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Oliver Rivero-Arias
- National Perinatal Epidemiology Unit, University Of Oxford, Oxford, United Kingdom
| | - Wai-Kit Ming
- Department of Obstetrics and Gynaecology, Sun Yat-Sen University, Guangzhou, China
| | - Carmelo Velardo
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
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Farmer A, Williams V, Velardo C, Shah SA, Yu LM, Rutter H, Jones L, Williams N, Heneghan C, Price J, Hardinge M, Tarassenko L. Self-Management Support Using a Digital Health System Compared With Usual Care for Chronic Obstructive Pulmonary Disease: Randomized Controlled Trial. J Med Internet Res 2017; 19:e144. [PMID: 28468749 PMCID: PMC5438446 DOI: 10.2196/jmir.7116] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 03/02/2017] [Accepted: 03/14/2017] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND We conducted a randomized controlled trial of a digital health system supporting clinical care through monitoring and self-management support in community-based patients with moderate to very severe chronic obstructive pulmonary disease (COPD). OBJECTIVE The aim of this study was to determine the efficacy of a fully automated Internet-linked, tablet computer-based system of monitoring and self-management support (EDGE' sElf-management anD support proGrammE) in improving quality of life and clinical outcomes. METHODS We compared daily use of EDGE with usual care for 12 months. The primary outcome was COPD-specific health status measured with the St George's Respiratory Questionnaire for COPD (SGRQ-C). RESULTS A total of 166 patients were randomized (110 EDGE, 56 usual care). All patients were included in an intention to treat analysis. The estimated difference in SGRQ-C at 12 months (EDGE-usual care) was -1.7 with a 95% CI of -6.6 to 3.2 (P=.49). The relative risk of hospital admission for EDGE was 0.83 (0.56-1.24, P=.37) compared with usual care. Generic health status (EQ-5D, EuroQol 5-Dimension Questionnaire) between the groups differed significantly with better health status for the EDGE group (0.076, 95% CI 0.008-0.14, P=.03). The median number of visits to general practitioners for EDGE versus usual care were 4 versus 5.5 (P=.06) and to practice nurses were 1.5 versus 2.5 (P=.03), respectively. CONCLUSIONS The EDGE clinical trial does not provide evidence for an effect on COPD-specific health status in comparison with usual care, despite uptake of the intervention. However, there appears to be an overall benefit in generic health status; and the effect sizes for improved depression score, reductions in hospital admissions, and general practice visits warrants further evaluation and could make an important contribution to supporting people with COPD. TRIAL REGISTRATION International Standard Randomized Controlled Trial Number (ISRCTN): 40367841; http://www.isrctn.com/ISRCTN40367841 (Archived by WebCite at http://www.webcitation.org/6pmfIJ9KK).
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Affiliation(s)
- Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Veronika Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Syed Ahmar Shah
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Heather Rutter
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Louise Jones
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Nicola Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Carl Heneghan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Jonathan Price
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Maxine Hardinge
- Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
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Shah SA, Velardo C, Farmer A, Tarassenko L. Exacerbations in Chronic Obstructive Pulmonary Disease: Identification and Prediction Using a Digital Health System. J Med Internet Res 2017; 19:e69. [PMID: 28270380 PMCID: PMC5360891 DOI: 10.2196/jmir.7207] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 02/14/2017] [Indexed: 11/13/2022] Open
Abstract
Background Chronic obstructive pulmonary disease (COPD) is a progressive, chronic respiratory disease with a significant socioeconomic burden. Exacerbations, the sudden and sustained worsening of symptoms, can lead to hospitalization and reduce quality of life. Major limitations of previous telemonitoring interventions for COPD include low compliance, lack of consensus on what constitutes an exacerbation, limited numbers of patients, and short monitoring periods. We developed a telemonitoring system based on a digital health platform that was used to collect data from the 1-year EDGE (Self Management and Support Programme) COPD clinical trial aiming at daily monitoring in a heterogeneous group of patients with moderate to severe COPD. Objective The objectives of the study were as follows: first, to develop a systematic and reproducible approach to exacerbation identification and to track the progression of patient condition during remote monitoring; and second, to develop a robust algorithm able to predict COPD exacerbation, based on vital signs acquired from a pulse oximeter. Methods We used data from 110 patients, with a combined monitoring period of more than 35,000 days. We propose a finite-state machine–based approach for modeling COPD exacerbation to gain a deeper insight into COPD patient condition during home monitoring to take account of the time course of symptoms. A robust algorithm based on short-period trend analysis and logistic regression using vital signs derived from a pulse oximeter is also developed to predict exacerbations. Results On the basis of 27,260 sessions recorded during the clinical trial (average usage of 5.3 times per week for 12 months), there were 361 exacerbation events. There was considerable variation in the length of exacerbation events, with a mean length of 8.8 days. The mean value of oxygen saturation was lower, and both the pulse rate and respiratory rate were higher before an impending exacerbation episode, compared with stable periods. On the basis of the classifier developed in this work, prediction of COPD exacerbation episodes with 60%-80% sensitivity will result in 68%-36% specificity. Conclusions All 3 vital signs acquired from a pulse oximeter (pulse rate, oxygen saturation, and respiratory rate) are predictive of COPD exacerbation events, with oxygen saturation being the most predictive, followed by respiratory rate and pulse rate. Combination of these vital signs with a robust algorithm based on machine learning leads to further improvement in positive predictive accuracy. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 40367841; http://www.isrctn.com/ISRCTN40367841 (Archived by WebCite at http://www.webcitation.org/6olpMWNpc)
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Affiliation(s)
- Syed Ahmar Shah
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
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Velardo C, Shah SA, Gibson O, Clifford G, Heneghan C, Rutter H, Farmer A, Tarassenko L. Digital health system for personalised COPD long-term management. BMC Med Inform Decis Mak 2017; 17:19. [PMID: 28219430 PMCID: PMC5319140 DOI: 10.1186/s12911-017-0414-8] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 02/08/2017] [Indexed: 11/10/2022] Open
Abstract
Background Recent telehealth studies have demonstrated minor impact on patients affected by long-term conditions. The use of technology does not guarantee the compliance required for sustained collection of high-quality symptom and physiological data. Remote monitoring alone is not sufficient for successful disease management. A patient-centred design approach is needed in order to allow the personalisation of interventions and encourage the completion of daily self-management tasks. Methods A digital health system was designed to support patients suffering from chronic obstructive pulmonary disease in self-managing their condition. The system includes a mobile application running on a consumer tablet personal computer and a secure backend server accessible to the health professionals in charge of patient management. The patient daily routine included the completion of an adaptive, electronic symptom diary on the tablet, and the measurement of oxygen saturation via a wireless pulse oximeter. Results The design of the system was based on a patient-centred design approach, informed by patient workshops. One hundred and ten patients in the intervention arm of a randomised controlled trial were subsequently given the tablet computer and pulse oximeter for a 12-month period. Patients were encouraged, but not mandated, to use the digital health system daily. The average used was 6.0 times a week by all those who participated in the full trial. Three months after enrolment, patients were able to complete their symptom diary and oxygen saturation measurement in less than 1 m 40s (96% of symptom diaries). Custom algorithms, based on the self-monitoring data collected during the first 50 days of use, were developed to personalise alert thresholds. Conclusions Strategies and tools aimed at refining a digital health intervention require iterative use to enable convergence on an optimal, usable design. ‘Continuous improvement’ allowed feedback from users to have an immediate impact on the design of the system (e.g., collection of quality data), resulting in high compliance with self-monitoring over a prolonged period of time (12-month). Health professionals were prompted by prioritisation algorithms to review patient data, which led to their regular use of the remote monitoring website throughout the trial. Trial registration Trial registration: ISRCTN40367841. Registered 17/10/2012.
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Affiliation(s)
- Carmelo Velardo
- Department of Engineering Science, University of Oxford, IBME, Oxford, UK.
| | - Syed Ahmar Shah
- Department of Engineering Science, University of Oxford, IBME, Oxford, UK
| | - Oliver Gibson
- Department of Engineering Science, University of Oxford, IBME, Oxford, UK
| | - Gari Clifford
- Department of Engineering Science, University of Oxford, IBME, Oxford, UK
| | - Carl Heneghan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Heather Rutter
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Andrew Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- Department of Engineering Science, University of Oxford, IBME, Oxford, UK
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Triantafyllidis AK, Velardo C, Salvi D, Shah SA, Koutkias VG, Tarassenko L. A Survey of Mobile Phone Sensing, Self-Reporting, and Social Sharing for Pervasive Healthcare. IEEE J Biomed Health Inform 2017. [DOI: 10.1109/jbhi.2015.2483902 https://doi.org/10.1109/jbhi.2015.2483902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Ming WK, Mackillop LH, Farmer AJ, Loerup L, Bartlett K, Levy JC, Tarassenko L, Velardo C, Kenworthy Y, Hirst JE. Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis. J Med Internet Res 2016; 18:e290. [PMID: 27829574 PMCID: PMC5121530 DOI: 10.2196/jmir.6556] [Citation(s) in RCA: 97] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 10/05/2016] [Accepted: 10/07/2016] [Indexed: 11/24/2022] Open
Abstract
Background Diabetes in pregnancy is a global problem. Technological innovations present exciting opportunities for novel approaches to improve clinical care delivery for gestational and other forms of diabetes in pregnancy. Objective To perform an updated and comprehensive systematic review and meta-analysis of the literature to determine whether telemedicine solutions offer any advantages compared with the standard care for women with diabetes in pregnancy. Methods The review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Randomized controlled trials (RCT) in women with diabetes in pregnancy that compared telemedicine blood glucose monitoring with the standard care were identified. Searches were performed in SCOPUS and PubMed, limited to English language publications between January 2000 and January 2016. Trials that met the eligibility criteria were scored for risk of bias using the Cochrane Collaborations Risk of Bias Tool. A meta-analysis was performed using Review Manager software version 5.3 (Nordic Cochrane Centre, Cochrane Collaboration). Results A total of 7 trials were identified. Meta-analysis demonstrated a modest but statistically significant improvement in HbA1c associated with the use of a telemedicine technology. The mean HbA1c of women using telemedicine was 5.33% (SD 0.70) compared with 5.45% (SD 0.58) in the standard care group, representing a mean difference of −0.12% (95% CI −0.23% to −0.02%). When this comparison was limited to women with gestational diabetes mellitus (GDM) only, the mean HbA1c of women using telemedicine was 5.22% (SD 0.70) compared with 5.37% (SD 0.61) in the standard care group, mean difference −0.14% (95% CI −0.25% to −0.04%). There were no differences in other maternal and neonatal outcomes reported. Conclusions There is currently insufficient evidence that telemedicine technology is superior to standard care for women with diabetes in pregnancy; however, there was no evidence of harm. No trials were identified that assessed patient satisfaction or cost of care delivery, and it may be in these areas where these technologies may be found most valuable.
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Affiliation(s)
- Wai-Kit Ming
- Nuffield Department of Obstetrics & Gynaecology, John Radcliffe Hospital, Oxford, United Kingdom.,Department of Obstetrics & Gynaecology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Lucy H Mackillop
- Women's Centre, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lise Loerup
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Katy Bartlett
- Women's Centre, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - Jonathan C Levy
- The Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - Lionel Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Carmelo Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Yvonne Kenworthy
- Nuffield Department of Obstetrics & Gynaecology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Jane E Hirst
- Nuffield Department of Obstetrics & Gynaecology, John Radcliffe Hospital, Oxford, United Kingdom
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Hirst JE, Loerup L, Mackillop L, Farmer A, Kenworthy Y, Bartlett K, Velardo C, Kevat DA, Tarassenko L, Levy JC. Digital blood glucose monitoring could provide new objective assessments of blood glucose control in women with gestational diabetes. Diabet Med 2016; 33:1598-1599. [PMID: 26606543 DOI: 10.1111/dme.13035] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- J E Hirst
- Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Oxford, UK
| | - L Loerup
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - L Mackillop
- Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Oxford, UK
- Oxford University Hospitals, NHS Trust, Oxford, UK
| | - A Farmer
- Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Y Kenworthy
- Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Oxford, UK
| | - K Bartlett
- Oxford University Hospitals, NHS Trust, Oxford, UK
| | - C Velardo
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - D A Kevat
- Oxford University Hospitals, NHS Trust, Oxford, UK
| | - L Tarassenko
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - J C Levy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals, NHS Trust, Oxford, UK
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Chantler T, Paton C, Velardo C, Triantafyllidis A, Shah SA, Stoppani E, Conrad N, Fitzpatrick R, Tarassenko L, Rahimi K. Creating connections - the development of a mobile-health monitoring system for heart failure: Qualitative findings from a usability cohort study. Digit Health 2016; 2:2055207616671461. [PMID: 29942568 PMCID: PMC6001232 DOI: 10.1177/2055207616671461] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Accepted: 09/02/2016] [Indexed: 11/17/2022] Open
Abstract
Objective There is significant interest in the role of digital health technology in enabling optimal monitoring of heart failure patients. To harness this potential, it is vital to account for users' capacity and preferences in the development of technological solutions. We adopted an iterative approach focussed on learning from users' interactions with a mobile-health monitoring system. Methods We used a participatory mixed methods research approach to develop and evaluate a mobile-health monitoring system. Fifty-eight heart failure patients were recruited from three health care settings in the UK and provided with Internet-enabled tablet computers that were wirelessly linked to sensor devices for blood pressure, heart rate and weight monitoring. One to two home visits were conducted with a subgroup of 29 participants to evaluate the usability of the system over a median follow-up period of six months. The thematic analysis of observational data and 45 interviews was informed by the domestication of technology theory. Results Our findings indicate that digital health technologies need to create and extend connections with health professionals, be incorporated into users' daily routines, and be personalised according to users' technological competencies and interest in assuming a proactive or more passive role in monitoring their condition. Conclusions Users' patterns of engagement with health technology changes over time and varies according to their need and capacity to use the technology. Incorporating diverse user experiences in the development and maintenance of mobile-health systems is likely to increase the extent of successful uptake and impacts on outcomes for patients and providers.
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Affiliation(s)
- Tracey Chantler
- George Institute for Global Health, University of Oxford, UK.,London School of Hygiene and Tropical Medicine, UK
| | - Chris Paton
- George Institute for Global Health, University of Oxford, UK
| | - Carmelo Velardo
- Institute of Biomedical Engineering, University of Oxford, UK
| | | | - Syed A Shah
- Institute of Biomedical Engineering, University of Oxford, UK
| | - Emma Stoppani
- George Institute for Global Health, University of Oxford, UK
| | - Nathalie Conrad
- George Institute for Global Health, University of Oxford, UK
| | | | | | - Kazem Rahimi
- George Institute for Global Health, University of Oxford, UK.,Division of Cardiovascular Medicine, University of Oxford, UK
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Mackillop LH, Bartlett K, Birks J, Farmer AJ, Gibson OJ, Kevat DA, Kenworthy Y, Levy JC, Loerup L, Tarassenko L, Velardo C, Hirst JE. Trial protocol to compare the efficacy of a smartphone-based blood glucose management system with standard clinic care in the gestational diabetic population. BMJ Open 2016; 6:e009702. [PMID: 26988348 PMCID: PMC4800121 DOI: 10.1136/bmjopen-2015-009702] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
INTRODUCTION The prevalence of gestational diabetes mellitus (GDM) is rising in the UK. Good glycaemic control improves maternal and neonatal outcomes. Frequent clinical review of patients with GDM by healthcare professionals is required owing to the rapidly changing physiology of pregnancy and its unpredictable course. Novel technologies that allow home blood glucose (BG) monitoring with results transmitted in real time to a healthcare professional have the potential to deliver good-quality healthcare to women more conveniently and at a lower cost to the patient and the healthcare provider compared to the conventional face-to-face or telephone-based consultation. We have developed an integrated GDm-health management system and aim to test the impact of using this system on maternal glycaemic control, costs, patient satisfaction and maternal and neonatal outcomes compared to standard clinic care in a single large publicly funded (National Health Service (NHS)) maternity unit. METHODS AND ANALYSIS Women with confirmed gestational diabetes in a current pregnancy are individually randomised to either the GDm-health system and half the normal clinic visits or normal clinic care. Primary outcome is mean BG in each group from recruitment to delivery calculated, with adjustments made for number of BG measurements, proportion of preprandial and postprandial readings and length of time in study, and compared between the groups. The secondary objective will be to compare the two groups for compliance to the allocated BG monitoring regime, maternal and neonatal outcomes, glycaemic control using glycated haemoglobin (HbA1c) and other BG metrics, and patient attitudes to care assessed using a questionnaire and resource use. ETHICS AND DISSEMINATION Thresholds for treatment, dietary advice and clinical management are the same in both groups. The results of the study will be published in a peer-reviewed journal and disseminated electronically and in print. TRIAL REGISTRATION NUMBER NCT01916694; Pre-results.
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Affiliation(s)
- Lucy H Mackillop
- Nuffield Department of Obstetrics & Gynaecology, Level 3, Women's Centre, John Radcliffe Hospital, Oxford, UK
| | - Katy Bartlett
- Women's Centre, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Jacqueline Birks
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | - Andrew J Farmer
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Oliver J Gibson
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Dev A Kevat
- Department of Endocrinology, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
- School of Public Health, Monash University, Melbourne, Australia
| | - Yvonne Kenworthy
- Nuffield Department of Obstetrics & Gynaecology, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Jonathan C Levy
- The Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Lise Loerup
- Department of Engineering Science, University of Oxford, Oxford, UK
| | | | - Carmelo Velardo
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Jane E Hirst
- Nuffield Department of Obstetrics & Gynaecology, Oxford University Hospitals NHS Trust, Oxford, UK
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Shah SA, Velardo C, Gibson OJ, Rutter H, Farmer A, Tarassenko L. Personalized alerts for patients with COPD using pulse oximetry and symptom scores. Annu Int Conf IEEE Eng Med Biol Soc 2015; 2014:3164-7. [PMID: 25570662 DOI: 10.1109/embc.2014.6944294] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a progressive chronic disease, predicted to become the third leading cause of death by 2030. COPD patients are at risk of sudden and acute worsening of symptoms, reducing the patient's quality of life and leading to hospitalization. We present the results of a pilot study with 18 COPD patients using an m-Health system, based on a tablet computer and pulse oximeter, for a period of six months. For prioritizing patients for clinical review, a data-driven approach has been developed which generates personalized alerts using the electronic symptom diary, pulse rate, blood oxygen saturation, and respiratory rate derived from oximetry data. This work examines the advantages of multivariate novelty detection over univariate approaches and shows the benefit of including respiratory rate as a predictor.
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Triantafyllidis A, Velardo C, Chantler T, Shah SA, Paton C, Khorshidi R, Tarassenko L, Rahimi K. A personalised mobile-based home monitoring system for heart failure: The SUPPORT-HF Study. Int J Med Inform 2015; 84:743-53. [DOI: 10.1016/j.ijmedinf.2015.05.003] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Revised: 12/27/2014] [Accepted: 05/13/2015] [Indexed: 11/25/2022]
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Triantafyllidis AK, Velardo C, Salvi D, Shah SA, Koutkias VG, Tarassenko L. A Survey of Mobile Phone Sensing, Self-Reporting, and Social Sharing for Pervasive Healthcare. IEEE J Biomed Health Inform 2015; 21:218-227. [PMID: 26441432 DOI: 10.1109/jbhi.2015.2483902] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The current institution-based model for healthcare service delivery faces enormous challenges posed by an aging population and the prevalence of chronic diseases. For this reason, pervasive healthcare, i.e., the provision of healthcare services to individuals anytime anywhere, has become a major focus for the research community. In this paper, we map out the current state of pervasive healthcare research by presenting an overview of three emerging areas in personalized health monitoring, namely: 1) mobile phone sensing via in-built or external sensors, 2) self-reporting for manually captured health information, such as symptoms and behaviors, and 3) social sharing of health information within the individual's community. Systems deployed in a real-life setting as well as proofs-of-concept for achieving pervasive health are presented, in order to identify shortcomings and increase our understanding of the requirements for the next generation of pervasive healthcare systems addressing these three areas.
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Rahimi K, Velardo C, Triantafyllidis A, Conrad N, Shah SA, Chantler T, Mohseni H, Stoppani E, Moore F, Paton C, Emdin CA, Ernst J, Tarassenko L, Rahimi K, Velardo C, Triantafyllidis A, Conrad N, Ahmar Shah S, Chantler T, Mohseni H, Stoppani E, Moore F, Paton C, Tarassenko L, Cleland J, Emptage F, Chantler T, Farmer A, Fitzpatrick R, Hobbs R, MacMahon S, Perkins A, Rahimi K, Tarassenko L, Altmann P, Chandrasekaran B, Emdin CA, Ernst J, Foley P, Hersch F, Salimi-Khorshidi G, Noble J, Woodward M. A user-centred home monitoring and self-management system for patients with heart failure: a multicentre cohort study. Eur Heart J Qual Care Clin Outcomes 2015; 1:66-71. [PMID: 29474596 DOI: 10.1093/ehjqcco/qcv013] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 07/03/2015] [Indexed: 11/13/2022]
Abstract
Aims Previous generations of home monitoring systems have had limited usability. We aimed to develop and evaluate a user-centred and adaptive system for health monitoring and self-management support in patients with heart failure. Methods and results Patients with heart failure were recruited from three UK centres and provided with Internet-enabled tablet computers that were wirelessly linked with sensor devices for blood pressure, heart rate, and weight monitoring. Patient observations, interviews, and concurrent analyses of the automatically collected data from their monitoring devices were used to increase the usability of the system. Of the 52 participants (median age 77 years, median follow-up 6 months [interquartile range, IQR, 3.6-9.2]), 24 (46%) had no, or very limited prior, experience with digital technologies. It took participants about 1.5 min to complete the daily monitoring tasks, and the rate of failed attempts in completing tasks was <5%. After 45 weeks of observation, participants still used the system on 4.5 days per week (confidence interval 3.2-5.7 days). Of the 46 patients who could complete the final survey, 93% considered the monitoring system as easy to use and 38% asked to keep the system for self-management support after the study was completed. Conclusion We developed a user-centred home monitoring system that enabled a wide range of heart failure patients, with differing degrees of IT literacy, to monitor their health status regularly. Despite no active medical intervention, patients felt that they benefited from the reassurance and sense of connectivity that the monitoring system provided.
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Affiliation(s)
- Kazem Rahimi
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Carmelo Velardo
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | | | - Nathalie Conrad
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Syed Ahmar Shah
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Tracey Chantler
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Hamid Mohseni
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Emma Stoppani
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Francesca Moore
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Chris Paton
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Connor A Emdin
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
| | - Johanna Ernst
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK.,Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- Division of Cardiovascular Medicine, George Institute for Global Health, University of Oxford, Broad Street 34, Oxford OX1 3DB, UK
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