Digital Health Advisers – The ‘person connection’ in Digital Health.
13 Oct, 2022
my mhealth recognised there was a need to create person-centred digital app delivery and support which led to the development of the DHA.
The NHS is facing continuing pressures with waiting lists at an all-time high(1). The increasing demand reaches across the health system affecting millions of patients and staff, recently exacerbated by the pandemic(2). GP practices across the UK continue to struggle with high demand and a reduction in workforce resulting in a knock-on effect for patients(3). Additionally, NHS hospital trusts are experiencing a backlog of patients leading to long waiting times and overdue appointments(4).
Those who suffer from a long-term health condition such as heart disease, diabetes and respiratory disease who require regular health reviews are unlikely to be receiving the support they need meaning, for the most part, they must manage their health themselves. However, without the skills, knowledge and confidence to self-manage, their health may be at greater risk. Digital health can provide patients and clinicians with an additional tool to create a supported self-management process(5), but many challenges exist with digital implementation on an already overstretched health service.
The digital revolution in healthcare.
Digital health interventions such as wellness, self-care and activity apps have been shown to promote healthy behaviours such as smoking cessation, reduced alcohol intake, support with exercise, and eating a healthy diet(6). Furthermore, recent evidence shows they can improve outcomes for patients with long-term conditions(6)(7)(8)(9), and importantly, they can improve accessibility to health-related information. Pre-pandemic the uptake of digital health technologies was slow(2)(10), however with the emergence of COVID-19, they became an immediate necessity and digital health adoption was greatly accelerated within healthcare service delivery(11)(12). NHS Digital reported a 111% usage increase in NHS app registrations(13).
Despite digital health interventions offering numerous benefits, a great challenge is promoting uptake and engagement(14)(15)(16). Making an App available to clinical teams and patients is unlikely to be enough to drive adoption and engagement. Instead, when deploying a solution, it’s imperative that the local needs of healthcare teams and their patients are considered carefully and a personal approach is taken. To ensure healthcare teams receive the necessary support to implement digital self-management apps with a personal touch, my mhealth created the Digital Health Adviser (DHA).
The Digital Health Adviser.
my mhealth recognised there was a need to create person-centred digital app delivery and support which led to the development of the DHA. By bringing together the technology and the needs of the service the perceived ‘heavy lift’ challenge of a digital transformation project has been reduced.This role works in partnership with my mhealth and the healthcare provider using an honorary contract. The healthcare team provides them with a list of patients to contact and offer the app(s). Those patients who would like to use the app(s) are offered guidance on how to use and are signposted to content related to goals set by the clinical teams. Similarly, the DHA’s support clinicians to engage with the technology, providing them with the skills to support, enhance and scale their service.
Since the creation of this new role, the benefits became evident very quickly. As a result, we now have a team of DHA’s working with NHS healthcare services across the country. They bridge the gap between the digital health platform, the clinician and the patient to support app uptake and engagement. Importantly, they promote digital inclusion and encourage the creation of local community digital champions. Figure 1 shows the increase in app usage for just five NHS sites since the DHA role was implemented.
- Case StudiesIn Mid and South Essex (MSE) DHA support was provided to compliment a drive from the clinical services to engage patients in myDiabetes. This saw an increase in app registrations from 1654 to 6356 users within 2 years, demonstrating a 284% increase. Furthermore, within 1 year in-app education video activity increased from 10,316 to 21,272
- Knowsley saw an increase in app registration from 277 to 3788 following DHA implementation over 2 years (1267% increase)
- Using the DHA, Cambridge and Peterborough CCG provided continuous access to education and self-management support using myAsthma, promoting equal access to the service for the local population. Nine practices with the highest healthcare utilisation were provided with 900 myAsthma licenses. All of these were supplied to patients within 6 months, of which 720 (80%) of patients activated the app.
- Kent and Medway CCG have registered over 6000 patients to the myDiabetes app in support of Structured Diabetes Education, driving a 200% increase in enrolment to the programme in 18 months.
Providing the ‘human’ connection in digital health Studies have shown that providing ‘human’ support in digital health interventions improves patient engagement(17). The DHA is the person-link between digital health apps, clinicians and patient users, providing a structured route for the implementation of digital therapeutics into the NHS at population scale, reaching high levels of user engagement. The interaction of the DHA with clinical teams is vital to increasing confidence in using technology for both clinicians and patients, working towards reducing digital exclusion. The DHA’s are in constant contact with clinical teams to support their service and patients to encourage usage to promote self-management. They are also able to obtain important feedback of how the app(s) are functioning in the real-world. Some comments received from clinical teams are:
“The DHA oversees the smooth running of patients who sign up for the app. They help patients with their many queries, and help the admin team to contact patients to take up the App. I could not do this part of my job without their input. Aside from the obvious impact they have on our patient’s education and management of their health, they are also enthusiastic and have a ‘can do’ attitude which really makes a difference when trying to encourage patients to use the app modules. They make my job much easier. I am so grateful for their help and feel totally supported at all times.” (Healthcare Administrator)
“Working with my mhealth and the DHA’s has been invaluable to our practice. Their help and support has enabled them to give patients an informed choice on how to manage their chronic disease. Not only has this taken pressure off general practice it has given people the tools they need to improve and manage their own health.” (Nurse Specialist)
Feedback from patients receiving DHA support include:
“Without your help I would have been 'out' of the my mhealth app for ever! Thank you so much for your patience and help with getting me started.”
“I have completed the exercises in Lifestyle tile is there another exercise tile or do I repeat what I have already completed? Your help would be appreciated.”
“Thank you for helping me - it's been a life changer for me and you can quote me on that.”
“For me personally to have someone as supportive as the DHA is as and when you need is invaluable. Diabetes is scary I'm still pretty new at finding out but the way your life works around it but with the proactiveness and correspondence and the regular updates from the DHA I don't know where I would be without it.”
As more healthcare services look to benefit from this support, the DHA team is expanding to meet the growing demand. Clinical partners are demonstrating a true step-change in the delivery of digital health to support healthcare delivery at population scale. Importantly, patients are provided with support both digitally and personally to self-manage their long-term condition without losing the human connection with their clinical teams.
References
Gardner T. Pressures on the NHS are far from ‘sustainable’ [Internet]. The Health Foundation. 2021 [cited 2022 Aug 24]. Available from: https://www.health.org.uk/news-and-comment/news/pressures-on-the-nhs-are-far-from-sustainable- Peek N, Sujan M, Scott P. Digital health and care in pandemic times : impact of COVID-19. BMJ Heal Care Informatics [Internet]. 2020;27:1–3. Available from: https://informatics.bmj.com/content/27/1/e100166
- Royal College of General Practitioners. Chronic shortage of GPs is the reason patients are facing long waiting times for appointments [Internet]. RCGP. 2021 [cited 2022 Aug 24]. Available from: https://www.rcgp.org.uk/news/2021/september/chronic-shortage-of-gps-is-the-reason-patients-are-facing-long-waiting-times-for-appointments
- United Lincolnshire Hospitals NHS Trust. Waiting for your outpatient appointment during the COVID-19 Pandemic [Internet]. NHS Trust. 2021 [cited 2022 Aug 24]. Available from: https://www.ulh.nhs.uk/patients/outpatients/waiting-for-your-outpatient-appointment-during-the-covid-19-pandemic/
- Bene BA, O’Connor S, Mastellos N, Majeed A, Fadahunsi KP, O’Donoghue J. Impact of mobile health applications on self-management in patients with type 2 diabetes mellitus: Protocol of a systematic review. BMJ Open. 2019;9(6).
- Murray E, Hekler EB, Professor A, Andersson G, Collins LM, Doherty A, et al. Evaluating digital health interventions: key questions and approaches HHS Public Access Background & Aims. Am J Prev Med [Internet]. 2016;51(5):843–51. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324832/pdf/nihms850074.pdf
- Murray E, Ross J, Pal K, Li J, Dack C, Stevenson F, et al. A web-based self-management programme for people with type 2 diabetes: the HeLP-Diabetes research programme including RCT. Program Grants Appl Res. 2018;6(5):1–242.
- Crooks MG, Elkes J, Storrar W, Roy K, North M, Blythin A, et al. Evidence generation for the clinical impact of myCOPD in patients with mild, moderate and newly diagnosed COPD: a randomised controlled trial. ERJ Open Res [Internet]. 2020;6(4):00460–2020. Available from: http://dx.doi.org/10.1183/23120541.00460-2020
- Nabutovsky I, Nachshon A, Klempfner R, Shapiro Y and TR. Digital Cardiac Rehabilitation Programs: The Future of Patient-Centred Medicine. Telemed e-Health [Internet]. 2020;26(1):34–41. Available from: https://www.liebertpub.com/doi/10.1089/tmj.2018.0302#:~:text=These programs imply a high level of patient,no significant differences in mortality or hospitalizations
- Pillay R. Digital Health Trends [Internet]. 2021. Available from: https://www.iqvia.com/-/media/iqvia/pdfs/institute-reports/digital-health-trends-2021/iqvia-institute-digital-health-trends-2021.pdf?&_=1630938621119
- National Diabetes Audit. Improving attendance and data recording for structured education. 2018; Available from: https://www.diabetes.org.uk/resources-s3/2018-12/SE Guidance_ v3.pdf
- DESMOND. MyDESMOND eLearning Platform [Internet]. 2019 [cited 2020 Sep 25]. Available from: https://www.desmond-project.org.uk/portfolio/mydesmond-elearning-platform/
- Poinasamy K. Useful Digital Health Apps and Platforms [Internet]. BLF and Asthma UK. 2022 [cited 2022 Feb 7]. Available from: https://www.asthma.org.uk/support-us/campaigns/campaigns-blog/useful-digital-health-apps-and-platforms/
- McGowan PT. Self-Management Education and Support in Chronic Disease Management. Prim Care Clin Off Pract [Internet]. 2012;39(2):307–25. Available from: https://www.sciencedirect.com/science/article/abs/pii/S009545431200019X?via%3Dihub
- Murray E, Sweeting M, Dack C, Pal K, Modrow K, Hudda M, et al. Web-based self-management support for people with type 2 diabetes (HeLPDiabetes): Randomised controlled trial in English primary care. BMJ Open. 2017;7(9):1–11.
- Torous J, Myrick KJ, Rauseo-Ricupero N, Firth J. Digital mental health and COVID-19: Using technology today to accelerate the curve on access and quality tomorrow. JMIR Ment Heal. 2020;7(3):1–6.
- Ritterband LM, Thorndike FP, Cox DJ, Kovatchev BP, Gonder-Frederick LA. A behavior change model for internet interventions. Ann Behav Med. 2009;38(1):18–27.
About my mhealthmy mhealth’s digital therapeutics have been prescribed to over 80,000 patients with chronic conditions, resulting in reduced morbidity and hospital admissions. It serves patients across a range of long term conditions, including COPD, asthma, diabetes and cardiovascular disease. Our flagship product, myCOPD, was the exclusive digital therapeutic deployed by the UK’s NHS to deliver pulmonary rehabilitation during the pandemic, when in person care was practically inaccessible. Real world and clinical trial evidence demonstrates the efficacy of digital interventions on the my mhealth platform.
For more information on my mhealth, visit www.mymhealth.com.
NHS University College London Hospitals NHS Foundation Trust, part of North Central London ICB, is taking a significant step towards enhancing patient empowerment and optimising disease management. Asthma is a chronic condition that affects millions of people worldwide, often leading to severe health complications if not managed properly. Recognising the critical need for effective self-management tools, NHS University College London Hospitals NHS Foundation Trust has chosen the myAsthma app to provide patients with the resources they need to take control of their health. Dr Kay Roy PhD FRCP, Consultant Respiratory Physician University College London Hospitals NHS Foundation Trust, comments “We are thrilled to introduce myAsthma as a self-management tool to our community. It represents a significant step forward in empowering our patients with asthma to take control of their health. By providing them with personalised support, we believe this tool will greatly improve their quality of life. Additionally, the use of myAsthma in outpatient settings will help triage patients more effectively, ensuring they are seen in a timely manner and appropriately referred for the right investigations and services. Our team is excited to see the positive impact this will have on the asthma population across North Central London ICB." The myAsthma app, part of the my mhealth suite of digital health solutions, is designed to empower patients with comprehensive tools and information to manage their asthma more effectively. Key features include: • Personalised Action Plans: Tailored asthma management plans based on individual patient needs. • Inhaler technique training: Contributing to better health outcomes and reduced risk of exacerbations • Medication Tracking: Reminders and logs to ensure patients take their medication as prescribed. • Symptom tracking: Easy-to-use tools for tracking symptoms and triggers. • Educational Resources: Access to a wealth of information on asthma, helping patients understand their condition and how to manage it. As more NHS partners embrace the my mhealth platform, we're thrilled to witness its growing impact and the positive changes it is bringing to long-term condition care. For more information on this article or other my mhealth projects, please get in touch https://mymhealth.com/contact-us
The my mhealth data library is an extensive resource designed to support healthcare providers by offering a wealth of information and tools related to COPD and long-term health conditions.
Permission to use received from Rebecca Fowler View poster
Henry M.G. Glyde1Alison M. Blythin2 Tom M.A. Wilkinson3Ian T. Nabney4 James W. Dodd5 EPSRC Centre for Doctoral Training in Digital Health and Care, University of Bristol, Bristol, UK my mHealth Limited, Bournemouth , UK my mHealth and Clinical and Experimental Science, University of Southampton, Southampton, UK School of Engineering Mathematics and Technology, University of Bristol, Bristol, UK Academic Respiratory Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK Abstract Background Acute exacerbations of COPD (AECOPD) are episodes of breathlessness, cough and sputum which are associated with the risk of hospitalisation, progressive lung function decline and death. They are often missed or diagnosed late . Accurate timely intervention can improve these poor outcomes. Digital tools can be used to capture symptoms and other clinical data in COPD. This study aims to apply machine learning to the largest available real-world digital dataset to identify AECOPD Prediction tool which could be used to support early intervention improve clinical outcomes. Objective To create and validate a machine learning predictive model that forecasts exacerbations of COPD 1-8 days in advance. The model is based on routine patient-entered data from myCOPD self-management app. Method Adaptations of the AdaBoost algorithm were employed as machine learning approaches. The dataset included 506 patients users between 2017-2021. 55,066 app records were available for stable COPD event labels and 1,263 records of AECOPD event labels. The data used for training the model included COPD assessment test (CAT) scores, symptom scores, smoking history, and previous exacerbation frequency. All exacerbation records used in the model were confined to the 1-8 days preceding a self-reported exacerbation event. Results TheEasyEnsemble Classifier resulted in a Sensitivity of 67.0% and a Specificity of 65% with a positive predictive value (PPV) of 5.0% and a negative predictive value (NPV) of 98.9%. An AdaBoost model with a cost-sensitive decision tree resulted in a a Sensitivity of 35.0% and a Specificity of 89.0% with a PPV of 7.08% and NPV of 98.3%. Conclusion This preliminary analysis demonstrates that machine learning approaches to real-world data from a widely deployed digital therapeutic has the potential to predict AECOPD and can be used to confidently exclude the risk of exacerbations of COPD within the next 8 days. Permission to use received from Henry Glyde. Read more on Heliyon website.
Charlotte Smith 1 Francesca D’angelo 2 University Hospital of Derby and Burton, Cardiac Rehabilitation Department, Burton Upon Trent, UK. University Hospital of Derby and Burton, Health and Wellbeing Department, Burton, UK To examine the effectiveness of physical activity outcomes using a web-based Cardiac Rehabilitation application compared with a conventional programme or a combination of both. University Hospitals of Derby and Burton NHS Foundation Trust poster presented at the BACPR Annual Conference October 5-6th 2023 Permission to use received from Charlotte Smith
Francesca D’angelo 1 Charlotte Smith 2 University Hospital of Derby and Burton, Health and Wellbeing Department, Burton, UK University Hospital of Derby and Burton, Cardiac Rehabilitation Department, Burton Upon Trent, UK. To examine the effectiveness of psychological outcomes using a web-based Cardiac Rehabilitation application compared with a conventional programme or a combination of both. University Hospitals of Derby and Burton NHS Foundation Trust poster presented at the BACPR Annual Conference October 5-6th 2023 Poster presented at the BACPR Annual Conference October 5-6th 2023 Permission to use received from Charlotte Smith
Christopher Duckworth 1 Bethany Cliffe 2. Brian Pickering 1 Ben Ainsworth 2 Alison Blythin 3 Adam Kirk 3 Adam Kirk Thomas M. A. Wilkinson 3,4,5 Michael J. Boniface 1 1 IT Innovation Centre, Digital Health and Biomedical Engineering, University of Southampton, Southampton, UK. 2. School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK my mHealth Limited, London, UK. National Institute for Health Research Applied Research Collaboration Wessex, University of Southampton , Southampton , GB Faculty of Medicine, University of Southampton, Southampton , GB Mobile Health (mHealth) has the potential to be transformative in the management of chronic conditions. Machine learning can leverage self-reported data collected with apps to predict periods of increased health risk, alert users, and signpost interventions. Despite this, mHealth must balance the treatment burden of frequent self-reporting and predictive performance and safety. Here we report how user engagement with a widely used and clinically validated mHealth app, myCOPD (designed for the self-management of Chronic Obstructive Pulmonary Disease), directly impacts the performance of a machine learning model predicting an acute worsening of condition (i.e., exacerbations). We classify how users typically engage with myCOPD, finding that 60.3% of users engage frequently, however, less frequent users can show transitional engagement (18.4%), becoming more engaged immediately ( < 21 days) before exacerbating. Machine learning performed better for users who engaged the most, however, this performance decrease can be mostly offset for less frequent users who engage more near exacerbation. We conduct interviews and focus groups with myCOPD users, highlighting digital diaries and disease acuity as key factors for engagement. Users of mHealth can feel overburdened when self-reporting data necessary for predictive modelling and confidence of recognising exacerbations is a significant barrier to accurate self-reported data. We demonstrate that users of mHealth should be encouraged to engage when they notice changes to their condition (rather than clinically defined symptoms) to achieve data that is still predictive for machine learning, while reducing the likelihood of disengagement through desensitisation. Read more
Christopher Duckworth 1 Michael J Boniface 1 Adam Kirk 2 Thomas M A Wilkinson 2 3 4 IT Innovation Centre, Digital Health and Biomedical Engineering, University of Southampton, Southampton, UK. my mHealth Limited, London, UK. National Institute for Health Research Applied Research Collaboration Wessex, University of Southampton , Southampton , GB Faculty of Medicine, University of Southampton, Southampton , GB Introduction: The GOLD (Global Initiative for Chronic Obstructive Lung Disease) 2023 guidelines proposed important changes to the stratification of disease severity using the "ABCD" assessment tool. The highest risk groups "C" and "D" were combined into a single category "E" based on exacerbation history, no longer considering symptomology. Purpose: We quantify the differential disease progression of individuals initially stratified by the GOLD 2022 "ABCD" scheme to evaluate these proposed changes. Patients and methods: We utilise data collected from 1529 users of the myCOPD mobile app, a widely used and clinically validated app supporting people living with COPD in the UK. For patients in each GOLD group, we quantify symptoms using COPD Assessment Tests (CAT) and rate of exacerbation over a 12-month period post classification. Results: CAT scores for users initially classified into GOLD C and GOLD D remain significantly different after 12 months (Kolmogorov-Smirnov statistic = 0.59, P = 8.2 × 10-23). Users initially classified into GOLD C demonstrate a significantly lower exacerbation rate over the 12 months post classification than those initially in GOLD D (Kolmogorov-Smirnov statistic = 0.26; P = 3.1 × 10-2; all exacerbations). Further, those initially classified as GOLD B have higher CAT scores and exacerbation rates than GOLD C in the following 12 months. Conclusion: CAT scores remain important for stratifying disease progression both in-terms of symptomology and future exacerbation risk. Based on this evidence, the merger of GOLD C and GOLD D should be reconsidered. Read more
Alison M. Blythin 1 Jack Elkes 2 Ronie Walter 3 Amber Bhogal 1 Ian Thompson Thomas van Lindholm 1 Matt Smith 1 Trish Gorely 3 Tom M.A. Wilkinson 1,5 Stephen J. Leslie 3,4 and Adam Kirk 1 my mhealth Limited, London, UK Imperial College London Clinical Trials Unit, London, UK University of the Highlands and Islands, SCOTLAND NHS Highlands Cardiology Department, SCOTLAND University of Southampton Faculty of Medicine, UK COVID-19 significantly impacted cardiac rehabilitation (CR) delivery. Service disruption left numerous patients without treatment access. Many healthcare teams made use of digital apps to support CR delivery and patients remotely. This evaluation aimed to analyse digital CR access from the myHeart interactive, cloud-based self-management app during the pandemic. Five NHS secondary care CR services agreed to combine existing anonymised app data between Mar-Oct 2020 for 12-weeks to align as much as possible with traditional CR models. No statistically significant differences were observed across age groups or gender between users who activated myHeart and those who did not. N=314/350 (89.7%) users accessed 5,469 CR videos with N=313/314 (99.7%) accessing 3,606 within the first 6-weeks of activation. No statistically significant differences were observed across gender or age group for education video views. Users with angina only diagnosis accessed more exercise videos than those with other reported diagnoses. Patient user feedback responses showed a statistically significant increase in self-management confidence following myHeart access. myHeart provided remote timely CR during service disruption. This evaluation is the beginning of a journey to understand app usage however further research is needed to fully understand the role digital health can play in the delivery of CR.f your post goes he re. To edit this text, click on it and delete this default text and start typing your own or paste your own from a different source. Read more.
A.M. Blythin 1, J. Elkes 2 T. van Lindholm 1 A. Bhogal 1 T.M.A. Wilkinson 1 C. Saville 3 A. Kirk 1 Department of Research & Innovation, my mhealth Limited, Bournemouth, UK. School of Public Health, Imperial College Clinical Trials Unit, London, UK. Faculty of Medicine, University of Southampton, Southampton, Hampshire, UK Digital health interventions provide a potential solution to improve diabetes education delivery at population scale, overcoming barriers identified with traditional approaches. This evaluation analysed usage data for people with type 2 diabetes focusing on digital structured diabetes education. Results showed a positive uptake and usage with myDiabetes, with increases in app activity post-COVID. No statistically significant differences were observed between gender or age for those activated. No statistically significant differences observed in education video views across age groups, gender, diabetes treatment type or smoking status. The findings support the use of digital health in the provision of additional support for the delivery of diabetes education. There is potential for increasing diabetes education rates by offering patients a digital option in combination with traditional service delivery which should be substantiated through future research. Read more
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