Brief exploration of the background to Telehealth Overview of our research programme

1. Telemetric Supported Self-Monitoring of Long-Term ConditionsBrian McKinstry (lead), Martin Egan (NHS Lothian), Janet Hanley (Qualitative), Paul Padfield (HBP), Hilary Pinnock (COPD), John McKnight (diabetes), Cathie Sudlow (stroke) Sarah Wild (epidemiology), Steff Lewis (statistics), Marjon van der Pol (economics), Claudia Pagliari (e-health), Lucy McCloughan (programme manager), Aziz Sheikh (primary care), Bill MacNee (respiratory), Sandra Auld (telecare). Collaborators: Wisia Wedzicha (COPD), J Roca (telemetry), Martin Dennis (stroke), Martin Denvir (CCF), Colin Fischbacher (ISD), John Steyn (GP IT), Angela Lindsay (physiotherapy)

2. Brief exploration of the background to Telehealth • Overview of our research programme • What patients and clinicians think of it • Discussion about what is useful to measure and how to interpret such measures • Implementation

3. Rapidly Aging Population • Expected growth in elderly population Scotland

4. Increasingly Unhealthy

5. Rise in Long Term Conditions • 17.5 million UK adults are living with a chronic disease • By 2030 the incidence of chronic disease will double

6. So how do we cope? • Policy drive towards self-monitoring and self-care • Is self-monitoring effective?

7. Why does self-monitoring fail • Difficulty in maintaining motivation • Infrequent feedback from clinical staff • Therapeutic inertia

8. Telemetrically supported supervised self-monitoring

9. Call centre Call to check situation Constant monitoring of potentially unstable conditions (e.g. COPD) Urgent referral if required Reminders to self monitor Automated feedback Links to online information Relatively stable conditions (e.g. diabetes, BP) checked intermittently (normally by practice nurse Internet or SMS Home GP practice Patient takes readings and enters symptom score Remote server Telephone or videolink Consultation arranged as appropriate Record of readings and symptom scores Models of telemetric supported self monitoring

10. Clinician View

11. Streaming Data

12. Does it work • Do patients and doctors like it? • Are outcomes improved? • Does it actually save time and resources?

13. TeleScot Randomised Controlled Trials • Hypertension • A common largely asymptomatic condition (n=400) • Stroke/HBP • Affecting older frailer group with challenging targets (n=400) • Diabetes • A condition requiring multiple measurements, blood pressure, blood glucose and weight (n=270) • COPD • A symptomatic potentially unstable progressive condition (n=300)

14. Qualitative and Economic Evaluations

15. COPD pilot • Complete questionnaire each day • Physiological measures as needed • Call centre monitors

16. COPDmonitoring Each day, please record any WORSENING of symptoms from your usual daily level. I am more breathless than usual My sputum has increased in colour My sputum has increased in amount I have a cold (such as runny or blocked nose) I have increased wheeze or chest tightness I have an increased cough I have a fever I have a sore throat <3is OK 3-4 watch next day 5+take action

17. Do the patients like it? • “I’ve never felt so well looked after in my life. I think it’s a godsend like.” (Patient aged 58) • “I don’t worry about him the same as I used tae. It’s all taken care of before it can get tae that level. That machine can tell Alec he’s ill even before he kens it hisself” (Spouse of patient aged 75) • “There’s some times you phone them up for an appointment ye cannae get one. . . So I feel if I’ve got that (telehealth device) I’ve got a chance of a doctor anyway.” (Patient age 75) • ”

18. What do the clinicians think? • Some concerns about workload • Worries about medicalisation • Concerns about false positives • Worries about the utility of physiological measurements • Some medicolegal worries

19. Workload • Doubling of prescriptions of antibiotics, prednisolone • Doubling of the number of times the record is opened • But • Probably reflects previously undiagnosed exacerbations • Partly reflects non-optimised care • Important to have a good existing infrastructure for management of exacerbations

20. Making sense of the symptom and telemetry data • Some patients have difficulty distinguishing ‘bad days’ from exacerbations • How do physiological measures relate to symptoms and exacerbations? • What types of measure are likely to be helpful • Is individual variation too great to allow setting parameters

21. Variation in events and data • Symptom Score • FEV1 • Pulse

22. A sensible relationship! • Symptom score according to whether taking antibiotics • Symptom score ------ • No Yes • Currently taking antibiotics?

24. Workload • Increase of prescriptions of antibiotics, prednisolone • But • Probably reflects previously undiagnosed exacerbations • Partly reflects non-optimised care • Important to have a good existing infrastructure for management of exacerbations

25. Workload • Large increase in telephone consultations • Similar face to face and home visits. • Similar hospital stays • Important to remember this is a deteriorating condition • Almost certainly reflects caution among clinicians in early days

26. Clinician Concerns • Spirometry..which I can’t imagine anybody would do properly. I mean how can they do that properly (at home). • Scores are only part of the picture. You need to see the person as well • You really need a sort of second layer (VC) to make sense of the scores, and decide if they need a visit. M’s scores are OK but I know..because I spoke to her that she’s really bad. Others score high and they’re fine • I think anything that gives better information more quickly is a good thing. But that’s the thing with information, if it’s not passed on to somebody then it’s NOT a good idea, so there have to be good procedures in place for making sure that the information goes to whoever needs it

27. Implementation

28. Drivers for Telehealthcare • Improve a service to patients • Reduce costs • In the frontline ( through time saving) • Further down the line (e.g. reduced admissions)

29. Why is it resisted? • Is there an evidence base? • Is that evidence base relevant to this situation? • Was the intervention applied in a real setting? • Will it work? • Will it mean changing what I do? • Will it mean increased workload? • Is it easy to learn how to use? • If I don’t benefit will resources be transferred to me?

30. “Moving on from the work of a small group of enthusiasts into a quasiroutine clinical service involved a significant level of investment in accommodation. This was not simply around building a technology that works, but actually reengineering the organization of knowledge in it, and constructing a service into which it could be practicably incorporated” (MAY ET AL)

31. Staff perception of workload capacity Perceived workload

32. Management perception and impact of telehealth capacity Perceived workload Management perception

33. Reality of impact of telehealth

34. Avoiding Angst in implementation • There has to be a perceived clear need for the device • The rationale for introduction needs to be explained • It should be easy to use • Time set aside for training, close to the introduction of the service • If workload is to increase a recognition of this should be made, with advice on rationalising what will have to be stopped to allow the new system (possibly temporarily). • Ideally, the product should be designed around the existing service if possible and the service not expected to be redesigned around the telehealthcare device. • If this is not possible then changes in role must be negotiated in advance and well defined and not as the technology is introduced.

35. Conclusions • Patients like Telehealth • It encourages evidence based practice and quality care • Telehealth systems need robust underpinning structures to observe and manage the data provided • They may not save time/resources in primary care • Implementation needs to involve users early and must emphasise patient benefit • We need rigorous research to discover where and how the systems are best applied