Patients are neglected in the provision of data. Session organized by Daniel Tagg.
Patients (with a chronic disease) should contribute data because:
- they spend 15 minutes every three months disentangling the previous diary and what it meant. Could submit observations by SMS and have them actionable earlier. Can also have them printable and plottable as a trend.
- Messaging access to the specialist nurse
- Early action on analyzing trend-lines
- Sharing information with community of patients and family
- too much data
- how do you manage the data (sorting, filtering, redirecting to different professionals)? E.g. EMIS is creating different summaries for different professionals.
- how to consume the information?
- security through decryption (patientslikeme) and encryption (facilitates clinical care but no social networking possible)
- information sharing creeps beyond original use case - Companies House is digitizing all information, including the signature, and Experia is crawling this information and reselling it
- check out role-based access within NHS as an API
What is the minimum necessary?
- shareable - needs easy access control
- computable - needs functional syntactic interpretable information
- must integrate with the clinicians' practice somehow - remember that the physician only spends one hour with the patient every year
- possibly work with existing PHR solution e.g. EMIS in the UK
- use existing standards, e.g. HL7 CDA CCD / ATSM CCR
- Look at existing sites e.g. patientslikeme.com as they have a social network around patients' experiences
- get 10,000 patients with a particular disease to adopt a tool like patientslikeme and then get the NHS to adopt it
- server has to be inside N3 for data to be shared with NHS
- check out Open Health Tools, created with BT Health, IBM and others to provide open source software tools
- also Continua Health Alliance consortium for data sharing between different devices
Disclosures are in three categories:
- identity - someone's name in the record
- attribute - knowing something about someone based on what they've done, e.g. where they live or which clinic they went
- distributional - statistical measure