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Outline• Understand your information requirements and
interface between clinical services and research
• Do this by conceptualising your information “problems”. Consider problems: • For the patient in front of you • For the service you run • For research
• Know about open standards and interoperability. Learn about SNOMED-CT.
PatientCare database• an all-Wales electronic patient record recording
diagnostic, treatment and interventional information using a web-based portal.
• underpinned by SNOMED CT
• benefits: information available immediately at point-of-care clinical governance and service management (aggregated data - secondary uses)recording generic and disease-specific patient outcomes
Are your requirements generic?
• SNOMED-CT encompasses all of the “nouns” of healthcare:your diagnoses, your problems, your complaints, your treatments, your drugs, your home… etc.
• Processes and pathways are the “verbs” of healthcare. there are more similarities than differences between specialties.
Our visionLaboratory
results
Laboratory results
Radiology reports and
images
Authoritative sources of
demography
Welsh Demographic
Service
Organisation PAS
Clinical information system
Multiple users Multiple devices
Healthcare team Patient
Clinical document
archive
Within organisations (NHS Wales)
Other systems
Integration via standardisedterminology and open data
Inside and out of NHS network
• Seamless integration between disparate systems
• Open data standards
• Not disease or speciality specific
• Patient-centric, not focused on organisation
Data standards• Consider a terminology - a “body of terms” much like words in a
dictionarye.g. ICD-10, Read codes, SNOMED CT
• However, whilst these terms have meaning when used in isolation (e.g. “myocardial infarction”), it is only when these terms are combined together in a logical way as part of a larger data model, that true meaning can be understood. It is analogous to definitions for individual words in a dictionary but true expression results only when these words are combined into sentences and paragraphs.
• This emphasises importance of a data model not just the terminology.
Paper medical recordsExpensive
Poorly accessible
No support for team working
Frequently poorly structured
Lots of data but difficult to measure
centred on the organisation or service, not the patient
• Clinical userecording data........using data................. decision support
• Users / centres / projects supportedsingle user.............multiple users...............multiple centres
• Supporting service governance what are we doing?.......................why are we doing that?
• Integration with external systemsnone .......................limited..................................extensive
A database or...an electronic health record?
on the medical record :
“You’re a victim of it or a triumph because of it. The human mind simply cannot carry all the information without error so the record becomes part of your practice” Dr Larry Weed, Internal Medicine Grand Rounds, 1971
http://bit.ly/1FXO98D
Your medical record supports your
clinical practice
What were we trying to do?• Develop a wish-list for a clinical information system
• Direct day-to-day clinical care (patient-specific, patient-level data)
• Audit and governance (service-specific, grouped patient data)
• Research (enrolment/consent/data)
Day-to-day clinical care
• Record what you & team are doing - a clinical narrative
• Team communication (including wider health “team”)
• Diagnostic, treatment and interventional registries
• Generic and disease-specific outcomes disability progression, relapses, seizures
Day-to-day clinical care• Multidisciplinary teams working across sites looking
after shared patients (often w long term conditions)
• This patient [phoned|emailed|texted|skyped]; what information do I have immediately accessible?
• Embed processes into routine day-to-day care.
• Work within our legal obligations to protect patient-identifiable information.
Day-to-day clinical care• Supporting clinical decision-making
• Making all relevant clinical, diagnostic information available in a clinically-useful, sometimes disease-specific manner
• Linking and integrating with other potential sources of patient-level data across the healthcare enterprise
Day-to-day clinical care• More patients with long-term health conditions
• Evolving technology, demand & patient expectation Can I have a telephone consultation?Can I email my doctor? Can I video-call my doctor?
• My [smart device] tracks my step-count, pulse rate, respiratory rate, plasma glucose, pain scores & seizures. What are you doing about it?
• I do my shopping tax return and banking online… Why can’t I see my appointments in my calendar Why can’t I see my test results as soon as they are available? In what century did they use the “facsimile”?
Research registries / portals• Many disease-specific
research portals and registries
• Not embedded in day-to-day workflow
• Little feedback, result or reward
• Potentially lots of disparate systems
Clinical and research data capture
Patient encounter
Research database
Researcher Research output
One-way traffic
Existing NHS systems• Paper records don’t scale to these requirements
• “cc. letters” doesn’t work for multi-disciplinary teams
• traditional “patient administrative systems” (PAS) don’t capture innovative methods of working (e.g. telephone* or email)
• just scanning documents without metadata / context / computer-based semantic understanding isn’t a solution
* invented in 1876
Example use cases
• Consider specific clinical examples and work to understand core underlying informatics requirements.
Example (1)
• Email me when one of my patients on methotrexate doesn’t have appropriate blood monitoring or there is a problem
Example (1)• Email me when one of my patients on methotrexate
doesn’t have appropriate blood monitoring or there is a problem
• Requires:
• Who am I? Who are my patients? Who is on methotrexate? What are the blood test results? [ and then some simple logic….]
Example (1)• Who am I? Who are my patients?
Who is on methotrexate?What are the blood test results? [ and then some simple logic….]
• Needs
Secure patient registry - diagnostic and treatment
Access to laboratory information system
Some simple code
Example (2)
• What is the incidence and prevalence of [multiple sclerosis] in a defined geographical region of [Wales]?
Example (2)• What is the incidence and prevalence of [multiple
sclerosis] in a defined geographical region of [Wales]?
• Requires:
• Core patient registryGood ascertainment (a system that is used day-to-day)Tracking address and address history Tracking date of diagnosis
Example (3)
• How is this patient with [multiple sclerosis] progressing compared to the rest of our cohort in [Wales]?
• Requires:a diagnostic registryreal-time individual measures of disease outcomes real-time calculation of whole-group progression
An iterative roadmap • Work through high-level clinical requirements and boil
them down to core informatics requirements
• Look for general core concepts and implement core functionality
• Test, deploy, real-life feedback and rinse/repeat.
• Agile development. The lean startup. Pivot. A-B testing. Continuous iterative innovation.
• “No plan survives contact with the enemy”
Waterfalls
Traditional development approach in NHS information technology
Product requirements documentProduct requirements document
Software architectureSoftware architecture
Implementation
Design
Requirements
Maintenance
Verification
SoftwareSoftware
Image courtesy of Peter Kemp / Paul Smith - Adapted from Paul Smith's work at wikipedia: Creative Commons Licence
How are we doing?
How are we doing?
Core patient registry tracking demography, treatments and interventions
Workload recording / clinical encounters
Clinical communication (messaging and letters)
Structured and unstructured outcome data
How are we doing?Links to demographic services in Cardiff and Gwent
Links to authentication systems in NHS Wales
Multiple specialty-specific, disease-specific subsystems
Multiple sclerosis / neuroinflammatory disease / epilepsy / Parkinson’s disease / ataxia / neuromuscular disease / motor neurone disease …
>23,000 patients registered >210,000 clinical encounters
Example : multiple sclerosis
Supporting clinical decision making
Example : acute
neurology referrals
2011−01−01 2011−12−01 2012−11−01 2013−10−01 2014−09−01 2015−08−01
050
010
0015
0020
0025
0030
00
UnknownTherapy groupTelephone callReview of notesResearch clinicPrivate clinicNHS clinicMultidisciplinary meetingInpatientHome visitHistoricGP clinicDiscussionCorrespondence
Figure 8: Clinical encounters per month for all patients with any diagnosis since 2011 by type of encounter.
13
3000 encounters/
month
49342 biological samples tracked linked to clinical data
2010−12−01 2011−11−01 2012−10−01 2013−09−01 2014−08−01 2015−07−01
020
040
060
080
010
00
SystemSpeech and language therapistSpeciality registrarSpecialist registrarSpecialist nurseSenior house officerPsychologistPhysiotherapistOtherOccupational therapistMedical studentContinence nurseConsultantClinical research fellowAdministrator
Figure 12: Secure messages sent by different members of the team for all patients using PatientCare.
17
1000/month secure messages
2000 2002 2004 2006 2008 2010 2012 2014
Year of disease onset
Med
ian
dela
y fro
m o
nset
to b
eing
see
n in
wee
ks
050
100
150
200
250
Figure 22: Mean delay from symptom onset to first encounter with MS service
28
Automatic workload reporting to defend service
And what can you do with all these data?
And…
idiopathic intracranial hypertension
and Parkinson’s disease
And introducing epilepsy
And…
Botulinum toxin treatment
Conclusions• Demand more. Become enthused by technology and the potential
benefits. Refine your requirements.
• How can SNOMED-CT be used in your department?
• Consider feedback loops workflow -> data -> workflow and examine methods to reduce the time to close the loop. What data would you want in a dashboard for a patient, and for your service? What are your outcome measures?
• Advocate for cross-disciplinary cross-organisational networked working / shared patient records. Engage, implement, pilot and share
• Any intervention that improves communication will improve care! Avoid data silos.
