6c lloyd et al. a database of patient experience, questions, concerns and preferences ehin 2014
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Amy Lloyd Dr., School of Medicine, Cardiff University Proof of concept: A database of patient experience, questions, concerns and preferences EHiN 2014, IKT-Norge og HODTRANSCRIPT
Proof of concept: A database of patient experience, questions, concerns and
preferences
Amy Lloyd, Jana Witt, Louise Locock, Fiona Wood, Sian Rees, Adrian Edwards
• The ‘Silent Misdiagnosis’: patients preferences matter
• How can Shared Decision Making help?
• How can information and communication technologies facilitate SDM?
Overview
The ‘Silent Misdiagnosis’
Patient A
• Linda, 58 years
• Diagnosed breast cancer
• Mastectomy went well
• Pathologist report – no sign of cancer
• Misdiagnosed
• Administrative error handling results of biopsy
• Hospital launched investigation; legal action
Patient B
• Susan, 78 years
• Diagnosed breast cancer
• Mastectomy went well
• Pathologist confirmed cancer
• Post-surgery – aware of other options
• High anxiety, depression and regret
• No corrective actions
Patients preferences matter
• Patients engaged in SDM more likely to:
– choose less invasive options (Arteburn 2012)
– Adhere to treatment regimens (Joosten 2008, Wilson 2010)
• “Patients should receive the care they want (and no less), and the care they need (and no more).” Al Mulley
Shared Decision Making: Two Experts
Clinician
Diagnosis
Disease aetiology
Prognosis
Treatment options
Outcome probabilities
Patient
Experience of illness
Social circumstances
Attitudes to risk
Values
Past experience
SDM
“Shared decision making is an approach where clinicians and patients work together using the best available evidence” Elwyn et al. BMJ 2010
Eliminating the silent misdiagnosis: the role of SDM and EBM
Best available evidence
Patient values and
expectations
Individual clinical
expertise
Evidence Based MedicineClinical Guidelines (that incorporate patient preferences)
Shared Decision MakingPatient Communication(skills, and decision support tools that incorporate patient preferences)
Decision Support Tools: facilitating SDM
What are they?
o Provide evidence based information and support for patients
facing decisions about treatment or care
o Make explicit the decision and options available
o Enable a personalised focus – encourage patients to think about
preferences
o Used inside (brief) or outside (extensive) consultations
o Complement, NOT replace
Decision Support Tools: facilitating SDM
Why use them?
In 115 RCTs evaluating decision support tools, use has led to:
• Greater knowledge • More accurate risk perceptions • Greater comfort with decisions • Greater participation in decision-making • Fewer people remaining undecided • Fewer patients choosing major surgery
Stacey et al. Cochrane Database of Systematic Reviews, 2014
Is it possible to develop a database of patient experience, questions and concerns and
preferences using existing sources of data?
Research Questions
– What are the existing sources of data on patient experience?
– Can we access them?
– Can we extract the data we need?
– Who might the end users be?
– What format would the data need to be in to be useful for them?
Background Methods Results Discussion
The Condition (case study)
Asthma selected as case study condition:
- Long term condition affecting significant and varied proportion of population (in terms of age, gender etc)
- Few decision support tools available- Asthma clinical guidelines under review (NICE)
Following steps undertaken:
1. Identify potential sources of data on patients’ experiences, concerns and questions for selected condition
2. Conduct secondary analysis of data from identified sources3. Identify potential users of the database (online questionnaire)4. Discuss formats for re-presenting data with potential users (follow-up interview)
Background Methods Results Discussion
Sources of data on patients’ experiences, concerns and questions (Asthma)
Background Methods Results Discussion
• Populated by Health Experiences Research Group (HERG), Oxford University
• 30-50 qualitative interviews per condition to explore patients experience
• Representative sample
• 80+ conditions covered
• Facilitates Priority Setting Partnerships to bring together patients, carers and clinicians to prioritise treatment uncertainties
• 19 conditions covered
Background Methods Results Discussion
Background Methods Results Discussion
Secondary analysis
Data sources:
1. HERG/HTO qualitative interviews (n=23)
2. James Lind Alliance (n=305)
3. Posts from Asthma UK forums (n=86)
4. Selected Asthma blogs (n=3)
5. PatientsLikeMe entries (n=19)
6. Patient Opinion entries (n=20)
Data coding scheme:
• Patient concerns and questions (disease and treatment)
• Patient wishes and expectations (disease, treatment, and health services)
• Patient experience (disease, treatment and health services)
Data differed in terms of:
• Accessibility
• Rigour
• Representativeness
• Analysis
Background Methods Results Discussion
Data distribution across codes
Background Methods Results Discussion
Data distribution across codes
Potential users of the database
• Still in process
• Range of organisations interested, including:
– Option Grid Collaborative: to inform development of decision support tools (patients’ FAQs)
– Healthwise: to inform development of personal care plans (a taxonomy of patient terminology)
– Mayo clinic: to inform study on how patients make treatment decision in asthma
– SHARE-IT/MAGIC
Background Methods Results Discussion
In summary…
• It is possible to extract data from existing data sources on patient experience, concerns and questions about disease and treatment
• Number of organisations interested in using the end product
• BUT!
– Existing data repositories vary in quality and focus
– Selection of the correct source is essential when planning secondary analyses
– HTO and JLA/Asthma UK PSP provided the most compelling combination of relevant data in terms of accessibility, rigour, representativeness and time required for analysis
– Some additional primary data collection may be required to obtain a more comprehensive appreciation of patient experience.
Background Methods Results Discussion
Key messages
• Important to diagnose patient preferences: SDM and EBM can help
• More needs to be done to incorporate patient preferences into key SDM and EBM interventions
• Database of patient preference is promising, but unlikely to be the only answer
Background Methods Results Discussion
