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. 2014 Nov 26;15:169. doi: 10.1186/s12875-014-0169-6

Table 2.

New Model of dimensions of readiness of practices to participate in research

Dimension of readiness Key attribute(s) Health System & Research network activity to promote research readiness
Existing New activity required
1 Data Coded data that identifies: Pay-for-performance (P4P) has improved (but also distorted) data quality Active engagement in data quality (of cases & likely controls)
Denominator
Cases (& controls)
Inclusion & exclusion criteria
2 Records Data are extractable Networks that extract data (research databases) Validation of extracts is required: these can have errors and be inconsistent.
One-off (MIQUEST) extraction
Practice searches (EPR vendor search tool)
3 Organisational Health system readiness Legislation (Health & Social Care Act 2012) Engagement with local primary care structures (Health service localities; Medical primary care societies etc.)
Socio-cultural Government/Health ministry promotion of bioscience research
Incentive schemes for practices
4 Governance Research governance (RG) RG emphasis of existing scheme Educational programme
Good Clinical Practice (for trials)
Information governance
Some confusion about “Opt out”
Practice has legal responsibility as the Data Controller in the UK (Data Protection Act) New national guidance about personal data is required.
5 Study Impossible to cover all eventualities Data quality for the specific study Responsive support, direct data collection from patients may be possible
Demographic data
6 Business Tipped in favour or participation Mechanism for funding research (e.g. some practices reluctant to carry out studies sponsored by pharmaceutical industry) Standard payments
Use quality improvement studies to promote research-relevant activities
Level of funding and whether provides sufficient incentive to participants Develop intangible resources
(social/relationship capital)
Feasibility of study being incorporated into existing workload
Any risk/perceived risk (e.g. new drug)
7 Patient Information consent Individual expectation to participate in research/“pre-consent” models Learn how to take consent
Develop intangible resources (relationships with practices)
Volunteer patient cohorts
Single disease (e.g. diabetes), where there may be an associated primary care clinic
Patient-practice culture & ethos about participating in research
Track record – previous experience of delivering projects - type, clinical domain, number of cases