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Use of intelligence by EPSO member states

Use of intelligence by EPSO member states. Dr Alex Mears Care Quality Commission. The Care Quality Commission . The Care Quality Commission is the regulator for England Created 1 st April 2009 (just over a year old)

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Use of intelligence by EPSO member states

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  1. Use of intelligence by EPSO member states Dr Alex Mears Care Quality Commission

  2. The Care Quality Commission • The Care Quality Commission is the regulator for England • Created 1st April 2009 (just over a year old) • Remit covers all aspects of health (NHS and privately owned) and adult social care • Does not include medical or clinical personnel (other bodies do that) • Registration-based model- initial registration then ongoing monitoring of compliance • Information is delivered to field staff through statistical risk model into the Quality and Risk Profile (QRP), indicating risk level for a number of outcomes for each service/ provider • QRP used by field staff to prioritise regulatory activity • QRP uses information from many sources including users of services

  3. The project- background • Different organisations within EPSO undertake different roles with different objectives. • This project questionnaire looks at how our organisations use intelligence, information and/or data as part of regulatory/ supervisory activity. • Some organisations will not use information very much, relying on a full-coverage model (where all providers of care are inspected on a rotational basis); others will use information to select or prioritise inspection activity. • This questionnaire aims to understand how supervisory bodies in EPSO use information, and how this is linked to their aims and goals and other factors such as how they interact with supervised organisations

  4. Methods • This questionnaire was sent out by the EPSO central secretariat to representatives of all nations active within EPSO, regardless of membership status, comprising 18 countries in total. • Two reminders were sent out to participants, each with a fresh copy of the questionnaire attached. • The questionnaire was developed to enable the researchers to understand more about a number of areas of regulation. • Sections gathered data on • Demographics • regulatory approach • availability of information • analysis capability • regulatory model • use of information. • Analyses run were descriptive (univariate) and cross-tabulation (bi- or multi-variate).

  5. Results: structure • Results are presented using a structured approach (this was a long questionnaire and there are lots to show)] • Viable responses were received from 12 nations of the 18 that received it, an adjusted response rate of 67% (some countries were not included in the original mail out and were added later). • Analyses are presented as descriptives (univariate) and crosstabulations (bi- and multi-variate) to show relationships. • The results presented do not represent the totality of data collected, but the highlights of analyses so far. • V. small dataset means findings are only illustrative.

  6. Demographics

  7. Organisation status • - Most organisations have no relationship with local government

  8. Entry to and exit from the market

  9. Service failure and economic factors - Most supervisors investigate service failure (10/12)

  10. Relations with supervised bodies • All respondents reported a good relationship with supervised organisations

  11. Reporting

  12. Team members & recruitment

  13. Research, mergers, change trends and finance • Some organisations commission independent research from third parties (7/12) • Most respondents feel that changes in their work follow a direction of travel (9/12) • Half of respondents have been involved in mergers

  14. Breadth of supervision

  15. Powers

  16. Data available for supervision 1

  17. Data available for supervision 2

  18. Data available for supervision 3

  19. Data available for supervision 4

  20. How information is used

  21. How data drives inspection

  22. Crosstabulations • Looked at relationships between different variables • created categories to explore the data • Countries: Eastern Europe, Western Europe, Nordic • Breadth of supervision: high, low • Powers available: many, few • Data use: basic to complex including risk-based • Inspection model: driven by defined period to risk based • Risk-model: hybrid of data use and inspection model

  23. Breadth of supervision activity by geographical area • Eastern European supervisors’ scope is relatively smaller • the Nordic scope is relatively wider • Western Europe is between

  24. Powers available by geographical region • Western Europe has comparatively more powers • Nordic countries have less powers • Eastern European countries are between

  25. Availability of data by geographical area

  26. Cluster chart of data available, powers and geographical region • More data is associated with more powers • This effect is most pronounced for Eastern European countries

  27. Data sources available by powers available

  28. Breadth of supervision by powers available

  29. Inspection frequency by most sophisticated form of analyses • There appears to be a loose relationship between responsiveness of model and sophistication of analysis • These two variables can be combined to form a proxy measure for how risk-based a regulator is

  30. Risk based model by geographical area

  31. Risk based model by analyses used • There appears to be a loose relationship between risk-based models of regulation and total use of analyses

  32. Risk based model by data available • There appears to be a loose relationship between risk-based models of regulation and availability of data

  33. Risk based model by breadth of supervision • risk-based regulation is loosely associated with a smaller regulatory scope

  34. Much more data to analyse! • I’ll stop there, as we will have no time for discussion • There are plans to complete the analyses, look for more associations and unpack the more qualitative information • Plan to write and submit a journal article, probably to the International Journal of Quality in Health Care • Open to the floor: invite comments, thoughts, opinion from delegates • Questions for discussion: • Does what the data show make sense? • Are there relationships that are expected? • Are there relationships that are surprising? • Are there discernable patterns in the data? • Are there other questions we should be asking? • What other analyses should we be doing?

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