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Choice and the Composition of General Practice Patient Registers

Choice and the Composition of General Practice Patient Registers. Daniel James Lewis BA Geography (LSE), MSc GIS (UCL) MPhil/PhD Student (UCL & CASA) PhD Upgrade Seminar, CASA 7 th October 2009. Seminar Plan. Introduction Key concepts and themes

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Choice and the Composition of General Practice Patient Registers

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  1. Choice and the Composition of General Practice Patient Registers Daniel James Lewis BA Geography (LSE), MSc GIS (UCL) MPhil/PhD Student (UCL & CASA) PhD Upgrade Seminar, CASA 7th October 2009.

  2. Seminar Plan • Introduction • Key concepts and themes • Research to date: Choice and the composition of GP patient registers • Future research direction • Questions

  3. Introduction • ESRC CASE award with Southwark Primary Care Trust. • Geography and spatial analysis of healthcare systems (NHS). • Equity • Accessibility • Choice

  4. Key concepts and themes • Equity (social justice, fairness) • Accessibility (geographical/non-geographical) • Choice (widening theme in NHS service provision) • Spatial analysis, modelling and classification • Interpretation and policy?

  5. Equity • Condition of fairness or justice. • NHS operates ‘universal service’, component of which is equity. • Access • Needs • Choice • Quality • Communities • Value • Accountability (DoH, 2009)

  6. Equity in health:Health equity vs. Healthcare equity • Health Equity: “equal opportunity to be healthy” • Healthcare equity: “equal opportunities of access for equal needs” (Asthana and Gibson,2008) • Another way of thinking of equity:

  7. Horizontal, Vertical and (Spatial) Equity • Horizontal – people in like circumstances should be treated the same. • Vertical – apportionment of services to individuals or groups in unlike circumstances as a response to their different needs. • Spatial – A definition of equity such as the ones above that values the importance of space.

  8. Health and Equity – The last word • Whitehead (1992) “The concepts and principles of equity and health” • Equal access to available care for equal need • Equal utilization for equal need • Equal quality of care for all

  9. Equity is important, but it’s an emotive word. • What about: • Distributional fairness • Who gets what? • Implications.

  10. Choice and the NHS • ‘Choosing health’ (DoH, 2005) and ‘Our health, our care, our say’ (DoH, 2006) • Establishes: • Right to choose • Concepts of locality, neighbourhood and community • Continuity in NHS Constitution (DoH, 2009) • “You have the right to choose your GP”

  11. Choice is a spatial decision • Choice in NHS is as much about where? as it is about what? why? and when? • Particularly when choosing a GP or Hospital. • How does the NHS handle choice of GP though?

  12. Directgov • The website of the UK government, providing information and online services for the public all in one place • Register with “your local GP” • What is local? – Commission on Integration and Cohesion suggests 15/20 minutes across an area.

  13. NHS Choices • Web portal for NHS services and information. • Should reflect choice in the NHS • Largely successful for Hospitals. • Much less so with GPs.

  14. Choice in the NHS • From “within walking distance for mothers with prams” (Ministry of Health, 1962) to • Community based provision (DoH, 2005, 2006, 2009) • Definition of choice still essentially geographical • Despite idea of access evolving to include more dimensions i.e. Deprivation.

  15. Spatial Analysis, modelling and classification • Geography is important in the analysis of healthcare systems. Spatial Analysis and Spatial models are useful in explaining how these systems function. • Classification helps us to systematically simplify patterns and group by similar characteristics.

  16. Spatial Models • Representations of Reality • Simplification/selective abstraction (Longley and Batty, 2003) • Symbolic vs. Iconic • Mathematical/statistical relationships that simulate reality. • Allows for associations to become apparent within otherwise complex systems • Spatial Models – add in space (encapulated/simplified)

  17. Distance in Spatial Models • Some measure of distance is vital • Geographic (Euclidian, Manhattan, Network) • Temporal (travel time or similar measure) • Cost Function (a function that describe the cost of doing something – may still be a distance measure, but augmented by other characteristics i.e. Price of travel, slope, scenicness etc) • Other (i.e. Lasker’s distance)

  18. Spatial Models: analytical/efficiency divide • Basic interpretation. • Some models exist to describe the current situation- allowing for an analysis of the current situation. • Some models exist to describe an optimally efficient situation – allowing for planning, scenario testing etc. (perhaps less used in healthcare) • The research presented is a somewhat mixed approach.

  19. Choice and the composition of GP patient registers A summary of work undertaken to date.

  20. Underlying Ideas and Questions • Choice, decision making and its spatial patterns. • What characterises choice of GP surgery by patients? • What can we learn from the patient register? • Why aren’t people simply choosing their closest GP? • Equity in health and health care service provision. • Is the situation equitable? How do we know? • How important is neighbourhood and ethnicity in choice?

  21. Source: Wikipedia Context of Study: Southwark PCT • Population c. 300,000 • Area: c. 30 km2 • Large areas of social housing • 26th of 354 most deprived Local Authority (IMD07) • ‘Multicultural’ neighbourhoods (OAC) • But, some areas of gentrification evident • Neighbourhood and Ethnic composition:

  22. How might choice of GP be investigated? • Hypothesis – People will use their most accessible GP. • Thus anyone not using their most accessible GP has another reason for doing so – this can be observed if we control for accessibility. • Is this a valid argument though? • Early NHS directives suggested GPs needed to be “Within walking distance for mothers with prams” (Sumner, 1971) • Now, rhetoric of ‘local’ coupled with community & neighbourhood perspectives- but still geographical.

  23. GP registration choices • Accessibility – distance/convenience • GP Characteristics (supply side) – ethnicity of doctor, gender of doctor, size of GP, services provided etc. • Patient Characteristics (demand side) – access to information, socio-economic status, neighbourhood types etc.

  24. How can this hypothesis be modelled? • One approach is to use: • Travel time between all GPs and areas in Southwark. • Population of areas from patient registration information. • Constrained by size of GP surgery. • Then solve the ‘transportation problem’. • A linear programming problem that requires you to minimise the objective function based upon distance between demand (GPs) and supply (Patients) sites with respect to some constraints. (using LPSolve in R)

  25. Data Sources • General Practice patient register for Southwark • From NHS central ‘exeter’ database • Calculate OA and GP populations • Over reporting and boundary effects • TfL public transport travel times for Southwark • Aggregated to OA level, for all services, bus, tube, train • What about private cars?

  26. Boundary Constraints • Southwark PCT is not a closed system. • There is some in and out migration. • However, the PCT generally prefers to work as a closed system: • “Southwark Health and Social Care is dedicated to improving the health and wellbeing of the people who live in the London Borough of Southwark” – (Southwark PCT, 2009) • Approach is to use entire Southwark Population and adjust GP capacity in line with this.

  27. Model Solutions • Due to the boundary problem 2 models are specified. • Model 1 (GP constrained) – Can only allocate population to a GP if that GP has free capacity, otherwise it closes its register. • Model 2 (OA constrained) – GPs have to reach a minimum capacity, but once reached have to satisfy all demand. • Mapped model solutions:

  28. Model 1 Model 2

  29. Using the models to create synthetic patient registers • Creating a synthetic registered patient population and comparing it to the real population. • Differences in the patient register will suggest that the particular variable being investigated is subject to individual choice beyond accessibility. • This presentation focuses on neighbourhood using the LOAC (Petersen et al, 2007) and Ethnicity using Onomap (Mateos et al, 2007)

  30. Analysis of Southwark GP patient register composition by LOAC Geodemographic • Neighbourhoods are important in the study of health. • The neighbourhood in which an individual lives may have an effect on likely health. • As well as quality of service provision. (Kawachi and Berkman, 2003)

  31. LOAC Classification for Southwark

  32. Neighbourhood composition Output Area Classification London Output Area Classification

  33. Typical LOAC Attributes by Supergroup

  34. Neighbourhood Composition by General Practice 2009

  35. A few interesting cases

  36. How diverse are the GPs? • In terms of equity, which we’ll loosely define as fairness or social justice here, which GPs have more or less diverse lists in terms of neighbourhood composition? • Using multigroup entropy scores (a basis for Theil’s H measure of segregation)

  37. Issue of spatial dependency and size of neighbourhood ‘building blocks’

  38. Analysis of Southwark GP patient register composition by Onomap taxonomy • Is there a cultural, ethnic or linguistic component to GP choice? • Reminder of Southwark’s ethnic composition from earlier:

  39. A few interesting cases

  40. Diversity of GPs by Onomap Group

  41. Discussion • Inference • Generalisation vs. Specificity • Causality and Choice • Equity vs. Evenness and needs. • Neighbourhoods and Ethnicity

  42. Direction and Further Work • Post residential sorting – some preliminaries • Classification of GPs by QoF data and analysis of patient register by types of GP for UK/London • Development of a Health Needs classification for England and investigation of differences in equity for UK/London

  43. Post residential sorting • Extension of current work. More focus on NHS choice agenda. • How will patients allocate themselves among GPs when given a less restrictive choice of GP? • More neighbourhood/peer effect based.

  44. Defining GP service areas • Using density/contour method from Gibin et al (2007) • Characterise potential for choice by areas in which core service areas overlap. • But how to define core service areas? • Two suggestions:

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