Semantic Interoperability for Health Network of Excellence

Transcription

1 Semantic Interoperability for Health Network of Excellence Deliverable 2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs: summarising health records for populations Cardiovascular healthcare enterprise analysis describing the need for semantically interoperable summaries of health records at the population level [Version 1.0] 31 March 2014 Call: FP7-ICT Grant agreement for: Network of Excellence (NoE) Project acronym: SemanticHealthNet Project full title: Semantic Interoperability for Health Network Grant agreement no.: Budget: EURO Funding: EURO Start: End: Website: Coordinators: The SemanticHealthNet project is partially funded by the European Commission.

2 Document Description Deliverable: 2.2 Publishable summary: Status: This deliverable is an enterprise analysis of information flows in cardiovascular healthcare demonstrating the need for semantically interoperable summaries of health records at the population level. Draft Version: 1.0 Public: No (not until completed) Deadline: 31 March 2014 Contact: Editors: James A. Cunningham, The University of Manchester Stephen Walker; John Ainsworth; Iain Buchan Document History Date Revision Author(s) Changes 25/11/2013 to 05/03/ to 0.80 Stephen Walker Initial content 04/01/ Simon Capewell & Helen Bromley European Public Health description 09/03/ John Ainsworth Revisions and comments 12/03/ Stephen Walker Additional content 15/03/ Iain Buchan Additions, revisions and comments 17/03/2014 to 18/03/ Stephen Walker Additions and final editing D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 2 of 66

3 1 Table of Contents 1 Table of Contents The SemanticHealthNet Project Executive Summary Introduction The Aims and Structure of Deliverable Building on Deliverable Relationship with Other SHN Deliverables Purpose and Approach Definitions Used In This Paper Context Overview of Public Health Professional Practice in Europe Electronic Health Record Standards and Population Health EHR Standards in England The Enterprise Analyses Issues Common to All Topics Topic 1 Employing Patient Held Records and Devices Topic 2 - Optimal Primary Prevention with Statins Topic 3 - Targeting Public Health Measures to Reduce Obesity Topic 4 - Monitoring Smoking Cessation Services Topic 5 - Mapping Missed Opportunities to Prevent Cardiovascular Events Topic 6 - Monitoring the Diagnosis and Treatment of Heart Failure Topic 7 - Co-production of Cardiovascular Health & Care Topic 8 - Real-world Trial of a New Medicine to Prevent Stroke Appendix 1 Topic 1: Examples of On-Line Physical Activity Logs Appendix 2 Further Information from the Enterprise Analyses Appendix 3 Metrics and Values D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 3 of 66

4 2 The SemanticHealthNet Project Semantic interoperability of electronic health record (EHR) systems is a prerequisite for enabling patient-centred care and advanced clinical and biomedical research. SemanticHealthNet will develop a scalable and sustainable pan-european organisational and governance process to achieve this objective across healthcare systems and institutions. A clinical focus on chronic heart failure management and cardiovascular preventive care in the work plan will drive the semantic resources to be developed. The exemplars in clinical and populationlevel (including Public Health) uses are specific enough to permit comprehensive development and validation of these resources, and yet typical enough for wider generalisation of the methodology and its governance. SemanticHealthNet will capture the needs articulated by clinicians and public health experts for evidence-based, patient-centred integrated care in these domains. Existing European consensus in the management of chronic heart failure and cardiovascular preventive care will then be integrated in EHR architectures, clinical data structures, terminologies and ontology by leading technical experts. Clinical and Industrial Advisory Boards will provide links with other domains in which these results can be used beneficially. The project will investigate how best to combine and adapt informatics resources to support semantic interoperability, and how these can be developed and supported at scale. Results of this investigation will be generalised and formalised. The involvement of health authorities, clinical professionals, insurers, ministries of health, vendors, and purchasers will ensure that the project approach and results are realistically adoptable and viable. This work will also build on the SemanticHEALTH and CALLIOPE roadmaps for ehealth interoperability. A business model to justify strategic investments, including the opportunity costs for key stakeholders such as Standards Development Organisations and industry, will be defined. Links with the epsos large scale pilot and the ehealth Governance Initiative, will inform the shape of the Virtual Organisation that this Network will establish to sustain semantic interoperability developments and their adoption. The consortium comprises 17 Partners and more than 40 internationally recognised experts, including from USA and Canada, ensuring a global impact. Partners 1. Research in Advanced Medical Informatics and Telematics (RAMIT) BE (Admin Coordinator) 2. Imperial College London (Imperial) UK 3. University of Hull (UHULL) UK 4. University Hospitals of Geneva (HUG) CH 5. World Health Organization (WHO) CH 6. The University of Manchester (UoM) UK 7. Medical University of Graz (MUG) AT 8. International Health Terminology Standards Development Organisation (IHTSDO) DK 9. Institut National de la Santé et la Recherche Médicale (INSERM) FR D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 4 of 66

5 10. Ocean Informatics (Ocean) UK 11. Health Level 7 International Foundation (HL7 International) BE 12. EN13606 Association (EN13606) NL 13. Empirica Gesellschaft für Kommunikations- und Technologieforschung mbh (EMPIRICA) DE 14. Standing Committee of European Doctors (CPME) BE 15. European Coordination Committee of the Radiological, Electromedical and Healthcare IT Industry (COCIR) BE 16. Whittington NHS Trust (WHIT) UK 17. European Institute for Health Records (EuroRec) FR (NoE Coordinator) Project Plan Workstream I: Workstream II: WP1: Patient care exemplar (heart failure) WP2: Public health exemplar (cardiovascular disease prevention) [Broadened to population-level uses of care records for cardiovascular preventive care] WP3: Stakeholder validation WP4: Harmonised resources WP5: Infostructure and tools WP6: Industrial engagement Workstream III: WP7: Adoption and sustainability WP8: European Virtual Organisation WP9: Project management, dissemination, promotion D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 5 of 66

6 3 Executive Summary Despite advances in care, cardiovascular disease (CVD) remains Europe s leading cause of death. Furthermore, most of the early deaths from CVD are preventable. This is of major public health concern, not only over the failures in prevention but also because the burden of disease, and the benefits of treatment outcomes, are spread unfairly across most societies. Accurate information about CVD prevention and treatment is required at the population level to guide the provision of safe, effective, efficient, acceptable and equitable services. In this report we focus on the informatics required to understand cardiovascular health at the population level so that policies and practices can be better informed. In particular, we consider the summarisation of data from electronic health records (EHRs) to provide metrics of cardiovascular health and care that are comparable across populations. We take the full view of prevention, encompassing primary, secondary and tertiary prevention. Primary approaches are through public health measures to reduce risk factors like smoking, poor diet, physical inactivity, and obesity; and through clinical measures such as drugs to control blood pressure and lipid metabolism. Secondary prevention involves slowing down the progression of established disease, and tertiary prevention concerns minimising suffering. Preventive services thus involve a spectrum of public health measures, primary care and hospital/specialist care. We revisit the use-cases of Deliverable 2.1 and analyse the informatics enterprise practicalities of delivering more semantically interoperable summaries of cardiovascular health and care from EHRs. This evidence provides the business and technical teams with detailed scenarios to work on. The key messages are: While CVD is used as an exemplar the principles described here apply generally. Large benefits can be achieved for local and national populations and individual patients if standards for semantic interoperability can be defined, agreed, delivered and enforced. The scope of information systems reaches beyond clinical care providers to include patient held devices, on-line activity logs and web-based personal health records. The scope of data items involved includes such areas as diet and exercise not just what would traditionally be seen as clinical. National and local health surveys should comply with agreed standards to enable comparison with data derived from EHRs. Human factors, including motivation to change, may be more limiting to the provision of semantically interoperable population summaries of EHR data than are technical factors. Many of the technologies required to deliver the systems outlined in this report are already in place. They may even be in widespread use, however take up is often piecemeal, driven by forces outside direct healthcare and often they do not provide a complete, end-to-end solution. The business cases that encourage people and organisations to change existing ways of working can be viable on large and small scale however it is important for those business cases to be formally developed in order to provide the evidence. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 6 of 66

7 Solving challenges relating to technical and semantic interoperability without addressing the accuracy and consistency of the coding of source data could lead to flawed decision making when those data are used at population level. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 7 of 66

8 4 Introduction 4.1 The Aims and Structure of Deliverable 2.2 This report is intended to describe common real-world situations that drive the flows of information influencing cardiovascular health and care across populations. These situations involve the need to improve decisions about healthcare provision at population level via the definition and management of semantic interoperability standards thereby ensuring a consistent, common understanding of what data items mean as they are shared between people and organisations. Other workstreams of the SHN project address the technical issues associated with this challenge. The aim of this deliverable is to focus on the business issues including benefits, deliverability and the need for changes in behaviour. The SHN project recognises that most current health information systems architectures were based on the historic needs of healthcare provider organisations and not on the needs of patients and communities. The main challenge that SHN seeks to address is improving this situation by enabling clinically safe exchange of data between organisation-level systems based on common standards adopted and enforced on a large scale. This principle underpins the thinking deliverable 2.2. However we also acknowledge the ultimate need to move beyond copying data between institutional systems to fundamentally new architectures with embedded standards that are designed to support healthcare delivery and management in the 21 st century. These architectures should provide optimum support for clinicians and patients based on the way in which patients are actually cared for rather than on how health service providers are organised. 4.2 Building on Deliverable 2.1 Issued in December 2012, Deliverable 2.1 Summarising Health Records for Populations (M12): Cardiovascular Use-cases 1 considered five population-level uses of health information for preventive and early healthcare: 1. public health and social interventions; 2. clinical audit and optimising healthcare services; 3. payer evidence and commissioning healthcare services; 4. consumer health applications; 5. research using health records. Central to each was a decision, or series of decisions, that needed to be taken for more than one patient although two of the cases start from the perspective of the individual patient. The scenarios were intended to give health informaticians a selection of use-cases for summarising health records across multiple patients. They highlighted the importance of information systems to enable better preventive and early healthcare a strategic priority for Europe. 1 Cardiovascular healthcare use-cases for semantically interoperable summaries of health records at the population level version 1.1 dated 31 December 2012 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 8 of 66

9 Deliverable 2.1 took a range of approaches to describing each scenario, but the over-arching intention was to highlight the clinical and business issues that apply for all the five uses listed above and to ensure that these are recognised as the main drivers for the implementation of integration technologies including semantic interoperability. 4.3 Relationship with Other SHN Deliverables The main intellectual challenge links Deliverable 2.2 with Deliverable 4.3 with respect to ontologies and information models. This report shows that the clinical meaning of data items does not necessarily translate to public health or population meaning of the same items. For example, risk factors recorded for the clinical purpose of prognostic evaluation and health promotion (influencing patient behaviour) may lack contextual information e.g. ex-smoker for the past 12 months transcribed from a self-assessment form in a clinical waiting room for population 1 may be incomparable with a nurse-administered standard question, confirmed with a cotinine breath test for population 2 summarising these records as proportions of patients who have quit smoking for 12 months in population/service 1 vs. population/service 2 would be biased, and could lead to perverse incentives to invest more in a poor quality service with inadequate metrics. So there is a need for ontologies and information models to incorporate the intended population uses of EHR data. Deliverable 4.3 touches on this and has initiated new work to address the problem. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 9 of 66

10 5 Purpose and Approach Working from the scenarios outlined in deliverable 2.1, the purpose here is to identify areas where specific, achievable improvements to the way in which data is collected, managed and shared can result in large-scale benefits for patients, populations and healthcare providers. While there is a focus is on challenges relating to semantic interoperability and the importance of agreeing, disseminating and supporting international standards, this is not the only focus. The enterprise analyses have been shaped to address not only the routine exchange of clinical information between healthcare providers, for example hospitals and general practitioners, but also the much broader context necessary to support care and decision-making at a population level. They therefore include aggregate datasets, the role of healthcare commissioners (including public health professionals), commercial solution providers and the patients themselves. A key element of most of the analyses is that they are based on practical questions that are routinely faced by clinicians and managers. These decisions determine how care services are delivered or commissioned and/or which patients are targeted. By introducing one new use case and refining and expanding upon the high-level requirements previously outlined in SHN deliverable 2.1 the intention is to: Identify the points at which data should flow or be shared between people/systems. Provide examples of the types of data involved. Describe the benefits that could accrue from the implementation of the improved ways of working supported by appropriate semantic technologies. Consider the relationship between benefits and the scale of implementation. Identify the changes to current systems, behaviours and processes that would need to take place to make this happen such as: - system interactions including technical and semantic interoperability; - system architectures; - ways of working; and - supplier engagement. The intention is to look beyond the boundaries of individual organisations, to consider the bigger picture and move towards a health systems architecture that is not based on isolated silos of data processing as at present. In doing so we recognise that, unless each organisation involved in the collection and flow of data can see clear benefits for themselves in making the changes necessary for integration, then there is little chance of this happening. Each analysis considers patients and populations with chronic, long-term conditions or at risk of developing these conditions. Some analyses also include patients with multiple conditions or risks because it is important to recognise not only that many people are in this situation but also that multi-morbidity represents a particular interoperability challenge. Care needs are not simply the sum of multiple separate pathways and therefore data requirements are not simply defined in the individual data flows associated with each condition. The data requirements are relatively routine and predictable. The data flows are not time critical in the way that they would be for immediate acute care; in fact it is likely that the decisions outlined in some of the analyses may only need to be taken once per year. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 10 of 66

11 It is important to remember also that a critical factor determining the usefulness of data is the accuracy of coding when that data is first recorded. Any subsequent decisions based on that data will be flawed if the initial coding is wrong. Indeed the overall risk is increased if solutions providing technical and semantic interoperability enable data reuse outside the original setting. In the UK, the new GP contract that operated from 2003 may have had the effect of improving primary care coding generally it has mainly served to standardise coding for certain conditions rather than ensuring a consistently high standard of coding overall. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 11 of 66

12 6 Definitions Used In This Paper Semantic Interoperability What is sent (or shared) is the same as what is understood. Beyond the ability of two or more computer systems to exchange information, semantic interoperability is the ability to automatically interpret the information exchanged meaningfully and accurately in order to produce useful results as defined by the end users of both systems. To achieve semantic interoperability, both sides must defer to a common information exchange reference model. The content of the information exchange requests are unambiguously defined. 2 Semantic Technologies Semantic Web Semantic technologies extract meaning from data, ranging from quantitative data and text, to video, voice and images. 3 An extension of the World Wide Web to incorporate semantic technologies providing a common framework that allows data to be shared and reused across application, enterprise, and community boundaries, creating a web of data that can be processed by machines. Healthcare Commissioning At its simplest, commissioning is the process of planning, agreeing and monitoring services. Commissioning is not one action but many, ranging from the health-needs assessment for a population, through the clinically based design of patient pathways, to service specification and contract negotiation or procurement, with continuous quality assessment. There is no single geography across which all services should be commissioned: some local services can be designed and secured for a population of a few thousand, while for rare disorders, services need to be considered and secured nationally 4 Population Health The health status and healthcare outcomes of populations of individuals can be collected under the umbrella term population health (3,4). Understanding the distribution and determinants of health within such populations is the underpinning discipline of epidemiology, or clinical epidemiology when applied to healthcare. The populations concerned may be residents of a whole geographic area the general population or other groupings that summarise health across individuals to help compare the groups for example grouping by gender, ethnicity, employment status, occupation, household income, socio-economic status of the area of residence etc. 5 2 EN1306 Association Gartner NHS England University of Wisconsin - D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 12 of 66

13 Public Health The concept and profession of public health is described in detail in section 7. Systems Architecture Systems architecture is the conceptual model that defines the structure, behaviour, and more views of a system. In this document we use a wider definition that includes the IT, information flows and ways of working that contribute to the recording and dissemination of the relevant information. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 13 of 66

14 7 Context The enterprise analyses that follow are set in the context of the English National Health Service and how it is organised in 2013/14. However it is important to stress that, while England has been used as the basis for these case studies, the eight enterprise analysis topics are expressed in generic terms and are largely applicable to any European country context. Most of the studies involve bringing data collected locally together with data from regional and national sources so that decisions can be made about the provision of care to individual patients or about the deployment of resources at a broader population level that impact directly on patients and patient groups. Therefore in order to understand the relationships presented in the use cases it is important to understand the structures and roles of the organisations involved. Hospital Trusts n=251 Mental Health n=56 Community n=34 GP Practices n=8032 Average 7058 patients Acute Hospital n=15 Provide Care Provide Care Member of Public Health Protect and improve the nation s health and to address inequalities 56m Patients Commissioning Plan and design local health services in England by buying health and care services Commission Care Public Health Centre n=15 Average 3.7m patients Clinical Commissioning Group n=211 Average 265k patients Public Health Region n=4 Average 14m patients NHSE Area n=25 Average 2.25m patients Public Health England NHSE Region n=3 Average 18.7m patients National Commissioning Board Figure 1 - Simplified NHS Structure D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 14 of 66

15 Figure 1 above shows elements of the structure of the NHS 6 as at February 2014, from patients through healthcare providers and up to government level. It has been simplified to show only those parts of the NHS that are relevant to the use cases and includes some information to indicate scale for example, number of patients or number of organisations of that type in England. 6 Further information can be found on the following websites - and D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 15 of 66

16 8 Overview of Public Health Professional Practice in Europe In Europe, there is a diversity of public health practice based on different historical traditions of public administration (both legal differences in responsibilities and financing of health and other services). Furthermore, the boundaries of public health and of what is considered to fall within public health capacity and services may therefore change over time and be described differently in different European countries. Inevitably, there is room for debate over the parameters and boundaries of public health services, especially given the importance of governance for health across the whole of government and the whole of society. Current public health capacities and arrangements of public health services vary considerably across Europe. These differences reflect variations in political prioritization and organizational models of public health services, as well as the distribution of functions and responsibilities across different administrative levels. However, there are many similarities across the European Region, mainly in basic needs for public health information, knowledge and competences. There are often continuing problems of under-resourcing, skill shortages, insufficient capacity, poor morale and low pay. Competency frameworks for a public health workforce, as well as career pathways, remain underdeveloped. Public health functions are fragmented and sections of the workforce may work in an isolated way. While research capacity is well established in some countries, effective facilitation of research capacities to support policy development and programmes still lags behind. The public health workforce can be defined as a diverse workforce whose prime responsibility is the provision of core public health activities, irrespective of their organizational base (Beaglehole and Dal Poz 2003), underlining the broad nature of public health. Many countries have moved from a medically dominated public health workforce to a multidisciplinary one. Given the breadth of factors with an impact on health, it is difficult to define the workforce precisely. In addition to a core workforce (focused on public health work), the potential for public health action in relation to many roles and responsibilities not typically associated with public health needs to be clarified. The public health workforce can be categorised according to three main groups of actors: 1. Public health specialists 2. Health professionals 3. Non health-sector professionals Public health specialists Include traditional public health occupations such as food safety inspectors, environmental health officers, communicable disease control staff, etc. This group also includes the new practitioners working in the broad field of protection, prevention and promotion. For instance, those employed as municipality health promoters and those involved in projects and programmes in the Healthy Cities and Health-Promoting Schools movements and other such initiatives. The task with public health workers is to enhance their knowledge and cement their skills and, crucially, to strengthen their credibility in the public arena and their sense of professional identity and responsibility. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 16 of 66

17 Health professionals Include personnel working in the health sector but without an explicit public health function, such as all those providing a personal service to users and other primary care physicians. Examples include hospital-based doctors and nurses, general practitioners, family health nurses and other communitybased nurses, dentists, social workers, psychologists and others in clinical roles. For healthcare workers, the main task is to ensure they are able to provide relevant health promotion and disease prevention services in the healthcare setting, and enable them to collaborate across often rigid boundaries, whether these are sectoral, professional, organizational or institutional. The non-health sector group Includes actors from other sectors whose activities and decisions have an impact on health, whether or not they themselves realize it. In Europe this is a large and very diverse group. Examples include professionals at various levels of government (national, regional and local) who are implementing policies and managing programmes in non-health sectors, technical officers such as city planners, and housing, education (including teachers), transport, finance, environment and other officials. For the non-health sector group, the task is to provide them with the understanding of how their activities and decisions have an impact on health, and how designing healthy policies can contribute to furthering the policy agendas in their own sectors. In many health systems, the public health function is fragmented and sections of the workforce may be isolated. There are often continuing problems of under-resourcing, skill shortages, insufficient capacity, poor morale and low pay. In order to meet population health needs, significant efforts are thus required to scale up not only the number of public health professionals, but also their quality and relevance to public health In conclusion, a large and diverse public health workforce exists in Europe; however, there is no reliable quantification of the public health workforce in Member States. Only crude estimates are available, as the public health workforce cannot be clearly identified or distinguished from the healthcare workforce (for example, doctors and nurses taking on public health service roles), or people working in other sectors. The workforce responsible for public health activities is engaged in many sectors and is not only limited to the health sector functions. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 17 of 66

18 Bibliography Aluttis CA, Chiotan C, Michelsen M, Costongs C, Brand H, on behalf of the public health capacity consortium (2013). Review of Public Health Capacity in the EU. Published by the European Commission Directorate General for Health and Consumers. Luxembourg, ISBN Beaglehole, R, & Dal Poz, M R (2003). Public health workforce: challenges and policy issues. Human Resources for Health, 1(1), 4. doi: / World Health Organization (2012) European Action Plan for Strengthening Public Health Capacities and Services. data/assets/pdf_file/0005/171770/rc62wd12rev1-eng.pdf D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 18 of 66

19 9 Electronic Health Record Standards and Population Health In a parallel exercise to the development of this report we have conducted a detailed literature review to identify and retrieve papers that address a number of relevant topics including: Semantic interoperability Systems architectures Population health Initial results show that there are few, if any, papers that focus on all three of these issues. 9.1 EHR Standards in England 7 While this report is not intended to provide an assessment of clinical coding standards, it is important to acknowledge the current state of those standards as they apply to the eight topics that follow. In the UK, although the NHS has adopted SNOMED CT as a strategic terminology, its uptake has been slow and a range of standards are currently in routine use. Primary care organisations code patient encounters using READ (Version 2 or Version 3). Secondary care organisations mainly use ICD-10 for diagnoses and OPCS-4.5 for procedures. So far, SNOMED CT has been successfully implemented on only a limited scale within a primary care clinical system that has a relatively small user base and in both secondary care and ambulance settings at early adopter sites. In October 2012 Lee et al 8 stated The Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) has been designated as the recommended clinical reference terminology for use in clinical information systems around the world and is reported to be used in over 50 countries. However, there are still few implementation details. This study examined the implementation of SNOMED CT in terms of design, use and maintenance issues involved in 13 healthcare organisations across eight countries through a series of interviews with 14 individuals. While a great deal of effort has been spent on developing and refining SNOMED CT, there is still much work ahead to bring SNOMED CT into routine clinical use. In the period since the publication of this paper these conclusions remain valid. In an earlier paper 9 they described various problems associated with the versioning of SNOMED CT and concluded that Of the 5182 concepts in the problem list subset, 2135 (41.2%) underwent some form of change Keeping track of these changes is important as they are not well published and have an impact in patient case queries and the accuracy of patient records. 7 See also and 8 A Survey of SNOMED CT Implementations Lee, Cornet, Lau and de Keizer, Journal of Biomedical Informatics, October Implications of SNOMED CT versioning, Lee, Cornet and Lau, International Journal of Medical Informatics, February 2011 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 19 of 66

20 The situation remains fragmented with a large, and growing, volume of data continuing to be recorded using what may ultimately be regarded as legacy standards. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 20 of 66

21 10 The Enterprise Analyses The topics described in this section are based on real situations that occur routinely across the illustrative health system, NHS England. They have been constructed to highlight system interactions and data flows, which, if supported by appropriate systems architectures and assured data quality, would result in significant benefits to patients and care providers. Some of the cases describe hypothetical optimal situations where integrated systems enable the participants to address the challenges that they face and make the necessary decisions. In others the current situation is outlined along with the consequences of the problems not being resolved. Each use case has been written from a particular perspective; either the patient, the general practitioner or a manager/clinical/public health lead responsible for commissioning or monitoring the delivery of healthcare services (see table 1 below). Topic # Topic Description Perspective Self-monitoring and Personal Health Records 1 Employing patient held records and devices Patient Targeting and Deployment of Health System Resources 2 Optimal primary prevention with statins Public Health Professional 3 Targeting public health measures to reduce obesity Commissioner 4 Monitoring smoking cessation services Public Health Professional 5 Mapping missed opportunities to prevent Commissioner cardiovascular events Clinical Care Delivery 6 Monitoring the diagnosis and treatment of Primary Care Clinician/Service Manager heart failure Co-production of Cardiovascular Health (Care) 7a Social networking and web-based access Patient 7b Vascular Wellbeing App Primary Care Clinician Investment in New Medicines 8 Real-world trial of a new medicine to prevent stroke Commissioner Table 1 In the descriptions that follow the topics have been grouped under the five headings shown above. Topics 2-5 in particular share many common aspects and this grouping helps to reduce duplication and bring out the key generic points. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 21 of 66

22 While optimal solutions that would deliver maximum gains might require a fundamental re-design of elements of the overarching systems architecture, many of the benefits that are identified below could be realised without significant investment in new systems or systems infrastructure. Furthermore they could start to be realised quickly on a small/local scale outwards rather than waiting for a large-scale/slow/ top-down approach. The challenges presented do not relate solely to technology and semantics. Indeed in some of the cases these may not be the most challenging elements. It is equally important to address human/professional behaviours and skills as well as organisational relationships as these will often be significant limiting factors. None of the topics require the development of new technologies, and to that extent it should be possible to realise the benefits of the suggested solutions quickly - provided there is a commitment to changing current, sub-optimal, ways of working. For example in topic 1, which focuses on patientheld devices, shared access to care records and social networking, could be implemented in England right now. There are small isolated instances of links between the patient, the device and the commercial providers are already in place, but no coherent overarching framework. For transformational change to take place on anything other than a very small scale approved data flows and protocols must be established. Critical to this is ensuring that there is a complete and common understanding of precisely what that information means so that healthcare providers, commissioners and public health managers can access and use trusted information from a range of sources Issues Common to All Topics The detail of the use cases varies in order to address data requirements from a range of perspectives the patient, the commissioner etc. However there are a number of recurrent themes: Data from multiple sources must be combined and analysed to enable decisions to be taken or benefits to arise Decisions relate to one or more of the following: o deployment of resources o identification and targeting of particular patient groups o risk assessment using modelling techniques Information governance policy and data protection legislation restricts who can access, process and use the data and for what purpose. Business Case Perspectives Each participant in a topic scenario requires clear reasons to change from current behaviours and ways of working. The motivations might include direct or indirect health benefits for themselves or friends/relatives, the ability to deliver more efficient or effective care services or even cost savings. All participants must contribute in order for benefits to be realised and for this to happen they must all be aware of the type and value of benefits to them as well as the costs, in terms of money and/or effort that they will incur. In other words the business case must make sense from every participant s point of view. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 22 of 66

23 The description of each of the following use cases includes a section where the likely benefits, costs and changes of current process are identified. While bottom-line cost will always be a limiting factor each participant will have other key questions such as: Patients (and relatives) How will this impact on my future health and well-being? Care Professionals How will it improve my ability to help my patient/client? Care Provider Organisation How will it impact on my organisation s budget, liabilities and development? Commissioner/Payer Community What is the effect on health and social care of my population? How will it affect my population s health, prosperity and social development? System and Service Providers How does this affect revenue and my position in the market? D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 23 of 66

24 Devices and Personal Health Records Linked to EHR 10.2 Topic 1 Employing Patient Held Records and Devices A new use case (additional to deliverable 2.1) Key Words/Tags Patient Held Records, Exercise, Personal Health Records (PHRs), Patient Devices, Social Networking, Health Promotion Source Professor Iain Buchan Chapter 16 Informatics for Healthcare Systems Decisions Requiring Population Health Summaries Multiple decisions over the costs/benefits of capturing & using health data from mobile devices and PHRs will need to be taken by both the patient and the healthcare provider. Purpose of Use Case This use case describes a potential solution that would provide primary care practitioners with more frequent patient sourced clinical data as well as engaging patients directly in reducing their own risk factors. It examines the interactions between the patient, primary care provider and commercial organisations. In particular how health data collected by the patient, when used with data derived from the GP clinical record and other sources, can contribute to: Scenario Reduced risk for the individual patient Better understanding of health risks and the effect of exercise both for individual patients and populations More effective targeting of health promotion resources Mr. Smith is a 43-year-old overweight man with a sedentary job, and he is an ex-smoker with is family history of myocardial infarction under age 65. His blood pressure and lipid profiles were in a slightly raised risk zone when he saw his GP three years ago, and he would like to be able to find the motivation to reduce his risk of a heart attack. His wife bought him a motion and position-tracking wristwatch for his birthday to encourage him to exercise. The device required him to register with the company s website and create a profile with the option to connect with social networks such as Facebook to get support from his friends. There was also a link to a general PHR system, where he decided to create a profile. His primary care organization had an agreement with the PHR provider to advertise a linkage scheme between medical records and PHRs. So he made an appointment with his GP and arranged for the records to be linked. Mr. Smith and his GP discussed cardiovascular risk reduction strategies. Use Cases of lifestyle change vs. risk were available for Mr. Smith to reflect via his PHR on the Web following the consultation. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 24 of 66

25 The act of sharing his physical activity achievements with his friends and GP motivated Mr. Smith to keep taking regular exercise. The treatment for high blood pressure that had been considered at the first consultation was no longer necessary after three months of regular exercise. The primary care organization had engaged actively in health promotion with a person who, in times before the PHR and connected devices, might not otherwise have presented until they had symptomatic disease. The consumer of a well-being product in this case had made first contact. First contact might otherwise be made by the healthcare provider running population based cardiovascular screening for the over-40s. Both of these approaches are pre-primary care. Participants and Roles Patient Acquire and utilise device Take measurements e.g. BP, weight, blood glucose Routinely connect device to web-service to maintain training log Maintain on-line personal health record Primary Care Physician (GP) Review and act upon data retrieved via PHR and/or access PHR service Supplier - Device Provide training log web-service and interfaces Provide user support service Supplier PHR Service Provide secure PHR service, interfaces and support including comparative data, guidelines, reporting, notifications and exports to primary care clinical record D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 25 of 66

26 High-Level System Interactions Figure 2 Data Capture and Data Flows The objects defined as red circles in figure 1 above relate to the flow of data items (see below). Examples of Data Capture and Data Flows In each of the steps below other key data items will also be captured automatically or by manual input e.g. person_id, date, time etc. Captured on Device and Uploaded to On-Line Activity Log (A) Frequency: as used Steps taken [number] Distance travelled [metres/yards] Calories burned [number] Sleep [hours/minutes] Very active minutes [number] Floors climbed [number] Input by Patient to On-Line Activity Log (B) Weight [lbs./kilos] Resting Pulse [b.p.m] D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 26 of 66

27 Blood Pressure [sys/dia mmhg] Blood Glucose [mmol/l or mg/dl] Medication Taken [text] Supplements Taken [text] Food Diary [text] Calories Consumed [number] On-Line Activity Log Upload to PHR (C) Daily summary/total/average of data input to on-line activity log May include symptoms e.g. headache, sore throat etc. Patient Review and Update of PHR (D) Addition of text notes and comments that may be associated with items uploaded from summary primary care record May include perceived side effects of medications PHR Update to Primary Care Record (E) Frequency: Daily/weekly/monthly Summary of activity [daily/weekly/monthly steps, calories etc.] Weight Blood Pressure [actual or average/min/max per period] Blood Glucose [actual or average/min/max per period] Medication Taken Supplements Taken Other items e.g. symptoms Primary Care Record Summary Update to PHR (F) Frequency: as required Appointment reminders Medication Prescribed Current conditions Alerts Normal values Business Case Perspectives Patient Benefits Costs Direct engagement of the patient in the management of their health risks and treatments with regular indicators of Purchase of device D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 27 of 66

28 progress and change. Potential reduction of medications Possible subscription service for on-line activity log and PHR Reduced risk and improved outcomes including reduction of hospitalisation and more serious interventions Holistic approach rather than separate treatment of individual conditions Access to knowledge bases and comparative information Provision of richer data to primary care practitioner improves decision making Ability to record effects of medications etc. Better engagement with primary care practitioner on the basis of a common data set Impact on My Current Behaviours and Ways of Working: The solutions proposed in this use case engage the patient directly in the monitoring and management of their own health but the benefits will only be achieved if the use of the device and maintenance of associated records becomes routine along with the obvious changes of lifestyle and compliance with medical advice that will actually bring about the reduced risk. Care Professional Direct and Indirect Care In this case the patient s G.P. and other practice staff e.g. dieticians and practice nurses. Benefits Access to a rich and timely set of patient recorded data including information that is not currently available e.g. daily measurements, medication compliance, medication effects, exercise data etc. More informed decision making. Costs Greater time required to review data Potential costs of changes to system functionality to support interaction with external systems i.e. PHR D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 28 of 66

29 More effective prescribing possible cost reduction. Reduction of medication with possible cost reduction Review of clinical records including audit of coding Impact on routine screening and chronic care management processes Reduction of referrals, hospitalisation and more serious interventions. Potential to engage other providers e.g. community pharmacists, to offer services such as BP measurement linked to PHR. Impact on Current Behaviours and Ways of Working: The direct costs for things such as system changes are likely to be very significantly less than the indirect costs associated with ensuring that: Time can be made available to review data retrieved from the PHR and to take any necessary action based on current values and trends The information contained in the local patient record is accurate with consistent coding Care Provider Organisation In this case the organisation view is very similar to the care professional view listed above. Commissioner/Payer Depends on take up within the locality but: Benefits Costs Healthier population More effective and reduced prescribing with associated cost savings Reduced referrals, hospitalisations and serious interventions with associated cost savings Funding required to enable primary care providers to undertake roles described above Additional informatics staff required to support practices and provide local intelligence services Improved intelligence about local population leads to more informed decision making resulting in more effective targeting and deployment of resources D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 29 of 66

30 Ability to engage with population/patients via integrated web-services Impact on Current Behaviours and Ways of Working: Development of a long-term strategic approach to investment in community-wide information systems. Community Benefits Costs Strengthen informal care networks through improved communication and data exchange through web-services Opportunity to self-organise patient groups around given disease(s) Impact on Current Behaviours and Ways of Working: Establishment of new support networks possibly linked to existing organisations. More awareness of and use of information systems System and Service Providers Benefits Costs More effective use of the systems that they provide with resultant improvements in personal and population health Increased revenue System changes required to ensure compliance with interoperability standards and integration with external systems Potentially larger market Impact on Current Behaviours and Ways of Working: Traditionally clinical system suppliers in England have developed solutions to meet the needs of specific markets that are largely determined by organisation type e.g. acute hospital, community hospital or primary care practice. This is not surprising as these are the only levels at which customers for their solutions exist. If the solutions proposed here are to be implemented on anything other than a small, local scale, requires a redefinition of the market both by the suppliers and the purchasers. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 30 of 66

31 Other Consequences It is likely there will be side effects from the implementation of the proposed solutions. In this case it is clear that the care professional could have access to more data about their individual patients that is potentially more accurate and certainly more frequent than they currently collect. However knowing that: More adverse medication effects are being reported Patients are not complying with medication regimes as expected Patient measurements weight, BP and blood glucose are fluctuating and do not appear to be the same as recorded in surgery Medications or exercise programmes may appear to have an unexpected adverse effect requiring the care professional to take directive actions that they may not have taken without this knowledge. This may not fit with existing care pathways. Scale Issues While the majority of the components are already available and in widespread use throughout the world, this has been driven predominantly by widely distributed individuals with a particular interest e.g. athletes, rather than by contiguous local populations. Clearly benefits can be derived by individual patients even if all the elements of this use case are not in place, but the benefits for larger populations are dependent on the scale at which these technologies are taken up and in particular on the linkage to the primary care clinical record system. If GP practices were to offer to make summary records available to their patients in this way it is likely that there would be significant take up by patients with high risk factors. Rate limiting factors include: Willingness and ability of primary care system suppliers to implement integrated solutions Resourcing of practices to cope with the consequences of receiving patient sourced data Ensuring that externally sourced data is clinically reliable Affordability devices and subscriptions. However, given the value of reducing risk factors and consequent savings from reduced interventions and hospitalisations it is likely that the overall effect in the medium to long-term would be at least cost neutral Willingness of patients to participate in a commercial PHR service. However it is likely that primary care system suppliers may provide PHR functionality as an extension of their clinical systems thereby increasingly levels of trust and more closely coupling the PHR and GP systems Semantic Interoperability Challenges The data items involved in this use case are relatively straightforward (and should not present complex interoperability challenges with respect to the clinical systems involved. However, given that the majority of the architecture components are outside the normal domain of clinical systems and the fact that suppliers of devices and support services have developed their own standards, there are still a number of issues that must be tackled. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 31 of 66

32 This reinforces the need for a body to take responsibility for coordinating existing standards and bringing together the academic and clinical stakeholders with the broadest supplier community based on a shared vision of safe, integrated systems. Current Status and Feasibility All of the individual systems and services required to support this use case are currently available and are being used by citizens, patients and providers to some extent. As an example information about some of the higher profile on-line activity logs and devices are included as Appendix 1 of this paper. However it is unlikely that the whole, end-to-end, process outlined in this use case is in use anywhere certainly not on a comprehensive community or population scale. There are a number of reasons for this including: Technical interoperability while some commercial providers of devices and on-line activity logs have reached agreements that enables the sharing of data between systems that are a variety of standards in use and it is not possible to share data between all devices and all systems Semantic interoperability suppliers claim to be able to collect medical-grade data with no clear definition of what this means. Some devices record measurements such as blood pressure and blood glucose using their own coding systems rather than internationally recognised standards such as SNOMED The suppliers and users of organisation-level patient record systems have not been motivated to develop solutions that support integration to external PHR and activity logging systems There have been no large-scale initiatives designed to assess the feasibility and cost/benefits Patients (individually or on a community level) are unable to exert pressure or influence on healthcare providers and system suppliers D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 32 of 66

33 Targeting and Deployment of Resources The four use cases that are included in this section have different perspectives and present specific individual requirements. However, in principle, they share many similar components as outlined in the following diagram: Figure 3 Aggregate or summary data is derived from primary care or hospital clinical systems for patients meeting particular criteria (A) This is brought together with comparative data obtained from research findings or literature sources (B) and data from national and/or local surveys (C). Data about the availability and deployment of local resources as well as local demographics may be added. The lead participant analyses the data and applies models using a variety of techniques to assess the impact of different interventions or approaches. Action is taken and the situation is monitored, using the same models refreshed with new data, in order to measure impact and make any changes that might be needed. Consequently, rather than repeat the various benefits/costs, other consequences and current feasibility sections for each use case, we have described these for the group as a whole and then addressed the differences within each case. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 33 of 66

34 Business Case Perspectives Patient Benefits Costs Reduced risk of CVD Increased well being Side effects of medications Cost of prescriptions Access to more support services as required dieticians, smoking cessation etc. Impact on Current Behaviours and Ways of Working: Significant behaviour and lifestyle changes required to reduce risk Need to provide more information to care professional Compliance with prescriptions Care Professional Benefits Costs Better understanding of risks of individual patients Better understanding of risks for population as a whole Better targeting of effort Improved monitoring of effectiveness of care Impact on Current Behaviours and Ways of Working: Need for more frequent, complete and consistent data collection Care Provider Organisation (Primary Care) Benefits Costs Reduced cost of referrals and interventions Better outcomes for patients Increased prescribing costs Increased screening for patients considered high risk Increased frequency of laboratory tests D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 34 of 66

35 Impact on Current Behaviours and Ways of Working: Need for more frequent, complete and consistent data collection Review of screening protocols and data quality assessment Commissioner/Payer Benefits Reduction in CVD risk for population Longer term reduced cost of referrals and interventions Better targeting of resources Better monitoring of effectiveness Costs Increased prescribing costs not only of statins but also for other medications associated with CVD risk factors Resources required to establish intelligence service and associated data management processes Awareness raising Need for other support services aimed at reducing risk factors e.g. smoking cessation Impact on Current Behaviours and Ways of Working: N/A Community Benefits Resources released for other purposes Awareness raising Costs Healthier population with reduced demand on health services Impact on Current Behaviours and Ways of Working: N/A System and Service Providers Benefits More effective use of systems Costs Possible cost of developing new functionality and compliance with interoperability standards Impact on Current Behaviours and Ways of Working: N/A D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 35 of 66

36 Data Issues The data sets and the data flows considered in each of the use cases are similar. Semantic Interoperability Challenges The semantic interoperability challenges contained in these use cases relate mainly to the consistent recording and extraction of specified datasets from primary care EHR/clinical systems (A) and the ability to integrate those data with summaries and reports from other sources. The main challenge is to ensure that, for each of the risk factors listed above, every practice is able routinely to generate consistent outputs of aggregated data that can be incorporated into the population risk models regardless of the source system. Associated with this is the need to consider the consistency and accuracy of the coded data that is provided by each practice. Current Status and Feasibility There are probably no significant mechanical barriers to establishing the risk management measures described in these use cases. Currently data can be derived from primary care clinical systems and loaded into public health and commissioning systems in order to assess/model risk and inform management decisions. Comparative national and international data is routinely available however this is not always in a consistent or easily usable format. Requirements include: Common data recording protocols for all CVD risk factors to ensure that data is captured consistently at source Definition of common CVD risk factor datasets D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 36 of 66

37 10.3 Topic 2 - Optimal Primary Prevention with Statins Keywords/Tags Risk assessment, population stratification, prevention, cardiovascular disease Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases - 31 December 2012 page 15 Decisions Needing Population Health Summaries At what level of CVD risk should practices be expected to prescribe statins in my local health economy? What is needed to enable an accurate and informed decision? 1. Calibrated and continuously validated model of risk, tuned to the local health economy what are the current levels of risk for our patients and what is being done to reduce that risk? 2. Evidence based policy of when to prescribe for a defined level of risk. Purpose of Use Case This use case describes a solution where significant population health benefits could arise from a situation where health and lifestyle data relating to CVD risk that is routinely collected in primary care across a large population area is aggregated and compared with other data sources to enable the effective targeting of risk-reducing medications. Scenario The public health team at Megachester 10 are concerned at the high prevalence of CVD and the associated high premature death rate locally. They know that people in their area have high levels of risk factors for CVD, and they want to explore the potential for reducing some of this risk by increasing access to statins. Using national data supplemented with local information on the characteristics of patients in their area they shrank some risk factor information down to neighbourhood level. For other risk factors they have more direct measures, for example cholesterol and blood pressure from vascular screening records in EHRs. Missing data was modelled using information derived from relevant research. They set out various options for increasing access to statins and used a Markov model to simulate the potential reductions in CVD incidence with each option. The options included all people with more than 20% 10 year risk, and targeting to various age and community groups. Monte Carlo simulations were used to reflect the uncertainty in the simulated information. 10 Note that this is the equivalent to a Public Health Centre as described in Figure 1 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 37 of 66

38 Data Issues Data Flows and Processing Figure 4 below shows the processes that the public health team follow as they calculate the effects of setting statin prescribing levels for their population. Research Findings Quantifying the effects of statin prescribing on the incidence of CVD Health Surveys Estimating the levels of CVD risk factors (and allied health status measures) Medical Records & Admin Data Reflecting CVD incidence, events and deaths Model the number of patients who are at high risk (>20%) of developing CVD during next 10 years Examine EHRs to determine prescribing history of patients at high risk Estimate number of patients who might benefit from statins but are not receiving them Simulate reduction of heart attacks among these patients if they took statins Cost of inviting for screening all patients estimated to be at elevated 10 year risk of CVD event Cost of prescribing statins to all patients considered high risk Cost benefit from reduced hospitalisation and other treatment events Figure 4 Data Items - CVD Risk Factors 11 These are also addressed in more detail by other SHN work streams which also examine the associated semantic interoperability issues involved. 11 Link to 2012 BHF Report ( ) D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 38 of 66

39 The public health team need consistent and comparable data for each risk factor for individual patients as well as for the whole population including: 1. Modifiable a. High blood pressure b. Smoking c. High blood cholesterol d. Diabetes e. Poor (high fat) diet f. Lack of exercise g. Overweight/obesity h. Excessive alcohol consumption i. Stress j. Effect of other medications k. Psychosocial Factors including: i. Low socio-economic status ii. Social isolation iii. Depression iv. Panic attacks 2. Not Modifiable a. Age b. Family history of CVD c. Gender d. Ethnic Origin Other Consequences While this use case focuses on determining the optimum level for prescription of statins there are various predictable effects that will arise when the data required to populate the risk models becomes available. The processes outlined here could equally be applied to other conditions e.g. diabetes, hypertension and obesity, all of which will place additional demands on resources and services. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 39 of 66

40 10.4 Topic 3 - Targeting Public Health Measures to Reduce Obesity Keywords/Tags Diet, exercise, physical activity, health promotion Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 18 Decisions Needing Population Health Summaries How can interventions to reduce the prevalence of overweight and obesity be targeted to achieve the maximum benefit in my population? What is needed to enable an accurate and informed decision? 1. Evidence for which interventions are most effective in reducing overweight and obesity 2. Data on current deployment of resources 3. Comparative data from other areas 4. Data about distribution of overweight and obesity in the local population Purpose of Use Case The use case describes a problem that the commissioner is not able to resolve satisfactorily due to lack of reliable data. The challenge presented is that sample data from national survey sources is not specific enough to inform critical local decisions on the deployment of scarce resources. More data on more patients in the local area is required to enable a detailed understanding of the local situation including comparison with the assumptions arising from the national data. It will be important also to refresh data regularly in order to: Monitor the effect of interventions Adjust decisions about the use of resources Scenario Peter, the weight management commissioner for Mezopolis 12, received the latest figures for his population from the national obesity surveillance scheme. The statistics placed Mezopolis as one of the worst areas in the country for excess body weight. Peter was concerned that this oversimplified the challenges that his relatively deprived community faced. So he asked the public health team to analyse the pattern of BMI by deprivation group. National surveys had sampled just enough households in Mezopolis to relate BMI to deprivation and sex. Consistent with scientific papers on the subject, women from the lower income households tended to carry more excess weight. Unlike the literature, however, the overweight and obese men 12 Note that this organisation is equivalent to an NHSE Area in Figure 1NHSE D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 40 of 66

41 in Mezopolis tended to have higher incomes. Peter and the public health team decided that a more detailed picture of BMI was required, including ethnicity and neighbourhood patterns. The national survey data was insufficient for profiling small groups and areas. The only unbiased data on BMI at this level was from child health surveys in the local schools. Adults are measured by their primary care services, but the fatter adults tend to be measured more than the slimmer ones, creating a biased picture. Some healthcare contacts, such as new patient registration in primary care, antenatal clinics, occupational health screening and vascular screening, lead to routine measurement of weight in some groups. So an adult obesity profile for Mezopolis would have to be estimated using a variety of assumptions and models. A statistician in the public health team considered using a synthetic shrinkage method to produce small area estimates of obesity prevalence from the national survey data linked to some detailed profiling of local neighbourhoods. He thought that the assumptions of this modelling were difficult to justify so he did not proceed. Instead he searched primary care records for contacts where weight was known to be recorded routinely. Three different models for estimating adult BMI by neighbourhood were used, but they produced a similar ranking of neighbourhoods by mean BMI or obesity prevalence. The neighbourhoods were categorised by BMI, deprivation, ethnicity and other factors known to affect either obesity risk or the uptake of weight management interventions. The evidence base on the effectiveness of interventions to control weight was too patchy to enable a simulation. So a sensitivity analysis using a selection of high quality studies was run in order to explore the value of targeting more weight management resources to specific neighbourhoods. Eventually, a largely qualitative decision was made to target deprived neighbourhoods, mainly because their residents are harder to reach with health promoting activities. It was also decided to improve the surveillance of adult obesity in primary care and some workplaces. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 41 of 66

42 Data Issues Data Processing Health Surveys e.g. Age, Gender, ethnicity, household income, education level, height, weight, waist circumference etc EHRs e.g. Height, recent weight, age, gender, geocode to infer economic status, relevant healthcare information Model prevalence of obesity by population sub-group in small areas Simulate public health impacts by subpopulation of interventions to promote healthy energy balance Figure 5 Survey Data For the public health team to gather the intelligence that they need to complete this task they need to be able to bring together survey data from a number of sources, for example Active People Survey for England 13 Adult Health Survey for England 14 Data items currently contained these surveys include: AreaCode (n=326) Number of people (n=134,000 with average of 410 per area code) % underweight (underweight defined as BMI less than 18.5kg/m2) % overweight (BMI greater than or equal to 25 but less than 30kg/m2) % obese (BMI greater than or equal to 25kg/m2 (overweight including obese) % excess weight (BMI greater than or equal to 25kg/m2 (overweight including obese)) Statistics on obesity for England can be found at D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 42 of 66

43 10.5 Topic 4 - Monitoring Smoking Cessation Services Keywords/Tags Smoking, Monitoring, Effectiveness, Public Health Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 20 Decisions Needing Population Health Summaries Is my local smoking cessation service as effective as those in other areas? If it is not then what changes need to be made to ensure that the service improves? What is needed to enable an accurate and informed decision? Comparative data about smoking quit rates identified down to local areas Information about resources deployed in smoking cessation both locally and in other areas Clinical data about local population Components of the decision include: How many of smokers and ex-smokers are there (and have there been) in my local population? How many of these develop CVD and cancer? How does this compare with other areas? Purpose of Use Case This use case describes a situation in which a public health manager is unable to reach a viable decision due to lack of local and comparative data. It shows that, without accurate data about the characteristics of the local population derived from clinical systems, it is not possible for public health managers to monitor the impact of local services or to compare the effectiveness of those services with equivalent services in other areas. Scenario Sarah, who works in Metroville s public health department 15, wanted to estimate the local smoking quit rate so she could forecast the impact on CVD and cancer rates. From reading the literature she was familiar with the characteristics of the smokers who quit. She used this information, along with intelligence from patient records and the quit smoking team, to construct a regression model to forecast the annual smoking quit rate in Metroville and its effect on CVD incidence. Sarah estimated the prevalence of smoking in Metroville by calculating a synthetic estimate from a combination of national and local data. She used patient EHRs and data from the smoking cessation 15 This is equivalent to a Public Health Centre in figure 1 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 43 of 66

44 service to estimate the annual number of smoking quitters. The model was revised and updated on a continuing basis as more data were collected. From the estimates of smoking prevalence and quit rates Sarah constructed a set of forecasts of the effect on the incidence of CVD and lung cancer. Although many of the factors associated with quit rates can be estimated from demographic and socio-economic data, e.g. age and social class, one crucial variable is the strength of the intention to quit. In the models Sarah changed the value of this variable and observed the effect on quit rates. It became clear that crude statistics on quit rates are inadequate for comparing one smoking cessation service with another. Data Issues Flows and Processing National Surveys EHRs Smoking Cessation Services Estimates of smoking quit rates Estimates of smoking quit rates Estimates of smoking quit rates Model overall quit rate for district Model effect on CVD, lung cancer and all-cause mortality rates of changes in smoking quit rates Figure 6 National smoking surveys 16 are conducted quarterly in England and include the following data items: Local Authority Code For males and females: o Number of people setting a quit date o Number of successful quitters o Number who had not quit 16 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 44 of 66

45 10.6 Topic 5 - Mapping Missed Opportunities to Prevent Cardiovascular Events Keywords/Tags Blood Pressure, care pathways, Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 22 Decisions Needing Population Health Summaries Which general practices should be alerted about the quality of their blood pressure control in respect of CVD care pathways and events? What is needed to enable an accurate and informed decision? Guidelines and care pathways expressed as structured protocols with appropriate clinical coding Clinical data from primary care systems for all patients including blood pressure, cholesterol, diagnosis etc. Hospital activity data for patients admitted for CVD events Purpose of Use Case This use case describes a solution where a clinician working as a commissioner is able to use patient data derived from primary care systems to identify which practices need to improve the frequency and consistency of data collected for patients at risk. It outlines a method for identifying sub-optimal treatment of patients who have experienced a cardiovascular (or any other chronic disease) event. Scenario Dr Jones, the lead commissioner for cardiovascular healthcare services for Megachester 17, suspected that the unusually high variation in CVD events across the district might be due to differences in vascular screening and risk control. She asked her informatics department to map the guidelines and care pathways for coronary heart disease (CHD) to EHR codes. They reported that blood pressure and cholesterol control in primary care was easily measured for patients with a CHD diagnosis. This information could be linked with hospital admissions for heart attack or acute coronary syndromes, and to deaths data. For all patients experiencing a CHD event their prior blood pressure and cholesterol levels were analysed 30% had poorly controlled blood pressure and 20% poorly controlled cholesterol. Many patients were also missing these measurements in the year before the event. The blood pressure and cholesterol control was then analysed for all patients with CHD, irrespective of whether or not they had experienced a cardiac event. Patients from some practices were found to have tighter risk factor control than others. On further analysis it was noted that patients who d 17 This is equivalent to NHSE Area in figure 1 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 45 of 66

46 experienced a missed opportunity tended to be from the more economically deprived areas of the district. There was also a higher proportion of missed opportunities among the older patients. Dr Jones used these findings to persuade her primary care colleagues to review the treatment of all patients with elevated risk factors for CVD, and to ensure that older patients and those living in the more deprived areas received close attention. Data Issues Data Flows and Processing Guidelines EHR Literature Identify the risk factor targets that clinical guideline recommend for optimal care and that are available from the EHR Identify from EHRs the patients who had experienced a CVD event Identify the patient whose CVD risk factor measurements do not meet targets and the extent to which target is missed Estimate (from a model) the number of cardiac events that might have been prevented if targets had been achieved Figure 7 Semantic Interoperability Challenges Guidelines and pathway definitions need to be expressed in terms that comply with interoperability standards and must be capable of being managed within the relevant systems. Care Delivery D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 46 of 66

47 10.7 Topic 6 - Monitoring the Diagnosis and Treatment of Heart Failure Keywords/Tags Heart failure, EHR, medication, guidelines Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 24 Decisions Needing Population Health Summaries What changes can be made to local services in order to optimise the management of patients with heart failure (HF) ensuring that all health professionals, the patient and carers have the information they need, particularly over medication? Scenario Dr Ellen Jackson, the CVD lead at the Buena Vista healthcare centre 18, wanted to improve the information in the EHR available on the diagnosis and treatment of the practice s patients with or at risk of heart failure. She was aware of the inadequacies of the current information collected, and drew up a specification for a more effective method of ensuring patients received the optimal medication. The following are the requirements that Jackson identified: Diagnosis Follow the NICE guidelines on the diagnosis of HF, and ensure each stage is recorded. If any patient has their name on the HF register on a provisional basis, remove the name from the register if there is no evidence of HF. For patients diagnosed in hospital with HF after admission, ensure that the diagnosis is received at the practice and entered on the patient s record. Specialist services should include the appropriate primary care read codes in order to ensure that patients are coded correctly on systems. Add the patient s name to the HF register. Ensure that the information received from the hospital relating to the admission is added to the record using agreed protocols. Treatment The prescribing of ACE inhibitors and beta-blockers for patients with HF is variable, especially the up-titration of medications to target doses. The information system should alert clinicians to those patients who may not be receiving the appropriate medication at an appropriate dose. 18 GP Practice in figure 1 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 47 of 66

48 Data Issues Long-term Condition Reviews Patients with HF typically have more than two serious health conditions. These other morbidities affect the treatment which is appropriate for those patients. Such reviews should not be held separately for each condition. Reviewing all the patient s morbidities at the same meeting will help to ensure appropriate treatment is offered, and contraindications taken into account. All the data presented at those meetings should be recorded consistently. Typical Workflow for Monitoring Heart Failure Care Patient seen by primary care clinician with HF signs and symptoms Patient admitted to hospital with e.g. breathlessness Investigation for HF BNP test and echocardiogram HF Suspected Patient admitted HF Diagnosed Enter patient details on heart failure register HF Diagnosed Send reports to be added to patient s primary care record. Specialist services should include primary care codes Record all treatment provided to the patient using clinical terms and codes understood by ALL members of the team providing care from different parts of the healthcare system Monitor treatment Assess regularly for signs of decompensation Figure 8 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 48 of 66

49 Verifying the Accuracy of a Heart Failure Register HF Register Search to verify that patients have a confirmed diagnosis of HF and are receiving appropriate treatment No Evidence Evidence Inconclusive Remove name from register. Investigate patients for other conditions. Test patient for signs of HF using BNP and echocardiogram HF Confirmed Ensure patient is receiving appropriate treatment Figure 9 Ensuring the Identification of Patients with Heart Failure EHR Search for evidence of patients receiving diagnostic tests or treatment for HF e.g. ACE inhibitors Sufficient Evidence Inconclusive No Evidence Add those patients to HF register and ensure that they receive appropriate treatment Invite patients to clinic to test for HF Investigate reasons for medication If diagnosed with HF add patients to HF register and ensure that appropriate treatment is received Figure 10 D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 49 of 66

50 Patient Co-Produced Information for Cardiovascular Health(care) 10.8 Topic 7 - Co-production of Cardiovascular Health & Care Keywords/Tags Apps, Mobile Technology, Patient Access, Patient Held Records, Personal Health Records, Patient Devices, Social Networking, Health Promotion Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 27 Decision Requiring Population Health Summaries What are the benefits for patients and practices from the use of Web and mobile technologies to improve the management of people with long-term conditions, particularly CVD? Scenario 7a Mrs Brown is a 76 year old lady with early HF and a history of coronary heart disease. She saw a poster in her primary care physician s office about accessing her records from the Web, so she gave consent for this to be switched on. The consent included linking to external services from approved suppliers, including companies making connected bathroom scales and pedometers. Mrs Brown asked her daughter to help her access her record via the Web. On doing so she noticed that a medication she no longer collects from the pharmacy was on repeat prescription. She also noticed that none was recorded under allergies when she remembered being very ill after receiving penicillin many years ago. So she used the comments box to make notes about this and her clinician called to discuss and make corrections. Mrs Brown s daughter bought her the weighing scales and pedometer for her birthday. She enjoyed using these, as she felt more involved in her own care, and had practical targets to aim for. The HF nurse told Mrs Brown about an application from a medical charity that connects people with HF with one another to compare progress with lifestyle targets such as walking more and to compare experiences with monitoring symptoms such as the weight gain due to fluid retention when drug treatment is out of kilter. Joining in this social network helped Mrs Brown to feel less like a passive patient and more like an active customer of wellbeing in spite of having HF. Scenario 7b As part of his clinic s vascular screening programme Dr Schmidt approached a local company about designing a mobile app to enhance the experience of his patients with screening. Initially he wanted to have more accurate CVD risk information available close to the time of screening. As discussions D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 50 of 66

51 progressed he became more interested in the potential of this technology to engage patients in risk factor control long after their contact with the screening programme. The app company raised the use of social media such as Facebook and Twitter. Dr Schmidt read some papers on cognitive models of health promotion in weight control and realised that effective intervention needed a less medical and more wellbeing approach. So he discussed a bigger project with the CVD service commissioners and public health team in his area. Together they decided to pilot the use of a vascular wellbeing app that would be offered as part of the invitation to vascular screening, and they linked the necessary consent process to the extant scheme to open primary care records to patients. There were some initial difficulties over validating the algorithms for calculating CVD risk but the pilot was very popular among patients. Dr Schmidt eventually took over the primary care aspects of the app to use it to help people with raised CVD risk to manage their condition including automatic alerts sent to him when patients on CVD care pathways are off target. The public health team and a group of patients eventually took over the pre-clinical aspects of the app maximising its appeal as a fun, wellbeing tool. Population Summaries In both of these use cases social network features were key to engaging individuals in monitoring their health. The social information may be with anonymous reference (to the average patient like me ) as well as supporting peer-to-peer communication. Thus population level searches of the data and modelling are key and this is an on-going process to keep apps fresh and to quality assure the medical aspects of the information. Business Case Perspectives Patient Benefits Costs Direct engagement in monitoring and managing their conditions Reduced risk Devices Subscription services/apps Potentially less frequent attendance at practice More complete and accurate GP records lead to better informed clinical decisions Alerts and early warnings Impact on Current Behaviours and Ways of Working Both parts of this use case require patients to accept responsibility for monitoring their condition but include solutions that enable this to be done easily using technologies with D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 51 of 66

52 which they may already be familiar. The tools and associated social networking provide strong motivation. Care Professional and Care Provider Organisation Benefits More timely, complete and accurate critical data available Early warnings Monitoring compliance with pathways Motivated and engaged patients Costs Time taken to review data Any costs associated with additional system functionality e.g. connection to PHR More aware and possibly more demanding patients Impact on Current Behaviours and Ways of Working: As with use case 1 widespread take up by patients of these solutions would have a significant effect on the day-to-day business of the practice. More time is required to review data that has been generated by patients and to act on the results where necessary. Note that the solutions described here could be used for a wide range of chronic, long-term conditions e.g. diabetes, COPD etc. Commissioner/Payer and Community Similar to use case 1 above System and Service Providers Benefits Increased market size Opportunity for innovation and differentiation Costs Development, marketing etc. Compliance with standards Opportunity for new suppliers to enter market Impact on Current Behaviours and Ways of Working: Need to architect systems to comply with agreed standards and participate as components of a secure open architecture rather than as meeting the needs of only one type of organisation e.g. general practice. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 52 of 66

53 Data Elements Inputs and Outputs Data Sources and Data Items From patient devices and via web forms including: Scale Issues Secure patient identifiers Date and time Weight, BMI, muscle mass, body fat etc. CVD risk factor data (see use case 2) Data Flows From the device via the PHR to the primary care practice system. The frequency of these data flows could be real-time or, for example, daily/weekly/monthly. The rate-limiting factor in these use cases is the willingness and ability of the primary care provider to engage with patients in this way. It is likely that opening up these channels would result in significant demand from patients with chronic conditions and therefore there is potential for large-scale take up on a practice-by-practice basis. Semantic Interoperability Challenges Very similar to use case 1. These are focused on the interface between the devices/apps/web services and the primary care clinical system however the actual data items are well understood and in widespread use. Current Status and Feasibility As in use case 1 the solutions described here are already in use and have been for some time. However there is little evidence in the UK of the completion of the data flow from the patient through into the practice system. Rather data collected by patients on devices such as smart phones is stored in on-line activity logs and PHR s but is not accessed by their care professionals unless perhaps it is printed out, presented during a consultation and then scanned into the clinical record. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 53 of 66

54 Investment in New Medications 10.9 Topic 8 - Real-world Trial of a New Medicine to Prevent Stroke This use case describes a situation where a range of stakeholders work together to link previously disconnected data sources as well as collecting data from patients via mobile and web channels to measure the clinical and cost effectiveness of a new medication. Keywords/Tags Research, commissioning, stroke, medication, pharmaceutical Source SHN Deliverable 2.1 Summarising Health Records for Populations: Cardiovascular Use-cases 31 December 2012 page 29 Decisions Requiring Population Health Summaries Initially the question is Should my health economy invest in a new, expensive medicine that provides a more convenient way to stop blood clots forming in patients with abnormal heart rhythms, thereby preventing strokes? However, in attempting to answer that question the various parties involved create an information systems architecture that enables them to assess the effectiveness of existing approaches as well as the effects of the proposed new medication. Use Case Description Drug GK5777 has just been given a license and is due to be marketed as Thinotran. The business case for this drug relies on adherence being better because it is more convenient for the patient to take it is taken once per day, at any time, can be taken with most other medicines, and does not require regular blood tests to get its dose right. Healthcare commissioners/payers are concerned that this approach will be more expensive than conventional warfarin due to the higher cost of the drug plus the associated monitoring. The current Thinotran trials exclude people with multiple conditions, but searching EHR data reveals that over half of the people with a code for AF and a warfarin prescription have more than one long-term condition. So the payers and the drug company decide to run a real world, open-label study 19 where patients are randomized to the new drug or warfarin. The local stroke service redesign group become involved in setting up the new Thinotran study. They raise the relation between deprivation, carer support and adherence to medication among the typical elderly person who may be offered Thinotran. The initial study design used postcode linkage to infer deprivation from a patient s area of residence. The stroke team then pointed out that 19 a type of clinical trial in which both the researchers and participants know which treatment is being administered D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 54 of 66

55 deprivation scores from a national database were unreliable for the area where the study was due to take place, so more detailed socio-economic measures were incorporated. The stroke team also raised concerns over some of the assumptions being made by economists modelling the costs of stroke due to failure of warfarin titration. EHR data were eventually linked with: the clinical trial information system, financial systems that record healthcare transactions/costs, pharmacies, and social care information systems. Patient reported measures of quality of life were also used via mobile devices as well as research nurses this provided a richer longitudinal picture for the subgroup able to take part. The eventual analysis was more inter-disciplinary than usual, and drew heavily on local healthcare knowledge as well as data available from databases. In mop-up meetings after the trial, the drug company, payers and the healthcare providers involved agreed that reusing the data linkages and overall information system that had been established for the trial could reduce the costs of similar future studies. Furthermore, all parties acknowledged that such an information system would support the quality improvement activities of the healthcare system substantially. Business Case Perspectives Patient Benefits Potential access to more efficacious treatment Costs N/A Reduction of CVD risk factors Ability to provide structured feedback to care providers Impact on Current Behaviours and Ways of Working: Need to ensure compliance with medication and to provide feedback. Care Professional and Care Provider Organisation Benefits Better targeting of patients Costs Time required to review data Detailed information from patients Commissioner/Payer Benefits Costs D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 55 of 66

56 Better tools to inform management decisions Better understanding of characteristics of local population Awareness raising Coordination tasks Re-usable architecture Pharmaceutical/Clinical Trial Management Organisation Benefits Costs Better targeting System changes Reduced costs Richer data (compliance, effectiveness, side effects, costs etc.) Re-usable architecture Closer involvement with local community D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 56 of 66

57 Data Issues Flows and Processing Figure 11 Figure 11 above summarises the relatively complex infrastructure involved in this use case. It contains elements of some of the other use cases e.g. patient held records and devices, but brings in new factors and therefore new system interface challenges. In this paper we provide a conceptual view of the architecture rather than attempting to determine the physical or technical design of the cloud system at the centre of the diagram. Nor do we attempt to suggest how or who should host this system. Some of the data flows contain only aggregated information (e.g. E), whereas others are two-way and contain identifiable patient data. Data Items Examples of the type of data required in each data flow include: From the patient (A) Consent Medication Compliance (date, time, quantity) D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 57 of 66

58 Measures e.g. BP Symptoms To the patient (A) Alerts and reminders Questions Reports To the pharmaceutical company (B), primary care provider (C) and community pharmacy (D) Patient ID Medication Compliance (date, time, quantity) Measures Symptoms From the primary care provider (C) Alerts Patients meeting trial eligibility criteria Semantic Interoperability Challenges In data terms this use case handles data that is similar to other use cases described in this paper e.g. patient collected data, measurements and aggregated population-based data, but the addition of community pharmacy systems and clinical trial management systems expands the scope of organisations and systems that need to comply with appropriate semantic interoperability standards. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 58 of 66

59 11 Appendix 1 Topic 1: Examples of On-Line Physical Activity Logs The following screen shots show the type of information that can be recorded by the user (figure 2) and the information that can be gathered from the device and therefore made available for inclusion in the PHR and HER. Figure 12 Training Peaks Metrics Figure 13 Training Peaks Activity Recording D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 59 of 66

60 Figure 14 Garmin Health Log Figure 15 Garmin Activity Log Note that preliminary discussions with commercial suppliers of on-line fitness devices and logs suggest that no structured clinical coding standards are used to store information such as blood D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 60 of 66

61 pressure etc. 3 rd parties including Fitness Syncer are emerging to provide tools to enable synchronisation between fitness logs such as Garmin, Nike and Training Peaks with on-phr s including Microsoft Health Vault. Qardioarm is a shortly to be released wireless blood pressure monitor that connects to mobile devices and transmits medical-grade data that doctors can review and report back allowing healthcare providers to remotely monitor your heart-health on a routine basis. D2.2 Semantic resources for supporting cardiovascular prevention across PHRs and EHRs Page 61 of 66