Unit VII Research Paper

Unit VII Research Paper

 

Weight: 12% of course grade

 

For this assignment, you will complete the research paper that you have been working on throughout the course. First, you will compile the first three sections that you completed:

· Unit I (the introduction section),

· Unit III (the review of literature), and

· Unit V (the air and water quality affects). Be sure to incorporate any feedback you have received from your professor.

Then you will add the items listed below.

· Include a section that examines injuries or workplace hazards related to your topic. In this section, you should include the following items:

. a brief overview of the injuries or workplace hazards associated with your topic to include the effects of these hazards,

. an explanation of the environmental factors associated with these hazards,

. a discussion of methods for preventing these hazards, and

. an explanation of the significance of occupational health in relation to your topic.

· Include a conclusion section that sums up your paper and includes any final thoughts you have on your subject.

 

Your final paper must be at least eight pages in length, not counting the title and reference pages. You must use at least seven academic resources in your paper. Any information from those sources must be cited and referenced in APA format.

Environmental Health and Human Health Environmental toxicology examines how environmental exposures to chemical pollutants may present risks to biological organisms,

Environmental Health and Human Health Environmental toxicology examines how environmental exposures to chemical pollutants may present risks to biological organisms, particularly animals, birds, and fishes. Exposure to a physical, chemical, or biological agent may arise from a number of environmental sources, including the workplace, the home, and the medications and foods that we consume. On the list of hazardous chemicals and other agents that impact human reproduction negatively are pesticides, drugs, and heavy metals. Using the South University Online Library or the Internet, research on the following topics: Physical Agents Chemical Agents Biological Agents On the basis of your research and understanding of the topic, answer the following questions: Identify and describe five factors that affect responses to a toxic chemical. What determines the toxicity of a chemical? To what extent do you agree with the assumption that “all substances are poisons”? What is human exposure assessment? Explain some of the methods of exposure assessment. Why is epidemiology important to research studies of environmental health? Give reasoning to support your answer. What are some of the important limitations of the epidemiologic approach with respect to the study of environmental health problems? Create a 3- to 4-page Microsoft Word document that includes the answers to the above questions. Submission Details Support your responses with reasoning and examples. Cite any sources in APA format.

Student Presentations

Student Presentations

The student presentations (Group Project #4) are scheduled. Each team should prepare a 15- minute power point presentation and explain to the class their research question, hypothesis, and the approach for obtaining the selected articles. Each group should also discuss selection bias, misclassification and confounding as well as other items that determined the rigor of the studies identified in the systematic review. Each group should leave 5 minutes for questions.

Each student groups must ask at least one method question at each presentation session to gain full credit for this group project.

Research question: Is smoking cigarettes during pregnancy a potential cause of offspring to develop ADHD?

Reference articles:

https://pubmed.ncbi.nlm.nih.gov/22791738/

 

https://pubmed.ncbi.nlm.nih.gov/28138005/

 

https://pubmed.ncbi.nlm.nih.gov/35213510/

Writing the narrative of a grant or contract is no different

It is a good idea to always begin with an outline of the information you eventually want to turn into a full document. Writing the narrative of a grant or contract is no different. A draft outline is a tool that can help you organize your thoughts and develop a narrative that is fully descriptive of what you want to write about.

Using the weekly readings, the South University online library resources, and the Internet, research how to write a draft outline. Then, address the following:

Prepare a draft outline that highlights what your proposal narrative might look like for your chosen public health FOA.
As this is an outline, use bullet points to identify the areas your proposal narrative will address. Be sure to include a title page, an abstract, and a reference page.

RESEARCH PAPER

RESEARCH PAPER

Rethinking healthcare building design quality: an evidence-based strategy

Grant R.W. Mills1, Michael Phiri2, Jonathan Erskine3 and Andrew D.F. Price4

1Bartlett School of Construction and Project Management,University College London, 1^19 Torrington Place, London WC1E 7HB,UK

E-mail: g.mills@ucl.ac.uk

2School of Architecture,University of She⁄eld, ArtsTower,Western Bank,She⁄eld S10 2TN,UK E-mail: m.phiri@she⁄eld.ac.uk

3Centre for Public Policy and Health,School for Medicine,Pharmacy and Health,Durham University, Queen’s Campus,Stockton-on-TeesTS176BH,UK

E-mail: jonathan.erskine@durham.ac.uk

4Department of Civil and Building Engineering, Loughborough University, Loughborough LE113TU,UK E-mail: a.d.f.price@lboro.ac.uk

Healthcare buildings play a significant role in delivering healthcare services and outcomes (e.g. quality, suitability,

cleanliness, patient experience, value for money and risk mitigation). However, the current diffusion of

responsibilities in England between central government and healthcare trusts has created gaps and weaknesses in the

evidence base, knowledge, skills and tools for creating and assessing healthcare building design quality. How can a

national healthcare building design quality improvement strategy be created? This question is explored in relation to

policy, strategy and organizational issues. Four evaluation studies and four action research studies indicate the

complexity and responsibilities in defining a design quality improvement strategy. It is found that the interdisciplinary

development of national standards and tools requires centralized investment to facilitate nationwide learning and

improvements in evidence and outcomes. In addition, the inevitable health policy changes made by successive

governments require a sustainable and strategic response. The creation and maintenance of capacity and capabilities

will require a dedicated team of professionals and a wide interdisciplinary network of long-term contributors who are

motivated by a long-term desire to improve healthcare building design quality.

Keywords: assessment tools, design guidance, design quality, healthcare buildings, public policy, outcomes, quality

assurance, standards, strategy

Introduction The National Health Service (NHS) in England is today an organizationally complex environment, subject to frequent shifts in policy and overseen by a mix of regulatory authorities (NHS England, 2015). The effects of the reforms resulting from policy changes are routinely subject to high-profile commen- tary and analysis (Edwards, Crump, & Dayan, 2015; Gregory, Dixon, & Ham, 2015) focusing mostly on issues such as access to healthcare services, quality and safety of clinical care, patient outcomes, staff

satisfaction, finances and rationing of resources in a time of constrained budgets. In contrast, the role of the healthcare built environment, and its quality, receives much less attention (Edwards, 2013). In part, this is due to the inflexible nature of healthcare buildings, which typically have a lifespan measured in decades. But it is also the case that there are far fewer healthcare infrastructure professionals such as property and estates managers according to NHS workforce statistics (HSCIC, 2015) available to lobby for resources, compared with the number of clinicians

BUILDING RESEARCH & INFORMATION 2015

Vol. 43, No. 4, 499 – 515, http://dx.doi.org/10.1080/09613218.2015.1033880

# 2015 The Author(s). Published by Taylor & Francis This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/Licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

 

 

and administrators, organized into professional associ- ations and clinical colleges.

While the individuals and organizations responsible for the healthcare built environment may not enjoy as high a profile as others in the health system, they nonetheless have an equal responsibility to respond to the highly dynamic landscape of healthcare policy and practice. Furthermore, this responsibility means that the future healthcare building design quality improvement strategy should be based on a robust evi- dence base (Phiri, 2006; Sadler et al., 2011; Ulrich et al., 2004, 2008). Those who plan, design, construct and maintain the healthcare estate, and who are charged with its strategic development, therefore need access to an authoritative, expert source of infor- mation and guidance. In the past, such a resource was available from central government. For example, the Department of Health (DH) has historically had a strong role in initiating and facilitating evidence- based strategy to capture and disseminate evidence in England. However, following a number of organiz- ational reconfigurations of the NHS in England, the key enabling role played by the DH has recently diminished, focusing evidence-based learning at a local NHS trust level, not at the level of national healthcare building standards and guidance. Against this background, two central questions emerge:

. How can a future strategy for improving quality and safety in healthcare facility design be estab- lished in a healthcare sector subject to frequently changing policy?

. How can there be national and long-term learning in the implementation of such a strategy to improve the evidence and quality of outcomes?

This article addresses these questions through a review of recent academic studies and the discussion of find- ings from eight studies which investigated evidence- based standards and strategic planning tools. To ensure consistent understanding through the article, three key definitions are provided:

. Health or healthcare policy is a government’s planned course of action or a pledge made by an political party. Healthcare policies are concerned with delivering change to healthcare services, to improve the affordability and accessibility of high-quality care. They may change relatively quickly and frequently compared with the typi- cally 60-year design life of buildings. Policies have various indirect influences on physical build- ings and so will contribute to their technical, social and clinical sustainability.

. A national healthcare building design quality improvement strategy is a cross-organizational

action plan that provides a shared interpretation of how research and development can respond to healthcare policy in order to maintain and sustain building design quality.

. Future national healthcare building design quality improvement scenarios are alternative descriptions of influencing factors and plausible futures that can support ‘forward looking’ (Godet, 1987). Scenarios can create alternatives and preparedness to address uncertainties. Scen- arios most critically allow the elaboration of strat- egy (ways to work out scenarios) and can identify strategic gaps.

Imperative for an emerging strategic response A strategy to improve the quality and safety of health- care building design was implicit in the 1946 Act and subsequent launch of the NHS in 1948 (The National Health Service Act 1946). Apart from occasional periods of focused attention and accompanying capital expenditure, healthcare facility design and planning has since continued to have a largely low- profile presence in high-level manifesto promises, the NHS Constitution (NHS for England, 2013) (which commits the NHS to ensuring ‘that services are pro- vided in a clean and safe environment that is fit for purpose, based on national best practice’), white papers and subsequent policy implementation initiat- ives (Secretary of State for Health, 2000; Wanless, 2002). Decisions on design strategy for healthcare buildings are rarely of the highest priority for health policy-makers, resulting in the past in somewhat frag- mented and disconnected mechanisms for national healthcare building design quality improvement. This article demonstrates how academics and practitioners can work together to address policy challenges through the ongoing development of design quality strategy.

Healthcare policy and healthcare building strategy have at times enjoyed greater and more explicit synergy, particularly during periods of significant capital expenditure on new buildings. For example, the 1962 ‘Hospital Plan’ aimed to build 90 new hospi- tals, remodel 134 others and provide 356 improve- ment schemes over a 10-year period (Ministry of Health, 1962). This plan was revised in 1966 into the ‘Hospital Building Programme’, followed by the Harness and Nucleus hospital building programmes in the 1970s and 1980s and the Private Finance Initiative (PFI)/Public – Private Partnership (PPP) hospi- tal building schemes of the 1990s and 2000s. The cen- tralized DH-coordinated capital programmes resulted in the prolific development of new standards and tools. These have contributed an evidence and experi- ence base, common benchmarks and level of rigour

Mills et al.

500

 

 

in methodology which is evident from the Health Building Notes (HBNs) developed at the time.

Significant capital building programmes have driven the development of standards, guidance and tools aimed at the successful delivery and achievement of specific quality outcomes. However, the current econ- omic climate makes large-scale national investment programmes unlikely for the foreseeable future. A low rate of new-build replenishment (estimated at less than 4% of the total NHS estate) is an underlying problem. In reality, many existing healthcare buildings suffer from under-investment in maintenance and require significant upgrading (Mills et al., 2015). To deliver success, any healthcare building design quality improvement strategy must acknowledge these realities beyond association with only new-build hospital programmes.

Academic attention has recently focused on the future direction of a more sustainable strategy. For example, research by Lindahl et al. (2010), Phiri, Mills, Chan, and Price (2011) and Mills et al. (2012) has examined healthcare building planning and development of strat- egies for design quality improvement. Barlow and Koberle-Gaise (2008) and Barlow et al. (2011) have investigated the impact of building finance and pro- curement models on healthcare policy. They found that the potential for buildings to accommodate future service change and innovation is restricted by private finance models. Significant within the health- care sector has been the basis of systematic evidence- based knowledge that has supported tool development (Phiri, 2014).

This background suggests a need to re-examine the interrelationships between existing organizations involved in healthcare policy and building design quality improvement, and to take an interdisciplinary approach to evidence-based design. This approach could continue to inform the dynamic relationship between healthcare infrastructure inputs, clinical outputs, patient outcomes and responsibilities shared across actors in the legislative framework (Figure 1).

In 2010/11, the NHS England building portfolio had a capital value of £83 billion (E106 billion) and operat- ing costs of £7.2 billion (E9.2 billion) according to Estates Return Information Collection (ERIC) data (HSCIC, 2015). So significant are these capital and operational resources that design quality improvement should be approached strategically and not be unduly diverted by short-term policy.

Strategy has been described as a means to create a bridge between ‘loose coupled’ organizations (Weick, 1969), such as those which comprise the NHS. This suggests that a national healthcare building design quality improvement strategy should be developed

and supported to address the strengths and weaknesses of possible future scenarios. It may also support the formation of ‘communities of practice’ and create net- works which transcend the boundaries of organiz- ations (Brown & Duguid, 1991, 2001) and so create national (and potential for international) knowledge sharing. Furthermore, a stronger and more cohesive strategy for collecting evidence, experience and learn- ing from best practice will almost certainly improve building quality. Baldwin, Cave, and Lodge (2012) described this type of smart, network-based policy system as involving a mix of institutions and instru- ments, and a move from measuring input alone (such as return on investment) to the evaluation of processes, outputs and outcomes.

Today, centralized responsibility for improving build- ing design quality has been greatly diminished and the quality orientation has narrowed from a broad per- spective of patient satisfaction to prioritizing compli- ance and quality control in terms of safety, suitability and cleanliness (Roberts, 2013). This leaves pro- fessional design institutions (some of which are them- selves threatened by loss of resources) and individual NHS trusts to champion a design-related view of quality and patient experience. Perversely, however, the current opportunities to improve the evidence of design quality are greater than ever. These include harnessing new forms of evidence from big data, data mining and benchmarking, and researching large-scale capital funding programmes using longi- tudinal studies. This article starts to demonstrate how research can create an environment for evi- dence-based strategy.

In recent years, the context of healthcare building safety and design quality in England has moved towards a looser, more distributed model (Mills et al., 2012). This is due to the changed role of the DH. It no longer has a significant role in defining stan- dards, but instead has become a ‘steward’ for good practice. The DH

no longer intends managing estates guidance, placing a significant onus on the estates commu- nity, the associated supply chain, and other healthcare personnel, to formulate and steer such guidance in the future.

(Roberts, 2013, p. 23)

Independent arm’s-length bodies such as the National Institute for Health and Care Excellence (NICE) provide guidance and quality standards, while regula- tors such as the Care Quality Commission (CQC) and Monitor now assume responsibility for quality and safety, but without responsibility for programmes of (continuous) improvement. At the same time, the costs, resources and technical expertise – people, intel- lectual property (IP) and information technology (IT)

Healthcare building design quality strategy

501

 

 

– required to maintain existing healthcare building quality standards have been dispersed under the aus- pices of rationalization, producing some unintended, and as yet poorly understood, consequences. A review by the European Health Property Network (EuHPN) (2010) funded by the DH found that many European Union countries had experienced change in organizational structure from centralized to decentra- lized, or vice versa. As health systems and associated health policy changes, so too must the healthcare design quality improvement strategy, such that it remains adaptive and responsive to these changes.

Method A mixed action and evaluation approach has been taken to answer the question: how can a sustainable national strategy for healthcare building design quality improvement be developed? A longitudinal study combined evaluation interviews and workshops to investigate evidence-based standards and tools (Studies A – D). Direct action research was undertaken to develop new strategic planning tools (Studies E – H). These tools were intended to have ‘a direct and immediate impact’ (Easterby-Smith, Thorpe, & Lowe, 2002). In order to address the research question,

Figure 1 Health building legislative framework for England Source: Department of Health (2014)

Mills et al.

502

 

 

both processes and outcomes were investigated (Langley, 2007; Pettigrew, Woodman, & Cameron, 2001) using a case study method to deal with a wide and complex range of issues (Yin, 2003) and contexts (Langley, 1999). All the studies are defined in Table 1.

An interdisciplinary sample design was applied (strati- fied as in Table 1) using a mix of non-probability sampling techniques. The sample was an expert sample, which focused on representatives from the healthcare property sector (both clients and providers) known for their expertise in relation to building design quality. The participants were also known to the research team (or involved by the steering group through snowball sampling). Some participants had previously been involved in research or had contribu- ted to policy formulation and the development of stan- dards, guidance and tools. There was some selective opportunistic sampling that was driven by the avail- ability and willingness of participants. The application of action research supported the selection of technically expert participants and introduced a greater level of applicability, timeliness and relevance into the research design and supported higher levels of engagement and greater continued access. There was also some level of theoretical sampling applied, commonly used in grounded theory, which sees emergence and theoretical completeness as the purpose of the study.

In order to draw comparisons between studies, the analysis followed basic grounded theory guidelines, using taped and transcribed interviews, coding, memo-writing, and sampling for theory development. This utilized Charmaz’s (2006) ‘flexible guidelines, not methodological rules, recipes and requirements’ (p. 9), and methods and tools to gather rich, detailed and full data in relevant situational and social contexts.

A structured and systematic approach to coding and theme abstraction (Krippendorff 2004; Miles & Huberman, 1994; Strauss & Corbin, 1998) provided the basis for data analysis. To ensure reliability, tran- scriptions were independently evaluated by multiple investigators and validated by a steering group of practitioners.

This approach was appropriate to address the complex healthcare context, characterized by many and varied mixed relationships between organizational structures, strategies, interventions, standards, guidance and tools. In the past, traditional command-and-control arrangements have helped create a purposeful system; however, constrained resources are now forcing change and there is a need to operate within a dynamic system of strategy formation that is respon- sive to potential future scenarios. Three such scenarios (1 – 3) were explored to test these complex interdepen- dencies (Figure 2). These scenarios emerged from the action research and were selected on the basis that

they were plausible, structurally different, overall con- sistent, insightful and challenging (Wilson, 1998, p. 91):

. Scenario 1: Raise awareness of the importance of central government (DH) command and control in driving improvements to healthcare building design quality.

. Scenario 2: Build a shared responsibility for healthcare design quality improvement and inter- disciplinary cooperation amongst stakeholders that acknowledges limited resources and reduced central government (DH) funding and absence of DH command and control.

. Scenario 3: Develop a wider delivery system of quality assurance based on new knowledge gener- ated through externally funded research and its subsequent exploitation.

Scenario 1 represents the situation where all actors involved in a hospital building programme are led by a central, government authority. In this scenario it is perceived as relatively straightforward to identify and commission the correct technical expertise from a wide sample of institutions and develop new approaches that drive excellence in healthcare building quality.

Scenario 2 describes a dispersal of authority and accountability, and a reliance on multiple stakeholders acting for the overall good. This is typical of situations in which no major healthcare building programmes are being undertaken.

Scenario 3 concerns how and why new quality approaches might be developed in the future. Specifi- cally, it focuses on how learning is achieved and incen- tivized through externally funded research and its subsequent exploitation. Critical to this is that quality improvements are made, new tools are devel- oped and customized, and a truly open market enables NHS trusts or commissioning organizations to select providers on the basis of expertise.

Data and ¢ndings Review of existing healthcare building standards and tools In the context of shifting responsibilities for building design strategy and academic focus on how to ensure a sustainable future strategy, this article reports on lessons learnt from a systematic review of Health Building Notes (HBN) standards. This analysis formed part of Study B (Tables 1 and 3). The aim was to characterize the definition and content of these documents and their level of specificity and

Healthcare building design quality strategy

503

 

 

Table 1 Longitudinal study research design as evaluation (i) and direct action research (ii)

Name/date Participants Meeting purpose

(i) Evaluation meetings, interviews and workshops investigating regulation, standards, tools, research and challenges

A.Healthcare Infrastructure Regulatory System and Department of Health Standards and Guidance Review Workshops (March 2009^November 2011)

3 × 3 h. Policy (n ¼ 3), 2 × 3 h. Arm’s-length (n ¼ 3),1 × 5 h. Policy/health planning (n ¼ 5),1 × 5 h. (Policy n ¼ 2, clinical n ¼ 1),1 × 5 h. (Policy n ¼ 3, fund n ¼ 1),1 × 6h.(Policy n ¼ 6,designn ¼ 3, healthcare planning n ¼ 3, tool developer n ¼ 2)

Twelve workshops involving 32 participants from key policy, clinical, funding, regulation and construction supply chain stakeholders. These informed the transformation of the healthcare infrastructure regulatory system and supported the reform of the Department of Health standards and guidance.These meetings investigated existing methods, data and research

B.Tool Review and Exploitation Workshops (April 2009^ November 2011)

1 × 2 h. Contractor (n ¼ 1),1 × 3 h. (n ¼ 3), 2 × 4 h. Policy (n ¼ 2), 2 × 4 h. (Clients n ¼ 1, contractor n ¼ 1, policy n ¼ 2, design n ¼ 3, information and communication technology developer n ¼ 2), 2 × 4 h. Policy (n ¼ 2)

Eight workshops involving17 participants (April 2009^May 2011) with key policy and construction supply chain stakeholders reviewed a sample of existing tools in the policy environment. Reviews of tools included: AEDET/ASPECT/BREEAM and ADB/ TAHPI/Active Plan/BIM.The meetings speci¢cally investigated the exploitability of methods

C.Research Steering Group Workshops (June 2010^ March 2011)

1 × 6h.(Clients n ¼ 2,contractor n ¼ 1, policy n ¼ 4, design/ engineern ¼ 6),1 × 6h.(Policyn ¼ 2, design n ¼ 2, healthcare planning n ¼ 3),1 × 6h.(Policyn ¼ 1, design n ¼ 3, healthcare planning n ¼ 3)

Three steering group workshops with 27 participants (June 2010^ March 2011) with key policy and construction supply chain stakeholders who directed the‘Evidence-Based Learning Environment’ (EBLE) research into the application of EBD and other tools to support learning

D.Technical Specialization and Challenge Workshops (April 2011^May 2011)

1 × 6 h (Policy n ¼ 2, design n ¼ 4), 1 × 6 h (Policy n ¼ 1, design n ¼ 9),1 × 6h(Policy n ¼ 2,designn ¼ 12,NHS client n ¼ 2)

Three challenge-based workshops involving 32 participants (April^ May 2011) tested the implications of (1) elderly, vulnerable, mental health and dementia, (2) recon¢guration/refurbishment and (3) children/third/independent sector provision for the regulatory system.This work aimed to contribute knowledge on how the de¢nition of standards could respond to the uniqueness and complexity of speci¢c user groups, the technical and specialist services di¡erences in clinical conditions, and the impact of building age and private/third sector procurement

(ii) Direct action research to develop new strategic planning tools

E.Tool1Development ^ Strategic Planning (May 2009^November 2010)

Two workshops, ¢ve interdisciplinary case studies and four workshops involving over 182 participants developed Planning Healthcare Infrastructure (PHI), a facilitated approach to support the use of SHAPE

2 × 3 h.Review of SHAPE (n ¼ 31including policy, transport planners, tool developers, healthcare clients, designers).The PHI framework and approach was developed through grounded theory analysis, including multi-stakeholder presentations and observation involving 62 h (n ¼ 32).Baseline data on care, estates and transport were gathered from ¢ve independent case study sites, desk-based reviews, multi-participant memoing and ¢ve multidisciplinary workshops (n ¼ 119).Four scenario-based behavioural simulations on four case studies.SHAPE application case study (20 h) and three 2-h interviews. Link to local transport timeanalysis.Review and modelling of hospital episode statistics

F.Tool 2 Development ^ Strategic Planning (February 2012^January 2013)

Eight workshops and three steering group meetings involving over 77 participants developed the Premises Assurance Model (PAM)

PAM was developed from 3^ 4-h workshops to direct its development (n ¼ 17).Three speci¢c mental health, primary care and acute trust validation workshops (n ¼ 7) plus a Delphi reviews with all participants and seven 5-h workshops with multidisciplinary stakeholders (n ¼ 53)

G.Tool 3 Development ^ Strategic Planning (January 2013^April 2013)

Three workshops and seven interviews with 34 directors of estates and facilities and ¢ve Department of Health representatives

Critical Infrastructure Risk (CIR) was developed from three 2^ 4-h workshops to direct the development of new CIR analytics (n ¼ 17) and detailed analysis of the dynamic situation of trusts’CIR strategies (n ¼ 15).Qualitative interviews with directors of estates and facilities (n ¼ 7) on self-reported backlog maintenance, with a focus on high and signi¢cant risk

H.Tool 4 Development Strategic Planning (November 2009^ on-going)

Eight workshops and four steering groups involving141participants on research into the design of accident and emergency (A&E) using open-scenario planning

A new open scenario planning approach was developed from eight case study workshops (n ¼ 5, 9, 5,14,7, 8, 5 and 7) from seven acute trusts and four steering groups (n ¼ 23,16, 23 and19) from across secondary, primary and mental health

Mills et al.

504

 

 

compliance. The triggers for new standards were many and varied, which may account for variability in their content and structure. Some were developed to respond to changing health policies, while others responded to new technologies, changing economics, catastrophes or legalities and risks. A detailed review of a sample of 17 (at a time when there were 76 HBNs in the DH series) found a mixed quality orien- tation. Most (82%) gave a direct definition of the spatial requirements (e.g. room data sheets and techni- cal space drawings, often defined directly as inputs such as measures of height, distance, volume, etc.). There were also many descriptions of outcomes. Descriptions of clinical processes were rare but were implicit in clinical adjacencies between spaces.

Table 2 shows that many tools were developed in the period 2000 – 09 (69%) and maintained prior to 2009 (69%), but that more recently there has been a complexity in the movement and transition of tools.

For example, the number of formal and informal withdrawals of funding is relatively high (38%) with only a few key risk-based and assurance tools retained (13%) directly by the DH.

Four empirical studies (i.e. A – D, as detailed in Table 3) addressed the evaluation of policy and standards, tools, research, technical specialization and the poten- tial challenges facing healthcare building design quality improvement. These highlighted (1) deficiencies in tool integration and (2) the need for healthcare planning to integrate early decision-making about configuration of clinical services and the scale, scope and distribution of built assets.

Impact of national standards and tools on local outcomes The existing minimum standard design guidance and tools such as HBNs, Health Technical Memoranda

Figure 2 Future national healthcare building design quality improvement scenarios

Figure 3 Refurbished single en suite rooms ^ Rotherham district hospital ward example

Healthcare building design quality strategy

505

 

 

Table 2 Review of national infrastructure planning, design and operation tools (2013 studies)

Tool Reference Contents Development and maintenance Status

20 10

^

20 0 9^

20 0 0

19 9 9^

19 9 0

19 8 9^

19 8 0

19 79

^1 97 0

19 6 9^

19 6 0

W it h d ra w n /n o t c en

tr a lly

su p p o rt e d

R e ta in e d

T h ir d -p a rt y o rg a n iz a ti o n

(c o m m er ci a l/ n o t fo r p ro ¢ t)

R e s ea

rc h a n d d ev

el o p m en

t

DesignTools

Achieving Excellence Design Evaluation Toolkit (AEDET Evolution)

DH (2008c) Functionality, Build Quality,Impact,Use, Access, Space, Performance, Engineering, Construction,Character and Innovation, Form and Materials, Sta¡ and Patient Environment,Urban and Social Integration

× ×

Achieving Excellence Design Evaluation Toolkit (ASPECT)

DH (2008a) Privacy,Company and Dignity,Views, Nature and Outdoors,Comfort and Control, Legibility of Place,Interior Appearance, Facilities, Sta¡

× ×

Achieving Excellence Design Evaluation Toolkit (BREEAM)

BRE (1990) Management, Health and Wellbeing, Energy, Transport,Water,Materials and Waste, Land Use and Ecology and Pollution

× × × ×

Activity DataBase (ADB) DH (2012b) Rooms, Activities, Personnel, Size, Environment, Fittings

× × × × ×

Inspiring Design Excellence and Achievements (IDEAS)

DH (2008b) Exemplars, Database, Places,Geographic Location, Evidence

× × ×

Enquiry by Design (EBD) The Prince’s Foundation for the Built Environment (2008)

Stakeholder Engagement × × ×

Evidence-Based Design EBD

Center for Health Design (1993)

Environment,Outcomes × × × × ×

Operational audits

Path Environment Audit Tool (PEAT)

National Patient Safety Agency

Food,Cleanliness,Infection control, Patient Environment

× × ×

M ills

e t a l.

5 0 6

 

 

Patient-led assessments of the care environment (PLACE)

HSCIC (2013) Privacy and Dignity,Wellbeing, Food, Cleanliness,General Maintenance

× ×

Strategic planning

Strategic Health Asset Planning and Evaluation application (SHAPE)

Public Health England (2008)

Demographic, Public Health,Clinical, Benchmarking, Primary Care, Access, Estate Performance

× × ×

Premises Assurance Model (PAM)

Department of Health (DH) (2012a)

Board Governance, Finance, Safety, Patient Experience and E¡ectiveness

× ×

Risk Adjusted Backlog Methodology

NHS Estates (2004) Risk, Backlog, Elements,Cost,Investment Options, Ranking

× × ×

Planning Healthcare Infrastructure (PHI)

The Prince’s Foundation for the Built Environment, HaCIRIC, et al. (2010)

Demographics,Travel, Public Health,Clinical Planning, Estates,Carbon

× × ×

Commissioning/providing

Scenario Generator NHS Institute for Innovation and Improvement (NHSII) (2006b)

Demographics, Public Health, Primary Care, Service Design, Modelling and Simulation

× ×

Opportunity Locator NHSII (2006a) Commissioning Potential, Shift,Cost, Benchmark

× × ×

Productive Ward NHSII (2011) Ward Design, Sta¡ Movement, Flow, Lean × × Tools (n ¼ 16) 11 (69%) 11 (69%) 3 (19%) 1 (6%) 1 (6%) 0 (0%) 6 (38%) 2 (13%) 9 (56%) 3 (19%)

H ea

lth c a re

b u ild

in g d e s ig n q u a lity

stra te g y

5 0 7

 

 

(HTMs), Mechanical Engineering Specification (MES) and the Activity DataBase (ADB), which drive and define the quality of the healthcare environment, were mostly produced during periods of relatively high capital investment. The findings of Study D (Table 3), a review of the technical specialization and challenge workshops (addressing three critical social, economic and environmental issues identified by an interdisci- plinary steering group), highlighted a shift in emphasis from a focus on new build (i.e. the PFI hospital building programme of the 2000s) to upgrading existing assets to improve standards and reduce running costs, and reconfiguring existing buildings to meet new healthcare delivery models.

There is still a question mark over the current appli- cation of standards, guidance and tools and the impor- tance of their maintenance in periods of limited capital investment. For example, the refurbishment of Rother- ham District Hospital comprised converting 35 beds (five six-bed wards and five single-bed rooms) to a new design that provided a 20-bed ward with eight single rooms and four three-bed rooms. The HBN 04 standard for single rooms, room sizing and the provision of en-suite facilities and nursing station

views was a significant consideration, although the brief provided by the NHS trust and their strategic objectives and patient demands led to a decision that any reduction in the total number of beds was unacceptable. The client and design team decided that both (1) compliance with the national standard and (2) a formal derogation from the DH were not required due to the scale and scope of the works. A relaxed interpretation for the design of the single rooms was applied. A floor area of 12.95 m

2 (3.7 × 3.6 m) was achieved. Whereas the national standard space allowance is 16 m2 (not including the en suite, which at 4.5 m2 complies with HBN 04). The uninten- tional consequence and resulting non-compliance has led to a design solution that may produce a sub- optimal experience for patients and their visitors (Figure 3).

Other examples include Stepping Hill Hospital’s (Stockport) refurbishment of a fourth-floor maternity block. This £1 million conversion was impacted by sig- nificant challenges to convert former wards (nine single rooms with no en suites and five four-bed bays) to four en-suite single rooms and six four-bed bays. The result- ing design provided en-suite rooms but significantly

Table 3 Findings from meetings and interviews investigating regulation, standards, tools, research and challenges (2013,Studies A^D)

Policy challenges overcome by academics and practitioners working together

A.Healthcare Infrastructure Regulatory System and Department of Health Standards and Guidance Review Workshops

Complex mix of regulatory standards, guidance and tools creates a confusing regulatory environment.

Signi¢cant numbers of standards have evolved over many years.Complex mixof risks and a lack of clarity on liabilities, compliance responsibilities and implications of maintenance, gaps and overlaps that may impact on safety, quality and innovation.

Transformation of the regulatory and policy environment has evolved with no understanding of estates and facilities quality and standards, and a need to drive greater awareness of the requirement to retain and grown competencies in this area.

No single healthcare infrastructure quality and safety tool to drive compliance, assurance and prevention.

Lack of information provided to regulators and policy-makers to monitor, report and benchmark premises assurance

B.Tool Review and Exploitation Workshops

A complex and diverse mix of tools is applied di¡erently and with di¡erent structures and contents.Signi¢cant duplication between these tools requires rationalization.Signi¢cant work to map and align these tools allows for rationalization into PAM and so enhanced safety and quality assurance across NHS trusts in practice and supported e⁄cient and e¡ective application.

Limited tool maintenance and development. Analysis of existing tools drove funding for development and so impacts assurance, safety and quality

C.Research Steering Group Workshops

No existing multidisciplinary network to involve researchalongside collaboratorsto inform policy and regulation.

Greater need for accessto evidenceand the creation of a peer network to share thisinformation

D.Technical Specialization and Challenge Workshops

Speci¢c patient groups are not well represented in existing standards and guidance. Impact of cultural values in building design is not well understood. Health outcomes should be understood in healthcare planning to inform operational principles and scale, scope and distribution of estates and facilities.

Di⁄cult to establish guidance for refurbishment as each setting is unique, and there could be a consequence if a lower (suboptimum) performance standard is set to cater for the constraints in dealing with existing buildings.

Sustainability and carbon is increasing in prominence and is supporting the creation of a purposeful system

Mills et al.

508

 

 

compromised the floor area of each room, as shown in Figure 4.

The ‘make do and mend’ approach to healthcare architecture (after the UK Ministry of Information’s Second World War slogan) may well be a practical and sensible response to tight budgets and lower expectations. However, this is not a position that sits well with strategic thinking and planning. Nor does it provide assurance of the quality of outcomes.

Existing national strategy development The direct action research undertaken by the authors in the four empirical studies (E-H) has been described in Table 4. In these studies four new strategic planning tools were established to analyze the geographical access of healthcare buildings, assure building quality, eradicate critical backlog building risk and support scenario planning.

A complex mix of incentives and commercial sensitivities was found. Study E found excellent engagement of tech- nical expertise and the advancement of modelling, including commercial exploitation of research. Perhaps unexpected was the complexity of problems in organiz- ational and collaborative terms. Studies F and G found not only that a significant network could be leveraged by the DH, including tools developed to support a broader and changing policy landscape, but also that under-resourcing and lack of commercial imperative contributed to missed opportunities and fractured relationships. Finally, Study H identified the need for long-term relationships to create an interdisciplinary approach.

Impact of changing healthcare policy and organizational roles Study A (see Table 3) found that recent changes to the landscape of healthcare policy, and the roles assigned to organizations, had affected their ability to formulate strategies to address specific design quality issues. As

the quotation below suggests, NHS trusts and commis- sioning agencies may not understand the changing landscape or appreciate their critical roles and responsibilities:

Cultural and attitude change is definitely an issue [ . . . ] it’s up to an autonomous NHS, its pro- fessional advisors and industry to get together to co-produce [standards . . . ] but it needs to have some branding of a sort that is recognized as being the industry leader, and impartial, and that’s how our guidance is seen. (NHS trust manager)

Command-and-control strategies in the healthcare building design quality system are unlikely, because centralized capital resources are no longer available.

Indirect methods, as in Studies F and G (Table 4), are effective in benchmarking, guiding the system and ‘nudging’ trusts to take action. Tools such as the Pre- mises Assurance Model (PAM) are providing data to arm’s-length regulators and are benchmarking NHS trust spatial efficiency, but have yet to show how healthcare building design quality can be improved over time. Critical Infrastructure Risk (CIR) (Table 1) has demonstrated the risk to HM Treasury (the UK government department responsible for developing and executing public finance and economic policies) of existing NHS assets.

Funding to create and maintain a broad database of guidance and standards (through direct government action and monopolistic public ownership) is thought to be unaffordable due to limited centralized resources. A targeted, manageable set of guidance notes with an active and interdisciplinary peer network is a viable option. One advantage of a more decentralized approach is the strong interdisciplinary relationships and wider institutional contributions critical to the continued development of standards (Study H). This, if well managed, could create greater local learning and innovation.

Figure 4 Refurbished single en suite rooms ^ Stepping Hill hospital,4th £oor maternity block example

Healthcare building design quality strategy

509

 

 

Another well-used strategy is a principle-based regime (through standards, guidance and tools), which defines outcomes but allows some freedom of response. Criti- cisms of such regimes are that they are open to manipu- lation, provide limited protection, and may not detect and allow the correction of poor performance.

Many stakeholders place considerable value on stan- dards because of the centralized approach taken to their development and the implicit assurance provided by central government or authority:

To remove the development of standards from the DH will cost practices like ours [architects] a lot of money. [It is essential not to] lose the arm’s-length body that the DH provides and the political direction/aim.

(Architect)

The same respondent stressed that, while the effects of removing a central authority are not immediately apparent, they will eventually materialize:

What we all know is that if we close the whole lot down tomorrow, it would not dramatically impact on anybody for at least three years.

Also usefully highlighted is the need to understand the rate of change of the content of standards and the trig- gers for change:

Now clearly radiology moves faster than potting sheds, but technology drives change, working practice drives change, and clinical policy and

politics drive change. (Healthcare policy-maker)

In summary, there is significant value in developing and maintaining national standards, and as a conse- quence, centralized resources are required.

Future policy landscape and responsibilities for design quality strategy A variety of institutional and organizational structures are currently in place, as previously described with reference to national, regional and local organizational structures (Figure 1). Given the frequency of change and the use of arm’s-length bodies (such as CQC and Monitor), a mix of institutional types is most probable in the future. Study F (Table 4) illustrates enforced self-/meta-regulation. The interdisciplinary nature of the PAM tool promotes risk sharing and ensures that the outcome is attuned to practice, while two leading institutions utilized a coordinated network for the sharing of information and a community of practice in its adoption. A range of data sets (ERIC, Hospital Episode Statistics (HES)), review processes (Gateway review and Commission for Architecture and the Built Environment (CABE) review) and tools (PEAT, PLACE and PAM) have also been developed to detect poor quality and non-compliance. However, the ‘response’, ‘enforcement’, ‘assessment’ and then ‘modi- fication’ interventions have been deficient, with limited direct checking. Study A (Table 3) found that funders and agencies with oversight of finance and quality indi- cators may check and enforce compliance with a

Table 4 Findings from direct action research to develop new strategic planning tools (2013,Studies E^H)

Policy challenges overcome by academics and practitioners working together

E.Tool1Development ^ Strategic Planning

The customization of tools for a speci¢c context and set of stakeholders requires speci¢c competencies and abilities.

Organizational,commissioningand regionalboundaries make information commerciallysensitiveand unable to be made openly available.

Care, estates and transport data lacks decision-making integration and scenario testing for regional recon¢guration (scale, scope and distribution).

Terms of collaboration and commercialization must be pre-agreed. Data collection is complex and advanced visualization with a clear framework for decision-making is needed.

F.Tool 2 Development ^ Strategic Planning

A changing political, regulatory and organizational landscape limited the position of the tool within a policy system.

Limited resources restricted the usability of the tool. No commercial agenda and limited investment beyond that of the Department of Health. Lack of long-term relationship management so research and development streams were fractured

G.Tool 3 Development ^ Strategic Planning

Limited commercial imperative, so lack of investment in tool development. Split between parties, with an alternative data set not integrated into the whole. Development threatened by third-party commercial interests. Under development of advanced and world-leading predictive-analytics solution.

H.Tool 4 Development ^ Strategic Planning

Exploitable idea has been provided to third party. Missed opportunity for a joined-up approach. Monopolization by lead commercial organization jeopardizes quality and restricts the involvement of experts. Lack of long-term relationship management so research and development streams are fractured. Confusion andcontractualintellectual property disagreements and lackof acknowledgement of contributions

Mills et al.

510

 

 

relatively narrow set of project-by-project measures, without a wider view or vital evidence checking across a series of projects or with those in other sectors:

because merchant bankers are probably risk- averse people, slavish adherence to standards which [may be outdated . . . ] so, everybody is comfortable that no one can be in trouble, but is it delivering what we really need? Is it cutting edge?

(Healthcare policy-maker)

The approach to standards and guidance currently in place to direct healthcare building design quality improvement lacks rigour. Until recently, preventative action was taken in the form of standards and guidance (e.g. measures to prevent or mitigate against cata- strophic danger and major reactive resource uses). This is no longer an option because almost all these standards have now been archived and replaced with harm- and act-based actions – specifically those devel- oped by the CQC, Monitor and the Health and Safety Executive (HSE), which inspect compliance with stan- dards, health and safety, and risk. An interview in Study A found a lack of expertise to judge building quality, despite expert technical support from pro- fessional institutions. Without the coordinating role of the DH, pressure to adopt a smart and interdisciplin- ary approach is put on others:

It is the approval process that sits behind these standards that is very important. This requires going to every clinical college to get sign off and buy in [ . . . it must be] inviting, it must allow anyone to feed into the process who wants to in the first group; however, the critical thing is [ . . . ] peer review.

Alongside some of these very instrumental things there is a network of people that are challenging and promulgating. It is the network that is most important, rather than the development of the standards – which does have a home alongside political change.

(NHS Trust Capital Development Manager)

As a consequence of political and structural change, the transition from one system to another is problematic:

DH are moving towards simpler accountability, but you are not making everything simpler – actually harder for clients, who will be involved in huge costly debates, which extend the time that it takes to have a hospital designed and built.

(Leading healthcare architect)

All this may suggest that much more work is required to develop a system that overcomes complexity and fragmentation during transition. It also indicates that

existing strong, open and interdisciplinary relation- ships will form a good starting point.

Existing tools as a vehicle for policy transformation Tools play a vital role in supporting a healthcare building design quality improvement system (Table 2). Some tools measure generic outcomes (e.g. AEDET and ASPECT), with no formalized mechanism to bench- mark quality centrally, while others are unresponsive to feedback and change. One tool (ADB) that facilitates a detailed and technical orientation to space (inputs) has been maintained for over 40 years but now suffers from a lack of development and investment to update data, frameworks and software. A stimulated open market (with customized software) would allow com- parability, consistency and standardization.

Other tools have facilitated the wide-scale capture and maintenance of a robust and academic knowledge base. Evidence-based design (EBD) connects structural and process measures of the estate with patient/staff outcomes (Lawson & Phiri, 2003). It indicates how the designed estate may impact on outputs such as length of hospital stay, trips and falls, rates of cross- infection, medical/medication errors, consumption of medication, as well as other detailed measures of heart rates, sleep patterns, staff absenteeism and the like. There are also links to qualitative outcome measures such as patient satisfaction and staff recruit- ment and retention. The advantage of these databases is that they are scientifically credible and, when kept up to date, stimulate continuous quality improvement.

Study C contributed directly to developing an evidence base, and supported access and peer feedback. Another example of an open systems approach has been design reviews facilitated by panels providing independent advice, such as the NHS Design Review Panel (DRP), the Gateway Review and the CABE Design Review (now managed by the Design Council). Strategic Health Asset Planning and Evaluation (SHAPE), which supports the strategic planning of services and physical assets across a whole health economy, is another example of an open system. Supported by a geographic information system (GIS), it combines benchmarks of existing national data sets of clinical activity, human geography and healthcare estates assets. Planning Healthcare Infrastructure (PHI), a methodology devised to facilitate wider stakeholder involvement in healthcare planning (Study E), has the potential to make this approach more flexible and usable, and the feedback more direct.

PAM is another open approach that allows process, output and outcomes to be benchmarked across NHS trusts. Advances in modelling and simulation are uti- lized in Scenario Generator, Opportunity Locator and the Productive Ward. Such tools are designed for

Healthcare building design quality strategy

511

 

 

use by experts, not novices. For example, Scenario Generator compares population and prevalence data (outcome data), cost (inputs) and activity (outputs) for generic pathways of care (mental health, urgent, planned and unplanned care). However, lack of techni- cal expertise and significant cost often mean that these are closed system approaches. Others, such as Building Research Establishment Environmental Assessment Method (BREEAM) and Design Quality Indicator (DQI) for Health (superseding AEDET Evolution) are commercially applied (for a fee) by an open system of trained technical experts, while other more commer- cially exploited tools may deliberately take a closed (black box) approach to protect IP and market pos- ition. Both closed and open approaches exist, with open systems offering the greatest opportunity for interdisciplinary integration and continuous whole- system learning.

Discussion The evidence emerging from action research suggests that there is a need for a strategy to address the future of national healthcare building design quality improvement. This section identifies three scenarios that could improve communication, create a common language for learning and put in place a roadmap for strategic conversations within and between organiz- ations (van der Heijden, 1996).

Scenario1: Raise awareness of the importance of central DH command and control in driving healthcare building design quality All studies A – H found that the centralized functional role performed by DH has had a significant impact on learning, has created open feedback loops, has reduced duplication, has created economies of scale and scope, and has almost certainly improved the quality of out- comes while mitigating failure.

With regard to development of standards such as HBNs, the successful outcome of Study H suggests that an inter- disciplinary peer network led by a clinical champion and supported by academics and practitioners should be used. But, perhaps most importantly this network must have the ability to innovate. This prompts oppor- tunism that must be managed to ensure that individual incentives for innovation are balanced against long- term whole-system learning. Strategy is a bridge that builds sense between organizations and individuals and combines interdisciplinary systems (Weick, 1969). Interdisciplinary peer networks must therefore have freedom to incentivize the creation of ‘communities of practice’ between professional networks which trans- cend the boundaries of organizations (Brown & Duguid, 1991, 2001), with the skills to build (Weick, 1969) and make sense (Gioia & Chittipeddi, 1991).

An important question with regard to the maintenance or wholesale transfer of existing standards is whether organizations other than DH have the credibility to maintain interdisciplinary networks and the ability to incentivize innovative relationships. From the authors’ experience in creating and maintaining such standards, the answer is quite often that they cannot. Rather, it is the skill of key individuals and the avail- ability of unique and agile skills sets that will drive quality development in this case. This is best initiated by DH, if only in part, and maintained by key credible individuals with interdisciplinary expertise in bridging and building sense between diverse specialities. The credibility and breadth of the resulting interdisciplinary representative network should prohibit the dominance of any single organization, and ensure deeper creative and critical reflection (Argyris & Schön, 1978).

Scenario 2: Build shared responsibility and interdisciplinary cooperation amongst stakeholders This scenario is concerned with the alignment of incen- tives and expertise in the development of hospital building design quality strategy. It specifically acknowl- edges the limited resources and reduced DH or central government funding. Study F identified the important role of accredited engineering institutions in attracting networks of professionals within an accreditation structure. These institutions seem to have been more stable than those within the policy landscape. Their involvement in shaping policy is important; however, without DH direction, arbitration and whole policy system championing, it is likely that clinical engage- ment may wane, monopolies may start to form and the purpose of the systems may erode.

Study G demonstrated that interdisciplinary sharing of accurate benchmarks may encourage appropriate devel- opment. However, there is a difficult tension. From a commercial viewpoint, Dale, Wiele, and Iwaarden (2007) describe the ultimate purpose of a firm as to become the ‘supplier of choice’ and to ‘lock’ themselves into their customers’ mode of operation by becoming their ‘sole supplier’. This is in opposition to the view of policy-makers, who see this as impacting on ‘contest- ability’ and ‘value for money’, so any new system must prevent ‘cream-skimming’, ‘anti-competitive’ and ‘mon- opoly’ behaviours (Baldwin et al., 2012). A wholly self- regulated system deals less directly with this tension.

Previously, IP was owned solely by the Crown (i.e. central government), but this position is no longer an option, with a greater need for flexible co-creation of value (Mont & Lindhqvist, 2003) and open source publication. The relationship between stakeholders requires expertise in bridging knowledge domains, building sense and meshing technical competencies. This requires moving beyond an economic and top- down model to a new paradigm in which the

Mills et al.

512

 

 

system’s ultimate goal is to serve patients (by meeting clinicians’ expectations). Study H demonstrates a way in which this could be achieved. At an individual level, participants must be engaged and motivated by economic, social and psychological policy goals relat- ing to personal fulfilment and must be directly recog- nized for their contributions. Studies E – H exhibited both successes and failures in this regard.

In terms of driving continuous learning, innovation and dynamic improvement, Study H demonstrates that this can be achieved through an open system of feedback – a system that trusts the judgement of experts, facilitates interdisciplinary working and places no expectation on static and optimized input, process, output or outcome alone. This supports Lang- ley’s (2007) proposal to investigate ‘outcomes as inputs’, continually monitor change and ‘not forget outcomes are often rather artificial staging points amid never-ending processes’ (p. 7).

Scenario 3: Develop a wider delivery system of quality assurance based on new knowledge generated through externally funded research and its subsequent exploitation Previously, the DH has been successful in providing the seed-corn investment to ‘nudge’ tool development (Baldwin et al., 2012) without dis-beneficial market monopolization. This precedent makes for a dynamic and changing landscape of quality management tools, with some being formally or informally withdrawn, some transferred between organizations, and others undergoing research and development (Table 2). Resources must therefore be provided to manage such a portfolio of tools, which also requires greater expertise in managing IP, open-source development and commercial acumen than was the case in the past. Different models of funding may support inno- vation by promoting the spread of knowledge beyond existing silos into the next generation of talented pro- fessionals. However, in order to motivate and incenti- vize innovation, recognition of organizational and individual efforts is essential. Paying greater attention to managing IP would lead to new exploitation and greater demonstration of impact.

All studies (A – G) found that while strong relationships are difficult to formulate and maintain over a long period, specific individuals with specialist expertise are highly motivated to hold together strong interdisci- plinary networks and develop both evidence and expertise with relatively small financial incentives.

With few centralized resources to develop new design quality approaches, new forms of relationship are needed, in addition to the seed-corn funding of research and innovation and the generation of alterna- tive revenue streams, for example, commercial tool

development and licensing or the joining up of various research funding organizations

Conclusions and recommendations As clinical and scientific practices develop and evolve, it is imperative to have an emerging strategy for healthcare facilities to develop a healthcare build- ing design quality strategy that spans changing incom- ing governments. The existing healthcare design quality system has been successful in delivering a mix of regulatory strategies combining command-and- control, incentive-based, market-harnessed and design action. However, the role of standards and guidance and the recognition of key roles have been affected by a period of major structural change. There are clear opportunities now for meta- and self-regulation regimes and a mix of interventions, tools and networks that will reduce the burden of rewriting standards, acknowledge individual con- tributions (and so build a reputation for ongoing business development) and create a wider ownership of building design quality standards throughout the supply chain. Comparison with other countries in the European Union and Australia shows that many strategies for design quality improvement are similarly disrupted (EuHPN, 2010). England has an active network of interdisciplinary contributors which

Using the Internet, research the two major study designs–cohort and case-control–used in health care research

Using the Internet, research the two major study designs–cohort and case-control–used in health care research. Find a research article on any topic in health care. Based on your research, please address the following:

  • Although cohort studies are very powerful, case-control studies tend to be more popular. Do you agree with the statement? Why or why not?
  • How does the cohort study design differ from the case-control study design?
  • What is essentially the main use or purpose of the cohort study design and case-control study design?
  • When it is best to use the cohort study design and when is it best to use the case-control study design?
  • What characteristics of cohort study design make it important in health care research?
  • Cohort studies can be retrospective or prospective. What makes a cohort study retrospective or prospective?

 As in all assignments, cite your sources in your work and provide references for the citations in APA format.

Your initial posting should be addressed at 150-300 words. Submit your document to this Discussion Area by the due date assigned . Be sure to cite your sources using APA format.

The discussion assignment provides a forum for discussing relevant topics for this week based on the course competencies covered.

The discussion assignment provides a forum for discussing relevant topics for this week based on the course competencies covered.

For this assignment, make sure you post your initial response to the Discussion Area by the due date assigned.

To support your work, use your course and text readings and also use outside sources. As in all assignments, cite your sources in your work and provide references for the citations in APA format.

Start reviewing and responding to the postings of your classmates as early in the week as possible. Respond to at least two of your classmates. Participate in the discussion by asking a question, providing a statement of clarification, providing a point of view with a rationale, challenging an aspect of the discussion, or indicating a relationship between two or more lines of reasoning in the discussion. Complete your participation for this assignment by the end of the week.

Structure of Health Insurance

The present health care system relies on public and private health insurance systems. On the basis of your understanding of the health insurance system, answer the following questions:

  • Explain the basic structure of health insurance and analyze its most important part. Describe the main purpose of health insurance in your own words.
  • What impact do you think health insurance has on our economy today?
  • Explain why managed care was incorporated in the US health care system long ago? Describe and contrast the three types of managed care plans—HMOs, PPOs, and POS?.
  • Should the same individuals who pay for your health care (managed care organizations [MCOs]) also make your treatment decisions? Why or why not?
  • Is the fee-for-service (FFS) system more beneficial for the consumer than the current MCO system? Why or why not? Explain.

Your Practicum and Evidence-Based Interventions

Your Practicum and Evidence-Based Interventions

Over the past decade, research has identified evidence-based programs, strategies, and interventions that are useful in attaining community health goals and improving overall health outcomes for a population. Such examples include safety belt use, physical activity, improved nutrition education, and safe sex practices. Think about evidence-based interventions you have studied or seen through your practicum experience or professional practice:

  • Where do you see a gap in evidence-based interventions in a specific population? Provide and cite evidence to show that this gap exists.
  • Cite literature that explains the social injustice or existing systems that cause or maintain this gap.
  • How could existing systems be changed, or which system could be developed to support a change to close this gap? How might you address it? Provide and cite evidence to show that your suggested approach could be successful in addressing the gap.
  • What potential problems do you see with your suggested approach? What additional information would you need to answer this question more thoroughly?

Public Health Competencies Self-Reflection Paper

The Public Health Competencies Self-Reflection Paper is the last assignment that you will save in your ePortfolio this quarter. In practice-immersion learning, you are both a participant and observer; as a participant, you will be contributing to the organization in which you are completing your practicum and learning new skills. But this is not what makes the experience worthy of academic credit; rather, it is the development of your ability to systematically observe what is going on around you and apply the course competencies. A well-written reflection is a tool that helps you practice moving quickly from your working environment to the didactic curriculum and theories you have learned over the course of your MPH program.

Instructions

First, review the six course competencies carefully. Reflect on the past nine weeks at your practicum site, study of the activities, and projects you have worked on during your practicum, and consider how you have grown as a scholar and practitioner in the public health field.

  1. Discuss the public health needs and capacities of the population served by your practicum agency.
    • Define public health needs and capacities.
  2. Discuss how you have applied a socioecological framework to the development of population-based intervention strategies to improve health and reduce inequities for the population you are serving.
    • Define the ecological framework.
    • Describe how you would apply an ecological framework to the development and implementation of population-based interventions.
  3. Analyze the insights gained concerning gender, race, poverty, history, migration, and culture when working toward health equity at organizational, community, and societal levels.
    • Discuss how these determinants undermine health and create challenges.
    • Discuss inclusive ways to achieve health equity at organizational, community, and societal levels.
  4. Differentiate among availability, acceptability, and accessibility of health care across diverse populations.
    • Describe how the population your agency serves is accessing health care and services, accepting the services available, and is willing to make behavioral changes.
    • Describe potential ways to improve the current state.
  5. Compare your practicum agency to other agencies in terms of structure, systems, and public health practices.
    • Define the agency structure, systems, and public health practices.
    • Provide examples of the agency structure, systems, and public health practices.
  6. Explain how professional ethics and practices relate to equity and accountability in diverse community settings.
    • Discuss how your own professional ethics have helped improve health equity for the populations served at your practicum site.
    • Identify ways to improve your knowledge, ethics, and practices to better serve diverse communities and populations.
  7. Analyze the systems-thinking or building tools you have used at your practicum site.
    • Define systems-thinking or building tools.
    • Describe how you have employed these tools to influence the community’s health behaviors to address health disparities or public health concerns.
    • Describe other tools you would like to use.
    • Describe how use of these tools would benefit the community.
  8. Write following APA style for in-text citations and references.
    • Determine the proper application of APA formatting requirements and scholarly writing standards.
    • Apply the principles of effective composition.
    • Describe any professional and scholarly resources, primarily peer-reviewed journal articles, government Web sites, and experiences gained in the practicum.
  9. Write clearly and logically with correct use of spelling and grammar.
    • Determine the proper application of the rules of grammar and mechanics.
    • Assess the relevance and credibility of information sources.

Remember that your instructor will be providing feedback on your assignments.

Additional Requirements

  • Written communication: Written communication is free of errors that detract from the overall message.
  • APA formatting: Resources and citations are formatted according to current APA style and formatting standards.
  • Cited resources: Minimum of three scholarly sources that relate to your professional experiences, points and/or course competencies. All literature cited should be current, with publication dates within the past five years.
  • Length of paper: 8–10 double-spaced pages.

American Journal of Public Health Myers

American Journal of Public Health Myers et al. | Peer Reviewed | Research and Practice | 685

 RESEARCH AND PRACTICE 

Objectives. We evaluated the association between ecological factors and rates of tuberculosis within California, using pediatric tuberculosis as an indicator of new transmission.

Methods. Ecological variables such as racial/ethnic distribution, immigration level, education, employment, poverty, and crowding were obtained from the United States Census for each census tract in California. These data were incor- porated into a negative binomial regression model with the rate of pediatric tu- berculosis disease in each census tract as an outcome variable. Disease rates were obtained by geocoding reported cases. Subsections of the state (San Fran- cisco and Los Angeles) were examined independently.

Results. Census tracts with lower median incomes, more racial/ethnic minorities, and more immigrants had higher rates of pediatric tuberculosis. Other frequently cited risk factors such as overcrowding and unemployment were not associated with increased disease after adjusting for other measures. Risks were compara- ble across regions, but subtle differences were noted.

Conclusions. The techniques used in this work provide a way to examine a dis- ease within its social context. The results confirmed that tuberculosis in California continues to be a disease of poverty and racial/ethnic minorities. (Am J Public Health. 2006;96:685–690. doi:10.2105/AJPH.2004.048132)

An Ecological Study of Tuberculosis Transmission in California | Ward P. Myers, MD, MPH, Janice L. Westenhouse, MPH, Jennifer Flood, MD, MPH, and Lee W. Riley, MD

Tuberculosis is a social disease caused by an airborne pathogen with low infectivity. The transmission of tuberculosis depends on human interaction within communities. However, some communities provide a better environment for disease transmission than others. Previous sur- veillance has documented great disparities in rates of tuberculosis among neighborhoods.1

These differences depended in part on commu- nity-level, ecological risk factors that facilitate transmission—poverty, crowding, and other markers of deprivation have long been associ- ated with increased rates of tuberculosis.2,3

Because of its airborne transmission and soci- etal impact, tuberculosis is closely monitored by local, state, and federal health departments. Cases of tuberculosis are subject to mandatory reporting in all 50 states, the District of Colum- bia, US dependencies and possessions, and inde- pendent nations within the United States (Native American lands).4 In addition to ensuring treat- ment, health departments collect case-specific demographic information (e.g., age, race, for- eign-born status) and disease information (e.g., site of infection, drug resistance).5 The focus on individual cases, however, neglects the ecologi- cal context of this disease. Information about community-level, ecological risk factors for con- tracting tuberculosis is important for structuring a public health response to this illness.

Ecological data can be obtained by geocod- ing addresses from reported cases, and then linking these cases to geographic locations such as the census tract. The US Census defines a census tract as a “small, relatively permanent statistical subdivision of a county . . . designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions at the time of establish- ment. Census tracts average about 4000 inhab- itants.”6 Every 10 years the US Census collects detailed demographic and socioeconomic infor- mation about the US population. When linked to reported tuberculosis cases, this information permits the examination of ecological factors

that are associated with disease. Use of the cen- sus tract has many advantages over the use of other geographic units such as zip codes. Previ- ous work has shown that populations defined by zip codes, being larger and more heteroge- neous, give more variable results than census tracts in ecological analysis.7

Ecological analysis of tuberculosis is compli- cated by the disease’s long incubation period. A delay of 30 years or more between infection and clinical disease has been documented,8

bringing into question the validity of studies comparing current ecological data to case re- ports from adults. Cases of tuberculosis in chil- dren, compared with cases in adults, have a short delay between infection and onset of clin- ical disease. The incubation period is limited by the child’s lifespan and, thus, a greater propor- tion of cases are likely to be primary disease. Cases occurring in children represent recently acquired infection and serve as a surrogate marker for ongoing transmission. For this rea- son, tuberculosis cases in children are used by state and local health departments to monitor the success of tuberculosis-control activities.

Recent studies have supported the role of ecological risk factors, such as poverty, lack of social capital, and overcrowding, in tuberculosis disease.1,7,9–15 Although these studies have used a variety of techniques, there are limited data using exclusively pediatric cases to look at eco- logical risks for tuberculosis.16 In this work, we developed a multivariate model for prediction of tuberculosis transmission on the basis of eco- logical measures and pediatric cases from cen- sus tracts in the state of California. Data from California are particularly useful for under- standing tuberculosis in the United States. In 2002, California reported 3159 cases of tuber- culosis, or 21% of the national total.4 Further- more, much of the United States is now begin- ning demographic and ethnic shifts that mirror the changes that have occurred in California over the past 10 years.

METHODS

Data Collection: Tuberculosis Cases Case information was obtained from the

California Department of Health Services,

 

 

American Journal of Public Health | April 2006, Vol 96, No. 4686 | Research and Practice | Peer Reviewed | Myers et al.

 RESEARCH AND PRACTICE 

TABLE 1—Ecological Measures Derived From Year 2000 US Census Tract Data

Summary Census Measure Operational Definition File Variable

Demographic

Asian race Percentage of population in census tract that self-reports Asian 1 P4

race (1 race only, non-Hispanic)

Black race Percentage of population in census tract that self-reports black 1 P4

race (1 race only, non-Hispanic)

Hispanic ethnicity Percentage of population in census tract that self-reports 1 P4

Hispanic ethnicity

Immigration Percentage of population that was born outside the United States 3 P21

Education: Low attainment Percentage of persons 25 years and older with less than a 3 P37

high-school diploma

Occupation: Unemployment Percentage of persons aged 16 and older in the labor force who 3 P43

are unemployed

Economy: Median income Median household income for census tract in 1999 3 P53

Housing

Crowded households Percentage of households with > 1 person per room 3 H20

Population density Number of people per square mile 1 P1

Note. P = population subjects; H = housing subjects.

TABLE 2—Descriptive Characteristics of 7018 Census Tracts in Californiaa

Variable Mean SD Range

Total population per census tract 4819.7 2129.8 3–36 146

Pediatric (0–14 years) population 1109.1 662.8 1–7962

Cases of TB aged 0–14 years from 1993–2002 0.5 1.0 0–15

Pediatric case rate (per 100 000 person-years) 3.8 9.0 0–230

Asian race, % 10.6 12.9 0–95

Black race, % 6.4 11.4 0–91

Hispanic ethnicity, % 31.0 25.5 0–98

Foreign born, % 25.5 16.1 0–100

Lower educated, % 24.4 19.3 0–100

Unemployed, % 7.4 5.6 0–100

Median household income, $ 51 615.7 24 685.4 0–200 001

Living in crowded housing, % 16.9 16.5 0–100

Population density (people/square mile) 8064.3 9205.1 0–156 015

Note. TB = tuberculosis; SD = standard deviation. aCalifornia has 7049 census tracts. Prior to analysis, 31 tracts were excluded because their pediatric population was 0. No TB cases were present in the excluded census tracts.

Tuberculosis Control Branch. We analyzed all 3208 cases of tuberculosis in children aged 0 to 14 years that were reported in the 10 years between January 1, 1993, and December 31, 2002. The cases were geocoded, and each case was linked to a census tract from the 2000 US Census. A census tract number was available for 3164 cases (98.6% of total). Use

of nonidentifying case information was ap- proved by the California Department of Health Services, Tuberculosis Control Branch. Tuber- culosis case rates per 100 000 person-years were calculated on the basis of populations from the 2000 Census.

The analysis was repeated, limiting tubercu- losis cases to children aged 0 to 4 years. As this

approach yielded similar results, the final analy- sis used cases in patients aged 0 to 14 years.

Data Collection: Ecological Measures Ecological measures were obtained from the

2000 US Census Web site.17,18 Individual vari- ables were selected from summary files 1 and 3 (Table 1). Prior to analysis, variables were chosen that characterized traditional risk fac- tors for transmission of tuberculosis.

Means and standard distributions for predic- tor variables were calculated for all included census tracts and are reported in Table 2. Vari- ables were standardized to a z scale on the basis of their mean and standard deviation ([X – mean] / SD). This standardization of vari- ability permitted the generation of tuberculosis incidence rate ratios that could be compared among ecological measures (e.g., how does the incidence rate change for a 1-standard-devia- tion increase in population density, compared with a 1-standard-deviation increase in percent- age of residents in poverty?).

Statistical Analysis The number of pediatric cases for each cen-

sus tract was modeled as a negative binomial distribution. In contrast to the Poisson distribu- tion, a negative binomial distribution does not assume that the variance equals the mean and allows for more zero counts and overdisper- sion.19 Therefore, it is a useful model when the variance of a population exceeds the mean. In this analysis, the model took the form of

log λi = β0 + β1xi 1 + β2x i 2 + . . . + βk x ik + σε + log ( popi )

for each census tract [i = 1, . . . 7018], where λ is the expected cases in each census tract, xj is each standardized ecological measure (with its associated βj regression coefficient), σε is the disturbance or error term, and pop is the 2000 population (age 0–14) in the census tract times the years exposed (times 10, for time exposed). The log( popi ) term has no re- gression coefficient because it serves as an offset (log λi – log( popi ) = log [case ratei ]). The σε term represents error and dispersion in the form of a negative binomial distribu- tion. The exponent of each βj regression coef- ficient provides the incidence rate ratio for a

 

 

April 2006, Vol 96, No. 4 | American Journal of Public Health Myers et al. | Peer Reviewed | Research and Practice | 687

 RESEARCH AND PRACTICE 

TABLE 3—Univariate and Multivariate Incidence Rate Ratios for Pediatric Tuberculosis and Selected Ecological Measures in the State of Californiaa

Univariate Analysis Intermediate Model Full Multivariate Analysis US-Born Stratum Only

Area-based measure IRR 95% CI IRR 95% CI IRR 95% CI IRR 95% CI

Asian race 1.08 (1.04, 1.13) 1.22 (1.14, 1.30) 1.18 (1.08, 1.28)

Black race 1.21 (1.17, 1.24) 1.19 (1.14, 1.23) 1.27 (1.22, 1.33)d

Hispanic ethnicity 1.56 (1.51, 1.62) 1.25 (1.12, 1.40) 1.38 (1.2, 1.58)

Foreign born 1.65 (1.59, 1.71) 1.26 (1.14, 1.40) 1.26 (1.11, 1.44)

Lower educated 1.67 (1.62, 1.73) 1.13 (1.01, 1.27) 1.12 (0.99, 1.27)c 1.13 (0.96, 1.32)

Unemployed 1.44 (1.40, 1.48) 1.04 (0.99, 1.10) 1.02 (0.97, 1.08)c 0.97 (0.9, 1.04)

Median incomeb 2.25 (2.11, 2.40) 1.55 (1.42, 1.70) 1.62 (1.48, 1.78) 1.75 (1.55, 1.97)

Crowded housing 1.59 (1.54, 1.64) 1.16 (1.05, 1.28) 0.87 (0.77, 0.98)c 0.81 (0.7, 0.93)

Population density 1.32 (1.28, 1.35) 1.07 (1.03, 1.12) 1 (0.95, 1.04)c 1 (0.95, 1.06)

Note. IRR = incidence rate ratio; CI = confidence interval. aIRRs reflect the change in the incidence rate that occurs when the area-based measure increases by 1 standard deviation. The multivariate analysis holds all other variables constant. bStandardized values for median income are inverted. IRR shows change for a 1-standard-deviation decrease in median income. cFour variables showed a loss of significance as a risk factor or changed to a mildly protective factor in the model that included all variables. d The IRR for 1 variable in the US-born stratum was outside the 95% confidence intervals for the full multivariate analysis model.

1-standard-deviation change in the correspon- ding ecological measure.

Each ecological measure was initially exam- ined alone and then as a part of a multivariate model with the other measures. To better un- derstand the loss of significance for many socio- economic variables in the full model, we ana- lyzed an intermediate multivariate model (without race, ethnicity, or immigration). Inci- dence rate ratios with 95% confidence inter- vals for each measure are reported in Table 3. The multivariate model is reported in full. All variables were selected prior to analysis, and none were eliminated.

To assess goodness of fit, deviance residuals were calculated for the multivariate negative bi- nomial model with constant dispersion. Greater than 99% of predicted standardized deviances fell within 2 standard deviations, signifying a very good fit.20 We also modeled the data using a Poisson distribution. Goodness of fit for the Poisson model, however, was poor (P < .01). Because additional evidence that the negative binomial model was more appropriate than the Poisson, the likelihood ratio test for dispersion parameter being equal to 0 (in the Poisson model, dispersion parameter equals zero) was P < .001. To assess the extent to which the population adjustment factor (log[popi ]) might explain the goodness of fit, a correlation coeffi- cient with the number of tuberculosis cases was

calculated (r 2 = 0.1). This value was significant (in part because of the larger number of census tracts), but was also too close to the null to solely explain the model’s goodness of fit.

To reduce error from the inclusion of tuber- culosis cases representing transmission that oc- curred outside the United States, a stratified analysis was also performed on the basis of country of origin. Analysis was repeated as in the full multivariate model, but the dependent variable included only cases in children born in the United States from each census tract. Inci- dence rate ratios and 95% confidence intervals for the stratum of cases in children born in the United States are reported in Table 3.

To allow the greater San Francisco and Los Angeles areas to vary independently from each other and the rest of the state, indicator vari- ables were created for corresponding metropol- itan statistical areas. The US Census defines a Metropolitan Statistical Area (MSA) as “a core area with a large population nucleus, plus adja- cent communities having a high degree of eco- nomic and social integration with that core.”21

Lists of counties and census tracts included in the Los Angeles and San Francisco MSAs are available from the US Census Web site.21

To compare differences in the predictive powers of ecological measures between the San Francisco and Los Angeles MSAs, an additional model was generated. This model included

cross-products that allowed coefficients for eco- logical measures from the 2 MSAs to vary in- dependently. For clarity, cross-products that were less significant than P = .05 were removed by backward elimination. The results are de- picted in Figure 1.

All analyses were conducted using Stata, Version 7.0 (Stata Corp, College Station, Tex).

RESULTS

Over the 10 years included in this study, Cal- ifornia had 3208 cases of tuberculosis in its pe- diatric population. On the basis of the 2000 census, there were 7.78 million individuals aged 0 to 14 years, yielding a crude incidence rate of 4.1 cases per 100 000 person-years. Individual census tracts, however, showed very divergent rates. Incidence rates ranged from 0 to 230 per 100 000 person-years.

Results of univariate, intermediate, multivari- ate, and stratified models are depicted in Table 3. In the univariate models, the tradi- tional ecological measures were all strongly as- sociated with pediatric tuberculosis. However, when the variables were combined into a single multivariate model, measures such as lower ed- ucation, unemployment, crowding, and popula- tion density became less predictive. Census tracts with lower median incomes and more ra- cial/ethnic minorities and foreign-born individ- uals were particularly likely to have increased rates of disease when the other variables were held constant. Notably, Asian race appeared to be a greater risk factor in the multivariate model than in the univariate model, and crowded housing became a mildly protective factor in the multivariate model.

The intermediate model suggested that much of the loss of significance for lower education, unemployment, crowding, and population den- sity was attributable to each factor’s collinearity with income. The incidence rate ratios in Table 3 are best conceptualized as changes to a hypothetical “average census tract.” This aver- age census tract is characterized by the ecologi- cal measures shown in Table 2. As the percent- age of foreign-born residents increases to 1 standard deviation above the average census tract (approximately from 26% to 42%) the in- cidence of pediatric tuberculosis would be ex- pected to increase 1.3-fold (assuming all other variables were held constant).

 

 

American Journal of Public Health | April 2006, Vol 96, No. 4688 | Research and Practice | Peer Reviewed | Myers et al.

 RESEARCH AND PRACTICE 

Note. Incidence rate ratios reflect the change in the incidence rate that occurs when the area-based measure increases by 1 standard deviation. Standardized values for median income are inverted. Incidence rate ratio shows change for a 1-standard- deviation decrease in median income.

FIGURE 1—Regional differences in incidence rate ratios for pediatric tuberculosis and ecologic variables, by race/ethnicity (a) and sociodemographic variables (b).

Differences between the US-born stratum and the full multivariate analysis were small but informative. Compared with the full model, census tracts with more Blacks showed an in- creased risk of disease. Additionally, Asian race seemed less strongly correlated (but still signifi- cant), and income became a slightly stronger risk factor.

Figure 1 depicts incidence rates for pedi- atric tuberculosis that were allowed to vary

independently across regions (i.e., other Cali- fornia [i.e., San Diego, Sacramento, Arcata, and so on], Los Angeles, San Francisco). For many ecological measures, the effects on incidence rates in the different regions were the same. Notable exceptions included differences in the effect of race/ethnicity, unemployment, and population density. In adjusted analysis, San Francisco–area census tracts with more Black residents had higher rates of tuberculosis

than equivalent census tracts in the rest of Cal- ifornia. This trend reversed itself for measures of the Hispanic population; increasing Hispanic population was less of a risk factor for disease in Los Angeles and San Francisco than in the rest of California. Population density was an important risk factor for disease in areas other than Los Angeles and San Francisco.

DISCUSSION

General Findings Using a multivariate model and ecological

data from census tract–level geography, we have shown that minority race/ethnicity, immi- gration, and low income are strong risk factors for new tuberculosis transmission.

This analysis is further support for earlier studies showing that minority race/ethnicity is a risk factor for disease. However, whereas previous research11 has suggested that the risk of race/ethnicity is largely secondary to its cor- relation with socioeconomic risk factors such as low education, high unemployment, crowd- ing, and high population density, our data did not support this conclusion. In our multivariate analysis, the variability in cases of tuberculosis was better explained by immigration, racial/ ethnic minority groupings, and median income than by other variables such as low education, high unemployment, crowded housing, and high population density. The risk of race for disease could be caused by a combination of factors. Although genetic differences have been linked to increased mycobacterial suscep- tibility,22–25 it seems more likely that minority populations are surrogates for larger reservoirs of latent tuberculosis infection. Many minori- ties have emigrated from regions with higher baseline rates of latent tuberculosis infection, and African Americans have for the past few generations lived disproportionately in urban centers with higher rates of tuberculosis dis- ease. In California, these groups are known to have high rates of active disease.26 Addition- ally, race and ethnicity are complex social con- structs that may be markers for other socioeco- nomic factors that are difficult to capture in such a model.

Like previous studies, our initial univariate analysis demonstrated that crowding is a risk factor for tubercular disease. However, after adjusting for other factors in the multivariate

 

 

April 2006, Vol 96, No. 4 | American Journal of Public Health Myers et al. | Peer Reviewed | Research and Practice | 689

 RESEARCH AND PRACTICE 

model, crowding was noted as developing a protective effect. Part of this change was likely because of its correlation with other variables that better explained the variability in tubercu- losis cases (most significantly, low education [ r 2 = 0.8], foreign birth [ r 2 = 0.8], and Hispanic ethnicity [ r 2 = 0.6]). Nevertheless, its reemer- gence as a significant protective factor suggests some benefit may remain after the negative ef- fects are removed by adjusting for other vari- ables. These results could be explained within the context of recent research on “social capi- tal” as a protective factor for tuberculosis.15

Crowding may be associated with a more tightly woven social network (i.e., increased so- cial capital) that could protect against disease. Although this research has shown potential, much controversy still exists on the precise measurement of social capital. Further research in this area is clearly warranted.

Our study also supports the association be- tween family income and tuberculosis disease. This finding is consistent with previous re- search showing a close link between tuberculo- sis and poverty. Although many racial or ethnic minorities may have higher rates of disease be- cause of historical reservoirs of tuberculosis in- fection, current levels of economic deprivation are of critical importance.

Regional Differences The effects for various ecological risk factors

were generally consistent across the 3 regions studied. Differences were noted in the risk of population density and in the risk of high ra- cial/ethnic minority populations. The lack of ef- fect for population density in San Francisco and Los Angeles was not unexpected because these 2 regions have uniformly high population den- sities in comparison to the rest of the state.

Conversely, the regional differences in the risk factors for Black and Hispanic populations were somewhat surprising. These risk differ- ences were not explained by differences in in- come or recent immigration. The increased rate of tuberculosis noted in predominantly Black census tracts near San Francisco may be at least partially attributable to a known persistent cluster of cases in a Black community in Contra Costa County (part of the San Francisco MSA).27

To assess the impact of this cluster on the gen- eral finding, the analysis was repeated, exclud- ing census tracts that corresponded to the

geographic location of the previously men- tioned cluster. In the new analysis, the inci- dence rate ratio decreased slightly, but not completely (1.4 to 1.34), suggesting that the known cluster may reflect a larger trend in the San Francisco area.

Also worthy of additional investigation is the lower baseline rate of tuberculosis in the Los Angeles MSA. After adjusting for variables in the model, the disease rate in Los Angeles was one third lower than expected. This finding is reflected by the crude rate of disease in Los Angeles. Despite Los Angeles having a higher level of diversity and immigration than the rest of the state, the crude rate of pediatric tubercu- losis there is roughly the same as that for the state as a whole.

Strengths and Limitations This analysis, in comparison to other studies

of ecological risk factors for tuberculosis, has the advantage of a focus on pediatric cases. This focus permits the results to more directly reflect risk factors for disease transmission. Previous studies of molecular epidemiology have shown that between 4% and 31% of all cases are the result of recent transmission.28,29 This means that for a vast majority of all cases, ecological data obtained at the time of disease onset may not represent factors relevant to transmission.

Insufficient data exist for similar estimations for pediatric cases, but it is generally assumed that pediatric cases represent recent transmis- sion. Therefore, analyses using exclusively pedi- atric cases would be expected to provide results with less misclassification and greater precision. Stratification by country of birth could also the- oretically reduce misclassification. Foreign-born children, compared with US-born children, may have been more likely to have acquired their infection overseas. Because the incidence rate ratios from the US-born–only stratum in our analysis are remarkably similar to the results from the full multivariate model, the degree of misclassification may be small.

Research that makes comparisons among different measures of social inequalities is chal- lenging; social measures of income, education, and ethnic heritage all use different units and scales. Furthermore, the shape of each distribu- tion differs, and threshold effects are often un- known. To address these challenges, we stan- dardized variables to a scale on the basis of

mean and variance. Because each independent variable is transformed through addition and multiplication of constants, the magnitude of the resulting incidence rate ratio changes, but its direction and significance do not.

Alternative methods of standardization for predictor variables have been used elsewhere. These include use of raw variables,13,15 compar- ison by quartiles,7 use of the relative index of inequality,7,30 use of a multiple variable index score,7,9 and numerous others.30 Each of these techniques has advantages and disadvantages (the full discussion of which is beyond the scope of this paper). Broadly speaking, these techniques tend to sacrifice either ease of com- parison to other variables (in the case of raw scores and log transformations) or clarity of technique (in the case of indices). We propose that although the technique of standardization by mean and variance is by no means perfect, it is an acceptable compromise that permits the clear comparison between ecological measures by nonstatisticians.

This analysis, however, is not without limita- tions. Collinearity, which occurs when indepen- dent variables are identical or very similar to each other, can be problematic in ecological studies. This occurs because aggregated socio- economic variables tend to be more highly cor- related with each other than individual socio- economic variables.31 This effect is magnified in studies with a small number of large hetero- geneous regions. Generally speaking, collinear- ity reduces the significance of a study’s findings by increasing the variance of its regression coef- ficients. This effect may have resulted in the underestimation of the incidence rate ratios reported in this article. We attempted to mini- mize this effect by analyzing 7018 census tracts and by selecting a variety of differing socioeco- nomic variables. Additionally, we confirmed that the potential collinearity because of crowd- ing did not destabilize the full model, because the remaining statistics changed only minimally (0.5% to 5%) when crowding was removed from the analysis.

Some misclassification may have occurred through the use of cases reported between January 1993 and December 2002 and eco- logical measures taken from the 2000 US Census. Although ecological measures for each census tract do shift over time, data from the national census is only collected

 

 

American Journal of Public Health | April 2006, Vol 96, No. 4690 | Research and Practice | Peer Reviewed | Myers et al.

 RESEARCH AND PRACTICE 

every 10 years. Because there are insufficient cases of pediatric tuberculosis each year to analyze individually, this study combined cases over 10 years and used census data that were obtained during that time period.

Aggregated ecological measures, such as those used in this study, are distinct from their analogous individual-level characteristics.32 For example, having a low income affects an indi- vidual differently than living in a poor neigh- borhood. Because the California Department of Health does not currently collect data on in- come, education, or household crowding from individual tuberculosis cases, we were unable to directly compare ecological and individual- level factors. However, such a multilevel analy- sis would be informative and should be pur- sued in future research.

Finally, tuberculosis transmission is a com- plex process that depends on many factors. The models developed in this investigation include several variables, but other important variables may be missing.

CONCLUSIONS

Ecological studies such as this provide valu- able information. Disease transmission within a population depends both on individual host risk factors and community-level risk factors that govern the individual’s exposure to disease. This research suggests specific ecological factors that are associated with increased rates of tuberculo- sis disease. State and local tuberculosis control programs may use this information to identify “at risk” geographic areas that merit increased disease surveillance. These techniques under- score both the importance of geographic infor- mation in case reporting and its contribution to the better understanding of disease.

About the Authors Ward P. Myers is with the Children’s Hospital, Boston, and Boston Medical Center, Boston, Mass. Janice L. Westenhouse and Jennifer Flood are with the Tuberculosis Control Branch, California Department of Health Services, Berkeley, Calif. Lee W. Riley is with the University of California, Berkeley, School of Public Health.

Request for reprints should be sent to Lee Riley, 140 War- ren Hall, Berkeley, CA 94720 (e-mail: lwriley@berkeley.edu).

This article was accepted May 30, 2005.

Contributors W. P. Myers originated the study and led the analysis and writing. J. L. Westenhouse assisted with the data collection

and analysis. J. Flood supervised data collection and anal- ysis. L. W. Riley supervised the analysis and writing.

Acknowledgments Material and financial support were provided by the Cali- fornia Department of Health Services and the University of California, Berkeley, School of Public Health.

We would like to thank Arthur Reingold for his guid- ance and assistance in reviewing the article.

Human Participant Protection No institutional review board protocol approval was needed for this study.

References 1. Barr RG, Diez-Roux AV, Knirsch CA, Pablos- Mendez A. Neighborhood poverty and the resurgence of tuberculosis in New York City, 1984–1992. Am J Public Health. 2001;91:1487–1493.

2. Hetherington HW, Landis M, Opie A. survey to de- termine the prevalence of tuberculosis infection in school children. Am Rev Tuberc. 1929:421.

3. Puccini G. La Boháeme. Milan, Italy: G Ricordi & C; 1896.

4. Reported Tuberculosis in the United States, 2002. Atlanta, Ga: US Dept of Health and Human Services, Centers for Disease Control and Prevention; September 2003.

5. Krieger N, Chen JT, Ebel G. Can we monitor socio- economic inequalities in health? A survey of U.S. health departments’ data collection and reporting practices. Pub- lic Health Rep. 1997;112:481–491.

6. United States Census Bureau. United States Census 2000 glossary of terms. Available at: http://www.census. gov/dmd/www/glossary. Accessed February 20, 2004.

7. Krieger N, Waterman PD, Chen JT, Soobader MJ, Subramanian SV. Monitoring socioeconomic inequalities in sexually transmitted infections, tuberculosis, and vio- lence: geocoding and choice of area-based socioeconomic measures—the public health disparities geocoding project (US). Public Health Rep. 2003;118:240–260.

8. Lillebaek T, Dirksen A, Baess I, Strunge B, Thomsen VO, Andersen AB. Molecular evidence of endogenous reactivation of Mycobacterium tuberculosis after 33 years of latent infection. J Infect Dis. 2002;185: 401–404.

9. Spence DP, Hotchkiss J, Williams CS, Davies PD. Tuberculosis and poverty. BMJ. 1993;307:759–761.

10. Doherty MJ, Davies PD, Bellis MA, Tocque K. Tu- berculosis in England and Wales. Ethnic origin is more important than social deprivation. BMJ. 1995;311:187.

11. Cantwell MF, McKenna MT, McCray E, Onorato IM. Tuberculosis and race/ethnicity in the United States: impact of socioeconomic status. Am J Respir Crit Care Med. 1998;157(4 pt 1):1016–1020.

12. Tocque K, Doherty MJ, Bellis MA, Spence DP, Wil- liams CS, Davies PD. Tuberculosis notifications in En- gland: the relative effects of deprivation and immigration. Int J Tuberc Lung Dis. 1998;2:213–218.

13. Hawker JI, Bakhshi SS, Ali S, Farrington CP. Eco- logical analysis of ethnic differences in relation be- tween tuberculosis and poverty. BMJ. 1999;319: 1031–1034.

14. Bennett J, Pitman R, Jarman B, et al. A study of the variation in tuberculosis incidence and possible influen- tial variables in Manchester, Liverpool, Birmingham and

Cardiff in 1991–1995. Int J Tuberc Lung Dis. 2001;5: 158–163.

15. Holtgrave DR, Crosby RA. Social determinants of tuberculosis case rates in the United States. Am J Prev Med. 2004;26:159–162.

16. Drucker E, Alcabes P, Bosworth W, Sckell B. Child- hood tuberculosis in the Bronx, New York. Lancet. 1994; 343:1482–1485.

17. United States Census Bureau. Census 2000 sum- mary file 1: California. Available at: http://factfinder.cen- sus.gov/home/saff/main.html?_lang=en. Accessed Febru- ary 20, 2004.

18. United States Census Bureau. Census 2000 sum- mary file 3: California. Available at: http://factfinder.cen- sus.gov/home/saff/main.html?_lang=en. Accessed Febru- ary 20, 2004.

19. Byers AL, Allore H, Gill TM, Peduzzi PN. Applica- tion of negative binomial modeling for discrete out- comes: a case study in aging research. J Clin Epidemiol. 2003;56:559–564.

20. Dupont W. Statistical Modeling for Biomedical Re- searchers. Cambridge, England: Cambridge University Press; 2002.

21. United States Census Bureau. Geography Division: Census 2000 products. Available at: http://www.census. gov/geo/www/census2k.html. Accessed May 15, 2004.

22. Ma X, Reich RA, Wright JA, et al. Association be- tween interleukin-8 gene alleles and human susceptibil- ity to tuberculosis disease. J Infect Dis. 2003;188: 349–355.

23. Stead WW, Senner JW, Reddick WT, Lofgren JP. Racial differences in susceptibility to infection by Mycobac- terium tuberculosis. N Engl J Med. 1990;322:422–427.

24. Bellamy R. Genetics and pulmonary medicine. 3. Genetic susceptibility to tuberculosis in human popula- tions. Thorax. 1998;53:588–593.

25. Abel L, Sanchez FO, Oberti J, et al. Susceptibility to leprosy is linked to the human NRAMP1 gene. J Infect Dis. 1998;177:133–145.

26. California Department of Health Services. Communicable disease control in California, 2000. Available at: http://www.dhs.ca.gov/ps/dcdc/pdf/ CDC2000_Document.pdf. Accessed June 17, 2004.

27. Chin DP, Crane CM, Diul MY, et al. Spread of My- cobacterium tuberculosis in a community implementing recommended elements of tuberculosis control. JAMA. 2000;283:2968–2974.

28. Heldal E, Docker H, Caugant DA, Tverdal A. Pul- monary tuberculosis in Norwegian patients. The role of reactivation, re-infection and primary infection assessed by previous mass screening data and restriction fragment length polymorphism analysis. Int J Tuberc Lung Dis. 2000;4:300–307.

29. Small PM, Hopewell PC, Singh SP, et al. The epide- miology of tuberculosis in San Francisco. A population- based study using conventional and molecular methods. N Engl J Med. 1994;330:1703–1709.

30. Wagstaff A, Paci P, van Doorslaer E. On the mea- surement of inequalities in health. Soc Sci Med. 1991;33: 545–557.

31. Morgenstern H. Ecologic studies in epidemiology: concepts, principles, and methods. Annu Rev Public Health. 1995;16:61–81.

32. Schwartz S. The fallacy of the ecological fallacy: the potentia