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187 results on '"Maddison, John"'

1. Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT)

Author

Stretton, Brandon, Booth, Andrew E. C., Satheakeerthy, Shrirajh, Howson, Sarah, Evans, Shaun, Kovoor, Joshua, Akram, Waqas, McNeil, Keith, Hopkins, Ashley, Zeitz, Kathryn, Leslie, Alasdair, Psaltis, Peter, Gupta, Aashray, Tan, Sheryn, Teo, Melissa, Vanlint, Andrew, Chan, Weng Onn, Zannettino, Andrew, O’Callaghan, Patrick G., Maddison, John, Gluck, Samuel, Gilbert, Toby, and Bacchi, Stephen

Published
2024
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3. Hospital and out‐of‐hospital services provided by public geriatric medicine departments in Australia and New Zealand

Author

Azarias, Eleni, primary, Thillainadesan, Janani, additional, Hanger, Carl, additional, Scott, John, additional, Boudville, Amanda, additional, Moran, Chris, additional, O'Sullivan, Robert, additional, Maddison, John, additional, Eagar, Kathy, additional, Harvey, Gillian, additional, King, Alison, additional, Kearney, Leanne, additional, and Naganathan, Vasi, additional

Published
2024
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4. A brief history of ramping.

Author

Cook, Benjamin, Evenden, James, Genborg, Ruby, Stretton, Brandon, Kovoor, Joshua, Gibson, Kieran, Tan, Sheryn, Gupta, Aashray, Chan, Weng O., Bacchi, Carol, Ittimani, Mana, Cusack, Michael, Maddison, John, Gluck, Samuel, Gilbert, Tony, McNeill, Keith, and Bacchi, Stephen

Subjects
TURNAROUND time, HOSPITAL utilization, RESOURCE allocation, HOSPITAL emergency services, PATIENT care, AMBULANCES, TREATMENT delay (Medicine), TIME
Abstract

'Ramping' is a commonly used term in contemporary Australian healthcare. It is also a part of the public and political zeitgeist. However, its precise definition varies among sources. In the published literature, there are distinctions between related terms, such as 'entry overload' and 'Patient Off Stretcher Time Delay'. How ramping is defined and how it came to be defined have significance for policies and procedures relating to the described phenomenon. Through examination of the history of the term, insights are obtained into the underlying issues contributing to ramping and, accordingly, associated possible solutions. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Predictors of mortality shortly after entering a long-term care facility.

Author

Jorissen, Robert N, Wesselingh, Steve L, Whitehead, Craig, Maddison, John, Forward, John, Bourke, Alice, Harvey, Gillian, Crotty, Maria, Collaborators, STAAR-SA Study, and Inacio, Maria C

Subjects
MORTALITY risk factors, RISK assessment, PREDICTION models, AUSTRALIANS, RESEARCH funding, HEALTH status indicators, LONG-term health care, SEX distribution, RETROSPECTIVE studies, DESCRIPTIVE statistics, LONGITUDINAL method, NURSING care facilities, CONFIDENCE intervals, DRUGS, PROPORTIONAL hazards models, ACTIVITIES of daily living
Abstract

Objective Moving into a long-term care facility (LTCF) requires substantial personal, societal and financial investment. Identifying those at high risk of short-term mortality after LTCF entry can help with care planning and risk factor management. This study aimed to: (i) examine individual-, facility-, medication-, system- and healthcare-related predictors for 90-day mortality at entry into an LTCF and (ii) create risk profiles for this outcome. Design Retrospective cohort study using data from the Registry of Senior Australians. Subjects Individuals aged ≥ 65 years old with first-time permanent entry into an LTCF in three Australian states between 01 January 2013 and 31 December 2016. Methods A prediction model for 90-day mortality was developed using Cox regression with the purposeful variable selection approach. Individual-, medication-, system- and healthcare-related factors known at entry into an LTCF were examined as predictors. Harrell's C-index assessed the predictive ability of our risk models. Results 116,192 individuals who entered 1,967 facilities, of which 9.4% (N  = 10,910) died within 90 days, were studied. We identified 51 predictors of mortality, five of which were effect modifiers. The strongest predictors included activities of daily living category (hazard ratio [HR] = 5.41, 95% confidence interval [CI] = 4.99–5.88 for high vs low), high level of complex health conditions (HR = 1.67, 95% CI = 1.58–1.77 for high vs low), several medication classes and male sex (HR = 1.59, 95% CI = 1.53–1.65). The model out-of-sample Harrell's C-index was 0.773. Conclusions Our mortality prediction model, which includes several strongly associated factors, can moderately well identify individuals at high risk of mortality upon LTCF entry. [ABSTRACT FROM AUTHOR]

Published
2024
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9. How will the artificial intelligence algorithm work within the constraints of this healthcare system?

Author

Stretton, Brandon, primary, Koovor, Joshua G., additional, Hains, Lewis, additional, Kleinig, Oliver, additional, Tan, Sheryn, additional, Gupta, Aashray K., additional, Ittimani, Mana, additional, Dwyer, Andrew, additional, McNeil, Keith, additional, Chan, WengOnn, additional, Cusack, Michael, additional, O'Callaghan, Patrick G., additional, Maddison, John, additional, and Bacchi, Stephen, additional

Published
2024
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16. Changing the narrative on osteoarthritis: A call for global action

Author

Allen, Kelli, Babatunde, Opeyemi O, Bennel, Kim L, Berry, Alice, Bierma-Zeinstra, Sita, Callahan, Leigh, Campbell, Laura, Dziedzic, Krysia S, Finney, Andrew, French, Helen P, Haber, Travis, Hadley-Barrows, Tina, Hall, Michelle, Hawker, Gillian, Henriksen, Marius, Hinman, Rana S, Ho-Pham, Lan, Hunter, David J, Lawford, Belinda J, Mallen, Christian D, McHugh, Gretl A, Kopkow, Christian, Neogi, Tuhina, Nicholls, Elaine, Nicolson, Philippa JA., Østerås, Nina, Paskins, Zoe, Protheroe, Joanne, Roos, Ewa M., Runhaar, Jos, Skou, Soren T, Simkins, Joanna, Swaithes, Laura, Thomas, Geraint, van der Esch, Martin, Whittaker, Jackie, Zhang, Weiya, Jinks, Clare, Botto-van Bemden, Angie, Bunzli, Samantha, Bowden, Jocelyn, Egerton, Thorlene, Eyles, Jillian, Foster, Nadine, Healey, Emma L., Maddison, John, O’Brien, Daniel, Quicke, Jonathan G., Schiphof, Dieuwke, Parry, Emma, Thomas, Martin J., and Holden, Melanie A.

Published
2024
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17. Digital image processing for prognostic and diagnostic clinical pathology

Author

Maddison, John, Tian, Gui Yun, Danielsen, Havard, and Thorn, Mike

Subjects
616.0750285637, Q Science (General), RB Pathology
Abstract

When digital imaging and image processing methods are applied to clinical diagnostic and prognostic needs, the methods can be seen to increase human understanding and provide objective measurements. Most current clinical applications are limited to providing subjective information to healthcare professionals rather than providing objective measures. This Thesis provides detail of methods and systems that have been developed both for objective and subjective microscopy applications. A system framework is presented that provides a base for the development of microscopy imaging systems. This practical framework is based on currently available hardware and developed with standard software development tools. Image processing methods are applied to counter optical limitations of the bright field microscope, automating the system and allowing for unsupervised image capture and analysis. Current literature provides evidence that 3D visualisation has provided increased insight and application in many clinical areas. There have been recent advancements in the use of 3D visualisation for the study of soft tissue structures, but its clinical application within histology remains limited. Methods and applications have been researched and further developed which allow for the 3D reconstruction and visualisation of soft tissue structures using microtomed serial histological sections specimens. A system has been developed suitable for this need is presented giving considerations to image capture, data registration and 3D visualisation, requirements. The developed system has been used to explore and increase 3D insight on clinical samples. The area of automated objective image quantification of microscope slides presents the allure of providing objective methods replacing existing objective and subjective methods, increasing accuracy and rsducinq manual burden. One such existing objective test is DNA Image Ploidy which seeks to characterise cancer by the measurement of DNA content within individual cell nuclei, an accepted but manually burdensome method. The main novelty of the work completed lies in the development of an automated system for DNA Image Ploidy measurement, combining methods for automatic specimen focus, segmentation, parametric extraction and the implementation of an automated cell type classification system. A consideration for any clinical image processing system is the correct sampling of the tissue under study. VVhile the image capture requirements for both objective systems and subjective systems are similar there is also an important link between the 3D structures of the tissue. 3D understanding can aid in decisions regarding the sampling criteria of objective tests for as although many tests are completed in the 2D realm the clinical samples are 3D objects. Cancers such as Prostate and Breast cancer are known to be multi-focal, with areas of seeming physically, independent areas of disease within a single site. It is not possible to understand the true 3D nature of the samples using 2D micro-tomed sections in isolation from each other. The 3D systems described in this report provide a platform of the exploration of the true multi focal nature of disease soft tissue structures allowing for the sampling criteria of objective tests such as DNA Image Ploidy to be correctly set. For the Automated DNA Image Ploidy and the 3D reconstruction and visualisation systems, clinical review has been completed to test the increased insights provided. Datasets which have been reconstructed from microtomed serial sections and visualised with the developed 3D system area presented. For the automated DNA Image Ploidy system, the developed system is compared with the existing manual method to qualify the quality of data capture, operational speed and correctness of nuclei classification. Conclusions are presented for the work that has been completed and discussion given as to future areas of research that could be undertaken, extending the areas of study, increasing both clinical insight and practical application.

Published
2005

22. P077 Developing a better explanation of osteoarthritis: results from a conjoint analysis of patient preferences

Author

Paskins, Zoe, primary, Nicholls, Elaine, additional, Grossmann, Heiko, additional, McRobert, Cliona, additional, Peat, George, additional, Shivji, Noureen, additional, Bartlam, Bernadette, additional, Croft, Peter, additional, Jinks, Clare, additional, Maddison, John, additional, Main, Chris, additional, Quicke, Jonathan, additional, Porcheret, Mark, additional, Protheroe, Joanne, additional, and Cottrell, Elizabeth, additional

Published
2022
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23. Predictors of hospitalisations and emergency department presentations shortly after entering a residential aged care facility in Australia: a retrospective cohort study

Author

Inacio, Maria C, primary, Jorissen, Robert N, additional, Wesselingh, Steve, additional, Sluggett, Janet K, additional, Whitehead, Craig, additional, Maddison, John, additional, Forward, John, additional, Bourke, Alice, additional, Harvey, Gillian, additional, and Crotty, Maria, additional

Published
2021
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25. Corrigendum to “Implementing patient direct access to musculoskeletal physiotherapy in primary care: views of patients, general practitioners, physiotherapists and clinical commissioners in England” [Physiotherapy 111 (June) (2021) 31–39]

Author

Igwesi-Chidobe, Chinonso N., primary, Bishop, Annette, additional, Humphreys, Katrina, additional, Hughes, Emily, additional, Protheroe, Joanne, additional, Maddison, John, additional, and Bartlam, Bernadette, additional

Published
2021
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30. Predictors of short‐term hospitalization and emergency department presentations in aged care

Author

Inacio, Maria C., primary, Jorissen, Robert N., additional, Khadka, Jyoti, additional, Whitehead, Craig, additional, Maddison, John, additional, Bourke, Alice, additional, Pham, Clarabelle T., additional, Karnon, Jonathon, additional, Wesselingh, Steve L., additional, Lynch, Elizabeth, additional, Harvey, Gillian, additional, Caughey, Gillian E., additional, and Crotty, Maria, additional

Published
2021
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31. Predictors of short-term hospitalization and emergency department presentations in aged care

Author

Inacio, Maria C., Jorissen, Robert N., Khadka, Jyoti, Whitehead, Craig, Maddison, John, Bourke, Alice, Pham, Clarabelle T., Karnon, Jonathon, Wesselingh, Steve L., Lynch, Elizabeth, Harvey, Gillian, Caughey, Gillian E., Crotty, Maria, Inacio, Maria C., Jorissen, Robert N., Khadka, Jyoti, Whitehead, Craig, Maddison, John, Bourke, Alice, Pham, Clarabelle T., Karnon, Jonathon, Wesselingh, Steve L., Lynch, Elizabeth, Harvey, Gillian, Caughey, Gillian E., and Crotty, Maria

Abstract

Objectives: To examine individual, medication, system, and healthcare related predictors of hospitalization and emergency department (ED) presentation within 90 days of entering the aged care sector, and to create risk-profiles associated with these outcomes. Design and setting: Retrospective population-based cohort study using data from the Registry of Senior Australians. Participants: Older people (aged 65 and older) with an aged care eligibility assessment in South Australia between January 1, 2013 and May 31, 2016 (N = 22,130). Measurements: Primary outcomes were unplanned hospitalization and ED presentation within 90 days of assessment. Individual, medication, system, and healthcare related predictors of the outcomes at the time of assessment, within 90 days or 1-year prior. Fine–Gray models were used to calculate subdistribution hazard ratios (sHR) and 95% confidence intervals (CI). Harrell's C-index assessed predictive ability. Results: Four thousand nine-hundred and six (22.2%) individuals were hospitalized and 5028 (22.7%) had an ED presentation within 90 days. Predictors of hospitalization included: being a man (hospitalization sHR = 1.33, 95% CI 1.26–1.42), ≥3 urgent after-hours attendances (hospitalization sHR = 1.21, 95% CI 1.06–1.39), increasing frailty index score (hospitalization sHR = 1.19, 95% CI 1.11–1.28), individuals using glucocorticoids (hospitalization sHR = 1.11, 95% CI 1.02–1.20), sulfonamides (hospitalization sHR = 1.18, 95% CI 1.10–1.27), trimethoprim antibiotics (hospitalization sHR = 1.15, 95% CI 1.03–1.29), unplanned hospitalizations 30 days prior (hospitalization sHR = 1.13, 95% CI 1.04–1.23), and ED presentations 1 year prior (hospitalization sHR = 1.07, 95% CI 1.04–1.10). Similar predictors and hazard estimates were also observed for ED presentations. The hospitalization models out-of-sample predictive ability (C-index = 0.653, 95% CI 0.635–0.670) and ED presentations (C-index = 0.647, 95% CI 0.630–0.663) were moderate. Conclusio

Published
2021

32. Predictors of hospitalisations and emergency department presentations shortly after entering a residential aged care facility in Australia: A retrospective cohort study

Author

Inacio, Maria C., Jorissen, Robert N., Wesselingh, Steve, Sluggett, Janet K., Whitehead, Craig, Maddison, John, Forward, John, Bourke, Alice, Harvey, Gillian, Crotty, Maria, Inacio, Maria C., Jorissen, Robert N., Wesselingh, Steve, Sluggett, Janet K., Whitehead, Craig, Maddison, John, Forward, John, Bourke, Alice, Harvey, Gillian, and Crotty, Maria

Abstract

Objectives: To: (1) examine the 90-day incidence of unplanned hospitalisation and emergency department (ED) presentations after residential aged care facility (RACF) entry, (2) examine individual-related, facility-related, medication-related, system-related and healthcare-related predictors of these outcomes and (3) create individual risk profiles. Design: Retrospective cohort study using the Registry of Senior Australians. Fine-Gray models estimated subdistribution HRs and 95% CIs. Harrell's C-index assessed risk models' predictive ability. Setting and participants: Individuals aged ≥65 years old entering a RACF as permanent residents in three Australian states between 1 January 2013 and 31 December 2016 (N=116 192 individuals in 1967 RACFs). Predictors examined: Individual-related, facility-related, medication-related, system and healthcare-related predictors ascertained at assessments or within 90 days, 6 months or 1 year prior to RACF entry. Outcome measures: 90-day unplanned hospitalisation and ED presentation post-RACF entry. Results: The cohort median age was 85 years old (IQR 80-89), 62% (N=71 861) were women, and 50.5% (N=58 714) had dementia. The 90-day incidence of unplanned hospitalisations was 18.0% (N=20 919) and 22.6% (N=26 242) had ED presentations. There were 34 predictors of unplanned hospitalisations and 34 predictors of ED presentations identified, 27 common to both outcomes and 7 were unique to each. The hospitalisation and ED presentation models out-of-sample Harrell's C-index was 0.664 (95% CI 0.657 to 0.672) and 0.655 (95% CI 0.648 to 0.662), respectively. Some common predictors of high risk of unplanned hospitalisation and ED presentations included: being a man, age, delirium history, higher activity of daily living, behavioural and complex care needs, as well as history, number and recency of healthcare use (including hospital, general practitioners attendances), experience of a high sedative load and several medications. Conclusions: Wi

Published
2021

36. An Integrated Knowledge Translation Study to Address Avoidable Rehospitalisations and Unplanned Admissions for Older People: Study Protocol

Author

Harvey, Gillian, primary, Pham, Clarabelle T., additional, Inacio, Maria C., additional, Laver, Kate, additional, Lynch, Elizabeth A., additional, Jorissen, Robert N., additional, Karnon, Jonathan, additional, Bourke, Alice, additional, Forward, John, additional, Maddison, John, additional, Whitehead, Craig, additional, Rupa, Jesmin A., additional, McNamara, Carmel, additional, and Crotty, Maria, additional

Published
2020
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38. A CNN-aided method to predict glaucoma progression using DARC (Detection of Apoptosing Retinal Cells)

Author

Normando, Eduardo M., primary, Yap, Tim E., additional, Maddison, John, additional, Miodragovic, Serge, additional, Bonetti, Paolo, additional, Almonte, Melanie, additional, Mohammad, Nada G., additional, Ameen, Sally, additional, Crawley, Laura, additional, Ahmed, Faisal, additional, Bloom, Philip A., additional, and Cordeiro, Maria Francesca, additional

Published
2020
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40. Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

Author

Skrede, Ole-Johan, primary, De Raedt, Sepp, additional, Kleppe, Andreas, additional, Hveem, Tarjei S, additional, Liestøl, Knut, additional, Maddison, John, additional, Askautrud, Hanne A, additional, Pradhan, Manohar, additional, Nesheim, John Arne, additional, Albregtsen, Fritz, additional, Farstad, Inger Nina, additional, Domingo, Enric, additional, Church, David N, additional, Nesbakken, Arild, additional, Shepherd, Neil A, additional, Tomlinson, Ian, additional, Kerr, Rachel, additional, Novelli, Marco, additional, Kerr, David J, additional, and Danielsen, Håvard E, additional

Published
2020
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41. Supplemental_Material – Supplemental material for A pilot cohort study of deprescribing for nursing home patients acutely admitted to hospital

Author

Russell, Patrick, Laubscher, Sara, Roberts, Gregory W., Mangoni, Arduino A., McDonald, Cameron, Hendrix, Ivanka, Udul Hewage, Hofmann, Dirk, Michell, Sophie, Taeuber, Lauren, Woodman, Richard J., Shakib, Sepehr, Crawford, Gregory B., Maddison, John, and Thompson, Campbell

Subjects
FOS: Clinical medicine, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified, 111299 Oncology and Carcinogenesis not elsewhere classified
Abstract

Supplemental material, Supplemental_Material for A pilot cohort study of deprescribing for nursing home patients acutely admitted to hospital by Patrick Russell, Sara Laubscher, Gregory W. Roberts, Arduino A. Mangoni, Cameron McDonald, Ivanka Hendrix, Udul Hewage, Dirk Hofmann, Sophie Michell, Lauren Taeuber, Richard J. Woodman, Sepehr Shakib, Gregory B. Crawford, John Maddison and Campbell Thompson in Therapeutic Advances in Drug Safety

Published
2019
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43. Automatisk validering av skärmgrafik med OpenCV och Tesseract

Author

Maddison, John

Subjects
validation, test, displays, Tesseract, Opencv, regression, Computer Engineering, Datorteknik
Abstract

I dagens flygplan finns det mycket information som på ett snabbt och pålitligt sätt behöver förmedlas till piloten via instrument på flera skärmar i cockpit. Att verifiera att skärmarna visar korrekt data för olika indata är ett tidskrävande och monotont arbete. Därför undersöker Saab möjligheten att automatisera delar av arbetet. Examensarbetet undersöker genom praktiskt implementation ifall det är möjligt att automatisera bildanalysen med hjälp av programmen OpenCV och Tesseract. Resultatet visade att det går att enkelt konstruera tester för att automatiskt identifiera oönskade förändringar i den implementerade instrumentingen.

Published
2018

44. A pilot cohort study of deprescribing for nursing home patients acutely admitted to hospital

Author

Russell, Patrick, primary, Laubscher, Sara, additional, Roberts, Gregory W., additional, Mangoni, Arduino A., additional, McDonald, Cameron, additional, Hendrix, Ivanka, additional, Hewage, Udul, additional, Hofmann, Dirk, additional, Michell, Sophie, additional, Taeuber, Lauren, additional, Woodman, Richard J., additional, Shakib, Sepehr, additional, Crawford, Gregory B., additional, Maddison, John, additional, and Thompson, Campbell, additional

Published
2019
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45. Predicting wet age-related macular degeneration (AMD) using DARC (detecting apoptosing retinal cells) AI (artificial intelligence) technology.

Author

Corazza, Paolo, Maddison, John, Bonetti, Paolo, Guo, Li, Luong, Vy, Garfinkel, Alan, Younis, Saad, and Cordeiro, Maria Francesca

Abstract

To assess a recently described CNN (convolutional neural network) DARC (Detection of Apoptosing Retinal Cells) algorithm in predicting new Subretinal Fluid (SRF) formation in Age-related-Macular-Degeneration (AMD). Anonymized DARC, baseline and serial OCT images (n = 427) from 29 AMD eyes of Phase 2 clinical trial (ISRCTN10751859) were assessed with CNN algorithms, enabling the location of each DARC spot on corresponding OCT slices (n = 20,629). Assessment of DARC in a rabbit model of angiogenesis was performed in parallel. A CNN DARC count >5 at baseline was significantly (p = 0.0156) related to development of new SRF throughout 36 months. Prediction rate of eyes using unique DARC spots overlying new SRF had positive predictive values, sensitivities and specificities >70%, with DARC count significantly (p < 0.005) related to the magnitude of SRF accumulation at all time points. DARC identified earliest stages of angiogenesis in-vivo. DARC was able to predict new wet-AMD activity. Using only an OCT-CNN definition of new SRF, we demonstrate that DARC can identify early endothelial neovascular activity, as confirmed by rabbit studies. Although larger validation studies are required, this shows the potential of DARC as a biomarker of wet AMD, and potentially saving vision-loss. [ABSTRACT FROM AUTHOR]

Published
2021
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46. Radio and Television in Literacy. A Survey of the Use of the Broadcasting Media in Combating Illiteracy among Adults.

Author

United Nations Educational, Scientific, and Cultural Organization, Paris (France). Dept. of Mass Communication. and Maddison, John

Abstract

Information obtained in a survey of the uses of radio and television in connection with literacy work in 40 countries of the world is presented. Much of the information consists of replies to Unesco questionnaires on the subject. The countries surveyed were: Algeria, Cameroon, Central African Republic, Chad, Congo (Brazzaville), Ethiopia, Gabon, Guinea, Ivory Coast, Kenya, Madagascar, Mali, Niger, Rwanda, Senegal, Sudan, Tunisia, United Arab Republic, Upper Volta, Zambia, Cuba, Guatemala, Jamaica, Mexico, United States, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Burma, China (Republic of--Taiwan), India, Iran, Laos, Italy, Spain, and Yugoslavia. A profile or composite picture of practices and experience in various countries is presented. The survey showed that broadcasting is making a valuable and in some cases essential contribution to literacy campaigns. Recommendations made include the following: (1) All the various ways of using radio and television should be fully exploited in all countries that have a sizeable illiteracy problem; (2) This should be done as part of an overall plan to develop the new techniques of communication for economic and social, and especially educational, advancement; (3) Research that aids in planning and further research as well as into "methods" and "materials" is needed; and (4) Training centers and programs for broadcasting personnel are needed. (DB)

Published
1971

49. L'Étude des médias dans l'enseignement

Author

Maddison John, Bennett Susan, Kruger Gerard, Alvarado Manuel, Pedersen Jens, Minkkinen Sirkka, Stenbeck Ingrid, Weissfeld Ilia, Sim John Cameron and Maddison John, Bennett Susan, Kruger Gerard, Alvarado Manuel, Pedersen Jens, Minkkinen Sirkka, Stenbeck Ingrid, Weissfeld Ilia, Sim John Cameron

Published
1977

50. British land

Author

Maddison, John

Subjects
Shopping malls -- Evaluation -- Management, Stores -- Forecasts and trends -- Customer relations -- Management, Company business management, Market trend/market analysis, Business, Business, international, Real estate industry
Abstract

The retail environment is evolving, and our response is to focus on delivering environments that are relevant to our customers. We undertake 60,000 exit surveys annually, and, acting on this [...]

Published
2014

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