Automated analysis of free-text comments and dashboard representations in patient experience surveys: a multimethod co-design study

Patient experience surveys (PESs) often include informative free-text comments, but with no way of systematically, efficiently and usefully analysing and reporting these. The National Cancer Patient Experience Survey (CPES), used to model the approach reported here, generates > 70,000 free-text comments annually.To improve the use and usefulness of PES free-text comments in driving health service changes that improve the patient experience.(1) To structure CPES free-text comments using rule-based information retrieval (IR) (‘text engineering’), drawing on health-care domain-specific gazetteers of terms, with in-built transferability to other surveys and conditions; (2) to display the results usefully for health-care professionals, in a digital toolkit dashboard display that drills down to the original free text; (3) to explore the usefulness of interdisciplinary mixed stakeholder co-design and consensus-forming approaches in technology development, ensuring that outputs have meaning for all; and (4) to explore the usefulness of Normalisation Process Theory (NPT) in structuring outputs for implementation and sustainability.A scoping review, rapid review and surveys with stakeholders in health care (patients, carers, health-care providers, commissioners, policy-makers and charities) explored clinical dashboard design/patient experience themes. The findings informed the rules for the draft rule-based IR [developed using half of the 2013 Wales CPES (WCPES) data set] and prototype toolkit dashboards summarising PES data. These were refined following mixed stakeholder, concept-mapping workshops and interviews, which were structured to enable consensus-forming ‘co-design’ work. IR validation used the second half of the WCPES, with comparison against its manual analysis; transferability was tested using further health-care data sets. A discrete choice experiment (DCE) explored which toolkit features were preferred by health-care professionals, with a simple cost–benefit analysis. Structured walk-throughs with NHS managers in Wessex, London and Leeds explored usability and general implementation into practice.A taxonomy of ranked PES themes, a checklist of key features recommended for digital clinical toolkits, rule-based IR validation and transferability scores, usability, and goal-oriented, cost–benefit and marketability results. The secondary outputs were a survey, scoping and rapid review findings, and concordance and discordance between stakeholders and methods.(1) The surveys, rapid review and workshops showed that stakeholders differed in their understandings of the patient experience and priorities for change, but that they reached consensus on a shortlist of 19 themes; six were considered to be core; (2) the scoping review and one survey explored the clinical toolkit design, emphasising that such toolkits should be quick and easy to use, and embedded in workflows; the workshop discussions, the DCE and the walk-throughs confirmed this and foregrounded other features to form the toolkit design checklist; and (3) the rule-based IR, developed using noun and verb phrases and lookup gazetteers, was 86% accurate on the WCPES, but needs modification to improve this and to be accurate with other data sets. The DCE and the walk-through suggest that the toolkit would be well accepted, with a favourable cost–benefit ratio, if implemented into practice with appropriate infrastructure support.Small participant numbers and sampling bias across component studies. The scoping review studies mostly used top-down approaches and focused on professional dashboards. The rapid review of themes had limited scope, with no second reviewer. The IR needs further refinement, especially for transferability. New governance restrictions further limit immediate use.Using a multidisciplinary, mixed stakeholder, use of co-design, proof of concept was shown for an automated display of patient experience free-text comments in a way that could drive health-care improvements in real time. The approach is easily modified for transferable application.Further exploration is needed of implementation into practice, transferable uses and technology development co-design approaches.The National Institute for Health Research Health Services and Delivery Research programme.

[1]  A. Kothari,et al.  Embracing complexity and uncertainty to create impact: exploring the processes and transformative potential of co-produced research through development of a social impact model , 2018, Health Research Policy and Systems.

[2]  M. Wells,et al.  Qualitative analysis of 6961 free-text comments from the first National Cancer Patient Experience Survey in Scotland , 2017, BMJ Open.

[3]  A. McMahon,et al.  Patient‐centred dietetic care from the perspectives of older malnourished patients , 2017, Journal of human nutrition and dietetics : the official journal of the British Dietetic Association.

[4]  Scott R. Rosas,et al.  Group concept mapping methodology: toward an epistemology of group conceptualization, complexity, and emergence , 2017 .

[5]  D. Lakens,et al.  Why Psychologists Should by Default Use Welch's t-test Instead of Student's t-test with Unequal Group Sizes , 2017 .

[6]  S. Chatterjee,et al.  Design and Usability of a Heart Failure mHealth System: A Pilot Study , 2017, JMIR human factors.

[7]  Chris Gibbons,et al.  Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy , 2017, Journal of medical Internet research.

[8]  Mathijs F. G. Lucassen,et al.  Tips and Traps: Lessons From Codesigning a Clinician E-Monitoring Tool for Computerized Cognitive Behavioral Therapy , 2017, JMIR mental health.

[9]  A. Gavin,et al.  Life after prostate cancer diagnosis: protocol for a UK-wide patient-reported outcomes study , 2016, BMJ Open.

[10]  Tracy Finch,et al.  Implementation, context and complexity , 2016, Implementation Science.

[11]  M. Wells,et al.  Scottish Cancer Patient Experience Survey 2015/16: Analysis of Free-text Comments , 2016 .

[12]  R. Walton,et al.  Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps , 2016, BMJ Open.

[13]  Iain E. Buchan,et al.  Interface design recommendations for computerised clinical audit and feedback: Hybrid usability evidence from a research-led system , 2016, Int. J. Medical Informatics.

[14]  C. Lyles,et al.  User-Centered Design of a Tablet Waiting Room Tool for Complex Patients to Prioritize Discussion Topics for Primary Care Visits , 2016, JMIR mHealth and uHealth.

[15]  C. Oldmeadow,et al.  Getting right to the point: identifying Australian outpatients' priorities and preferences for patient-centred quality improvement in chronic disease care. , 2016, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[16]  A. While,et al.  An e-health intervention to support the transition of young people with long-term illnesses to adult healthcare services: Design and early use. , 2016, Patient education and counseling.

[17]  J. McClure,et al.  Prioritizing the mHealth Design Space: A Mixed-Methods Analysis of Smokers’ Perspectives , 2016, JMIR mHealth and uHealth.

[18]  Dan Wilson,et al.  Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study , 2016, BMC Medical Informatics and Decision Making.

[19]  Adir Even,et al.  Simulating the impact of an online digital dashboard in emergency departments on patients length of stay , 2016, J. Decis. Syst..

[20]  S. Patten,et al.  Preferred Features of E-Mental Health Programs for Prevention of Major Depression in Male Workers: Results From a Canadian National Survey , 2016, Journal of medical Internet research.

[21]  Zarnie Khadjesari,et al.  User Preferences for Content, Features, and Style for an App to Reduce Harmful Drinking in Young Adults: Analysis of User Feedback in App Stores and Focus Group Interviews , 2016, JMIR mHealth and uHealth.

[22]  R Brian Haynes,et al.  The McMaster Optimal Aging Portal: Usability Evaluation of a Unique Evidence-Based Health Information Website , 2016, JMIR human factors.

[23]  K. Sherman,et al.  My Changed Body: Background, development and acceptability of a self-compassion based writing activity for female survivors of breast cancer. , 2016, Patient education and counseling.

[24]  O. Lian,et al.  Factors facilitating patient satisfaction among women with medically unexplained long-term fatigue: A relational perspective , 2016, Health.

[25]  Eric J. Bruns,et al.  Applying User Input to the Design and Testing of an Electronic Behavioral Health Information System for Wraparound Care Coordination , 2016, Administration and Policy in Mental Health and Mental Health Services Research.

[26]  Miriam M. R. Vollenbroek-Hutten,et al.  Co-creation of an ICT-supported cancer rehabilitation application for resected lung cancer survivors: design and evaluation , 2016, BMC Health Services Research.

[27]  A. Carrico,et al.  Creating Effective Mobile Phone Apps to Optimize Antiretroviral Therapy Adherence: Perspectives From Stimulant-Using HIV-Positive Men Who Have Sex With Men , 2016, JMIR mHealth and uHealth.

[28]  J. Winterling,et al.  Development of a Self-Help Web-Based Intervention Targeting Young Cancer Patients With Sexual Problems and Fertility Distress in Collaboration With Patient Research Partners , 2016, JMIR research protocols.

[29]  L. Currie,et al.  Evaluation of QuitNow Men: An Online, Men-Centered Smoking Cessation Intervention , 2016, Journal of medical Internet research.

[30]  A. Bierman,et al.  Improving Patient Experience and Primary Care Quality for Patients With Complex Chronic Disease Using the Electronic Patient-Reported Outcomes Tool: Adopting Qualitative Methods Into a User-Centered Design Approach , 2016, JMIR research protocols.

[31]  Glyn Elwyn,et al.  ‘Much clearer with pictures’: using community-based participatory research to design and test a Picture Option Grid for underserved patients with breast cancer , 2016, BMJ Open.

[32]  J. Eakin Educating Critical Qualitative Health Researchers in the Land of the Randomized Controlled Trial , 2016 .

[33]  Julie A. Jacko,et al.  Designing an Educational Website to Improve Quality of Supportive Oncology Care for Women with Ovarian Cancer: An Expert Usability Review and Analysis , 2016, Int. J. Hum. Comput. Interact..

[34]  Harri Oinas-Kukkonen,et al.  Insights from the Design and Evaluation of a Personal Health Dashboard , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[35]  Goran Nenadic,et al.  Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database , 2015, BMC Medical Informatics and Decision Making.

[36]  J. Donovan,et al.  Maximising the impact of qualitative research in feasibility studies for randomised controlled trials: guidance for researchers , 2015, Trials.

[37]  M. Simon,et al.  Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care , 2015, BMJ Quality & Safety.

[38]  Erik Duval,et al.  Design and Evaluation of an Interactive Proof-of-Concept Dashboard for General Practitioners , 2015, 2015 International Conference on Healthcare Informatics.

[39]  Megan L Ranney,et al.  Online emergency department ratings, patient satisfaction and the age-old issue of communication , 2015, BMJ Quality & Safety.

[40]  K. Kozhimannil,et al.  Women’s Experiences with Neuraxial Labor Analgesia in the Listening to Mothers II Survey: A Content Analysis of Open-Ended Responses , 2015, Anesthesia and analgesia.

[41]  Reza Safdari,et al.  Development of Performance Dashboards in Healthcare Sector: Key Practical Issues , 2015, Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH.

[42]  K. Pritchard-Jones,et al.  Insights into the experiences of patients with cancer in London: framework analysis of free-text data from the National Cancer Patient Experience Survey 2012/2013 from the two London Integrated Cancer Systems , 2015, BMJ Open.

[43]  C. Goodman,et al.  ReseArch with Patient and Public invOlvement: a RealisT evaluation – the RAPPORT study , 2015 .

[44]  J. Donovan,et al.  Maximising the impact of qualitative research in feasibility studies for randomised controlled trials: guidance for researchers , 2015, Pilot and Feasibility Studies.

[45]  Carl R May,et al.  Promoting professional behaviour change in healthcare: what interventions work, and why? A theory-led overview of systematic reviews , 2015, BMJ Open.

[46]  Howard Chen,et al.  Development and Evaluation of a Health Information Technology Dashboard of Quality Indicators , 2015 .

[47]  C. Drossaert,et al.  Feasibility of a Website and a Hospital-Based Online Portal for Young Adults With Juvenile Idiopathic Arthritis: Views and Experiences of Patients , 2015, JMIR research protocols.

[48]  J. Bernhardt,et al.  An Iterative Process for Developing and Evaluating a Computer-Based Prostate Cancer Decision Aid for African American Men , 2015, Health promotion practice.

[49]  G. Giovannoni,et al.  Multiple sclerosis outpatient future groups: improving the quality of participant interaction and ideation tools within service improvement activities , 2015, BMC Health Services Research.

[50]  Tatiana Dilla,et al.  No big data without small data: learning health care systems begin and end with the individual patient , 2015, Journal of evaluation in clinical practice.

[51]  David R. Flum,et al.  Integrating Patient-Reported Outcomes into Spine Surgical Care through Visual Dashboards: Lessons Learned from Human-Centered Design , 2015, EGEMS.

[52]  H. D. de Melker,et al.  Consistency between stated and revealed preferences: a discrete choice experiment and a behavioural experiment on vaccination behaviour compared , 2015, BMC Medical Research Methodology.

[53]  Jorge A. Gálvez,et al.  Optimization of drug-drug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard , 2015, J. Am. Medical Informatics Assoc..

[54]  William B. Lober,et al.  Development and usability testing of a web-based cancer symptom and quality-of-life support intervention , 2015, Health Informatics J..

[55]  Geraldine Fitzpatrick,et al.  Dashboards for improving patient care: Review of the literature , 2015, Int. J. Medical Informatics.

[56]  Samantha R. Paige,et al.  Engaging Community Stakeholders to Evaluate the Design, Usability, and Acceptability of a Chronic Obstructive Pulmonary Disease Social Media Resource Center , 2015, JMIR research protocols.

[57]  W. V. van Harten,et al.  Development of MijnAVL, an Interactive Portal to Empower Breast and Lung Cancer Survivors: An Iterative, Multi-Stakeholder Approach , 2015, JMIR research protocols.

[58]  L. Freedman,et al.  Women know best--findings from a thematic analysis of 5,214 surveys of abortion care experience. , 2014, Women's health issues : official publication of the Jacobs Institute of Women's Health.

[59]  Y. Miller,et al.  What women want: qualitative analysis of consumer evaluations of maternity care in Queensland, Australia , 2014, BMC Pregnancy and Childbirth.

[60]  G. Lyratzopoulos,et al.  Cancer patient experience, hospital performance and case mix: evidence from England. , 2014, Future oncology.

[61]  Jelena Mirkovic,et al.  Supporting Cancer Patients in Illness Management: Usability Evaluation of a Mobile App , 2014, JMIR mHealth and uHealth.

[62]  Colin Tysall,et al.  A Systematic Review of the Impact of Patient and Public Involvement on Service Users, Researchers and Communities , 2014, The Patient - Patient-Centered Outcomes Research.

[63]  M. Bracher,et al.  Exploration and analysis of free-text comments from the 2013 Wales Cancer Patient Experience Survey (WCPES) , 2014 .

[64]  Elvin K. Wyly,et al.  Automated (post)positivism , 2014 .

[65]  Alison Richardson,et al.  Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness , 2014, BMC Health Services Research.

[66]  T. Khoshgoftaar,et al.  A review of data mining using big data in health informatics , 2014, Journal Of Big Data.

[67]  Qiaozhu Mei,et al.  Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis , 2014, ICML.

[68]  A. O’Cathain,et al.  Getting added value from using qualitative research with randomized controlled trials: a qualitative interview study , 2014, Trials.

[69]  H. Iversen,et al.  Patient evaluation of hospital outcomes: an analysis of open-ended comments from extreme clusters in a national survey , 2014, BMJ Open.

[70]  Julie Roberts,et al.  The Warwick Patient Experiences Framework: patient-based evidence in clinical guidelines. , 2014, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[71]  Louise Locock,et al.  Collecting data on patient experience is not enough: they must be used to improve care , 2014, BMJ : British Medical Journal.

[72]  Babis Theodoulidis,et al.  Analyzing Customer Experience Feedback Using Text Mining , 2014 .

[73]  N. Martin,et al.  Tracking and sustaining improvement initiatives: leveraging quality dashboards to lead change in a neurosurgical department. , 2014, Neurosurgery.

[74]  T. Sibanda,et al.  Adaptation and implementation of local maternity dashboards in a Zimbabwean hospital to drive clinical improvement. , 2014, Bulletin of the World Health Organization.

[75]  Sabine Van Huffel,et al.  Use of a group concept mapping approach to define learning outcomes for an interdisciplinary module in medicine , 2013, Perspectives on medical education.

[76]  Kristopher Reese,et al.  KnowYourColors: Visual dashboards for blood metrics and healthcare analytics , 2013, IEEE International Symposium on Signal Processing and Information Technology.

[77]  Nadim Anani,et al.  Integrated information visualization to support decision making for use of antibiotics in intensive care: design and usability evaluation , 2013, Informatics for health & social care.

[78]  M. Chao,et al.  Patient perspectives on care received at community acupuncture clinics: a qualitative thematic analysis , 2013, BMC Complementary and Alternative Medicine.

[79]  Kalina Bontcheva,et al.  TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text , 2013, RANLP.

[80]  K. Seers,et al.  Patient and public involvement in the implementation of evidence into practice , 2013, Evidence-Based Nursing.

[81]  A. Glaser,et al.  Qualitative analysis of patients’ feedback from a PROMs survey of cancer patients in England , 2013, BMJ Open.

[82]  H. Daudt,et al.  Enhancing the scoping study methodology: a large, inter-professional team’s experience with Arksey and O’Malley’s framework , 2013, BMC Medical Research Methodology.

[83]  J. Browne,et al.  Does providing feedback on patient-reported outcomes to healthcare professionals result in better outcomes for patients? A systematic review , 2013, Quality of Life Research.

[84]  C. May Towards a general theory of implementation , 2013, Implementation Science.

[85]  Kalina Bontcheva,et al.  Getting More Out of Biomedical Documents with GATE's Full Lifecycle Open Source Text Analytics , 2013, PLoS Comput. Biol..

[86]  A. Busse,et al.  Voluntary treatment, not detention, in the management of opioid dependence. , 2013, Bulletin of the World Health Organization.

[87]  Jette Ammentorp,et al.  The value of open-ended questions in surveys on patient experience: number of comments and perceived usefulness from a hospital perspective. , 2012, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[88]  Zein Kallas,et al.  A Dual response choice experiments (DRCE) design to assess rabbit meat preference in Catalonia: A Heterocscedatistic extreme-value model , 2012 .

[89]  Brian R Needham The Truth About Patient Experience: What We Can Learn from Other Industries, and How Three Ps Can Improve Health Outcomes, Strengthen Brands, and Delight Customers , 2012, Journal of healthcare management / American College of Healthcare Executives.

[90]  G. Velikova,et al.  Cancer patients’ and clinicians’ opinions on the best time in secondary care to approach patients for recruitment to longitudinal questionnaire-based research , 2012, Supportive Care in Cancer.

[91]  Mary Kane,et al.  Quality and rigor of the concept mapping methodology: a pooled study analysis. , 2012, Evaluation and program planning.

[92]  D. Barron,et al.  The National Adult Inpatient Survey conducted in the English National Health Service from 2002 to 2009: how have the data been used and what do we know as a result? , 2012, BMC Health Services Research.

[93]  Richard Churchman,et al.  Free-Text Comments , 2012, The American journal of hospice & palliative care.

[94]  Khaled M Musallam,et al.  Implementation of an emergency department computer system: design features that users value. , 2011, The Journal of emergency medicine.

[95]  Jean-Guy Meunier,et al.  Text Mining Methods for Social Representation Analysis in Large Corpora , 2011 .

[96]  Rosemary Barber,et al.  The GRIPP checklist: Strengthening the quality of patient and public involvement reporting in research , 2011, International Journal of Technology Assessment in Health Care.

[97]  J. Sims-Gould,et al.  “I'm Satisfied … But”: Clients' and Families' Contingent Responses About Home Care , 2011, Home health care services quarterly.

[98]  J. Archer,et al.  Factors that might undermine the validity of patient and multi‐source feedback , 2011, Medical education.

[99]  P. Kofoed,et al.  Semi-customizing patient surveys: linking results and organizational conditions. , 2011, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[100]  Julie L Cidell,et al.  Content clouds as exploratory qualitative data analysis , 2010 .

[101]  A. Edwards,et al.  Exploring patients’ self-reported experiences of out-of-hours primary care and their suggestions for improvement: a qualitative study , 2010, Family practice.

[102]  Susan Halford,et al.  RECONCEPTUALIZING DIGITAL SOCIAL INEQUALITY , 2010 .

[103]  D. Levac,et al.  Scoping studies: advancing the methodology , 2010, Implementation science : IS.

[104]  Shubhajit Roy Chowdhury,et al.  Development of a FPGA based fuzzy neural network system for early diagnosis of critical health condition of a patient , 2010, Comput. Biol. Medicine.

[105]  Yue Xu,et al.  State-of-the-art review on opinion mining from online customers' feedback , 2009 .

[106]  Urs Winter-Pfändler,et al.  Are Surveys on Quality Improvement of Healthcare Chaplaincy Emotionally Distressing for Patients? A Pilot Study , 2009, Journal of health care chaplaincy.

[107]  Lifford McLauchlan,et al.  Enabling a Common and Consistent Enterprise-Wide Terminology: An Initial Assessment of Available Tools , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[108]  M. Capuzzo,et al.  Is it possible to measure and improve patient satisfaction with anesthesia? , 2008, Anesthesiology clinics.

[109]  W. Greene,et al.  Discrete Choice Modeling , 2007 .

[110]  Mary Kane,et al.  Concept Mapping for Planning and Evaluation , 2006 .

[111]  Emily Lancsar,et al.  Deleting 'irrational' responses from discrete choice experiments: a case of investigating or imposing preferences? , 2006, Health economics.

[112]  R. Maljanian,et al.  Patient satisfaction measurement in the disease management industry. , 2005, Disease management : DM.

[113]  W. Greene,et al.  Applied Choice Analysis: A Primer , 2005 .

[114]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[115]  H. Arksey,et al.  Scoping studies: towards a methodological framework , 2005 .

[116]  G. Robert,et al.  Diffusion of innovations in service organizations: systematic review and recommendations. , 2004, The Milbank quarterly.

[117]  Eeva M. Pilke Flow experiences in information technology use , 2004, Int. J. Hum. Comput. Stud..

[118]  Terry Elrod,et al.  A new integrated model of noncompensatory and compensatory decision strategies , 2004 .

[119]  M. Ryan,et al.  Modelling non-demanders in choice experiments. , 2004, Health economics.

[120]  Machdel C. Matthee,et al.  Differentiating data- and text-mining terminology , 2003 .

[121]  William M. K. Trochim,et al.  Concept Mapping as an Alternative Approach for the Analysis of Open-Ended Survey Responses , 2002 .

[122]  J. R. DeShazo,et al.  Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency , 2002 .

[123]  Joffre Swait,et al.  Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice , 2001 .

[124]  Joffre Swait,et al.  A NON-COMPENSATORY CHOICE MODEL INCORPORATING ATTRIBUTE CUTOFFS , 2001 .

[125]  A. V. Lamsweerde Goal-oriented requirements engineering: a guided tour , 2001, Proceedings Fifth IEEE International Symposium on Requirements Engineering.

[126]  A. Zaslavsky,et al.  Adjusting for Patient Characteristics When Analyzing Reports From Patients About Hospital Care , 2001, Medical care.

[127]  J. Swait,et al.  The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching , 2001 .

[128]  Richard Giordano,et al.  Participant stakeholder evaluation as a design process , 2000, CUU '00.

[129]  C. Weisman,et al.  Gender and patient satisfaction with primary care: tuning in to women in quality measurement. , 2000, Journal of women's health & gender-based medicine.

[130]  K. A. Sturrock,et al.  A Multidimensional Scaling Stress Evaluation Table , 2000 .

[131]  Jakob Nielsen,et al.  Designing web usability , 1999 .

[132]  J. Calder Survey research methods , 1998, Medical education.

[133]  Gustavo Rossi,et al.  An Object Oriented Approach to Web-Based Applications Design , 1998, Theory Pract. Object Syst..

[134]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[135]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[136]  Joel Huber,et al.  The Importance of Utility Balance in Efficient Choice Designs , 1996 .

[137]  Jill Gerhardt-Powals Cognitive engineering principles for enhancing human-computer performance , 1996, Int. J. Hum. Comput. Interact..

[138]  R. Rust,et al.  Return on Quality (ROQ): Making Service Quality Financially Accountable , 1995 .

[139]  Jakob Nielsen Heuristic evaluation , 1994 .

[140]  Iris Vessey,et al.  Cognitive Fit: A Theory‐Based Analysis of the Graphs Versus Tables Literature* , 1991 .

[141]  A. Hochschild,et al.  The Managed Heart: Commercialization of Human Feeling. , 1985 .

[142]  C. Manski The structure of random utility models , 1977 .

[143]  R. Dawes,et al.  Linear models in decision making. , 1974 .

[144]  S. Rosen Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition , 1974, Journal of Political Economy.

[145]  Norman C. Dalkey,et al.  Experimental Assessment of Delphi Procedures with Group Value Judgments , 1971 .

[146]  K. Lancaster A New Approach to Consumer Theory , 1966, Journal of Political Economy.

[147]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[148]  J. Kruskal Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis , 1964 .

[149]  Kalina Bontcheva,et al.  Crowdsourcing Named Entity Recognition and Entity Linking Corpora , 2017 .

[150]  John L. Gore,et al.  Design and feasibility of integrating personalized PRO dashboards into prostate cancer care , 2016, J. Am. Medical Informatics Assoc..

[151]  Jianhe Xiao,et al.  Appropriate time for assessing patient satisfaction with cataract surgery care. , 2011, Journal of cataract and refractive surgery.

[152]  P. Rumrill,et al.  Using scoping literature reviews as a means of understanding and interpreting existing literature. , 2010, Work.

[153]  Allan Hanbury,et al.  Advances in Multidisciplinary Retrieval, First Information Retrieval Facility Conference, IRFC 2010, Vienna, Austria, May 31, 2010. Proceedings , 2010, IRFC.

[154]  Amir Ghazvinian Star Quality: Sentiment Categorization of Restaurant Reviews , 2010 .

[155]  Jakob Nielsen,et al.  Severity Ratings for Usability Problems , 2006 .

[156]  J. Nielsen F-shaped pattern for reading Web content, Jakob Nielsen's Alertbox , 2006 .

[157]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[158]  L. Marcinowicz,et al.  [Methodologic difficulties in measuring patient satisfaction--discrepancy coming from formulating questions]. , 2002, Wiadomosci lekarskie.

[159]  H. Bernard,et al.  Data Management and Analysis Methods , 2000 .

[160]  David Tripp Critical incidents in action inquiry , 1998 .

[161]  Lois W. Sayrs Interviews : an introduction to qualitative research interviewing , 1996 .

[162]  Joel Huber,et al.  A General Method for Constructing Efficient Choice Designs , 1996 .

[163]  André de Palma,et al.  Rational Choice under an Imperfect Ability to Choose , 1994 .

[164]  J. Kitzinger The methodology of focus groups: the importance of interaction between research participants , 1994 .

[165]  Jakob Nielsen,et al.  Chapter 4 – The Usability Engineering Lifecycle , 1993 .

[166]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .