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Data-driven healthcare [[electronic resource] ] : how analytics and BI are transforming the industry
Data-driven healthcare [[electronic resource] ] : how analytics and BI are transforming the industry
Autore Madsen Laura B. <1973->
Pubbl/distr/stampa Hoboken, : Wiley, 2014
Descrizione fisica 1 online resource (219 p.)
Disciplina 362.1068/4
Collana Wiley and SAS Business Series
Soggetto topico Health services administration - Data processing
Medical informatics
Big data
Health Care Sector
Confidentiality
Data Interpretation, Statistical
Forms and Records Control
Medical Records
Health insurance - Finance - United States
Business intelligence - United States
ISBN 1-119-20501-8
1-118-97388-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910132160203321
Madsen Laura B. <1973->  
Hoboken, : Wiley, 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data-driven healthcare : how analytics and BI are transforming the industry
Data-driven healthcare : how analytics and BI are transforming the industry
Autore Madsen Laura B. <1973->
Edizione [1st ed.]
Pubbl/distr/stampa Hoboken, : Wiley, 2014
Descrizione fisica 1 online resource (219 p.)
Disciplina 362.1068/4
Collana Wiley and SAS Business Series
Soggetto topico Health services administration - Data processing
Medical informatics
Big data
Health Care Sector
Confidentiality
Data Interpretation, Statistical
Forms and Records Control
Medical Records
Health insurance - Finance - United States
Business intelligence - United States
ISBN 1-119-20501-8
1-118-97388-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Data-Driven Healthcare -- Contents -- Foreword -- For the Skimmers -- Acknowledgments -- Chapter 1 What Does Data Mean to You? -- The Gap -- Data Is a Four-Letter Word -- Strengths -- Weaknesses -- Opportunities -- Threats -- Setting the Stage -- Is This Book for You? -- References -- Chapter 2 What Happens When You Use Data to Transform an Industry? -- The History of Change -- On the Brink -- What Is "Data Driven," and Why Does It Matter? -- Management and Measurement -- Planning the Approach -- RISE -- Reduce the Unknowns -- Identify the Alternatives -- Streamline the Standards -- Evaluate the Activities -- Change Mechanisms of RISE -- Revolution -- References -- Chapter 3 How the Lack of Data Standardization Impedes Data-Driven Healthcare -- Healthcare Data Complexity -- Moving Data -- Data Is Your Asset-Manage It That Way -- Standards . . . Because Everyone Else Has Them -- Pareto's Principle -- The Great Wall of Data -- References -- Note -- Chapter 4 Adopting Your Data Warehouse for the Next Step in BI Maturity -- Go Boldly -- Disruptive Technologies -- Hadoop, the Cloud, and Modern Data Platforms -- The New Way Forward -- Reduce the Unknowns -- Identify the Alternatives -- Standardize -- Evaluate and Improve -- The Future Is Now -- Chapter 5 Creating a Data-Driven Healthcare Organization -- IT or the Business? -- Training -- What and How Should We Teach? -- Governing Data for Our New MDP -- Chapter 6 Applying "Big Data" to Change Healthcare -- The Call of Big Data -- Evolve or Die -- Let's Organize This and Take All the Fun Out of It -- Dipping Your Big Toe into Big Data -- References -- Chapter 7 Making Data Consumable -- How We Present Information Matters -- When We Present the Information Matters, Too -- Why Do We Want to Visually Represent Our Data? -- Learning a New Language -- A Multimedia Approach to Consumable Data.
References -- Chapter 8 Data Privacy and Confidentiality: A Brave New World -- Who Owns the Data? -- Barriers Are Everywhere -- Process and Technology -- Reference -- Chapter 9 A Call to Action -- Applying RISE to Your Efforts -- Some Distinctions about Being New -- Getting Started -- You Know What They Say about Assuming -- What Does Data Mean to You? -- Transforming an Industry -- Data Standardization -- The Next Step in BI Maturity -- Creating the DDHO -- "Big Data" -- Make Your Data Consumable -- Privacy and Confidentiality -- Final Thoughts on Data-Driven Healthcare -- Appendix A Readiness for Change -- Appendix B Tenets of Healthcare BI -- Appendix C Estimating the Efforts -- Appendix D Business Metrics -- Appendix E Agenda | Company Name | JAD Session -- Appendix F Data Visualization Guide -- Afterword -- About the Author -- Index -- EULA.
Record Nr. UNINA-9910814457903321
Madsen Laura B. <1973->  
Hoboken, : Wiley, 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Autore Penta Massimo
Pubbl/distr/stampa [Place of publication not identified], : Mardaga, 2005
Soggetto topico Statistics as Topic
Decision Support Techniques
Models, Theoretical
Medical Informatics Applications
Investigative Techniques
Health Care Evaluation Mechanisms
Epidemiologic Methods
Quality of Health Care
Analytical, Diagnostic and Therapeutic Techniques and Equipment
Medical Informatics
Public Health
Health Care Quality, Access, and Evaluation
Information Science
Environment and Public Health
Health Care
Data Interpretation, Statistical
Models, Statistical
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione fre
Record Nr. UNINA-9910159401003321
Penta Massimo  
[Place of publication not identified], : Mardaga, 2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Autore Penta Massimo
Pubbl/distr/stampa [Place of publication not identified], : Mardaga, 2005
Soggetto topico Statistics as Topic
Decision Support Techniques
Models, Theoretical
Medical Informatics Applications
Investigative Techniques
Health Care Evaluation Mechanisms
Epidemiologic Methods
Quality of Health Care
Medical Informatics
Public Health
Health Care Quality, Access, and Evaluation
Information Science
Environment and Public Health
Health Care
Data Interpretation, Statistical
Models, Statistical
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione fre
Record Nr. UNINA-9910788249203321
Penta Massimo  
[Place of publication not identified], : Mardaga, 2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
Autore Penta Massimo
Pubbl/distr/stampa [Place of publication not identified], : Mardaga, 2005
Soggetto topico Statistics as Topic
Decision Support Techniques
Models, Theoretical
Medical Informatics Applications
Investigative Techniques
Health Care Evaluation Mechanisms
Epidemiologic Methods
Quality of Health Care
Medical Informatics
Public Health
Health Care Quality, Access, and Evaluation
Information Science
Environment and Public Health
Health Care
Data Interpretation, Statistical
Models, Statistical
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione fre
Record Nr. UNINA-9910818883703321
Penta Massimo  
[Place of publication not identified], : Mardaga, 2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Empirical evaluation of the association between methodological shortcomings and estimates of adverse events
Empirical evaluation of the association between methodological shortcomings and estimates of adverse events
Pubbl/distr/stampa [Place of publication not identified], : U S Dept of Health and Human Services Agency for Healthcare Research and Quality, 2006
Descrizione fisica 1 online resource
Collana Technical Reviews
AHRQ publication
Soggetto topico Outcome Assessment, Health Care
Data Interpretation, Statistical
Soggetto genere / forma Review
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910698400803321
[Place of publication not identified], : U S Dept of Health and Human Services Agency for Healthcare Research and Quality, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Fatality and injury rates for two types of rotorcraft accidents [[electronic resource] ] : final report / / David Palmerton
Fatality and injury rates for two types of rotorcraft accidents [[electronic resource] ] : final report / / David Palmerton
Autore Palmerton David
Pubbl/distr/stampa Washington, DC : , : Federal Aviation Administration, Office of Aerospace Medicine, , [2005]
Descrizione fisica 1 volume : digital, PDF file
Soggetto topico Accidents, Aviation - mortality
Aircraft
Data Interpretation, Statistical
Wounds and Injuries - mortality
Helicopters - Accidents - Investigation
Aircraft accidents - Research
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Fatality and injury rates for two types of rotorcraft accidents
Record Nr. UNINA-9910694623603321
Palmerton David  
Washington, DC : , : Federal Aviation Administration, Office of Aerospace Medicine, , [2005]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
Autore Campbell Michael J. <1950->
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (268 p.)
Disciplina 610.72/4
Collana Statistics in Practice
Soggetto topico Randomized Controlled Trials as Topic
Data Interpretation, Statistical
Health Services Research - method
Research Design
ISBN 1-118-76360-2
1-118-76345-9
1-118-76359-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface; Acronyms and abbreviations; Chapter 1 Introduction; 1.1 Randomised controlled trials; 1.1.1 A-Allocation at random; 1.1.2 B-Blindness; 1.1.3 C-Control; 1.2 Complex interventions; 1.3 History of cluster randomised trials; 1.4 Cohort and field trials; 1.5 The field/community trial; 1.5.1 The REACT trial; 1.5.2 The Informed Choice leaflets trial; 1.5.3 The Mwanza trial; 1.5.4 The paramedics practitioner trial; 1.6 The cohort trial; 1.6.1 The PoNDER trial; 1.6.2 The DESMOND trial; 1.6.3 The Diabetes Care from Diagnosis trial; 1.6.4 The REPOSE trial
1.6.5 Other examples of cohort cluster trials 1.7 Field versus cohort designs; 1.8 Reasons for cluster trials; 1.9 Between- and within-cluster variation; 1.10 Random-effects models for continuous outcomes; 1.10.1 The model; 1.10.2 The intracluster correlation coefficient; 1.10.3 Estimating the intracluster correlation (ICC) coefficient; 1.10.4 Link between the Pearson correlation coefficient and the intraclass correlation coefficient; 1.11 Random-effects models for binary outcomes; 1.11.1 The model; 1.11.2 The ICC for binary data; 1.11.3 The coefficient of variation
1.11.4 Relationship between cvc and ρ for binary data 1.12 The design effect; 1.13 Commonly asked questions; 1.14 Websources; Exercise; Appendix 1.A; Chapter 2 Design issues; 2.1 Introduction; 2.2 Issues for a simple intervention; 2.2.1 Phases of a trial; 2.2.1.1 Preclinical; 2.2.1.2 Sequence of phases; 2.2.2 'Pragmatic' and 'explanatory' trials; 2.2.3 Intention-to-treat and per-protocol analyses; 2.2.4 Non-inferiority and equivalence trials; 2.3 Complex interventions; 2.3.1 Design of complex interventions; 2.3.1.1 Theory (preclinical); 2.3.2 Phase I modelling/qualitative designs
2.3.3 Pilot or feasibility studies 2.3.4 Example of pilot/feasibility studies in cluster trials; 2.4 Recruitment bias; 2.5 Matched-pair trials; 2.5.1 Design of matched-pair studies; 2.5.2 Limitations of matched-pairs designs; 2.5.3 Example of matched-pair design: The Family Heart Study; 2.6 Other types of designs; 2.6.1 Cluster factorial designs; 2.6.2 Example cluster factorial trial; 2.6.3 Cluster crossover trials; 2.6.4 Example of a cluster crossover trial; 2.6.5 Stepped wedge; 2.6.6 Pseudorandomised trials; 2.7 Other design issues; 2.8 Strategies for improving precision; 2.9 Randomisation
2.9.1 Reasons for randomisation 2.9.2 Simple randomisation; 2.9.3 Stratified randomisation; 2.9.4 Restricted randomisation; 2.9.5 Minimisation; Exercise; Appendix 2.A; Chapter 3 Sample size: How many subjects/clusters do I need for my cluster randomised controlled trial?; 3.1 Introduction; 3.1.1 Justification of the requirement for a sample size; 3.1.2 Significance tests, P-values and power; 3.1.3 Sample size and cluster trials; 3.2 Sample size for continuous data-comparing two means; 3.2.1 Basic formulae; 3.2.2 The design effect (DE) in cluster RCTs; 3.2.3 Example from general practice
3.3 Sample size for binary data-comparing two proportions
Record Nr. UNINA-9910139141103321
Campbell Michael J. <1950->  
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
Autore Campbell Michael J. <1950->
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (268 p.)
Disciplina 610.72/4
Collana Statistics in Practice
Soggetto topico Randomized Controlled Trials as Topic
Data Interpretation, Statistical
Health Services Research - method
Research Design
ISBN 1-118-76360-2
1-118-76345-9
1-118-76359-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface; Acronyms and abbreviations; Chapter 1 Introduction; 1.1 Randomised controlled trials; 1.1.1 A-Allocation at random; 1.1.2 B-Blindness; 1.1.3 C-Control; 1.2 Complex interventions; 1.3 History of cluster randomised trials; 1.4 Cohort and field trials; 1.5 The field/community trial; 1.5.1 The REACT trial; 1.5.2 The Informed Choice leaflets trial; 1.5.3 The Mwanza trial; 1.5.4 The paramedics practitioner trial; 1.6 The cohort trial; 1.6.1 The PoNDER trial; 1.6.2 The DESMOND trial; 1.6.3 The Diabetes Care from Diagnosis trial; 1.6.4 The REPOSE trial
1.6.5 Other examples of cohort cluster trials 1.7 Field versus cohort designs; 1.8 Reasons for cluster trials; 1.9 Between- and within-cluster variation; 1.10 Random-effects models for continuous outcomes; 1.10.1 The model; 1.10.2 The intracluster correlation coefficient; 1.10.3 Estimating the intracluster correlation (ICC) coefficient; 1.10.4 Link between the Pearson correlation coefficient and the intraclass correlation coefficient; 1.11 Random-effects models for binary outcomes; 1.11.1 The model; 1.11.2 The ICC for binary data; 1.11.3 The coefficient of variation
1.11.4 Relationship between cvc and ρ for binary data 1.12 The design effect; 1.13 Commonly asked questions; 1.14 Websources; Exercise; Appendix 1.A; Chapter 2 Design issues; 2.1 Introduction; 2.2 Issues for a simple intervention; 2.2.1 Phases of a trial; 2.2.1.1 Preclinical; 2.2.1.2 Sequence of phases; 2.2.2 'Pragmatic' and 'explanatory' trials; 2.2.3 Intention-to-treat and per-protocol analyses; 2.2.4 Non-inferiority and equivalence trials; 2.3 Complex interventions; 2.3.1 Design of complex interventions; 2.3.1.1 Theory (preclinical); 2.3.2 Phase I modelling/qualitative designs
2.3.3 Pilot or feasibility studies 2.3.4 Example of pilot/feasibility studies in cluster trials; 2.4 Recruitment bias; 2.5 Matched-pair trials; 2.5.1 Design of matched-pair studies; 2.5.2 Limitations of matched-pairs designs; 2.5.3 Example of matched-pair design: The Family Heart Study; 2.6 Other types of designs; 2.6.1 Cluster factorial designs; 2.6.2 Example cluster factorial trial; 2.6.3 Cluster crossover trials; 2.6.4 Example of a cluster crossover trial; 2.6.5 Stepped wedge; 2.6.6 Pseudorandomised trials; 2.7 Other design issues; 2.8 Strategies for improving precision; 2.9 Randomisation
2.9.1 Reasons for randomisation 2.9.2 Simple randomisation; 2.9.3 Stratified randomisation; 2.9.4 Restricted randomisation; 2.9.5 Minimisation; Exercise; Appendix 2.A; Chapter 3 Sample size: How many subjects/clusters do I need for my cluster randomised controlled trial?; 3.1 Introduction; 3.1.1 Justification of the requirement for a sample size; 3.1.2 Significance tests, P-values and power; 3.1.3 Sample size and cluster trials; 3.2 Sample size for continuous data-comparing two means; 3.2.1 Basic formulae; 3.2.2 The design effect (DE) in cluster RCTs; 3.2.3 Example from general practice
3.3 Sample size for binary data-comparing two proportions
Record Nr. UNINA-9910828428003321
Campbell Michael J. <1950->  
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
International journal of big data and analytics in healthcare
International journal of big data and analytics in healthcare
Pubbl/distr/stampa Hershey, PA : , : IGI Publishing, an imprint of IGI Global, , 2016-
Disciplina 610.285
Soggetto topico Medical informatics
Big data
Medical Informatics
Data Interpretation, Statistical
Soggetto genere / forma Periodical
Periodicals.
Soggetto non controllato Behavioral data
Big data for disease diagnosis
Clinical data
Clustering in electronic health records
Data mining
Data visualization
Environmental exposure data processing
Genetic data
Large-scale patient data
Medical imaging data
Personalized care through big data
Predictive modeling
Security issues
Text mining
Unstructured clinical notes
ISSN 2379-738X
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Altri titoli varianti IJBDAH
Record Nr. UNISA-996546858303316
Hershey, PA : , : IGI Publishing, an imprint of IGI Global, , 2016-
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui