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از ساعت 7 صبح تا 10 شب
ویرایش: [2 ed.]
نویسندگان: LLOYD P MURRAY SANDRA PROVOST
سری:
ISBN (شابک) : 9781119690139, 1119690137
ناشر: JOHN WILEY & SONS
سال نشر: 2022
تعداد صفحات: [649]
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 32 Mb
در صورت تبدیل فایل کتاب the HEALTH CARE DATA GUIDE : learning from data for improvement. به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب راهنمای داده های مراقبت های بهداشتی: یادگیری از داده ها برای بهبود. نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
یک متن ضروری برای تبدیل دادههای خام به بهبودهای ملموس مراقبتهای بهداشتی اکنون در ویرایش دوم خود، راهنمای دادههای مراقبت سلامت: یادگیری از دادهها برای بهبود، طرحی کاربردی برای استفاده از دادههای موجود برای بهبود نتایج مراقبتهای بهداشتی ارائه میدهد. در این کتاب، تیمی از نویسندگان برجسته بررسی میکنند که چگونه پزشکان، محققان و سایر متخصصان مراقبتهای بهداشتی میتوانند با اطمینان، پیشرفتها و تغییرات مراقبتهای بهداشتی را برنامهریزی و اجرا کنند، در حالی که اطمینان حاصل میشود که این تغییرات واقعاً باعث بهبود میشوند. این کتاب منبع کاملی برای راهنمای بهبود: رویکردی عملی برای افزایش عملکرد سازمانی، ویرایش دوم است و بحثهای کاملی در مورد نحوه استفاده از دادهها برای آزمایش، تطبیق، پیادهسازی و مقیاسبندی تغییرات مثبت سازمانی ارائه میدهد. راهنمای دادههای مراقبت بهداشتی: یادگیری از دادهها برای بهبود، ویرایش دوم ارائه میکند: استراتژیهایی با استفاده آسان برای یادگیری آسانتر از دادههای مراقبتهای بهداشتی موجود راهنمایی واضح در مورد مفیدترین نمودار برای انواع مختلف دادههای مورد استفاده در مراقبتهای بهداشتی. روش گامی برای استفاده از دادههای بسیار انباشته برای بهبود نمونههایی از استفاده از دادههای سطح بیمار در مراقبت روشهای متعدد برای استفاده از دادههای بازخورد بیمار و دیگر روشهای بسیار بهتر برای مشاهده دادهها برای رهبری اجرایی راهحلهایی برای کار با دادههای رویدادهای نادر، فصلی و سایر مسائل مزاحم استفاده از روشهای بهبود با دادههای اپیدمی مطالعات موردی بهبود با استفاده از دادهها برای یادگیری منبعی باید برای کسانی که متعهد به بهبود مراقبتهای بهداشتی هستند، از جمله متخصصان بهداشتی متحد در تمام جنبههای مراقبتهای بهداشتی، پزشکان، مدیران، رهبران مراقبتهای بهداشتی و محققان مطالعه شود. .
An Essential text on transforming raw data into concrete health care improvements Now in its second edition, The Health Care Data Guide: Learning from Data for Improvement delivers a practical blueprint for using available data to improve healthcare outcomes. In the book, a team of distinguished authors explores how health care practitioners, researchers, and other professionals can confidently plan and implement health care enhancements and changes, all while ensuring those changes actually constitute an improvement. This book is the perfect companion resource to The Improvement Guide: A Practical Approach to Enhancing Organizational Peformance, Second Edition, and offers fulsome discussions of how to use data to test, adapt, implement, and scale positive organizational change. The Health Care Data Guide: Learning from Data for Improvement, Second Edition provides: Easy to use strategies for learning more readily from existing health care data Clear guidance on the most useful graph for different types of data used in health care A step-by-step method for making use of highly aggregated data for improvement Examples of using patient-level data in care Multiple methods for making use of patient and other feedback data A vastly better way to view data for executive leadership Solutions for working with rare events data, seasonality and other pesky issues Use of improvement methods with epidemic data Improvement case studies using data for learning A must read resource for those committed to improving health care including allied health professionals in all aspects of health care, physicians, managers, health care leaders, and researchers.
THE HEALTH CARE DATA GUIDE Contents Figures, Tables, and Exhibits Preface The Authors About the Companion Website Part I Using Data for Improvement Chapter 1 Improvement Methodology Fundamental Questions for Improvement What Are We Trying to Accomplish? How Will We Know that a Change is an Improvement? What Changes Can We Make That Will Result in Improvement? The PDSA Cycle for Improvement Tools and Methods to Support the Model for Improvement Designing PDSA Cycles for Testing Changes Analysis of Data from PDSA Cycles Summary Key Terms Chapter 2 Using Data for Improvement What Does the Concept of Data Mean? How are Data Used? Types of Data Using A Family of Measures The Importance of Operational Definitions Sampling Sampling Strategies What About Sample Size? Stratification of Data What about Case-Mix Adjustment? Transforming Data Analysis and Presentation of Data Summary Key Terms Chapter 3 Understanding Variation Using Run Charts Introduction What Is a Run Chart? Use of a Run Chart Constructing a Run Chart Examples of Run Charts for Improvement Projects Rules to Aid in Interpreting Run Charts Special Issues in Using Run Charts Stratification with Run Charts Using the Cumulative Sum Statistic with Run Charts Summary Key Terms Chapter 4 Learning from Variation in Data The Concept of Variation Introduction to Shewhart Charts Depicting and Interpreting Variation Using Shewhart Charts The Role of Annotation with Shewhart Charts Establishing Limits for Shewhart Charts Revising Limits for Shewhart Charts Stratification with Shewhart Charts Shewhart Charts and Targets, Goals, or Other Specifications Special Cause: Is It Good or Bad? Summary Key Terms Chapter 5 Understanding Variation Using Shewhart Charts Selecting the Type of Shewhart Chart Shewhart Charts for Continuous Data I Charts Examples of Shewhart Charts for Individual Measurements Rational Ordering with an I Chart Example of I Chart for Deviations from a Target Xbar S Shewhart Charts Shewhart Charts for Attribute Data Subgroup Size for Attribute Charts The P Chart for Classification Data Examples of P Charts Creation of Funnel Limits for a P Chart Shewhart Charts for Counts of Nonconformities C Charts U Chart Creation of Funnel Limits for a U Chart Alternatives for Attribute Charts for Rare Events G Chart for Opportunities between Rare Events T Chart for Time between Rare Events Process Capability Process Capability from an I Chart Capability of a Process from Xbar and S Charts Capability of a Process from Attribute Control Charts Capability from a P Chart Capability from a C or U Chart Summary Key Terms Appendix 5.1 Calculating Shewhart Limits I Chart (For Individual Values Of Continuous Data) Xbar S Chart (For Continuous Data In Subgroups) P Chart (For Classification Data) C Chart (Count Of Incidences) U Chart (Incidences Per Area Of Opportunity) G Chart (Cases Between Incidences) T Chart Chapter 6 Additional Tools For Understanding Variation In Data Depicting Variation Additional Tools for Learning from Variation Frequency Plots Frequency Plot Construction Frequency Plots Used with Shewhart Charts Frequency Plots and Stratification Pareto Charts Pareto Chart Construction Pareto Charts Used with Shewhart Charts Pareto Chart and Stratification Scatterplots Scatterplot Construction Scatterplots Used with Shewhart Charts Scatterplots and Stratification Radar Charts Constructing a Radar Chart Radar Charts Used with Shewhart Charts Radar Charts and Stratification Summary Key Terms Chapter 7 Shewhart Chart Savvy: Dealing with Common Issues Creating Effective Shewhart Charts Tip 1: Type of Data and Subgroup Size Tip 2: Rounding Data Tip 3: Formatting Charts Tip 4. Decisions for Recalculating limits, or Rephasing, on a Shewhart Chart Extending Centerline and Limits Backward Typical Problems with Software for Calculating Shewhart Charts Characteristics to Consider When Purchasing SPC Software Another Caution with I Charts and Chart Selection Guidelines for Shewhart Charts in Research Studies and Publications Use of Shewhart Charts in Research Studies Shewhart Charts in Publications Shewhart’s Theory versus Statistical Inference Summary Key Terms Part II Advanced Theory and Methods with Data For Improvement Chapter 8 More Shewhart-Type Charts Other Shewhart-Type Charts The NP Chart Xbar Range (Xbar R) Chart Median Chart Attribute Charts with Large Subgroup Sizes (P’ and U’) Prime Charts (P’ and U’) Negative Binomial Chart Some Adaptations to Shewhart Charts MA Chart CUSUM Chart Exponentially Weighted Moving Average (EWMA) Chart Standardized Shewhart Charts Multivariate Shewhart-Type Charts Summary Key Terms Chapter 9 Special Uses for Shewhart Charts Shewhart Charts with a Changing Centerline Shewhart Charts with a Sloping Centerline Shewhart Charts with Seasonal Effects Adjusting Shewhart Charts for Confounders Transformation of Data with Shewhart Charts Shewhart Charts for Autocorrelated Data Risk-Adjusted or Case-Mix Adjusted Shewhart Charts Comparison Charts Confidence Intervals and Confidence Limits Summary Key Terms Chapter 10 Drilling Down into Aggregate Data for Improvement II What are Aggregate Data? What is the Challenge Presented by Aggregate Data? Introduction to the Drill Down Pathway Stratification Sequencing Rational Subgrouping An Illustration of the Drill Down Pathway: Adverse Drug Events Drill Down Pathway Step One Drill Down Pathway Step Two Drill Down Pathway Step Three Drill Down Pathway Step Three, Continued Drill Down Pathway Step Three, Continued Drill Down Pathway Step Four Drill Down Pathway Step Five Drill Down Pathway Step Six Summary Key Terms Part III Applications of Shewhart Charts in Health Care Chapter 11 Learning from Individual Patient Data Examples of Shewhart Charts for Individual Patients Example 1: Asthma Patient Use of Shewhart Charts Example 2: Prostate-Specific Antigen (PSA) Screening for Prostate Cancer Example 3: Monitoring Patient Measures in the Hospital Example 4: Bone Density for a Patient Diagnosed with Osteoporosis Example 5: Temperature Readings for a Hospitalized Patient Example 6: Shewhart Charts for Continuous Monitoring of Patients Example 7: Monitoring Weight Example 8: Monitoring Blood Sugar Control for Patients with Diabetes Example 9: Using Shewhart Charts in Pain Management Summary Chapter 12 Learning from Patient Feedback to Improve Care Summarizing Patient Feedback Data Presentation of Patient Satisfaction Data Using Patient Feedback for Improvement The PDSA Cycle for Testing and Implementing Changes Improvement Team Working on Clinic Satisfaction Improvement Team Working on Pain Feedback from Employees Using Patient Satisfaction Data in Planning for Improvement Special Issues with Patient Feedback Data Are There Challenges When Summarizing and Using Patient Satisfaction Survey Data? Does Survey Scale Matter? Summary Key Terms Chapter 13 Using Shewhart Charts in Health Care Leadership A Health Care Organization’s Vector of Measures Developing a VOM So How do We Best Display a VOM? Administrative Issues with a VOM Some Examples of Measures for Other VOMs Emergency Department Primary Care Center System Flow Measures Health Authority Large Urban Hospital IHI Whole System Measures Summary Key Terms Chapter 14 Shewhart Charts for Epidemic Data Shewhart Charts in Epidemiology Development of Shewhart Charts for Epidemic Data C Charts (Epoch 1) Charts of Epoch 2 Charts for Epoch 3 Charts for Epoch 4 Some Issues with the Hybrid Chart for COVID-19 Deaths Data Quality Day-of-the-Week Adjustment Application of the Hybrid Charts to Cases, Hospitalizations, and Intensive Care Unit Admissions Summary Key Term Chapter 15 Case Studies Case Study A: Improving Access to a Specialty Care Clinic Case Study B: Radiology Improvement Projects Case Study C: Reducing Post-Cabg Infections Case Study D: Drilling Down into Percentage of C-Sections Case Study E: Reducing Length of Stay After Surgery Case Study F: Reducing Hospital admissions Case Study G: Accidental Puncture/Laceration Rate Case Study H: Improving Telemedicine Failed Calls and No Shows Case Study I: Variation in Financial Data Index Shewhart Chart Selection Guide EULA