دانلود کتاب Measuring Capacity to Care Using Nursing Data

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Front Matter Copyright About the authors Preface Organization of the book Acknowledgments Dynamic health care environments How is capacity to care defined? Healthcare environments What influences the capacity to care? Leadership and governance Healthcare financing Health workforce Medical products, devices and technologies Health service delivery Information and research What are the desired health system outcomes? Improved health, efficiency, responsiveness and caring Nursing data at the center Health care operational inefficiencies: Costly events Workforce management Nursing workloads and nurse staffing methods Measuring operational activity and efficiency Care recipient characteristics Types of resource input Healthcare activity processes Measuring health outcomes Learning health systems Making better use of data and information Operational research Digital transformation needs to measure nursing and midwifery care demands and workloads What determines nursing workloads? Nurse staffing methods in use or recommended Methods in use to measure nursing care demand Nursing Hours Per Patient Day Nurse staffing ratios Patient/client types Patient classification How do nursing service demand measurement methods compare? Patient type and treatment protocol patterns by clinical speciality Variables influencing nursing service demands, workloads, and costs Information flows and patient/client journeys Digital transformation enabling nursing data inclusion Nursing minimum data sets Nursing data and standards Reference terminologies Use of metadata Nursing service demand metadata Service capacity - Identifying required nursing skill mix Service capacity - Nursing working conditions Admission and continuing service determinants Indicators of nursing care demand Metadata enabling the evaluation of nursing service contributions relative to patient outcomes Nursing workload management metadata need Optimizing workplace efficiencies Political, professional, managerial, and industrial influencers Conclusion Nursing and midwifery work measurement methods and use Describing nursing work Boundaries or scope of nursing/midwifery practice Analyzing nursing work to be measured Work measurement methods Nursing staff availability and performance - Input variables A nursing practice taxonomy - Process variables Time study methodology Self-recording of nursing activity Work sampling methodology Professional judgments/estimates Conversion of work measurement data to a workload measure Making use of study results Using workload measurement systems with established time standards Nursing workload measures' validity Nursing work measures in use Patient classification principles Developing national nursing service weight measures Evidence of acuity link with patient outcomes Future directions Identifying skill mix needs Matching available skills with service demands Addressing qualified nurse staffing shortages Working with a varied skill mix Working to scope Current skill mix identification methods Specializations and competencies Occupational classifications Nursing industry awards, agreements and skill mix Job evaluation and skill assessment methods Skills Framework for the Information Age (SFIA) Education and professional development contributions Nursing career pathways Re-engineering clinical services using non-nursing support staff Example Future directions for identifying and matching skill mix needs with available staffing resources Nursing and organizational models of care Factors known to influence nursing models of care The nursing process - Conceptual base for nursing practice Nursing care plans Functional or task allocation Patient allocation Primary nursing Team nursing - A collaborative model of care Small team nursing The benefits of small team nursing Leading the change The shift routine example Evaluate success of team nursing implementation Inter and multidisciplinary models of care Organizational models of care influencing patient outcomes Success factors Staffing resource allocation, budgets and management Using demand side organizational nursing and midwifery workforce planning methods Professional and government nurse staffing initiatives Rostering fundamentals Data variables required to calculate nurse staffing needs Projecting nursing service demand and workforce requirements Calculating departmental/unit nurse staffing requirements Use of nurse:patient ratios to capture FTE/WTE measures for clinical care Use of Nursing (Care) Hours Per Patient Day (NHPPD) Use of patient acuity data Using patient demand measures to calculate staff establishments Staffing needs for other service types Day only departments Obstetric services Geriatric, disability and rehabilitation residential services Operating theaters Accident and emergency departments Specialist outpatient departments Supervisory and administrative clinical staff Significant variations resulting from method used An international patient type HPPD benchmarking research study Rostering methods Foundations for roster development Cyclic rostering Self rostering Request focus rostering Rostering process Rostering principles Evaluating the suitability of rosters Roster reengineering Workforce availability Financial management Roster budgeting processes based on service demand Staffing establishment budgeting processes Zero based budgeting Activity based costing (ABC)/funding (ABF) Casemix definitions (hospital `products) Use of casemix classifications and nursing service costs Connectivity requirements for nursing resource management Linking electronic health records with nursing resource management Capturing and using the data operationally Workforce planning Nursing and Midwifery Workforce Statistics Nursing and midwifery's future perspectives Nursing workforce structures and statistics Nursing and midwifery workforce education and professional development Workforce planning models and tools Recruitment to the profession Workforce participation Employment characteristics Retention and turnover rates Causes of dissatisfaction and turnover Replacement and succession planning Meeting future demands Digital health ecosystems: Use of informatics, connectivity and system interoperability A need to resolve data issues What is a digital health ecosystem? Essential ecosystem features Healthcare ecosystem connectivity frameworks Today's state of the art Shadow systems and health data Connectivity and interoperability Measuring interoperability Interoperability standards and schema Computing platforms Interoperability, clinical needs and secondary data use Using source data and information for multiple purposes Decision support systems - Using secondary data National and international health data uses National and international reporting - An example Genomics data and personalized medicine Gap analysis and digital transformation Conclusion A digital transformation strategy enabling nursing data use System implementation and change management Changing organizational digital health infrastructures Common barriers Using `Lean and `Six Sigma techniques to design new work processes Potential use of nursing data Patient acuity/nurse dependency/nurse-patient ratios Work hours per patient day/visit/procedure/attendance/birth/occasion of service/operating minute etc. Workload management Workforce planning Care capacity management Pathways and care plans with outcome reporting Nursing intensity measures Retrospective and proactive discharge analysis Diet ordering Rostering for clinical and non-clinical departments Clinical handovers Allied health intervention register and reporting Patient risk assessments with action plans Human resource management registers and staff health profiles with reports Staff health system Efficiency measures/benchmarking all departments Patient acuity and workload management system implementation project plan - A generic example using legacy systems Aim of the plan Objectives of the plan are to provide Organizational benefits of implementing the system Scope of project Project priorities Project prerequisite Software development project team Project lead: Primary (lead) and secondary IT support: Primary (lead) and secondary Clinical support Governance structure Hospital project sponsor Project manager System co-ordinator/administrator IT lead for the project (organization wide) Technical lead (hospital based) Executive lead for motivational strategy Resource allocation and task allocation for system implementation Risk assessment Risk rating matrix scale Desired outcome measures benefitting nurses and their patients Data collection methods Measuring patient acuity on a shift Local nursing acuity data use Allocating staff to workloads Handovers Workforce planning Ward/unit manager/senior nurse daily routines to ensure data accuracy Health IT evaluation methods A nursing workload management system and change management evaluation framework Measuring health service quality What is quality? Quality programs Nursing practice environments influencing quality Collegial cultures Data quality Health data uses and links to nursing data Using data to support decision making Data sets and data repositories Data governance mechanisms Standards, accreditation and governance Accreditation standards Types of standards Standards governance Reliability and quality measures associated with patient acuity data Clinical data management issues Outcomes research and big data Performance indicators and health system frameworks Measuring caring as an outcome measure Impact of funding arrangements on the selection of performance indicators Big data management and governance Health quality measurement issues References Residential and community care management Introduction Residential care environments Measuring care service demand and funding mechanisms Residential service work measurement methods and outcomes Identifying skill mix needs Organizational and nursing models of care Staffing resource management Aged care workforce planning Use of informatics, digital transformation Documentation, reporting and change management Measuring service quality Qualify of life-future vision References Current and future vision Global health and capacity to care Nurses and midwives' unique contributions to global health Our digital health ecosystem Measuring health system effectiveness Hospital performance statistics and costs Safe patient care vs costs Benefits from using nursing data Optimizing our capacity to care in a sustainable health system Close the loop between resource flows into and out of the system Nursing workload analysis Nursing and midwifery work characteristics and measurements The nursing and midwifery workforce Digital transformation needs A future vision References Case study 1 — Patient Assessment and Information System (PAIS): Work measurement research and workload measurement method ... Study purpose Original sample Methods Research objectives Original study design Data analysis Findings Results Staffing methodology development PAIS implementation and use Use of PAIS in New South Wales, Queensland and Western Australia Discussion Issues encountered Political interference References Case Study 2 - Design, development and use of the TrendCare system Study purpose Original sample Research objective Methods Study design Data analysis Findings Results Staffing methodology development TrendCare implementation and use Discussion Validation and endorsement Lessons learned References Index A B C D E F G H I J L M N O P Q R S T U V W Z