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E-raamat: Measuring Capacity to Care Using Nursing Data

(CEO and Director, eHealth Education Pty Ltd, East Melbourne, VIC, Australia), (CEO and Director, Trend Care Systems Pty Ltd, Brisbane, QLD, Australia
CEO and Director, Trend Care Systems UK Ltd, Manchester, United Kingdom
Founder )
  • Formaat: 498 pages
  • Ilmumisaeg: 13-Mar-2020
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128169780
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  • Formaat: 498 pages
  • Ilmumisaeg: 13-Mar-2020
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128169780

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Measuring Capacity to Care Using Nursing Data presents evidence-based solutions regarding the adoption of safe staffing principles and the optimum use of operational data to enable health service delivery strategies that result in improved patient and organizational outcomes. Readers will learn how to make better use of informatics to collect, share, link and process data collected operationally for the purpose of providing real-time information to decision- makers. The book discusses topics such as dynamic health care environments, health care operational inefficiencies and costly events, how to measure nursing care demand, nursing models of care, data quality and governance, and big data.

The content of the book is a valuable source for graduate students in informatics, nurses, nursing managers and several members involved in health care who are interested in learning more about the beneficial use of informatics for improving their services.

  • Presents and discusses evidences from real-world case studies from multiple countries
  • Provides detailed insights of health system complexity in order to improve decision- making
  • Demonstrates the link between nursing data and its use for efficient and effective healthcare service management
  • Discusses several limitations currently experienced and their impact on health service delivery

Arvustused

"The book has relevant information to help guide the utilization and application of nursing data. It does have a periodic focus on midwifery but is useful across the nursing spectrum." --Doody

About the authors xiii
Preface xvii
Acknowledgments xxi
Chapter 1 Dynamic health care environments
1(12)
How is capacity to care defined?
1(1)
Healthcare environments
2(1)
What influences the capacity to care?
3(4)
Leadership and governance
5(1)
Healthcare financing
5(1)
Health workforce
6(1)
Medical products, devices and technologies
6(1)
Health service delivery
7(1)
Information and research
7(1)
What are the desired health system outcomes?
7(1)
Improved health, efficiency, responsiveness and caring
7(1)
Nursing data at the center
8(3)
References
11(2)
Chapter 2 Health care operational inefficiencies: Costly events
13(16)
Workforce management
13(1)
Nursing workloads and nurse staffing methods
14(2)
Measuring operational activity and efficiency
16(5)
Care recipient characteristics
17(1)
Types of resource input
18(1)
Healthcare activity processes
18(1)
Measuring health outcomes
19(2)
Learning health systems
21(5)
Making better use of data and information
23(3)
Operational research
26(1)
References
27(2)
Chapter 3 Digital transformation needs to measure nursing and midwifery care demands and workloads
29(52)
What determines nursing workloads?
29(2)
Nurse staffing methods in use or recommended
31(1)
Methods in use to measure nursing care demand
32(11)
Nursing Hours Per Patient Day
34(3)
Nurse staffing ratios
37(3)
Patient/client types
40(1)
Patient classification
41(2)
How do nursing service demand measurement methods compare?
43(2)
Patient type and treatment protocol patterns by clinical speciality
45(1)
Variables influencing nursing service demands, workloads, and costs
45(2)
Information flows and patient/client journeys
47(2)
Digital transformation enabling nursing data inclusion
49(8)
Nursing minimum data sets
50(1)
Nursing data and standards
51(3)
Reference terminologies
54(3)
Use of metadata
57(2)
Nursing service demand metadata
59(8)
Service capacity---Identifying required nursing skill mix
60(2)
Service capacity---Nursing working conditions
62(1)
Admission and continuing service determinants
62(5)
Indicators of nursing care demand
67(4)
Metadata enabling the evaluation of nursing service contributions relative to patient outcomes
69(2)
Nursing workload management metadata need
71(1)
Optimizing workplace efficiencies
71(3)
Political, professional, managerial, and industrial influencers
72(2)
Conclusion
74(1)
References
75(6)
Chapter 4 Nursing and midwifery work measurement methods and use
81(42)
Describing nursing work
85(2)
Boundaries or scope of nursing/midwifery practice
87(1)
Analyzing nursing work to be measured
87(3)
Work measurement methods
90(15)
Nursing staff availability and performance---Input variables
91(1)
A nursing practice taxonomy---Process variables
92(3)
Time study methodology
95(2)
Self-recording of nursing activity
97(2)
Work sampling methodology
99(4)
Professional judgments/estimates
103(2)
Conversion of work measurement data to a workload measure
105(4)
Making use of study results
109(5)
Using workload measurement systems with established time standards
111(2)
Nursing workload measures' validity
113(1)
Nursing work measures in use
114(2)
Patient classification principles
116(1)
Developing national nursing service weight measures
117(1)
Evidence of acuity link with patient outcomes
118(1)
Future directions
119(1)
References
120(3)
Chapter 5 Identifying skill mix needs
123(30)
Matching available skills with service demands
123(2)
Addressing qualified nurse staffing shortages
125(3)
Working with a varied skill mix
127(1)
Working to scope
127(1)
Current skill mix identification methods
128(3)
Specializations and competencies
128(2)
Occupational classifications
130(1)
Nursing industry awards, agreements and skill mix
131(2)
Job evaluation and skill assessment methods
133(5)
Skills Framework for the Information Age (SFIA)
135(3)
Education and professional development contributions
138(2)
Nursing career pathways
140(2)
Re-engineering clinical services using non-nursing support staff
142(6)
Example
144(4)
Future directions for identifying and matching skill mix needs with available staffing resources
148(1)
References
149(3)
Further reading
152(1)
Chapter 6 Nursing and organizational models of care
153(28)
Factors known to influence nursing models of care
156(3)
The nursing process---Conceptual base for nursing practice
159(8)
Nursing care plans
161(2)
Functional or task allocation
163(1)
Patient allocation
164(1)
Primary nursing
165(1)
Team nursing---A collaborative model of care
165(2)
Small team nursing
167(6)
The benefits of small team nursing
168(2)
Leading the change
170(2)
The shift routine example
172(1)
Evaluate success of team nursing implementation
173(1)
Inter and multidisciplinary models of care
173(2)
Organizational models of care influencing patient outcomes
175(1)
Success factors
176(1)
References
177(4)
Chapter 7 Staffing resource allocation, budgets and management
181(56)
Using demand side organizational nursing and midwifery workforce planning methods
181(1)
Professional and government nurse staffing initiatives
181(3)
Rostering fundamentals
184(1)
Data variables required to calculate nurse staffing needs
185(3)
Projecting nursing service demand and workforce requirements
188(1)
Calculating departmental/unit nurse staffing requirements
189(7)
Use of nurse: Patient ratios to capture FTE/WTE measures for clinical care
191(1)
Use of Nursing (Care) Hours Per Patient Day (NHPPD)
192(1)
Use of patient acuity data
193(3)
Staffing needs for other service types
196(5)
Day only departments
196(1)
Obstetric services
197(1)
Geriatric, disability and rehabilitation residential services
197(1)
Operating theaters
198(1)
Accident and emergency departments
199(1)
Specialist outpatient departments
200(1)
Supervisory and administrative clinical staff
200(1)
Significant variations resulting from method used
201(1)
An international patient type HPPD benchmarking research study
202(4)
Rostering methods
206(13)
Foundations for roster development
207(4)
Cyclic rostering
211(1)
Self rostering
211(1)
Request focus rostering
212(1)
Rostering process
213(1)
Rostering principles
214(1)
Evaluating the suitability of rosters
215(1)
Roster reengineering
216(3)
Workforce availability
219(1)
Financial management
220(6)
Roster budgeting processes based on service demand
220(2)
Staffing establishment budgeting processes
222(1)
Zero based budgeting
223(1)
Activity based costing (ABC)/funding (ABF)
223(3)
Casemix definitions (hospital `products')
226(3)
Use of casemix classifications and nursing service costs
227(2)
Connectivity requirements for nursing resource management
229(3)
Linking electronic health records with nursing resource management
230(2)
Capturing and using the data operationally
232(1)
References
232(5)
Chapter 8 Workforce planning
237(26)
Nursing and midwifery workforce statistics
237(2)
Nursing and midwifery's future perspectives
239(2)
Nursing workforce structures and statistics
241(1)
Nursing and midwifery workforce education and professional development
242(2)
Workforce planning models and tools
244(4)
Recruitment to the profession
248(1)
Workforce participation
249(6)
Employment characteristics
250(1)
Retention and turnover rates
250(2)
Causes of dissatisfaction and turnover
252(3)
Replacement and succession planning
255(2)
Meeting future demands
257(2)
References
259(4)
Chapter 9 Digital health ecosystems: Use of informatics, connectivity and system interoperability
263(46)
A need to resolve data issues
263(1)
What is a digital health ecosystem?
264(2)
Essential ecosystem features
266(3)
Healthcare ecosystem connectivity frameworks
269(3)
Today's state of the art
272(14)
Shadow systems and health data
274(2)
Connectivity and interoperability
276(1)
Measuring interoperability
277(2)
Interoperability standards and schema
279(4)
Computing platforms
283(3)
Interoperability, clinical needs and secondary data use
286(11)
Using source data and information for multiple purposes
289(4)
Decision support systems---Using secondary data
293(1)
National and international health data uses
294(3)
Genomics data and personalized medicine
297(1)
Gap analysis and digital transformation
297(4)
Conclusion
301(1)
References
302(7)
Chapter 10 A digital transformation strategy enabling nursing data use
309(46)
System implementation and change management
309(1)
Changing organizational digital health infrastructures
310(4)
Common barriers
313(1)
Using `Lean' and `Six Sigma techniques' to design new work processes
314(2)
Potential use of nursing data
316(29)
Patient acuity/nurse dependency/nurse-patient ratios
317(1)
Work hours per patient day/visit/procedure/attendance/birth/occasion of service/operating minute etc.
317(1)
Workload management
317(1)
Workforce planning
318(1)
Care capacity management
318(1)
Pathways and care plans with outcome reporting
319(1)
Nursing intensity measures
319(1)
Retrospective and proactive discharge analysis
320(1)
Diet ordering
321(1)
Rostering for clinical and non-clinical departments
322(1)
Clinical handovers
322(1)
Allied health intervention register and reporting
323(1)
Patient risk assessments with action plans
323(1)
Human resource management registers and staff health profiles with reports
324(1)
Staff health system
324(1)
Efficiency measures/benchmarking all departments
324(1)
Patient acuity and workload management system implementation project plan---A generic example using legacy systems
325(6)
Executive lead for motivational strategy
331(1)
Resource allocation and task allocation for system implementation
331(10)
Risk assessment
341(4)
Desired outcome measures benefitting nurses and their patients
345(1)
Data collection methods
346(1)
Measuring patient acuity on a shift
346(1)
Local nursing acuity data use
347(1)
Allocating staff to workloads
347(1)
Handovers
347(1)
Workforce planning
348(1)
Ward/unit manager/senior nurse daily routines to ensure data accuracy
348(1)
Health IT evaluation methods
349(1)
A nursing workload management system and change management evaluation framework
350(3)
References
353(2)
Chapter 11 Measuring health service quality
355(34)
What is quality?
355(3)
Quality programs
357(1)
Nursing practice environments influencing quality
358(2)
Collegial cultures
360(1)
Data quality
360(5)
Health data uses and links to nursing data
362(1)
Using data to support decision making
363(1)
Data sets and data repositories
363(1)
Data governance mechanisms
364(1)
Standards, accreditation and governance
365(5)
Accreditation standards
366(1)
Types of standards
367(2)
Standards governance
369(1)
Reliability and quality measures associated with patient acuity data
370(2)
Clinical data management issues
372(1)
Outcomes research and big data
373(8)
Performance indicators and health system frameworks
375(3)
Measuring caring as an outcome measure
378(1)
Impact of funding arrangements on the selection of performance indicators
379(2)
Big data management and governance
381(3)
Health quality measurement issues
384(1)
References
384(5)
Chapter 12 Residential and community care management
389(24)
Introduction
389(1)
Residential care environments
390(2)
Measuring care service demand and funding mechanisms
392(4)
Residential service work measurement methods and outcomes
396(1)
Identifying skill mix needs
397(1)
Organizational and nursing models of care
398(3)
Staffing resource management
401(1)
Aged care workforce planning
402(1)
Use of informatics, digital transformation
403(2)
Documentation, reporting and change management
405(1)
Measuring service quality
406(1)
Qualify of life-future vision
407(2)
References
409(4)
Chapter 13 Current and future vision
413(28)
Global health and capacity to care
413(2)
Nurses and midwives' unique contributions to global health
415(3)
Our digital health ecosystem
418(4)
Measuring health system effectiveness
422(1)
Hospital performance statistics and costs
423(2)
Safe patient care vs costs
425(1)
Benefits from using nursing data
425(4)
Optimizing our capacity to care in a sustainable health system
429(7)
Close the loop between resource flows into and out of the system
430(1)
Nursing workload analysis
431(1)
Nursing and midwifery work characteristics and measurements
432(1)
The nursing and midwifery workforce
433(2)
Digital transformation needs
435(1)
A future vision
436(1)
References
437(4)
Appendix 1 Case study 1---Patient Assessment and Information System (PAIS): Work measurement research and workload measurement methodology 441(12)
Appendix 2 Case Study 2---Design, development and use of the TrendCare system 453(12)
Index 465
Evelyn Hovenga, RN, PhD, FACS, FANC, FIAHSI, currently manages eHealth Education, an RTO, and the not-for-profit Global eHealth Collaborative (GeHCo) and continues to work as a digital health consultant. She retired as Professor of Health Informatics in 2007, following a 25-year career in this discipline with a focus on standards development as these apply to EHRs, semantic interoperability, and terminology and is Honorary Senior Research Associate at the Centre for Health Informatics and Multiprofessional Education, University College London (http://www.chime.ucl.ac.uk/). Evelyn started her career as a registered nurse; has health executive, public service, educational and research experience; obtained a PhD in Health Administration (Nursing Informatics); initiated and hosted the first National Health Informatics Conference (HIC) in Melbourne in 1993; is one of the founders of HISA and the Australasian College of Health Informatics; and is a founding fellow of the International Academy of Health Sciences Informatics (FIAHSI), Geneva. She is also widely published. Evelyn is an honorary member of the International Medical Informatics Associations Nursing Informatics SIG as a result of representing Australian nurses from 1984 for many years, as a member and Past Chair of this group. Cherrie Lowe is a registered nurse, midwife, an innovator and business manager, who brings local, national and international health service executive management, research, software development and system implementation experiences. Her health industry experience includes past roles as a Nurse Educator, Quality Manager, Director of Nursing, Director of Clinical Services, hospital accreditation surveyor and medico-legal expert witness.

Her executive level industry experience began as a Director of Nursing for Mercy Health and Aged Care where she maintained an efficient nursing service and improved the hospitals profit margin assisted by making use of her patient acuity system. Cherrie initiated the development of a hospital promotion campaign, complete with television video that significantly increased the hospitals bed occupancy. The success of this campaign achieved the Australian Council on Healthcare Standards (ACHS) quality award for large hospitals.

As Director of Clinical Services for Ramsay Health Care she played a major role in managing the transition of a large Commonwealth funded veteran hospital to Australias largest private hospital where she developed a strong, efficient and dynamic nursing service and allied health team. Cherrie assisted in the expansion of clinical services, including: Cardiac, Gynaecology and Neurosurgery. She again achieved the ACHS Quality Award for large hospitals and the hospital was also awarded the Employer of the Year Award for large organizations in Brisbane. Cherrie was again responsible for generating a significant profit margin for that organisation by maintaining a high level of efficiency in clinical services, an achievement made possible through the use of her patient acuity system.

During her years as a nurse executive, Cherrie managed her family, undertook her post graduate studies as an external student, was a surveyor for the Australian Health Care Council, developed, tested andmade use of a patient acuity system, and undertook various consultancies. She partnered in business with a software developer and her system was fully computerized taking advantage of ongoing technical developments. Cherrie shared her research findings with other Directors of Nursing who then worked with her by facilitating ongoing research and development activities in their facilities. This research was presented at a world informatics conference in San Antonio in 1994. During the mid 1990s both Cherries and Evelyns patient acuity systems were used by numerous Queensland hospitals. The Queensland Government funded a validation study enabling a comparison to be made between these two systems using the same patient populations which validated both systems, as the use of their systems provided comparable results.

The success of Cherries automated and highly interoperable TrendCare system led her to assume the CEO, researcher and developer role on a full-time basis. Her primary focus has always been to take on the many ensuing challenges to benefit the nursing and midwifery professions As recognition Cherrie received a Nursing Excellence award from the Royal College of Nursing for her contribution to nursing in Australia.

Developing and continuously improving the reliability of an evidence based patient acuity and workload management system for nursing and midwifery has been a challenging undertaking, and during the past 25 years Cherrie has had to overcome many barriers. These include (1) convincing nursing and midwifery leaders, colleges and unions that nursing services need to collect and present their own evidence of nursing demand in order for nursing services to be adequately resourced, (2) convincing health service senior executives, including CEOs, finance managers and chief information officers of the methodologies that are best suited to measuring nursing demand and the value of nursing demand measurements for effective budget management and accurate costings of episodes of care, (3) Convincing nurses and midwives generally of the importance of collecting nursing and midwifery data so that safe staffing and fair workloads can be a reality. These barriers have been overcome in some countries but are still ongoing in others. Developing a viable small business, while trying to provide an affordable software product to health services that are financially stretched, has tested Cherries business skills. Transforming a small local business to an international business with a customer footprint across six countries in the health care environment is testament to her determination, commitment and sound business strategies.

Cherrie has won the AustCham Business Award in Singapore, the Australian national and state Microsoft eHealth iAwards for innovation in IT development and the Australian national ICT exporter of the Year Award.