About Special Kids (ASK)

, 214–215

Accountable Care Organizations (ACOs)

, 186

Activity planning

, 35–36

Acute care hospitals, factors affecting operating results for

, 152–155

Adapt strategies

, 22–23

Adaptation

, 12

strategies

, 12

Adoption of innovations

, 57–59, 68–69

Affordability Care Act (ACA)

, 30–31, 184–185

Agency for Healthcare Research and Quality Hospital Survey of Patient Safety Culture (AHRQ Hospital Survey of Patient Safety Culture)

, 123–124

Agent-based modeling (ABM)

, 37–38, 40, 43–45

simulation

, 45

Aggregated precision investment (API)

, 194–195

Ambidexterity

, 17–18

Ambulatory surgery centers

, 122

American health delivery system

, 191

American health sector

, 182

American Hospital Association (AHA)

, 189

Annual Survey

, 146

Population Health Framework

, 189

American Medical Association (AMA)

, 231–232

Analyzer strategy

, 12

Area Health Resource File (AHRF)

, 62, 146

Article inclusion criteria

, 163

Artificial intelligence (AI)

, 10, 79, 99, 185–186

chatbots

, 10

relationship between innovation diffusion scores and perceived value of AI assistance

, 109–110

Association of International Certified Professional Accountants

, 158

Atypical pneumonia

, 165

Automating documentation

, 101–102

Average marginal effects (AME)

, 65

Bioterrorism Hospital Preparedness Program of the Health Resources and Services Administration

, 164–165

Bioterrorism sparks emergency readiness responses

, 164–165

Bivariate analysis

, 105

Bivariate relationship between change management practice and perceived safety culture

, 128–132

Black, Indigenous, and People of Color (BIPOC)

, 214

Boundary spanning issues

, 197–198

Break-even analysis

, 40–41

Cancer Incidence Missouri Information for Community Assessment website

, 40

Care conference interview guide

, 227–229

background

, 227–229

COVID-19

, 229

Care coordination

, 212

Care planning

, 223

Caregiver Advise, Record, Enable Act (CARE Act)

, 233–234

CARES Act

, 155, 158

Case conference model

, 214–215

Case study, simulation

, 39–45

Centers for Disease Control and Prevention (CDC)

, 165, 171–172

Centers for Medicaid and Medicare Services (CMS)

, 57, 144–145, 186

Flex Monitoring

, 156

Central line-associated bloodstream infection (CLABSI)

, 118

Change

, 98–99

process

, 48–49

Change management

, 38

association between perceived safety culture

, 137

bivariate relationship between perceived safety culture and

, 128–132

process

, 39, 46

ChatGPT

, 10

Checklists

, 119

Chief Executive Officers (CEOs)

, 123

Chief Financial Officers (CFOs)

, 124

Chief Nursing Officers (CNOs)

, 123, 127

Children with special healthcare needs

analysis

, 216

background

, 213–215

case conference model

, 214–215

Eskenazi Health

, 214

findings

, 216–223

interview guide

, 215–216

methods

, 215–216

practice implications

, 224–225

strengths and limitations

, 225

study design and population

, 215

Clinical decision support

, 101–102

Clinical Excellence Research Center, The

, 101

Clinical specialty, knowledge and awareness of current and future implementations overall and by

, 104–105

Clinician/provider

, 228–229

Community health improvement plans (CHIPs)

, 190

Community health needs assessments (CHNAs)

, 190

Complex adaptive systems (CASs)

, 20–21

Control

, 14

strategy

, 11–12, 15–16

Coproduction of health framework

advancing progress

, 184–187

coproduction of health research directions

, 199–200

crisis of disruption leading to coproduction of health solution

, 189–191

emerging coproduction of health framework

, 191–193

identification and dissolution of current health paradigm

, 183–184

implementing coproduction of health framework

, 193–195

organizational science theories underlying coproduction of health framework

, 195–199

population health framework as paradigm change precursor/enabler

, 188–189

resource dependency theory

, 199

2019 Coronavirus Disease (SARS-CoV-2)

, 163

COVID–19

, 157–158, 163, 173, 229

crisis

, 20

financial performance for hospitals during

, 145–146

pandemic

, 4–5, 8, 15, 78, 146, 155, 162, 183–184, 214, 222–223

Create

, 12–13

approach

, 12

strategy

, 16–17, 22–23

Critical access hospitals (CAHs)

, 144–145

factors affecting operating results for

, 150–152

margins

, 152

Cross-disciplinary teams

, 232–233

Culture change

, 62

Culture of Health

, 188

Culture–change initiatives

, 68–69

Culture–change movement

, 56–59

Decision-making process

, 6–7

Defenders

, 14–15

strategy

, 11–12

Deoxyribonucleic acid (DNA)

, 79–80

metaphor

, 81–83

Department of Health and Human Services, The

, 172

Design process

, 38

Dichotomy of social and technical strings

, 81–82

Diffusion of innovation

, 99–100

Diffusion of value-enhancing

, 98–99

Digital communication

, 186–187

Digital twin

, 49

Digitalization

, 10

Diseases

, 168

Disproportionate share (DSH)

, 148

Disruption leading to coproduction of health solution, crisis of

, 189–191

Double helix

, 79–80

Dynamic capabilities

, 15–16

Ebola

, 168–171

Ebola Virus Disease (EVD)

, 163

Electronic health records (EHRs)

, 185–186

Emergency departments (EDs)

, 167–168

Emergency Management Program (EMP)

, 171–172

Emerging infectious disease (EID)

, 167–168

Enhanced health organizational structures

, 186

Environmental uncertainty, model of strategic responses to

, 22–23

Eskenazi Health

, 214

case conferences

, 214–215

European health observatory

, 10

Exogenous uncertainty

, 6

External uncertainty

, 6

Family care partners

, 231–232

fragmented policy landscape

, 233–234

future of healthcare team

, 234–235

team

, 232–233

Family Caregiver Alliance

, 232

Family caregivers

, 233–234

Federal Emergency Management Agency (FEMA)

, 162–163

Federally Qualified Community Health Center (FQHC)

, 214

Fee-for-service (FFS)

, 112

Financial performance for all hospitals during COVID-19

, 145–146

Fragmented policy landscape

, 233–234

Future studies

, 18–19

Futurescapes

, 19

General practitioners (GPs)

, 21

Government Finance Officers Association

, 156

Grand challenges

, 4, 18

Grand health challenges

, 182

Grassroots movement

, 57

Great Recession

, 34–35

Health Alert Network (HAN)

, 171

Health framework

emerging coproduction of

, 191–193

implementing coproduction of

, 193–195

organizational science theories underlying coproduction of

, 195–199

Health in All Policies (HiAP)

, 188

Health information technology (HIT)

, 185–186

Health Information Technology for Economic and Clinical Health Act (HITECH Act)

, 185–186

Health Insurance and Portability and Accountability Act (HIPAA)

, 185–186, 234

Health Maintenance Organizations (HMOs)

, 194–195

Health paradigm, identification and dissolution of current

, 183–184

Health policy transformations

, 184–185

Health research directions, coproduction of

, 199–200

Health Resources and Services Administration (HRSA)

, 62, 164–165

Health sector

disruption

, 190

organizations

, 186

Health solution, crisis of disruption leading to coproduction of

, 189–191

Health system

enhanced health organizational structures

, 186

examples of health systems’ transitions and transformations

, 184–187

health management adapting to cultural shifts

, 186–187

health policy transformations

, 184–185

innovations

, 199–200

technological achievements

, 185–186

Healthcare

, 16, 30, 39, 119

delivery process

, 39–40

future of healthcare team

, 234–235

management scholars

, 12–13

persisting uncertainty in

, 8–10

professionals

, 98–99

RPBS in practice in

, 90–92

systems

, 185–186

Healthcare Emergency Medical Services (Healthcare EMS)

, 169

Healthcare organizations (HCOs)

, 5, 8–10, 12–13, 16, 18, 224

organizational capabilities amid uncertainty

, 15–18

proposed strategies to embrace uncertainty

, 13–15

strategic responses to uncertainty

, 10–13

(un)certain future

, 18–23

uncertainty

, 6–10

HealthPartners

, 194–195

Healthy People initiatives

, 183–184

Herfindahl–Hirschman Index (HHI)

, 148–150

High-cost healthcare delivery strategies

, 37

High-Medicaid-census nursing homes

, 57–58

conceptual framework

, 59–61

methods

, 61–66

results

, 66–68

High-Value Care Method Adoption Survey

, 101

Highly infectious diseases (HIDs)

, 170–171

Hospital finances

analysis

, 148

annual operating margins

, 150

factors affecting operating results for acute care hospitals

, 152–155

factors affecting operating results for CAHs

, 150–152

factors affecting operating results for SN Hospitals

, 152

financial outcomes

, 147–148

financial performance for all hospitals during COVID-19

, 145–146

hospital category variables

, 147

limitations

, 158

practice and policy implications

, 155–156

sample characteristics

, 148–150

SN and CAHs

, 144–145

study data and methods

, 146–148

study results

, 148–155

theoretical implications

, 156–158

Hospitals

bioterrorism sparks emergency readiness responses

, 164–165

category variables

, 147

Ebola

, 168–171

key lessons learned for hospital administration preparedness

, 173–174

MERS

, 166–168

methods

, 163

results

, 164–174

SARS

, 165–166

SARS-COVID-19

, 171–173

Implementation strategies

, 189

Improvements

, 79

Incident Management System (IMS)

, 171–172

Inductive coding

, 216

Information technology (IT)

, 90

Innovation adoption

, 59, 71

Innovation and awareness of implementation, knowledge of

, 100

Innovation diffusion

, 99–101, 110

analysis

, 103–104

background

, 99–101

characteristics of new adopters

, 100–101

diffusion of innovation

, 99–100

knowledge and awareness of current and future implementations overall and by clinical specialty

, 104–105

knowledge of innovation and awareness of implementation

, 100

measures

, 102–103

methods

, 101, 104, 111

relationship between innovation diffusion scores and perceived value of AI assistance

, 109–110

relationship of clinician characteristics with

, 105–109

results

, 104–110

sample

, 102

survey administration

, 102

survey development

, 101–102

theory

, 99–100

Institute of Medicine

, 56–57

Institutional Review Board

, 216

Institutional theory

, 81–82, 196–197

literature

, 84

Integrator model

, 194–195

Isolation Communication Management System (iSOCOMS)

, 170–171

Joint Commission International (JCI)

, 119

Knowledge acquisition

, 60

Knowledge and awareness of current and future implementations overall and clinical specialty

, 104–105

Knowledge dissemination

, 60

Knowledge management (KM)(see also Change management)

, 58, 60

activities

, 69–70

index

, 62–64

Knowledge of innovation and awareness of implementation

, 100

Knowledge responsiveness

, 60

Knowledge sharing mechanisms

, 98–99

Knowledge-based view (KBV)

, 59

Kruskal–Wallis H test

, 103–104

Leadership

, 120–121

Lessons learned

, 163, 166

Licensed practical nurses (LPNs)

, 65

Logistic regression

models

, 65

results

, 66

Long–term Care (LTC)

, 62

Malaria

, 168–169

Management and Organizational Practices Survey (MOPS)

, 123–124, 135–136

Management practice

, 134

Mann-Whitney U-test

, 103–104

Medicaid waivers

, 233–234

Medicaid-enrolled aging population

, 59

Medicare Access and Chip Reauthorization Act (MACRA)

, 185–186

Medicare Cost Reports

, 62

Medicare Payment Advisory Commission (MedPAC)

, 156

MERS

, 166–168

Middle East Respiratory Syndrome Coronavirus (MERS-CoV)

, 163, 166–167

Missouri Department of Health and Senior Services

, 40

Mobile radiation oncology

, 40

implementation of mobile radiation oncology unit

, 39–45

system

, 44–45

Mobile radiation system

, 43–44

Mobilize energy for change and empower others to act

, 35–36

Model-based systems engineering (MBSE)

, 38

Modeling

, 37

and simulation techniques

, 39

techniques

, 45

Modified MOPS

, 125–126

Monte Carlo modeling

, 40–41

Monte Carlo simulation

, 37, 40, 46

Monte Carlo techno-economic feasibility simulations

, 46

National health system

, 187

National Hospital Flash Reports

, 145–146

National Incident Management System (NIMS)

, 172–173

Network collaborations

, 198–199

Network theory

, 198–199

Nursing home (NH)

, 56–57, 60–61

respondents

, 66

Oncological care

, 39

Operating room (OR)

, 119

Operational strategies

, 194–195

Organizational behavior theories and models

, 200

Organizational capabilities amid uncertainty

, 15–18

ambidexterity

, 17–18

Organizational change

, 79, 82

Organizational decision strategies

, 198

Organizational DNA

, 79

applying RPBS in change practice

, 93

case study

, 90–92

change considered from perspective of RPBS

, 87–90

DNA as organizational metaphor

, 80–81

theory of

, 79–81, 86

Organizational members in temporal work, ways to support

, 20

Organizational science theory

, 197

institutional theory

, 196–197

network collaborations and network theory

, 198–199

socioeconomic model

, 197–198

underlying coproduction of health framework

, 195–199

Organizations

, 12, 234–235

theorists

, 14–15

ways to build systems thinking in

, 21–22

Paradigm change precursor/enabler, population health framework as

, 188–189

Parent liaisons

, 213, 215, 227–228

Parent-to-parent support

, 213

Patient Protection and Affordable Care Act (PPACA)

, 186, 190

Perceived safety culture

association between change management practice and

, 137

bivariate relationship between change management practice and

, 128–132

Person-centered care for aging strategies

, 71

Person-centered individualized care

, 57

Physical action support

, 101–102

Policies

, 233–234

Policymakers

, 234–235

Population Health Alliance (PHA)

, 189

Population Health Management framework

, 189

Population health framework as paradigm change precursor/enabler

, 188–189

Population health management strategies

, 189

Population health models

, 188–189

Potential solutions

, 78–79

Primary care organization

, 17

Principles and beliefs

, 87

Probability-based approach

, 40

Prospector strategy

, 12

Psychological safety

, 20

Quadruple Aim

, 16–17, 188

Qualitative interviews

, 216

Quality health care

, 232–233

Radiation oncology machines

, 39

Reactors

, 14–15

strategy

, 11–12

Reasoned action approach theory

, 41–42

Registered nurses (RNs)

, 65

Reinforcement, sustain and monitor momentum through short-term wins and

, 36

Religious institutions

, 31

Renewals

, 79, 89–90

Research

, 224

Resident choice

, 57

Resource dependency theory

, 157, 199

Resource-based theories

, 157

Resource-based view (RBV)

, 62–64

of firm

, 157

Routines

, 79, 83

Routines, Principles, and Beliefs (RPBs)

, 79–81, 85–86

change considered from perspective of

, 87–90

in change practice

, 93

ladders

, 86

in practice in healthcare setting

, 90–92

Rural communities

, 30–32

Rural healthcare change management, systems engineering to advance

, 36–39

Rural healthcare organizations

, 33, 35

approach closure

, 34–35

grand challenges

, 32–33

Rural healthcare provider’s grand challenges

, 31–32

‘Rural patients’ grand challenges

, 30–31

Rural residents

, 31

Safe healthcare systems

, 118

Safe Procedure Review (SPR)

, 122

Safe Surgery Checklist, The

, 121–122, 133

association between change management practice and perceived safety culture

, 137

bivariate relationship between change management practice and perceived safety culture

, 128–132

data analysis

, 124–127

descriptive changes in safety culture

, 128

implementation

, 122

measures

, 123–124

methods

, 122–127

results

, 127–133

sample and data collection

, 122–123

sample characteristics

, 127–128

setting

, 122

theoretical background

, 120–122

Safe Surgery Saves Lives

, 119

Safe Surgery South Carolina

, 122

Safe Surgical Practice Survey

, 123, 135–136

Safety

, 135

Safety culture

, 118

descriptive changes in

, 128

Safety–net hospitals (SN hospitals)

, 144–145

SARS

, 165–166

SARS-CoV

, 167

SARS-COVID-19

, 171–173

Secondary datasets

, 62

Seizing

, 16

Severe Acute Respiratory Syndrome (SARS-CoV-1)

, 163

Short-term wins and reinforcement, sustain and monitor momentum through

, 36

Simulation

, 37

assessing opportunity/problem motivating change

, 34

formulating and communicating clear, compelling vision

, 35

grand challenges contribute to change management challenges

, 33

implementation of mobile radiation oncology unit

, 39–45

implications

, 46–49

mobilize energy for change and empower others to act

, 35–36

modeling

, 49

rural healthcare organization’s grand challenges

, 32–33

rural healthcare provider’s grand challenges

, 31–32

rural patients’ grand challenges

, 30–31

select and support guiding coalition

, 34–35

sustain and monitor momentum through short-term wins and reinforcement

, 36

using systems engineering to advance rural healthcare change management

, 36–39

techniques

, 45

SN Hospitals, factors affecting operating results for

, 152

Social determinants of health (SDOH)

, 212

Social DNA strings

, 79–80

Social string

, 81

Socio-technical literature

, 86

Socioeconomic model

, 197–198

Socio–technical systems (STS)

, 79

Spanish flu

, 163

State uncertainty

, 8

Strategic management

, 13

Structuration theory

, 120–122

Surgical safety checklists

, 119

Sustainable strategies

, 19

System of-systems (SoS)

, 36–37

Systems engineering

, 38

to advance rural healthcare change management

, 36–39

Systems modeling

for healthcare

, 40

methodology

, 45

Systems thinking

, 36–37

Team

, 232–233

Technical DNA strings

, 79–80

Technical string

, 81

Technology-enhanced workflow

, 186

Temporal work, ways to support organizational members in

, 20

Theory of Planned Behavior (TPB)

, 41–42

research design

, 43

Total Design Method

, 61–62

Traditional healthscape

, 190

Transcriptions

, 216

Transformations

, 79, 87–90

Triple Aim model

, 188

Trust

, 233

Tuberculosis

, 168

(Un)certain future

, 18–23

applying systems thinking and management

, 20–22

future work

, 18–20

model of strategic responses to environmental uncertainty

, 22–23

ways to build systems thinking in organization

, 21–22

ways to support organizational members in temporal work

, 20

Uncertainty

, 6–10

adapt

, 12

from adapting to creating

, 15

control

, 11–12

from controlling to adapting

, 14–15

create

, 12–13

as given environmental feature

, 7–8

healthcare organizations

, 12–13

persisting uncertainty in health care

, 8–10

proposed strategies to embrace

, 13–15

strategic responses to

, 10–13

US healthcare environment

, 212

US system of healthcare

, 183

“Value-based” payment systems

, 157

Veterans Health Administration

, 157–158

Volatile, uncertain, complex, and ambiguous (VUCA)

, 18

Voluntary incident reporting system (VIRS)

, 90–91

Washington State data

, 147–148

Wicked problems

, 182

Workforce

operations improvements

, 186

redesign

, 57

World Health Organization (WHO)

, 10, 119, 165

Safe Surgery Checklist

, 122

World Management Survey (WMS)

, 123–124