Organizational Adaptation Under Stress: Tracing Communication Processes in Four California County Health Departments During the H1N1 Threat,April 28,2009,to March 11,2011

Abstract

Urgent public health threats present a growing problem for public health surge. This study addresses tensions that occur in organizations as they confront unexpected, urgent demands for performance that exceed their existing allocation of resources and personnel, patterns of adaptation in response, and consequences for continued functionality in their mission. We view the problem through a conceptual lens of complex adaptive systems and distributed cognition to focus on patterns of organizational communication as critical factors in shaping organizational response to crisis operations. We employ a mixed-methods approach to examine communication and coordination patterns in a small-N comparative case study of four California county health departments during the H1N1 threat in late spring–summer of 2009 and the following 24 months. Findings indicate factors that contribute to, or inhibit, the communication process, such as organizational structure, past experiences, exercise of authority, and document the occurrence of defensive routines as a distortion of internal communication practices. Communication and coordination within and among entities engaged in response operations are critical to managing urgent public health threats, indicating that mechanisms which place a cognitive burden on staff exacerbate existing problems in performance.

Keywords

organizational communication defensive routines crisis operations organizational adaptation

Organizational Adaptation in Stressful Environments

How do organizations respond and adapt to disruptive challenges and unanticipated demands in their operational environments? Managing unexpected events that strain budgets, tempers, and schedules represents a recurring problem for organizations seeking to achieve professional performance. Organizations are designed to perform a defined set of functions within a set of known constraints and planned allocation of resources (Mackenzie, 1993; Simon, 1997). As their internal operational environments are buffeted by external demands that may exceed their internal resources, training, and expectations for professional performance, tensions arise among personnel within the organization (Argyris, 1990).

Tensions also increase between the organization and external clientele, as affiliated actors expect timely, dedicated performance of the organization’s daily functions as well as prompt response to an urgent situation that requires immediate action and a reallocation of resources (Kettl, 2014). Such conditions test an organization’s capacity to adapt its internal structure to meet unexpected external demands, while still maintaining its daily functions (Krackhardt & Stern, 1988). In most cases, the internal structure of the organization needs to communicate its need for immediate assistance to external organizations that can provide supplementary support, while specifying tasks, allocating resources, and assigning personnel to meet unexpected demands. In all cases, the daily work environment is altered by the sudden increase in demands for extra services, while maintaining daily functions (Solé, 2011).

Managers operating in situations of rapid change confront a difficult dilemma. With limited resources and time, they can either set aside their daily tasks to focus on the crisis or continue their daily tasks and risk public criticism for failing to meet obvious demands of the crisis (Argyris, 1990; Meltsner & Bellavita, 1983). This dilemma is particularly cruel for managers of public organizations that are often tightly limited in resources, highly visible in their actions, and slow to activate mechanisms that can provide external assistance to meet internal needs. We explore the process of organizational adaptation to stressful operational environments, and address three basic research questions:

Research Question 1: What factors enable organizations to manage stress effectively?

Research Question 2: What factors inhibit organizational adaptation under stressful conditions?

Research Question 3: What costs and consequences ensue for organizations that fail to adapt their performance under stress?

These questions focus an inquiry into organizational adaptation in actual practice.

In this study, we define the key terms for analysis as follows. Organizational stress means operating conditions that require heightened attention, extra physical demands in terms of work load, and altered tasks for personnel that exceed their normal responsibilities for a sustained period of time (Argyris, 1993; Kettl, 2014; Mackenzie, 1993). Adaptation means iterative patterns of communication and coordination among actors and groups to adjust tasks, time, and resources reciprocally to meet external demands more appropriately (Comfort, 1999, 2007, 2018; Glass et al., 2011). Internal structure is defined as the formal set of rules of operation for the organization, well known to the employees and specified in organizational documents (Ostrom, 2005; Simon, 1997). Internal processes are defined as the informal modes of interaction that are developed among organizational personnel seeking to meet the demands for performance expected of the organization (Argyris & Schön, 1996; Fligstein & McAdam, 2012; Kettl, 2018). External demands represent a sudden increase in the number of clientele seeking services, reduced allocation of resources to support agency performance, or changed expectations for types of services provided by the agency (Klein, Orasanu, Calderwood, & Zsambok, 1993; Koppenjan & Klijn, 2004).

A Conceptual Framework for Organizational Adaptation Under Stress

Organizational adaptation is a process intrinsic to complex systems of interacting organizations (Glass et al., 2011; Holland, 1995/1996; Miller & Page, 2007). Organizations are social constructs that, in their best form, facilitate action toward a shared goal for large numbers of people (Simon, 1997). Designed for operation in stable environments, organizations respond differently to stress, that is, conditions affecting their regular operating environment that may exceed the organization’s standard operating procedures and resources (Kettl, 2014, 2018). Such conditions reveal strengths and weaknesses not only in the organization’s internal structure but also in the informal processes that personnel develop to manage uncertainty in their workload and resources during unexpected events. Fligstein and McAdam (2012) describe the shifting environments, in which organizations operate as “fields of action” that adapt and change as the flux of social, economic, and political events in a society alter the expected context of action. Importantly, the extent to which an organization’s internal structure can recognize external risk and adapt its policies and procedures to accommodate the influx of new information, urgent demands, and potential shortfall of essential resources enables the organization to manage the initial challenge successfully. This process of adaptation, however, requires that internal members of the organization have sufficient knowledge of the external environment that they know how and when to seek additional support (Krackhardt & Stern, 1988). Furthermore, such a relationship of exchange depends on sufficient empathy between the internal and external actors to reduce the uncertainty that characterizes interactions between unfamiliar organizations and enhances the willingness of both sets of actors to collaborate in activities that cross organizational and jurisdictional scales of operation (La Porte, 1975/2015). It also means that as new actors enter response operations in crisis environments, interactions among participating actors become more complex, altering existing relationships and forging novel patterns of behavior as actors and groups seek—or fail—to adapt (Castells, 2009).

Role of Initial Conditions

Comfort (2018) identifies four initial conditions that affect an organization’s ability to adapt its performance under stress: time, scale, space, and energy. Briefly, these conditions define the arena of action within which organizations interact. Time refers to the duration of the urgent event, in hours, days, weeks, months, and, for some events, years. Scale refers to the levels of jurisdiction that are involved in any decision process, from individual units within the organization, to administrative units that represent the whole organization, to external levels of decision-making authority from local to county to state to federal decision-making bodies. Different jurisdictional levels of decision making have varying requirements for information and distinct audiences for organizational accountability (Axelrod & Cohen, 2000; Glass et al., 2011; Meltsner & Bellavita, 1983). These differences need to be acknowledged and bridged to forge a coherent organizational response system, capable of functioning under altered conditions as an adaptive system. The process of adaptation necessarily requires communication among different actors, likely using different forms of communication under urgent time constraints (Comfort, 2007). Space refers not only to the geographic area covered but also to the density of population within that area and serves as an indicator of the size of the clientele claiming access to services (Cutter, 2006). Energy refers to the information and communication processes that activate the dynamics of the interacting systems (Smith, 2008) and inform actors within the whole system of potential choices for action.

Of these four types of initial conditions, the most critical are the information and communication processes that engender social action in urgent events. Recognized by Smith (2012) as the energy that engenders collective response and enables individuals, units, and organizations to focus on a shared goal, information is transmitted both within operational organizations and between organizations and their wider social environment. The process of communication, early characterized by Shannon (1948) and Wiener (1971) as a sociotechnical process, links a sender (human or technical sensor) through a transmitter (technical device or other human) to a receiver (human or technical device) to convey information that serves as a basis for action. Decades of further study of communication processes has emphasized the role of basic knowledge or understanding of context in this process. That is, the level of knowledge held by the receiver regarding the context of the message being communicated increases the accuracy and likelihood of the receiver’s timely comprehension of the sender’s message (Luhmann, 1989/1996). For organizations operating under stressful conditions, rapid and accurate comprehension of valid information regarding a changing environment is essential to achieve coordination in a shared effort to reduce risk (Comfort, Oh, Ertan, & Scheinert, 2010).

Facilitating Communication

Creating the technical and organizational conditions that enable timely, valid communication in stressful operating conditions is not trivial. In virtually all instances, no single organization or authority can perceive the whole profile of a rapidly changing set of complex operations (Hutchins, 1995). Information and knowledge that are central to effective performance may be distributed among multiple organizations, jurisdictions, and disciplines (Hutchins, 1995). Not only marshaling incoming information regarding changing conditions but also integrating it with known information about existing conditions are central functions of organizations that adapt effectively to a changing context for action. Little is known about how organizations successfully manage this critical process of recognizing a threat or risk.

Recognition of threat entails reallocating resources and time internally to address the perceived risk, mobilizing external resources and knowledge, if necessary, to supplement existing personnel, and evaluating and adjusting performance to changing levels of threat and resources. This is a complex process in which an organization’s capacity to adjust its internal performance creates the basis for its actions in an external environment. The intent of the organization’s external action is to secure greater resources in terms of staff and personnel to minimize a threat to its internal performance or failure to achieve the organization’s basic mission. Observing this process in practice allows analysts to gain insight into the patterns of behavior within organizations that either facilitate or hinder adaptive performance under stressful conditions.

Research Design: A Small-N Comparative Case Study of Four California County Health Departments Under Stress

We explored the process of organizational adaptation under stress by conducting a small-N qualitative case study of four California counties that experienced the 2009 H1N1 influenza crisis under different initial conditions, examining how exposure to the same external threat generated different patterns of internal organizational performance in response.

Crisis in Public Health: The 2009 H1N1 Outbreak

The H1N1 threat represented the transmission of influenza from swine populations to humans, a condition that had been recognized as possible, but rare (Centers for Disease Control and Prevention [CDC], 2017). From 2005 until January 2009, just before the beginning of the primary outbreak, 12 cases of H1N1 had been identified (CDC, 2010; Shinde et al., 2009). On April 15, 2009, laboratory testing, done by the Centers for Disease Control, confirmed the first human case of H1N1, in a 10-year-old girl from California. The testing also confirmed that this case presented a previously unknown strain of influenza, one that had never been observed in human populations (CDC, 2010). A second case of an 8-year-old boy was confirmed only days later but located more than 100 miles away from the first. These cases, with no apparent connection, suggested a new influenza strain was already in the human population and spreading. By May 21, 2009, the CDC was reporting 5,764 cases in 48 states and Washington, D.C., along with nine deaths, in the United States, as well as total of 10,243 cases in 41 countries (Pennsylvania Department of Health, 2009).

Under the 2005 International Health Regulations (IHR), the World Health Organization (WHO) called on its member nations to establish clear criteria for the declaration of an international health emergency (WHO, 2005). As of 2017, officials for the CDC indicated that they still follow WHO’s lead on how and when to declare such an emergency, noting that the United States lacks clear federal-level rules even 8 years after the H1N1 outbreak (Y.A. Shin, personal communication, March 2017).

With critical gaps in resources and knowledge, and rapidly spreading infections, WHO declared an international public health emergency for H1N1 on April 25, 2009 (CDC, 2010). Yet, even 3 weeks after the declaration of an international health emergency, the Pan American Health Organization (2009) estimated that it would be another 6 months before a vaccine could be ready for distribution in affected communities, emphasizing the need for a thorough investigation of response operations, particularly factors facilitating and inhibiting overall response operations during 2009 H1N1.

Unit of Analysis: County Health Department

The unit of analysis for this small-N comparative case study is a county health department. County health departments are critical actors in the complex system of health services design and delivery, given their mesolevel function in managing both intra- and interscale interactions in the delivery of public health services (Fligstein & McAdam, 2012). County health departments include local-level decision makers who manage emergency operations to protect public health in their respective jurisdictions. Furthermore, county departments mediate communications among municipalities by relaying directives from state and federal governments regarding emergency operations, such as implementing public policies regarding specific diseases and delivering public services such as vaccinations to citizens.¹ Recognizing their critical role in responding to health crises, we selected county health departments as our unit of analysis.

Regarding intrascale operations, the capacity of a county public health department to mobilize surge activities and make decisions regarding internal allocation of time, space, and energy is interdependent with actions of other administrative units within the department (Agranoff, 2007). Consequently, internal communications within county health departments shape the capacity of the department to mobilize response actions to a public health emergency.

Regarding interscale operations, county health departments constitute an administrative organization that mediates among different operational scales, for example, municipal, state, and federal levels of jurisdiction in the larger federal public health system (Ansell & Gash, 2008, 2017). Reciprocally, county governments transmit assessments of current needs from the municipalities to state and federal agencies in rapidly changing conditions. External communications to outside actors shape the context in which the department operates, as well as its capacity to secure additional resources for service delivery and to inform its clientele regarding expected changes in the time and scale of available services. These reciprocal communication functions create a continuing dialogue both within county departments regarding management of their respective internal operations and between the county departments and the municipalities within their jurisdictional boundaries as well as state-level agencies that may offer external resources and support or set constraints for performance.

Escalating Stress on County Health Departments During the 2009 H1N1 Outbreak

Analyses of the departments’ response operations show the effects of the stresses most clearly. During the H1N1 crisis, county health departments’ operations were extremely stretched due to the institutional and contextual conditions. Public health departments have a full slate of ongoing responsibilities in delivering public services. Local, state, and federal laws and regulations determine what these responsibilities are, so each county health department has a specific set of responsibilities, although sets are broadly similar across a single state in the United States (National Association of County and City Health Officials, 1995). Cases were growing rapidly, and even though the death rate was low, there was a great need for a vaccine and for testing to identify cases at the community level. Without proper response at the community level, the infection would continue to spread, largely unchecked, escalating the crisis.

County health departments across the United States assumed the task of responding to and addressing the H1N1 outbreak, given their roles in monitoring disease outbreaks and serving as key players in providing vaccines in their respective communities. Budget crises across the country following the 2007 recession had depleted health department budgets, leading to reduced resources and staffing levels, just as pressure built on laboratories and epidemiologists employed by health departments to track and respond to health emergencies. Surge operations, such as response to large-scale outbreaks such as the 2009 H1N1 crisis, placed additional burdens on the staff of a health department, because staff must respond to the emergency while maintaining day-to-day responsibilities. These tensions created a management challenge for county health departments that revealed different strategies of coping and different consequences for departmental personnel in practice.

Case Selection: Four Counties in California

As a subset of a larger study on preparedness of public health agencies for managing major public health emergencies in the United States,² the research team observed four county health departments that responded to the H1N1 threat in one state from April 2009 and 12 months following. By choosing public health departments in one state, the research team held constant the legal status and role of health departments. The state jurisdiction is the lowest administrative level at which county-level health departments can be compared as distinct units of analysis. Because different states organize and empower their counties differently, comparing counties across states would add a confounding variable for differing political and legal situations.

California was selected as the state in which to conduct a set of qualitative case studies for several reasons. The state, bordering on Mexico, was the epicenter of the H1N1 outbreak in the United States, as well as a state in which budget challenges placed additional stress on its county health departments. There are 58 county health departments in California, representing wide variation in basic characteristics. These characteristics include size of population served, number of personnel employed, type of organizational structure, decision-making styles, information infrastructure, exercise of authority, experience with past public health threats, severity of exposure to the H1N1 threat, proportion of county budget available for surge activities, relations with external stakeholders, and other environmental and geographic conditions (see Table 1).

Table 1.

Case Selection Categories (H1N1 Incidence Rate/Organizational Capacity).

H1N1 incidence		Organizational Capacity: [Public health budget + staff size]/per capita
H1N1 incidence		Large	Mid–small
Incidence Rate: H1N1 incidence/100,000 population	High	High incidence rate + large organizational capacity	High incidence rate + mid/small organizational capacity
Incidence Rate: H1N1 incidence/100,000 population	Low/Med	Low/Med incidence rate + large organizational capacity	Low/Med incidence rate + mid-small organizational capacity

To capture the operational context in which health departments functioned during the crisis, we used a mixed-methods research design, combining incidence data from the CDC (Centers for Disease Control, June, 2010, budgetary and personnel data from California counties (California Department of Health, 2005-2011), and qualitative interview data from four county health departments in California. The research team purposefully selected cases utilizing the combination of the most similar and the most different system design strategy (Przeworski & Teune, 1970). The similarity between groups allows the identification of concomitant variations among the cases that might affect the response communication and performance. At the same time, by comparing differences among cases, extraneous variations are excluded among the cases. This case selection strategy allows comparison of both response communication and performance of health departments that have similar characteristics, as well as variation in their capacity to respond. This case selection strategy also enables control of alternative factors, such as number of H1N1 cases and initial organizational capacity, which might affect equally the level of stress on county departments as well as response communication and performance. In addition, we included geographic location and per capita adjustment to the case selection process to control for variation due to proximity to possible H1N1 threats and population sizes.

Of the 58 counties in California, the research team identified two clusters of counties based on the initial size of the H1N1 incidence on response performance (high/low incidence). The initial size of the H1N1 incidence is the major extraneous factor that could affect the inter- and intraorganizational response communications, decision making, and performance of actors (Ostrom, 2005). A high level of incidence at the initial phase increases stress and can be detrimental to an organization’s response performance. A sudden outbreak limits time for organizations to acquire necessary information and resources, thus increasing organizational stress. Comparatively, lower levels of H1N1 cases seeking services or an incremental increase in incidents allow time for organizational learning and adaptation. With more time for adaptation to the threat, departments may experience less strain in their response processes.

Based on the county health department’s initial organizational capacity (large/mid–small), the research team identified a second set of clusters. Organizational capacity was measured by size of budget and number of full-time equivalent (FTE) staff. Counties with higher public health budgets and more personnel have greater resources and, so, can more readily adapt to higher levels of stress, whereas counties with lower budgets and smaller staff size will have fewer resources and greater constraints in adapting to stress.

Within the strategic combination of two group clusters, four different grouping combinations were identified. This strategy supports the comparison of the most similar and most different subsystems. Any two county groups became the most similar cases in one context (e.g., H1N1 incidence) or the most different cases in another context (organizational capacity; Przeworski & Teune, 1970) (see Table 2).

Table 2.

Selected Cases: County Health Departments.

H1N1 incidence		Public health budget, staff size per capita
H1N1 incidence		Large	Mid–small
H1N1 incidence/100,000 population	High	County B Health Dept	County A Health Dept
H1N1 incidence/100,000 population	Low/Med	County C Health Dept	County D Health

Finally, one county from each group category was selected for a total of four counties, labeled A, B, C, and D. In the final selection process, variations in geographic location were considered, as well as the level of urbanization of counties. Additional criteria controlled for extraneous impacts on communication and response performance. Among the selected counties, two are large, urban counties; one is a medium suburban county; and the other is a small, rural county. The four county cases are geographically dispersed across California. We do not disclose any county identifiers to protect the confidentiality of respondents and their organizations.

Figure 1 presents the per capita incidence of H1N1 in that county during the initial surge, May 28 to July 16, 2009. Counties A and B showed the higher incidence of H1N1 cases for the initial phases, and Counties C and D a lesser incidence. Figure 2 presents the budget allocations for the public health departments over the 5 years from 2005 to 2010. Counties A and D had the larger budget amount, and B and C the smaller. Figure 3 presents staffing that shows the larger organizational capacity of A and D, and comparatively smaller capacity of B and C. The smaller budgets and declining personnel of B and C might contribute to the initial tension between existing resources and increasing demand for public health services with the onset of the surge.

Figure 1.

H1N1 incidence: Total cases per 100,000 population.

Figure 2.

Public health departments’ total budget per capita.

Figure 3.

Public health department staffing per capita.

The research team examined how a select set of county health departments in California responded to the H1N1 outbreak to investigate ways in which this stress affected individual behaviors in county-level public health departments, the primary responders to health crises in California, and how organizational unit behaviors within departments influenced department-level performance.

Data: Semistructured, Face-to-Face Interviews and Secondary Data

Qualitative interviews served as the primary method of data collection, supplemented by review of secondary documents and policy reports. The interview protocol was designed to identify factors that either positively or negatively affected the overall public health response operations during the response to H1N1. Although the protocol provided the primary guidelines for making observations, interviews were conducted in a more flexible, semistructured, or open ended, format. During some of the interviews, interviewers adapted the questions to allow respondents to provide specific information about their response behaviors in varying organizational contexts. Thus, the interview data provide rich information of both intra- and interorganizational communication in the response systems and contextual information, such as emerging threats, and intra- and interorganizational behaviors for adapting to organizational stresses.

In addition to the interview data, we sought information from multiple secondary data sources. We reviewed documents characterizing the initial conditions of the counties in terms of population, budget data, and organizational size of county health departments. Furthermore, we analyzed policies and protocols of the public health system for managing infectious diseases to define the organizational structure within which the H1N1 outbreak occurred. These types of secondary data provided the essential background information for the four cases, as well as evidence to eliminate potential common-source and retrospection bias. These additional sources of data served to validate the results from the interview data and improved the reliability of the study findings.

Fieldwork

To gain direct insight into the impact of the H1N1 surge on departmental performance, the research team conducted 28 semistructured, face-to-face interviews with health department staff from the four selected counties after the H1N1 surge had largely concluded. Table 3 provides information about interview participation and scheduling. The interviews were scheduled with the full cooperation of each department, which self-selected the most knowledgeable personnel to participate in the process. Each interview included at least one and most often a small group of two to four health department employees representing at least one and, most often, two or three different divisions within the department. This collaborative survey method ensured the willingness of the participants to discuss the effects of the H1N1 surge on departmental performance but changed the interview process into a more informal focus group of informed departmental employees, rather than a set of individual interviews to be analyzed as a representative sample. Instead, this set of interviews and the data produced by this method constitute qualitative profiles of each county health department that provide candid insight into the actual practices carried out in each organization. We do not claim representativeness for the data in standard survey terms; instead, we use process tracing and abductive reasoning (Bennett & Checkel, 2015) to produce the most logical interpretation of organizational performance under stress, given the data available.

Table 3.

Interview Information.

County	A	B	C	D
Interview dates (2010)	March 10-11	April 12-14	February 17	February 18-19
Number of interviews	9	7	9	3
Interviewers per interview	2-3	3-5	2-3	1-4
Interviewees per interview	1-3	1-4	1	1-2
Divisions represented per interview	1	1-3	1	1-2

Given the constraints of the data collection process, the number of researchers conducting the interviews varied by day and time for the four site locations. An experienced researcher, assisted by two to three additional researchers, conducted each interview. For three of the four cases, interviews were scheduled over several days, depending on the availability of the designated interviewees. Assistant researchers served to corroborate professional observations based on the shared interview protocol, as well as to validate information reported informally. All interview recordings were transcribed, and after transcription, the original protocols were destroyed for the protection of the interviewees. This protection was an explicit condition requested by the health departments to gain their participation in the study.

Qualitative Data Analysis

In a qualitative study, data processing, analysis, findings, and interpretations are not independent but continuous and simultaneous processes (Lacey & Luff, 2001). In this study, important themes and their causal relationships are identified through iterative data reviews and analyses (Bennett & Checkel, 2015; Bennett & George, 1997; Martin & Turner, 1986) using (a) traditional grounded theory-based qualitative analysis (Martin & Turner, 1986) and (b) process tracing (Bennett & George, 1997) in conjunction with qualitative Bayesian network analysis.

The first step, traditional grounded theory-based qualitative analysis, focuses on identifying emerging themes and specific factors within each theme, if applicable, that influenced the county public health departments’ response behaviors under stress and that were attributable to conditions of response operations. The analysis started from data processing, transcribing the interview data. Each researcher transcribed information from recorded files of interviews into text, grasping the overall content of the interviews and identifying both common and distinctive ideas repeated across the set of respondents. Next, the researchers conducted an axial coding analysis using Atlas.ti software. Specifically, individual researchers entered the transcribed data into Atlas.ti software, and read through the whole set of interview transcripts multiple times, marking and revisiting relevant information regarding the research questions. Finally, researchers collectively verified emerging themes and specific factors within each theme by cross comparing their codes and identifying common characteristics, that influenced the county public health departments’ communication patterns under stress and that were attributable to conditions of response operations.

As the second step analysis, we used process tracing (Bennett & Checkel, 2015; Bennett & George, 1997) to develop a qualitative Bayesian network analysis platform, based on iterative reviews of both interview transcripts and secondary data. In this step, we first traced detailed relationships among the emerging themes/specific factors, such as the increase in number of reported cases, the increase in number of hours worked by departmental personnel, and the decline in reported communications among affected units in responding departments. These steps were then correlated with data verifying the decrease in budgets among the affected counties. Based on comprehensive understanding of the interview content, we determined a step-by-step time sequence among themes and factors and visually mapped the sequential relationships among themes and factors.

In the meanwhile, we measured subjective probabilities—prior and posterior probabilities—of presence and absence of those themes/factors in actual H1N1 response operations. A prior probability indicates the chance of a theme/factor being present or absent by itself, independent from any connections to other themes/factors. Because the desired value for an actual prior probability of each theme/factor was unknown, we assigned neutral probability, 50%, to each theme/factor, given the 0% (absence) and 100% (presence) range. A posterior probability denotes the conditional probability of a theme/factor being present or absent depending on the presence/absence of its antecedent theme/factor. The posterior probabilities were identified as a composite value by researchers’ collective assessment of interview data, such as relative frequencies of each theme/factor and interviewees’ opinions or evaluations on each theme and factor.

Finally, we built a qualitative Bayesian network by assigning subjective probabilities of absence and presence to each theme and its factors on the sequential map among the themes and factors. In the process, QGeNie (Decision Systems Laboratory, 2013), a decision analysis software program, was used to build the Bayesian network that presents composite conditional probabilities of presence/absence of themes/factors taking account of the interdependence among connected themes/factors. The program calculates the composite probability of a theme/factor within the complex network and translates the probability as a color within the spectrum between red (0% indicating a total absence), white (50%, neutral), and green (100%, a total presence).

For example, if the composite probability of a theme/factor is close to 95%, the color theme/factor is a darker green than another theme with 75%. In addition, if the composite probability of a theme/factor is 5% (close to total absence), its color is darker red than another theme with 30% (some absence). Within this color spectrum, the program supports visualization of both direct and indirect relationships between any two themes/factors within the network. For example, the relationships include cause (e.g., presence of A causes absence/presence of B), required (e.g., presence of A is required for absence/presence of B), barriers (e.g., absence of A results in absence/presence of B), or inhibitive (presence of A limits presence/absence of B). These relationships represent the actual H1N1 response operations of the county departments of public health, as documented by the qualitative interviews reported in Table 4, below (Decision Systems Laboratory, 2013).

Table 4.

Emerging Themes From Grounded Theory Qualitative Analysis.

Emerging themes	Dimensional factors within themes	Definition/meaning
Collaboration		Any collaboration between health department and nonprofit, private organizations, other public agencies
Command	Reporting structure	Any preset or emergent structure that lower level employees in public health department followed for making reports to superior officers within or outside of public health department
Command	Consistency of command chain	Given command structure which public health department employees were supposed to follow or emerged command structure that was followed
Communication	External—other public agencies	Any communication between health department and other public agencies at any level
	County—other departments	Any communication between the health department and other departments in the county government
	Internal—within public health department	Any communications between employees of the same county health department
	Internal communication structure	Any informal communication that occurred outside official channels or based on personal relationships within the public health department (degrees of freedom)
Decision making		State decision for emergency declaration
Defensive routines		Any defensive or self-protective actions or behaviors by employees or organizations (mostly at the lower level), which do not necessarily improve the efficiency or effectiveness of their tasks or actions but satisfy the criteria imposed by their superiors
Distributed cognition		Indications of differentiated knowledge between actors or events that provided differing understandings of the developing situation, not including job specializations
Information channels	External—other public agencies	Any information-sharing activities between health department and other public agencies at any level
	County—other departments	Any information-sharing activities between health department and other departments in the county government
	Internal—within public health department	Any information-sharing activities between employees of the same county health department
Organizational adaptation		The capacity of a department to adjust its allocation of resources, time, and personnel to meet current demands appropriately
Preparedness		Any sets of skills, resources, relationships, or techniques that the public health department possessed as part of preincident preparedness training or preparation
Role of the public health department		The major role of department of public health in each county in response to H1N1 incident
Resource	Allocation	Any activities related to way in which public health allocated resources, including human resources, to carry out its response to H1N1
Resource	Procurement	Any activities related to way in which public health obtained resources, including human resources, to carry out its response to H1N1
Task adjustment		Any indication of adjustments by public health department personnel to adjust activities according to changes or updates in actual or perceived conditions
Response performance		Any actions taken by the public health department in response to H1N1 threat

In addition, the Q-GeNIe program supports sensitivity testing of the model and assessment of the absence/presence of critical factors that affect the county public health departments’ performance in response to the H1N1 crisis (Decision Systems Laboratory, 2013). Every step of data analysis involved iterative review of the transcribed interview data and was validated by information from secondary sources regarding the H1N1 outbreak and the reported structure and responsibilities of county health departments in California. In addition, each preceding analysis provided findings for data interpretation, as well as the basis for the next step of the analysis.

Findings

From the iterative review of data and coding processes, we identified a total of 13 emerging themes. As shown in Table 4, among the 13 themes, four themes (first column, bold text) are composed of two to three associated factors (second column, italicized text) for a total of 11 associated factors, whereas nine themes are specific enough to have no associated factors. The associated factors indicate components of the theme, describing diverse dimensions of the respective emerging themes. Definitions for both themes and their associated factors are listed in the third column. The definitions explain the meaning of each theme and factor based on how respondents spoke about their experiences during the H1N1 crisis.

Based on an iterative assessment of the interview and documentary data, we identified that presence/absence of “distributed cognition” (Hutchins, 1995) among staff of a department of public health (DPH), public health department “adaptation” (Fligstein & McAdam, 2012) and “defensive routines” (Argyris, 1990) were the direct antecedents of “actual department of public health response on H1N1 (response performance).” In addition, we observed that presence and absence of these direct antecedents were conditional on the complex interdependence among themes/factors operating at different scales. The operational scales include (a) county DPH level (individual unit at the lowest [micro] scale), (b) county government level (administrative unit at midlevel [meso] scale), (c) external to county government level (external decision-making authorities at the highest [macro] level, such as state and federal government, and nonprofit and private organizations), (d) contextual level (themes and factors exogenous to any of the scales).

Interpreting the data according to scale of operations, Figure 4 identifies the relationships among the scales that influence the three major antecedents of DPH response performance. The right side of the figure presents the causal relationship between distributed cognition and adaptation to the effectiveness of the organization’s response to the H1N1 outbreak. The ability to adapt in response to the outbreak and an organization’s ability to transfer information from those who know the information to those who need it, especially, when no one person knows all the relevant information, drives an organization’s response and highly influences the organization’s behavior. The more readily and accurately this information is transmitted and received, the more effective the response will be (Comfort, 2007; Comfort, Oh, Ertan, & Scheinert, 2010; Holland, 1995/1996; Luhmann, 1989/1996; Smith, 2012). This assertion is supported not only by theory and research findings but also by the respondents in the qualitative interviews.

Figure 4.

Operational scales and DPH H1N1 response performance.

The key insight of Figure 4 is not this relationship, although it is important, but that defensive routines (Argyris, 1990) inhibit the transfer of information and the organization’s ability to adapt. Defensive routines break down communication as staffers seek to avoid interaction, breaking information channels and preventing information from reaching those who need it.

We arranged the remaining themes/factors according to the scales of operation from which they emerged and identified the detailed relationships among themes and factors embedded within each operational scale, shown in Figure 5. At the external authority scale (top left), hierarchical command structures exercised by the external authority inhibit public health departments’ communication and collaboration with a variety of groups, such as nonprofits, private, state, and federal actors. Department of health respondents indicate how hierarchies can inhibit collaboration and communication. Organizational hierarchies enforce interaction within the hierarchy, while limiting the interaction of ground-level operators with ground-level operators from other organizations and hierarchies (Chisholm, 1989).

Figure 5.

Intrascale operations.

At the county government scale (top right), communication and effective information flows were required for the decision to declare an emergency. A declaration of public health emergency might encourage organizational adaptation, allowing the health department to shift staff responsibilities from daily maintenance to focus on the emergency. As discussed by the respondents, maintaining the primary (nonemergency) roles of each department inhibits communication and information flow regarding the immediate crisis, presumably by enforcing existing organizational priorities and hierarchical rules. However, responses and after-action reports indicated general confusion about who could and could not declare public health emergencies at the county level. Whereas most local health officers and county executives declared emergencies locally, allowing the county health departments to change or reprioritize responsibilities toward responding to the emergency, it cannot be assumed that a department would easily accomplish this shift of responsibilities and operations once the local emergency is declared.

The relationships among themes/factors that emerged at the county department level (bottom right) show the importance of communication structure (freedom to choose how communication is routed in an organization) in the presence of actual communication among divisions during response operations. In addition, the data also indicated that task adjustment connects to communication among division managers and division staff through an inhibitor link. However, if staff members have greater freedom in their communication across organizational units, they can calibrate the adjustments more appropriately to reduce this inhibition. That is, task adjustment makes operations more complex, whereas freedom in communication allows staff members to adapt their actions reciprocally, reaping the benefits of task adjustment while minimizing its costs.

Altogether, the results of intrascale operations indicate communication patterns (diverse probability of absence or presence) at each scale of operation as the major force that was either required or causing the presence and absence of other succeeding themes/factors within each scale.

Finally, we traced the extended relationships among all themes/factors across four different scales of operation to examine the extent to which the presence/absence of individual themes/factors within the four scales of operation are required, necessary, impeding, or causing the presence/absence of the direct antecedents of effective response performance of county public health departments. Figure 6 depicts the overarching relationship among all factors interacting across all scales of operation into a single Bayesian network. The diagram shows how the prevalence of each theme/factor across operational scales changed relative to the presence/absence of a relationship with other themes/factors.

Figure 6.

Overarching relationships among factors as an interscale operation.

Again, the overarching relationship among themes/factors emphasize that limited/lacking communication weakened organizational adaptation among divisions within public health departments, hampered information distribution between those who had it and those who needed it, in a context of distributed cognition (Hutchins, 1995). Limited communication then fueled defensive routines, which, in turn, undermined the response operations. In addition, the data show that an overreliance on hierarchical structure and ongoing day-to-day tasks, combined with a lack of communication, led to a strong presence of defensive routines as behaviors that undermined the departments’ actual response performance and challenged organizational adaptation that would have aided the response performance.

Discussion

Our exploration of the H1N1 response processes of four county public health departments in California in 2009 to 2010 as a comparative case study offers insights into the process of organizational adaptation in stressful operational environments. With the above findings, we can now return to the questions stated earlier, and which we restate here: (1) What factors enable organizations to manage stress effectively? (2) What factors inhibit organizational adaptation under stressful conditions? (3) What costs and consequences ensue for organizations that fail to adapt their performance under stress?

First, findings indicate that organizational adaptation served as the primary determinant of the departments’ H1N1 response performance and occurred as a function of complex and constant communications within and across operational scales. We found a higher level of adaptation in county public health departments that had open communication structures and encouraged active communications within and across organizations. Through communications, the departments obtained information regarding changing situations and mobilized additional resources to meet unexpected needs. With additional information and resources, departments could adapt their operations to manage emerging stress effectively during the response surge.

Second, we documented that weak or absent communication within and across different operational scales hindered adaptation, while contributing to the creation of defensive routines that focus on protecting internal operations from external stressors. The defensive routines further distorted communication channels and inhibited departments in adjusting their resources, time, and personnel to meet the increasing demand from clients seeking information regarding H1N1 or presenting symptoms that were similar to H1N1. The findings documented the concept of defensive routines, initially identified by Argyris (1990), as disruptive to organizational performance in changing conditions.

Third, findings indicate that successful adaptation to stressful environments helped the department focus more time and energy at different scales of operation over a wider space of service delivery in meeting their emerging priority, responding to H1N1. Likewise, departmental failure to adapt to stressful operational environments caused a drain on internal capacity that delayed timely response and engendered public criticism for failing to meet obvious demands of the crisis.

These findings emphasize “communication” as the key to the overarching system process because the composite probability of communication factors across scales was required or causing presence/absence of many other succeeding factors that have strong impact on the intensity and occurrence of major antecedents of DPH response performance: “distributed cognition,” “defensive routines,” and “DPH organizational adaptations.” First, in the overarching interscale response process, communication processes that were either weak or absent within and across scales of operation discouraged distribution of information and formation of distributed cognition within public health departments. Second, at the public health department scale, weak communication structures caused weak communication processes among divisions within public health departments. Communication with other departments within county governments was more likely to be absent. In addition, lack of communication between public health departments and other external authorities resulted in the absence of multiple other factors that ultimately weakened communication among divisions within public health departments. The cumulative impact of weak/no communications within and across operational scales contributed to the strong presence of defensive routines within the public health departments (Argyris, 1990).

Defensive routines represent actions and behaviors that are taken to protect the interests of individual personnel or departmental units from criticism or heavier workloads (Argyris, 1990). Defensive routines within the department prevented effective and adaptive emergency responses under stressful work conditions. Finally, communication within and across scales was required for emergence of themes/factors influencing the public health department organizational adaptation, such as resource procurement and allocation at the county level, collaboration and information sharing at the external authority level, and task adjustment at the public health department level. However, gaps in communication within and across scales contributed to the weak capacity of departments to adjust their resources, time, and personnel to meet the increasing demand from clients seeking information regarding H1N1 or presenting symptoms that were similar to H1N1.

Conclusion

In today’s world of rapid social, technical, and economic change, organizations are operating in increasingly complex environments that generate urgent demands for immediate action (Innes & Booher, 2010). Yet, organizations are constrained by the limits of human capacity to manage physical and mental stress for sustained periods (Klein et al., 1993; Rittel & Webber, 1973). A key measure of an organization’s resilience is the ability to adapt its internal structure to create a viable mode of operation in urgent environments, thereby increasing its capacity to meet heavy external demands. Calibrating the internal structure of the organization to fit the demands from its external environment requires a dynamic process of adaptation within the organization as it seeks assistance from external sources and integrates external resources into daily operations to manage both daily and external demands.

Previous research has explained the impact of organizational adaptation on organizational performance, but has tended to focus only on internal operations in stable environments (Barzelay, 1992; Hoschka, 1996; Staw & Cummings, 1990). Existing studies also stress organizational interaction with external factors for effective organizational adaptation (Kelman, 2005; Kettl, 2016; Nohria & Eccles, 1992) but most look at adaptation in isolation from the constraints and tasks of organizations in a given context. This study addresses that gap, explaining why the internal structure of the organization needs to communicate its need for immediate assistance to those external organizations that can provide supplementary support. Taking a comprehensive approach to system analysis and assessment, this study acknowledges the complex interdependencies between internal operations, external stressors, and communication processes, and explains how organizations adapt to a sudden increase in demands for extra services, while maintaining daily functions.

Crises will continue to occur and health departments need to respond to them. This research underlines the importance of clear and open channels of communication both within and between organizations. For health departments to improve their response to crises and address the criticisms that were made during the H1N1 crisis, they will need to find tools and techniques to facilitate this communication more effectively. Many organizations already make regular use of dashboard tools designed to facilitate communication, but users often report that these tools are difficult or cumbersome. In addition, there is a proliferation of different platforms in different organizations and in different response arenas. Often, the emergency services – medical, fire, and police – personnel, emergency management professionals, and health officials will each have a form of dashboard, but, frequently, these will be different dashboard platforms. This situation presents problems with interoperability among systems, preventing these tools from aiding communication or the formation of common operating pictures. Nevertheless, these sociotechnical platforms offer a viable approach to address the twin challenges of maintaining both internal and external communications in crisis conditions if the platforms can be aligned. Aligning these tools will minimize the burden to responders, while ensuring that communications reach all responders who need access to this information.

Our conclusions come with limitations. We transcribed, coded, and analyzed interview data that had been collected by a subgroup of researchers in a larger research team, months after the height of the H1N1 crisis.³ This constraint limits the ability to generalize conclusions from the analysis, even within the case study settings. The data remain applicable to the research question and underline the importance of communication. That is, the data support the formulation of the conceptual Bayesian influence diagrams presented in Figures 4 to 6, but cannot be used to support a full Bayesian network analysis that formulates probability estimates of different outcomes or directly estimates how likely different policies or procedures will be in changing the outcomes of crises. Rather, the analysis provides general guidance regarding the impact of crisis conditions on organizational communication, but not specific instructions for improving communication channels both within and between organizations engaged in responding to public health crises. Yet, these findings are highly relevant to organizations operating in increasingly complex, dynamic, and often stressful contexts.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partially supported by Public Health Adaptive Systems (PHASYS), a project funded through the Center for Public Health Practice, University of Pittsburgh, by the Centers for Disease Control and Prevention (CDC; cooperative agreement 5P01TP000304-04). We further acknowledge, with thanks and appreciation, Margaret A. Potter, Past Principal Investigator, PHASYS, and Russell Schuh, Luis Duran, and Samuel Stebbins, colleagues on the PHASYS project. We also thank the anonymous reviewers for their thoughtful comments that contributed substantively to this article.

Notes

ORCID iDs

Louise K. Comfort

Jungwon Yeo

Author Biographies

Louise K. Comfort, PhD, is professor of public and international affairs and past director, Center for Disaster Management, University of Pittsburgh. She is a fellow of the National Academy of Public Administration and recipient of the 2016 Distinguished Citizen Award from Macalester College, St. Paul, Minnesota. Her primary research interests are in decision making under conditions of uncertainty and rapid change, interactions among technical and organizational systems under stress, and uses of information technology to develop decision support systems for managers operating under urgent conditions. She has engaged in field studies following 23 earthquake disasters in 14 countries, including the recent 2015 Kathmandu-Gorkha Earthquakes, Nepal.

Jungwon Yeo, PhD, is an assistant professor in the School of Public Administration at the University of Central Florida (UCF). Her main research interests include emergency and crisis management, decision analysis and decision support in complex environment, migrant and refugee integration, and organizational behaviors in the public sector.

Steven R. Scheinert, PhD, is a research assistant professor at the UCF, Department of Industrial Engineering and Management Systems. He is associated with the department’s Complex Adaptive Systems Lab (CASLab) and focuses on computational social science and data science. He received his PhD from the Graduate School for Public and International Affairs (GSPIA) at the University of Pittsburgh and recently completed a postdoctoral posting at the University of Vermont, which focused on computationally modeling public policy implementation.

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