Life Is All about Timing: An Examination of Differences in Treatment Quality for Trauma Patients Based on Hospital Arrival Time

In health care, most quality transparency and improvement programs focus on the quality variation across hospitals, while we know much less about within‐hospital quality variation. This study examines one important factor that is associated with the fluctuation of quality of care in the same hospital—the timing of patient arrival. We analyze data from the National Trauma Data Bank and find that patients arriving at the hospital during off‐hours (6 PM–6 AM) receive significantly lower quality care than those who arrive during the daytime, as reflected in higher mortality rates, among other measures. More importantly, we try to uncover the mechanism for the quality variation. Interestingly, we find consistent evidence that the inferior care received during off‐hours is not likely due to unobserved heterogeneity, disruptions in circadian rhythms, or delays in receiving treatment. Instead, it is more likely due to the limited availability of high‐quality resources. This leads to a higher surgical complication rate, a higher likelihood of multiple surgeries, and longer patient length of stay in the intensive care unit. These findings have important implications for optimal resource allocation in hospitals to improve the quality‐of‐care delivery.     

An Empirical Study of the Relations Between Hospital Volume,Teaching Status,and Service Quality

This paper contributes to research on quality drivers in healthcare settings by examining the relationships between patient volume, teaching mission, and process quality in US hospitals. To develop a model that accurately assesses the impact of patient volume and teaching status on quality, we draw on three related research streams pertaining to the volume–quality relationship, the comparative quality of care in teaching and non‐teaching hospitals, and quality drivers in service institutions. We propose the impact of patient volume on process quality varies across hospitals with different teaching intensities. The test of this proposition uses a large data set that measures process quality for treatments for heart attacks and heart failures in all major US hospitals. Our results suggest that, as hospital teaching intensity increases, greater patient volume is associated with decreased process quality. Never before was such a relationship uncovered. This initial finding has important practical implications. First, the regionalization policy of hospitals should be re‐evaluated in light of their teaching function. Second, the root causes for the lower quality scores of large, high resident‐to‐bed ratio teaching hospitals, compared with smaller versions, must be found.     

Benefits of Surgical Smoothing and Spare Capacity: An Econometric Analysis of Patient Flow

In this study, we examine the hospital's ability to admit patients from its emergency department. From a medical perspective, the number of patients being admitted should depend solely on the patients’ clinical conditions. Using a large‐scale econometric study that includes detailed operational and clinical data on all cardiac patient encounters from a set of 128 hospitals over a period of four years, we show that this is not the case. In particular, we find that independent of their medical condition, many emergency patients are denied hospital admission because of a lack of inpatient beds. Our analysis suggests that having one more inpatient bed at the start of a day can increase the likelihood of an emergency room patient admission by around 3% on average. We examine two policies – active discharge and demand smoothing – that can help hospitals improve patient access. We find that some hospitals actively discharge inpatients when beds become scarce; hospitals that follow such an active discharge protocol are, on average, able to admit more patients. We also investigate to what extent the hospital's ability to smooth its surgical schedule impacts hospital admissions. Hospitals tend to schedule their elective patients early in the week (Mondays and Tuesdays), and discharge them by the weekend in order to minimize weekend staffing, effectively maximizing bed occupancy during the middle of the week. This “weekend effect” artificially induces variability, and reduces effective system capacity. We find that by scheduling patients more uniformly over the week, hospitals can dramatically increase patient access, obviating the need for active discharges or additional capacity investment. Our analysis quantifies these effects, and can help hospitals make effective capacity management decisions in order to improve patient flow.     

Competition and The Operational Performance of Hospitals: The Role of Hospital Objectives

We examine the effect of a hospital's objective (i.e., non‐profit vs. for‐profit) in hospital markets for elective care. Using game‐theoretic analysis and queueing models to capture the operational performance of hospitals, we compare the equilibrium behavior of three market settings in terms of such criteria as waiting times and patient costs from waiting and hospital payments. In the first setting, a monopoly, patients are served exclusively by a single non‐profit hospital; in the second, a homogeneous duopoly, patients are served by two competing non‐profit hospitals. In our third setting, a heterogeneous duopoly, the market is served by one non‐profit hospital and one for‐profit hospital. A non‐profit hospital provides free care to patients, although they may have to wait; for‐profit hospitals charge a fee to provide care with minimal waiting. A comparison between the monopolistic and each of the duopolistic settings reveals that the introduction of competition can hamper a hospital's ability to attain economies of scale and can also increase waiting times. Moreover, the presence of a for‐profit sector may be desirable only when the hospital market is sufficiently competitive. A comparison across the duopolistic settings indicates that the choice between homogeneous and heterogeneous competition depends on the patients' willingness to wait before receiving care and the reimbursement level of the non‐profit sector. When the public funder is not financially constrained, the presence of a for‐profit sector may allow the funder to lower both the financial costs of providing coverage and the total costs to patients. Finally, our analysis suggests that the public funder should exercise caution when using policy tools that support the for‐profit sector—for example, patient subsidies—because such tools may increase patient costs in the long run; it might be preferable to raise the non‐profit sector's level of reimbursement.     

When push comes to shove: implementing VBAC practice guidelines

The dramatic increase in U.S. cesarean sections over the past two decades has been significantly driven by repeat C-sections. In response to this trend, clinical guidelines recommending vaginal birth after cesarean-section (VBAC) have been promulgated by national organizations. Adherence to these guidelines would reduce the number of repeat C-sections, lower the overall C-section rate, and improve both the quality and the cost of health care. While these guidelines have received professional endorsement, their implementation has been clouded by issues of patient acceptance and provider payment. To examine implementation of these guidelines by health care organizations, the authors surveyed 156 members of the American College of Physician Executives to determine their policies, practices, and attitudes toward VBAC guidelines. Those surveyed generally were medical directors in HMOs, hospitals, and other practice settings. The findings indicate that the health care organizations represented by these physician executives have not consistently implemented VBAC guideline and that they are reluctant to hold physicians, their patients, or hospitals accountable for the financial, utilization, and quality impact of the elective decision ot to pursue appropriate VBACs. We conclude that, even when widely accepted, clinical practice guidelines may be ineffective in reducing the costs or improving the quality of medical care.     

The Role of Clinical and Process Quality in Achieving Patient Satisfaction in Hospitals

Managers constantly struggle with where to allocate their resources and efforts in managing the complex service delivery system called a hospital. In the broadest sense, their decisions and actions focus on two important aspects of health care—clinical or technical medical care that emphasizes “what” the patient receives and process performance that emphasizes “how” health care services are delivered to patients. Here, we investigate the role of leadership, clinical quality, and process quality on patient satisfaction. A causal model is hypothesized and evaluated using structural equation modeling for a sample of 202 U.S. hospitals. Statistical results support the idea that leadership is a good exogenous construct and that clinical and process quality are good intermediate outcomes in determining patient satisfaction. Statistical results also suggest that hospital leadership has more influence on process quality than on clinical quality, which is predominantly the doctors' domain. Other results are discussed, such as that hospital managers must be mindful of the fact that process quality is at least as important as clinical quality in predicting patient satisfaction. The article concludes by proposing areas for future research.     

A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health‐Care Settings

In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment‐caused injuries while in the hospital. While risk cannot be entirely eliminated from health‐care activities, an important goal is to develop effective and durable mitigation strategies to render the system “safer.” In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health‐care domain, this can be extremely challenging due to the wide variability in the way that health‐care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational‐level and policy‐level contributions to risk evolve over time, and how policies and decisions may affect the general system‐level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation‐based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient‐level factors and also physician‐level decisions and factors in the management of an individual patient, which contribute to the risk of hospital‐acquired AE. BBNs are networks of probabilities that can capture probabilistic relations between variables and contain historical information about their relationship, and are powerful tools for modeling causes and effects in many domains. The model is intended to support hospital decisions with regard to staffing, length of stay, and investments in safety, which evolve dynamically over time. The methodology has been applied in modeling the two types of common AEs: pressure ulcers and vascular‐catheter‐associated infection, and the models have been validated with eight years of clinical data and use of expert opinion.     

The Effect of Integrated Scheduling and Capacity Policies on Clinical Efficiency

In outpatient healthcare clinics, capacity, patient flow, and scheduling are rarely managed in an integrated fashion, so a question of interest is whether clinic performance can be improved if the policies that guide these decisions are set jointly. Despite the potential importance of this issue, we find surprisingly few studies that look at how the allocation of capacity, paired with various appointment scheduling policies and different patient flow configurations, affects patient flow and clinical efficiency. In this paper, we develop an empirically based discrete‐event simulation to examine the interactions between patient appointment policies and capacity allocation policies (i.e., the number of available examination rooms) and how they jointly affect various performance measures, such as resource utilization and patient waiting time. Findings suggest that scheduling lower‐variance, shorter appointments earlier in the clinic (and, conversely, higher‐variance, longer appointments later) results in less overall patient waiting without reducing physician utilization or increasing clinic duration. Additionally, exam rooms exhibited classic bottleneck behavior: there was no effect on physician utilization by adding exam rooms beyond a certain threshold, but too few exam rooms were devastating to clinic throughput. Some significant interactions between these variables were observed, but were not influential to the level of managerial concern. Clinicians' intuition about managing capacity in healthcare settings may differ substantially from best policies.     

Ice‐Breaker vs. Standalone: Comparing Alternative Workflow Modes of Mid‐level Care Providers

Capitalizing on the operational concept of division‐of‐labor, clinics often reduce physician service time by off‐loading some of his/her clinical activities to lower‐cost personnel. These personnel, such as nurse practitioners and physician assistants, are often collectively referred to as “mid‐level providers” (MLPs) and can perform many patient‐consultation tasks. The common rationale is that using an MLP allows the physician to serve more patients, increase patients’ access to care, and, due to MLPs’ lower salaries, improve the clinic's financial performance. An MLP is typically integrated into the outpatient clinic process in one of two modes: as an “ice‐breaker,” seeing each patient before the physician, or as a “standalone” provider, a substitute for the physician for the entirety of some patients’ visits. Despite both of these modes being widely used in practice, we find no research that identifies the circumstances under which either one is preferable. This study examines these two modes’ effects on operational performance, such as patient flow and throughput, as well as on financial measures. Using queueing and bottleneck analysis, discrete‐event simulation, and profit modeling, we compare these two deployment modes and identify the optimal policies for deploying MLPs as either ice‐breakers or as standalone providers. Interestingly, we also find there exists a range of scenarios where not hiring an MLP at all (i.e., the physician works alone) is likely to be most profitable for the clinic. Implications for practice are discussed.     

Formatting and presenting quality data to medical staffs and hospital boards

A host of historical and practical precedents have made hospitals responsible for the quality of care rendered within their facilities. The medical staff and the board of trustees share in this responsibility. Increasing demands for demonstrative evidence of the quality of care in an institution have made the process data-based. There is no substitute for specific data on the performance of both the hospital and its providers in the delivery of care. The trick, however, is in presenting this information to the medical staff and the board in a fashion that will be understandable and that will still maintain confidentiality of provider and patient. The authors offer a presentation system that has met with success in their community hospital.     

Performance Effects Related to the Sequence of Integration of Healthcare Technologies

There is a natural order to most events in life: Everything from learning to read to DNA sequences in molecular biology follows some predetermined, structured methodology that has been refined to yield improved results. Likewise, it would seem that firms could benefit by adopting and implementing technologies in some logical way so as to increase their overall performance. In this study of 555 hospitals, we investigate the order in which medical technologies are transformed into information technologies through a process of converting them from stand‐alone technologies to interoperable, integrated information systems and whether certain configurations of sequences of integration yield additional value. We find that sequence does matter and that hospitals that integrated foundational technologies first—which in this case are known to be more complex—tend to perform better. Theoretical and practical implications of this finding and others are discussed.     

Are Patients Patient? The Role of Time to Appointment in Patient Flow

The current state of outpatient healthcare delivery is characterized by capacity shortages and long waits for appointments, yet a substantial fraction of valuable doctors’ capacity is wasted due to no‐shows. In this study, we examine the effect of wait to appointment on patient flow, specifically on a patient's decision to schedule an appointment and to subsequently arrive to it. These two decisions may be dependent, as appointments are more likely to be scheduled by patients who are more patient and are thereby more likely to show up. To estimate the effect of wait on these two decisions, we introduce the willingness to wait (WTW), an unobservable variable that affects both bookings and arrivals for appointments. Using data from a large healthcare system, we estimate WTW with a state‐of‐the‐art non‐parametric method. The WTW, in turn, allows us to estimate the effect of wait on no‐shows. We observe that the effect of increased wait on the likelihood of no‐shows is disproportionately greater among patients with low WTW. Thus, although reducing the wait to an appointment will enable a provider to capture more patient bookings, the effects of wait time on capacity utilization can be non‐monotone. Our counterfactual analysis suggests that increasing wait times can sometimes be beneficial for reducing no‐shows.     

Clinical Capital and the Risk of Maternal Labor and Delivery Complications: Hospital Scheduling,Timing, and Cohort Turnover Effects

The establishment of interventions to maximize maternal health requires the identification of modifiable risk factors. Toward the identification of modifiable hospital‐based factors, we analyze over 2 million births from 2005 to 2010 in Texas, employing a series of quasi‐experimental tests involving hourly, daily, and monthly circumstances where medical service quality (or clinical capital) is known to vary exogenously. Motivated by a clinician's choice model, we investigate whether maternal delivery complications (1) vary by work shift, (2) increase by the hours worked within shifts, (3) increase on weekends and holidays when hospitals are typically understaffed, and (4) are higher in July when a new cohort of residents enter teaching hospitals. We find consistent evidence of a sizable statistical relationship between deliveries during nonstandard schedules and negative patient outcomes. Delivery complications are higher during night shifts (OR = 1.21, 95% CI: 1.18–1.25), and on weekends (OR = 1.09, 95% CI: 1.04–1.14) and holidays (OR = 1.29, 95% CI: 1.04–1.60), when hospitals are understaffed and less experienced doctors are more likely to work. Within shifts, we show deterioration of occupational performance per additional hour worked (OR = 1.02, 95% CI: 1.01–1.02). We observe substantial additional risk at teaching hospitals in July (OR = 1.28, 95% CI: 1.14–1.43), reflecting a cohort‐turnover effect. All results are robust to the exclusion of noninduced births and intuitively falsified with analyses of chromosomal disorders. Results from our multiple‐test strategy indicate that hospitals can meaningfully attenuate harm to maternal health through strategic scheduling of staff.     

Controversial Role of GPOs in Healthcare‐Product Supply Chains

This paper examines the controversial role that Group Purchasing Organizations (GPOs) play in the supply chains for healthcare products. Among the controversies, perhaps the most fundamental one is whether or not GPOs reduce purchasing costs for their members. However, the fiercest controversy is around the “contract administration fees (CAFs)” that GPOs charge to manufacturers. We examine these and other controversies using a Hotelling duopoly model. Among our conclusions: GPOs increase competition between manufacturers and lower prices for healthcare providers. However, GPOs reduce manufacturers' incentives to introduce innovations to existing products. We also demonstrate that the existence of lower off‐contract prices is not, per se, evidence of anticompetitive behavior on the part of GPOs. Indeed, we demonstrate that, under certain circumstances, the presence of a GPO lowers off‐contract prices. We also examine the consequences of eliminating the “safe harbor” provisions that permit healthcare GPOs to charge CAFs to manufacturers, and conclude that it would not affect any party's profits or costs.     

Predicting System Usage from Intention and Past Use: Scale Issues in the Predictors

The objective of this study is to provide insights into how the predictive power for computer‐recorded system usage can be improved. Based on 386 responses from actual users of an information system, we examine the predictive power for system usage according to the scales of the predictors used, namely, intention and past use. First, we show that the predictive power of intention can be significantly improved with the choice of an appropriate measure. However, even the desirable intention measure failed to explain two‐thirds of the variance in system usage. Second, the results show that past use as measured by computer‐recorded log data can significantly enhance our ability to predict system usage. Finally, when both intention and past use are controlled for, the explained variance in system usage is shown to vary widely from 20% to 73%, depending on the predictors' scales. Overall, our findings suggest that an accurate prediction of system usage requires a more rigorous approach than that often applied in information systems research.     

Toward an Effective Design of Behavioral Health Care Delivery: An Empirical Analysis of Care for Depression

A criticism of behavioral health care delivery is that it has largely missed the social determinants of behavioral health disorders and their diagnosis. Toward addressing this criticism, this study evaluates the delivery of behavioral health care as a part of primary care operations. Focusing on the treatment of depression, the study results show that: (i) primary care clinics operating in communities with superior social environment characteristics are associated with improved depression outcomes in the short term, and (ii) psychosocial resources (social and emotional support) and the built environment (man‐made resources and infrastructure to support human activity) of primary care clinics are associated with sustaining the improvement in depression outcome in the long term. Centering our attention on IT‐enabled, evidence‐based, and affordable primary care as mechanisms that can enable the integration of behavioral and medical care delivery, the results suggest that IT‐enabled and evidence‐based primary care are associated with improvements in depression outcomes. We also find that the effect of improving the affordability of behavioral health care delivery depends on the community's socioeconomic status. Primary care clinics in socioeconomically disadvantaged communities practicing cost‐containment are associated with improvements in depression outcomes, and, therefore, can contribute toward reducing disparities in behavioral health care delivery. Counter to our original expectations, we find that the effect of evidence‐based care on improvements on depression outcomes increases as the availability of medically trained behavioral health care specialists practicing in a community increases lending support to concerns that primary care clinics in resource‐rich communities obtain greater benefit from quality improvement interventions.     

Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise

Many real‐world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info‐gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable‐choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam.     

Quality management in ambulatory care: the future is now

Ambulatory care has always been a stepchild. Hospitals have been and are the focal point of quality activity. Traditionally driven by Joint Commission decree and more recently inspired by market forces, hospitals find the resources to do quality. It was quality assurance in the '80s. It is quality management in the '90s. Some of this activity has oozed out into ambulatory care, but not much. We in ambulatory care have been too busy producing as many patient visits as possible in an environment of limited resources. All that is now changing. As ambulatory care becomes more and more important in the overall health care delivery scheme, medical quality management in this environment will also take on greater significance. Leading the way will be the electronic medical record.     

Blocking in Healthcare Operations: A New Heuristic and an Application

We consider the problem of optimal capacity allocation in a hospital setting, where patients pass through a set of units, for example intensive care and acute care (AC), or AC and post‐acute care. If the second stage is full, a patient whose service at the first stage is complete is blocked and cannot leave the first stage. We develop a new heuristic for tandem systems to efficiently evaluate the effects of such blocking on system performance and we demonstrate that this heuristic performs well when compared with exact solutions and other approaches presented in the literature. In addition, we show how our tandem heuristic can be used as a building block to model more complex multi‐stage hospital systems with arbitrary patient routing, and we derive insights and actionable capacity strategies for a real hospital system where such blocking occurs between units.     

LEAN,GREEN, AND THE QUEST FOR SUPERIOR ENVIRONMENTAL PERFORMANCE

We examine the relationship between lean manufacturing practices and environmental performance as measured in terms of air emissions and resource use. We draw on two unique surveys of 31 automobile assembly plants in North America and Japan, which contain information on manufacturing practice and environmental performance, as well as in‐depth interviews with 156 plant level employees at 17 assembly plants. Our survey results and interviews suggest that lean management and reduction of air emissions of volatile organic compounds (vocs) are associated negatively. Lean manufacturing practices contribute to more efficient use of paints and cleaning solvents, but these in‐process changes are not sufficient to meet the most stringent air regulations. We found some evidence to support the link between lean practices and resource efficiency. While our survey results were in hypothesized direction, they were not statistically significant. In‐depth semi‐structured interviews, however, suggest a more robust relationship, and we use them to describe some mechanisms by which all three aspects of lean management (buffer minimization, work systems, and human resource management) may be related to environmental management practices and performance.