Cost-Effective Drug Switch Options After Unsuccessful Treatment With an SSRI for Depression.

OBJECTIVE: Multiple treatment options are available for patients who do not respond to initial treatment for major depressive disorder. Previous results show that bupropion, sertraline, and venlafaxine are comparable in terms of therapeutic effectiveness following unsuccessful treatment with citalopram. In this study, we extended these results by incorporating costs of treatment to determine if one option was more cost-effective relative to others. METHODS: In the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) trial, 727 patients were randomly assigned to a switch drug treatment during level 2; 239 (33%) were assigned to bupropion, 238 (33%) to sertraline, and 250 (34%) to venlafaxine. For each study medication, the total costs included the costs of the medication, other concomitant medication and antidepressants, and health care facility utilization. Effectiveness was measured as remission and response. Cost-effectiveness was assessed as net health benefits. Stochastic analysis was performed by using the bootstrapping method. RESULTS: During level 2, mean medication costs were significantly higher for venlafaxine than for bupropion and sertraline ($968, $607, and $703, respectively). There were no significant differences among the switch medications in costs for other medications and health care facility utilization. Although the total costs were significantly different for the three medications (p=.025), none of the pairwise differences between medications were significant. Also, after jointly estimating costs and effects, the analyses found that net health benefits were not significantly different among the three drugs. CONCLUSIONS: After unsuccessful treatment with citalopram, the switch options of bupropion, sertraline, and venlafaxine were not significantly different from each other in terms of cost-effectiveness.

State-level legal preparedness for nuclear and radiological emergencies in the U.S.: a network analysis of state laws and regulations.

OBJECTIVE: This study explored if and to what extent the laws of U.S. states mirrored the U.S. federal laws for responding to nuclear-radiological emergencies (NREs). METHODS: Emergency laws from a 12-state sample and the federal government were retrieved and translated into numeric codes representing acting agents, their partner agents, and the purposes of activity in terms of preparedness, response, and recovery. We used network analysis to explore the relationships among agents in terms of legally directed NRE activities. RESULTS: States' legal networks for NREs appear as not highly inclusive, involving an average of 28% of agents among those specified in the federal laws. Certain agents are highly central in NRE networks, so that their capacity and effectiveness might strongly influence an NRE response. CONCLUSIONS: State-level lawmakers and planners might consider whether or not greater inclusion of agents, modeled on the federal government laws, would enhance their NRE laws and if more agents should be engaged in planning and policy-making for NRE incidents. Further research should explore if and to what extent legislated NRE directives impose constraints on practical response activities including emergency planning.

The effects of funding change and reorganization on patterns of emergency response in a local health agency.

Indicators for Stress Adaptation Analytics (ISAAC) is a protocol to measure the emergency response behavior of organizations within local public health systems. We used ISAAC measurements to analyze how funding and structural changes may have affected the emergency response capacity of a local health agency. We developed ISAAC profiles for an agency's consecutive fiscal years 2013 and 2014, during which funding cuts and organizational restructuring had occurred. ISAAC uses descriptive and categorical response data to obtain a function stress score and a weighted contribution score to the agency's total response. In the absence of an emergency, we simulated one by assuming that each function was stressed at an equal rate for each of the two years and then we compared the differences between the two years. The simulations revealed that seemingly minor personnel or budget changes in health departments can mask considerable variation in change at the internal function level.

State procurement law: facilitating the collaboration between health department and school of public health.

The mark of an "academic health department" includes shared activity by academic and practice partners sustained over time. Despite a long history of productive interactivity, the Pennsylvania Department of Health and the University of Pittsburgh's Graduate School of Public Health often faced administrative hurdles in contracting for projects of mutual interest. Seeking to overcome these hurdles, the Commonwealth of Pennsylvania and the University of Pittsburgh's Graduate School of Public Health negotiated a Master Agreement on the basis of statutes designating both as "public procurement units." This provided a template for project specifications, standard financial terms, and a contracting process. Since taking effect, the Master Agreement has supported projects in policy development, capacity building, workforce development, program evaluation, data analysis, and program planning. This experience suggests an approach potentially useful for other states and localities seeking to solidify academic health department partnerships either envisioned for the future or already in place.

Data for preparedness metrics: legal, economic, and operational.

Tracking progress toward the goal of preparedness for public health emergencies requires a foundation in evidence derived both from scientific inquiry and from preparedness officials and professionals. Proposed in this article is a conceptual model for this task from the perspective of the Centers for Disease Control and Prevention-funded Preparedness and Emergency Response Research Centers. The necessary data capture the areas of responsibility of not only preparedness professionals but also legislative and executive branch officials. It meets the criteria of geographic specificity, availability in standardized and reliable measures, parameterization as quantitative values or qualitative distinction, and content validity. The technical challenges inherent in preparedness tracking are best resolved through consultation with the jurisdictions and communities whose preparedness is at issue.

Geospatial analytics to evaluate point-of-dispensing sites for mass immunizations in Allegheny County, Pennsylvania.

CONTEXT: Public health agencies use mass immunization locations to quickly administer vaccines to protect a population against an epidemic. The selection of such locations is frequently determined by available staffing levels and in some places, not all potential sites can be opened, often because of a lack of resources. Public health agencies need assistance in determining which n sites are the prime ones to open given available staff to minimize travel time and travel distance for those in the population who need to get to a site to receive treatment. OBJECTIVE: Employ geospatial analytical methods to identify the prime n locations from a predetermined set of potential locations (eg, schools) and determine which locations may not be able to achieve the throughput necessary to reach the herd immunity threshold based on varying R0 values. DESIGN: Spatial location-allocation algorithms were used to select the ideal n mass vaccination locations. SETTING: Allegheny County, Pennsylvania, served as the study area. MAIN OUTCOME MEASURES: The most favorable sites were selected and the number of individuals required to be vaccinated to achieve the herd immunity threshold for a given R0, ranging from 1.5 to 7, was determined. Locations that did not meet the Centers for Disease Control and Prevention throughput recommendation for smallpox were identified. RESULTS: At R0 = 1.5, all mass immunization locations met the required throughput to achieve the herd immunity threshold within 5 days. As R0s increased from 2 to 7, an increasing number of sites were inadequate to meet throughput requirements. CONCLUSIONS: Identifying the top n sites and categorizing those with throughput challenges allows health departments to adjust staffing, shift length, or the number of sites. This method has the potential to be expanded to select immunization locations under a number of additional scenarios.

The adaptive response metric: toward an all-hazards tool for planning, decision support, and after-action analytics.

Local health departments are organized, resourced, and operated primarily for routine public health services. For them, responding to emergencies and disasters requires adaptation to meet the demands of an emergency, and they must reallocate or augment resources, adjust work schedules, and, depending on severity and duration of the event, even compromise routine service outputs. These adaptations occur to varying degrees regardless of the type of emergency or disaster. The Adaptive Response Metric was developed through collaboration between a number of California health departments and university-based preparedness researchers. It measures the degree of "stress" from an emergency response as experienced by local health departments at the level of functional units (eg, nursing, administration, environmental services). Pilot testing of the Adaptive Response Metric indicates its utility for emergency planning, real-time decision making, and after-action analytics.

Using Bayesian influence diagrams to assess organizational performance in 4 California county health departments, April-July 2009.

A Bayesian influence diagram is used to analyze interactions among operational units of county health departments. This diagram, developed using Bayesian network analysis, represents a novel method of analyzing the internal performance of county health departments that were operating under the simultaneous constraints of budget cuts and increased demand for services during the H1N1 threat in California, April-July 2009. This analysis reveals the interactions among internal organizational units that degrade performance under stress or, conversely, enable a county health department to manage heavy demands effectively.

The importance of nursing homes in the spread of methicillin-resistant Staphylococcus aureus (MRSA) among hospitals.

BACKGROUND: Hospital infection control strategies and programs may not consider control of methicillin-resistant Staphylococcus aureus (MRSA) in nursing homes in a county. METHODS: Using our Regional Healthcare Ecosystem Analyst, we augmented our existing agent-based model of all hospitals in Orange County (OC), California, by adding all nursing homes and then simulated MRSA outbreaks in various health care facilities. RESULTS: The addition of nursing homes substantially changed MRSA transmission dynamics throughout the county. The presence of nursing homes substantially potentiated the effects of hospital outbreaks on other hospitals, leading to an average 46.2% (range, 3.3%-156.1%) relative increase above and beyond the impact when only hospitals are included for an outbreak in OC's largest hospital. An outbreak in the largest hospital affected all other hospitals (average 2.1% relative prevalence increase) and the majority (~90%) of nursing homes (average 3.2% relative increase) after 6 months. An outbreak in the largest nursing home had effects on multiple OC hospitals, increasing MRSA prevalence in directly connected hospitals by an average 0.3% and in hospitals not directly connected through patient transfers by an average 0.1% after 6 months. A nursing home outbreak also had some effect on MRSA prevalence in other nursing homes. CONCLUSIONS: Nursing homes, even those not connected by direct patient transfers, may be a vital component of a hospital's infection control strategy. To achieve effective control, a hospital may want to better understand how regional nursing homes and hospitals are connected through both direct and indirect (with intervening stays at home) patient sharing.

School closure as an influenza mitigation strategy: how variations in legal authority and plan criteria can alter the impact.

BACKGROUND: States' pandemic influenza plans and school closure statutes are intended to guide state and local officials, but most faced a great deal of uncertainty during the 2009 influenza H1N1 epidemic. Questions remained about whether, when, and for how long to close schools and about which agencies and officials had legal authority over school closures. METHODS: This study began with analysis of states' school-closure statutes and pandemic influenza plans to identify the variations among them. An agent-based model of one state was used to represent as constants a population's demographics, commuting patterns, work and school attendance, and community mixing patterns while repeated simulations explored the effects of variations in school closure authority, duration, closure thresholds, and reopening criteria. RESULTS: The results show no basis on which to justify statewide rather than school-specific or community-specific authority for school closures. Nor do these simulations offer evidence to require school closures promptly at the earliest stage of an epidemic. More important are criteria based on monitoring of local case incidence and on authority to sustain closure periods sufficiently to achieve epidemic mitigation. CONCLUSIONS: This agent-based simulation suggests several ways to improve statutes and influenza plans. First, school closure should remain available to state and local authorities as an influenza mitigation strategy. Second, influenza plans need not necessarily specify the threshold for school closures but should clearly define provisions for early and ongoing local monitoring. Finally, school closure authority may be exercised at the statewide or local level, so long as decisions are informed by monitoring incidence in local communities and schools.

Simulation shows hospitals that cooperate on infection control obtain better results than hospitals acting alone.

Efforts to control life-threatening infections, such as with methicillin-resistant Staphylococcus aureus (MRSA), can be complicated when patients are transferred from one hospital to another. Using a detailed computer simulation model of all hospitals in Orange County, California, we explored the effects when combinations of hospitals tested all patients at admission for MRSA and adopted procedures to limit transmission among patients who tested positive. Called "contact isolation," these procedures specify precautions for health care workers interacting with an infected patient, such as wearing gloves and gowns. Our simulation demonstrated that each hospital's decision to test for MRSA and implement contact isolation procedures could affect the MRSA prevalence in all other hospitals. Thus, our study makes the case that further cooperation among hospitals--which is already reflected in a few limited collaborative infection control efforts under way--could help individual hospitals achieve better infection control than they could achieve on their own.

Preparedness for pandemics: does variation among states affect the nation as a whole?

OBJECTIVE: Since states' public health systems differ as to pandemic preparedness, this study explored whether such heterogeneity among states could affect the nation's overall influenza rate. DESIGN: The Centers for Disease Control and Prevention produced a uniform set of scores on a 100-point scale from its 2008 national evaluation of state preparedness to distribute materiel from the Strategic National Stockpile (SNS). This study used these SNS scores to represent each state's relative preparedness to distribute influenza vaccine in a timely manner and assumed that "optimal" vaccine distribution would reach at least 35% of the state's population within 4 weeks. The scores were used to determine the timing of vaccine distribution for each state: each 10-point decrement of score below 90 added an additional delay increment to the distribution time. SETTING AND PARTICIPANTS: A large-scale agent-based computational model simulated an influenza pandemic in the US population. In this synthetic population each individual or agent had an assigned household, age, workplace or school destination, daily commute, and domestic intercity air travel patterns. MAIN OUTCOME MEASURES: Simulations compared influenza case rates both nationally and at the state level under 3 scenarios: no vaccine distribution (baseline), optimal vaccine distribution in all states, and vaccine distribution time modified according to state-specific SNS score. RESULTS: Between optimal and SNS-modified scenarios, attack rates rose not only in low-scoring states but also in high-scoring states, demonstrating an interstate spread of infections. Influenza rates were sensitive to variation of the SNS-modified scenario (delay increments of 1 day versus 5 days), but the interstate effect remained. CONCLUSIONS: The effectiveness of a response activity such as vaccine distribution could benefit from national standards and preparedness funding allocated in part to minimize interstate disparities.

Developing a measure of local agency adaptation to emergencies: a metric.

Local public health agencies often must respond to health-related emergencies or disasters, while continuing to fulfill all public health functions for which they are funded. This article reports the development and initial pilot test of a method for measuring the nature and degree of a public health agency's response to such an emergency or disaster. How the instrument was developed as well as the initial results from the pilot study of four local public health systems (LPHSs) are presented and discussed. The instrument measured the extent to which each function and division of each of the four LPHSs were affected and provided a metric that could be used across LPHSs to indicate the burden experienced by each due to the emergency. Results obtained from the pilot study indicate that size and complexity of an LPHS was not predictive of its ability to respond to the emergency. These results support the use of the framework and associated measurement procedures to provide valuable information to managers responsible for such LPHSs. Such information should provide a foundation for comparing variations in performance and outcomes to various types of emergencies that vary in their severity and focus.

The benefits to all of ensuring equal and timely access to influenza vaccines in poor communities.

When influenza vaccines are in short supply, allocating vaccines equitably among different jurisdictions can be challenging. But justice is not the only reason to ensure that poorer counties have the same access to influenza vaccines as do wealthier ones. Using a detailed computer simulation model of the Washington, D.C., metropolitan region, we found that limiting or delaying vaccination of residents of poorer counties could raise the total number of influenza infections and the number of new infections per day at the peak of an epidemic throughout the region-even in the wealthier counties that had received more timely and abundant vaccine access. Among other underlying reasons, poorer counties tend to have high-density populations and more children and other higher-risk people per household, resulting in more interactions and both increased transmission of influenza and greater risk for worse influenza outcomes. Thus, policy makers across the country, in poor and wealthy areas alike, have an incentive to ensure that poorer residents have equal access to vaccines.

Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania.

BACKGROUND: During the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees. METHODS: A combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs. not closing schools) for different durations (range: 1 to 8 weeks) and symptomatic case incidence triggers (range: 1 to 30) for the state of Pennsylvania during the 2009 H1N1 epidemic. Different scenarios varied the basic reproductive rate (R(0)) from 1.2, 1.6, to 2.0 and used case-hospitalization and case-fatality rates from the 2009 epidemic. Additional analyses determined the cost per influenza case averted of implementing school closure. RESULTS: For all scenarios explored, closing schools resulted in substantially higher net costs than not closing schools. For R(0) = 1.2, 1.6, and 2.0 epidemics, closing schools for 8 weeks would have resulted in median net costs of $21.0 billion (95% Range: $8.0 - $45.3 billion). The median cost per influenza case averted would have been $14,185 ($5,423 - $30,565) for R(0) = 1.2, $25,253 ($9,501 - $53,461) for R(0) = 1.6, and $23,483 ($8,870 - $50,926) for R(0) = 2.0. CONCLUSIONS: Our study suggests that closing schools during the 2009 H1N1 epidemic could have resulted in substantial costs to society as the potential costs of lost productivity and childcare could have far outweighed the cost savings in preventing influenza cases.

Long-term care facilities: important participants of the acute care facility social network?

BACKGROUND: Acute care facilities are connected via patient sharing, forming a network. However, patient sharing extends beyond this immediate network to include sharing with long-term care facilities. The extent of long-term care facility patient sharing on the acute care facility network is unknown. The objective of this study was to characterize and determine the extent and pattern of patient transfers to, from, and between long-term care facilities on the network of acute care facilities in a large metropolitan county. METHODS/PRINCIPAL FINDINGS: We applied social network constructs principles, measures, and frameworks to all 2007 annual adult and pediatric patient transfers among the healthcare facilities in Orange County, California, using data from surveys and several datasets. We evaluated general network and centrality measures as well as individual ego measures and further constructed sociograms. Our results show that over the course of a year, 66 of 72 long-term care facilities directly sent and 67 directly received patients from other long-term care facilities. Long-term care facilities added 1,524 ties between the acute care facilities when ties represented at least one patient transfer. Geodesic distance did not closely correlate with the geographic distance among facilities. CONCLUSIONS/SIGNIFICANCE: This study demonstrates the extent to which long-term care facilities are connected to the acute care facility patient sharing network. Many long-term care facilities were connected by patient transfers and further added many connections to the acute care facility network. This suggests that policy-makers and health officials should account for patient sharing with and among long-term care facilities as well as those among acute care facilities when evaluating policies and interventions.