Social network analysis of patient sharing among hospitals in Orange County, California

Healthcare Antibiotic Resistance Prevalence - DC (HARP-DC): A Regional Prevalence Assessment of Carbapenem-Resistant Enterobacteriaceae (CRE) in Healthcare Facilities in Washington, District of Columbia

OBJECTIVE Carbapenem-resistant Enterobacteriaceae (CRE) are a significant clinical and public health concern. Understanding the distribution of CRE colonization and developing a coordinated approach are key components of control efforts. The prevalence of CRE in the District of Columbia is unknown. We sought to determine the CRE colonization prevalence within healthcare facilities (HCFs) in the District of Columbia using a collaborative, regional approach. DESIGN Point-prevalence study. SETTING This study included 16 HCFs in the District of Columbia: all 8 acute-care hospitals (ACHs), 5 of 19 skilled nursing facilities, 2 (both) long-term acute-care facilities, and 1 (the sole) inpatient rehabilitation facility. PATIENTS Inpatients on all units excluding psychiatry and obstetrics-gynecology. METHODS CRE identification was performed on perianal swab samples using real-time polymerase chain reaction, culture, and antimicrobial susceptibility testing (AST). Prevalence was calculated by facility and unit type as the number of patients with a positive result divided by the total number tested. Prevalence ratios were compared using the Poisson distribution. RESULTS Of 1,022 completed tests, 53 samples tested positive for CRE, yielding a prevalence of 5.2% (95% CI, 3.9%-6.8%). Of 726 tests from ACHs, 36 (5.0%; 95% CI, 3.5%-6.9%) were positive. Of 244 tests from long-term-care facilities, 17 (7.0%; 95% CI, 4.1%-11.2%) were positive. The relative prevalence ratios by facility type were 0.9 (95% CI, 0.5-1.5) and 1.5 (95% CI, 0.9-2.6), respectively. No CRE were identified from the inpatient rehabilitation facility. CONCLUSION A baseline CRE prevalence was established, revealing endemicity across healthcare settings in the District of Columbia. Our study establishes a framework for interfacility collaboration to reduce CRE transmission and infection. Infect Control Hosp Epidemiol 2017;38:921-929.

Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections

Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006-2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility's C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting "sensor" hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as "sensors" could be a cost-effective mechanism to monitor emerging nosocomial infections.

Transfer Frequency as a Measure of Hospital Capability and Regionalization

OBJECTIVE

To provide metrics for quantifying the capability of hospitals and the degree of care regionalization.

DATA SOURCE

Administrative database covering more than 10 million hospital encounters during a 3-year period (2012-2014) in Massachusetts.

PRINCIPAL FINDINGS

We calculated the condition-specific probabilities of transfer for all acute care hospitals in Massachusetts and devised two new metrics, the Hospital Capability Index (HCI) and the Regionalization Index (RI), for analyzing hospital systems. The HCI had face validity, accurately differentiating academic, teaching, and community hospitals of varying size. Individual hospital capabilities were clearly revealed in "fingerprints" of their condition-specific transfer behavior. The RI also performed well, with those of specific conditions successfully quantifying the concentration of care arising from regulatory and public health activity. The median RI of all conditions within the Massachusetts health care system was 0.21 (IQR, 0.13-0.36), with a long tail of conditions that were very highly regionalized. Application of the HCI and RI metrics together across the entire state identified the degree of interdependence among its hospitals.

CONCLUSIONS

Condition-specific transfer activity, as captured in the HCI and RI, provides quantitative measures of hospital capability and regionalization of care.

Spread of Carbapenem-Resistant Enterobacteriaceae Among Illinois Healthcare Facilities: The Role of Patient Sharing

BACKGROUND

Carbapenem-resistant Enterobacteriaceae (CRE) spread regionally throughout healthcare facilities through patient transfer and cause difficult-to-treat infections. We developed a state-wide patient-sharing matrix and applied social network analyses to determine whether greater connectedness (centrality) to other healthcare facilities and greater patient sharing with long-term acute care hospitals (LTACHs) predicted higher facility CRE rates.

METHODS

We combined CRE case information from the Illinois extensively drug-resistant organism registry with measures of centrality calculated from a state-wide hospital discharge dataset to predict facility-level CRE rates, adjusting for hospital size and geographic characteristics.

RESULTS

Higher CRE rates were observed among facilities with greater patient sharing, as measured by degree centrality. Each additional hospital connection (unit of degree) conferred a 6% increase in CRE rate in rural facilities (relative risk [RR] = 1.056; 95% confidence interval [CI], 1.030-1.082) and a 3% increase among Chicagoland and non-Chicago urban facilities (RR = 1.027; 95% CI, 1.002-1.052 and RR = 1.025; 95% CI, 1.002-1.048, respectively). Sharing 4 or more patients with LTACHs was associated with higher CRE rates, but this association may have been due to chance (RR = 2.08; 95% CI, .85-5.08; P = .11).

CONCLUSIONS

Hospitals with greater connectedness to other hospitals in a statewide patient-sharing network had higher CRE burden. Centrality had a greater effect on CRE rates in rural counties, which do not have LTACHs. Social network analysis likely identifies hospitals at higher risk of CRE exposure, enabling focused clinical and public health interventions.

Expelled uninsured patients in a less-competitive hospital market in Florida, USA

BACKGROUND

This research evaluates the effect of hospital competition on inward and outward patient transfers for different types of payers including the uninsured. Although it is a less spotlighted issue, an equally important topic is the likelihood of inter-hospital patient transfers of the insured and the uninsured. This study attempts to fill a gap in the research about the relationship between hospital competition and patient transfers.

METHODS

By developing the payer-specific level of hospital competition, this research evaluates the effect of hospital competition on inward and outward patient sharing (or patient transfers) for different types of payers including the uninsured. For patient transfers, instead of focusing on whether a patient is transferred from one hospital to another hospital at the patient level, we measure the numbers of patient transfers between hospitals (both inward and outward) at the hospital level. These dependent variables-the numbers of outward and inward patient transfers by the principal payers-are count variables, and we employ either a Poisson regression model or a negative binomial regression model.

RESULTS

Controlling for hospital characteristics, when the uninsured Hirschman-Herfindahl Index (HHI) increased by 0.01, the uninsured were 593 % more likely to be transferred to another hospital. When a hospital dominates its market, it tends to expel uninsured patients to other hospitals.

CONCLUSION

If patient transfers are medically unnecessary and primarily due to financial incentives, health administrators and policymakers should minimize such events. Since the uninsured who are admitted to a hospital that dominates its hospital market are likely to be much more vulnerable in their access to health care services, the state government of Florida needs to move toward increased health insurance coverage for eligible Floridians.

Electronic Public Health Registry of Extensively Drug-Resistant Organisms, Illinois, USA

In response to clusters of carbapenem-resistant Enterobacteriaceae (CRE) in Illinois, USA, the Illinois Department of Public Health and the Centers for Disease Control and Prevention Chicago Prevention Epicenter launched a statewide Web-based registry designed for bidirectional data exchange among health care facilities. CRE occurrences are entered and searchable in the system, enabling interfacility communication of patient information. For rapid notification of facilities, admission feeds are automated. During the first 12 months of implementation (November 1, 2013-October 31, 2014), 1,557 CRE reports (≈4.3/day) were submitted from 115 acute care hospitals, 5 long-term acute care hospitals, 46 long-term care facilities, and 7 reference laboratories. Guided by a state and local public health task force of infection prevention specialists and microbiologists and a nonprofit informatics entity, Illinois Department of Public Health deployed a statewide registry of extensively drug-resistant organisms. The legal, technical, and collaborative underpinnings of the system enable rapid incorporation of other emerging organisms.

Beyond the Intensive Care Unit (ICU): Countywide Impact of Universal ICU Staphylococcus aureus Decolonization

A recent trial showed that universal decolonization in adult intensive care units (ICUs) resulted in greater reductions in all bloodstream infections and clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA) than either targeted decolonization or screening and isolation. Since regional health-care facilities are highly interconnected through patient-sharing, focusing on individual ICUs may miss the broader impact of decolonization. Using our Regional Healthcare Ecosystem Analyst simulation model of all health-care facilities in Orange County, California, we evaluated the impact of chlorhexidine baths and mupirocin on all ICU admissions when universal decolonization was implemented for 25%, 50%, 75%, and 100% of ICU beds countywide (compared with screening and contact precautions). Direct benefits were substantial in ICUs implementing decolonization (a median 60% relative reduction in MRSA prevalence). When 100% of countywide ICU beds were decolonized, there were spillover effects in general wards, long-term acute-care facilities, and nursing homes resulting in median 8.0%, 3.0%, and 1.9% relative MRSA reductions at 1 year, respectively. MRSA prevalence decreased by a relative 3.2% countywide, with similar effects for methicillin-susceptible S. aureus. We showed that a large proportion of decolonization's benefits are missed when accounting only for ICU impact. Approximately 70% of the countywide cases of MRSA carriage averted after 1 year of universal ICU decolonization were outside the ICU.

Healthy versus Unhealthy Suppliers in Food Desert Neighborhoods: A Network Analysis of Corner Stores' Food Supplier Networks

Background: Products in corner stores may be affected by the network of suppliers from which storeowners procure food and beverages. To date, this supplier network has not been well characterized. Methods: Using network analysis, we examined the connections between corner stores (n = 24) in food deserts of Baltimore City (MD, USA) and their food/beverage suppliers (n = 42), to determine how different store and supplier characteristics correlated. Results: Food and beverage suppliers fell into two categories: Those providing primarily healthy foods/beverages (n = 15) in the healthy supplier network (HSN) and those providing primarily unhealthy food/beverages (n = 41) in the unhealthy supplier network (UHSN). Corner store connections to suppliers in the UHSN were nearly two times greater (t = 5.23, p < 0.001), and key suppliers in the UHSN core were more diverse, compared to the HSN. The UHSN was significantly more cohesive and densely connected, with corner stores sharing a greater number of the same unhealthy suppliers, compared to HSN, which was less cohesive and sparsely connected (t = 5.82; p < 0.001). Compared to African Americans, Asian and Hispanic corner storeowners had on average −1.53 (p < 0.001) fewer connections to suppliers in the HSN (p < 0.001). Conclusions: Our findings indicate clear differences between corner stores’ HSN and UHSN. Addressing ethnic/cultural differences of storeowners may also be important to consider.

Quantifying the Exposure to Antibiotic-Resistant Pathogens Among Patients Discharged From a Single Hospital Across All California Healthcare Facilities

OBJECTIVE

To assess the time-dependent exposure of California healthcare facilities to patients harboring methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), extended-spectrum β-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae, and Clostridium difficile infection (CDI) upon discharge from 1 hospital.

METHODS

Retrospective multiple-cohort study of adults discharged from 1 hospital in 2005-2009, counting hospitals, nursing homes, cities, and counties in which carriers were readmitted, and comparing the number and length of stay of readmissions and the number of distinct readmission facilities among carriers versus noncarriers.

RESULTS

We evaluated 45,772 inpatients including those with MRSA (N=1,198), VRE (N=547), ESBL (N=121), and CDI (N=300). Within 1 year of discharge, MRSA, VRE, and ESBL carriers exposed 137, 117, and 45 hospitals and 103, 83, and 37 nursing homes, generating 58,804, 33,486, and 15,508 total exposure-days, respectively. Within 90 days of discharge, CDI patients exposed 36 hospitals and 35 nursing homes, generating 7,318 total exposure-days. Compared with noncarriers, carriers had more readmissions to hospitals (MRSA:1.8 vs 0.9/patient; VRE: 2.6 vs 0.9; ESBL: 2.3 vs 0.9; CDI: 0.8 vs 0.4; all P<.001) and nursing homes (MRSA: 0.4 vs 0.1/patient; VRE: 0.7 vs 0.1; ESBL: 0.7 vs 0.1; CDI: 0.3 vs 0.1; all P<.001) and longer hospital readmissions (MRSA: 8.9 vs 7.3 days; VRE: 8.9 vs 7.4; ESBL: 9.6 vs 7.5; CDI: 12.3 vs 8.2; all P<.01).

CONCLUSIONS

Patients harboring antibiotic-resistant pathogens rapidly expose numerous facilities during readmissions; regional containment strategies are needed.

Effect of hospital referral networks on patient readmissions

Previous studies have shown that referral networks encompass important mechanisms of coordination and integration among hospitals, which enhance numerous organizational-level benefits, such as productivity, efficiency, and quality of care. The present study advances previous research by demonstrating how hospital referral networks influence patient readmissions. Data include 360,697 hospitalization events within a regional community of hospitals in the Italian National Health Service. Multilevel hierarchical regression analysis tests the impacts of referral networks' structural characteristics on patient hospital readmissions. The results demonstrate that organizational centrality in the overall referral network and ego-network density have opposing effects on the likelihood of readmission events within hospitals; greater centrality is negatively associated with readmissions, whereas greater ego-network density increases the likelihood of readmission events. Our findings support the (re)organization of healthcare systems and provide important indications for policymakers and practitioners.

Venue-based network analysis to inform HIV prevention efforts among young gay, bisexual, and other men who have sex with men

In the USA, human immunodeficiency virus (HIV) incidence rates continue to increase among young gay, bisexual, and other men have sexual intercourse with men. Young men who have sex with men (YMSM) indicate interest in HIV prevention programming that is implemented in the social venues that they frequent when they want to socialize with other men. We sought to understand YMSM venues as a networked space to provide insights into venue-based HIV prevention intervention delivery. The present study used survey data reported by 526 YMSM (ages 18-24) in 2005 to conduct a venue-based social network analysis. The latter sought to determine if the structure and composition of the networks in Los Angeles could be used to facilitate the delivery of HIV prevention messages to YMSM. Degree of person sharing between venues was used to demonstrate interconnectivity between venues classified as low risk (e.g., coffee shops) and high risk (e.g., bars and clubs) by a Community Advisory Board. Sixty-five percent of the 110 venues nominated were bars and clubs. Nearly all YMSM were connected by a single venue and over 87 % were connected by the six most central venues. A handful of highly connected low-risk venues was central to the venue network and connected to popular high-risk venues. Venue-based network analysis can inform tailored HIV prevention messaging for YMSM. Targeted delivery of prevention messaging at low-risk centralized venues may lead to widespread diffusion among venue-attending YMSM.

The spread and control of norovirus outbreaks among hospitals in a region: a simulation model

BACKGROUND

Because hospitals in a region are connected via patient sharing, a norovirus outbreak in one hospital may spread to others.

METHODS

We utilized our Regional Healthcare Ecosystem Analyst software to generate an agent-based model of all the acute care facilities in Orange County (OC), California and simulated various norovirus outbreaks in different locations, both with and without contact precautions.

RESULTS

At the lower end of norovirus reproductive rate (R0) estimates (1.64), an outbreak tended to remain confined to the originating hospital (≤6.1% probability of spread). However, at the higher end of R0 (3.74), an outbreak spread 4.1%-17.5% of the time to almost all other OC hospitals within 30 days, regardless of the originating hospital. Implementing contact precautions for all symptomatic cases reduced the probability of spread to other hospitals within 30 days and the total number of cases countywide, but not the number of other hospitals seeing norovirus cases.

CONCLUSIONS

A single norovirus outbreak can continue to percolate throughout a system of different hospitals for several months and appear as a series of unrelated outbreaks, highlighting the need for hospitals within a region to more aggressively and cooperatively track and control an initial outbreak.

Quality of care and interhospital collaboration: a study of patient transfers in Italy

OBJECTIVES

We examine the dynamics of patient-sharing relations within an Italian regional community of 35 hospitals serving approximately 1,300,000 people. We test whether interorganizational relations provide individual patients access to higher quality providers of care.

RESEARCH DESIGN AND METHODS

We reconstruct the complete temporal sequence of the 3461 consecutive interhospital patient-sharing events observed between each pair of hospitals in the community during 2005-2008. We distinguish between transfers occurring between and within different medical specialties. We estimate newly derived models for relational event sequences that allow us to control for the most common forms of network-like dependencies that are known to characterize collaborative relations between hospitals. We use 45-day risk-adjusted readmission rate as a proxy for hospital quality.

RESULTS

After controls (eg, geographical distance, size, and the existence of prior collaborative relations), we find that patients flow from less to more capable hospitals. We show that this result holds for patient being shared both between as well as within medical specialties. Nonetheless there are strong and persistent other organizational and relational effects driving transfers.

CONCLUSIONS

Decentralized patient-sharing decisions taken by the 35 hospitals give rise to a system of collaborative interorganizational arrangements that allow the patient to access hospitals delivering a higher quality of care. This result is relevant for health care policy because it suggests that collaborative relations between hospitals may produce desirable outcomes both for individual patients, and for regional health care systems.

Site of hospital readmission and mortality: a population-based retrospective cohort study

BACKGROUND

Unplanned hospital readmission is a complex process, particularly if the patient is readmitted to an acute care institution other than the original hospital. This study tested the hypothesis that readmission to an alternative hospital is associated with increased mortality compared with readmission to the original hospital.

METHODS

We performed a population-based retrospective cohort analysis set between 1995 and 2010 for all 21 acute care adult general hospitals in the Greater Toronto and Hamilton Area. Participants were consecutive adults (age ≥ 18 yr) readmitted through the emergency department within 30 days after hospital discharge. The primary outcome measure was all-cause mortality within 30 days after readmission.

RESULTS

Of the 198 149 patients included in the study, 38 134 (19.2%) died within 30 days after readmission. Patients readmitted to an alternative hospital were more likely than those readmitted to the original hospital to be older, reside in a chronic-care facility and arrive by ambulance. Alternative-hospital readmission was associated with a higher risk of death within 30 days (22.3% v. 18.6%, p < 0.001; odds ratio [OR] 1.26, 95% confidence interval [CI] 1.23-1.30). The increased risk was substantially less after adjustment for patient- and hospital-level covariables (adjusted OR 1.06, 95% CI 1.02-1.10). Unadjusted Kaplan-Meier survival curves separated early and the absolute difference in mortality continued throughout the entire 1-year follow-up period, but no difference between groups was observed based on adjusted survival analyses.

INTERPRETATION

Among patients readmitted within 30 days after discharge, readmission to an alternative hospital was associated with a higher risk of death than readmission to the original hospital. Whether this adverse prognosis reflects a true causal relation or residual confounding is unknown.

Dispersal of antibiotic-resistant high-risk clones by hospital networks: changing the patient direction can make all the difference

BACKGROUND

Patients who seek treatment in hospitals can introduce high-risk clones of hospital-acquired, antibiotic-resistant pathogens from previous admissions. In this manner, different healthcare institutions become linked epidemiologically. All links combined form the national patient referral network, through which high-risk clones can propagate.

AIM

To assess the influence of changes in referral patterns and network structure on the dispersal of these pathogens.

METHODS

Hospital admission data were mapped to reconstruct the English patient referral network, and 12 geographically distinct healthcare collectives were identified. The number of patients admitted and referred to hospitals outside their collective was measured. Simulation models were used to assess the influence of changing network structure on the spread of hospital-acquired pathogens.

FINDINGS

Simulation models showed that decreasing the number of between-collective referrals by redirecting, on average, just 1.5 patients/hospital/day had a strong effect on dispersal. By decreasing the number of between-collective referrals, the spread of high-risk clones through the network can be reduced by 36%. Conversely, by creating supra-regional specialist centres that provide specialist care at national level, the rate of dispersal can increase by 48%.

CONCLUSION

The structure of the patient referral network has a profound effect on the epidemic behaviour of high-risk clones. Any changes that affect the number of referrals between healthcare collectives, inevitably affect the national dispersal of these pathogens. These effects should be taken into account when creating national specialist centres, which may jeopardize control efforts.

Modeling the regional spread and control of vancomycin-resistant enterococci

BACKGROUND

Because patients can remain colonized with vancomycin-resistant enterococci (VRE) for long periods of time, VRE may spread from one health care facility to another.

METHODS

Using the Regional Healthcare Ecosystem Analyst, an agent-based model of patient flow among all Orange County, California, hospitals and communities, we quantified the degree and speed at which changes in VRE colonization prevalence in a hospital may affect prevalence in other Orange County hospitals.

RESULTS

A sustained 10% increase in VRE colonization prevalence in any 1 hospital caused a 2.8% (none to 62%) average relative increase in VRE prevalence in all other hospitals. Effects took from 1.5 to >10 years to fully manifest. Larger hospitals tended to have greater affect on other hospitals.

CONCLUSIONS

When monitoring and controlling VRE, decision makers may want to account for regional effects. Knowing a hospital's connections with other health care facilities via patient sharing can help determine which hospitals to include in a surveillance or control program.

The co-seasonality of pneumonia and influenza with Clostridium difficile infection in the United States, 1993-2008

Seasonal variations in the incidence of pneumonia and influenza are associated with nosocomial Clostridium difficile infection (CDI) incidence, but the reasons why remain unclear. Our objective was to consider the impact of pneumonia and influenza timing and severity on CDI incidence. We conducted a retrospective cohort study using the US National Hospital Discharge Survey sample. Hospitalized patients with a diagnosis of CDI or pneumonia and influenza between 1993 and 2008 were identified from the National Hospital Discharge Survey data set. Poisson regression models of monthly CDI incidence were used to measure 1) the time lag between the annual pneumonia and influenza prevalence peak and the annual CDI incidence peak and 2) the lagged effect of pneumonia and influenza prevalence on CDI incidence. CDI was identified in 18,465 discharges (8.52 per 1,000 discharges). Peak pneumonia prevalence preceded peak CDI incidence by 9.14 weeks (95% confidence interval: 4.61, 13.67). A 1% increase in pneumonia prevalence was associated with a cumulative effect of 11.3% over a 6-month lag period (relative risk = 1.113, 95% confidence interval: 1.073, 1.153). Future research could seek to understand which mediating pathways, including changes in broad-spectrum antibiotic prescribing and hospital crowding, are most responsible for the associated changes in incidence.

Predictors of hospitals with endemic community-associated methicillin-resistant Staphylococcus aureus

OBJECTIVE

We sought to identify hospital characteristics associated with community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) carriage among inpatients.

DESIGN

 Prospective cohort study.

SETTING

 Orange County, California.

PARTICIPANTS

 Thirty hospitals in a single county.

METHODS

 We collected clinical MRSA isolates from inpatients in 30 of 31 hospitals in Orange County, California, from October 2008 through April 2010. We characterized isolates by spa typing to identify CA-MRSA strains. Using California's mandatory hospitalization data set, we identified hospital-level predictors of CA-MRSA isolation.

RESULTS

 CA-MRSA strains represented 1,033 (46%) of 2,246 of MRSA isolates. By hospital, the median percentage of CA-MRSA isolates was 46% (range, 14%-81%). In multivariate models, CA-MRSA isolation was associated with smaller hospitals (odds ratio [OR], 0.97, or 3% decreased odds of CA-MRSA isolation per 1,000 annual admissions; P < .001, hospitals with more Medicaid-insured patients (OR, 1.2; P = .002), and hospitals with more patients with low comorbidity scores (OR, 1.3; P < .001). Results were similar when restricted to isolates from patients with hospital-onset infection.

CONCLUSIONS

 Among 30 hospitals, CA-MRSA comprised nearly half of MRSA isolates. There was substantial variability in CA-MRSA penetration across hospitals, with more CA-MRSA in smaller hospitals with healthier but socially disadvantaged patient populations. Additional research is needed to determine whether infection control strategies can be successful in targeting CA-MRSA influx.

The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system

OBJECTIVE

As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control.

MATERIALS AND METHODS

We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases.

RESULTS

To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity).

DISCUSSION

Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities.

CONCLUSIONS

A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.

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.

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.

Infection prevention in a connected world: the case for a regional approach

Results from microbiological and epidemiological investigations, as well as mathematical modelling, show that the transmission dynamics of nosocomial pathogens, especially of multiple antibiotic-resistant bacteria, is not exclusively amenable to single-hospital infection prevention measures. Crucially, their extent of spread depends on the structure of an underlying "healthcare network", as determined by inter-institutional referrals of patients. The current trend towards centralized healthcare systems favours the spread of hospital-associated pathogens, and must be addressed by coordinated regional or national approaches to infection prevention in order to maintain patient safety. Here we review recent advances that support this hypothesis, and propose a "next-generation" network-approach to hospital infection prevention and control.

Patient sharing and population genetic structure of methicillin-resistant Staphylococcus aureus

Rates of hospital-acquired infections, specifically methicillin-resistant Staphylococcus aureus (MRSA), are increasingly being used as indicators for quality of hospital hygiene. There has been much effort on understanding the transmission process at the hospital level; however, interhospital population-based transmission remains poorly defined. We evaluated whether the proportion of shared patients between hospitals was correlated with genetic similarity of MRSA strains from those hospitals. Using data collected from 30 of 32 hospitals in Orange County, California, multivariate linear regression showed that for each twofold increase in the proportion of patients shared between 2 hospitals, there was a 7.7% reduction in genetic heterogeneity between the hospitals' MRSA populations (permutation P value = 0.0356). Pairs of hospitals that both served adults had more similar MRSA populations than pairs including a pediatric hospital. These findings suggest that concerted efforts among hospitals that share large numbers of patients may be synergistic to prevent MRSA transmission.

Dynamic analysis of interhospital collaboration and competition: empirical evidence from an Italian regional health system

BACKGROUND

Policymakers stimulate competition in universalistic health-care systems while encouraging the formation of service provision networks among hospital organizations. This article addresses a gap in the extant literature by empirically analyzing simultaneous collaboration and competition between hospitals within the Italian National Health Service, where important procompetition reforms have been implemented.

PURPOSE

To explore how rising competition between hospitals relates to their propensity to collaborate with other local providers.

METHODS

Longitudinal data on interhospital collaboration and competition collected in an Italian region from 2003 to 2007 are analyzed. Social network analysis techniques are applied to study the structure and dynamics of interhospital collaboration. Negative binomial regressions are employed to explore how interhospital competition relates to the collaborative network over time.

RESULTS

Competition among providers does not hinder interhospital collaboration. Collaboration is primarily local, with resource complementarity and differentials in the volume of activity and hospital performance explaining the propensity to collaborate.

CONCLUSIONS

Formation of collaborative networks among hospitals is not hampered by reforms aimed at fostering market forces. Because procompetition reforms elicit peculiar forms of managed competition in universalistic health systems, studies are needed to clarify whether the positive association between interhospital competition and collaboration can be generalized to other health-care settings.

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.

Modeling the spread of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks throughout the hospitals in Orange County, California

BACKGROUND

Since hospitals in a region often share patients, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in one hospital could affect other hospitals.

METHODS

Using extensive data collected from Orange County (OC), California, we developed a detailed agent-based model to represent patient movement among all OC hospitals. Experiments simulated MRSA outbreaks in various wards, institutions, and regions. Sensitivity analysis varied lengths of stay, intraward transmission coefficients (β), MRSA loss rate, probability of patient transfer or readmission, and time to readmission.

RESULTS

Each simulated outbreak eventually affected all of the hospitals in the network, with effects depending on the outbreak size and location. Increasing MRSA prevalence at a single hospital (from 5% to 15%) resulted in a 2.9% average increase in relative prevalence at all other hospitals (ranging from no effect to 46.4%). Single-hospital intensive care unit outbreaks (modeled increase from 5% to 15%) caused a 1.4% average relative increase in all other OC hospitals (ranging from no effect to 12.7%).

CONCLUSION

MRSA outbreaks may rarely be confined to a single hospital but instead may affect all of the hospitals in a region. This suggests that prevention and control strategies and policies should account for the interconnectedness of health care facilities.