Nursing home residents may be particularly vulnerable to coronavirus disease 2019 (COVID-19). Therefore, a question is when and how often nursing homes should test staff for COVID-19 and how this may change as severe acute respiratory coronavirus virus 2 (SARS-CoV-2) evolves.

We developed an agent-based model representing a typical nursing home, COVID-19 spread, and its health and economic outcomes to determine the clinical and economic value of various screening and isolation strategies and how it may change under various circumstances.

Under winter 2023–2024 SARS-CoV-2 omicron variant conditions, symptom-based antigen testing averted 4.5 COVID-19 cases compared to no testing, saving $191 in direct medical costs. Testing implementation costs far outweighed these savings, resulting in net costs of $990 from the Centers for Medicare & Medicaid Services perspective, $1,545 from the third-party payer perspective, and $57,155 from the societal perspective. Testing did not return sufficient positive health effects to make it cost-effective [$50,000 per quality-adjusted life-year (QALY) threshold], but it exceeded this threshold in ≥59% of simulation trials. Testing remained cost-ineffective when routinely testing staff and varying face mask compliance, vaccine efficacy, and booster coverage. However, all antigen testing strategies became cost-effective (≤$31,906 per QALY) or cost saving (saving ≤$18,372) when the severe outcome risk was ≥3 times higher than that of current omicron variants.

SARS-CoV-2 testing costs outweighed benefits under winter 2023–2024 conditions; however, testing became cost-effective with increasingly severe clinical outcomes. Cost-effectiveness can change as the epidemic evolves because it depends on clinical severity and other intervention use. Thus, nursing home administrators and policy makers should monitor and evaluate viral virulence and other interventions over time.

Due to shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCWs) to inform manufacturing targets and resource allocation.

We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute-care hospital and the United States.

For an acute-care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% interpercentile range [IPR], 50–229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR, 5,904–25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases to a range of 22 (95% IPR, 10–43) to 4,445 (95% IPR, 1,975–8,684) if each N95 is used for 5 patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645–13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW–patient encounters, and reusing N95s 5–10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR, 37.1–200.6 million) to 1.6 billion (95% IPR, 0.7–3.6 billion) as 5%–90% of the population is exposed (single-use). This number ranges from 17.4 million (95% IPR, 7.3–41 million) to 312.3 million (95% IPR, 131.5–737.3 million) using each respirator for 5 encounters.

We quantified the number of N95 respirators needed for a given acute-care hospital and nationally during the COVID-19 pandemic under varying conditions.

Previous research has suggested an association between depression and subsequent acute stroke incidence, but few studies have examined any effect modification by sociodemographic factors. In addition, no studies have investigated this association among primary care recipients with hypertension.

We examined the anonymized records of all public general outpatient visits by patients aged 45+ during January 2007–December 2010 in Hong Kong to extract primary care patients with hypertension for analysis. We took the last consultation date as the baseline and followed them up for 4 years (until 2011–2014) to observe any subsequent acute hospitalization due to stroke. Mixed-effects Cox models (random intercept across 74 included clinics) were implemented to examine the association between depression (ICPC diagnosis or anti-depressant prescription) at baseline and the hazard of acute stroke (ICD-9: 430–437.9). Effect modification by age, sex, and recipient status of social security assistance was examined in extended models with respective interaction terms specified.

In total, 396 858 eligible patients were included, with 9099 (2.3%) having depression, and 10 851 (2.7%) eventually hospitalized for stroke. From the adjusted analysis, baseline depression was associated with a 17% increased hazard of acute stroke hospitalization [95% confidence interval (CI) 1.03–1.32]. This association was suggested to be even stronger among men than among women (hazard ratio = 1.29, 95% CI 1.00–1.67).

Depression is more strongly associated with acute stroke incidence among male than female primary care patients with hypertension. More integrated services are warranted to address their needs.

While previous work showed that the Centers for Disease Control and Prevention toolkit for carbapenem-resistant Enterobacteriaceae (CRE) can reduce spread regionally, these interventions are costly, and decisions makers want to know whether and when economic benefits occur.

Economic analysis

Orange County, California

Using our Regional Healthcare Ecosystem Analyst (RHEA)-generated agent-based model of all inpatient healthcare facilities, we simulated the implementation of the CRE toolkit (active screening of interfacility transfers) in different ways and estimated their economic impacts under various circumstances.

Compared to routine control measures, screening generated cost savings by year 1 when hospitals implemented screening after identifying ≤20 CRE cases (saving $2,000–$9,000) and by year 7 if all hospitals implemented in a regional coordinated manner after 1 hospital identified a CRE case (hospital perspective). Cost savings was achieved only if hospitals independently screened after identifying 10 cases (year 1, third-party payer perspective). Cost savings was achieved by year 1 if hospitals independently screened after identifying 1 CRE case and by year 3 if all hospitals coordinated and screened after 1 hospital identified 1 case (societal perspective). After a few years, all strategies cost less and have positive health effects compared to routine control measures; most strategies generate a positive cost-benefit each year.

Active screening of interfacility transfers garnered cost savings in year 1 of implementation when hospitals acted independently and by year 3 if all hospitals collectively implemented the toolkit in a coordinated manner. Despite taking longer to manifest, coordinated regional control resulted in greater savings over time.

Infect Control Hosp Epidemiol 2018;39:516–524

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.

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.

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).

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

Infect. Control Hosp. Epidemiol. 2015;36(11):1275–1282

To explore the economic impact to a hospital of universal methicillin-resistant Staphylococcus aureus (MRSA) screening.

We used a decision tree model to estimate the direct economic impact to an individual hospital of starting universal MRSA screening and contact precautions. Projected costs and benefits were based on literature-derived data. Our model examined outcomes of several strategies including non-nares MRSA screening and comparison of culture versus polymerase chain reaction–based screening.

Under baseline conditions, the costs of universal MRSA screening and contact precautions outweighed the projected benefits generated by preventing MRSA-related infections, resulting in economic costs of $104,000 per 10,000 admissions (95% CI, $83,000–$126,000). Cost-savings occurred only when the model used estimates at the extremes of our key parameters. Non-nares screening and polymerase chain reaction–based testing, both of which identified more MRSA-colonized persons, resulted in more MRSA infections averted but increased economic costs of the screening program.

We found that universal MRSA screening, although providing potential benefit in preventing MRSA infection, is relatively costly and may be economically burdensome for a hospital. Policy makers should consider the economic burden of MRSA screening and contact precautions in relation to other interventions when choosing programs to improve patient safety and outcomes.

Infect Control Hosp Epidemiol 2015;36(1): 2–13

While the persistence of high surgical site infection (SSI) rates has prompted the advent of more expensive sutures that are coated with antimicrobial agents to prevent SSIs, the economic value of such sutures has yet to be determined.

Using TreeAge Pro, we developed a decision analytic model to determine the cost-effectiveness of using antimicrobial sutures in abdominal incisions from the hospital, third-party payer, and societal perspectives. Sensitivity analyses systematically varied the risk of developing an SSI (range, 5%–20%), the cost of triclosan-coated sutures (range, $5–$25/inch), and triclosan-coated suture efficacy in preventing infection (range, 5%–50%) to highlight the range of costs associated with using such sutures.

Triclosan-coated sutures saved $4,109–$13,975 (hospital perspective), $4,133–$14,297 (third-party payer perspective), and $40,127–$53,244 (societal perspective) per SSI prevented, when a surgery had a 15% SSI risk, depending on their efficacy. If the SSI risk was no more than 5% and the efficacy in preventing SSIs was no more than 10%, triclosan-coated sutures resulted in extra expenditure for hospitals and third-party payers (resulting in extra costs of $1,626 and $1,071 per SSI prevented for hospitals and third-party payers, respectively; SSI risk, 5%; efficacy, 10%).

Our results suggest that switching to triclosan-coated sutures from the uncoated sutures can both prevent SSIs and save substantial costs for hospitals, third-party payers, and society, as long as efficacy in preventing SSIs is at least 10% and SSI risk is at least 10%.

Implementation of contact precautions in nursing homes to prevent methicillm-resistant Staphylococcus aureus (MRSA) transmission could cost time and effort and may have wide-ranging effects throughout multiple health facilities. Computational modeling could forecast the potential effects and guide policy making.

Our multihospital computational agent-based model, Regional Healthcare Ecosystem Analyst (RHEA).

All hospitals and nursing homes in Orange County, California.

Our simulation model compared the following 3 contact precaution strategies: (1) no contact precautions applied to any nursing home residents, (2) contact precautions applied to those with clinically apparent MRSA infections, and (3) contact precautions applied to all known MRSA carriers as determined by MRSA screening performed by hospitals.

Our model demonstrated that contact precautions for patients with clinically apparent MRSA infections in nursing homes resulted in a median 0.4% (range, 0%–1.6%) relative decrease in MRSA prevalence in nursing homes (with 50% adherence) but had no effect on hospital MRSA prevalence, even 5 years after initiation. Implementation of contact precautions (with 50% adherence) in nursing homes for all known MRSA carriers was associated with a median 14.2% (range, 2.1%–21.8%) relative decrease in MRSA prevalence in nursing homes and a 2.3% decrease (range, 0%–7.1%) in hospitals 1 year after implementation. Benefits accrued over time and increased with increasing compliance.

Our modeling study demonstrated the substantial benefits of extending contact precautions in nursing homes from just those residents with clinically apparent infection to all MRSA carriers, which suggests the benefits of hospitals and nursing homes sharing and coordinating information on MRSA surveillance and carriage status.

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

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.

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%).

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.

To estimate the economic value of dispensing preoperative home-based Chlorhexidine bathing cloth kits to orthopedic patients to prevent surgical site infection (SSI).

A stochastic decision-analytic computer simulation model was developed from the hospital’s perspective depicting the decision of whether to dispense the kits preoperatively to orthopedic patients. We varied patient age, cloth cost, SSI-attributable excess length of stay, cost per bed-day, patient compliance with the regimen, and cloth antimicrobial efficacy to determine which variables were the most significant drivers of the model’s outcomes.

When all other variables remained at baseline and cloth efficacy was at least 50%, patient compliance only had to be half of baseline (baseline mean, 15.3%; range, 8.23%–20.0%) for Chlorhexidine cloths to remain the dominant strategy (ie, less costly and providing better health outcomes). When cloth efficacy fell to 10%, 1.5 times the baseline bathing compliance also afforded dominance of the preoperative bath.

The results of our study favor the routine distribution of bathing kits. Even with low patient compliance and cloth efficacy values, distribution of bathing kits is an economically beneficial strategy for the prevention of SSI.

To compare use of chlorhexidine with use of iodine for preoperative skin antisepsis with respect to effectiveness in preventing surgical site infections (SSIs) and cost.

We searched the Agency for Healthcare Research and Quality website, the Cochrane Library, Medline, and EMBASE up to January 2010 for eligible studies. Included studies were systematic reviews, meta-analyses, or randomized controlled trials (RCTs) comparing preoperative skin antisepsis with chlorhexidine and with iodine and assessing for the outcomes of SSI or positive skin culture result after application. One reviewer extracted data and assessed individual study quality, quality of evidence for each outcome, and publication bias. Meta-analyses were performed using a fixed-effects model. Using results from the meta-analysis and cost data from the Hospital of the University of Pennsylvania, we developed a decision analytic cost-benefit model to compare the economic value, from the hospital perspective, of antisepsis with iodine versus antisepsis with 2 preparations of chlorhexidine (ie, 4% chlorhexidine bottle and single-use applicators of a 2% chlorhexidine gluconate [CHG] and 70% isopropyl alcohol [IPA] solution), and also performed sensitivity analyses.

Nine RCTs with a total of 3,614 patients were included in the meta-analysis. Meta-analysis revealed that chlorhexidine antisepsis was associated with significantly fewer SSIs (adjusted risk ratio, 0.64 [95% confidence interval, [0.51–0.80]) and positive skin culture results (adjusted risk ratio, 0.44 [95% confidence interval, 0.35–0.56]) than was iodine antisepsis. In the cost-benefit model baseline scenario, switching from iodine to chlorhexidine resulted in a net cost savings of $16-$26 per surgical case and $349,904–$568,594 per year for the Hospital of the University of Pennsylvania. Sensitivity analyses showed that net cost savings persisted under most circumstances.

Preoperative skin antisepsis with chlorhexidine is more effective than preoperative skin antisepsis with iodine for preventing SSI and results in cost savings.

Assessments of infectious disease spread in hospitals seldom account for interfacility patient sharing. This is particularly important for pathogens with prolonged incubation periods or carrier states.

We quantified patient sharing among all 32 hospitals in Orange County (OC), California, using hospital discharge data. Same-day transfers between hospitals were considered “direct” transfers, and events in which patients were shared between hospitals after an intervening stay at home or elsewhere were considered “indirect” patient-sharing events. We assessed the frequency of readmissions to another OC hospital within various time points from discharge and examined interhospital sharing of patients with Clostridium difficile infection.

In 2005, OC hospitals had 319,918 admissions. Twenty-nine percent of patients were admitted at least twice, with a median interval between discharge and readmission of 53 days. Of the patients with 2 or more admissions, 75% were admitted to more than 1 hospital. Ninety-four percent of interhospital patient sharing occurred indirectly. When we used 10 shared patients as a measure of potential interhospital exposure, 6 (19%) of 32 hospitals “exposed” more than 50% of all OC hospitals within 6 months, and 17 (53%) exposed more than 50% within 12 months. Hospitals shared 1 or more patient with a median of 28 other hospitals. When we evaluated patients with C. difficile infection, 25% were readmitted within 12 weeks; 41% were readmitted to different hospitals, and less than 30% of these readmissions were direct transfers.

In a large metropolitan county, interhospital patient sharing was a potential avenue for transmission of infectious agents. Indirect sharing with an intervening stay at home or elsewhere composed the bulk of potential exposures and occurred unbeknownst to hospitals.