Implementing data-to-care initiatives for HIV in New York state: assessing the value of community health centers identifying persons out of care for health department follow-up.

To end the HIV/AIDS epidemic, innovative strategies are needed to improve outcomes along the HIV care continuum. Data-to-Care is a public health strategy whereby HIV surveillance data are used to identify people living with HIV/AIDS for linkage to, or re-engagement in HIV medical care. Three main approaches to Data-to-Care are defined by where persons out of care are identified and where outreach activities are initiated: the Health Department level, the Healthcare Provider level, or a combination of the two (Combination Model). The purpose of this evaluation was to compare successes and challenges for two Data-to-Care models implemented in New York State between 1 January 2015 and 1 September 2016: a Health Department Model, and a Combination Model. The Health Department Model identifies persons presumed to be out of care based on an absence of HIV laboratory tests within the states surveillance system alone, and the Combination Model identifies individuals based on both an absence of a medical provider visit at a partnering health center, and an absence of HIV laboratory tests in the surveillance system. Only counties served by partnering health centers were included in this evaluation. In the Health Department Model, 348 out of 1352 (26%) surveillance identified individuals were truly out of care; of those, re-linkage success was 78%. In the Combination Model, 19 out of 51 (37%) individuals were truly out of care; of those, re-linkage success was 63%. The proportion of cases truly out of care was significantly higher for the Combination Model than the Health Department Model (p-value: 0.08). Both models were successful in re-linking a high proportion of individuals back to care, though the efficiency of identifying individuals who are truly out of care remains an area in need of further refinement for both models.

Evacuation During Hurricane Sandy: Data from a Rapid Community Assessment.

INTRODUCTION: In anticipation of Hurricane Sandy in 2012 New York City officials issued mandatory evacuation orders for evacuation Zone A. However, only a small proportion of residents complied. Failure to comply with evacuation warnings can result in severe consequences including injury and death. To better ascertain why individuals failed to heed pre--emptive evacuation warnings for Hurricane Sandy we assessed factors that may have affected evacuation among residents in neighborhoods severely affected by the storm. METHODS: Data from a mental health needs assessment survey conducted among adult residents in South Brooklyn, the Rockaways, and Staten Island from December 13--18, 2012 was assessed. Several disasters related questions were evaluated, and prevalence estimates of evacuation and evacuation timing by potential factors that may influence evacuation were estimated. Measures of association were assessed using chi--square and t--test. RESULTS: Our sample consisted of 420 residents of which, only 49% evacuated at any time for Sandy. Evacuation was higher among those who witnessed trauma to others related to the World Trade Center attacks (66% vs. 40%, p=0.024). Those who reported extensive household damage after Sandy, had a higher rate of evacuation than those with minimal damage (83% vs. 30%, p<0.001). Among those who evacuated, evacuation before the storm was lower among residents living on higher floors (56% vs. 22%, p=0.022). DISCUSSION: Given that warnings to evacuate were issued before Sandy made landfall, evacuation among residents in South Brooklyn, the Rockaways and Staten Island, while higher than the overall Zone A evacuation rate, was less than optimal. Continued research on evacuation behaviors is needed, particularly on how timing affects evacuation. A better understanding may help to reduce barriers, and improve evacuation compliance.

Hurricane Sandy Evacuation Among World Trade Center Health Registry Enrollees in New York City.

OBJECTIVE: Timely evacuation is vital for reducing adverse outcomes during disasters. This study examined factors associated with evacuation and evacuation timing during Hurricane Sandy among World Trade Center Health Registry (Registry) enrollees. METHODS: The study sample included 1162 adults who resided in New York City's evacuation zone A during Hurricane Sandy who completed the Registry's Hurricane Sandy substudy in 2013. Factors assessed included zone awareness, prior evacuation experience, community cohesion, emergency preparedness, and poor physical health. Prevalence estimates and multiple logistic regression models of evacuation at any time and evacuation before Hurricane Sandy were created. RESULTS: Among respondents who evacuated for Hurricane Sandy (51%), 24% had evacuated before the storm. In adjusted analyses, those more likely to evacuate knew they resided in an evacuation zone, had evacuated during Hurricane Irene, or reported pre-Sandy community cohesion. Evacuation was less likely among those who reported being prepared for an emergency. For evacuation timing, evacuation before Hurricane Sandy was less likely among those with pets and those who reported 14 or more poor physical health days. CONCLUSIONS: Higher evacuation rates were observed for respondents seemingly more informed and who lived in neighborhoods with greater social capital. Improved disaster messaging that amplifies these factors may increase adherence with evacuation warnings. (Disaster Med Public Health Preparedness. 2016;10:411-419).

Investigation to identify a resource-efficient case-control methodology for determining antibiotics associated with Clostridium difficile infection.

BACKGROUND: Antimicrobial exposure remains an important risk factor for developing Clostridium difficile infection (CDI). Efficient method to identify antibiotics associated with CDI is important for formulating strategies to curtail their use. As a prelude to a more extensive Agency for Healthcare Research and Quality-funded project (Evaluation & Research on Antimicrobial Stewardship's Effect on Clostridium difficile), we undertook an exploratory evaluation to determine a resource-efficient method for identifying antibiotic targets for antimicrobial stewardship interventions. METHODS: The study compared a series of 6 focused case-control studies. Cases consisted of patients with laboratory-confirmed CDI admitted from July-October 2009. Controls were selected from patients without CDI hospitalized during the same period. Five groups of controls were matched to cases (2:1 ratio) using group-specific matching criteria, including admission date, age, type of admission, length of stay (LOS) to discharge, and/or LOS to CDI diagnosis. The final control group was selected from patients who received antibiotics during hospitalization. Data, including demographics and antibiotic usage, were compared between case and control groups. RESULTS: A total of 126 cases were matched to 6 groups of 252 controls. For control groups 1-5, the use of piperacillin and tazobactam, ceftriaxone or cefepime, ciprofloxacin or moxifloxacin, intravenous vancomycin, azithromycin, and antibiotics of last resort were significantly more frequent in case than control patients. For the final control group, the associations between ceftriaxone or cefepime, and ciprofloxacin or moxifloxacin use and CDI no longer persisted. This could in part be explained by differences in comorbidities between case and control patients even with stringent matching criteria. CONCLUSION: Use of a simple matching strategy to conduct case-control studies is an efficient and feasible compromise strategy, especially in resource-limited settings, to identify high-risk antibiotics associated with CDI.

Antimicrobial stewardship and automated pharmacy technology improve antibiotic appropriateness for community-acquired pneumonia.

BACKGROUND: The Centers for Medicare and Medicaid Services' (CMS's) Hospital Inpatient Quality Reporting program includes the initial selection of antibiotics for adult community-acquired pneumonia (CAP) patients as a performance measure. A multidisciplinary team defined opportunities for improving performance in appropriate antibiotic use among CAP patients. The team consisted of personnel from the emergency department (ED), the antimicrobial stewardship program (infectious disease, pharmacy), and performance improvement. DESIGN: Quasi-experimental before-after study. SETTING: A large, urban, multicampus academic medical center. Interventions. Interventions included an algorithm for ED providers identifying appropriate antibiotic selections, development of a CAP kit consisting of appropriate antibiotics and dosing regimens bundled with the treatment algorithm, and preloading an automated ED medication dispensing and management system. A quality improvement methodology ("plan, do, check, act") was used to pilot stewardship interventions at one ED campus and later at a second ED campus. RESULTS: In the pilot ED, appropriate antibiotic selection for CAP improved from 54.9% before the intervention in 2008 to 93.4% after the intervention in 2011 (P = .001). Subsequently, in the second ED appropriate antibiotic regimens for CAP improved from 64.6% before the intervention in 2008 to 91.3% after the intervention in 2011 (P = .004)). The rates of another CMS measure, antibiotic administration within 6 hours, were not statistically different before and after the interventions. In an interrupted time series logistic regression analysis, the intervention was found to be significantly associated with the improved prescribing ([Formula: see text]). DISCUSSION: The combination of interdisciplinary teamwork, antibiotic stewardship, education, and information technology is associated with replicable and sustained prescribing improvements.