Demographic factors influencing nonurgent emergency department utilization among a Medicaid population.

To use administrative medical encounter data to examine nonurgent emergency department (ED) utilization as it relates to member characteristics (i.e., age, gender, race/ethnicity, urbanicity and federal poverty level (FPL)). This 1 year cross-sectional study used medical claims from a managed care organization for Medicaid members enrolled from October 1, 2010 - September 30, 2011. ED encounters occurring during the study period were classified as either urgent or nonurgent using ICD-9 diagnosis codes obtained from medical claims. Examples of urgent diagnoses include head traumas, burns, allergic reactions, poisonings, preterm labor or maternal/fetal distress. A total of 187,263 members aged 2 to 65 years were retained for study. A zero-inflated Poisson regression model examined the influence of member-level characteristics on nonurgent ED utilization, while simultaneously adjusting for all factors. Females were 41 % more likely to have a nonurgent ED visit (p ≤ 0.0001). Members ages 50-65 were least likely to have a nonurgent ED visit (p ≤ 0.0001). White members had higher odds of having at least one nonurgent ED visit (p ≤ 0.0002). Rural members were 7.7 % less likely to have a nonurgent ED visit. Members in the 400 % + FPL category were less likely to seek nonurgent care from an ED (p ≤ 0.0001). A nonurgent ED visit occurs when care is sought at an ED that could have been handled in a primary care setting. Approximately 30-50 % of all ED visits in the United States are considered nonurgent. This study supports the need to determine factors associated with misuse of ED services for nonurgent care. Demographic factors significantly impacting nonurgent ED utilization include gender, age, race/ethnicity, urbanicity and percent of the FPL. Results may be useful in ED utilization management efforts.

Short Report. Audit of Conscious Sedation Provision in a Salaried Dental Service.

Clinical audit is a tool that may be used to improve the quality of care and outcomes for patients in a health care setting as well as a mechanism for clinicians to reflect on their performance. The audit described in this short report involved the collection and analysis of data related to the administration of 1,756 conscious sedations, categorised as standard techniques, by clinicians employed by an NHS Trust-based dental service during the year 2014. Data collected included gender, age and medical status of subject, the type of care delivered, the dose of drug administered and the quality of the achieved sedation and any sedation-related complications. This was the first time that a service-wide clinical audit had been undertaken with the objective of determining the safety and effectiveness of this aspect of care provision. Evaluation of the analysed data supported the perceived view that such care was being delivered satisfactorily. This on-going audit will collect data during year 2016 on the abandonment of clinical sessions, in which successful sedation had been achieved, due to the failure to obtain adequate local anaesthesia.

Enhancing Lyme Disease Surveillance by Using Administrative Claims Data, Tennessee, USA.

Lyme disease is underreported in the United States. We used insurance administrative claims data to determine the value of such data in enhancing case ascertainment in Tennessee during January 2011-June 2013. Although we identified ≈20% more cases of Lyme disease (5/year), the method was resource intensive and not sustainable in this low-incidence state.

Using administrative medical claims data to supplement state disease registry systems for reporting zoonotic infections.

OBJECTIVE: To determine what, if any, opportunity exists in using administrative medical claims data for supplemental reporting to the state infectious disease registry system. MATERIALS AND METHODS: Cases of five tick-borne (Lyme disease (LD), babesiosis, ehrlichiosis, Rocky Mountain spotted fever (RMSF), tularemia) and two mosquito-borne diseases (West Nile virus, La Crosse viral encephalitis) reported to the Tennessee Department of Health during 2000-2009 were selected for study. Similarly, medically diagnosed cases from a Tennessee-based managed care organization (MCO) claims data warehouse were extracted for the same time period. MCO and Tennessee Department of Health incidence rates were compared using a complete randomized block design within a general linear mixed model to measure potential supplemental reporting opportunity. RESULTS: MCO LD incidence was 7.7 times higher (p<0.001) than that reported to the state, possibly indicating significant under-reporting (∼196 unreported cases per year). MCO data also suggest about 33 cases of RMSF go unreported each year in Tennessee (p<0.001). Three cases of babesiosis were discovered using claims data, a significant finding as this disease was only recently confirmed in Tennessee. DISCUSSION: Data sharing between MCOs and health departments for vaccine information already exists (eg, the Vaccine Safety Datalink Rapid Cycle Analysis project). There may be a significant opportunity in Tennessee to supplement the current passive infectious disease reporting system with administrative claims data, particularly for LD and RMSF. CONCLUSIONS: There are limitations with administrative claims data, but health plans may help bridge data gaps and support the federal administration's vision of combining public and private data into one source.

Influence of spatial resolution on space-time disease cluster detection.

BACKGROUND: Utilizing highly precise spatial resolutions within disease outbreak detection, such as the patients' address, is most desirable as this provides the actual residential location of the infected individual(s). However, this level of precision is not always readily available or only available for purchase, and when utilized, increases the risk of exposing protected health information. Aggregating data to less precise scales (e.g., ZIP code or county centroids) may mitigate this risk but at the expense of potentially masking smaller isolated high risk areas. METHODS: To experimentally examine the effect of spatial data resolution on space-time cluster detection, we extracted administrative medical claims data for 122500 viral lung episodes occurring during 2007-2010 in Tennessee. We generated 10000 spatial datasets with varying cluster location, size and intensity at the address-level. To represent spatial data aggregation (i.e., reduced resolution), we then created 10000 corresponding datasets both at the ZIP code and county level for a total of 30000 datasets. Using the space-time permutation scan statistic and the SaTScan™ cluster software, we evaluated statistical power, sensitivity and positive predictive values of outbreak detection when using exact address locations compared to ZIP code and county level aggregations. RESULTS: The power to detect disease outbreaks did not largely diminish when using spatially aggregated data compared to more precise address information. However, aggregations negatively impacted the ability to more accurately determine the exact spatial location of the outbreak, particularly in smaller clusters (<800 km²). CONCLUSIONS: Spatial aggregations do not necessitate a loss of power or sensitivity; rather, the relationship is more complex and involves simultaneously considering relative risk within the cluster and cluster size. The likelihood of spatially over-estimating outbreaks by including geographical areas outside the actual disease cluster increases with aggregated data.

Comparing spatio-temporal clusters of arthropod-borne infections using administrative medical claims and state reported surveillance data.

Considered separately, notifiable disease registries and medical claims data have certain advantages (e.g., consistent case definitions and electronic records, respectively) and limitations (e.g., incomplete reporting and coding errors, respectively) within disease outbreak research. Combined however, these data could provide a more complete source of information. Using a retrospective space-time permutation scan statistic, zoonotic case information from a state registry system (TDH) was compared with administrative medical claims information from a managed care organization (MCO) to examine how data sources differ. Study observations included case information for four tick-borne (Lyme disease, ehrlichiosis, Rocky Mountain spotted fever, tularemia) and two mosquito-borne diseases (West Nile virus, La Crosse viral encephalitis) occurring in Tennessee. One hundred and three clusters were detected, of which nine were significant (P<0.05). Considering only significant clusters, no spatial or temporal overlapping between data sources occurred. In conclusion, data integration efforts and data limitations should be considered to provide more comprehensive case information.

Ear microbiology reports: a need for better communication with the microbiologists.

Most ENT surgeons treat discharging ears with topical antibiotics but many may not routinely utilise ear microbiology specimens. One reason could be that ear microbiology reports may not reflect their usual therapeutic options. This paper explores how microbiology departments in England process ear swabs. We carried out a telephone questionnaire of 104 microbiology departments in England. Results were obtained from 95 hospitals. Various culture methods are used, with sensitivity testing for up to 51 different antibiotics. Only five are licensed for topical use. Systemic antibiotics seemed to be preferentially tested for over topical antibiotics. Anaerobes and fungus are routinely tested. Many microbiology departments do not routinely report on all sensitivities tested. Antibiotic sensitivity testing for various micro-organisms cultured from ear swabs seemed to be guided by protocols for systemic infections. Microbiologists may not fully appreciate ENT surgeons' preferential usage of topical antibiotics in treating discharging ears, albeit there are other factors in their consideration for antibiotics to test. To gain better guidance from swab results, and to reduce needless lab costs, discussion with the microbiologists may be of benefit.

Spatial implications associated with using Euclidean distance measurements and geographic centroid imputation in health care research.

OBJECTIVE: To determine the effect of using Euclidean measurements and zip-code centroid geo-imputation versus more precise spatial analytical techniques in health care research. DATA SOURCES: Commercially insured members from a southeastern managed care organization. STUDY DESIGN: Distance from admitting inpatient facility to member's home and zip-code centroid (geographic placement) was compared using Euclidean straight-line and shortest-path drive distances (measurement technique). DATA COLLECTION: Administrative claims from October 2005 to September 2006. PRINCIPAL FINDINGS: Measurement technique had a greater impact on distance values compared with geographic placement. Drive distance from the geocoded address was highly correlated (r=0.99) with the Euclidean distance from the zip-code centroid. CONCLUSIONS: Actual differences were relatively small. Researchers without capabilities to produce drive distance measurements and/or address geocoding techniques could rely on simple linear regressions to estimate correction factors with a high degree of confidence.

Distal upper and lower limb fractures associated with thiazolidinedione use.

OBJECTIVE: To determine if patients with diabetes mellitus taking a thiazolidinedione experienced higher proportions of distal upper and lower limb fractures compared with those not taking a thiazolidinedione, as recent US Food and Drug Administration safety alerts suggested. STUDY DESIGN: This 3-year cross-sectional study used medical and pharmacy claims from a large southeastern managed care organization for continuously enrolled members from January 1, 2004, through December 31, 2006. METHODS: A total of 29,284 patients with type 2 diabetes mellitus aged 18 to 64 years were allocated to mutually exclusive study groups of thiazolidinedione users versus thiazolidinedione nonusers and thiazolidinedione type (pioglitazone hydrochloride, rosiglitazone maleate, or a combination). chi(2) Tests were used to determine if fracture proportions for thiazolidinedione users differed from those of thiazolidinedione nonusers and if thiazolidinedione type was significant. Multivariate logistic regression models and backward stepwise elimination algorithms were constructed to evaluate associations of fracture proportions with age, sex, and chronicity of drug use for 7462 members using a thiazolidinedione. RESULTS: The mean (SE) fracture proportions were significantly higher for thiazolidinedione users (5.1% [0.5%]) versus nonusers (4.5% [0.3%]) (P = .03). Fracture proportions did not differ by thiazolidinedione type (P = .86). Overall, women experienced a higher mean (SE) proportion of fractures compared with men (6.0% [0.4%] vs 3.5% [0.3%]) (P <.001), regardless of thiazolidinedione use. On average, the odds of experiencing a fracture for women using a thiazolidinedione increased 2% for every year increase in age. CONCLUSIONS: Patients with diabetes using thiazolidinediones, regardless of type, had higher proportions of distal upper and lower limb fractures compared with those not using thiazolidinediones. Fracture proportions were higher among women and increased with age.