Chronic Disease or Injury

As a Centers for Disease Control and Prevention Enhanced State Opioid Overdose Surveillance (ESOOS) funded state, Kentucky started utilizing Emergency Medical Services (EMS) data to increase timeliness of state data on drug overdose events in late 2016. Using developed definitions of heroin overdose for EMS emergency runs, Kentucky analyzed the patterns of refused/transported EMS runs for both statewide and local jurisdictions. Changes in EMS transportation patterns of heroin overdoses can have a dramatic impact on other surveillance systems, such as emergency department (ED) claims data or syndromic surveillance (SyS) data.

Objective: The aim of this project was to explore changing patterns in patient refusal to transport by emergency medical services for classified heroin overdoses and possible implications on heroin overdose surveillance in Kentucky.

Black Hoosiers, the largest minority population in Indiana, make up almost 10% of the state's population, and accounted for 8% of the total resident drug overdose deaths from 2013-2017 compared to whites at 91%. However, a closer look at race-specific mortality rates might reveal racial inequalities. Therefore, the purpose of this project was to analyze drug overdose morality rates among white and black Hoosiers to discover possible racial inequalities and to discover trends in drug involvement in overdose deaths among blacks.

Objective: To understand trends in race-specific mortality rates between blacks and whites to discover any racial inequalities that might exist for drug overdose deaths. To delve into the types of drugs that are prominently involved in black drug overdose deaths from 2013-2017 in the state of Indiana.

Chronic diseases, including hypertension, type 2 diabetes mellitus (diabetes), obesity, and hyperlipidemia, are some of the leading causes of morbidity and mortality in the United States. Monitoring disease prevalence guides public health programs and policies that help prevent this burden. EHRs can supplement traditional sources of chronic disease surveillance, such as health surveys and administrative claims datasets, by offering near real-time data, large sample sizes, and a rich source of clinical data. However, few studies have provided clear, consistent EHR phenotypes that were developed to inform population health surveillance.

Objective: To utilize clinical data in Electronic Health Records (EHRs) to develop chronic disease phenotypes appropriate for conducting population health surveillance.

Syndromic surveillance systems, although initially developed in response to bioterrorist threats, are increasingly being used at the local, state, and national level to support early identification of infectious disease and other emerging threats to public health. To facilitate detection, one of the goals of CDC's National Syndromic Surveillance Program (NSSP) is to develop and share new sets of syndrome codes with the syndromic surveillance Community of Practice. Before analysts, epidemiologists, and other practitioners begin customizing queries to meet local needs, especially monitoring ED visits in near-real time during public health emergencies, they need to understand how syndromes are developed. More than 4,000 hospital routinely send data to NSSP's BioSense Platform, representing about 55 percent of ED visits in the United States (2). The platform's surveillance component, ESSENCE,* is a web-based application for analyzing and visualizing prediagnostic hospital ED data. ESSENCE's Chief Complaint Query Validation (CCQV) data source, which is a national-level data source with access to chief complaint (CC) and discharge diagnoses (DD) from reporting sites, was designed for testing new queries.

Objective: Emergency department (ED) visits related to mental health (MH) disorders have increased since 2006 (1), indicating a potential burden on the healthcare delivery system. Surveillance systems has been developed to identify and understand these changing trends in how EDs are used and to characterize populations seeking care. Many state and local health departments are using syndromic surveillance to monitor MH-related ED visits in near real-time. This presentation describes how queries can be created and customized to identify select MH sub-indicators (for adults) by using chief complaint text terms and diagnoses codes. The MH sub-indicators examined are mood and depressive disorders, schizophrenic disorders, and anxiety disorders. Wider adoption of syndromic surveillance for characterizing MH disorders can support long-term planning for healthcare resources and service delivery.

Cerebral Palsy (CP) is the most common cause of motor disability in children. CP registries often rely on administrative data such as CP diagnoses or International Classification of Diseases (ICD) codes indicative of CP. However, little is known about the validity of these indicators. We calculated sensitivity, specificity, positive and negative predictive values of CP ICD-9 codes and CP diagnoses compared to a gold standard CP classification based on detailed medical and education record review.

Objective: To compare prevalence estimates obtained by the ADDM cerebral palsy surveillance method to other administrative or diagnostic indications of cerebral palsy.

Injury and violence are public health problems now-a-days all over the world. Over 950000 children less than 18 years of age die as a result of injuries, 95% of which occur in low and middle income countries (LMIC) including India. Unintentional injuries account for 90% of these cases. The death rate due to unintentional injuries is almost double in LMIC as compared to developed countries. It is seen that most of childhood unintentional injuries occur in and around the home of children. India, with a population of app 1.25 billion, had about 40% children. India is passing through a major socio-economic, epidemiological and technological transition. Migration and rapid urbanization is contributing towards the development and growth. Mechanization is changing the traditional lifestyle and thereby resulting an increase in injuries in India. Despite efforts to understand the burden of injuries, the magnitude in terms of morbidity and mortality is still not clear as injury information did not receive much importance in the health sector. Few small studies have reported the prevalence and causes of childhood unintentional injuries. However, there is lack of proper surveillance data on burden of unintentional injuries among children.

Objective: 1. To determine the prevalence and pattern of unintentional injuries among children 2. To study the physical environment of house for various risk factors leading to unintentional injuries.

Southwest states are prone to wildfires, dust storms, and high winds especially during the monsoon season (June- September). Wildfire smoke is a complex mixture of carbon monoxide, carbon dioxide, water vapor, hydrocarbons, nitrogen, oxides, metals, and particulate matter (PM). Dust storms are made up of aerosols and dust particles varying in size; particles bigger than 10 µm are not breathable, but can damage external organs such as causing skin and eye irritations. Particles smaller than 10 µm are inhalable and often are trapped in the nose, mouth, and upper respiratory tracts, and can cause respiratory disorders such as asthma and pneumonia. Numerous studies have characterized the epidemiological and toxicological impact of exposure to PM in dust or smoke form on human health. All of these environmental conditions can have impacts on cardiovascular conditions such as hypertension and cause respiratory flare ups, especially asthma. Previous studies have shown a relationship between PM exposure and increases in respiratory-related hospital admissions. In an analysis of the health effects of a large wildfire in California in 2008, Reid, et. al, observed a linear increase in risk for asthma hospitalizations (RR=1.07, 95% CI= (1.05, 1.10) per 5 µg/m3 increase) and asthma emergency department visits (RR=1.06, 95% CI=(1.05, 1.07) per 5 µg/m3 increase) with increasing PM2.5 during wildfires. In a study specific to New Mexico, Resnick, et. al, found that smoke from the Wallow fire in Arizona in 2011 impacted the health of New Mexicans, observing increases in emergency department visits for asthma flare-ups in Santa Fe, Espanola, and Albuquerque residents. This current study will evaluate the effectiveness of outreach to asthmatic members during times of poor air quality; informing them of the air quality, instructing them to limit their outdoor activity, and to remind them to carry or access their inhalers or other medical necessities if/when needed.

Objective: To inform asthmatic, health plan patients of air quality conditions in their specific geographic location and to assess if the communication is successful in reducing the number of emergency department visits for asthmatic/respiratory flare ups.

Unlike other health threats of recent concern for which widespread mortality was hypothetical, the high fatality burden of opioid overdose crisis is present, steadily growing, and affecting young and old, rural and urban, military and civilian subpopulations. While the background of many public health monitors is mainly infectious disease surveillance, these epidemiologists seek to collaborate with behavioral health and injury prevention programs and with law enforcement and emergency medical services to combat the opioid crisis. Recent efforts have produced key terms and phrases in available data sources and numerous user-friendly dashboards allowing inspection of hundreds of plots. The current effort seeks to distill and present combined fusion alerts of greatest concern from numerous stratified data outputs. Near-term plans are to implement best-performing fusion methods as an ESSENCE module for the benefit of OHA staff and other user groups.

Objective: In a partnership between the Public Health Division of the Oregon Health Authority (OHA) and the Johns Hopkins Applied Physics Laboratory (APL), our objective was develop an analytic fusion tool using streaming data and report-based evidence to improve the targeting and timing of evidence-based interventions in the ongoing opioid overdose epidemic. The tool is intended to enable practical situational awareness in the ESSENCE biosurveillance system to target response programs at the county and state levels. Threats to be monitored include emerging events and gradual trends of overdoses in three categories: all prescription and illicit opioids, heroin, and especially high-mortality synthetic drugs such as fentanyl and its analogues. Traditional sources included emergency department (ED) visits and emergency management services (EMS) call records. Novel sources included poison center calls, death records, and report-based information such as bad batch warnings on social media. Using available data and requirements analyses thus far, we applied and compared Bayesian networks, decision trees, and other machine learning approaches to derive robust tools to reveal emerging overdose threats and identify at-risk subpopulations.

Motor vehicle injury is the leading cause of death in injury category in the United States. In 2016, motor vehicle crashes were one of the main causes of death resulting from injury (8.8 per 100,000 population) in Utah. Motor vehicle crashes can lead to physical and economic consequences that impact the lives of individuals and their families. In addition, the treatment of injuries places an enormous burden on hospital Emergency Departments (EDs). Currently; there are no data sources other than syndromic data in the Utah Department of Health to monitor ED visits due to motor vehicle injuries in real time.

Objective: To describe the characteristics of emergency department (ED) visits for motor vehicle injuries in Utah using 2016 syndromic surveillance data.

Drug overdoses are now the leading cause of accidental death in the United States, with an estimated 60,000 deaths in 2016. Nationally, EMS overdose responses with naloxone administration have nearly doubled from 2012 to 2016 from 573.6 to 1004.4 per 100,000 EMS events. Resuscitation using the opioid antagonist, naloxone is recommended in cases of suspected opioid ODs, and has been increasingly used by EMS agencies, law enforcement, healthcare providers, and Good Samaritans. While naloxone can save lives, it is not clear how often its use is appropriate; delivering the right care to the right patient at the right time. It has been suggested that community paramedic programs teamed with recovery services may help link OD patients to recovery and rehabilitation services and establish mechanisms for follow-up care. Prior to implementing community EMS programs, it is important to understand the EMS utilization patterns of the OD population. I-EMS interactions may present an opportunity for behavioral intervention and linkage to services to prevent future OD and death in the opioid-using population. Accurately documenting substances involved in drug overdose deaths has been of increasing interest to Marion County and Indiana with a recent law requiring toxicology testing 5,6. This project linked individual-level data across public health information systems to assess the appropriateness of naloxone administration, the frequency of I-EMS service utilization until final death outcome among the I-EMS OD deceased cohort, and underlying causes of death among the cohort.

Objective: To characterize the appropriateness of naloxone administration, causes of death, and history of Indianapolis Emergency Medical Services (I-EMS) service utilization among the drug overdose population in Marion County, Indiana between 2011 to 2017.