Designing a Multilevel Strategy to Enhance Secondary Prevention of Heart Disease.

Background Coronary artery calcification (CAC), the presence and severity of which strongly predict underlying coronary artery disease (CAD), can be seen on dedicated cardiac imaging studies or incidentally on noncardiac ones; however, the latter findings are commonly managed by primary care clinicians without clear accompanying recommendations and may represent an underrecognized opportunity to optimize secondary prevention of CAD. Methods Standardized practice guidelines and a multilevel implementation strategy for improving secondary prevention of cardiovascular disease through incidentally identified CAC were developed by an interdisciplinary committee. Evidence-based implementation strategies were selected and included integrating practice guidelines into radiology reports within the electronic medical records.

Personalized treatment options for chronic diseases using precision cohort analytics.

To support point-of-care decision making by presenting outcomes of past treatment choices for cohorts of similar patients based on observational data from electronic health records (EHRs), a machine-learning precision cohort treatment option (PCTO) workflow consisting of (1) data extraction, (2) similarity model training, (3) precision cohort identification, and (4) treatment options analysis was developed. The similarity model is used to dynamically create a cohort of similar patients, to inform clinical decisions about an individual patient. The workflow was implemented using EHR data from a large health care provider for three different highly prevalent chronic diseases: hypertension (HTN), type 2 diabetes mellitus (T2DM), and hyperlipidemia (HL).

Precision population analytics: population management at the point-of-care.

Objective: To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.

Materials And Methods: We developed disease-specific, machine-learning, patient-similarity models for hypertension (HTN), type II diabetes mellitus (T2DM), and hyperlipidemia (HL) using data on approximately 2.5 million patients in a large medical group practice.

Harnessing Full Value from the DoD Serum Repository and the Defense Medical Surveillance System.

The Army manages the Department of Defense Serum Repository (DoDSR) of over 43 million serum samples and the associated Defense Medical Surveillance System (DMSS) database that links individual service member characteristics to these biological samples. The main mission and use of these resources has been for military health surveillance. The Army turned to RAND Arroyo Center to systematically examine current requirements and capabilities of the DoDSR and DMSS, identify gaps, and suggest strategies to improve their ability to meet current and potential future military health needs, including surveillance, outbreak investigation, research, and clinical support, particularly as these relate to influenza and other infectious disease threats.

Will routine annual influenza prevention and control systems serve the United States well in a pandemic?

Objective: To assess the extent to which the systems in place for prevention and control of routine annual influenza could provide the information and experience needed to manage a pandemic.

Methods: The authors conducted a qualitative assessment based on key informant interviews and the review of relevant documents.

Results: Although there are a number of systems in place that would likely serve the United States well in a pandemic, much of the information and experience needed to manage a pandemic optimally is not available.

Strategies to improve global influenza surveillance: a decision tool for policymakers.

Background: Global pandemic influenza preparedness relies heavily on public health surveillance, but it is unclear that current surveillance fully meets pandemic preparedness needs.

Methods: We first developed a conceptual framework to help systematically identify strategies to improve the detection of an early case or cluster of novel human influenza disease during the pre-pandemic period. We then developed a process model (flow diagram) depicting nine major pathways through which a case in the community could be detected and confirmed, and mapped the improvement strategies onto this model.

Methadone maintenance in prison: evaluation of a pilot program in Puerto Rico.

Objectives: To describe and evaluate a pilot methadone maintenance program for heroin-dependent inmates of Las Malvinas men's prison in San Juan, Puerto Rico.

Methods: Data from self-report of inmates' drug use before and during incarceration, attitudes about drug treatment in general and methadone maintenance in particular, and expectations about behaviors upon release from prison and from testing inmates' urine were analyzed comparing program patients (n=20) and inmates selected at random from the prison population (n=40). Qualitative data obtained by interviewing program staff, the correctional officers and superintendent, and commonwealth officials responsible for establishing and operating the program were analyzed to identify attitudes about methadone and program effectiveness.