EPIDEMIOLOGY

Epidemiology has become a cornerstone for clinical research. The study of how diseases tend to occur in various populations can contribute to our ability to generate and test hypotheses, to the formation of etiological studies, and to risk management and prediction.

The scientific analysis of treatment efficiency and cost versus effectiveness ratio is the foundation on which health policy decision-making is built. Valid evidence produced by various studies, using longitudinal and real-world patient data, may influence decision-makers to reduce damaging health factors and improve public healthcare regimes – thus creating treatment plans better suited for the entire population.

Knowledge gained can suggest new directions for clinical trials, while the development of new medical technologies can significantly improve medicine and the provision of care.

Maccabi Database provides unique advantage

Established in 2010 by Profs. Varda Shalev and Gabriel Chodick, the Epidemiological department has the supreme advantage of access to Maccabi’s immense medical database. Comprised of the medical information of 2.5 million members, collected over 25 years, the database includes demographic data, lab results, clinical visit records, pharmacy purchase data, scans and images.

In addition, the wealth of longitudinally-collected medical information provides a unique advantage in being able to hone in on a single patient or group and follow them across years and even decades, in some instances.

The department team members have expertise in a wide range of medical fields, and their highly thorough and fast-paced research process and groundbreaking medical accomplishments have earned the department its reputation for excellence.

Various Studies Underway

Epidemiological Investigations & Observational Studies

Based on Maccabi’s data mainframes, which contain the medical data of 25% of Israel’s population, we aim to enhance our understanding of the causes, incidence and frequency of disease emerging within the population. As the population of Israel is characterized by a range of ethnicities, the broad range of diversity in the data collected becomes a vital element in many of the studies.
Our existing disease registries include the following:
• Cancer
• Cardiovascular Diseases
• Chronic Kidney Disease
• Chronic Obstructive Pulmonary Disease
• Diabetes
• Home Care
• Hypertension
• Infertility
• Osteoporosis and osteopenia
• Schizophrenia and Bipolar Syndrome
• Warfarin Treatment
• Weight Disorders

The registries inclusion criteria are based on international guidelines, and are the result of a lengthy process of validation. The validation of the specificity and sensitivity of the information using different sets of criteria for the registries allow constant database improvement.

Burden of Disease and Cost-Effectiveness Studies

Burden of disease and cost-effectiveness research provides improved understanding of the cost economic burden of disease within a certain population. This includes the costs of hospitalizations, use of diagnostic services, utilization of healthcare services and medications, lab work and loss of work days. The studies also include comparison of the cost and burden of various treatments, disease management programs and other interventions. These study results are essential for defining the proper priority settings and subsequently the proper allocation of healthcare resources among the entire population.

Comparative Effectiveness Studies

Comparative effectiveness research aims to find the most effective and efficient healthcare procedures and treatments for a specific patient population. It does so by comparing the procedures and outcomes of previously tried methods, techniques and approaches for the same medical conditions. Conducting these studies in a large-scale population provides convincing evidence for the best treatment method. This type of research is an essential stepping stone before further clinical trials can take place.

Research Case Studies

Early identification of patients with high risk of colorectal cancer via a routine blood test

Machine learning of big data in gaining insight into successful treatment of hypertension

From studying disease epidemiology to evaluating the effectiveness and provision of novel therapies: The case of Hepatitis C

Challenges in defining the rates of ADHD diagnosis and treatment: trends over the last decade

Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
Read more >

Machine learning of big data in gaining insight into successful treatment of hypertension.
Read more >

Epidemiology of hepatitis C virus infection in a large Israeli health maintenance organization.
Read more >

Challenges in defining the rates of ADHD diagnosis and treatment: trends over the last decade.
Read more >

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer
Read more >

Sustained virological response to ombitasvir/paritaprevir/
ritonavir and dasabuvir treatment for hepatitis C: Real-world data from a large healthcare provider.

Read more >

Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.
Read more >

Multi-disciplinary patient-centered model for the expedited provision of costly therapies in community settings: the case of new medication for hepatitis C.
Read more >

Early Identification of Patients with High Risk of Colorectal Cancer Via a Routine Blood Test

Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records

Read more >

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer

Read more >

Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.

Read more >

Machine learning of big data in gaining insight into successful treatment of hypertension

Machine learning of big data in gaining insight into successful treatment of hypertension.

Read more >

From epidemiological study to expedited provision of costly therapies in community settings: the case of new medication for hepatitis C

Multi-disciplinary patient-centered model for the expedited provision of costly therapies in community settings: the case of new medication for hepatitis C.

Read more >

Sustained virological response to ombitasvir/paritaprevir/ritonavir and dasabuvir treatment for hepatitis C: Real-world data from a large healthcare provider.

Read more >

Epidemiology of hepatitis C virus infection in a large Israeli health maintenance organization.

Read more >

Challenges in defining the rates of ADHD diagnosis and treatment: trends over the last decade

Challenges in defining the rates of ADHD diagnosis and treatment: trends over the last decade.

Read more >

Our Team