Dr. Wisco's research program focuses on how data, clinical informatics, performance measurement, and health-system design can be used to improve healthcare quality, access, and outcomes. His team studies how clinical, demographic, socioeconomic, geographic, and health-system factors interact to influence disease severity, access to care, treatment decisions, and patient outcomes. The overarching goal is to move beyond describing variation in healthcare and instead develop practical, scalable methods to identify high-risk populations, improve care delivery, and direct resources where they can have the greatest impact.

A major area of this work is the development of healthcare performance measurement and data infrastructure. The Healthcare Performance Measurement Lab develops care pathway-based performance measures, clinical registries, risk-stratification approaches, and data models that allow clinicians and health systems to better understand the populations they serve and evaluate whether care is producing meaningful outcomes. This work incorporates clinical informatics, population health, epidemiology, geospatial analysis, and implementation science to connect individual patient care with broader patterns of healthcare delivery.

The laboratory is particularly interested in understanding barriers to access and the geographic distribution of healthcare resources. Where patients live, the availability of local expertise, socioeconomic conditions, referral pathways, and competing health priorities can substantially influence when and how patients receive care. By combining clinical and population-level data with geospatial methods, the team seeks to identify communities at greatest risk for poor access or adverse outcomes and to develop targeted interventions that better connect patients and local clinicians with appropriate expertise.

Skin cancer and cutaneous oncology represent one of the laboratory's principal areas of investigation and provide an important model for this work. Current research examines the factors associated with high-risk and advanced skin cancer, including traditional clinical risk factors, genetics, socioeconomic conditions, geography, workforce availability, and access to specialty care. The team uses regional and national datasets to develop risk models, evaluate disparities, and identify populations in which earlier intervention or improved access may reduce disease severity. The laboratory also participates in investigator-initiated and industry-sponsored clinical research evaluating emerging diagnostic, prognostic, preventive, and therapeutic approaches in cutaneous oncology.

A parallel focus of the program is the development of new models for delivering specialty expertise to rural and underserved communities. Dr. Wisco's work in rural Oregon provides a real-world environment for studying how workforce limitations, geography, referral networks, technology, and local healthcare infrastructure affect specialty care delivery. The team is exploring how virtual collaboration, clinical decision support, artificial intelligence, education, regional specialty networks, and other informatics-enabled approaches can extend expertise beyond traditional academic and specialty centers. Rather than requiring every patient to travel to a tertiary center, this work asks how knowledge, decision support, and specialty resources can be brought closer to patients and the clinicians who already care for them.

Across these areas, Dr. Wisco's research is centered on translating data into action. The goal is not simply to create additional datasets or describe disparities, but to build systems that help clinicians and organizations identify risk earlier, measure what matters, improve clinical workflows, allocate resources more effectively, and evaluate whether interventions actually improve outcomes.

Ultimately, the laboratory seeks to develop scalable approaches for creating more effective, equitable, and sustainable healthcare systems. Skin cancer serves as one important focus area and testing ground for these methods, but the broader objective is to develop principles, tools, and care-delivery models that can be applied across specialties and healthcare settings.

Dr. Wisco's research team's current major projects include the following:

Healthcare Performance Measurement and Clinical Data Infrastructure

A central focus of the Healthcare Performance Measurement Lab is developing methods to transform clinical data into meaningful measures of healthcare quality and outcomes. Current work focuses on care pathway-based performance measurement, clinical registry development, risk stratification, and the creation of data infrastructures that allow clinicians and health systems to identify gaps in care and evaluate whether interventions improve meaningful patient outcomes. The broader objective is to develop performance measurement methodologies that are clinically relevant, reproducible, and scalable across healthcare settings and specialties. This work builds upon Dr. Wisco's longstanding national work in performance measurement and registry development and increasingly incorporates clinical informatics, population health analytics, and data-driven healthcare system design.

Evaluation of Advanced Skin Cancer Risk in the United States: A National County-Level Geospatial Risk Analysis

This project uses skin cancer as a model for understanding how geography, healthcare access, population characteristics, and disease risk interact to influence health outcomes. Using large public-domain datasets, including cancer, U.S. Census, healthcare workforce, and public health data, the research team applies multivariate and geospatial methods to identify communities at greatest risk for advanced skin cancer. The project seeks to move beyond traditional individual risk factors by examining how healthcare access, socioeconomic conditions, geography, and local resources may magnify disease risk. A longer-term objective is to develop an open-access population health mapping framework that can help researchers, healthcare organizations, and communities better identify populations that may benefit from targeted interventions.

Predictive Modeling of Advanced Skin Cancer Risk in Rhode Island: A Geospatial Risk Analysis

This Brown-based project examines clinical, demographic, geographic, and access-to-care factors associated with advanced skin cancer across Rhode Island. By integrating patient-level clinical data with population and geospatial information, the research team aims to develop models that identify populations at greatest risk for presenting with more advanced disease. An equally important objective is to evaluate the data infrastructure required to perform population-level risk assessment within a health system. The project is therefore being used both to study skin cancer risk and to identify institutional data gaps, improve clinical research infrastructure, and develop a sustainable registry capable of supporting future population health, quality improvement, and outcomes research.

Rural Specialty Care Access and Health System Design

A major emerging area of the research program examines how specialty expertise can be delivered more effectively to rural and underserved communities. This work evaluates how geography, workforce shortages, referral pathways, socioeconomic factors, technology, and local healthcare infrastructure influence access to specialty care. Current work in rural Oregon includes studying barriers to skin cancer screening and treatment through engagement with primary care clinicians and patients. These projects also serve as a foundation for evaluating broader models of specialty-care delivery using clinical informatics, virtual collaboration, decision support, education, and regional networks. The long-term objective is to develop sustainable models that allow specialty knowledge and resources to move toward patients and local clinicians rather than requiring patients to travel to large tertiary centers whenever specialized expertise is needed. Although dermatology provides an initial model for this work, the principles are intended to be applicable across medical specialties.

Department of Defense Melanoma Prognostic Risk Analysis and Disease Surveillance Infrastructure

This Department of Defense-wide initiative evaluates factors associated with melanoma risk, disease severity, and outcomes among military personnel, retirees, and dependents. The project combines epidemiologic, clinical, occupational, and geospatial approaches, with particular interest in military populations that may experience unique environmental and occupational exposures. The research program is designed to ultimately support development of a comprehensive melanoma prognostic risk model and a performance-driven disease registry and surveillance infrastructure. Future translational work is intended to integrate clinical risk assessment with tissue, genomic, and other biologic data to refine risk prediction and inform prevention, surveillance, and care strategies throughout the military health system.

Cutaneous Oncology Clinical Trials and Precision Risk Assessment

The research team maintains an active clinical research program evaluating emerging approaches to the prevention, risk stratification, and treatment of skin cancer. This work provides an important translational complement to the laboratory's informatics and population health research by connecting health-system questions with advances in molecular diagnostics and therapeutics. Current studies include a multicenter Phase 3 trial evaluating intralesional cemiplimab compared with primary surgery for early-stage cutaneous squamous cell carcinoma, as well as prospective studies examining how melanoma gene-expression profiling influences sentinel lymph node biopsy decisions, surveillance strategies, treatment decisions, and long-term clinical outcomes. These studies also provide an opportunity to evaluate how emerging technologies should be incorporated into real-world clinical pathways and how their effectiveness and value can be measured after implementation.

Immuno-Oncology Education and Knowledge Translation

The research program also examines how rapidly evolving medical knowledge can be translated into accessible education for clinicians and trainees. The Immuno-Oncology Training Academy is developing an interactive educational platform focused on FDA-approved cancer immunotherapies, their mechanisms of action, clinical indications, and immune-related adverse events.

This project serves as a model for developing scalable educational resources that connect academic expertise with clinicians regardless of geographic location. More broadly, the team is interested in how digital education, informatics, and emerging artificial intelligence tools can accelerate dissemination of specialized knowledge and support clinicians practicing in settings where direct access to subspecialty expertise may be limited.

Unifying Goal

Although these projects span several domains, they share a common objective: to use data, informatics, measurement, and healthcare system design to identify risk, improve access to expertise, and create more effective and sustainable systems of care. Skin cancer and cutaneous oncology remain major areas of investigation, but they also provide a practical environment in which methods can be developed, tested, and ultimately adapted to other diseases, specialties, and healthcare settings.

Academic Faculty, Master's in Health Informatics
Affiliated Faculty, Spatial Structures in the Social Sciences (S4)
Affiliated Faculty, Data Science Institute
Brown University

Adjunct Associate Professor of Dermatology
F. Edward Hebert School of Medicine of the Uniformed Services University

Dr. Wisco's teaching philosophy centers on developing the next generation of data-empowered healthcare leaders. He believes that future healthcare professionals must learn not only how to care for individual patients, but also how to understand and improve the complex systems in which care is delivered. His educational approach therefore integrates clinical medicine with leadership, clinical informatics, data science, quality improvement, healthcare operations, and population health. The goal is to help learners become curious, thoughtful leaders who can use data to identify problems, bring people together around solutions, and translate ideas into meaningful improvements in healthcare.

At Brown University, Dr. Wisco teaches across multiple levels of education. He is academic faculty in the Master's in Health Informatics Program, where he teaches Healthcare Acculturation, a course focused on helping learners understand the culture, structure, complexity, and real-world operation of the U.S. healthcare system. At the Warren Alpert Medical School, he teaches a Preclinical Elective in Healthcare Leadership, introducing medical students early in their training to leadership, health-system thinking, organizational change, and the responsibility physicians have to improve the systems in which they practice. He also serves on the Brown University Fulbright Review Committee, where he has served as an application reviewer since 2025 and began serving as a Group Leader in 2026, supporting Brown students pursuing opportunities for international scholarship, research, education, and service.

Dr. Wisco also works closely with Brown undergraduate and medical students through Directed Research/Independent Study and longitudinal research mentorship. He views research as an important vehicle for leadership development rather than simply an exercise in producing publications. Students are encouraged to participate in the entire process of inquiry, including defining meaningful questions, understanding data, developing analytic approaches, working within multidisciplinary teams, interpreting results, communicating findings, and ultimately considering how those findings can be translated into action. Through this model, students progressively develop independence and are encouraged to become mentors and leaders themselves.

Within dermatology, Dr. Wisco teaches residents and fellows in cutaneous oncology, dermatologic surgery, clinical informatics, performance measurement, patient safety, and quality improvement. He also lectures nationally on topics including skin cancer risk analysis, healthcare quality, patient safety, performance measurement, informatics, and emerging therapies in cutaneous oncology. Across each of these settings, his educational objective is the same: to develop clinicians who can combine clinical expertise with data, systems thinking, leadership, and a commitment to service to improve care for both individual patients and the populations they serve.