About

Catherine Hayes is a Clinical Professor of Health Policy and Health Services Research at the Henry M. Goldman School of Dental Medicine. She holds a Doctor of Medicine in Science (Epidemiology) from Harvard University, earned in 1993, a Master of Science in Epidemiology from Harvard University, earned in 1989, and a Doctor of Dental Medicine (DMD) from Tufts University, earned in 1987. Her academic and professional focus is on health policy and health services research, contributing to the education and training of students in these fields at Boston University.

Research topics

• Medicine
• Family medicine
• Environmental health
• Demography
• Psychology
• Pediatrics
• Internal medicine
• Psychiatry
• Clinical psychology

Selected publications

• Determination of the apparent prevalence of Neospora caninum in bovine foetuses: a comparison of three diagnostics tests

  Animal - science proceedings · 2025-06-01

  article1st author
  PublisherDOI

• Factors influencing use and choice of Core Outcome Sets and Outcome Measurement Instruments in trials of interventions to prevent childhood obesity: a mixed-methods survey

  Journal of Clinical Epidemiology · 2025-12-12

  articleOpen access
  PublisherOA PDFDOI

• Potential of national/regional datasets to support targeted service planning.

  PubMed · 2025-01-27

  article1st authorCorresponding

  Aim: This survey reviewed the content of national and regional health datasets to assess their potential to support service planning and sub-population targeting. Methods: The Health Information and Quality Authority catalogue (v.4) of health and social care datasets (129) was examined. Datasets relevant to the implementation of Sláintecare (37) were selected by consensus. A variable list was constructed for geographic granularity, and inclusivity measures. An online survey of the presence of parameters was sent to the database managers in Microsoft Forms. Analysis was descriptive. Results: The survey response rate was 33/36 (92%), (one duplicate removed). Age was recorded on all databases and sex on 31/33 (94%). Socio-economic, medical-card and education status were poorly recorded on 11 (33%,) 10 (30%) and 9 (27%) databases respectively). Race, ethnicity or cultural details were recorded on 16 (49% and disability on 12 (36%). County was recorded on 27 (82%) , Health Region (not current) on 13, (38%) electoral division on 11 (33%), and CSO small area on 8 (24%). Concerns around GDPR and lack of resources emerged as key themes from comments. Discussion: Existing datasets have large gaps in variables that could support tailored health service planning. A standardised approach to the inclusion of critical parameters within health datasets is required to support the full implementation of Sláintecare.

  Publisher

• Validate artificial intelligence for the diagnosis of periodontal disease

  BMC Oral Health · 2025-12-11

  articleOpen accessSenior author

  Periodontal disease is among the most prevalent diseases globally, yet it often goes undetected, with only 27% of cases reported to receive treatment in the US. In situations when clinical examination is not possible, radiographic findings may serve as an alternative method for periodontal disease diagnosis. Several Artificial Intelligence (AI) platforms were developed to detect the amount of radiographic bone loss with different accuracy levels. Therefore, this study aimed to validate the Overjet AI platform for diagnosing periodontal disease using full-mouth radiographs against the gold standard of clinical-radiographic analysis, and to compare its diagnostic accuracy with manual radiographic assessment by a general practitioner (GP). In this study radiographic records of patients aged over 29 years were utilized to validate the use of radiographic analysis (using full-mouth radiographs) solely by GP and by Overjet AI software for detecting periodontal disease. A sample size calculation was performed with 95% power and an alpha of 0.05 to identify an effect size of 0.2. To evaluate the diagnostic accuracy of the Overjet AI software, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated against the gold standard of the combined clinical and radiographic analysis conducted by a periodontist. Cohen’s Kappa agreement was used to compare results from manual radiographic analysis by GP verses AI platform. The study included radiographic records of 103 patients. Results showed that detecting periodontal disease across different severity level using radiographic analysis manually achieved 100 − 83% sensitivity and 94 − 90% specificity. While Overjet AI software achieved 100 − 82% sensitivity and 96 − 89% specificity. The Cohen’s Kappa agreement between the GP and AI platform results was between 0.49 and 0.85 representing a moderate to almost perfect agreement. AI-based radiographic analysis offers a rapid and accurate alternative to manual dentist assessments, particularly for detecting moderate to severe periodontal disease. The findings suggest a potential for integrating AI technology with conventional clinical exam to improve the efficiency and accuracy of periodontal disease detection and monitoring.

  PublisherDOI

• Not Enough Dentistry

  JAMA Otolaryngology–Head & Neck Surgery · 2025-01-23 · 2 citations

  article

  This Viewpoint discusses the gap in dental insurance coverage for patients with head and neck cancer, many of whom forego dental care to treat or prevent oral complications of head and neck cancer therapy due to financial hardship.

  PublisherDOI

• Use of implementation science frameworks to identify core components and sustainability characteristics of a quality improvement learning collaborative

  BMC Health Services Research · 2025-09-30 · 1 citations

  articleOpen accessSenior author

  BACKGROUND: Implementation Science (IS) frameworks facilitate definition of core and optional components of innovations, interventions and programmes, which increases the likelihood of successful implementation and sustainment. We used IS frameworks to characterise a hospital-based interdisciplinary quality improvement learning collaborative (QILC) which was established to develop quality improvement (QI) capability among front-line staff. The aim was to identify factors that supported implementation, potential threats to sustainability and elements that may influence dissemination into other settings. METHODS: Of five IS frameworks evaluated, two were selected, the Active Implementation Framework (action-oriented, dependent on feedback loops and improvement cycles) and the Consolidated Framework for Implementation Research (enabled definition of core components). The QILC was mapped against the drivers and constructs of each. RESULTS: Factors relating to the QILC's leadership; the generation of tension for change; and the use of both internal and external networks were central features in implementation. Key drivers included the characteristics of front-line ownership, iterative development and tribality of the QILC, each being central to QI methodology. Risks to sustainability included patchy implementation, a requirement for greater alignment with organisational priorities, requirement for coaching and recruitment of additional leaders to support succession planning. CONCLUSIONS: IS provided frameworks for retrospective analysis of a QI learning collaborative and identified factors that threaten sustainability. This analysis should help guide formative evaluations of similar QI learning collaboratives and offer an organisational framework to facilitate successful replication within different parts of an organisation and across multiple settings.

  PublisherOA PDFDOI

• 1259 Integrating findings from a mixed method study to inform multi-level interventions for advance care planning

  Poster · 2025-09-01

  articleOpen access

  <h3>Aim</h3> To synthesize findings from a mixed method project to inform the design of a multilevel ACP intervention for community-dwellers (≥50 years old). <h3>Background</h3> A systematic findings synthesis can enhance an understanding of the key factors that drive behavior change in planning for future care (1). However, existing ACP interventions fail to build on findings from studies using such methodologies. This research aimed to address this gap by integrating findings from across three studies to inform an evidence-based solution. <h3>Method</h3> The study used an adapted Framework for Integration in a Mixed Methods Study (2,3), which included six staged: (a) data reduction, (b) data transformation, (c) data comparison, (d) data integration, (e) mapping, and (f) credibility checks. Using the ‘following the thread’ technique, the findings from a large-scale mixed research systematic review (n=187) were used as a base when considering the results of the analysis of population-based data from the Irish Longitudinal Study of Aging (TILDA) (n=2884) and the findings from three collective intelligence workshops (n=22). The levels of agreement, complementarity, dissonance, and silence were explored across the datasets. The integrated findings were mapped across the Conceptual Model of ACP Behaviors and Influencing Factors (2). <h3>Results</h3> Across the three phases of the mixed-methods study, 37 integrated findings were generated. They were further clustered into five higher-level patterns, each including a problem and a solution dimension. These meta-themes highlighted the need to: (A) Embrace Intersubjectivity within a Spatiotemporal Paradox; (B) Take a Life Course, Existential, and Multi-stakeholder Approach to Capacity Building; (C) Consider Vulnerability and Responsibility within a Mindful, Inclusive, and Empowering Stakeholders’ Interaction; (D) Account for all Stakeholders‘ Needs in the Co-production of an Innovative, Accessible, Evidence-based, and Patient-centered Solution; and (E) Embed Positive and Empowering Interventions within Transformed, Services, Societies, and Cultures. <h3>Discussion</h3> The meta-themes represent overarching patterns of ACP behaviors embedded in complex social contexts. The mapping of the integrated findings across a theoretical model highlighted that future ACP interventions should target factors at the intersection of individual, interpersonal, service and system levels. <h3>Implications for Policy and Practice</h3> The problem-solution lenses ensured an applied focus and facilitated specification of intervention development and policy recommendations. The findings point to the need to take a holistic approach and emphasize relational autonomy. <h3>Unique Contribution</h3> By using systematic integration techniques, the study enriched an understanding of the problem situation in the field of ACP and helped define requirements for a comprehensive ACP solution.

  PublisherOA PDFDOI

• Public Health in Sub-Saharan Africa

  2024-08-22 · 1 citations

  book

  This fascinating collection shines a social epidemiological spotlight onto the key public health issues effecting sub-Saharan Africa today. Beginning with the legacy of colonial rule, the book outlines the complex interplay between population health and a range of social, economic and cultural factors. It shows how social epidemiological methods can offer a deeper understanding of population health, and features chapters on a range of infectious diseases which continue to have a devastating impact on the region, including Sickle Cell Disease, HIV /AIDS, Leprosy and Ebola. The final section of the book includes a series of case studies where social epidemiological methods have been used to explore specific public health issues. Providing a timely overview of the relationship between social systems and human biology in the region, this important book will interest students and researchers across Public Health, Medicine and African Studies

  PublisherDOI

• Referee report. For: Linked Cardiology records of the children in the Avon Longitudinal Study of Parents and Children (ALSPAC) From The University Hospitals Bristol and Weston NHS Foundation Trust (UHBW) Heart-Suite (HS) dataset [version 1; peer review: 2 approved with reservations]

  Faculty of 1000 Research Ltd · 2024-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• Vaccine-preventable Diseases

  2024-08-22 · 1 citations

  book-chapterSenior author

  This chapter provides insight into a unique aspect of social epidemiology in Africa, represented by the Fulani community. This has relevance to the effective delivery and tangible impact of vaccination programmes, since the Fulanis, as a nomadic community, often live in particularly remote, severely compromised, and strife-torn geographical areas that remain difficult to access in terms of their location, cultures, and communities. Part of the rich cultural heritage of nomadic communities is their continual pastoral movement across states, their occupation of traditional settings, and their strict adherence to orthodox cultural values and beliefs. While this intergenerational culture is fundamentally unique and characterised by deep pride in ancestral heritage, it has also been historically associated with increased incidence and prevalence rates of vaccine-preventable diseases. The chapter focuses on a unique contribution to healthcare knowledge and the planning of prospective strategic interventions via focused public health research regarding the health-seeking behaviour of the nomadic Fulani tribe. Via the adoption of a situational analysis methodological approach guided by the process of constructivist grounded theory, the chapter provides a window into how Deleuze and Guattari’s concepts of assemblage, becoming, territorialisation, deterritorialization, and reterritorialisation could serve as a theoretical lens, which provides a clarity of perspective on how best the data collected could be analysed and consequently recorded.

  PublisherDOI

Frequent coauthors

• Oliver FitzGerald

  University College Dublin

  53 shared

• Z. Johnson

  42 shared

• Cliona OʼFarrelly

  40 shared

• D. Sugrue

  Mater Misericordiae University Hospital

  40 shared

• Barry Bresnihan

  St. Vincent's University Hospital

  38 shared

• J. Feely

  St. James's Hospital

  36 shared

• M. X. FitzGerald

  35 shared

• H. McCann

  Mater Misericordiae University Hospital

  32 shared

Education

• Other

  Tufts University

  1987

• Other, Epidemiology

  Harvard University

  1989

• Other, Epidemiology

  Harvard University

  1993