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Mollalo A, Hamidi B, Lenert L, Alekseyenko AV. Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends. RESEARCH SQUARE 2024:rs.3.rs-3443865. [PMID: 37886509 PMCID: PMC10602163 DOI: 10.21203/rs.3.rs-3443865/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background Electronic health records (EHR) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHR in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. Objective This study reviews advanced spatial analyses that employed individual-level health data from EHR within the US to characterize patient phenotypes. Methods We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, study design, or specific health domains. Results Only 49 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. A noteworthy surge (n = 42, 85.7%) in publications was observed post-2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized. Conclusions This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future clinical decision support.
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Nyame YA, Cooperberg MR, Cumberbatch MG, Eggener SE, Etzioni R, Gomez SL, Haiman C, Huang F, Lee CT, Litwin MS, Lyratzopoulos G, Mohler JL, Murphy AB, Pettaway C, Powell IJ, Sasieni P, Schaeffer EM, Shariat SF, Gore JL. Deconstructing, Addressing, and Eliminating Racial and Ethnic Inequities in Prostate Cancer Care. Eur Urol 2022; 82:341-351. [PMID: 35367082 DOI: 10.1016/j.eururo.2022.03.007] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 02/24/2022] [Accepted: 03/10/2022] [Indexed: 12/24/2022]
Abstract
CONTEXT Men of African ancestry have demonstrated markedly higher rates of prostate cancer mortality than men of other races and ethnicities around the world. In fact, the highest rates of prostate cancer mortality worldwide are found in the Caribbean and Sub-Saharan West Africa, and among men of African descent in the USA. Addressing this inequity in prostate cancer care and outcomes requires a focused research approach that creates durable solutions to address the structural, social, environmental, and health factors that create racial disparities in care and outcomes. OBJECTIVE To introduce a conceptual model for evaluating racial inequities in prostate cancer care to facilitate the development of translational research studies and interventions. EVIDENCE ACQUISITION A collaborative review of literature relevant to racial inequities in prostate cancer care and outcomes was performed. Existing literature was used to highlight various components of the conceptual model to inform future research and interventions toward equitable care and outcomes. EVIDENCE SYNTHESIS Racial inequities in prostate cancer outcomes are driven by a series of structural and social determinants of health that impact exposures, mediators, and outcomes. Social determinants of equity, such as laws/policies, economic systems, and structural racism, affect the inequitable access to environmental and neighborhood exposures, in addition to health care access. Although the incidence disparity remains problematic, various studies have demonstrated parity in outcomes when social and health factors, such as access to equitable care, are normalized. Few studies have tested interventions to reduce inequities in prostate cancer among Black men. CONCLUSIONS Worldwide, men of African ancestry demonstrate worse outcomes in prostate cancer, a phenomenon driven largely by social factors that inform biologic, environmental, and health care risks. A conceptual model was presented that organizes the many factors that influence prostate cancer incidence and mortality. Within that framework, we must understand the current state of inequities in clinical prostate cancer practice, the optimal state of what equitable practice would be, and how achieving equity in prostate cancer care balances costs, benefits, and harms. More robust characterization of the sources of prostate cancer inequities should inform testing of ambitious and innovative interventions as we work toward equity in care and outcomes. PATIENT SUMMARY Men of African ancestry demonstrate the highest rates of prostate cancer mortality, which may be reduced through social interventions. We present a framework for formalizing the identification of the drivers of prostate cancer inequities to facilitate the development of interventions and trials to eradicate them.
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Affiliation(s)
- Yaw A Nyame
- Department of Urology, University of Washington Medical Center, Seattle, WA, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Matthew R Cooperberg
- Department of Urology, University of California at San Francisco, San Francisco, CA, USA
| | | | - Scott E Eggener
- Department of Urology, University of Chicago, Chicago, IL, USA
| | - Ruth Etzioni
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Scarlett L Gomez
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Christopher Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Franklin Huang
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Cheryl T Lee
- Department of Urology, The Ohio State University, Columbus, OH, USA
| | - Mark S Litwin
- Department of Urology, University of California Los Angeles, Los Angeles, CA, USA
| | - Georgios Lyratzopoulos
- Epidemiology of Cancer Healthcare & Outcomes, Institute of Epidemiology & Health Care, University College London, London, UK
| | - James L Mohler
- Department of Urology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Adam B Murphy
- Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Curtis Pettaway
- Department of Urology, M.D. Anderson Cancer Center, The University of Texas, Houston, TX, USA
| | - Isaac J Powell
- Department of Urology, Wayne State University, Detroit, MI, USA
| | - Peter Sasieni
- Cancer Research UK & King's College London Cancer Prevention Trials Unit, King's College London, London, UK
| | - Edward M Schaeffer
- Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Division of Urology, Department of Special Surgery, Jordan University Hospital, The University of Jordan, Amman, Jordan; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia; Department of Urology, Weill Cornell Medical College, New York, NY, USA; Department of Urology, University of Texas Southwestern, Dallas, TX, USA
| | - John L Gore
- Department of Urology, University of Washington Medical Center, Seattle, WA, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Georgantopoulos P, Eberth JM, Cai B, Rao G, Bennett CL, Emrich CT, Haddock KS, Hébert JR. A spatial assessment of prostate cancer mortality-to-incidence ratios among South Carolina veterans: 1999-2015. Ann Epidemiol 2021; 59:24-32. [PMID: 33836289 DOI: 10.1016/j.annepidem.2021.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 03/23/2021] [Accepted: 03/25/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To assess veteran-specific prostate cancer (PrCA) mortality-to-incidence ratios (MIR) in South Carolina's (SC) veteran population. METHODS U.S. Veterans Health Administration electronic medical records from January 1999 to December 2015 identified 3,073 PrCA patients residing in 345 ZIP code tabulation areas (ZCTA) within SC. MIRs were calculated for all SC ZCTAs and by key patient- and neighborhood-level risk factors for PrCA. Comparisons between ZCTAs identified as part of a spatial cluster were compared with non-significant ZCTAs using t tests. RESULTS The MIR was 0.17 overall, ranging from a low of 0.15 among Black men to 0.20 among White men. Among metropolitan ZCTAs, the MIR was 0.18 compared to 0.16 in non-metropolitan ZCTAs. Two clusters of higher-than-expected MIRs were found in the Upstate region. CONCLUSIONS Identification of spatial clusters of higher- or lower-than-expected MIRs allows for further testing of possible explanatory factors, and the capacity to target resources and policies according to greatest need.
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Affiliation(s)
- Peter Georgantopoulos
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC; Southern Network on Adverse Reactions (SONAR), South Carolina Center of Economic Excellence for Medication Safety, College of Pharmacy, University of South Carolina, Columbia, SC; Columbia Veterans Affairs Health Care System, Columbia, SC.
| | - Jan M Eberth
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Bo Cai
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Gowtham Rao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Charles L Bennett
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC; Southern Network on Adverse Reactions (SONAR), South Carolina Center of Economic Excellence for Medication Safety, College of Pharmacy, University of South Carolina, Columbia, SC; Columbia Veterans Affairs Health Care System, Columbia, SC
| | - Christopher T Emrich
- College of Community Innovation and Education, University of Central Florida, Orlando, FL
| | | | - James R Hébert
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
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