Geographical information system (GIS) as a new tool to evaluate epidemiology based on spatial analysis and clinical outcomes in acromegaly

Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends

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.

Value of Geographical Information Systems in Analyzing Geographic Accessibility to Inform Radiotherapy Planning: A Systematic Review

PURPOSE

Vulnerable populations face geographical barriers in accessing radiotherapy (RT) facilities, resulting in heterogeneity of care received and cancer burden faced. We aimed to explore the current use of Geographical Information Systems (GIS) in access to RT and use these findings to create sustainable solutions against barriers for access in low- and middle-income countries.

MATERIALS AND METHODS

A systematic review using the PRISMA search strategy was done for studies using GIS to explore outcomes among patients with cancer. Included studies were reviewed and classified into three umbrella categories of how GIS has been used in studying access to RT.

RESULTS

Forty articles were included in the final review. Thirty-eight articles were set in high-income countries and two in upper-middle-income countries. Included studies were published from 2000 to 2020, and were comprised of patients with all-cancers combined, breast, colon, skin, lung, prostate, ovarian, and rectal carcinoma patients. Studies were categorized under three groups on the basis of how they used GIS in their analyses: to describe geographic access to RT, to associate geographic access to RT with outcomes, and for RT planning. Most studies fell under multiple categories.

CONCLUSION

Although this field is relative nascent, there is a wide array of functions possible through GIS for RT planning, including identifying high-risk populations, improving access in high-need areas, and providing valuable information for future resource allocation. GIS should be incorporated in future studies, especially set in low- and middle-income countries, which evaluate access to RT.

Implementation and Monitoring of a Telemedicine Model in Acromegalic Outpatients in a Low-Income Country During the COVID-19 Pandemic

Background: Telemedicine is a resource to provide health care to patients social distancing and prevent their exposure to the risk of contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in medical-hospital settings. This study evaluated a virtual model of care in acromegalic patients. Methods: We recruited 78 acromegalic patients, 65% female, median age 63 years. Outpatient management was remodeled to simplify access to care by (1) adoption of virtual meetings; (2) collection of blood samples at home; (3) abolishment of printed prescription and provision of electronic files directly to central pharmacy; and (4) drugs delivered to patients' home. Patients and physicians filled electronic surveys 48 h after each consultation. Results: The patients expressed satisfaction with convenience (91.1%), decreased wait time (85.1%), and saving money (79.2%) compared to face-to-face visits. Most patients felt supported by the medical team (89.1%) and kept the prescriptions updated (84.8%). The physicians reported resolutive appointments in 92.2% of cases, despite longer time to reach the patients and subsequent calls to complement missing information. Satisfaction and patient-provider relationship were maintained during the study, but the choice for virtual appointment for the next appointment fell from 78.7% to 34.8% after 6 months. Coronavirus disease 2019 (COVID-19) was confirmed in 13% of patients, mostly mild and moderate manifestations. Conclusion: Telemedicine is a tool for medical care in underserved populations, feasible even in low-income countries. This study suggests that it is difficult to sustain exclusive remote care for more than 6 months. The method could be adopted interchangeably with in-person consultations in acromegalic patients with stable disease.

Spatial distribution of vaccine-preventable diseases in central Iran in 2015-2018: A GIS-based study

Vaccination is the second most effective health measure to maintain public health and prevent diseases after providing safe drinking water. This study aimed to determine the geographical distribution of vaccine-preventable diseases (VPDs) in Qom Province in four years (2015–2018) using Geographic Information System (GIS). In this cross-sectional study, the indicators of VPDs surveillance were extracted from the VPDs surveillance system at the Centers for Disease Control and Prevention (CDC) in Qom University of Medical Sciences. They were further evaluated, and the incidences of VPDs in the study years were investigated. Finally, the spatial distribution map of VPDs was provided for surveillance quality in each Qom district by Arc GIS 10.3 software. The annual incidence rate (AIR) was estimated to be 18.47 for hepatitis B, 0.29 for measles, 0.13 for rubella, 0.09 for pertussis, 0.29 for diphtheria and 0.91 for acute flaccid paralysis (AFP). The highest incidences of AFP, rubella and measles were observed in Markazi district. Salafchegan was a district with the highest incidence of diphtheria, and the highest incidence rate of hepatitis B was observed in Khalajestan district. In addition, all pertussis cases were reported from Qom city. According to thematic maps of GIS, the annual incidence rate of VPDs in Qom Province was lower than the mean rate in Iran. Nevertheless, it is highly recommended that a high immunization coverage should be done in the childhood and good surveillance indicators such as non-disease discarded rate, and the proportion of suspected cases with an adequate investigation should be used to monitor VPDs.

The Epidemiology of Pituitary Adenomas

Pituitary adenomas are usually nonmalignant, but have a heavy burden on patients and health care systems. Increased availability of MRI has led to an increase in incidentally found pituitary lesions and clinically relevant pituitary adenomas. Epidemiologic studies show that pituitary adenomas are increasing in incidence (between 3.9 and 7.4 cases per 100,000 per year) and prevalence (76 to 116 cases per 100,000 population) in the general population (approximately 1 case per 1000 of the general population). Most new cases diagnosed are prolactinomas and nonsecreting pituitary adenomas. Most clinically relevant pituitary adenomas occur in females, but pituitary adenomas are clinically heterogeneous.

Long-term real-life outcomes in a georrefered cohort of acromegalic patients in Brazil

PURPOSE

Epidemiological data on acromegaly therapeutic outcomes in real-life conditions are scarce in Brazil. Information on the geographical accessibility to the dispensation of medicines and its impact on biochemical control is also poorly known. We aimed to describe the clinical outcomes of long-term therapy in patients with acromegaly at a referral medical centre in Brazil and to perform a spatial analysis of patients according to the distance from home to the drug-dispensing pharmacies aiming to evaluate its impact on biochemical control.

METHODS

Global retrospective data analysis of 111 patients followed at the University Hospital of Brasília from January 1980 to March 2015 was performed, as well as a separate review of 17 new cases operated on from April 2015 to June 2019 according to surgery results. Spatial analysis of patients under pharmacological treatment applying Geographic Information System (GIS) software (ArcGIS, ESRI, Redlands, CA) was performed.

RESULTS

Considering surgery alone, the cure rate was 23% from 1980 to 2015 and 29.4% from 2015 to 2019. In the long-term follow-up of the 111 patients from 1980 to 2015, 25.2% (n = 29) were cured, 40.6% (n = 44) presented controlled disease and 34.2% (n = 38) were biochemically uncontrolled after a period of follow-up of 8.9 ± 6.4 years. Biochemical control obtained in patients on pharmacological treatment (n = 76) was 58% (n = 44) after 5.8 ± 3.8 years. The distance from home to the drug-dispensing pharmacy did not influence biochemical control (p = 0.7616).

CONCLUSIONS

Most patients presented with disease under control. No evidence on the effect of the distance between home and drug-dispensing pharmacies on biochemical control was obtained.

Epidemiology of acromegaly in Italy: analysis from a large longitudinal primary care database

PURPOSE

Epidemiological data are pivotal for the estimation of disease burden in populations.

AIM

Of the study was to estimate the incidence and prevalence of acromegaly in Italy along with the impact of comorbidities and hospitalization rates as compared to the general population.

METHODS

Retrospective epidemiological study (from 2000 to 2014) and case control-study. Data were extracted from the Health Search Database (HSD). HSD contains patient records from about 1000 general practitioners (GPs) throughout Italy, covering a population of more than 1 million patients. It includes information about patient demographics and medical data including clinical diagnoses and diagnostic tests.

RESULTS

At the end of the study period, 74 acromegaly patients (out of 1,066,871 people) were identified, resulting in a prevalence of 6.9 per 100,000 inhabitants [95% CI 5.4-8.5]. Prevalence was higher in females than men (p = 0.004), and showed a statistically significant trend of increase over time (p < 0.0001). Overall, incidence during the study period was 0.31 per 100,000 person-years. Hypertension and type II diabetes mellitus were the comorbidities more frequently associated with acromegaly (31.3 and 14.6%, respectively) and patients were more likely to undergo a high frequency of yearly hospitalization (≥3 accesses/year, p < 0.001) compared to sex-age matched controls.

CONCLUSIONS

This epidemiological study on acromegaly carried out using a large GP-based database, documented a disease prevalence of about 7 cases per 100,000 inhabitants. As expected, acromegaly was associated with a number of comorbidities (mainly hypertension and type II diabetes mellitus) and a high rate of patients' hospitalization.

Oral primary care: an analysis of its impact on the incidence and mortality rates of oral cancer

Background

Oral cancer is a potentially fatal disease, especially when diagnosed in advanced stages. In Brazil, the primary health care (PHC) system is responsible for promoting oral health in order to prevent oral diseases. However, there is insufficient evidence to assess whether actions of the PHC system have some effect on the morbidity and mortality from oral cancer. The purpose of this study was to analyze the effect of PHC structure and work processes on the incidence and mortality rates of oral cancer after adjusting for contextual variables.

Methods

An ecological, longitudinal and analytical study was carried out. Data were obtained from different secondary data sources, including three surveys that were nationally representative of Brazilian PHC and carried out over the course of 10 years (2002–2012). Data were aggregated at the state level at different times. Oral cancer incidence and mortality rates, standardized by age and gender, served as the dependent variables. Covariables (sociodemographic, structure of basic health units, and work process in oral health) were entered in the regression models using a hierarchical approach based on a theoretical model. Analysis of mixed effects with random intercept model was also conducted (alpha = 5%).

Results

The oral cancer incidence rate was positively association with the proportion of of adults over 60 years (β = 0.59; p = 0.010) and adult smokers (β = 0.29; p = 0.010). The oral cancer related mortality rate was positively associated with the proportion of of adults over 60 years (β = 0.24; p < 0.001) and the performance of preventative and diagnostic actions for oral cancer (β = 0.02; p = 0.002). Mortality was inversely associated with the coverage of primary care teams (β = −0.01; p < 0.006) and PHC financing (β = −0.52⁻⁹; p = 0.014).

Conclusions

In Brazil, the PHC structure and work processes have been shown to help reduce the mortality rate of oral cancer, but not the incidence rate of the disease. We recommend expanding investments in PHC in order to prevent oral cancer related deaths.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3700-z) contains supplementary material, which is available to authorized users.

Stroke Mortality Attributable to Ambient Particulate Matter Pollution from 1990 to 2015 in China: An Age-Period-Cohort and Spatial Autocorrelation Analysis

In this study, we analyzed the temporal and spatial variations of stroke mortality attributable to ambient particulate matter pollution (stroke mortality-PM_2.5) in China from 1990 to 2015. Data were collected from the Global Burden of Disease (GBD) 2015 study and analyzed by an age-period-cohort model (APC) with an intrinsic estimator (IE) algorithm, as well as spatial autocorrelation based on the Geographic Information System. Based on APC analysis with the IE method, stroke mortality-PM_2.5 increased exponentially with age, its relative risk reaching 42.85 (95% CI: 28.79, 63.43) in the 75–79 age group. The period effects showed a reversed V-shape and its highest relative risk was 1.22 (95% CI: 1.15, 1.27) in 2005. The cohort effects decreased monotonically from 1915–1919 to 1990–1994. The change rate fluctuated from 1920–1924 to 1990–1994, including three accelerating and three decelerating decreases. There was a positive spatial autocorrelation in stroke mortality-PM_2.5 from 1990 to 2015. Hot-spots moved from the northeastern areas to the middle and southwestern areas, whereas cold-spots lay mostly in coastal provinces. Besides the aging process in recent years, stroke mortality-PM_2.5 had significantly declined from 2005 to 2015 due to socio-economic and healthcare development. Stroke mortality-PM_2.5 varied substantially among different regions, and cost-effective prevention and control should be implemented more in the middle and southwestern areas of China.

Geographic information system analysis on the distribution of patients visiting the periodontology department at a dental college hospital

PURPOSE

The aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases.

METHODS

Basic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution.

RESULTS

The visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient's regional center to the hospital was 30.94±29.62 km and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was 52.41±12.97 years. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses.

CONCLUSIONS

The distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.

Prognostic Value of Invasion, Markers of Proliferation, and Classification of Giant Pituitary Tumors, in a Georeferred Cohort in Brazil of 50 Patients, with a Long-Term Postoperative Follow-Up

Although some pituitary adenomas may have an aggressive behavior, the vast majority are benign. There are still controversies about predictive factors regarding the biological behavior of these particular tumors. This study evaluated potential markers of invasion and proliferation compared to current classification patterns and epidemiogeographical parameters. The study included 50 patients, operated on for tumors greater than 30 mm, with a mean postoperative follow-up of 15.2 ± 4.8 years. Pituitary magnetic resonance was used to evaluate regrowth, invasion, and extension to adjacent tissue. Three tissue biomarkers were analyzed: p53, Ki-67, and c-erbB2. Tumors were classified according to a combination of histological and radiological features, ranging from noninvasive and nonproliferative (grade 1A) to invasive-proliferative (grade 2B). Tumors grades 2A and 2B represented 42% and 52%, respectively. Ki-67 (p = 0.23) and c-erbB2 (p = 0.71) had no significant relation to tumor progression status. P53 (p = 0.003), parasellar invasion (p = 0.03), and classification, grade 2B (p = 0.01), were associated with worse clinical outcome. Parasellar invasion prevails as strong predictive factor of tumor recurrence. Severe suprasellar extension should be considered as invasion parameter and could impact prognosis. No environmental factors or geographical cluster were associated with tumor behavior.

A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China

BACKGROUND

Acute exacerbations of COPD (AECOPD) are important events during disease procedure. AECOPD have negative effect on patients' quality of life, symptoms and lung function, and result in high socioeconomic costs. Though previous studies have demonstrated the significant association between outdoor air pollution and AECOPD hospitalizations, little is known about the spatial relationship utilized a spatial analyzing technique- Geographical Information System (GIS).

OBJECTIVE

Using GIS to investigate the spatial association between ambient air pollution and AECOPD hospitalizations in Jinan City, 2009.

METHODS

414 AECOPD hospitalization cases in Jinan, 2009 were enrolled in our analysis. Monthly concentrations of five monitored air pollutants (NO2, SO2, PM10, O3, CO) during January 2009-December 2009 were provided by Environmental Protection Agency of Shandong Province. Each individual was geocoded in ArcGIS10.0 software. The spatial distribution of five pollutants and the temporal-spatial specific air pollutants exposure level for each individual was estimated by ordinary Kriging model. Spatial autocorrelation (Global Moran's I) was employed to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. A generalized linear model (GLM) using a Poisson distribution with log-link function was used to construct a core model.

RESULTS

At residence, concentrations of SO2, PM10, NO2, CO, O3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O3, CO at workplace is 11.39, 8.07, 6.10, and 5.08 respectively. After adjusting for potential confounders in the model, only the PM10 concentrations at workplace showed statistical significance, with a 10 μg/m(3) increase of PM10 at workplace associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD.

CONCLUSIONS

Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 μg/m(3) increase of PM10 at workplace was associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD in Jinan, 2009. As a spatial data processing tool, GIS has novel and great potential on air pollutants exposure assessment and spatial analysis in AECOPD research.