Next Article in Journal
Predictions of Preterm Birth from Early Pregnancy Characteristics: Born in Guangzhou Cohort Study
Previous Article in Journal
Calcification Patterns in Papillary Thyroid Carcinoma are Associated with Changes in Thyroid Hormones and Coronary Artery Calcification
Open AccessArticle

General Practitioners Records Are Epidemiological Predictors of Comorbidities: An Analytical Cross-Sectional 10-Year Retrospective Study

1
Department of Physics “E.R. Caianiello”, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy
2
Cooperativa Medi-Service, Via R. Lettieri, 2, 84129 Salerno, Italy
3
Miller School of Medicine, University of Miami, Gables One Tower, 1320 S Dixie Hwy, Miami, FL 33146-2930, USA
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2018, 7(8), 184; https://doi.org/10.3390/jcm7080184
Received: 24 April 2018 / Revised: 19 July 2018 / Accepted: 23 July 2018 / Published: 27 July 2018
(This article belongs to the Section Epidemiology & Public Health)
Background. Comorbidity represents the co-occurrence of pathological conditions in the same individual, and presents with very complex patterns. In most cases, reference data for the study of various types of comorbidities linked to complex diseases are those of hospitalized patients. Such patients may likely require cure due to acute conditions. We consider the emerging role of EHR (Electronic Healthcare Records), and study comorbidity patterns in a general population, focusing on diabetic and non-diabetic patients. Methods. We propose a cross-sectional 10-year retrospective study of 14,958 patients and 1,728,736 prescriptions obtained from family doctors, and thus refer to these data as General Practitioner Records (GPR). We then choose networks as the tools to analyze the diabetes comorbidity patterns, distinguished by both prescription type and main patient characteristics (age, gender). Results. As expected, comorbidity increases with patients’ age, and the network representations allow the assessment of associations between morbidity groups. The specific morbidities present in the diabetic population justify the higher comorbidity patterns observed in the target group compared to the non-diabetic population. Conclusions. GPR are usually combined with other data types in EHR studies, but we have shown that prescription data have value as standalone predictive tools, useful to anticipate trends observed at epidemiological level on large populations. This study is thus relevant to policy makers seeking inference tools for an efficient use of massive administrative database resources, and suggests a strategy for detecting comorbidities and investigating their evolution. View Full-Text
Keywords: comorbidity; electronic health records; general practitioner; network analysis; general population; diabetes comorbidity; electronic health records; general practitioner; network analysis; general population; diabetes
Show Figures

Figure 1

MDPI and ACS Style

Cavallo, P.; Pagano, S.; De Santis, M.; Capobianco, E. General Practitioners Records Are Epidemiological Predictors of Comorbidities: An Analytical Cross-Sectional 10-Year Retrospective Study. J. Clin. Med. 2018, 7, 184.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop