Community determinants of COPD exacerbations in elderly patients in Poland: protocol for a retrospective Big Data observational cohort study

Community determinants of COPD exacerbations in elderly patients in Lodz province, Poland: a retrospective observational Big Data cohort study

OBJECTIVES

To evaluate the prevalence and identify demographic, economic and environmental local community determinants of chronic obstructive pulmonary disease (COPD) exacerbations in elderly in primary care using Big Data approach.

DESIGN

Retrospective observational case-control study based on Big Data from the National Health Found, Tax Office and National Statistics Center databases in 2016.

SETTING

Primary care clinics in the Lodz province in Poland.

PARTICIPANTS

472 314 patients aged 65 and older in primary care, including 17 240 patients with COPD and 1784 with exacerbations (including deaths).

OUTCOME MEASURES

Exacerbations with demographic, economic and environmental local community determinants were retrieved. Conditional logistic regression for matched pairs was used to evaluate the local community determinants of COPD exacerbations among patients with COPD.

RESULTS

The overall prevalence of COPD in the population of elderly patients registered in primary healthcare clinic clinics in Lodz province in 2016 was 3.65%, 95% CI (3.60% to 3.70%) and the prevalence of exacerbations was 10.35%, 95% CI (9.89% to 10.80%). The high number of consultations in primary care clinics was associated with higher risk of COPD exacerbations (p=0.0687).High-income patients were less likely to have exacerbations than low-income patients (high vs low OR 0.601, 95% CI (0.385 to 0.939)). The specialisation of the primary care physician did not have an effect on exacerbations (OR 1.076, 95% CI (0.920 to 1.257)). Neither the forest cover per gmina (high vs low OR 0.897, 95% CI (0.605 to 1.331); medium vs low OR 0.925, 95% CI (0.648 to 1.322)), nor location of gmina (urban vs urban-rural OR 1.044; 95% CI (0.673 to 1.620)), (rural vs urban-rural OR 0.897, 95% CI (0.630 to 1.277)) appears to influence COPD exacerbations.

CONCLUSIONS

Big Data statistical analysis facilitated the evaluation of the prevalence and determinants of COPD exacerbation in the elderly residents of Lodz province, Poland.Modification of identified local community determinants may potentially decrease the number of exacerbations in elderly patients with COPD.

[Respiratory Disease in the Era of Big Data]

One of the key elements of medicine in the second decade of the 21st century is the exponential growth of patient-produced information, due not only to the transition to the digitization of medical records, but also to the emergence of new sources of information and the capacity for analysis and interpretation of existing ones. The amount of medical information is expected to double every 2 years, which means that there will be 50 times more information available in 2020 than in 2011. In this setting, these large amounts of data or «big data» must be properly managed to implement new initiatives that improve the diagnosis, treatment, and prognosis of patients on the path to personalized medicine.The concept of personalization or precision medicine is of special interest in chronic respiratory disease. In recent years, research in entities such as asthma, COPD, cancer, or SAHS has focused on the identification of genomic, molecular, metabolic, and protein changes (biomarkers). Big data analysis tools can be used to move on from models based on the mean response to treatment, which are suboptimal for most patients, to focus on the individualized response. Part of this journey involves systems medicine, which also integrates clinical and population data to provide a multidimensional view of the disease and help identify causal associations that are usually only evident on big data analysis.