Ciencia y Salud (Jun 2024)

Adherence, burden, and morbidity of chronic diseases in an outpatient clinic: A-CaMo I

  • Ramón Romano,
  • Juan Espaillat,
  • Gabriela Anzani,
  • Arthur Leyba,
  • Isabella Gutiérrez,
  • Génesis Vegazo,
  • Michael Richardson,
  • Laura Reyes,
  • Laura Díaz,
  • Shamelle López,
  • Sharon Calderato,
  • Nadja García,
  • Rosaliz Piña,
  • Erika Alcántara

DOI
https://doi.org/10.22206/cysa.2024.v8i2.3099
Journal volume & issue
Vol. 8, no. 2

Abstract

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Introduction: Chronic non-communicable diseases (NCDs) are a significant global health challenge due to their prolonged duration and varied progression rates, leading to increased noncompliance, especially in developing nations. Pharmacological adherence, defined by WHO, is crucial for maintaining patients' quality of life and reducing morbidity, yet it remains inadequate, with about 50% non-adherence in developed countries, 30% of which is unintentional. Understanding disease burden is vital, but research on medication adherence, burden, and morbidity in the Dominican Republic and Latin American countries is lacking, necessitating comprehensive studies. Objectives: Ascertaining the degree of pharmaceutical adherence, disease burden, and morbidity amongst individuals with chronic illnesses were the study’s primary endpoints. Methodology: The project was a cross-sectional, prospective study that examined the sociodemographic data, past medical history, and medication regimens of a sample of 284 patients attending an outpatient clinic. Patients were selected using convenience sampling, to be later screened and interviewed after consultation for any of the diseases present on the MAR-Scale or the DBMA questionnaires. The screening sought only those individuals who met inclusion criteria (> 18 years old, diagnosed with a disease present on either scale) and did not meet exclusion criteria (not being able to fill the questionnaire due to language barrier). Data collected was stored using the KoboToolBox program and later summarized with mean and standard deviation for further processing using STATA BE. Statistical tests were programmed with an alpha of 5%, 95% CI, and p < 0.05 for statistical significance. Results: The sample, comprising 133 individuals, had a mean age of approximately 58.4 years, with a majority of female participants. Most participants were married, Dominican, and of Hispanic Latino ethnicity, with Christianity being the predominant religion. Regarding past medical history, while a substantial portion had no prior respiratory or cardiovascular ailments, diabetes mellitus was prevalent, indicating potential implications for current health status and treatment adherence. Adherence, measured by daily and weeklyscores, ranged from 1.0 to 3.8, with the burden score per patient averaging 50.1 and per disease averaging 2.6. The analysis revealed that 16.9% of participants were monomorbid, while 83.1% were multimorbid, showcasing the complexity of health conditions within the cohort. Conclusion: The study's key results reveal a significant portion of patients without a history of respiratory or cardiovascular diseases, suggesting a relatively healthy baseline. However, a notable proportion had diabetes, potentially impacting their current health status and treatment adherence. Furthermore, the study delves into factors influencing adherence, burden levels, and reasons for nonadherence. Findings indicate unmarried patients and those with lower education levels tend to exhibit higher burden levels and lower adherence scores. Mental health conditions like depression or anxiety, osteoporosis, and heart failure are associated with elevated burden levels. The study also assesses the reliability of adherence and burden measurement tools, emphasizing the importance of considering population variability in interpreting results. Limitations include challenges in patient selection and data collection, particularly regarding patients with multimorbidity. Overall, the study highlights the need for comprehensive exploration of adherence, burden, and morbidity to predict disease control, progression, and patient quality of life effectively in future research endeavors.

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