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Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

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Leveraging Digital Infrastructure for Data Analysis: An Example in Bariatric Surgery.

John Hagen¹, Lazar Klein², Ethan Miller³

¹Chief of Surgery, and Medical Director of Bariatrics at the Humber River Hospital, as well as a faculty member of the University of Toronto's MIS fellowship training program. He can be reached by email at JHagen@hrh.ca.

Healthcare Quarterly (Toronto, Ont.)

|April 26, 2020

Summary

This summary is machine-generated.

Electronic medical records (EMRs) offer valuable insights into bariatric surgery outcomes. Age, baseline BMI, and diabetes predict weight loss six months post-surgery, improving patient care.

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Area of Science:

Health Informatics
Medical Data Analysis
Surgical Outcomes Research

Background:

Digitalization of healthcare information enables hospitals to analyze disease and management patterns.
Electronic medical record (EMR) data holds potential for generating clinical insights.
Bariatric patient data was utilized to explore EMR data capabilities.

Purpose of the Study:

To extract EMR data for bariatric patients.
To identify predictive factors for post-bariatric surgery weight loss.

Main Methods:

Retrospective cohort study of 502 bariatric surgery patients (January 2018 - April 2019).
Multiple linear regression analysis.
Examined age, baseline BMI, comorbidities, and mental health disorders as predictors of weight loss at 6 months.

Main Results:

Age, baseline BMI, and diabetes were significantly associated with weight loss 6 months post-surgery.
Specifically, older age and higher baseline BMI predicted greater weight loss, while diabetes showed a positive association.
Statistical significance was observed for age (p=0.005), baseline BMI (p<0.0001), and diabetes (p=0.007).

Conclusions:

EMRs are a rich data source for clinical insights.
Data-driven insights from EMRs can enhance patient care strategies.
Further research can leverage EMR data for improved bariatric surgery management.