International Journal of Health Sciences

Population Health Management: Leveraging it for Better Patient Outcome’s

Ankur Tak — Sun, 07 Apr 2024 00:00:00 +0300

Purpose: The primary aim is to investigate how IT integration within PHM frameworks significantly improves patient care by enabling proactive health interventions and fostering a comprehensive understanding of population health trends.

Methodology: Utilizing a mixed-method approach, the study evaluates various IT tools and technologies ranging from EHRs to AI-driven analytics within PHM contexts. The research methodology includes data analysis through Python’s scikit-learn and pandas libraries, emphasizing model training, evaluation, and application areas in real healthcare settings.

Findings: Results indicate that IT advancements, particularly EHRs, telehealth, and AI predictive analytics, markedly enhance the effectiveness of PHM. Key outcomes include improved chronic disease management, more effective preventive healthcare measures, and heightened patient engagement. Moreover, IT facilitates optimal resource allocation and operational efficiency within healthcare systems.

Unique Contribution to Theory, Policy, and Practice: This study contributes to healthcare literature by providing empirical evidence on the transformative role of IT in PHM. It offers a theoretical framework for integrating IT solutions in healthcare strategies, informing policy by highlighting the necessity for interoperability standards, and suggesting practical guidelines for healthcare practitioners to implement technology-driven PHM effectively.

Comprehending Qualifying Payment Amount (QPA) and the No Surprise Act in Healthcare

Nithin Narayan Koranchirath — Fri, 22 Mar 2024 00:00:00 +0300

Purpose: This article investigates the No Surprise Act, a pivotal piece of legislation designed to protect consumers from unexpected out-of-network healthcare charges, emphasizing the Qualifying Payment Amount (QPA) mechanism.

Methodology: Through a comprehensive literature review, analysis of legislative texts, and examination of case studies, this study elucidates the Act's origins, objectives, and operational framework of the QPA. It also explores the challenges of implementing the Act, its impact on various stakeholders (patients, healthcare providers, and insurers), and the broader implications for the U.S. healthcare system. Despite its intentions to curb surprise billing practices, the No Surprise Act and its QPA component face several implementation challenges, including administrative burdens, disputes over payment calculations, and unintended consequences on insurance premiums and healthcare market dynamics. This article leverages recent data, expert opinions, and comparative analysis with other healthcare models to provide a nuanced evaluation of the Act's effectiveness and areas for improvement.

Findings: The findings suggest that while the No Surprise Act represents a significant step forward in patient financial protection, ongoing adjustments and policy refinements are essential for achieving its intended outcomes without compromising the sustainability of healthcare providers and insurers.

Unique Contributor to Theory, Policy and Practice: Study and policy recommendations aims to contribute to the ongoing dialogue and efforts to enhance patient protection and healthcare affordability in the U.S., ensuring that the No Surprise Act lives up to its promise and potential..

Unveiling the Impact of Demographic Factors on Disease Survival: A Multifaceted Examination across Diverse Medical Conditions

Lakshmi Sahitya Cherukuri , Rohan Singh Rajput , Shantanu Neema — Sun, 17 Mar 2024 00:00:00 +0300

Purpose: In this research, we studied the intricate interplay between demographic indicators and survival rates across various diseases, aiming to address the gap in comprehensive analyses across multiple conditions.

Methodology: Drawing from a dataset encompassing 9105 critically ill patients from five medical centers in the United States [1], admitted between1989-1991 and 1992-1994, our analysis spans eight disease categories. Leveraging techniques such as Cox-proportional hazard models and machine learning algorithms, we explore the influence of socio-economic status, gender, race, and education on survival outcomes.

Findings: Our findings underscore significant demographic disparities in disease survivability, with ethnicity, gender, and education level showing varying impacts across different medical conditions. Notably, Asians exhibit lower hazards for certain diseases but higher hazards for others, while females demonstrate better survival probabilities compared to males. Moreover, individuals with higher education levels tend to have slightly increased hazards for certain conditions.

Unique Contribution to Theory, Practice, and Policy: The call for comparative analyses across multiple diseases using comprehensive datasets marks a pivotal shift in research strategy. It aims to highlight the interplays and shared risk factors across diseases, contributing significantly to the advancement of theoretical frameworks, the refinement of healthcare practices, and the shaping of informed public health policies. This approach seeks to bridge a critical gap in the literature, offering a foundation for interventions designed to enhance disease management and improve population health outcomes comprehensively.

Deciphering the Genomic Complexity of Acromesomelic Dysplasia Type Maroteaux: Insights from a Consanguineous Pakistani Family

Sat, 06 Apr 2024 00:00:00 +0300

Purpose: This study delves into the genetic basis of Acromesomelic Dysplasia (AMD), a rare skeletal disorder, particularly focusing on the Maroteaux type within a consanguineous Pakistani family. The purpose is to explore the genetic landscape beyond known mutations and understand the underlying causes of AMD.

Methodology: A comprehensive approach was adopted, combining detailed clinical examinations with advanced genomic methodologies. Ethical clearance was obtained, and pedigree design facilitated the identification of affected individuals. Molecular techniques including DNA extraction and linkage analysis were conducted to investigate known AMD-related genes such as NPR2, BMPR1B, GDF5, GALNS, GLB1, and GHR. Whole-genome sequencing was emphasized despite financial constraints to uncover potential novel genetic loci associated with AMD.

Findings: Despite exhaustive analysis, no mutations in known AMD-related genes were identified within the studied family. Linkage analysis did not correlate with any known genetic loci, suggesting the presence of unidentified genetic elements contributing to AMD. Autosomal recessive inheritance was confirmed through pedigree and molecular scrutiny, highlighting the complexity of AMD genetics.

Unique Contribution to Theory, Policy and Practice: This research underscores the importance of employing advanced genomic strategies, such as whole-genome sequencing, in decoding rare genetic disorders like AMD. By revealing the limitations of current diagnostic approaches and advocating for collaborative efforts and resource pooling, this study contributes to the advancement of genetic counseling, therapeutic interventions, and precision medicine in rare genetic disorders.

Addressing Health Disparities using Social Determinants of Health: A Descriptive Analytics Approach

Bharath Srinivasaiah — Wed, 20 Mar 2024 00:00:00 +0300

Purpose: This paper explores Social Determinants of Health (SDOH) data and its implications using descriptive data analytics. The analysis aims to help healthcare organizations understand the trends and impact on the industry and develop strategies to resolve disparities and eventually reduce healthcare costs.

Methodology: This paper uses descriptive data analytics to analyze Social Determinants of Health (SDOH) data and its implications. The study focuses on the Centers for Disease Control and Prevention's (CDC) five critical areas of SDOH: healthcare quality and access, education quality and access, economic stability, social and economic context, and built and neighborhood environment.

Findings: Health equity remains a significant challenge in the world and the United States, with persistent inequalities and injustice among different populations. Failure to address health equity issues could lead to social problems, including violent crimes, alcohol, and substance abuse, and potentially a global pandemic, which could significantly impact healthcare systems and increase costs. According to a report published by Deloitte, inequities in the United States cost more than 300 billion dollars in 2022. If not addressed, they could account for more than a trillion dollars in annual spending by 2040. Social Determinants of Health (SDOH) are critical in providing health equity and reducing disparities.

Unique Contribution to Theory, Practice, and Policy: Understanding the implications and trends of SDOH data is crucial in developing targeted strategies to achieve health equity for all. Healthcare organizations can use this analysis's findings to establish policies and practices that address social determinants of health and reduce disparities. This, in turn, will help improve overall health outcomes and reduce healthcare costs.