Advancing Patient-Centered Care: A Nationwide Analysis of Hospital Efficiency and Morbidity Using Innovative Propensity Score Techniques.

Abstract

Introduction The patient-centered care model emphasizes patient autonomy in recovery, acknowledging each individual's unique journey. Despite challenges in the healthcare system, this model has gained traction nationwide. Advances in healthcare technology have highlighted obstacles to independent decision-making. This study addresses these issues by emphasizing the need for consistent access to health information, which is crucial for empowering patients. We aim to proactively identify information gaps and propose new insights for better data precision and synchronization protocols. Our analysis of nationwide hospital length of stay (LOS) data demonstrates data-driven interventions tailored to patients' needs, aiming to improve the hospital experience and reduce care fragmentation. Methods We examined the complex nature of hospital LOS and various variables across nationwide healthcare settings using CMS data from 2011 to 2021. To enhance our national findings, we incorporated a local perspective by analyzing LOS data from Arrowhead Regional Medical Center (ARMC) and its associated diagnosis-related groups (DRGs). We employed a propensity score to adjust for variables and proactively drive realistic predictions of hospital outcomes. This methodological approach emphasizes the importance of using tools that can be scaled from localized settings to a broader national context. Furthermore, our study highlights the critical need for continuous quality assessment of hospital LOS. This includes measuring LOS and developing innovative tools capable of predicting, analyzing, intervening, and prompting actions based on insights gained from data analysis. The study aims to achieve several core objectives by integrating these components: enhancing patient empowerment through improved communication, refining LOS assessment through innovative techniques, and developing predictive tools to inform clinical practice and policy. Ultimately, this research contributes to a more patient-centered approach to managing inpatient care, improving patient outcomes and satisfaction. Results Our study aspires to transform three pivotal domains that can enhance patient autonomy, optimize hospital recovery, and elevate the overall experience. First, the cost of care reveals that prolonged hospital stays and escalating expenses are often linked to more severe health consequences. Second, our analysis uncovers the intricate relationship between hospital outcomes, such as mortality and readmissions, showing that shorter hospital stays can diminish patients' risk of complications. However, we must tread carefully, as this approach may lead to premature discharges. Lastly, providers can gain more precise insights into these interconnected outcomes by leveraging data tools such as propensity scores. We advocate for the dissolution of care fragmentation through robust health information exchange (HIE), and the adoption of innovative strategies such as blockchain and advanced machine learning (ML) techniques that rise to contemporary medicine and adapt to the growing patient needs.