Real-world patient data: Can they support decision making and patient engagement?

The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century

As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging as a key force for transformation. This review is motivated by the urgent need to harness AI's potential to mitigate these issues and aims to critically assess AI's integration in different healthcare domains. We explore how AI empowers clinical decision-making, optimizes hospital operation and management, refines medical image analysis, and revolutionizes patient care and monitoring through AI-powered wearables. Through several case studies, we review how AI has transformed specific healthcare domains and discuss the remaining challenges and possible solutions. Additionally, we will discuss methodologies for assessing AI healthcare solutions, ethical challenges of AI deployment, and the importance of data privacy and bias mitigation for responsible technology use. By presenting a critical assessment of AI's transformative potential, this review equips researchers with a deeper understanding of AI's current and future impact on healthcare. It encourages an interdisciplinary dialogue between researchers, clinicians, and technologists to navigate the complexities of AI implementation, fostering the development of AI-driven solutions that prioritize ethical standards, equity, and a patient-centered approach.

Adoption of Patient-Reported Outcomes by Health Systems and Physician Practices in the USA

BACKGROUND

Patient-reported outcome measures (PROs) can help clinicians adjust treatments and deliver patient-centered care, but organizational adoption of PROs remains low.

OBJECTIVE

This study examines the extent of PRO adoption among health systems and physician practices nationally and examines the organizational capabilities associated with more extensive PRO adoption.

DESIGN

Two nationally representative surveys were analyzed in parallel to assess health system and physician practice capabilities associated with adoption of PROs of disability, pain, and depression.

PARTICIPANTS

A total of 323 US health system and 2,190 physician practice respondents METHODS: Multivariable regression models separately estimated the association of health system and physician practice capabilities associated with system-level and practice-level adoption of PROs.

MAIN MEASURES

Health system and physician practice adoption of PROs for depression, pain, and disability.

KEY RESULTS

Pain (50.6%) and depression (43.8%) PROs were more commonly adopted by all hospitals and medical groups within health systems compared to disability PROs (26.5%). In adjusted analyses, systems with more advanced health IT functions were more likely to use disability (p<0.05) and depression (p<0.01) PROs than systems with less advanced health IT. Practice-level advanced health IT was positively associated with use of depression PRO (p<0.05), but not disability or pain PRO use. Practices with more chronic care management processes, broader medical and social risk screening, and more processes to support patient responsiveness were more likely to adopt each of the three PROs. Compared to independent physician practices, system-owned practices and community health centers were less likely to adopt PROs.

CONCLUSIONS

Chronic care management programs, routine screening, and patient-centered care initiatives can enable PRO adoption at the practice level. Developing these practice-level capabilities may improve PRO adoption more than solely expanding health IT functions.

Den Patienten wirklich verstehen lernen: Real-world-Evidenz aus der „patient journey“

Hintergrund

Die COVID-19-Pandemie („coronavirus disease 2019“) hat die Bedeutung von Real World Data (RWD) im klinischen Alltag unterstrichen und die fatalen Folgen von längst existierenden Problemen wie Lücken in der Primärdatenerfassung, Hürden bei der Auswertung von Patientendaten sowie erschwertem Patientendatenaustausch zwischen verschiedenen Einrichtungen nochmal deutlich gemacht. Darüber hinaus haben Entwicklungen weg von einem paternalistischen hin zu einem partnerschaftlichen Modell der Arzt-Patienten-Beziehung sowie die zunehmende Digitalisierung unser Verständnis von Gesundheitsversorgung geprägt, das Thema der Patientenautonomie und Selbstwirksamkeit in den Vordergrund gebracht und den Bedarf an innovativen, patientenzentrierten Lösungsansätzen verdeutlicht.

Methoden

Wir nutzen die „patient journey“ als theoretisches Konstrukt, entlang dessen wir die Sammlung von verschiedenen Typen von RWD, ihre Bedeutung und Umgang damit beschreiben.

Schlussfolgerung

Die Abbildung der „patient journey“ in Verbindung mit der Nutzung eines einheitlichen Datenstandards kann zur Erfassung von Primärdaten im Gesundheitswesen führen, die von allen medizinischen Behandlungseinrichtungen genutzt werden können. Dies wird den Austausch von Daten zwischen Einrichtungen erleichtern. Darüber hinaus könnte die fortlaufende Auswertung von patientenberichteten Ereignissen als Standard in der klinischen Routine die Patientenautonomie stärken und die Behandlung optimieren. Zusammenfassend lässt sich sagen, dass der Behandlungserfolg, das Gesamtüberleben und das Wohlbefinden der Patienten durch die Schaffung einer gemeinsamen Datensprache und eines ganzheitlichen, menschenzentrierten Ansatzes verbessert werden können.