Purpose This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in ...healthcare settings. Design/methodology/approach The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized. Findings Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords. Research limitations/implications The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future. Practical implications The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services. Originality/value By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.
Healthcare is a key element of the state's national security. The effectiveness of the healthcare industry functioning is a relevant object of research today, especially after the outbreak of the ...COVID-19 pandemic, during which this sector globally demonstrated its potential and problems. It necessitates a comprehensive assessment of the competitiveness of the healthcare industry and institutions as an important component of their effective management. The objects of the research are public healthcare and institutions as service organizations. The purpose is to develop a scientific-methodical approach to managing the competitiveness in the country’s healthcare industry. That is, the research is aimed at developing a market-oriented competitiveness management mechanism for public healthcare institutions. The construction of the mechanism is based on the analysis of statistical data on Ukrainian healthcare institutions according to indicators based on the "7P" marketing concept. Clustering methods, an integral indicator of competitiveness, and multidimensional methods of taxonomic analysis were also used for assessing the level of competitiveness of healthcare institutions and the comparative effectiveness of alternative measures to increase it.
Allied Healthcare encompasses various professions involved in diagnosing, evaluating, and preventing diseases and disorders. Allied Healthcare Institutes (AHIs) provide education and training in ...these professions. However, there is currently a lack of explicit guidelines for ensuring quality excellence in AHIs. This narrative review aims to address this gap by examining existing literature on quality assurance in AHIs and proposing a conceptual framework that outlines essential components for establishing a high-quality AHI. A comprehensive search of PubMed and Google Scholar electronic databases yielded 86 relevant articles, which were analyzed and grouped into Nine themes related to the study's objectives. These themes include leadership in AHIs, student selection and support, teaching quality, curriculum development, research opportunities, stakeholder involvement, quality improvement initiatives, the impact of accreditation/certification, and physical facilities. Based on the review, the study presents 33 carefully formulated recommendations. By implementing these guidelines, policymakers and those interested in establishing AHIs can create institutions that promote the acquisition of new knowledge and skills, foster research and development, and provide excellent educational resources.
Primary healthcare institutions face limitations in medical resources, leading to concerns from patients and their families regarding the quality of medical services, resulting in complaints against ...these institutions. This study aims to analyze the causes of complaints and implement improvement measures to enhance the service quality of primary healthcare institutions, increase satisfaction among patients and their families, and reduce the number of complaints. Relevant data were collected, and verified complaints were categorized based on departments, administrative office, and category. Pearson Chi-square test, Spearman correlation analysis, as well as univariate logistic regression were employed to analyze factors influencing patient satisfaction. A complaint-handling process was established, and regulations pertaining to complaints were formulated. Pearson Chi-square test results indicated a significant correlation between satisfaction and departments (P = .016) and administrative office (P = .022). Spearman correlation analysis revealed a significant correlation between satisfaction and departments (ρ = 0.157, P = .017) and administrative office (ρ = 0.151, P = .021). Univariate logistic regression analysis demonstrated a significant correlation between satisfaction and other related complaints in administrative office (OR = 3.321, 95% CI = 1.196-9.218, P = .021). Complaints related to departments and administrative offices are significantly correlated with satisfaction. After the implementation of a complaint management system in primary healthcare institutions, there is a notable improvement in service quality, enhanced patient experience, increased satisfaction, and a reduction in hospital complaints.
We develop a lean readiness framework and an assessment methodology to quantify the readiness of healthcare institutions for implementing lean. We use stakeholder theory and work with a lean ...implementation team responsible for process improvement in a healthcare group to develop the framework. The framework uses fuzzy based input derived from the stakeholders of the healthcare institution to generate an overall ranking through ideal solution technique. The assessment method derives input from the readiness scores shared by various stakeholders. The ranking suggests future improvement areas to prepare the healthcare institution for a lean implementation project. We provide an alternative perspective of assessing the lean readiness of healthcare institutions before beginning a lean implementation project for both researchers and practitioners. Our research is the first to develop a lean readiness framework for healthcare institutions and demonstrate it using an assessment technique.
•We propose a stakeholder-based lean readiness framework for healthcare institution.•We develop a procedure for assessing the readiness of a healthcare institution.•We report experiences of deploying the framework in a US healthcare institution.•The readiness of stakeholders is quantified and ranked with future recommendations.•We discuss a lean readiness laboratory initiative for testing pilot lean projects.
Understanding location-specific travel modes and acceptable travel time to primary healthcare institutions across large regions is important for measuring accessibility and allocation of health ...resources. However, few studies have either focused on such analysis or provided efficient methods.
We developed a framework to understand the diversity of travel modes and acceptable travel time across large regions and chose Inner Mongolia Autonomous Region, China as the study region. Information on health-seeking travel behaviors to primary healthcare institutions was collected using a simple online questionnaire, based on which, Bayesian statistical models were developed and high-resolution maps for travel mode selection and acceptable travel time were produced.
Age, gender, occupation, travel time to the nearest urban center, and nighttime light had significant associations with the choice of travel modes. And age, gender, occupation, travel mode, and nighttime light showed significant relationships with levels of the acceptance of travel time. The proportions of travel modes and levels of acceptable travel time show heterogeneous across the study region. Most people chose to walk or travel by bus, with population weighted average proportions 40.59% and 21.11% across the study region, and people in the southeastern part were less tolerable for longer travel time than those in other regions.
This study provided a framework to estimate travel modes and acceptable travel time across large regions. The outcomes can provide important information on the assessment of accessibility to primary healthcare services and health resource allocation in Inner Mongolia.
•We developed a framework to map travel modes and acceptable travel time to primary healthcare institutions in large regions.•Several factors were identified significantly associated with the choice of travel modes and the acceptable travel time.•High-resolution maps for travel mode selection and acceptable travel time in Inner Mongolia were produced.
Background: In the coronavirus disease (COVID-19) era, healthcare delivery toward patient-centered orientation has gone a paradigm shift. High levels of adherence to treatment and recommended ...prevention are usually the outcome of perceived patient satisfaction. Aims: The present study aimed to assess patient satisfaction levels in the COVID-19 era and explore its determinants. Settings and Design: A cross-sectional study from outpatient department of a tertiary care hospital in Jammu, UT of J&K, India. Materials and Methods: The present cross-sectional study was carried out in outpatient department of a tertiary care hospital in the Jammu district. A total of 220 patients were interviewed using consecutive sampling. The tool used to assess patient satisfaction was the patient satisfaction questionnaire-18 (PSQ-18). Statistical Analysis: Data were analyzed using Statistical Package for Social Sciences (SPSS) version 20.0. Tests of significance used were ANOVA and t-test. Results: The overall mean satisfaction score was found to be 2.91 ± 0.17 and it was highest in the communication domain (3.12 ± 1.50), whereas it was lowest in the accessibility and convenience domain (2.73 ± 1.17). Except for religion, which was found to be statistically significant (P < 0.05) with overall mean satisfaction score, other sociodemographic variables (occupation, marital status, and monthly family income) were found to be statistically insignificant (P > 0.05). Conclusions: Out of the seven subscales of patient satisfaction, results revealed high scores for communication and financial aspects. Only religion as a demographic variable was found to be significantly associated with patient satisfaction scores. There is a need to improvise the healthcare services in this COVID-19 era in such a manner so that we can contribute to better patient trust leading to a positive influence on health outcomes.
Dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare institutions affects both patients and health-care workers (HCW), as well as the institutional capacity to ...provide essential health services. Here, we investigated an outbreak of SARS-CoV-2 in a "non-COVID-19" hospital ward unveiled by massive testing, which challenged the reconstruction of transmission chains. The contacts network during the 15-day period before the screening was investigated, and positive SARS-CoV-2 RNA samples were subjected to virus genome sequencing. Of the 245 tested individuals, 48 (21 patients and 27 HCWs) tested positive for SARS-CoV-2. HCWs were mostly asymptomatic, but the mortality among patients reached 57.1% (12/21). Phylogenetic reconstruction revealed that all cases were part of the same transmission chain. By combining contact tracing and genomic data, including analysis of emerging minor variants, we unveiled a scenario of silent SARS-CoV-2 dissemination, mostly driven by the close contact within the HCWs group and between HCWs and patients. This investigation triggered enhanced prevention and control measures, leading to more timely detection and containment of novel outbreaks. This study shows the benefit of combining genomic and epidemiological data for disclosing complex nosocomial outbreaks, and provides valuable data to prevent transmission of COVID-19 in healthcare facilities.
PDF
