scholarly journals Heterogeneous effects of hospital competition on inpatient expenses: an empirical analysis of diseases grouping basing on conditions’ complexity and urgency

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Liyong Lu ◽  
Xiaojun Lin ◽  
Jay Pan
Keyword(s):  
Regression Model ◽  
Patient Flow ◽  
Statistical Significance ◽  
Healthcare Delivery ◽  
Hospital Competition ◽  
Process Of Care ◽  
Healthcare Delivery System ◽  
Discharge Data ◽  
Heterogeneous Effects ◽  
Hospital Administrative

Abstract Background Multiple pro-competition policies were implemented during the new round of healthcare reform in China. Differences in conditions’ complexity and urgency across diseases associating with various degrees of information asymmetry and choice autonomy in the process of care provision, would lead to heterogeneous effects of competition on healthcare expenses. However, there are limited studies to explore it. This study aims to examine the heterogeneous effects of hospital competition on inpatient expenses basing on disease grouping according to conditions’ complexity and urgency. Methods Collecting information from discharge data of inpatients and hospital administrative data of Sichuan province in China, we selected representative diseases. K-means clustering was used to group the selected diseases and Herfindahl-Hirschman Index (HHI) was calculated based on the predicted patient flow to measure the hospital competition. The log-linear multivariate regression model was used to examine the heterogeneous effects of hospital competition on inpatient expenses. Results We selected 19 representative diseases with significant burdens (more than 1.1 million hospitalizations). The selected diseases were divided into three groups, including diseases with highly complex conditions, diseases with urgent conditions, and diseases with less complex and less urgent conditions. For diseases with highly complex conditions and diseases with urgent conditions, the estimated coefficients of HHI are mixed in the direction and statistical significance in the identical regression model at the 5% level. For diseases with less complex and less urgent conditions, the coefficients of HHI are all positive, and almost all of them significant at the 5% level. Conclusions We found heterogeneous effects of hospital competition on inpatient expenses across disease groups: hospital competition does not play an ideal role in reducing inpatient expenses for diseases with highly complex conditions and diseases with urgent conditions, but it has a significant effect in reducing inpatient expenses of diseases with less complex and less urgent conditions. Our study offers implications that the differences in condition’s complexity and urgency among diseases would lead to different impacts of hospital competition, which would be given full consideration when designing the pro-competition policy in the healthcare delivery system to achieve the desired goal.

Variability in Surgical Caseload and Access to Intensive Care Services

2003 ◽  
Vol 98 (6) ◽  
pp. 1491-1496 ◽  
Author(s):  
Michael L. McManus ◽  
Michael C. Long ◽  
Abbot Cooper ◽  
James Mandell ◽  
Donald M. Berwick ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Delivery System ◽  
Care Delivery ◽  
Patient Flow ◽  
Healthcare Delivery ◽  
Hospital Data ◽  
Healthcare Delivery System ◽  
Care Services

Background Variability in the demand for any service is a significant barrier to efficient distribution of limited resources. In health care, demand is often highly variable and access may be limited when peaks cannot be accommodated in a downsized care delivery system. Intensive care units may frequently present bottlenecks to patient flow, and saturation of these services limits a hospital's responsiveness to new emergencies. Methods Over a 1-yr period, information was collected prospectively on all requests for admission to the intensive care unit of a large, urban children's hospital. Data included the nature of each request, as well as each patient's final disposition. The daily variability of requests was then analyzed and related to the unit's ability to accommodate new admissions. Results Day-to-day demand for intensive care services was extremely variable. This variability was particularly high among patients undergoing scheduled surgical procedures, with variability of scheduled admissions exceeding that of emergencies. Peaks of demand were associated with diversion of patients both within the hospital (to off-service care sites) and to other institutions (ambulance diversions). Although emergency requests for admission outnumbered scheduled requests, diversion from the intensive care unit was better correlated with scheduled caseload (r = 0.542, P < 0.001) than with unscheduled volume (r = 0.255, P < 0.001). During the busiest periods, nearly 70% of all diversions were associated with variability in the scheduled caseload. Conclusions Variability in scheduled surgical caseload represents a potentially reducible source of stress on intensive care units in hospitals and throughout the healthcare delivery system generally. When uncontrolled, variability limits access to care and impairs overall responsiveness to emergencies.

scholarly journals Clinical management: quality and safety of interdisciplinary obstetric gynaecological care in a health care institution

2018 ◽  
Vol 2 (1) ◽  
pp. 13
Author(s):  
María Guima Reinoso Huerta ◽  
Luis Alberto Núñez Lira
Keyword(s):  
Regression Model ◽  
Clinical Management ◽  
Statistical Significance ◽  
Continuous Process ◽  
Health Sector ◽  
Primary Objective ◽  
Public Hospitals ◽  
Quality And Safety ◽  
Process Of Care ◽  
Theoretical Significance

Safe surgery in public hospitals is a primary objective for the achievement of services-safety and -quality provided in the health sector. Within this framework, the research aimed to establish how clinical management affects the quality and safety of interdisciplinary obstetric gynecological care received by the user of a Lima public hospital. The population consisted of 150 health professionals: doctors, obstetricians, nurses and technicians. The instruments applied in the data collection were three questionnaires, the results of which indicate that clinical management is a tool of continuous process of quality improvement directly linked to the moral commitment of health institutions to safeguard the quality and safety of the care provided to the user from a right to health context. The statistical significance of the regression model proposed to express the analogy between clinical management and quality was 0.056, higher than the theoretical significance. However, the statistical significance of the regression model proposed to expose the analogy between Clinical Management and Safety was 0.019, lower than the theoretical significance. It is concluded that hospital management is a complex process, which requires the intervention of all actors involved in the process of care to assume the commitment to control, monitor and improve the risks that may affect the quality and safe environment of the services provided to the patient.

Prerequisites to support high-quality clinical trials in children and young people

2020 ◽  
pp. archdischild-2019-318677
Author(s):  
Steven Hirschfeld ◽  
Florian B Lagler ◽  
Jenny M Kindblom
Keyword(s):  
Clinical Trials ◽  
Healthcare Delivery ◽  
Paediatric Population ◽  
Ecosystem Functions ◽  
Healthcare Delivery System ◽  
High Quality ◽  
Children And Young People ◽  
The Right ◽  
Support Decision Making

Children have the right to treatment based on the same quality of information that guides treatment in adults. Without the proper evaluation of medicinal products and devices in paediatric clinical trials that are designed to meet the rigorous standards of the competent authorities, children are discriminated from advances in medicine. There are regulatory, scientific and ethical incentives to address the knowledge gap regarding efficacy and safety of medicines in the paediatric population. High-quality clinical trials involving children of all ages can generate data that will ultimately close the knowledge gaps and support decision making.For clinical trials that enrol children, the needs are specialised and often resource intensive. Prerequisites for successful paediatric clinical trials are personnel with training in both paediatrics and neonatology and expertise in clinical trials in these populations. Moreover, national and international networks for efficient collaboration, dissemination of information, and sharing of resources and expertise are also needed, together with competent, efficient and high-quality local infrastructure with effective processes. Monitoring and oversight bodies with the relevant competence, including expertise in paediatrics, is also an important prerequisite for paediatric clinical trials. Compromise in any of these components will compromise the downstream results.This paper discusses the structures and competences needed in order to perform effective, high-quality paediatric clinical trials with the ultimate goal of better medicines and treatments for children. We propose a model of examining the process as a series of components that each has to be optimised, then all the components are actively optimised to function together as an ecosystem, and the resulting ecosystem functions well with the general research system and the healthcare delivery system.

The healthcare delivery system: an overview

2017 ◽  
Author(s):  
Jan Abel Olsen
Keyword(s):  
Delivery System ◽  
Chronic Care ◽  
Tertiary Care ◽  
Healthcare Delivery ◽  
Healthcare Delivery System ◽  
Care Level ◽  
Primary Care Level ◽  
Internal Markets ◽  
System A ◽  
Policy Challenge

This chapter provides an overview of the healthcare delivery system. A figure illustrates how six different parts of the system relate to each other. The primary care level plays a key role in many countries by representing the gate, in which referrals to secondary care are being made. Tertiary care is principally of two types depending on patients’ prognosis: chronic care or rehabilitation. In addition to the three care levels, there are two parts with quite different roles: pharmacies provide pharmaceuticals, and sickness benefit schemes compensate the sick for their income losses. A recurrent policy challenge is to make each provider level take into account the resource implications of their isolated decisions outside of their own budgets. A brief discussion is included on the scope for ‘internal markets’.

How Research Will Adapt to HIPAA: A View from Within the Healthcare Delivery System

2002 ◽  
Vol 28 (4) ◽  
pp. 491-502
Author(s):  
Mary L. Durham
Keyword(s):  
Health Information ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
The United States ◽  
Personal Health Information ◽  
Personal Health ◽  
Business Associations ◽  
Electronic Information ◽  
Healthcare Delivery System ◽  
Institutional Review

While the new Health Insurance Privacy and Accountability Act (HIPAA) research rules governing privacy, confidentiality and personal health information will challenge the research and medical communities, history teaches us that the difficulty of this challenge pales in comparison to the potential harms that such regulations are designed to avoid. Although revised following broad commentary from researchers and healthcare providers around the country, the HIPAA privacy requirements will dramatically change the way healthcare researchers do their jobs in the United States. Given our reluctance to change, we risk overlooking potentially valid reasons why access to personal health information is restricted and regulated. In an environment of electronic information, public concern, genetic information and decline of public trust, regulations are ever-changing. Six categories of HIPAA requirements stand out as transformative: disclosure accounting/tracking, business associations, institutional review board (IRB) changes, minimum necessary requirements, data de-identification, and criminal and civil penalties.

scholarly journals Seroprevalence of antibodies to SARS-CoV-2 in healthcare workers: a cross-sectional study

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043584 ◽  
Author(s):  
Joseph E Ebinger ◽  
Gregory J Botwin ◽  
Christine M Albert ◽  
Mona Alotaibi ◽  
Moshe Arditi ◽  
...  
Keyword(s):  
African American ◽  
Los Angeles ◽  
Delivery System ◽  
Healthcare Workers ◽  
Los Angeles County ◽  
Healthcare Delivery ◽  
Healthcare Delivery System ◽  
Hispanic Ethnicity ◽  
Factors Associated ◽  
African American Race

ObjectiveWe sought to determine the extent of SARS-CoV-2 seroprevalence and the factors associated with seroprevalence across a diverse cohort of healthcare workers.DesignObservational cohort study of healthcare workers, including SARS-CoV-2 serology testing and participant questionnaires.SettingsA multisite healthcare delivery system located in Los Angeles County.ParticipantsA diverse and unselected population of adults (n=6062) employed in a multisite healthcare delivery system located in Los Angeles County, including individuals with direct patient contact and others with non-patient-oriented work functions.Main outcomesUsing Bayesian and multivariate analyses, we estimated seroprevalence and factors associated with seropositivity and antibody levels, including pre-existing demographic and clinical characteristics; potential COVID-19 illness-related exposures; and symptoms consistent with COVID-19 infection.ResultsWe observed a seroprevalence rate of 4.1%, with anosmia as the most prominently associated self-reported symptom (OR 11.04, p<0.001) in addition to fever (OR 2.02, p=0.002) and myalgias (OR 1.65, p=0.035). After adjusting for potential confounders, seroprevalence was also associated with Hispanic ethnicity (OR 1.98, p=0.001) and African-American race (OR 2.02, p=0.027) as well as contact with a COVID-19-diagnosed individual in the household (OR 5.73, p<0.001) or clinical work setting (OR 1.76, p=0.002). Importantly, African-American race and Hispanic ethnicity were associated with antibody positivity even after adjusting for personal COVID-19 diagnosis status, suggesting the contribution of unmeasured structural or societal factors.Conclusion and relevanceThe demographic factors associated with SARS-CoV-2 seroprevalence among our healthcare workers underscore the importance of exposure sources beyond the workplace. The size and diversity of our study population, combined with robust survey and modelling techniques, provide a vibrant picture of the demographic factors, exposures and symptoms that can identify individuals with susceptibility as well as potential to mount an immune response to COVID-19.

scholarly journals The characteristics of patients with possible familial hypercholesterolemia—screening a large payer/provider healthcare delivery system

QJM ◽  
2019 ◽  
Vol 113 (6) ◽  
pp. 411-417 ◽  
Author(s):  
A Elis ◽  
M Leventer-Roberts ◽  
A Bachrach ◽  
N Lieberman ◽  
R Durst ◽  
...  
Keyword(s):  
General Population ◽  
Health Services ◽  
Familial Hypercholesterolemia ◽  
Chronic Kidney Disease Stage ◽  
Healthcare Delivery ◽  
Disease Stage ◽  
Study Cohort ◽  
Healthcare Delivery System ◽  
Cross Sectional ◽  
History Of

Abstract Background Familial hypercholesterolemia (FH) is an under-diagnosed condition. Aim We applied standard laboratory criteria across a large longitudinal electronic medical record database to describe cross-sectional population with possible FH. Methods A cross-sectional study of Clalit Health Services members. Subjects who met the General Population MED-PED laboratory criteria, excluding: age &lt;10 years, documentation of thyroid, liver, biliary or autoimmune diseases, a history of chronic kidney disease stage 3 or greater, the presence of urine protein &gt;300 mg/l, HDL-C&gt;80 mg/dl, active malignancy or pregnancy at the time of testing were considered possible FH. Demographic and clinical characteristics are described at time of diagnosis and at a single index date following diagnosis to estimate the burden on the healthcare system. The patient population is also compared to the general population. Results The study cohort included 12 494 subjects with out of over 4.5 million members of Clalit Health Services. The estimated prevalence of FH in Israel was found to be 1:285. These patients are notably positive for, and have a family history of, cardiovascular disease and risk factors. For most of them the LDL-C levels are not controlled, and only a quarter of them are medically treated. Conclusions By using the modified MED-PED criteria in a large electronic database, patients with possible FH can be identified enabling early intervention and treatment.

scholarly journals Big Data Analytics in Healthcare

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Ashwin Belle ◽  
Raghuram Thiagarajan ◽  
S. M. Reza Soroushmehr ◽  
Fatemeh Navidi ◽  
Daniel A. Beard ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Care Delivery ◽  
Healthcare Delivery ◽  
Big Data Analytics ◽  
Healthcare Systems ◽  
Medical Data ◽  
Unstructured Data ◽  
Process Of Care ◽  
Multimodal Data

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

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