Graph and download economic data for Labor Productivity for Health Care and Social Assistance: Medical and Diagnostic Laboratories (NAICS 62151) in the United States (IPURN62151L000000000) from 1994 to 2024 about diagnostic labs, healthcare, social assistance, medical, productivity, health, NAICS, IP, labor, and USA.

The use of 5G in healthcare will unlock *** billion U.S. dollars in productivity gains by 2030, through new applications made possible by the new mobile broadband standard. This will come through the use of telemedicine, drones to transport medical equipment and therapies, and streamlined doctor-patient interactions.

Health care productivity in the United Kingdom grew at a slower rate than the whole economy but at a faster rate than the total public sector in the period between 1997 and 2019. This statistic presents the health care productivity index in the United Kingdom between 1997 and 2019 compared to whole economy and total public sector productivity.

Public service healthcare growth rates and indices for inputs, quality and non-quality adjusted output and productivity, totals and components, for UK, 1995 to 2021

Graph and download economic data for Output per Worker for Health Care and Social Assistance: Diagnostic Imaging Centers (NAICS 621512) in the United States (IPURN621512W001000000) from 1995 to 2022 about diagnostic imaging, healthcare, social assistance, output, health, NAICS, IP, employment, and USA.

Public service healthcare growth rates and indices for inputs, quality and non-quality adjusted output and productivity, totals and components.

Productivity growth

The latest estimates of change in the volume of Healthcare inputs

The latest estimates of change in the volume of Healthcare output, and impact of quality adjustment

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Healthcare Productivity Estimates

ObjectiveThis study aims to assess the efficiency and productivity of the Luohu Hospital Group after the reform and to identify factors influencing the efficiency to support the future development of medical consortia.MethodsData on health resources from Shenzhen and the Luohu Hospital Group for the years 2015 to 2021 were analyzed using the super-efficiency slack-based measure data envelopment analysis (SE-SBM-DEA) model, Malmquist productivity index (MPI), and Tobit regression to evaluate changes in efficiency and productivity and to identify determinants of efficiency post-reform.ResultsAfter the reform, the efficiency of health resource allocation within the Luohu Hospital Group improved by 33.87%. Community health centers (CHCs) within the group had an average efficiency score of 1.046. Moreover, the Luohu Hospital Group’s average total factor productivity change (TFPCH) increased by 2.5%, primarily due to gains in technical efficiency change (EFFCH), which offset declines in technical progress change (TECHCH). The efficiency scores of CHCs were notably affected by the ratio of general practitioners (GPs) to health technicians and the availability of home hospital beds.ConclusionThe reform in the Luohu healthcare system has shown preliminary success, but continuous monitoring is necessary. Future strategies should focus on strengthening technological innovation, training GPs, and implementing the home hospital bed policy. These efforts will optimize the efficiency of health resource allocation and support the integration and development of resources within the medical consortium.

Public service healthcare inputs and quality adjusted output and productivity growth rates compared to previously published statistics.

Graph and download economic data for Labor Productivity for Health Care and Social Assistance: Hospitals, Except Psychiatric and Substance Abuse Hospitals (NAICS 622A) in the United States (IPURN622AL001000000) from 1994 to 2022 about healthcare, hospitality, hospitals, social assistance, productivity, health, NAICS, IP, labor, and USA.

Estimates of healthcare expenditure in the UK to the definitions contained in the System of Health Accounts (SHA, OECD 2000)

Source agency: Office for National Statistics

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Expenditure on Healthcare in the UK

Public service healthcare growth rates and indices for inputs, quantity and quality adjusted output and productivity.

Associations with total health care costs and productivity costs based on generalized linear models.

Health care utilization by category of service of adult trauma patients (ISS≥16).

Majority of the population of Mizoram relies on public hospitals as a primary provider of healthcare services. These hospitals are burdened with the ever-increasing demand for healthcare without much improvement in resource allocation and equitable distribution of manpower in the healthcare sector. Mizoram spends only 4.2 per cent of its GSDP on healthcare as per the report of National Health Profile, 2020. This paper aims to investigate the efficiency and productivity of public hospitals in Mizoram following the post-reform period, and to compare these findings with hospitals in other states across India. We utilized the input-oriented variable returns to scale model of Data Envelopment Analysis (DEA) to compute efficiency scores. Subsequently, we applied the Malmquist Total Factor Productivity Index to assess productivity trends over time. Data of 11 public hospitals was collected from the Ministry of Health, Mizoram form the period 2016-17 to 2022-23. The findings highlight that most of the public hospitals in Mizoram operate on an efficient level with an overall technical efficiency of 0.914. Furthermore, total factor productivity increased by 7 per cent during the study period. This paper suggests the need for reallocation of manpower from inefficient to efficient hospitals. The paper provides a novel insight regarding the health care sector’s efficiency and productivity in which has been overlooked till date.

Work Productivity Loss, Activity Impairment, and Healthcare Resource Use by T1DM/No Diabetes groups.

🇬🇧 영국

Characteristics of the study population, by participation.

The conventional wisdom in health economics is that large differences in average productivity across US hospitals are the result of idiosyncratic features of the healthcare sector which dull the role of market forces. Strikingly, however, we find that productivity dispersion in heart attack treatment across hospitals is, if anything, smaller than in narrowly defined manufacturing industries such as ready-mixed concrete. While this fact admits multiple interpretations, it suggests that healthcare may have more in common with "traditional" sectors than is often assumed, and relatedly, that insights from research on productivity and allocation in other sectors may enrich analysis of healthcare.