Background: Health care provider (HCP) performance in low- and middle-income countries (LMICs) is often inadequate. The Health Care Provider Performance Review (HCPPR) is a comprehensive systematic review of the effectiveness and cost of strategies to improve HCP performance in LMICs. We present the HCPPR's methods, describe methodological and contextual attributes of included studies, and examine time trends of study attributes.

Methods: The HCPPR includes studies from LMICs that quantitatively evaluated any strategy to improve HCP performance for any health condition, with no language restrictions. Eligible study designs were controlled trials and interrupted time series. In 2006, we searched 15 databases for published studies; in 2008 and 2010, we completed searches of 30 document inventories for unpublished studies. Data from eligible reports were double-abstracted and entered into a database, which is publicly available. The primary outcome measure was the strategy's effect size. We assessed time trends with logistic, Poisson, and negative binomial regression modeling. We were unable to register with PROSPERO (International Prospective Register of Systematic Reviews) because the protocol was developed prior to the PROSPERO launch.

Results: We screened 105,299 citations and included 824 reports from 499 studies of 161 intervention strategies. Most strategies had multiple components and were tested by only one study each. Studies were from 79 countries and had diverse methodologies, geographic settings, HCP types, work environments, and health conditions. Training, supervision, and patient and community supports were the most commonly evaluated strategy components. Only 33.6% of studies had a low or moderate risk of bias. From 1958-2003, the number of studies per year and study quality increased significantly over time, as did the proportion of studies from low-income countries. Only 36.3% of studies reported information on strategy cost or cost-effectiveness.

Conclusions: Studies have reported on the efficacy of many strategies to improve HCP performance in LMICs. However, most studies have important methodological limitations. The HCPPR is a publicly accessible resource for decision-makers, researchers, and others interested in improving HCP performance.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544255PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217617PLOS

Publication Analysis

Top Keywords

hcp performance
20
strategies improve
12
health care
12
care provider
12
improve hcp
12
studies
12
systematic review
8
review effectiveness
8
provider performance
8
performance low-
8

Similar Publications

qPRF: A system to accelerate population receptive field modeling.

Neuroimage

January 2025

Division of Arts and Sciences, NYU Shanghai, 567 West Yangsi Road, Pudong New District, 200124, Shanghai, China; Center for Neural Science, New York University, 4 Washington Place, NY, 10003, NY, USA; NYU-ECNU Institute of Brain and Cognitive Science, 3663 Zhongshan Road North, Putuo District, 200062, Shanghai, China. Electronic address:

BOLD response can be fitted using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). Fitting the PRF model costs considerable time, often requiring days to analyze BOLD signals for a small cohort of subjects. We introduce the qPRF ("quick PRF"), a system for accelerated PRF modeling that reduced the computation time by a factor ¿1,000 without losing goodness-of-fit when compared to another widely available PRF modeling package (Kay et al.

View Article and Find Full Text PDF

A core problem with the current risk-adjustment system in Medicare Advantage and accountable care organization (ACO) programs-the Hierarchical Condition Categories (HCC) model-is that the inputs (coded diagnoses) can be influenced for gain by risk-bearing plans or providers. Using existing survey data on health status (which provide less manipulable inputs), we found that the use of a hybrid risk score drawing from survey data and a scaled-back set of HCCs would, in addition to mitigating coding incentives, modestly lessen risk-selection incentives, strengthen payment incentives to deliver efficient care, allocate payment across ACOs more efficiently according to markers of population health that are not as affected by practice patterns or coding efforts, and redistribute payment in a manner that supports equity goals. Although sampling error and survey nonresponse present challenges, analyses suggest that these should not be prohibitive.

View Article and Find Full Text PDF

Perceptions of sarcopenia in patients, health and care professionals, and the public: a scoping review of studies from different countries.

Eur Geriatr Med

January 2025

AGE Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.

Rationale And Objective: Perceptions of sarcopenia have rarely been explored, yet understanding these will be key for successful translation of sarcopenia research findings into meaningful benefits for patients and the public. This scoping review aimed to explore how sarcopenia is perceived amongst patients, health and care professionals (HCP), and the public in different countries.

Methods: Seven electronic databases were searched from inception up to December 2023 with no geographical or language limitations.

View Article and Find Full Text PDF

Background: The purpose of this study is to determine the effect of the type of I-125 radioactive source on dose distribution in the planning process of ultra-low dose rate (uLDR) prostate brachytherapy.

Material And Methods: 7 patients who had undergone brachytherapy in our center were included in the study. Dose in five geometrical points were analyzed for 12 types of implants that are available on the market.

View Article and Find Full Text PDF

Background And Objective: Inferring large-scale brain networks from functional magnetic resonance imaging (fMRI) provides more detailed and richer connectivity information, which is critical for gaining insight into brain structure and function and for predicting clinical phenotypes. However, as the number of network nodes increases, most existing methods suffer from the following limitations: (1) Traditional shallow models often struggle to estimate large-scale brain networks. (2) Existing deep graph structure learning models rely on downstream tasks and labels.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!