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Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care.

ABSTRACT: Inadequate quality of care in healthcare facilities is one of the primary causes of patient mortality in low- and middle-income countries, and understanding the behavior of healthcare providers is key to addressing it. Much of the existing research concentrates on improving resource-focused issues, such as staffing or training, but these interventions do not fully close the gaps in quality of care. By contrast, there is a lack of knowledge regarding the full contextual and internal drivers-such as social norms, beliefs, and emotions-that influence the clinical behaviors of healthcare providers. We aimed to provide two conceptual frameworks to identify such drivers, and investigate them in a facility setting where inadequate quality of care is pronounced. Using immersion interviews and a novel decision-making game incorporating concepts from behavioral science, we systematically and qualitatively identified an extensive set of contextual and internal behavioral drivers in staff nurses working in reproductive, maternal, newborn, and child health (RMNCH) in government public health facilities in Uttar Pradesh, India. We found that the nurses operate in an environment of stress, blame, and lack of control, which appears to influence their perception of their role as often significantly different from the RMNCH program's perspective. That context influences their perceptions of risk for themselves and for their patients, as well as self-efficacy beliefs, which could lead to avoidance of responsibility, or incorrect care. A limitation of the study is its use of only qualitative methods, which provide depth, rather than prevalence estimates of findings. This exploratory study identified previously under-researched contextual and internal drivers influencing the care-related behavior of staff nurses in public facilities in Uttar Pradesh. We recommend four types of interventions to close the gap between actual and target behaviors: structural improvements, systemic changes, community-level shifts, and interventions within healthcare facilities.

SUBMITTER: Engl E

PROVIDER: S-EPMC6469845 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care.

Engl Elisabeth E Kretschmer Steve S Jain Mokshada M Sharma Saransh S Prasad Ram R Ramesh B M BM Shetye Mrunal M Tandon Seema S Kumar Sanjiv S Barrios Wilson Tisa T Sgaier Sema K SK

PloS one 20190417 4

Inadequate quality of care in healthcare facilities is one of the primary causes of patient mortality in low- and middle-income countries, and understanding the behavior of healthcare providers is key to addressing it. Much of the existing research concentrates on improving resource-focused issues, such as staffing or training, but these interventions do not fully close the gaps in quality of care. By contrast, there is a lack of knowledge regarding the full contextual and internal drivers-such ...[more]

PMID: 30995274

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Project description:OBJECTIVE:To develop a tool for use by non-clinical fieldworkers for assessing the quality of care delivered by community health workers providing comprehensive care in households in low- and middle-income countries. DESIGN:We determined the content of the tool using multiple sources of information, including interactions with district managers, national training manuals and an exploratory study that included observations of 70 community health workers undertaking 518 household visits collected as part of a wider study. We also reviewed relevant literature, selecting relevant domains and quality markers. To refine the tool and manual we worked with the fieldworkers who had undertaken the observations. We constructed two scores summarising key aspects of care: (1) delivering messages and actions during household visit, and (2) communicating with the household; we also collected contextual data. The fieldworkers used the tool with community health workers in a different area to test feasibility. SETTING:South Africa, where community health workers have been brought into the public health system to address the shortage of healthcare workers and limited access to healthcare. It was embedded in an intervention study to improve quality of community health worker supervision. PRIMARY AND SECONDARY OUTCOMES:Our primary outcome was the completion of a tool and user manual. RESULTS:The tool consists of four sections, completed at different stages during community health worker household visits: before setting out, at entry to a household, during the household visit and after leaving the household. Following tool refinement, we found no problems on field-testing the tool. CONCLUSIONS:We have developed a tool for assessing quality of care delivered by community health workers at home visits, often an unobserved part of their role. The tool was developed for evaluating an intervention but could also be used to support training and management of community health workers.

Project description:Background:Whether health care provider burnout contributes to lower quality of patient care is unclear. Purpose:To estimate the overall relationship between burnout and quality of care and to evaluate whether published studies provide exaggerated estimates of this relationship. Data Sources:MEDLINE, PsycINFO, Health and Psychosocial Instruments (EBSCO), Mental Measurements Yearbook (EBSCO), EMBASE (Elsevier), and Web of Science (Clarivate Analytics), with no language restrictions, from inception through 28 May 2019. Study Selection:Peer-reviewed publications, in any language, quantifying health care provider burnout in relation to quality of patient care. Data Extraction:2 reviewers independently selected studies, extracted measures of association of burnout and quality of care, and assessed potential bias by using the Ioannidis (excess significance) and Egger (small-study effect) tests. Data Synthesis:A total of 11 703 citations were identified, from which 123 publications with 142 study populations encompassing 241 553 health care providers were selected. Quality-of-care outcomes were grouped into 5 categories: best practices (n = 14), communication (n = 5), medical errors (n = 32), patient outcomes (n = 17), and quality and safety (n = 74). Relations between burnout and quality of care were highly heterogeneous (I2 = 93.4% to 98.8%). Of 114 unique burnout-quality combinations, 58 indicated burnout related to poor-quality care, 6 indicated burnout related to high-quality care, and 50 showed no significant effect. Excess significance was apparent (73% of studies observed vs. 62% predicted to have statistically significant results; P = 0.011). This indicator of potential bias was most prominent for the least-rigorous quality measures of best practices and quality and safety. Limitation:Studies were primarily observational; neither causality nor directionality could be determined. Conclusion:Burnout in health care professionals frequently is associated with poor-quality care in the published literature. The true effect size may be smaller than reported. Future studies should prespecify outcomes to reduce the risk for exaggerated effect size estimates. Primary Funding Source:Stanford Maternal and Child Health Research Institute.

Project description:BACKGROUND:The increased use of electronic medical records (EMRs) in Canadian primary health care practice has resulted in an expansion of the availability of EMR data. Potential users of these data need to understand their quality in relation to the uses to which they are applied. Herein, we propose a basic model for assessing primary health care EMR data quality, comprising a set of data quality measures within four domains. We describe the process of developing and testing this set of measures, share the results of applying these measures in three EMR-derived datasets, and discuss what this reveals about the measures and EMR data quality. The model is offered as a starting point from which data users can refine their own approach, based on their own needs. METHODS:Using an iterative process, measures of EMR data quality were created within four domains: comparability; completeness; correctness; and currency. We used a series of process steps to develop the measures. The measures were then operationalized, and tested within three datasets created from different EMR software products. RESULTS:A set of eleven final measures were created. We were not able to calculate results for several measures in one dataset because of the way the data were collected in that specific EMR. Overall, we found variability in the results of testing the measures (e.g. sensitivity values were highest for diabetes, and lowest for obesity), among datasets (e.g. recording of height), and by patient age and sex (e.g. recording of blood pressure, height and weight). CONCLUSIONS:This paper proposes a basic model for assessing primary health care EMR data quality. We developed and tested multiple measures of data quality, within four domains, in three different EMR-derived primary health care datasets. The results of testing these measures indicated that not all measures could be utilized in all datasets, and illustrated variability in data quality. This is one step forward in creating a standard set of measures of data quality. Nonetheless, each project has unique challenges, and therefore requires its own data quality assessment before proceeding.

Project description:BackgroundAs community case management of childhood illness expands in low-income countries, there is a need to assess the quality of care provided by community health workers. This study had the following objectives: 1) examine methods of recruitment of sick children for assessment of quality of care, 2) assess the validity of register review (RR) and direct observation only (DO) compared to direct observation with re-examination (DO+RE), and 3) assess the effect of observation on community health worker performance.MethodsWe conducted a survey to assess the quality of care provided by Ethiopian Health Extension Workers (HEWs). The sample of children was obtained through spontaneous consultation, HEW mobilization, or recruitment by the survey team. We assessed patient characteristics by recruitment method. Estimates of indicators of quality of care obtained using RR and DO were compared to gold standard estimates obtained through DO+RE. Sensitivity, specificity, and the area under receiver operator characteristic curve (AUC) were calculated to assess the validity of RR and DO. To assess the Hawthorne effect, we compared estimates from RR for children who were observed by the survey team to estimates from RR for children who were not observed by the survey team.ResultsParticipants included 137 HEWs and 257 sick children in 103 health posts, plus 544 children from patient registers. Children mobilized by HEWs had the highest proportion of severe illness (27%). Indicators of quality of care from RR and DO had high sensitivity for most indicators, but specificity was low. The AUC for different indicators from RR ranged from 0.47 to 0.76, with only one indicator above 0.75. The AUC of indicators from DO ranged from 0.54 to 1.0, with three indicators above 0.75. The differences between estimates of correct care for observed versus not observed children were small.ConclusionsMobilization by HEWs and recruitment by the survey teams were feasible, but potentially biased, methods of obtaining sick children. Register review and DO underestimated performance errors. Our data suggest that being observed had only a small positive effect on the performance of HEWs.

Project description:The quality of care (QoC) of primary health care (PHC) services in Albania faces challenges on multiple levels including governance, access, infrastructure and health care workers. In addition, there is a lack of trust in the latter. The Health for All Project (HAP) funded by the Swiss Agency for Development and Cooperation therefore aimed at enhancing the population's health by improving PHC services and implementing health promotion activities following a multi-strategic health system strengthening approach. The objective of this article is to compare QoC before and after the 4 years of project implementation. A cross-sectional study was implemented at 38 PHC facilities in urban and rural locations in the Diber and Fier regions of Albania in 2015 and in 2018. A survey measured the infrastructure of the different facilities, provider-patient interactions through clinical observation and patient satisfaction. During clinical observations, special attention was given to diabetes and hypertensive patients. Infrastructure scores improved from base- to endline with significant changes seen on national level and for rural facilities (p < 0.01). Facility infrastructure and overall cleanliness, hygiene and basic/essential medical equipment and supplies improved at endline, while for public accountability/transparency and guidelines and materials no significant change was observed. The overall clinical observation score increased at endline overall, in both areas and in rural and urban setting. However, infection prevention and control procedures and diabetes treatment still experienced relatively low levels of performance at endline. Patient satisfaction on PHC services is generally high and higher yet at endline. The changes observed in the 38 PHC facilities in two regions in Albania between 2015 and 2018 were overall positive with improvements seen at all three levels assessed, e.g., infrastructure, service provision and patient satisfaction. However, to gain overall improvements in the QoC and move toward a more efficient and sustainable health system requires continuous investments in infrastructure alongside interventions at the provider and user level.

Dataset Information

Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care.

Publications

Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care.

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