The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe

Matching Mobile Crisis Models to Communities: An Example from Northwestern Ontario

Police are often the first to encounter individuals when they are experiencing a mental health crisis. Other professionals with different skill sets, however, may be needed to optimize crisis response. Increasingly, police and mental health agencies are creating co-responder teams (CRTs) in which police and mental health professionals co-respond to crisis calls. While past evaluations of CRTs have shown promising results (e.g. hospital diversions; cost-effectiveness), most studies occurred in larger urban contexts. How CRTs function in smaller jurisdictions, with fewer complementary resources and other unique contextual features, is unknown. This paper describes the evaluation of a CRT operating in a geographically isolated and northern mid-sized city in Ontario, Canada. Data from program documents, interviews with frontline and leadership staff, and ride-along site visits were analyzed according to an extended Donabedian framework. Through thematic analysis, 12 themes and 11 subthemes emerged. Overall, data showed that the program was generally operating and supporting the community as intended through crisis de-escalation and improved quality of care, but it illuminated potential areas for improvement, including complementary community-based services. Data suggested specific structures and processes of the embedded CRT model for optimal function in a northern context, and it demonstrated the transferability of the CRT model beyond large urban centres. This research has implications for how communities can make informed choices about what crisis models are best for them based on their resources and context, thus potentially improving crisis response and alleviating strain on emergency departments and systems.

Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium

BACKGROUND

To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape.

METHODS

Based on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets.

RESULTS

To address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level.

CONCLUSION

In this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices.

Exploring motivations and resistances for implementing shared decision-making in clinical practice: A systematic review based on a structure-process-outcome model

OBJECTIVE

Shared decision-making (SDM) as a multicollaborative approach is vital for facilitating patient-centred care. Considering the limited clinical practice, we attempted to synthesize the motivations and resistances, and investigate their mutual relationships for advancing the implementation of SDM.

METHODS

A comprehensive systematic review using Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines was performed. 'Shared decision making' was searched as the mesh term through PubMed, Web of Science and EBSCO from 2000 to 2021, and the quality of literature was appraised using the QualSyst Tool. Motivations and resistances were categorized based on content analysis and the 'structure-process-outcome' model.

RESULTS

From 8319 potential citations, 105 were included, comprising 53 qualitative studies (the average quality score is 0.92) and 52 quantitative studies (the average quality score is 0.95). A total of 42 categories of factors were identified into 11 themes and further grouped into three dimensions: structure, process and outcome. The structure dimension comprised six themes (71.43%), the process dimension contained four themes (11.01%) and the outcome dimension covered only one theme. Across all categories, decision-making time and patients' decision preparedness in the process dimension were the most reported, followed by physicians' communication skills and health care environment in the structure dimension. Analysis of implementation of SDM among various types of diseases showed that more influencing factors were extracted from chronic diseases and unspecified disease decisions.

CONCLUSIONS

The major determinants for the implementation of SDM are focused on the structural dimension, which challenges the health systems of both developed and low- and middle-income countries. Furthermore, we consider it important to understand more about the interactions among the factors to take integrated measures to address the problems and to ensure the effectiveness of implementing SDM.

PATIENT OR PUBLIC CONTRIBUTION

Patients, healthcare professionals and other stakeholders articulated their perspectives on the implementation of SDM actively, and these were adopted and analysed in this study. However, the above-mentioned individuals were not directly involved in the process of this study. Protocol was registered on PROSPERO (CRD42021259309).

From Theory to Implementation: Adaptations to a Quality Improvement Initiative According to Implementation Context

As countries continue to invest in quality improvement (QI) initiatives in health facilities, it is important to acknowledge the role of context in implementation. We conducted a qualitative study between February 2019 and January 2020 to explore how a QI initiative was adapted to enable implementation in three facility types: primary health centres, public hospitals and private facilities in Lagos State, Nigeria.Despite a common theory of change, implementation of the initiative needed to be adapted to accommodate the local needs, priorities and organisational culture of each facility type. Across facility types, inadequate human and capital resources constrained implementation and necessitated an extension of the initiative's duration. In public facilities, the local governance structure was adapted to facilitate coordination, but similar adaptations to governance were not possible for private facilities. Our findings highlight the importance of anticipating and planning for the local adaptation of QI initiatives according to implementation environment.

Identifying associations between health services operational factors and health experience for patients with type 2 diabetes in Iran

Background

Facing limited health resources, healthcare providers need to rely on health service delivery models that produce the best clinical outcomes and patient experience. We aimed to contribute to developing a patient experience-based type 2 diabetes service delivery model by identifying operational structures and processes of care that were associated with clinical outcome, health experience, and service experience.

Methods

We conducted a cross-sectional survey of type 2 diabetes patients between January 2019 to February 2020. Having adjusted for demand variables, we examined relationships between independent variables (behaviours, services/processes, and structures) and three categories of dependent variables; clinical outcomes (HbA1c and fasting blood glucose), health experience (EuroQol quality of life (EQ-5D), evaluation of quality of life (visual analgene scale of EQ-5D), and satisfaction with overall health status), and service experience (evaluation of diabetes services in comparison with worst and best imaginable diabetes services and satisfaction with diabetes services). We analysed data using multivariate linear regression models using Stata software.

Results

After adjusting for demand variables; structures, diabetes-specific health behaviours, and processes explained up to 22, 12, and 9% of the variance in the outcomes, respectively. Based on significant associations between the diabetes service operations and outcomes, the components of an experience-based service delivery model included the structural elements (continuity of care, redistribution of task to low-cost resources, and improved access to provider), behaviours (improved patient awareness and adherence), and process elements (reduced variation in service utilization, increased responsiveness, caring, comprehensiveness of care, and shared decision-making).

Conclusions

Based on the extent of explained variance and identified significant variables, health services operational factors that determine patient-reported outcomes for patients with type 2 diabetes in Iran were identified, which focus on improving continuity of care and access to providers at the first place, improving adherence to care at the second, and various operational process variables at the third place.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06932-0.

Introducing an efficient sampling method for national surveys with limited sample sizes: application to a national study to determine quality and cost of healthcare

Background

Sampling a small number of participants from an entire country is not straightforward. In this case, researchers reluctantly sample from a single setting or few settings, which limits the generalizability of findings. Therefore, there is a need to design efficient sampling method for small sample size surveys that can produce generalizable results at the country level.

Methods

Data comprised of twenty proxy variables to measure health services demands, structures, and outcomes of 413 districts of Iran. We used two data mining methods (hierarchical clustering method (HCM) and model-based clustering method (MCM)) to create homogenous groups of districts, i.e., strata based on these variables. We compared the internal and stability validity of the methods by statistical indices. An expert group checked the face validity of the methods, particularly regarding the total number of strata and the combination of districts in each stratum. The efficiency of selected method, which is measured by the inverse of variance, was compared with a simple random sampling (SRS) through simulation. The sampling design was tested in a national study in Iran, which aimed to evaluate the quality and costs of medical care for eight selected diseases by only recruiting 300 participants per disease at the country level.

Results

MCM and HCM divided the districts into eight and two clusters, respectively. The measures of internal and stability validity showed that clusters created by MCM were more separated, compact, and stable, thus forming our optimum strata. The probability of death from stroke, chronic obstructive pulmonary disease, and in-hospital mortality rate were the most important indicators that distinguished the eight strata. Based on the simulation results, MCM increased the efficiency of the sampling design up to 1.7 times compared to SRS.

Conclusions

The use of data mining improved the efficiency of sampling up to 1.7 times greater than SRS and markedly reduced the number of strata to eight in the entire country. The proposed sampling design also identified key variables that could be used to classify districts in Iran for sampling from these target populations in the future studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11441-0.

Health extension workers' perceived health system context and health post preparedness to provide services: a cross-sectional study in four Ethiopian regions

OBJECTIVE

The health system context influences the implementation of evidence-based practices and quality of healthcare services. Ethiopia aims at reaching universal health coverage but faces low primary care utilisation and substandard quality of care. We assessed the health extension workers' perceived context and the preparedness of health posts to provide services.

SETTING

This study was part of evaluating a complex intervention in 52 districts of four regions of Ethiopia. This paper used the endline data collected from December 2018 to February 2019.

PARTICIPANTS

A total of 152 health posts and health extension workers serving selected enumeration areas were included.

OUTCOME MEASURES

We used the Context Assessment for Community Health (COACH) tool and the Service Availability and Readiness Assessment tool.

RESULTS

Internal reliability of COACH was satisfactory. The dimensions community engagement, work culture, commitment to work and leadership all scored high (mean 3.75-4.01 on a 1-5 scale), while organisational resources, sources of knowledge and informal payments scored low (1.78-2.71). The general service readiness index was 59%. On average, 67% of the health posts had basic amenities to provide services, 81% had basic equipment, 42% had standard precautions for infection prevention, 47% had test capacity for malaria and 58% had essential medicines.

CONCLUSION

The health extension workers had a good relationship with the local community, used data for planning, were highly committed to their work with positive perceptions of their work culture, a relatively positive attitude regarding their leaders, and reported no corruption or informal payments. In contrast, they had insufficient sources of information and a severe lack of resources. The health post preparedness confirmed the low level of resources and preparedness for services. These findings suggest a significant potential contribution by health extension workers to Ethiopia's primary healthcare, provided that they receive improved support, including new information and essential resources.

Modeling Patient Journeys for Demand Segments in Chronic Care, With an Illustration to Type 2 Diabetes

Chronic care is an important area for cost-effective and efficient health service delivery. Matching demand and services for chronic care is not easy as patients may have different needs in different stages of the disease. More insight is needed into the complete patient journey to do justice to the services required in each stage of the disease, to the different experiences of patients in each part of the journey, and to outcomes in each stage. With patient journey we refer to the “journey” of the patient along the services received within a demand segment of chronic care. We developed a generic framework for describing patient journeys and provider networks, based on an extension of the well-known model of Donabedian, to relate demand, services, resources, behavior, and outcomes. We also developed a generic operational model for the detailed modeling of services and resources, allowing for insight into costs. The generic operational model can be tailored to the specific characteristics of patient groups. We applied this modeling approach to type 2 diabetes (T2D) patients. Diabetes care is a form of chronic care for patients suffering diabetes mellitus. We studied the performance of T2D networks, using a descriptive model template. To identify and describe demand we made use of the following demand segments within the diabetes type 2 population: patients targeted for prevention; patients with stage 1 diabetes treated by their GP with lifestyle advice; patients with diabetes stage 2 treated by their GP with lifestyle advice and oral medication; patients with stage 3 diabetes treated by their GP with lifestyle advice, oral medication, and insulin injections; patients with stage 4 diabetes with complications (treated by internal medicine specialists). We used a Markov model to describe the transitions between the different health states. The model enables the patient journey through the health care system for cohorts of newly diagnosed T2D patients to be described, and to make a projection of the resource requirements of the different demand segments over the years. We illustrate our approach with a case study on a T2D care network in The Netherlands and reflect on the role of demand segmentation to analyse the case study results, with the objective of improving the T2D service delivery.

Insight into blood pressure targets for universal coverage of hypertension services in Iran: the 2017 ACC/AHA versus JNC 8 hypertension guidelines

BACKGROUND

We compared the prevalence, awareness, treatment, and control of hypertension in Iran based on two hypertension guidelines; the 2017 ACC/AHA -with an aggressive blood pressure target of 130/80 mmHg- and the commonly used JNC8 guideline cut-off of 140/90 mmHg. We shed light on the implications of the 2017 ACC/AHA for population subgroups and high-risk individuals who were eligible for non-pharmacologic and pharmacologic therapies.

METHODS

Data was obtained from the Iran national STEPS 2016 study. Participants included 27,738 adults aged ≥25 years as a representative sample of Iranians. Regression models of survey design were used to examine the determinants of prevalence, awareness, treatment, and control of hypertension.

RESULTS

The prevalence of hypertension based on JNC8 was 29.9% (95% CI: 29.2-30.6), which soared to 53.7% (52.9-54.4) based on the 2017 ACC/AHA. The percentage of awareness, treatment, and control were 59.2% (58.0-60.3), 80.2% (78.9-81.4), and 39.1% (37.4-40.7) based on JNC8, which dropped to 37.1% (36.2-38.0), 71.3% (69.9-72.7), and 19.6% (18.3-21.0), respectively, by applying the 2017 ACC/AHA. Based on the new guideline, adults aged 25-34 years had the largest increase in prevalence (from 7.3 to 30.7%). They also had the lowest awareness and treatment rate, contrary to the highest control rate (36.5%) between age groups. Compared with JNC8, based on the 2017 ACC/AHA, 24, 15, 17, and 11% more individuals with dyslipidaemia, high triglycerides, diabetes, and cardiovascular disease events, respectively, fell into the hypertensive category. Yet, based on the 2017 ACC/AHA, 68.2% of individuals falling into the hypertensive category were eligible for receiving pharmacologic therapy (versus 95.7% in JNC8). LDL cholesterol< 130 mg/dL, sufficient physical activity (Metabolic Equivalents≥600/week), and Body Mass Index were found to change blood pressure by - 3.56(- 4.38, - 2.74), - 2.04(- 2.58, - 1.50), and 0.48(0.42, 0.53) mmHg, respectively.

CONCLUSIONS

Switching from JNC8 to 2017 ACC/AHA sharply increased the prevalence and drastically decreased the awareness, treatment, and control in Iran. Based on the 2017 ACC/AHA, more young adults and those with chronic comorbidities fell into the hypertensive category; these individuals might benefit from earlier interventions such as lifestyle modifications. The low control rate among individuals receiving treatment warrants a critical review of hypertension services.

Relationships Between Context, Process, and Outcome Indicators to Assess Quality of Physiotherapy Care in Patients with Whiplash-Associated Disorders: Applying Donabedian's Model of Care

BACKGROUND

Quality indicators (QIs) are measurable elements of practice performance and may relate to context, process, outcome and structure. A valid set of QIs have been developed, reflecting the clinical reasoning used in primary care physiotherapy for patients with whiplash-associated disorders (WAD). Donabedian's model postulates relationships between the constructs of quality of care, acting in a virtuous circle.

AIM

To explore the relative strengths of the relationships between context, process, and outcome indicators in the assessment of primary care physiotherapy in patients with WAD.

MATERIALS AND METHODS

Data on WAD patients (N=810) were collected over a period of 16 years in primary care physiotherapy practices by means of patients records. This routinely collected dataset (RCD-WAD) was classified in context, process, and outcome variables and analyzed retrospectively. Clinically relevant variables were selected based on expert consensus. Associations were expressed, using zero-order, as Spearman rank correlation coefficients (criterion: rs >0.25 [minimum: fair]; α-value = 0.05).

RESULTS

In round 1, 62 of 85 (72.9%) variables were selected by an expert panel as relevant for clinical reasoning; in round 2, 34 of 62 (54.8%) (context variables 9 of 18 [50.0%]; process variables 18 of 34 [52.9]; outcome variables 8 of 10 [90.0%]) as highly relevant. Associations between the selected context and process variables ranged from 0.27 to 0.53 (p≤0.00), between selected context and outcome variables from 0.26 to 0.55 (p≤0.00), and between selected process and outcome variables from 0.29 to 0.59 (p≤0.00). Moderate associations (rs >0.50; p≤0.00) were found between "pain coping" and "fear avoidance" as process variables, and "pain intensity" and "functioning" as outcome variables.

CONCLUSION

The identified associations between selected context, process, and outcome variables were fair to moderate. Ongoing work may clarify some of these associations and provide guidance to physiotherapists on how best to improve the quality of clinical reasoning in terms of relationships between context, process, and outcome in the management of patients with WAD.

Correction: The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe

[This corrects the article DOI: 10.1371/journal.pone.0192599.].