Client Factors Affect Provider Adherence to Guidelines during First Antenatal Care in Public Health Facilities, Ethiopia: A Multi-Center Cross-Sectional Study

BACKGROUND፡ Timely entry to an antenatal care with a healthcare provider who follows a set of national guidelines is assumed to ensure higher levels of client satisfaction. It is also expected to improve perinatal outcomes. Little is known about the level of adherence of Ethiopian providers to these guidelines. Therefore, this study aims to assess the proportion of clients who received complete (100%) provider adherence to antenatal care guidelines at the first visit and client associated factors in Gondar Town.METHODS: A cross-sectional study of 834 study participants was conducted in public health facilities of Gondar Town in Ethiopia. An 18 point checklist was used to observe provider adherence to the first antenatal care visit guidelines. Descriptive statistics and multivariable binary logistic regression model were done by using STATA 14 software.RESULT: The proportion of clients who received the complete provider’s adherence to the first antenatal care guideline was 32.25% (95% CI: 29.1-35.5). The mean adherence score was 16.78%. Women who had prior history of pregnancy and/or birthrelated complications (AOR = 1.58; 95%CI: 1.04-2.04) and late antenatal care booking at gestational week 16 or greater (AOR =1.45; 95%CI: 1.03-2.03) were significantly associated with clients receiving complete providers’ adherence to the first antenatal guideline.CONCLUSIONS: We found the level of adherence to national antenatal care guidelines during first visit as surprisingly low. When considering to upgrade the guidelines to the actual WHO guideline of eight visits, we recommend that refresher training be provided regularly to help staff understand the importance of following the guidelines as closely as possible. Perhaps, we need to learn more from the health care providers themselves about their reasons for not following the guidelines

Medical Quality Assessment by Scoring Adherence to Guideline Intentions

Quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe an approach for evaluating and consistently scoring clinician adherence to medical guidelines using the intentions of guideline authors. We present the Quality Indicator Language (QUIL) that may be used to formally specify quality constraints on physician behavior and patient outcomes derived from medical guidelines. We present a modeling and scoring methodology for consistently evaluating multi-step and multi-choice guideline plans based on guideline intentions and their revisions

Agent-based management of clinical guidelines

Les guies de pràctica clínica (GPC) contenen un conjunt d'accions i dades que ajuden a un metge a prendre decisions sobre el diagnòstic, tractament o qualsevol altre procediment a un pacient i sobre una determinada malaltia. És conegut que l'adopció d'aquestes guies en la vida diària pot millorar l'assistència mèdica als pacients, pel fet que s'estandarditzen les pràctiques. Sistemes computeritzats que utilitzen GPC poden constituir part de sistemes d'ajut a la presa de decisions més complexos amb la finalitat de proporcionar el coneixement adequat a la persona adequada, en un format correcte i en el moment precís. L'automatització de l'execució de les GPC és el primer pas per la seva implantació en els centres mèdics.Per aconseguir aquesta implantació final, hi ha diferents passos que cal solucionar com per exemple, l'adquisició i representació de les GPC, la seva verificació formal, i finalment la seva execució. Aquesta Tesi està dirigida en l'execució de GPC i proposa la implementació d'un sistema multi-agent. En aquest sistema els diferents actors dels centres mèdics coordinen les seves activitats seguint un pla global determinat per una GPC. Un dels principals problemes de qualsevol sistema que treballa en l'àmbit mèdic és el tractament del coneixement. En aquest cas s'han hagut de tractar termes mèdics i organitzatius, que s'ha resolt amb la implementació de diferents ontologies. La separació de la representació del coneixement del seu ús és intencionada i permet que el sistema d'execució de GPC sigui fàcilment adaptable a les circumstàncies concretes dels centres, on varien el personal i els recursos disponibles.En paral·lel a l'execució de GPC, el sistema proposat manega preferències del pacient per tal d'implementar serveis adaptats al pacient. En aquesta àrea concretament, a) s'han definit un conjunt de criteris, b) aquesta informació forma part del perfil de l'usuari i serveix per ordenar les propostes que el sistema li proposa, i c) un algoritme no supervisat d'aprenentatge permet adaptar les preferències del pacient segons triï.Finalment, algunes idees d'aquesta Tesi actualment s'estan aplicant en dos projectes de recerca. Per una banda, l'execució distribuïda de GPC, i per altra banda, la representació del coneixement mèdic i organitzatiu utilitzant ontologies.Clinical guidelines (CGs) contain a set of directions or principles to assist the health care practitioner with patient care decisions about appropriate diagnostic, therapeutic, or other clinical procedures for specific clinical circumstances. It is widely accepted that the adoption of guideline-execution engines in daily practice would improve the patient care, by standardising the care procedures. Guideline-based systems can constitute part of a knowledge-based decision support system in order to deliver the right knowledge to the right people in the right form at the right time. The automation of the guideline execution process is a basic step towards its widespread use in medical centres.To achieve this general goal, different topics should be tackled, such as the acquisition of clinical guidelines, its formal verification, and finally its execution. This dissertation focuses on the execution of CGs and proposes the implementation of an agent-based platform in which the actors involved in health care coordinate their activities to perform the complex task of guideline enactment. The management of medical and organizational knowledge, and the formal representation of the CGs, are two knowledge-related topics addressed in this dissertation and tackled through the design of several application ontologies. The separation of the knowledge from its use is fully intentioned, and allows the CG execution engine to be easily customisable to different medical centres with varying personnel and resources.In parallel with the execution of CGs, the system handles citizen's preferences and uses them to implement patient-centred services. With respect this issue, the following tasks have been developed: a) definition of the user's criteria, b) use of the patient's profile to rank the alternatives presented to him, c) implementation of an unsupervised learning method to adapt dynamically and automatically the user's profile.Finally, several ideas of this dissertation are being directly applied in two ongoing funded research projects, including the agent-based execution of CGs and the ontological management of medical and organizational knowledge

Ecology and emergence: Understanding factors that drive variation in process quality and clinical outcomes in general practice

Clinical practice variation (CPV), where differences in healthcare delivery do not reflect differences in patient preferences or clinical need, is considered a hallmark of poor quality care. 'Unwarranted' variation is the focus of mounting policy attention and a growing body of literature, but remains poorly explained and theorised, with ways of determining when variation is warranted only weakly developed. Many assertions around CPV remain under-explored and untested. Much of the literature operates on the assumption that the legitimacy of variation depends on its source or cause, and that variation in processes of care will lead to related variation in outcomes. This doctoral research focuses on two overarching questions relating to CPV in Australian general practice: (1) what is CPV, and how can it be best conceptualised and understood; and (2) what can routinely-collected clinical data tell us about the phenomenon of CPV in general practice? Accordingly, this thesis explores the operationalisation of CPV as a theoretical construct and also examines variation in a series of clinical performance measures for coronary heart disease (CHD) and diabetes. Together, these lines of inquiry constitute a mixed-methods 'sense-making' exercise that seeks an incremental interplay between literature and data, to shed light on the phenomenon of CPV. Data are drawn from a unique dataset of aggregate reporting metrics, using extracted electronic medical record data, among an affiliated group of 36 general practice clinics serving approximately 189,848 patients over a 5-year period. These data are examined descriptively and ultimately analysed using Qualitative Comparative Analysis (QCA) against an empirically derived explanatory framework. Theory development draws on complexity science, especially complex adaptive systems theory, and the disciplines of social epidemiology and health ecology. Results show that a series of discourses have strongly shaped thinking about CPV, converging around a normative 'bad apples' approach to understanding variation. However, CPV may also contribute to healthcare quality in ways that are not well considered, especially in primary care settings. I demonstrate that there may be unconventional but more illuminating ways to conceptualise variation that enable our collective understanding to progress. These include using an ecological framework to conceive CPV as an emergent property of coupled, complex adaptive systems, and employing an equity lens to distinguish between CPV in processes and outcomes of care. In descriptive analyses, I find that variation frequently behaves differently across different measures, with crucial system information contained in the interstices of the data. Contrary to common assumptions, relationships between processes and outcomes of care are not straightforward. Using a framework of factors associated with CPV in general practice management of diabetes and CHD, I confirm that causality is complex and multifactorial, operating at a number of levels. Employing the case-based configurational method of QCA, I show that there may be no single or primary cause for CPV. Instead, clinics can arrive at a particular outcome via multiple independent causal pathways which are themselves multifactorial. These multi-component causes may be defined as much by the interactions between component elements as by individual elements themselves. The same factor may have differential effects within different combinations, or at different scales. These findings suggest that relying on causal explanations to demarcate unwarranted variation may be insufficient. However, both theory and methods require continued development to ensure an adequate understanding of the role and representation of warranted and unwarranted variation in performance measurement systems. Case-based configurational methods such as QCA may have substantial utility in helping to explain and delineate these phenomena