An integrated framework for verifying multiple care pathways

Common chronic conditions are routinely treated following standardised procedures known as clinical pathways. For patients suffering from two or more chronic conditions, referred to as multimorbidities, several pathways have to be applied simultaneously. However, since pathways rarely consider the presence of comorbidities, applying several pathways may lead to potentially harmful (medication) conflicts. This paper proposes an automated framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidites. We use BPMN as a modelling language for capturing care guidelines. A BPMN model is transformed into an intermediate formal model capturing the possible unfoldings of the pathway. Through a combination of the constraint solver Z3 and the theorem prover Isabelle, we check the correctness of combined treatment plans. We illustrate the approach with an example from the medical domain and discuss future work.Postprin

Using care plans to better manage multimorbidity

BACKGROUND: The health care for patients having two or more long-term medical conditions is fragmented between specialists, allied health professionals, and general practitioners (GPs), each keeping separate medical records. There are separate guidelines for each disease, making it difficult for the GP to coordinate care. The TrueBlue model of collaborative care to address key problems in managing patients with multimorbidity in general practice previously reported outcomes on the management of multimorbidities. We report on the care plan for patients with depression, diabetes, and/or coronary heart disease that was embedded in the TrueBlue study. METHODS: A care plan was designed around diabetes, coronary heart disease, and depression management guidelines to prompt implementation of best practices and to provide a single document for information from multiple sources. It was used in the TrueBlue trial undertaken by 400 patients (206 intervention and 194 control) from 11 Australian general practices in regional and metropolitan areas. RESULTS: Practice nurses and GPs successfully used the care plan to achieve the guideline-recommended checks for almost all patients, and successfully monitored depression scores and risk factors, kept pathology results up to date, and identified patient priorities and goals. Clinical outcomes improved compared with usual care. CONCLUSION: The care plan was used successfully to manage and prioritise multimorbidity. Downstream implications include improving efficiency in patient management, and better health outcomes for patients with complex multimorbidities

A framework for automated conflict detection and resolution in medical guidelines

This research is supported by the MRC-funded UK Research and Innovation grant MR/S003819/1 and by EPSRC grant EP/M014290/1.Common chronic conditions are routinely treated following standardised procedures known as clinical guidelines. For patients suffering from two or more chronic conditions, known as multimorbidity, several guidelines have to be applied simultaneously, which may lead to severe adverse effects when the combined recommendations and prescribed medications are inconsistent or incomplete. This paper presents an automated formal framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidities focusing on medications. The presented extended framework has a front-end which takes guidelines captured in a standard modelling language and returns the visualisation of the detected conflicts as well as suggested alternative treatments. Internally, the guidelines are transformed into formal models capturing the possible unfoldings of the guidelines. The back-end takes the formal models associated with multiple guidelines and checks their correctness with a theorem prover, and inherent inconsistencies with a constraint solver. Key to our approach is the use of an optimising constraint solver which enables us to search for the best solution that resolves/minimises conflicts according to medication efficacy and the degree of severity in case of harmful combinations, also taking into account their temporal overlapping. The approach is illustrated throughout with a real medical example.Publisher PDFPeer reviewe

Lived experiences of multimorbidity: an interpretative meta-synthesis of patients', general practitioners' and trainees' perceptions

OBJECTIVES: Multimorbidity is an increasing challenge. Better understanding of lived experiences of patients, general practitioners and trainees, may advance patient care and medical education. This interpretative meta-synthesis sought to (i) understand lived experiences of patients, general practitioners and trainees regarding multimorbidity, (ii) identify how similarities and differences in experiences should shape future solutions. METHODS: Empirical studies containing qualitative data and pertaining to lived experiences from our recent realist synthesis (PROSPERO 2013:CRD42013003862) were included. Following quality assessment, data were extracted from key studies to build an integrated analytic framework. Data from remaining studies were utilised to expand and refine the framework through thematic analysis of concepts within and between perspectives. RESULTS: Twenty-one papers were included in the meta-synthesis. Analysis of 70 concepts produced five themes: (1) goals of care and decision making, (2) complexity, (3) meeting expectations, (4) logistics and (5) interpersonal dynamics. The complexities of multimorbidity lead to shared feelings of vulnerability, uncertainty and enforced compromises. Barriers to optimal care-education included system constraints, inadequate continuity and role uncertainty. DISCUSSION: There was little evidence of shared discussion of these challenges. Addressing these issues and more explicit exploration of the experiences of each group during interactions may improve delivery and satisfaction in care and education

Argumentation-based explanations of multimorbidity treatment plans

We present an argumentation model to explain the optimal treatment plans recommended by a Satisfiability Modulo Theories solver for multimorbid patients. The resulting framework can be queried to obtain supporting reasons for nodes on a path following a model of argumentation schemes. The modelling approach is generic and can be used for justifying similar sequences.Postprin

From the biomedical to the biopsychosocial model: the implementation of a stepped and collaborative care model in Swiss general hospitals

Background and objectives International and national initiatives like the Sustainable Development Goals and the National Strategy on the Prevention of non-communicable diseases aim to reduce the burden of mental health. Early detection of mental health conditions is thus, a major priority of public health. Stepped and Collaborative Care Models (SCCMs) offer an opportunity to early detect and appropriately treat mental health conditions in vulnerable populations, fostering integrated care. This thesis focuses on a SCCM that aims to implement a routine psychosocial distress assessment and offers appropriate treatment to distressed hospital patients. However, integration of mental health services into somatic settings was seen to be challenging in other settings, e.g., primary care. Evidence for patients with mental–somatic multimorbidities in hospital settings is scarce. Thus, the main objectives of this thesis were to assess the integration of mental health services and to assess implementation of a SCCM into general hospitals in Basel-Stadt, Switzerland (Objectives 1 and 2). The unforeseen coronavirus disease 2019 (COVID-19) pandemic additionally triggered further research questions. We investigated the association between COVID-19 restrictions and mental health of non-COVID-19 hospital patients (Objective 3). Additionally, we explored an alternative method to monitor mental health consequences of the COVID-19 pandemic, the use of Big Data (Objective 4). Methods This thesis focuses on a SCCM implemented in four hospitals, three of which were included in the studies presented here: the University Hospital Basel, the University Department of Geriatric Medicine FELIX PLATTER, and the Bethesda Hospital. Including three hospitals differing in structure and focus allowed us to get a broader view of possible facilitators and barriers to the integration of mental health and the implementation of the SCCM. We conducted qualitative interviews with physicians and nurses operating the SCCM at the hospital before (N = 18) and after (N = 18) the implementation of the SCCM. Additionally, we used quantitative data of 873 patients on COVID-19 distress, mental health consequences, and social support collected during periods with different COVID-19 restriction levels, using multiple regression models. The last objective was presented as an opinion paper, highlighting advantages and disadvantages of Big Data based on literature. Results Before the SCCM was implemented in hospital settings in Basel, Switzerland, healthcare professionals perceived mental–somatic multimorbidities to be relevant due to their high perceived frequency (Objective 1). Mental health dimensions had, however, a low priority due to suboptimal environments, suboptimal interprofessional collaboration, existing stigma among healthcare professionals and patients, lack of mental health knowledge, and the strong emphasis on somatic diseases. Particularly physicians reported the low priority of mental health, also due to historical views focusing on biomedical aspects and time constraints. Afterwards, we assessed facilitators and barriers of implementing the first step of the SCCM (Objective 2). The first step of the SCCM is a psychosocial distress assessment of patients through healthcare professionals. Healthcare professionals highlighted the importance of integrating the assessment into preexisting hospital workflows and IT systems. Being able to adapt certain workflows to the needs of the different wards and hospitals was key to adherence and thus, to the sustainability of the SCCM. Still, structural and social barriers to the implementation of the psychosocial distress assessment were emphasized. Hospitals are characterized by a strong focus on somatic diseases with tight working routines. Adding additional tasks like the mental health assessment constituted a challenge. Besides the strong emphasis on somatic diseases and the time constraints, lack of knowledge, awareness, and familiarity and subjectivity of the mental health assessment were impeding the efforts towards integrated care. This, partially, is also caused by the high turnover rate of physicians. The implementation of the SCCM described herewas accompanied by the COVID-19 pandemic. The Swiss government set different COVID-19 restrictions depending on COVID-19 case numbers, hospitalizations, and deaths. Thus, we investigated the association between the COVID-19 restrictions and the COVID-19-related distress, mental health consequences, and social support (Objective 3). Multiple regression analyses of non-COVID-19 patients during different levels of COVID-19 restrictions indicated that hospital patients were more distressed related to leisure time and loneliness when stronger COVID-19 restrictions were in place. Surprisingly, this did not result in increased mental health consequences or changes in social support. Another approach to monitor mental health of the general population or subgroups like hospital patients could be Big Data, such as social media or routine hospital data (Objective 4). These may help to tailor appropriate interventions to populations at risk of mental health consequences. Applying Big Data should always consider ethical and legal concerns to protect privacy and data. Particularly, transparency regarding data analysis may prevent these concerns. Conclusion This thesis adds evidence to the integration of mental health and implementation of a SCCM to hospital settings in Switzerland. Structural and social challenges, such as missing knowledge and awareness, strong emphasis on somatic diseases, time constraints, suboptimal environment, suboptimal interprofessional collaboration, and stigma were emphasized by healthcare professionals. To overcome these challenges, hospitals and policy makers need to think about changes in the healthcare system. For instance, task shifts, new roles, and new processes are needed in the hospital setting to better achieve integrated care. Hospitals are built to care for patients in acute medical situations. Patients with mental–somatic multimorbidities, however, need continuous and long-term care. Certain patient groups (e.g., cancer patients, transplantation patients) receive this care within hospitals. Other patient groups rely on treatment outside hospital. Strong networks between services within and outside hospitals are, thus, essential to guarantee continuity of care. Overall, the current healthcare system with its strong biomedical focus needs to adapt to the increasing number of patients with chronic diseases, including mental–somatic multimorbidities. This system change could be achieved through learning health systems, where interprofessional and interdisciplinary work is a high priority. Continuously collected data supports the adaptation of the healthcare system to the current needs and evidence base. Thus, the change from the biomedical to the biopsychosocial model may be strengthened

Illness representations and associated coping responses in adults experiencing multimorbidity: A systematic review and narrative synthesis.

LITERATURE REVIEW Abstract Objectives: Research indicates that illness representations are associated with the management of health conditions. They are therefore important to understand when supporting people to best cope with their illnesses. This systematic review aims to summarise and synthesise the literature exploring illness representations and associated coping responses in people experiencing more than one chronic condition. Methods: A systematic review of literature published prior to November 2018 on MEDLINE, Embase, CINAHL, Web of Science and PsycINFO databases. Search terms included three broad areas; multimorbidity, health and illness representations. Results are synthesised using a narrative approach. Results: Eight papers are included in the review and comprise qualitative and quantitative research designs. Findings indicate that illness representations in those with multimorbidity vary across conditions and individuals, while people hold representations relating to both individual conditions and multimorbidity. These representations have been associated with medication adherence and self-management behaviours. Conclusions: This narrative synthesis highlights that representations have a role in coping. There is a need to consider illness representations in clinical consultations and in the delivery of care to improve condition management. Further research is needed to establish how this may be best achieved and to consider other variables which may influence representations and coping. Developing a theoretical framework which may account for both single and multimorbid representations will be important for such future research. Keywords: Multimorbidity, chronic condition, common-sense model, illness representation, systematic review, narrative synthesis. EMPIRICAL PAPER Abstract Objectives: Research has highlighted an association between illness representations and coping responses, such as self-management, medication taking and treatment-seeking. However, illness representations for common mental health symptoms when experienced alongside multimorbidity are poorly understood. The current study aims to understand how people experiencing multimorbidity represent and respond to their common mental health symptoms. Methods: Semi-structured interviews were conducted with thirteen participants experiencing mild to moderate symptoms of anxiety and/or depression alongside physical multimorbidity. Thematic analysis combined with deviant case analysis was used to analyse the data. Results: The results provide an understanding of illness representations and coping responses for common mental health symptoms in those experiencing multimorbidity. Four key themes were identified; 1) interconnected conditions, 2) methods of responding to mental health difficulties, 3) relationships: the importance of connection and understanding, and 4) narrow treatment options. Conclusions: Illness representations for common mental health symptoms appear to have a role in guiding coping responses, including treatment-seeking. Having an awareness of people’s illness representations will be useful in clinical practice to guide consultations and interventions. By understanding and working with illness representations and increasing primary care accessibility we may begin to improve coping and treatment-seeking within this population. The implications of this research will be useful in allowing health services to meet the needs of the growing multimorbidity population and close the mental health treatment gap. Keywords: Multimorbidity, chronic conditions, mental health, illness representations, coping responses, treatment-seeking, qualitative research

Using care plans to better manage multimorbidity

Background The health care for patients having two or more long-term medical conditions is fragmented between specialists, allied health professionals, and general practitioners (GPs), each keeping separate medical records. There are separate guidelines for each disease, making it difficult for the GP to coordinate care. The TrueBlue model of collaborative care to address key problems in managing patients with multimorbidity in general practice previously reported outcomes on the management of multimorbidities. We report on the care plan for patients with depression, diabetes, and/or coronary heart disease that was embedded in the TrueBlue study. Methods A care plan was designed around diabetes, coronary heart disease, and depression management guidelines to prompt implementation of best practices and to provide a single document for information from multiple sources. It was used in the TrueBlue trial undertaken by 400 patients (206 intervention and 194 control) from 11 Australian general practices in regional and metropolitan areas. Results Practice nurses and GPs successfully used the care plan to achieve the guideline-recommended checks for almost all patients, and successfully monitored depression scores and risk factors, kept pathology results up to date, and identified patient priorities and goals. Clinical outcomes improved compared with usual care. Conclusion The care plan was used successfully to manage and prioritise multimorbidity. Downstream implications include improving efficiency in patient management, and better health outcomes for patients with complex multimorbidities

Testing implementation facilitation of a primary care-based collaborative care clinical program using a hybrid type III interrupted time series design: a study protocol

Abstract Background Dissemination of evidence-based practices that can reduce morbidity and mortality is important to combat the growing opioid overdose crisis in the USA. Research and expert consensus support reducing high-dose opioid therapy, avoiding risky opioid-benzodiazepine combination therapy, and promoting multi-modal, collaborative models of pain care. Collaborative care interventions that support primary care providers have been effective in medication tapering. We developed a patient-centered Primary Care-Integrated Pain Support (PIPS) collaborative care clinical program based on effective components of previous collaborative care interventions. Implementation facilitation, a multi-faceted and dynamic strategy involving the provision of interactive problem-solving and support during implementation of a new program, is used to support key organizational staff throughout PIPS implementation. The primary aim of this study is to evaluate the effectiveness of the implementation facilitation strategy for implementing and sustaining PIPS in the Veterans Health Administration (VHA). The secondary aim is to examine the effect of the program on key patient-level clinical outcomes—transitioning to safer regimens and enhancing access to complementary and integrative health treatments. The tertiary aim is to determine the categorical costs and ultimate budget impact of PIPS implementation. Methods This multi-site study employs an interrupted time series, hybrid type III design to evaluate the effectiveness of implementation facilitation for a collaborative care clinical program—PIPS—in primary care clinics in three geographically diverse VHA health care systems (sites). Participants include pharmacists and allied staff involved in the delivery of clinical pain management services as well as patients. Eligible patients are prescribed either an outpatient opioid prescription greater than or equal to 90 mg morphine equivalent daily dose or a combination opioid-benzodiazepine regimen. They must also have an upcoming appointment in primary care. The Consolidated Framework for Implementation Research will guide the mixed methods work across the formative evaluation phases and informs the selection of activities included in implementation facilitation. The RE-AIM framework will be used to assess Reach, Effectiveness, Adoption, Implementation, and Maintenance of PIPS. Discussion This implementation study will provide important insight into the effectiveness of implementation facilitation to enhance uptake of a collaborative care program in primary care, which targets unsafe opioid prescribing practices.https://deepblue.lib.umich.edu/bitstream/2027.42/146542/1/13012_2018_Article_838.pd