Patient-Centred Innovations for Persons With Multimorbidity - Quebec

Overview

The aim of Patient-Centred Innovations for Persons With Multimorbidity (PACE in MM) study is to reorient the health care system from a single disease focus to a multimorbidity focus; centre on not only disease but also the patient in context; and realign the health care system from separate silos to coordinated collaborations in care. PACE in MM will propose multifaceted innovations in Chronic Disease Prevention and Management (CDPM) that will be grounded in current realities (i.e. Chronic Care Models including Self-Management Programs), that are linked to Primary Care (PC) reform efforts. The study will build on this firm foundation, will design and test promising innovations and will achieve transformation by creating structures to sustain relationships among researchers, decision-makers, practitioners, and patients. The Team will conduct inter-jurisdictional comparisons and is mainly a Quebec (QC) - Ontario (ON) collaboration with participation from 3 other provinces: British Columbia (BC); Manitoba (MB); and Nova Scotia (NS). The Team's objectives are: 1) to identify factors responsible for success or failure of current CDPM programs linked to the PC reform, by conducting a realist synthesis of their quantitative and qualitative evaluations; 2) to transform consenting CDPM programs identified in Objective 1, by aligning them to promising interventions on patient-centred care for multimorbidity patients, and to test these new innovations' in at least two jurisdictions and compare among jurisdictions; and 3) to foster the scaling-up of innovations informed by Objective 1 and tested/proven in Objective 2, and to conduct research on different approaches to scaling-up. This registration for Clinical Trials only pertains to Objective 2 of the study.

A recent systematic review on the prevalence of Multimorbidity (MM) recommended a count of 3+ chronic diseases, with no focus on any single chronic disease in particular. This definition identifies a more vulnerable population with higher needs, lower income or poverty, poorer outcomes and challenging processes of care. It includes people with a wide array of complexity from the uncomplicated course of minimally interacting chronic diseases to the highly complex MM patients. MM is not only important due to the burden on patients, but because it accounts for high utilization. The definition represents a continuum of vulnerability in which there are many opportunities for prevention and management. Despite the high prevalence of MM, most research and health care is still based on a single disease paradigm which may not be appropriate as 45% of primary care patients have MM. A recent Cochrane systematic review on the impact of interventions for patients with MM has identified a paucity of studies internationally with mixed results, thus paving the way for the work of this Team. The most promising intervention, to date, was enhanced teamwork in a multifaceted intervention involving multiple professionals. Patient-Centred Partnerships between Patients and Providers: The definition of patient-centred partnerships is derived from Canadian policy reports: "collaboration between informed, respected patients and a healthcare team." There is an internationally accepted comprehensive operational definition with four components which will guide many aspects of the proposed research program: first, exploring the patients' diseases and the illness experience; second, understanding the whole person in context; third, finding common ground; and fourth, enhancing the patient-provider relationship. There is empirical evidence for the impact of patient-centred partnerships on better patient outcomes and lower costs. Systematic reviews of interventions indicated promising results for feasible practice-based interventions targeting both providers and patients. Canadian policy reports defined this second facet of patient-centredness, as "seamless coordination and integration of care." Transitions requiring coordination are a key feature of care for patients with MM. Coordination has been shown to positively impact: symptom relief; social functioning; hospital re-admission and related costs. Papers reviewed by this Team identified the most promising type of intervention to be structured delivery system re-design. STUDY #2.1 Qualitative Evaluation of the aligned Programs Purpose: The study will: assess how the transformed program performs; distinguish between components of the interventions; and identify contextual factors that may have influenced the content and effectiveness of the intervention. It will also examine the local barriers and facilitators as well as the transitions and coordination of care. Methods and design: The Team will conduct a qualitative evaluation of the transformed programs to explain how various contexts influence observed effects \[1\] including the context of the health care systems in each province. A recent example of this research approach in Canada is Best et al, 2012 \[2\]. Data will be obtained from interviews and written documents. In-depth interviews will be conducted among the four categories of stakeholders. This will include: a) decision-makers (n = 10); b) primary care physicians (n = 10); c) professionals doing the interventions (n = 10); and a d) purposive sample of patients with multimorbidity (n = 10) and their informal caregivers (n=10) \[51\]. The number of interviews are estimates and will be guided by the saturation of data \[3\]. Data collection: In-depth interviews, lasting 30 to 60 minutes will ensure complete and detailed participation. The data collection will be held during the second year of the transformed program. The interview guides will examine how the context variables influence the effects and the elements that could potentially inform the development of future interventions. All interviews will be audiotaped and transcribed verbatim. Additionally, written documents will be collected (program team meeting summaries, a sample of 10 medical records or research records at each participating site, a checklist describing the fidelity of the intervention, all documents produced specifically for the intervention) to provide an in-depth understanding of the various contexts in which the interventions occurred. Data analysis: The data will be analyzed using an iterative and interpretative approach \[4\]. The data from all participants will be examined through both independent and team analysis occurring in a concurrent manner to build and develop on the emerging themes. A coding template will be developed and edited as new themes emerge while others are reclassified or discarded. A data management software will be used to organize the coded data and identify exemplar quotes reflecting the central themes. All written documents will undergo a content analysis. The final step of the analysis will be the triangulation of the synthesis of the themes from the stakeholder participants and the content analysis of the documents.\[3-4\] STUDY #2.2: Evaluation of effects of the aligned Programs Setting: The same consenting participating sites as described in study 2.1. The methods presented below are for one setting and will be duplicated in the second setting. Patients are referred to receive the services of these programs by their providers. The intervention the investigators are testing here is the aligned programs. Patients referred to these programs are new patients and have never been exposed to the intervention. In addition to the main reason for referral to the program, the referral form will also include eligibility details for the evaluation, including diagnoses. Patient sample: Patients recruited for the study will be cognitively intact and literate and aged between 18 and 80 years of age. The upper limit of 80 years is to avoid recruiting patients at risk of being institutionalized or dependent during the follow-up. Patients will present at least three chronic conditions. Methods and Design: Patients agreeing to participate will complete questionnaires at baseline (T1) collecting the sociodemographic data and baseline measures, which will be used to document equivalence between groups (groups are defined below). Effectiveness of the aligned program will be assessed using three strategies. 1. To measure short-term effects (4 months), a randomized controlled trial (RCT) design with a delayed intervention will be used \[5\]. Eligible patients will be randomized after consent to receive either the intervention within a short period of time (Group A) or 4 months later (Group B); self-reported mailed questionnaires will be completed at baseline (T1) for all patient participants, 4 months after the end of the intervention for group A (T2) and 4 months after baseline for control group B (T2). This will constitute the short-term measure of effectiveness of the intervention. Group B will then receive the intervention. 2. To measure the mid-term effects (one year) on patient-reported outcomes, a before and after study is proposed combining groups A and B together. The patients will complete the same questionnaire 12 months after the end of the intervention (T3). 3. To measure mid-term (T3) and long-term effects (T4 after 2 years) on health services utilization and cost, all patients (groups A and B) will provide consent to give access to their health administrative (HA) data. At baseline, a control Group C will be constituted using anonymized HA data. Patients will be matched for gender, age, region and main three diagnoses. The Team will build algorithms for matching every set of controls. Groups A and B together will be compared to this propensity matched control group C in a before-after study using administrative (HA) data. Variables and outcome measures: The variables fall into 5 categories: sociodemographic; PC context; main co-variables of interest; primary outcomes; secondary outcomes. Socio-demographic characteristics include gender, age, education, family income, marital status, occupation, housing and number of persons living under the same roof. Context variables refer to type of PC organization in which the intervention occurs (Family Medicine Group). The three main co-variables of interest are the Team's three innovations: self-reported multimorbidity (measured by the Disease Burden Morbidity Assessment \[6\]; patient-centred partnership (Patient Perception of Patient-Centredness Scale \[7-9\]); and Patient centered coordination (the Patient Perceptions of Transitions in care, adapted by the investigators from Coleman \[10\]). The two primary outcome measures are the Health Education Impact Questionnaire (HeiQ) that provides a broad profile of the potential impacts of patient education interventions \[11\] and the level of perceived disease-management self-efficacy using the 6-item Self-Efficacy for Managing Chronic Disease (SEM-CD) \[12\]. Secondary patient perceived outcomes will be the VR-12 as a measure of health status and the "EuroQoL group" instrument called "EQ5D" as a measure of Quality of Life \[13\]. The Kessler psychological distress scale K-6 will measure psychological distress \[14\]. The investigators will also use a questionnaire on health behaviors \[15\]. Finally, HA data will also be used as secondary outcomes to compare health care utilization and cost before and after the intervention. HA data will include emergency department visits, avoidable hospital admissions, readmissions, time to first primary care visit after emergency department visit and continuity of care. Data analysis: Investigators will first describe participants' baseline characteristics in each group and compare among groups. To evaluate short-term effect, Groups A and B will be compared on T2 scores with an analysis of co-variance (ANCOVA) adjusted for T1 scores \[16\]. To document mid-term effects, a before and after measures analysis of variance will be used to study the evolution of continuous variables collected 3 times \[17\]. Sub-analyses by gender will be performed. Health system costs in intervention and control groups will be evaluated by using amounts paid to providers based on provincial fee schedules and cost-weighted utilization of institutions including hospitals and long-term care. Utilization records obtained from HA data will be multiplied by applicable cost weights \[18\] The methods employed will model the individual patient-level costs incurred in the health system, using methods developed for costing using administrative data\[19\]. Incremental resources in the intervention group will be identified and costed using applicable time/resource inputs and relevant wage rates following guidelines for economic evaluation in health interventions \[20\].