The association of self-perceived changes due to COVID-19 with mental and physical health among adult primary care patients with multiple chronic conditions: A US-based longitudinal study.

Introduction: This study explores the association between self-perceived personal and community changes due to COVID-19 and health among vulnerable primary care patients experiencing multiple chronic conditions. Methods: Between September 2017 and February 2021, we obtained data from 2,426 primary care patients managing multiple chronic conditions from across the United States. We assessed the relationship between self-perceived personal and community changes due to COVID-19 and change in health measured by the PROMIS-29 mental and physical health summary scores, GAD-7 (anxiety), andPHQ-9 (depression), and DASI (functional capacity) adjusting for relevant demographic, neighborhood characteristics, and county covariates. Results: After adjustment, self-perceived personal and community changes due to COVID-19 were associated with significantly worse mental health summary scores (ß = -0.55; 95% Confidence Interval (CI) = -0.72, -0.37), anxiety (ß = 0.28; 95% CI = 0.16, 0.39), depression (ß = 0.35; 95% CI = 0.22, 0.47), and physical health summary scores (ß = -0.44; 95% CI = 0.88, 0.00). There was no association with functional capacity (ß = - 0.05; 95% CI = -0.16, 0.05). Discussion: Among adults managing multiple chronic conditions, self-perceived personal and community changes due to COVID-19 were associated with health. This vulnerable population may be particularly susceptible to the negative effects of COVID-19. As we do not know the long-term health effects of COVID, this paper establishes a baseline of epidemiological data on COVID-19 burden and health among primary care patients with multiple chronic conditions.

A Cluster Randomized Trial of Primary Care Practice Redesign to Integrate Behavioral Health for Those Who Need It Most: Patients With Multiple Chronic Conditions.

PURPOSE: Patient outcomes can improve when primary care and behavioral health providers use a collaborative system of care, but integrating these services is difficult. We tested the effectiveness of a practice intervention for improving patient outcomes by enhancing integrated behavioral health (IBH) activities. METHODS: We conducted a pragmatic, cluster randomized controlled trial. The intervention combined practice redesign, quality improvement coaching, provider and staff education, and collaborative learning. At baseline and 2 years, staff at 42 primary care practices completed the Practice Integration Profile (PIP) as a measure of IBH. Adult patients with multiple chronic medical and behavioral conditions completed the Patient-Reported Outcomes Measurement Information System (PROMIS-29) survey. Primary outcomes were the change in 8 PROMIS-29 domain scores. Secondary outcomes included change in level of integration. RESULTS: Intervention assignment had no effect on change in outcomes reported by 2,426 patients who completed both baseline and 2-year surveys. Practices assigned to the intervention improved PIP workflow scores but not PIP total scores. Baseline PIP total score was significantly associated with patient-reported function, independent of intervention. Active practices that completed intervention workbooks (n = 13) improved patient-reported outcomes and practice integration (P ≤ .05) compared with other active practices (n = 7). CONCLUSION: Intervention assignment had no effect on change in patient outcomes; however, we did observe improved patient outcomes among practices that entered the study with greater IBH. We also observed more improvement of integration and patient outcomes among active practices that completed the intervention compared to active practices that did not. Additional research is needed to understand how implementation efforts to enhance IBH can best reach patients.

Community Health Teams: a qualitative study about the factors influencing the decision-making process.

BACKGROUND: The purpose of this study was to explore the factors influencing how individual Community Health Teams (CHTs) make decisions about what services to offer and how to allocate their resources. METHODS: We conducted thirteen semi-structured interviews with all 13 CHTs program managers between January and March, 2021. We analyzed interviewees descriptions of their service offerings, resources allocation, and decision-making process to identify themes. RESULTS: Four major themes emerged from the interview data as factors influencing community health team program managers' decision-making process: commitment to offering high-quality care coordination, Blueprint's stable and flexible structure, use of data in priority setting, and leveraging community partnerships and local resources. CONCLUSIONS: Community-based CHTs with flexible funding allowed programs to tailor service offerings in response to community needs. It is important for teams to have access to community-level data. Teams are cultivating and leveraging community partners to increase their care coordination capacity, which is focus of their work. CHTs are a model for leveraging community partnerships to increase service capacity and pubic engagement in health services for other states to replicate.

Integrating behavioural health and primary care: qualitative findings on contextual factors that influence integration.

BACKGROUND: Integrating behavioural health care into primary care practices may increase patients' access to behavioural health services and improve health outcomes. However, few studies have explored factors that influence integration processes. OBJECTIVE: We sought to better understand contextual factors that support or impede behavioural health integration in primary care practices. METHODS: We conducted 71 semi-structured interviews with providers, staff, and leaders from eight primary care practices in the United States with integrated behavioural health services, which were participating in a randomized control, pragmatic trial: Integrating Behavioural Health and Primary Care. Practices were selected for diversity on geographic location, size, ownership, and experience with integration. We conducted a thematic analysis of the qualitative data derived from the interviews. RESULTS: We identified four categories of contextual factors influencing behavioural health integration: leadership commitment to integration, financial considerations, workflow and communication systems, and providers' perspectives on integration and team-based healthcare. Supportive factors included leaders' commitment to integration, adequate staffing, customized communication and workflow systems, collaborative practice culture, and healthy working relationships amongst providers. Impediments included staffing issues and payment models that do not reimburse for activities required to support integrated care. CONCLUSION: Interviewees described various benefits of integration, including providers feeling better equipped to address patients' needs due to collaboration between medical and behavioural providers and resulting interdisciplinary learning. Given concerns about provider burnout, this finding warrants further study.

This study examines the integration of behavioural health services, such as mental health counselling, into primary care practices. We conducted interviews with representatives from eight primary care practices with integrated behavioural health services. The participating practices are located in diverse geographic locations across the United States, and all were engaged in a large, national project entitled Integrating Behavioural Health and Primary Care. A total of 71 healthcare providers, staff, and practice leaders were interviewed and asked to discuss the factors that influenced efforts to integrate behavioural healthcare in their primary care practice. We analysed the interview transcripts and identified factors that supported or impeded behavioural health integration. Supportive factors included practice leaders' commitment to integration, adequate staffing, customized communication and workflow systems within the practice, a collaborative practice culture, and healthy working relationships amongst the medical and behavioural health providers. Impediments included staffing issues and a lack of reimbursement from insurance companies and government payers for the time and effort that practice staff needs to devote in order to provide integrated care. Interviewees described various benefits of behavioural health integration, including providers feeling better equipped to address patients' needs due to collaboration between medical and behavioural providers.

Intraclass Correlation and Variance in the Characteristics of Primary Care Patients Managing Chronic Medical and Behavioral Conditions.

Background To avoid statistical errors, researchers who recruit patients from selected medical practices and analyze them at the individual level need to account for the clustered nature of their sample. This is most often done using the intraclass correlation coefficients (ICCs), a measure of how strongly subjects recruited from the same cluster (in this case patients from a clinic) resemble each other. Aims The aim is to support the design of cluster-randomized studies by supplying estimates of variance and ICC of various measures using a population of patients from multiple primary care clinics. Materials and methods ICCs were extracted from a large cluster-randomized pragmatic clinical trial of adult primary care patients managing multiple chronic conditions, the Integrating Behavioral Health and Primary Care study (IBH-PC). IBH-PC collected demographics and patient-reported health outcomes on over 3,000 adults from 44 primary care practices in 13 states across the US. We present estimates of the standard deviation and ICC for gender, race, ethnicity, marital status, employment, income, education, social determinants of health, PROMIS-29 functional status, Duke Activity Status Index (DASI), nine-item Patient Health Questionnaire (PHQ-9) depression score, Generalized Anxiety Disorder (GAD-7) anxiety score, Asthma Symptom Utility Index, restricted activity days, medication adherence, health care visits in the past month, emergency room visits in the past year, hospital days in the past year, perception of quality and patient-centeredness of care, alcoholic drinks per month, and the GAIN substance use disorder screener. Results ICCs varied broadly with the highest values found for race and income and the lowest for short-term estimates of the GAIN. Conclusions These values can be used to inform the design, especially power estimates and sample size requirements, of future studies.

Development and validation of the patient centeredness index for primary care.

AIMS AND OBJECTIVES: To describe the development of the Patient Centeredness Index (PCI), evaluate its psychometric characteristics and evaluate the relationships between scores on the PCI and an established measure of empathy. BACKGROUND: Patient centeredness helps patients manage multiple chronic conditions with their providers, nurses and other team members. However, no instrument exists for evaluating patient centeredness within primary care practices treating this population. DESIGN: Multi-site instrument development and validation. STROBE reporting guidelines were followed. METHODS: To identify themes, we consulted literature on patient centeredness and engaged stakeholders who had or were caring for people with multiple chronic conditions (n = 7). We composed and refined items to represent those themes with input from clinicians and researchers. To evaluate reliability and convergent validity, we administered surveys to participants (n = 3622) with chronic conditions recruited from 44 primary care practices for a large-scale cluster randomised clinical trial of the effects of a practice-level intervention on patient and practice-level outcomes. Participants chose to complete the 16-item survey online, on paper or by phone. Surveys assessed demographics, number of chronic conditions and ratings of provider empathy. We conducted exploratory factor analysis to model the interrelationships among items. RESULTS: A single factor explained 93% of total variance. Factor loadings ranged from 0.55-0.85, and item-test correlations were ≥.67. Cronbach's alpha was .93. A moderate, linear correlation with ratings of provider's empathy (r = .65) supports convergent validity. CONCLUSIONS: The PCI is a new tool for obtaining patient perceptions of the patient centeredness of their primary care practice. The PCI shows acceptable reliability and evidence of convergent validity among patients managing chronic conditions. RELEVANCE TO CLINICAL PRACTICE: The PCI rapidly identifies patients' perspectives on patient centeredness of their practice, making it ideal for administration in busy primary care settings that aim to efficiently address patient-identified needs. TRIAL REGISTRATION: Clinicaltrials.org Protocol ID: WLPS-1409-24372. TITLE: Integrating Behavioural Health and Primary Care for Comorbid Behavioural and Medical Problems (IBHPC).