Psychometric Properties of the Problem-Oriented Patient Experience-Primary Care (POPE-PC) Survey.

INTRODUCTION: Measuring the experiences of patients regarding delivery and receipt of person-oriented primary care is of increasing policy and research interest and is a core component of the Institute for Healthcare Improvement's Quadruple Aim. OBJECTIVE: To describe the Problem-Oriented Patient Experience-Primary Care (POPE-PC) survey, a novel instrument designed to measure patients' experiences of primary care, and to assess the instrument's psychometric properties. METHODS: Psychometric testing was performed using data from a Canadian urgent primary care center, derived from March 2019 to September 2019. Patients automatically received the 9-question survey by email after leaving the clinic. Exploratory factor analysis (EFA) on all questions and the entire dataset was performed using parallel analysis and scree plot for factor extraction. Internal consistency was assessed by calculating Cronbach α. A split-half cross-validation of the ensuing factor structure was conducted. A correlation analysis helped explore associations between the survey's questions. RESULTS: Results from the initial EFA indicate that the POPE-PC has a conceptually sound 2-factor structure, with good internal consistency. A split-half validation yielded the same findings, reaffirming that the 2-factor model has good psychometric properties. The correlation analysis indicated that the concept of respect is strongly associated with clinical functions related to problem recognition. DISCUSSION: Problem recognition, despite being the cornerstone of person-oriented primary care, remains largely overlooked in health services research. The POPE-PC's validity and problem orientation render it potentially useful in rigorously assessing patient experiences of problem-oriented primary care. CONCLUSION: The survey's conceptual underpinning and psychometric properties, coupled with its simple and parsimonious design, enable application in primary care settings to provide person-oriented care.

A problem-oriented systems approach to primary care system development: development and initial testing of the problem-oriented primary care system development record.

BACKGROUND: There is significant global policy interest related to enabling a data-driven approach for evidence-based primary care system development. This paper describes the development and initial testing of a prototype tool (the Problem-Oriented Primary Care System Development Record, or PCSDR) that enables a data-driven and contextualized approach to primary care system development. METHODS: The PCSDR is an electronic record that enables the systematic input, classification, structuring, storage, processing and analysis of different types of data related to the structure, function and performance of primary care systems over time. Data inputted into the PCSDR was coded using the WHO's PHC-IMPACT framework and classification system. The PCSDR's functionalities were tested by using a case study of primary care system development in Tajikistan. RESULTS: Tajikistan's case study demonstrated that the PCSDR is a potentially effective and conceptually-sound tool for the input, classification, structuring and storage of different data types from myriad sources. The PCSDR is therefore a basic data entry and data management system that enables query and analytics functions for health services research and evidence-based primary care system development functions. CONCLUSIONS: The PCSDR is a data system that enables a contextualized approach to evidence-based primary care system development. It represents a coherent and effective synthesis of the fields of primary care system development and performance assessment. The PCSDR enables analysts to leverage primary care performance assessment frameworks for a broad range of functions related to health systems analysis, improvement and the development of learning health systems.

A Novel Instrument for Integrated Measurement and Assessment of Intrinsic Motivation, Team Climate, and Burnout in Multidisciplinary Teams.

INTRODUCTION: There is increasing recognition of the importance of intrinsic motivation, team dynamics, and burnout in multidisciplinary teams striving to achieve the Quadruple Aim. OBJECTIVE: To assess self-rated team climate, intrinsic motivation, and burnout of a multidisciplinary team at an urgent primary care center and to explore potential relationships between the concepts. METHODS: A scoping review of the English-language literature was conducted to identify any validated team climate, intrinsic motivation, and burnout measurement tools. The Team Climate Inventory Short Form and a single-item measure of burnout were chosen because of their validity, appropriateness to the study setting, and practicality. Daniel Pink's concept of motivation was operationalized into a novel, 13-question survey tool. The face validity of the motivation questions was assessed by various clinicians. The online survey was administered to a 38-member multidisciplinary team working at an urgent primary care center in Vancouver, Canada. Scores for team climate, motivation, and burnout were assessed, along with the tool's internal consistency. RESULTS: The survey findings (33 responses) indicate a relatively high-performing multidisciplinary team, with high scores in all categories related to team climate and intrinsic motivation. Only 8% of 25 respondents met the threshold level of burnout, with no respondents indicating severe or complete burnout. Reliability analysis produced α coefficients of 0.956 and 0.945 for team climate and intrinsic motivation, respectively, indicating satisfactory reliability. DISCUSSION: The burnout ratings align with the scores for team climate and intrinsic motivation. The study findings suggest that the clinic's current approach to leadership and management has been effective in promoting a healthy team and work environment. The small sample size does not permit statistical inferences without further testing and validation. Further exploration is warranted of various structural, organizational, system-level, and environmental factors that affect the survey's results. CONCLUSION: The study fills a gap in the health services research literature pertaining to the performance of multidisciplinary teams.

The Vancouver Community Analytics Tool (VCAT): Software Enabling Operationalization of the Building Blocks of High-Performing Primary Care at Community Health Centers in British Columbia, Canada.

BACKGROUND: Community health centers (CHCs) in British Columbia, Canada, are using a data-driven approach to enable functions related to the design, organization, management, delivery, and evaluation of primary health care services for complex populations. METHODS: Descriptive study leveraging case studies from 4 CHCs in Vancouver, Canada, to provide an overview and examples of the functions and outputs of the Vancouver Community Analytics Tool (VCAT). Quantitative data were derived from electronic medical record data and regional emergency department data. Data were analyzed and reported by the VCAT software. RESULTS: VCAT is a health system modeling, analytics, and reporting application suite that enables operationalization of the Ten Building Blocks of High-Performing Primary Care framework via 1) creation of a virtual patient record, 2) modeling and measurement of epidemiological profiles, 3) population management and quality improvement, 4) measurement and assessment of biopsychosocial complexity, 5) empanelment, and 6) design and optimization of team-based care. The software captures data on patient pathways and service operations for over 300 service sites, including community health centers, detox centers, and emergency departments. The software integrates data on service utilization and myriad other variables for over 750,000 individuals. DISCUSSION: Using case studies, the article describes how the software helps solve practical clinical, organizational, and performance issues facing CHCs. CONCLUSIONS: VCAT models, analyzes, and visualizes the complexity profiles and service utilization patterns of complex populations, thereby enabling system administrators and clinicians to improve system performance and quality of care. The software represents a significant advance for health services research and is transforming the organization, delivery, and evaluation of primary health care services.

A Multi-sourced Data Analytics Approach to Measuring and Assessing Biopsychosocial Complexity: The Vancouver Community Analytics Tool Complexity Module (VCAT-CM).

Operationalization of the fundamental building blocks of primary care (i.e. empanelment, team-based care and population management) within the context of Community Health Centers requires accurate and real-time measures of biopsychosocial complexity, at both client and population-levels. This article describes the conceptualization, design and development of a novel software tool (the VCAT-Complexity Module) that can calculate and report real-time person-oriented biopsychosocial complexity profiles, using multiple data sources. The tool aligns with a profile approach to conceptualizing health outcomes, and represents a potentially significant advance over disease-oriented complexity assessment tools. The results and face validity of the software's complexity score outputs are discussed, along with their practical implications on functions related to the development of primary care within Vancouver Coastal Health, a Canadian Regional Health Authority.

Developing Community-Based Primary Health Care for Complex and Vulnerable Populations in the Vancouver Coastal Health Region: HealthConnection Clinic.

INTRODUCTION: Designing, delivering, and evaluating high-performing primary health care services for complex and vulnerable subpopulations are challenging endeavors. However, there is a relative paucity of research evidence available to support such work. OBJECTIVE: To provide a case study using HealthConnection Clinic, a public primary care center located in Metropolitan Vancouver's North Shore. METHODS: Developmental evaluation approach operationalizing the 10 Building Blocks of High-Performing Primary Care framework using qualitative and quantitative methods. RESULTS: The clinic provided valuable insights to policymakers and researchers related to development of the Building Blocks' foundational elements, particularly engaged leadership, empanelment, and data-driven improvement. The study highlighted the key enablers, achievements, challenges, and barriers related to operationalizing each Building Block. The Building Blocks were a useful heuristic that enabled the development and evaluation of primary care for complex subpopulations. Particularly salient from a Canadian policy perspective was the demonstration that system integration was possible when highly engaged leaders from a Regional Health Authority and a Division of Family Practice shared a common vision and purpose. HealthConnection Clinic's entrepreneurial spirit has enabled the development of innovative, evidence-based tools such as the AMPS complexity assessment tool (attachment, medical conditions, psychological/mental health/addictions challenges, and socioeconomic status), designed to identify and assess biopsychosocial complexity and needs. The study also highlighted the importance of incorporating community orientation and equity into developmental work. CONCLUSION: The study demonstrates how the Building Blocks approach can be adapted to operationalize high-performing primary care standards in settings serving complex and vulnerable populations.

An Alternative Paradigm for Evidence-Based Medicine: Revisiting Lawrence Weed, MD's Systems Approach.

Lawrence Weed, MD, is renowned for being the father of the Problem-Oriented Medical Record (POMR), the medical care standard for collecting, managing, and contextualizing patient data in medical records. What have been consistently overlooked are his teachings on knowledge coupling, which refers to matching patient data with associated medical knowledge. Together, the POMR standard and knowledge coupling are meant to form the basis of a systems approach that enables individualized evidence-based decision making within the context of multimorbidity and patient complexity.The POMR and knowledge coupling tools operationalize a problem-oriented model that reflects a sophisticated general systems theoretical approach to knowledge. This paradigm transcends reductionist approaches to knowledge by depicting how the meaning of specific entities (eg, disease constructs) and their associated probabilities can only be understood within their respective spatiotemporal and biopsychosocial relational contexts. Rigorous POMRs therefore require knowledge inputs from a network of interconnections among specific entities, which Dr Weed enabled through development of the Knowledge Net standard. The Knowledge Net's relational structure determines the applicability of knowledge within specific patient contexts. To enable the linkage of unique combinations of data in individual patient POMRs with existing medical knowledge structured in Knowledge Nets, Dr Weed developed the Knowledge Coupling standard.Dr Weed's standards for record keeping and knowledge coupling form the basis of a combinatorial approach to evidence-based medicine that fulfills Stange's call for a science of connectedness. Ensuing individualized processes of care become the dynamo powering a learning health care system that enables a co-construction of health premised on empowerment and intelligent human decision making, rather than promoting the artificial intelligence of tools. If the value of Engel's biopsychosocial model indeed relates to "guiding the parsimonious application of medical knowledge to the needs of each patient," Dr Weed's approach warrants serious consideration.