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Background: The patient-centered medical home (PCMH) concept requires collaboration among clinicians both within the medical home clinic, and outside the clinic. As we redesign health information technology (HIT) to support transformation to the PCMH, we need to better understand these collaboration patterns. This study provides quantitative data describing these collaborations in order to facilitate the design of systems to allow for more efficient collaboration. Approach: Eighty-four clinicians in eight clinics identified their two most recent significant collaborators - one each within the clinic and in the medical neighborhood. They also identified the communication channels used in these collaborations. We used k-means clustering to identify communication patterns. Results: Within the clinic, half of the primary care providers (PCPs) identified a care manager as their most recent collaborator. Outside specialists were their most common external collaborators. Ninety-two percent of the non-PCP participants identified PCP's as their most recent internal collaborators, The best model for communication channel usage (p < .0001) had six clusters. In general, inside communications were more informal but outside collaborations were more often formal written communications (faxes, letters) or the exchange of electronic health record progress notes. But there were exceptions to these patterns and in many cases multiple channels were used for the same collaboration. Conclusion: Systems design (and redesign) needs to focus on reducing communications load and increasing communication effectiveness while maintaining flexibility. [ABSTRACT FROM AUTHOR]

Medication-prescribing errors generated at interfaces-in-care are the most common cause of preventable health care errors and contribute substantially to adverse patient outcomes. For this reason, standardized medication reconciliation (MR) processes need to be inserted at these interfaces. However, MR is an inherently complex task, and little data exist to inform system-based operationalization. The Portland Informatics Center addressed this challenge by creating an electronic patient-directed multimedia survey to automate the medication history collection. This article describes a research protocol designed to compare the software's medication discrepancy detection rate with traditional history collection strategies. For this randomized, controlled, single-blind trial, participants are randomly allocated into one of two groups: the control group reviews a paper list printed from the electronic record, whereas the intervention group uses a computer-assisted reconciliation survey that includes display of visual data (i.e., medication pictures). © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The goal of this study is to describe a framework that allows decision makers to efficiently evaluate factors that affect Electronic Health Record (EHR) adoption and test suitable interventions; specifically financial incentives. The United States healthcare delivery system is experiencing a transformation to improve population health. There is strong agreement that “meaningful use” of Health Information Technology (HIT) is a major enabler in this effort. However it's also understood that the high cost of implementing an EHR is an obstacle for adoption. To help understand these complexities we developed a simulation model designed to capture the dynamic nature of policy interventions that affect the adoption of EHR. We found that “Effective” use of HIT approaches break-even-point and larger clinic revenue many times faster that “average” or “poor” use of HIT. This study uses a systems perspective to the evaluate EHR adoption process through the “meaningful use” redesign as proposed in the American Reinvestment and Recovery Act 2009 in the United States healthcare industry by utilizing the System Dynamics methodology and Scenario Analysis. [ABSTRACT FROM AUTHOR]

Background: In populations with chronic illness, outcomes improve with the use of care models that integrate clinical information, evidence-based treatments, and proactive management of care. Health information technology is believed to be critical for efficient implementation of these chronic care models. Health care organizations have implemented information technologies, such as electronic medical records, to varying degrees. However, considerable uncertainty remains regarding the relative impact of specific informatics technologies on chronic illness care.Objective: To summarize knowledge and increase expert consensus regarding informatics components that support improvement in chronic illness care.Design: A systematic review of the literature was performed. "Use case" models were then developed, based on the literature review, and guidance from clinicians and national quality improvement projects. A national expert panel process was conducted to increase consensus regarding information system components that can be used to improve chronic illness care.Results: The expert panel agreed that informatics should be patient-centered, focused on improving outcomes, and provide support for illness self-management. They concurred that outcomes should be routinely assessed, provided to clinicians during the clinical encounter, and used for population-based care management. It was recommended that interactive, sequential, disorder-specific treatment pathways be implemented to quickly provide clinicians with patient clinical status, treatment history, and decision support.Conclusions: Specific informatics strategies have the potential to improve care for chronic illness. Software to implement these strategies should be developed, and rigorously evaluated within the context of organizational efforts to improve care. [ABSTRACT FROM AUTHOR]

Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials. The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM. Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis. Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13]). In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD. [ABSTRACT FROM AUTHOR]

Background: Patients with opioid use disorder (OUD) experience various forms of stigma at the individual, public, and structural levels that can affect how they access and engage with healthcare, particularly with medications for OUD treatment. Telehealth is a relatively new form of care delivery for OUD treatment. As reducing stigma surrounding OUD treatment is critical to address ongoing gaps in care, the aim of this study was to explore how telehealth impacts patient experiences of stigma. Methods: In this qualitative study, we interviewed patients with OUD at a single urban academic medical center consisting of multiple primary care and addiction clinics in Oregon, USA. Participants were eligible if they had (1) at least one virtual visit for OUD between March 2020 and December 2021, and (2) a prescription for buprenorphine not exclusively used for chronic pain. We conducted phone interviews between October and December 2022, then recorded, transcribed, dual-coded, and analyzed using reflexive thematic analysis. Results: The mean age of participants (n = 30) was 40.5 years (range 20–63); 14 were women, 15 were men, and two were transgender, non-binary, or gender-diverse. Participants were 77% white, and 33% had experienced homelessness in the prior six months. We identified four themes regarding how telehealth for OUD treatment shaped patient perceptions of and experiences with stigma at the individual (1), public (2–3), and structural levels (4): (1) Telehealth offers wanted space and improved control over treatment setting; (2) Public stigma and privacy concerns can impact both telehealth and in-person encounters, depending on clinical and personal circumstances; (3) The social distance of telehealth could mitigate or exacerbate perceptions of clinician stigma, depending on both patient and clinician expectations; (4) The increased flexibility of telehealth translated to perceptions of increased clinician trust and respect. Conclusions: The forms of stigma experienced by individuals with OUD are complex and multifaceted, as are the ways in which those experiences interact with telehealth-based care. The mixed results of this study support policies allowing for a more individualized, patient-centered approach to care delivery that allows patients a choice over how they receive OUD treatment services. [ABSTRACT FROM AUTHOR]

Background The rapidly growing field of multimorbidity research demonstrates that changes in multimorbidity in mid- and late-life have far reaching effects on important person-centered outcomes, such as health-related quality of life. However, there are few organizing frameworks and comparatively little work weighing the merits and limitations of various quantitative methods applied to the longitudinal study of multimorbidity. Methods We identify and discuss methods aligned to specific research objectives with the goals of (i) establishing a common language for assessing longitudinal changes in multimorbidity, (ii) illuminating gaps in our knowledge regarding multimorbidity progression and critical periods of change, and (iii) informing research to identify groups that experience different rates and divergent etiological pathways of disease progression linked to deterioration in important health-related outcomes. Results We review practical issues in the measurement of multimorbidity, longitudinal analysis of health-related data, operationalizing change over time, and discuss methods that align with 4 general typologies for research objectives in the longitudinal study of multimorbidity: (i) examine individual change in multimorbidity, (ii) identify subgroups that follow similar trajectories of multimorbidity progression, (iii) understand when, how, and why individuals or groups shift to more advanced stages of multimorbidity, and (iv) examine the coprogression of multimorbidity with key health domains. Conclusions This work encourages a systematic approach to the quantitative study of change in multimorbidity and provides a valuable resource for researchers working to measure and minimize the deleterious effects of multimorbidity on aging populations. [ABSTRACT FROM AUTHOR]

Purpose: We conducted a randomized controlled trial to compare the effectiveness of adding various forms of enhanced external support to practice facilitation on primary care practices' clinical quality measure (CQM) performance.Methods: Primary care practices across Washington, Oregon, and Idaho were eligible if they had fewer than 10 full-time clinicians. Practices were randomized to practice facilitation only, practice facilitation and shared learning, practice facilitation and educational outreach visits, or practice facilitation and both shared learning and educational outreach visits. All practices received up to 15 months of support. The primary outcome was the CQM for blood pressure control. Secondary outcomes were CQMs for appropriate aspirin therapy and smoking screening and cessation. Analyses followed an intention-to-treat approach.Results: Of 259 practices recruited, 209 agreed to be randomized. Only 42% of those offered educational outreach visits and 27% offered shared learning participated in these enhanced supports. CQM performance improved within each study arm for all 3 cardiovascular disease CQMs. After adjusting for differences between study arms, CQM improvements in the 3 enhanced practice support arms of the study did not differ significantly from those seen in practices that received practice facilitation alone (omnibus P = .40 for blood pressure CQM). Practices randomized to receive both educational outreach visits and shared learning, however, were more likely to achieve a blood pressure performance goal in 70% of patients compared with those randomized to practice facilitation alone (relative risk = 2.09; 95% CI, 1.16-3.76).Conclusions: Although we found no significant differences in CQM performance across study arms, the ability of a practice to reach a target level of performance may be enhanced by adding both educational outreach visits and shared learning to practice facilitation. [ABSTRACT FROM AUTHOR]

Background: Early advance care planning (ACP) conversations are essential to deliver patient-centered care. While primary care is an ideal setting to initiate ACP, such as Serious Illness Conversations (SICs), many barriers exist to implement such conversations in routine practice. An interprofessional team approach holds promises to address barriers. Objective: To develop and evaluate SIC training for interprofessional primary care teams (IP-SIC). Design: An existing SIC training was adapted for IP-SIC and then implemented and evaluated for acceptability and effectiveness. Setting/Context: Interprofessional teams in 15 primary care clinics in five US states. Measures: Acceptability of the IP-SIC training and participants' self-reported likelihood to engage in ACP after the training. Results: The 156 participants were a mix of physicians and advanced practice providers (APPs) (44%), nurses and social workers (31%), and others (25%). More than 90% of all participants rated the IP-SIC training positively. While nurse/social worker and other groups were less likely than physician and APP group to engage in ACP before training (4.4, 3.7, and 6.4 on a 1–10 scale, respectively), all groups showed significant increase in likelihood to engage in ACP after the IP-SIC training (8.5, 7.7, and 9.2, respectively). Both physician/APP and nurse/social worker groups showed significant increase in likelihood to use the SIC Guide after the IP-SIC training, whereas an increase in likelihood to use SIC Guide among other groups was not statistically significant. Conclusion: The new IP-SIC training was well accepted by interprofessional team members and effective to improve their likelihood to engage in ACP. Further research exploring how to facilitate collaboration among interprofessional team members to maximize opportunities for more and better ACP is warranted. ClinicalTrials.gov ID: NCT03577002 [ABSTRACT FROM AUTHOR]

"Research Data Sharing: A Maturity Model for Organizational Capacity" can also serve as a tool to guide a gap analysis, helping organizations identify specific resource investments and interventions to increase their data sharing performance. Rule 1: Use a maturity model to understand organizational qualities that impact data sharing Organizations need to understand their baseline capabilities for data sharing, and a maturity model can facilitate this assessment. We consider an institution's organizational culture about data sharing to encompass how leaders and researchers generally interpret data sharing, how its reward systems express these attitudes, and how it treats decisions for engaging with new data sharing opportunities and best practices. [Extracted from the article]