Clinical Interviewing: An Essential but Neglected Method of Medicine.

Clinical interviewing is the basic method to understand how a person feels and what are the presenting complaints, obtain medical history, evaluate personal attitudes and behavior related to health and disease, give the patient information about diagnosis, prognosis, and treatment, and establish a bond between patient and physician that is crucial for shared decision making and self-management. However, the value of this basic skill is threatened by time pressures and emphasis on technology. Current health care trends privilege expensive tests and procedures and tag the time devoted to interaction with the patient as lacking cost-effectiveness. Instead, the time spent to inquire about problems and life setting may actually help to avoid further testing, procedures, and referrals. Moreover, the dialogue between patient and physician is an essential instrument to increase patient's motivation to engage in healthy behavior. The aim of this paper was to provide an overview of clinical interviewing and its optimal use in relation to style, flow and hypothesis testing, clinical domains, modifications according to settings and goals, and teaching. This review points to the primacy of interviewing in the clinical process. The quality of interviewing determines the quality of data that are collected and, eventually, of assessment and treatment. Thus, interviewing deserves more attention in educational training and more space in clinical encounters than it is currently receiving.

Back to basics for curricular development: A proposed framework for thinking about how interprofessional learning occurs.

The persistent difficulty of defining the mechanisms of interprofessional learning that can lead to collaborative behavior poses a challenge to evidence-based curricular design. To begin the process of building a framework for curricular development we used an inductive approach to better understand the lived experience of students engaged in an interprofessional activity. Utilizing methods from grounded theory, we analyzed reflective essays from an interprofessional classroom-based workshop for early learners at Case Western Reserve University. Students from four professional schools (medicine, nursing, social work, and dentistry) participated in facilitator guided small groups for an interactive, case-based, tabletop simulation workshop. Written reflections (N = 245) were collected, and a coding scheme was iteratively developed through constant comparison analysis in the review of a random subsample of essays (n = 19), and saturation was achieved in the second subset (n = 15). Second-order themes and four aggregate dimensions arose from the data. Aggregate dimensions were integrated into a proposed framework for the interprofessional learning process, including factors identified as necessary for the learning to occur. In this report, we describe the development of this preliminary framework, examine its components, and demonstrate potential utility in relation to established theory and research.

Association of Serious Hypoglycemic Events in Older Adults With Changes in Glycemic Performance Measures.

BACKGROUND: Reducing serious hypoglycemic events is a Federal-wide objective. Despite studies of trends for rates of serious hypoglycemia in existing literature, rigorous evaluation of links between the observed trends and changes in professional guidelines or performance measures for glycemic control is lacking. OBJECTIVE: To evaluate whether changes in professional society guidelines and performance measures for glycemic control correspond to changes in rates of serous hypoglycemia. RESEARCH DESIGN: This was a retrospective observational study. We merged Veterans Health Administration (VHA) and Medicare patient-level databases of VHA patients and identified those aged 65 years and above and receiving hypoglycemic agents. We derived age-adjusted and sex-adjusted annual rates and constructed piecewise Poisson regression models adjusting for age and sex to assess time trends of the rates. SUBJECTS: VHA patients, 2002-2015. MEASURES: The main outcome was the annual rates (2004-2015) of serious hypoglycemia, defined as hypoglycemia-related emergency department visits or hospitalizations. Secondary outcomes were annual rates of hemoglobin (Hb) A1c level <7% and >9%. Age and sex were additional variables. RESULTS: The annual rate for hypoglycemia decreased by 4.8% (rate ratio: 0.952; 95% confidence interval, 0.949-0.956) for 2008-2015 but did not change (1.001; 0.994-1.001) in 2004-2008. In 2008-2015, the annual rate for HbA1c <7% decreased by 5.0% (0.950; 0.949-0.951) but for HbA1c >9%, increased by 7.9% (1.079; 1.076-1.082). CONCLUSION: The cooccurrence of decreasing rates for HbA1c<7% and serious hypoglycemia since 2008 supports the possibility that withdrawal of a <7% HbA1c measure in 2008 impacted clinical practice and patient outcomes.

The interprofessional VA quality scholars program: Promoting predoctoral nursing scientists and their career trajectories.

BACKGROUND: The VA Quality Scholars (VAQS) program is an interprofessional fellowship that provides a unique opportunity for predoctoral nurse scientists to embed their work in quality improvement learning "laboratories" to inform their scholarship, science, and research. PURPOSE: To describe the VAQS program in relation to promoting nursing science and predoctoral nurse scientist (PhD) career trajectories, and to propose policy implications. METHOD: Data were collected on all predoctoral (PhD, DNP) nurses who entered and completed the VAQS program nationally. FINDINGS: A total of 17 predoctoral nurses (11 PhD and 6 DNP) have completed the VAQS program. Ten predoctoral PhD nurses (91%) completed their degree while in the program. Nine predoctoral PhD nurses (82%) entered a postdoctoral fellowship, and many obtained positions as faculty at research-intensive universities postfellowship. DISCUSSION: The knowledge, skills, and experiences gained by predoctoral nurse scientists from the VAQS's program contribute to their nursing research and professional career growth.

Balancing measures: identifying unintended consequences of diabetes quality performance measures in patients at high risk for hypoglycemia.

OBJECTIVE: To determine if changes in overtreatment rates were associated with changes in undertreatment rates. DESIGN: Pre-test/post-test study used cross-sectional administrative data from calendar years (CYs) 2013 and 2016. SETTING: The Veterans Health Administration. PARTICIPANTS: Patients with diabetes at risk for hypoglycemia (n = 171 875 and 166 703 in 2013 and 2016, respectively). INTERVENTION: Observational study of extant initiatives to reduce overtreatment. MAIN OUTCOME MEASURES: Overtreatment rate of diabetes defined at the proportion of patients in the group at high risk for hypoglycemia with A1c < 7.0%. Undertreatment defined as A1C > 9%. RESULTS: There was marked variation in overtreatment rates; for A1c < 7%, overtreatment rates ranged from 26.4% to 58.2% and 26.2% to 49.2% at the facility level in 2013 and 2016, respectively. The mean (±standard deviation (SD)) facility-level overtreatment rates fell from 40.3 (±5.3)% in 2013 to 37.75 (±4.70)% in 2016 (P < 0.001, paired t-test). Facility undertreatment rates ranged from 5.8% to 16.9% and 6.8% to 18.7% at the facility level in 2013 and 2016, respectively. The mean (±SD) undertreatment rate rose from 10.3 (±2.2)% in 2013 to 11.0 (±2.4)% in 2016 (P ≤ 0.001, paired t-test). However, change at individual facilities ranged from a decrease of 4.6% to an increase of 7.2%. Within year correlations were stronger than between year correlations. Overtreatment defined as A1c < 7 in this population inversely correlated strongly with undertreatment (r = -0.653, P < 0.001). CONCLUSIONS: Promotion of overtreatment reduction may be associated with an increase in undertreatment in patients with diabetes. Unintended consequence should be considered when implementing and evaluating quality measures and systems should include balancing measures to identify potential unintended harms.

Implementing team-based primary care models: a mixed-methods comparative case study in a large, integrated health care system.

BACKGROUND: Successful implementation of new care models within a health system is likely dependent on contextual factors at the individual sites of care. OBJECTIVE: To identify practice setting components contributing to uptake of new team-based care models. DESIGN: Convergent mixed-methods design. PARTICIPANTS: Employees and patients of primary care practices implementing two team-based models in a large, integrated health system. MAIN MEASURES: Field observations of 9 practices and 75 interviews, provider and staff surveys to assess adaptive reserve and burnout, analysis of quality metrics, and patient panel comorbidity scores. The data were collected simultaneously, then merged, thematically analyzed, and interpreted by a multidisciplinary team. KEY RESULTS: Based on analysis of observations and interviews, the 9 practices were categorized into 3 groups-high, partial, and low uptake of new team-based models. Uptake was related to (1) practices' responsiveness to change and (2) flexible workflow as related to team roles. Strength of local leadership and stable staffing mediated practices' ability to achieve high performance in these two domains. Higher performance on several quality metrics was associated with high uptake practices compared to the lower uptake groups. Mean Adaptive Reserve Measure and Maslach Burnout Inventory scores did not differ significantly between higher and lower uptake practices. CONCLUSION: Uptake of new team-based care delivery models is related to practices' ability to respond to change and to adapt team roles in workflow, influenced by both local leadership and stable staffing. Better performance on quality metrics may identify high uptake practices. Our findings can inform expectations for operational and policy leaders seeking to implement change in primary care practices.

Synopsis of the 2017 U.S. Department of Veterans Affairs/U.S. Department of Defense Clinical Practice Guideline: Management of Type 2 Diabetes Mellitus.

DESCRIPTION: In April 2017, the U.S. Department of Veterans Affairs (VA) and the U.S. Department of Defense (DoD) approved a joint clinical practice guideline for the management of type 2 diabetes mellitus. METHODS: The VA/DoD Evidence-Based Practice Work Group convened a joint VA/DoD guideline development effort that included a multidisciplinary panel of practicing clinician stakeholders and conformed to the Institute of Medicine's tenets for trustworthy clinical practice guidelines. The guideline panel developed key questions in collaboration with the ECRI Institute, which systematically searched and evaluated the literature through June 2016, developed an algorithm, and rated recommendations by using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. RECOMMENDATIONS: This synopsis summarizes key features of the guideline in 7 areas: patient-centered care and shared decision making, glycemic biomarkers, hemoglobin A1c target ranges, individualized treatment plans, outpatient pharmacologic treatment, glucose targets for critically ill patients, and treatment of hospitalized patients.

Using Shared Decision-Making to Address Possible Overtreatment in Patients at High Risk for Hypoglycemia: The Veterans Health Administration's Choosing Wisely Hypoglycemia Safety Initiative.

IN BRIEF Successful management of patients with diabetes requires individualizing A1C and treatment goals in conjunction with identifying and managing hypoglycemia risk. This article describes the Veterans Health Administration's Choosing Wisely Hypoglycemia Safety Initiative (CW-HSI), a voluntary program that aims to reduce the occurrence of hypoglycemia through shared decision-making about deintensifying diabetes treatment in a dynamic cohort of patients identified as being at high risk for hypoglycemia and potentially overtreated. The CW-HSI incorporates education for patients and clinicians, as well as clinical decision support tools, and has shown decreases in the proportions of high-risk patients potentially overtreated and impacts on the frequency of reported hypoglycemia.

Identification of outliers and positive deviants for healthcare improvement: looking for high performers in hypoglycemia safety in patients with diabetes.

BACKGROUND: The study objectives were to determine: (1) how statistical outliers exhibiting low rates of diabetes overtreatment performed on a reciprocal measure - rates of diabetes undertreatment; and (2) the impact of different criteria on high performing outlier status. METHODS: The design was serial cross-sectional, using yearly Veterans Health Administration (VHA) administrative data (2009-2013). Our primary outcome measure was facility rate of HbA1c overtreatment of diabetes in patients at risk for hypoglycemia. Outlier status was assessed by using two approaches: calculating a facility outlier value within year, comparator group, and A1c threshold while incorporating at risk population sizes; and examining standardized model residuals across year and A1c threshold. Facilities with outlier values in the lowest decile for all years of data using more than one threshold and comparator or with time-averaged model residuals in the lowest decile for all A1c thresholds were considered high performing outliers. RESULTS: Using outlier values, three of the 27 high performers from 2009 were also identified in 2010-2013 and considered outliers. There was only modest overlap between facilities identified as top performers based on three thresholds: A1c < 6%, A1c < 6.5%, and A1c < 7%. There was little effect of facility complexity or regional Veterans Integrated Service Networks (VISNs) on outlier identification. Consistent high performing facilities for overtreatment had higher rates of undertreatment (A1c > 9%) than VA average in the population of patients at high risk for hypoglycemia. CONCLUSIONS: Statistical identification of positive deviants for diabetes overtreatment was dependent upon the specific measures and approaches used. Moreover, because two facilities may arrive at the same results via very different pathways, it is important to consider that a "best" practice may actually reflect a separate "worst" practice.

A realist review of shared medical appointments: How, for whom, and under what circumstances do they work?

BACKGROUND: Shared medical appointments (SMAs) are doctor-patient visits in which groups of patients are seen by one or more health care providers in a concurrent session. There is a growing interest in understanding the potential benefits of SMAs in various contexts to improve clinical outcomes and reduce healthcare costs. This study builds upon the existing evidence base that suggests SMAs are indeed effective. In this study, we explored how they are effective in terms of the underlying mechanisms of action and under what circumstances. METHODS: Realist review methodology was used to synthesize the literature on SMAs, which included a broad search of 800+ published articles. 71 high quality primary research articles were retained to build a conceptual model of SMAs and 20 of those were selected for an in depth analysis using realist methodology (i.e.,middle-range theories and and context-mechanism-outcome configurations). RESULTS: Nine main mechanisms that serve to explain how SMAs work were theorized from the data immersion process and configured in a series of context-mechanism-outcome configurations (CMOs). These are: (1) Group exposure in SMAs combats isolation, which in turn helps to remove doubts about one's ability to manage illness; (2) Patients learn about disease self-management vicariously by witnessing others' illness experiences; (3) Patients feel inspired by seeing others who are coping well; (4) Group dynamics lead patients and providers to developing more equitable relationships; (5) Providers feel increased appreciation and rapport toward colleagues leading to increased efficiency; (6) Providers learn from the patients how better to meet their patients' needs; (7) Adequate time allotment of the SMA leads patients to feel supported; (8) Patients receive professional expertise from the provider in combination with first-hand information from peers, resulting in more robust health knowledge; and (9) Patients have the opportunity to see how the physicians interact with fellow patients, which allows them to get to know the physician and better determine their level of trust. CONCLUSIONS: Nine overarching mechanisms were configured in CMO configurations and discussed as a set of complementary middle-range programme theories to explain how SMAs work. It is anticipated that this innovative work in theorizing SMAs using realist review methodology will provide policy makers and SMA program planners adequate conceptual grounding to design contextually sensitive SMA programs in a wide variety of settings and advance an SMA research agenda for varied contexts.

Evaluation of the Veterans Health Administration's Specialty Care Transformational Initiatives to Promote Patient-Centered Delivery of Specialty Care: A Mixed-Methods Approach.

INTRODUCTION: Veteran's Affairs Office of Specialty Care (OSC) launched four national initiatives (Electronic-Consults [e-Consults], Specialty Care Access Networks-Extension for Community Healthcare Outcomes [SCAN-ECHO], Mini-Residencies, and Specialty Care Neighborhood) to improve specialty care delivery and funded a center to evaluate the initiatives. METHODS: The evaluation, guided by two implementation frameworks, provides formative (administrator/provider interviews and surveys) and summative data (quantitative data on patterns of use) about the initiatives to OSC. RESULTS: Evaluation of initiative implementation is assessed through CFIR (Consolidated Framework for Implementation Research)-grounded qualitative interviews to identify barriers/facilitators. Depending on high or low implementation, factors such as receiving workload credit, protected time, existing workflow/systems compatibility, leadership engagement, and access to information/resources were considered implementation barriers or facilitators. Findings were shared with OSC and used to further refine implementation at additional sites. Evaluation of other initiatives is ongoing. CONCLUSIONS: The mixed-methods approach has provided timely information to OSC about initiative effect and impacted OSC policies on implementation at additional sites.

Integrating support persons into diabetes telemonitoring to improve self-management and medication adherence.

OBJECTIVE: The purpose of this study was to investigate the potential benefits for medication adherence of integrating a patient-selected support person into an automated diabetes telemonitoring and self-management program, and to determine whether these benefits vary by patients' baseline level of psychological distress. STUDY DESIGN: The study was a quasi-experimental patient preference trial. METHODS: The study included patients with type 2 diabetes who participated in three to six months of weekly automated telemonitoring via interactive voice response (IVR) calls, with the option of designating a supportive relative or friend to receive automated updates on the patient's health and self-management, along with guidance regarding potential patient assistance. We measured long-term medication adherence using the four-point Morisky Medication Adherence Scale (MMAS-4, possible range 0-4), weekly adherence with an IVR item, and psychological distress at baseline with the Mental Composite Summary (MCS) of the SF-12. RESULTS: Of 98 initially nonadherent patients, 42% opted to involve a support person. Participants with a support person demonstrated significantly greater improvement in long-term adherence than those who participated alone (linear regression slopes: -1.17 vs. -0.57, respectively, p =0.001). Among distressed patients in particular, the odds of weekly nonadherence tended to decrease 25% per week for those with a support person (p =0.030), yet remained high for those who participated alone (p =0.820). CONCLUSIONS: Despite their multiple challenges in illness self-management, patients with diabetes who are both nonadherent and psychologically distressed may benefit by the incorporation of a support person when they receive assistance via automated telemonitoring.

Evaluation of a telementoring intervention for pain management in the Veterans Health Administration.

OBJECTIVE: Half of all Veterans experience chronic pain yet many face geographical barriers to specialty pain care. In 2011, the Veterans Health Administration (VHA) launched the Specialty Care Access Network-ECHO (SCAN-ECHO), which uses telehealth technology to provide primary care providers with case-based specialist consultation and pain management education. Our objective was to evaluate the pilot SCAN-ECHO pain management program (SCAN-ECHO-PM). DESIGN AND SETTING: This was a longitudinal observational evaluation of SCAN-ECHO-PM in seven regional VHA healthcare networks. METHODS: We identified the patient panels of primary care providers who submitted a consultation to one or more SCAN-ECHO-PM sessions. We constructed multivariable Cox proportional hazards models to assess the association between provider SCAN-ECHO-PM consultation and 1) delivery of outpatient care (physical medicine, mental health, substance use disorder, and pain medicine) and 2) medication initiation (antidepressants, anticonvulsants, and opioid analgesics). RESULTS: Primary care providers (N = 159) who presented one or more SCAN-ECHO-PM sessions had patient panels of 22,454 patients with chronic noncancer pain (CNCP). Provider consultation to SCAN-ECHO-PM was associated with utilization of physical medicine [hazard ratio (HR) 1.10, 95% confidence interval (CI) 1.05-1.14] but not mental health (HR 0.99, 95% CI 0.93-1.05), substance use disorder (HR 0.93, 95% CI 0.84-1.03) or specialty pain clinics (HR 1.01, 95% CI 0.94-1.08). SCAN-ECHO-PM consultation was associated with initiation of an antidepressant (HR 1.09, 95% CI 1.02-1.15) or anticonvulsant medication (HR 1.13, 95% CI 1.06-1.19) but not an opioid analgesic (HR 1.05, 0.99-1.10). CONCLUSIONS: SCAN-ECHO-PM was associated with increased utilization of physical medicine services and initiation of nonopioid medications among patients with CNCP. SCAN-ECHO-PM may provide a novel means of building pain management competency among primary care providers.

A Mobile Health Intervention Supporting Heart Failure Patients and Their Informal Caregivers: A Randomized Comparative Effectiveness Trial.

BACKGROUND: Mobile health (mHealth) interventions may improve heart failure (HF) self-care, but standard models do not address informal caregivers' needs for information about the patient's status or how the caregiver can help. OBJECTIVE: We evaluated mHealth support for caregivers of HF patients over and above the impact of a standard mHealth approach. METHODS: We identified 331 HF patients from Department of Veterans Affairs outpatient clinics. All patients identified a "CarePartner" outside their household. Patients randomized to "standard mHealth" (n=165) received 12 months of weekly interactive voice response (IVR) calls including questions about their health and self-management. Based on patients' responses, they received tailored self-management advice, and their clinical team received structured fax alerts regarding serious health concerns. Patients randomized to "mHealth+CP" (n=166) received an identical intervention, but with automated emails sent to their CarePartner after each IVR call, including feedback about the patient's status and suggestions for how the CarePartner could support disease care. Self-care and symptoms were measured via 6- and 12-month telephone surveys with a research associate. Self-care and symptom data also were collected through the weekly IVR assessments. RESULTS: Participants were on average 67.8 years of age, 99% were male (329/331), 77% where white (255/331), and 59% were married (195/331). During 15,709 call-weeks of attempted IVR assessments, patients completed 90% of their calls with no difference in completion rates between arms. At both endpoints, composite quality of life scores were similar across arms. However, more mHealth+CP patients reported taking medications as prescribed at 6 months (8.8% more, 95% CI 1.2-16.5, P=.02) and 12 months (13.8% more, CI 3.7-23.8, P<.01), and 10.2% more mHealth+CP patients reported talking with their CarePartner at least twice per week at the 6-month follow-up (P=.048). mHealth+CP patients were less likely to report negative emotions during those interactions at both endpoints (both P<.05), were consistently more likely to report taking medications as prescribed during weekly IVR assessments, and also were less likely to report breathing problems or weight gains (all P<.05). Among patients with more depressive symptoms at enrollment, those randomized to mHealth+CP were more likely than standard mHealth patients to report excellent or very good general health during weekly IVR calls. CONCLUSIONS: Compared to a relatively intensive model of IVR monitoring, self-management assistance, and clinician alerts, a model including automated feedback to an informal caregiver outside the household improved HF patients' medication adherence and caregiver communication. mHealth+CP may also decrease patients' risk of HF exacerbations related to shortness of breath and sudden weight gains. mHealth+CP may improve quality of life among patients with greater depressive symptoms. Weekly health and self-care monitoring via mHealth tools may identify intervention effects in mHealth trials that go undetected using typical, infrequent retrospective surveys. TRIAL REGISTRATION: ClinicalTrials.gov NCT00555360; https://clinicaltrials.gov/ct2/show/NCT00555360 (Archived by WebCite at http://www.webcitation.org/6Z4Tsk78B).

Understanding the Health Needs and Barriers to Seeking Health Care of Veteran Students in the Community.

OBJECTIVES: Access to care at Veterans Affairs facilities may be limited by long wait times; however, additional barriers may prevent US military veterans from seeking help at all. We sought to understand the health needs of veterans in the community to identify possible barriers to health-seeking behavior. METHODS: Focus groups were conducted with veteran students at a community college until thematic saturation was reached. Qualitative data analysis involved both an inductive content analysis approach and deductive elements. RESULTS: A total of 17 veteran students participated in 6 separate focus groups. Health needs affecting health-seeking behavior were identified. Themes included lack of motivation to improve health, concern about social exclusion and stigma, social interactions and behavior, limited access to affordable and convenient health care, unmet basic needs for self and family, and academics competing with health needs. CONCLUSIONS: Veterans face a range of personal, societal, and logistical barriers to accessing care. In addition to decreasing wait times for appointments, efforts to improve the transition to civilian life; reduce stigma; and offer assistance related to work, housing, and convenient access to health care may improve health in veteran students.

Quality indicators and performance measures in diabetes care.

The operations of any portion of the healthcare delivery system, eg, ambulatory care, the consultation and referral process, or hospital care, are critically dependent upon their control systems. The quality of health care produced by the system and its components is also subject to "control." One of the regulatory mechanisms involves performance measures. The development of good measures of quality is a complex and dynamic process. Within endocrinology, most measures have addressed diabetes care and most quality measurement in diabetes has focused on the ambulatory setting and mainly includes measures of process and intermediate outcomes. This review addresses quality and performance measures for diabetes, their development, characteristics, use, misuse, and future prospects.

Empowering diabetes management: The impact of patient-provider collaboration on type 2 diabetes outcomes through autonomy support and shared decision-making.

OBJECTIVES: Through the lens of self-determination theory, this quantitative study investigates how patient-provider collaboration through perceived shared decision-making (SDM) and autonomy support impact type 2 diabetes (T2D) outcomes. METHODS: We sampled 474 individuals over 18 years old who self-identified as having T2D. Completed and valid responses were received from 378 participants from two separate groups in an online survey. Data was analyzed using the IBM Statistical Package for Social Sciences (SPSS), AMOS package, version 28, and Mplus, version 8.8. RESULTS: Patient-provider collaboration through autonomy support improved treatment satisfaction (ß = .16, ρ < .05) and self-management adherence (ß = .43, ρ < .001). While collaboration through SDM improved treatment satisfaction (ß = .25, ρ < .01), it worsened SM adherence (ß = -.31, ρ < .001). The negative impact of SDM on self-management adherence was mitigated by our moderator, coping ability. However, coping ability minimally impacted treatment satisfaction and SM adherence when autonomous support was provided. CONCLUSIONS: Autonomy support increases treatment satisfaction and self-management adherence. SDM enhances treatment satisfaction but may adversely affect self-management adherence. The study also suggests that coping ability can mitigate the negative effect of SDM on self-management adherence, although its influence is limited when autonomy support is provided by the provider. PRACTICAL IMPLICATIONS: For providers, SDM and autonomy support permits shared power over treatment decisions while fostering independence over self-management tasks. Providers should evaluate patients' coping ability and adapt their approach to care based on the patient's coping capacity.

Drivers of telemedicine in primary care clinics at a large academic medical centre.

BACKGROUND: COVID-19 disrupted healthcare routines and prompted rapid telemedicine implementation. We investigated the drivers of visit modality selection (telemedicine versus in-person) in primary care clinics at an academic medical centre. METHODS: We used electronic medical record data from March 2020 to May 2022 from 13 primary care clinics (N = 21,031 new, N = 207,292 return visits), with 55% overall telemedicine use. Hierarchical logistic regression and cross-validation methods were used to estimate the variation in visit modality explained by the patient, clinician and visit factors as measured by the mean-test area under the curve (AUC). RESULTS: There was significant variation in telemedicine use across clinicians (ranging from 0-100%) for the same visit diagnosis. The strongest predictors of telemedicine were the clinician seen for new visits (mean AUC of 0.79) and the primary visit diagnosis for return visits (0.77). Models based on all patient characteristics combined accounted for relatively little variation in modality selection, 0.54 for new and 0.58 for return visits, respectively. Amongst patient characteristics, males, patients over 65 years, Asians and patient's with non-English language preferences used less telemedicine; however, those using interpreter services used significantly more telemedicine. CONCLUSION: Clinician seen and primary visit diagnoses were the best predictors of visit modality. The distinction between new and return visits and the minimal impact of patient characteristics on visit modality highlights the complexity of clinical care and warrants research approaches that go beyond linear models to uncover the emergent causal effects of specific technology features mediated by tasks, people and organisations.