Terminations in Primary Care: a Retrospective Observational Study of 16 Primary Care Clinics.

BACKGROUND: The relationship between clinician and patient is the cornerstone of primary care. Breakdown and termination of this relationship are understudied yet important, undesirable outcomes. OBJECTIVE: To better understand the nature and extent of provider and clinic termination of the primary care relationship. DESIGN: Retrospective observational case-control study. SUBJECTS: Adult patients in Eastern Massachusetts who received primary care at hospital- and community-based clinics and health centers participating in a practice-based research network between January 2013 and June 2017. MAIN MEASURES: Formal termination by primary care physician (PCP), reasons for termination, independent predictors of termination based on mixed-effects logistic regression, and documentation of a new PCP after termination. KEY RESULTS: We identified 158,192 patients who received primary care from 182 PCPs across 16 clinics. We found 536 cases of formal termination. Clinics ranged from 4 to 119 terminations per 10,000 patients (intraclass correlation coefficient [ICC]=0.21; 95% CI: 0.18-0.24). Patient age, race/ethnicity, educational attainment, relationship status, employment status, and insurance type were independent predictors of termination (e.g., compared to patients employed full-time, patients unemployed due to disability were more likely to be terminated [adjusted OR:9.26; 95% CI: 6.74-12.74]). The most common cause for termination (38%) was appointment "no-shows" with some PCPs/clinics found to enforce a policy of dismissal following three no-shows. At the time of chart review, 201 patients (38%) had no documentation of a new PCP. Among patients who re-established care within the network, 134 (25%) had a primary care visit within 6 months of termination. CONCLUSIONS: Detailed chart review found that, unlike previous survey-based studies, dismissal was often for missed appointments based on enforcement of no-show policies. Many sociodemographic factors were associated with termination. Variability among clinics highlights the need for further research to better understand circumstances surrounding terminations, with the principal goals of improving patient-provider relationships and providing equitable care.

Professional-Patient Boundaries: a National Survey of Primary Care Physicians' Attitudes and Practices.

BACKGROUND: The essence of humanism in medicine and health care is relationships-caring relationships between clinicians and patients. While raising concerns regarding professional-patient boundaries has positively contributed to our understanding and prevention of potentially harmful boundary violations, there is controversy about which types of relationships, caring acts, and practices are acceptable versus cross boundary lines. OBJECTIVE: To examine primary care physicians' practices and attitudes regarding acts that have been questioned as potentially "inappropriate" or "unethical" crossing of professional-patient boundaries. DESIGN: Surveys conducted via in-person polling or electronic and mailed paper submissions from April 2016 to July 2017. We calculated descriptive statistics and examined associations with practices and attitudes using logistic regression. PARTICIPANTS: Random sample of all US primary care physicians who treat adult patients; convenience sample of attendees at medicine grand rounds presentations. MAIN MEASURES: Outcomes were self-reported practices and attitudes related to giving patients rides home, paying for patients' medication, helping patients find jobs, employing patients, going to dinner with patients, and providing care to personal friends. KEY RESULTS: Among 1563 total respondents, 34% had given a ride home, 34% had paid for medications, 15% helped patients find a job, 7% had employed a patient, 10% had dinner with patients, and 59% provided care to personal friends. A majority disapproved of dinner with a patient (75%) but approved of or were neutral on all other scenarios (61-90%). CONCLUSIONS: The medical profession is quite divided on questions related to drawing lines about appropriate boundaries. Contrary to official and widespread proscriptions against such practices (with exception of dinner dates), many have actually engaged in such practices and the majority found them acceptable.

Comparative Effectiveness of Second-line Antihyperglycemic Agents for Cardiovascular Outcomes: A Large-scale, Multinational, Federated Analysis of the LEGEND-T2DM Study.

Background: SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP1-RAs) reduce 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 trials. Methods: Across the LEGEND-T2DM network, we included ten federated international data sources, spanning 1992-2021. We identified 1,492,855 patients with T2DM and established cardiovascular disease (CVD) on metformin monotherapy who initiated one of four second-line agents (SGLT2is, GLP1-RAs, dipeptidyl peptidase 4 inhibitor [DPP4is], sulfonylureas [SUs]). We used large-scale propensity score models to conduct an active comparator, target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, we fit on-treatment Cox proportional hazard models for 3-point MACE (myocardial infarction, stroke, death) and 4-point MACE (3-point MACE + heart failure hospitalization) risk, and combined hazard ratio (HR) estimates in a random-effects meta-analysis. Findings: Across cohorts, 16·4%, 8·3%, 27·7%, and 47·6% of individuals with T2DM initiated SGLT2is, GLP1-RAs, DPP4is, and SUs, respectively. Over 5·2 million patient-years of follow-up and 489 million patient-days of time at-risk, there were 25,982 3-point MACE and 41,447 4-point MACE events. SGLT2is and GLP1-RAs were associated with a lower risk for 3-point MACE compared with DPP4is (HR 0·89 [95% CI, 0·79-1·00] and 0·83 [0·70-0·98]), and SUs (HR 0·76 [0·65-0·89] and 0·71 [0·59-0·86]). DPP4is were associated with a lower 3-point MACE risk versus SUs (HR 0·87 [0·79-0·95]). The pattern was consistent for 4-point MACE for the comparisons above. There were no significant differences between SGLT2is and GLP1-RAs for 3-point or 4-point MACE (HR 1·06 [0·96-1·17] and 1·05 [0·97-1·13]). Interpretation: In patients with T2DM and established CVD, we found comparable cardiovascular risk reduction with SGLT2is and GLP1-RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of GLP1-RAs and SGLT2is should be prioritized as second-line agents in those with established CVD. Funding: National Institutes of Health, United States Department of Veterans Affairs.

Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes: A Multinational, Federated Analysis of LEGEND-T2DM.

BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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. RESULTS: 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]). CONCLUSIONS: 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.

Effect of Telemedicine and the COVID-19 Pandemic on Medical Trainees' Usage of the Electronic Health Record in the Outpatient Setting.

OBJECTIVES: This study aimed to (1) determine the impact of COVID-19 (coronavirus disease 2019) and the corresponding increase in use of telemedicine on volume, efficiency, and burden of electronic health record (EHR) usage by residents and fellows; and (2) to compare these metrics with those of attending physicians. METHODS: We analyzed 11 metrics from Epic's Signal database of outpatient physician user logs for active residents/fellows at our institution across three 1-month time periods: August 2019 (prepandemic/pre-telehealth), May 2020 (mid-pandemic/post-telehealth implementation), and July 2020 (follow-up period) and compared these metrics between trainees and attending physicians. We also assessed how the metrics varied for medical trainees in primary care as compared with subspecialties. RESULTS: Analysis of 141 residents/fellows and 495 attendings showed that after telehealth implementation, overall patient volume, Time in In Basket per day, Time outside of 7 a.m. to 7 p.m., and Time in notes decreased significantly compared with the pre-telehealth period. Female residents, fellows, and attendings had a lower same day note closure rate before and during the post-telehealth implementation period and spent greater time working outside of 7 a.m. to 7 p.m. compared with male residents, fellows, and attendings (p < 0.01) compared with the pre-telehealth period. Attending physicians had a greater patient volume, spent more time, and were more efficient in the EHR compared with trainees (p < 0.01) in both the post-telehealth and follow-up periods as compared with the pre-telehealth period. CONCLUSION: The dramatic change in clinical operations during the pandemic serves as an inflection point to study changes in physician practice patterns in the EHR. We observed that (1) female physicians closed fewer notes the same day and spent more time in the EHR outside of normal working hours compared with male physicians, and (2) attending physicians had higher patient volumes and also higher efficiency in the EHR compared with resident physicians.

A Practical Approach to Optimize Computerized Provider Order Entry Systems and Reduce Clinician Burden: Pre-Post Evaluation of Vendor-Derived "Order Friction" Data.

Computerized provider order entry (CPOE) systems have been cited as a significant contributor to clinician burden. Vendor-derived measures and data sets have been developed to help with optimization of CPOE systems. We describe how we analyzed vendor-derived Order Friction (OF) EHR log data at our health system and propose a practical approach for optimizing CPOE systems by reducing OF. We also conducted a pre-post intervention study using OF data to evaluate the impact of defaulting the frequency of urine, stool and nasal swab tests and found that all modified orders had significantly fewer changes required per order (p<0.01). Our proposed approach is a six-step process: 1) understand the ordering process, 2) understand OF data elements contextually, 3) explore ordering user-level factors, 4) evaluate order volume and friction from different order sources, 5) optimize order-level design, 6) identify high volume alerts to evaluate for appropriateness.

Characteristics of Disease-Specific and Generic Diagnostic Pitfalls: A Qualitative Study.

Importance: Progress in understanding and preventing diagnostic errors has been modest. New approaches are needed to help clinicians anticipate and prevent such errors. Delineating recurring diagnostic pitfalls holds potential for conceptual and practical ways for improvement. Objectives: To develop the construct and collect examples of "diagnostic pitfalls," defined as clinical situations and scenarios vulnerable to errors that may lead to missed, delayed, or wrong diagnoses. Design, Setting, and Participants: This qualitative study used data from January 1, 2004, to December 31, 2016, from retrospective analysis of diagnosis-related patient safety incident reports, closed malpractice claims, and ambulatory morbidity and mortality conferences, as well as specialty focus groups. Data analyses were conducted between January 1, 2017, and December 31, 2019. Main Outcomes and Measures: From each data source, potential diagnostic error cases were identified, and the following information was extracted: erroneous and correct diagnoses, presenting signs and symptoms, and areas of breakdowns in the diagnostic process (using Diagnosis Error Evaluation and Research and Reliable Diagnosis Challenges taxonomies). From this compilation, examples were collected of disease-specific pitfalls; this list was used to conduct a qualitative analysis of emerging themes to derive a generic taxonomy of diagnostic pitfalls. Results: A total of 836 relevant cases were identified among 4325 patient safety incident reports, 403 closed malpractice claims, 24 ambulatory morbidity and mortality conferences, and 355 focus groups responses. From these, 661 disease-specific diagnostic pitfalls were identified. A qualitative review of these disease-specific pitfalls identified 21 generic diagnostic pitfalls categories, which included mistaking one disease for another disease (eg, aortic dissection is misdiagnosed as acute myocardial infarction), failure to appreciate test result limitations, and atypical disease presentations. Conclusions and Relevance: Recurring types of pitfalls were identified and collected from diagnostic error cases. Clinicians could benefit from knowledge of both disease-specific and generic cross-cutting pitfalls. Study findings can potentially inform educational and quality improvement efforts to anticipate and prevent future errors.

Physician Electronic Health Record Usage as Affected by the COVID-19 Pandemic.

OBJECTIVES: To utilize metrics from physician action logs to analyze volume, physician efficiency and burden as impacted by telemedicine implementation during the COVID-19 (coronavirus disease 2019) pandemic, and physician characteristics such as gender, years since graduation, and specialty category. METHODS: We selected 11 metrics from Epic Signal, a functionality of the Epic electronic health record (EHR). Metrics measuring time spent in the EHR outside working hours were used as a correlate for burden. We performed an analysis of these metrics among active physicians at our institution across three time periods-prepandemic and telehealth implementation (August 2019), postimplementation of telehealth (May 2020), and follow-up (July 2020)-and correlated them with physician characteristics. RESULTS: Analysis of 495 physicians showed that after the start of the pandemic, physicians overall had fewer appointments per day, higher same day visit closure rates, and spent less time writing notes in the EHR outside 7 a.m. to 7 p.m. on patient scheduled days. Across all three time periods, male physicians had better EHR-defined "efficiency" measures and spent less time in the EHR outside working hours. Years since graduation only had modest associations with higher same day visit closure rates and appointments per day in May 2020. Specialty category was significantly associated with appointments per day and same day closure visit rates and also was a significant factor in the observed changes seen across the three time periods. CONCLUSION: Utilizing EHR-generated reports may provide a scalable and nonintrusive way to monitor trends in physician usage and experience to help guide health systems in increasing productivity and reducing burnout.