Trends in Timing of and Glycemia at Initiation of Second-line Type 2 Diabetes Treatment in U.S. Adults

OBJECTIVE

Therapeutic inertia threatens the potential long-term benefits of achieving early glycemic control after type 2 diabetes diagnosis. We evaluated temporal trends in second-line diabetes medication initiation among individuals initially treated with metformin.

RESEARCH DESIGN AND METHODS

We included data from 199,042 adults with type 2 diabetes in the U.S. Department of Veterans Affairs health care system initially treated with metformin monotherapy from 2005 to 2013. We used multivariable Cox proportional hazards and linear regression to estimate associations of year of metformin monotherapy initiation with time to second-line diabetes treatment over 5 years of follow-up (primary outcome) and with hemoglobin A1c (HbA1c) at the time of second-line diabetes treatment initiation (secondary outcome).

RESULTS

The cumulative 5-year incidence of second-line medication initiation declined from 47% among metformin initiators in 2005 to 36% in 2013 counterparts (P < 0.0001) despite a gradual increase in mean HbA1c at the end of follow-up (from 6.94 ± 1.28% to 7.09 ± 1.42%, Ptrend < 0.0001). In comparisons with metformin monotherapy initiators in 2005, adjusted hazard ratios for 5-year initiation of second-line diabetes treatment ranged from 0.90 (95% CI 0.87, 0.92) for 2006 metformin initiators to 0.68 (0.66, 0.70) for 2013 counterparts. Among those receiving second-line treatment within 5 years of metformin initiation, HbA1c at second-line medication initiation increased from 7.74 ± 1.66% in 2005 metformin initiators to 8.55 ± 1.92% in 2013 counterparts (Ptrend < 0.0001).

CONCLUSIONS

We observed progressive delays in diabetes treatment intensification consistent with therapeutic inertia. Process-of-care interventions early in the diabetes disease course may be needed to reverse adverse temporal trends in diabetes care.

Effectiveness of the rural transitions nurse program for Veterans: A multicenter implementation study

BACKGROUND

Veterans are often transferred from rural areas to urban VA Medical Centers for care. The transition from hospital to home is vulnerable to postdischarge adverse events.

OBJECTIVE

To evaluate the effectiveness of the rural Transitions Nurse Program (TNP).

DESIGN, SETTING, AND PARTICIPANTS

National hybrid-effectiveness-implementation study, within site propensity-matched cohort in 11 urban VA hospitals. 3001 Veterans were enrolled in TNP from April 2017 to September 2019, and 6002 matched controls.

INTERVENTION AND OUTCOMES

The intervention was led by a transitions nurse who assessed discharge readiness, provided postdischarge communication with primary care providers (PCPs), and called the Veteran within 72 h of discharge home to assess needs, and encourage follow-up appointment attendance. Controls received usual care. The primary outcomes were PCP visits within 14 days of discharge and all-cause 30-day readmissions. Secondary outcomes were 30-day emergency department (ED) visits and 30-day mortality. Patients were matched by length of stay, prior hospitalizations and PCP visits, urban/rural status, and 32 Elixhauser comorbidities.

RESULTS

The 3001 Veterans enrolled in TNP were more likely to see their PCP within 14 days of discharge than 6002 matched controls (odds ratio = 2.24, 95% confidence interval [CI] = 2.05-2.45). TNP enrollment was not associated with reduced 30-day ED visits or readmissions but was associated with reduced 30-day mortality (hazard ratio = 0.33, 95% CI = 0.21-0.53). PCP and ED visits did not have a significant mediating effect on outcomes. The observational design, potential selection bias, and unmeasurable confounders limit causal inference.

CONCLUSIONS

TNP was associated with increased postdischarge follow-up and a mortality reduction. Further investigation to understand the reduction in mortality is needed.

Increasing enrolment in a national VA transitions of care programme: a pre-post evaluation of a data dashboard and nudge-based intervention

Background

The rural transitions nurse programme (TNP) is a care coordination intervention for high-risk veterans. An interactive dashboard was used to provide real-time performance metrics to sites as an audit and feedback tool. One-year post implementation, enrolment goals were not met. Nudge emails were introduced to increase TNP veteran enrolment. This study evaluated whether veteran enrolment increased when feedback occurred through a dashboard plus weekly nudge email versus dashboard alone.

Setting/population

This observational study included veterans who were hospitalised and discharged from four Veterans Health Administration hospitals participating in TNP.

Methods

Veteran enrolment counts between the dashboard phase and dashboard plus weekly nudge email phase were compared. Nudge emails included run charts of enrolment data. The difference of means for weekly enrolment between the two phases were calculated. After 3 months of nudge emails, a survey assessing TNP transitions nurse and physician champion perceptions of the nudge emails was distributed.

Results

The average enrolment for the four TNP sites during the ~20-month dashboard only phase was 4.23 veterans/week. The average during the 3-month dashboard plus nudge email phase was 4.21 veterans/week. The difference in means was −0.03 (p=0.73). Adjusting for time trends had no further effect. Four nurses responded to the survey. Two nurses reported neutral and two reported positive perceptions of the nudge emails.

Conclusion

Drawing attention to metrics, through nudge emails, maintained, but did not increase TNP veteran discharges compared to dashboard feedback alone.

Association of Ischemic Evaluation and Clinical Outcomes Among Patients Admitted With New-Onset Heart Failure

Background

The significant morbidity associated with systolic heart failure makes it imperative to identify patients with a reversible cause. We thus sought to evaluate the proportion of patients who received an ischemic evaluation after a hospitalization for new‐onset systolic heart failure.

Methods and Results

Patients admitted with a new diagnosis of heart failure and a reduction in left ventricular ejection fraction (≤40%) were identified in the VA Healthcare System from January 2006 to August 2017. Among those who survived 90 days without a readmission, we evaluated the proportion of patients who underwent an ischemic evaluation. We identified 9625 patients who were admitted with a new diagnosis of systolic heart failure with a concomitant reduction in ejection fraction. A minority of patients (3859, 40%) underwent an ischemic evaluation, with significant variation across high‐performing (90th percentile) and low‐performing (10th percentile) sites (odds ratio, 3.79; 95% CI, 2.90–4.31). Patients who underwent an evaluation were more likely to be treated with angiotensin‐converting enzyme inhibitors (75% versus 64%, P<0.001) or beta blockers (92% versus 82%, P<0.001) and subsequently undergo percutaneous (8% versus 0%, P<0.001) or surgical (2% versus 0%, P<0.001) revascularization. Patients with an ischemic evaluation also had a significantly lower adjusted hazard of all‐cause mortality (hazard ratio, 0.54; 95% CI, 0.47–0.61) compared with those without an evaluation.

Conclusions

Ischemic evaluations are underutilized in patients admitted with heart failure and a new reduction in left ventricular systolic function. A focused intervention to increase guideline‐concordant care could lead to an improvement in clinical outcomes.

Quantifying the incremental value of deep learning: Application to lung nodule detection

We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some domains; however, implementation of these methods is in early development. Often these methods are only directly compared to existing methods; here we present a framework for assessing the value of a machine learning model by assessing the incremental value. We developed a machine learning model to identify and classify lung nodules and assessed the incremental value added to existing risk prediction models. Multiple external datasets were used for validation. We found that our image model, trained on a dataset from The Cancer Imaging Archive (TCIA), improves upon existing models that are restricted to patient characteristics, but it was inconclusive about whether it improves on models that consider nodule features. Another interesting finding is the variable performance on different datasets, suggesting population generalization with machine learning models may be more challenging than is often considered.

Identification of Emergency Care-Sensitive Conditions and Characteristics of Emergency Department Utilization

IMPORTANCE

Monitoring emergency care quality requires understanding which conditions benefit most from timely, quality emergency care.

OBJECTIVES

To identify a set of emergency care-sensitive conditions (ECSCs) that are treated in most emergency departments (EDs), are associated with a spectrum of adult age groups, and represent common reasons for seeking emergency care and to provide benchmark national estimates of ECSC acute care utilization.

DESIGN, SETTING, AND PARTICIPANTS

A modified Delphi method was used to identify ECSCs. In a cross-sectional analysis, ECSC-associated visits by adults (aged ≥18 years) were identified based on International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes and analyzed with nationally representative data from the 2016 US Nationwide Emergency Department Sample. Data analysis was conducted from January 2018 to December 2018.

MAIN OUTCOMES AND MEASURES

Identification of ECSCs and ECSC-associated ED utilization patterns, length of stay, and charges.

RESULTS

An expert panel rated 51 condition groups as emergency care sensitive. Emergency care-sensitive conditions represented 16 033 359 of 114 323 044 ED visits (14.0%) in 2016. On average, 8 535 261 of 17 886 220 ED admissions (47.7%) were attributed to ECSCs. The most common ECSC ED visits were for sepsis (1 716 004 [10.7%]), chronic obstructive pulmonary disease (1 273 319 [7.9%]), pneumonia (1 263 971 [7.9%]), asthma (970 829 [6.1%]), and heart failure (911 602 [5.7%]) but varied by age group. Median (interquartile range) length of stay for ECSC ED admissions was longer than non-ECSC ED admissions (3.2 [1.7-5.8] days vs 2.7 [1.4-4.9] days; P < .001). In 2016, median (interquartile range) ED charges per visit for ECSCs were $2736 ($1684-$4605) compared with $2179 ($1118-$4359) per visit for non-ECSC ED visits (P < .001).

CONCLUSIONS AND RELEVANCE

This comprehensive list of ECSCs can be used to guide indicator development for pre-ED, intra-ED, and post-ED care and overall assessment of the adult, non-mental health, acute care system. Health care utilization and costs among patients with ECSCs are substantial and warrant future study of validation, variations in care, and outcomes associated with ECSCs.