Impact of Nurse Residency Program on Time-to-Fill Nurse Vacancies at the Veterans Health Administration.

BACKGROUND: The Department of Veterans Affairs (VA) offers a 1-year Post-Baccalaureate-Registered Nurse Residency (PB-RNR) Program. The impact of the PB-RNR program on local RN recruitment was unknown. OBJECTIVES: We aimed to evaluate the effect of the size of the PB-RNR program at a VA facility on its time-to-fill RN vacancies. PROJECT DESIGN: We used an instrumental variable approach with a 2-stage residual inclusion specification. SUBJECTS: We included RN filled vacancies in the VA that were posted nationwide between 2020 and 2021. MEASURES: Our independent variable was the facility-year level number of PB-RNR program allocations. The 3 binary outcomes were whether the RN vacancy was filled within 90, 60, or 30 days. RESULTS: An increase of one training allocation was significantly associated with a 5.60 percentage point (PP) (95% CI: 2.74-8.46) higher likelihood of filling a vacancy within 90 days, 7.34 PP (95% CI: 4.66-10.03) higher likelihood of filling a vacancy within 60 days, and 5.32 PP (95% CI: 3.18-7.46) higher likelihood of filling a vacancy within 30 days. The impact was significant in both 2020 and 2021 positions, and in facilities located in areas with lower social deprivation scores, higher-quality public schools, or with either no or partial primary care physician shortages. CONCLUSIONS: We found favorable impacts of the size of the PB-RNR program at a VA facility on filling RN vacancies.

Effect of the Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act Scribes Trial on Emergency Department Provider Productivity and Patient Throughput Times.

BACKGROUND: To help improve access to care, section 507 of the VA MISSION (Maintaining Internal Systems and Strengthening Integrated Outside Networks) Act of 2018 mandated a 2-year trial of medical scribes in the Veterans Health Administration (VHA). OBJECTIVE: The impact of scribes on provider productivity and patient throughput time in VHA emergency departments (EDs) was evaluated. METHODS: A clustered randomized trial was designed using intent-to-treat difference-in-differences analysis. The intervention period was from June 30, 2020 to July 1, 2022. The trial included six intervention and six comparison ED clinics. Two ED providers who volunteered to participate in the trial were assigned two scribes each. Scribes assisted providers with documentation and visit-related activities. The outcomes were provider productivity and patient throughput time per clinic-pay period. RESULTS: Randomization to intervention resulted in decreased provider productivity and increased patient throughput time. In adjusted regression models, randomization to scribes was associated with a decrease of 8.4 visits per full-time equivalent (95% confidence interval [CI] 12.4-4.3; p < 0.001) and 0.5 patients per day per provider (95% CI 0.8-0.3; p < 0.001). Intervention was associated with increases in length of stay of 29.1 min (95% CI 21.2-36.9 min; p < 0.001), 6.3 min in door to doctor (95% CI 2.9-9.6 min; p < 0.001), 19.5 min in door to disposition (95% CI 13.2-25.9 min; p < 0.001), and 13.7 min in doctor to disposition (95% CI 8.8-18.6 min; p < 0.001). CONCLUSIONS: Scribes were associated with decreased provider productivity and increased patient throughput time in VHA EDs. Although scribes may have contributed to improvements in other dimensions of quality, further examination of the ways in which scribes were used is advisable before widespread adoption in VHA EDs.

Caring Letters Sent by a Clinician or Peer to At-Risk Veterans: A Randomized Clinical Trial.

Importance: Caring letters is an evidence-based suicide prevention intervention in acute care settings, but its outcomes among individuals who contact a national crisis line have not previously been evaluated. Objective: To examine the outcomes of the Veterans Crisis Line (VCL) caring letters intervention and determine whether there are differences in outcomes by signatory. Design, Setting, and Participants: This parallel randomized clinical trial compared signatories of caring letters and used an observational design to compare no receipt of caring letters with any caring letters receipt. Participants included veterans who contacted the VCL. Enrollment occurred between June 11, 2020, and June 10, 2021, with 1 year of follow-up. Analyses were completed between July 2022 and August 2023. Intervention: Veterans were randomized to receive 9 caring letters for 1 year from either a clinician or peer veteran signatory. Main Outcomes and Measures: The primary outcome measure was suicide attempt incidence in the 12 months following the index VCL contact. Incidence of Veterans Health Administration (VHA) inpatient, outpatient, and emergency health care use were secondary outcomes. All-cause mortality was an exploratory outcome. Wilcoxon rank-sum tests and χ2 tests were used to assess the differences in outcomes among the treatment and comparison groups. Results: A total of 102 709 veterans (86 942 males [84.65%]; 15 737 females [15.32%]; mean [SD] age, 53.82 [17.35] years) contacted the VCL and were randomized. No association was found among signatory and suicide attempts, secondary outcomes, or all-cause mortality. In the analysis of any receipt of caring letters, there was no evidence of an association between caring letters receipt and suicide attempt incidence. Caring letters receipt was associated with increased VHA health care use (any outpatient: hazard ratio [HR], 1.10; 95% CI, 1.08-1.13; outpatient mental health: HR, 1.19; 95% CI, 1.17-1.22; any inpatient: HR, 1.13; 95% CI, 1.08-1.18; inpatient mental health: HR, 1.14; 95% CI, 1.07-1.21). Caring letters receipt was not associated with all-cause mortality. Conclusions and Relevance: Among VHA patients who contacted the VCL, caring letters were not associated with suicide attempts, but were associated with a higher probability of health care use. No differences in outcomes were identified by signatory. Trial Registration: isrctn.org Identifier: ISRCTN27551361.

Costs and Productivity Benefits of the Department of Veterans Affairs Maintaining Internal Systems and Strengthening Integrated Outside Networks Act Scribes Trial.

OBJECTIVES: To improve access, the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 mandated a 2-year study of medical scribes in Veterans Health Administration specialty clinics and emergency departments. Medical scribes are employed in clinical settings with the goals of increasing provider productivity and satisfaction by minimizing physicians' documentation burden. Our objective is to quantify the economic outcomes of the MISSION Act scribes trial. METHODS: A cluster-randomized trial was designed with 12 Department of Veterans Affairs (VA) medical centers randomized into the intervention. We estimated the total cost of the trial, cost per scribe-year, and projected cost of hiring additional physicians to achieve the observed scribe productivity benefits in relative value units and visits per full-time-equivalent over the 2-year intervention period (June 30, 2020 to July 1, 2022). RESULTS: The estimated cost of the trial was $4.6 million, below the Congressional Budget Office estimate of $5 million. A full-time scribe-year cost approximately $74 600 through contracting and $62 900 through VA hiring. Randomization into the trial led to an approximate 30% increase in productivity in cardiology and 20% in orthopedics. The projected incremental cost of using additional physicians instead of scribes to achieve the same productivity benefits was nearly $1.7 million more, or 75% higher, than the observed cost of scribes in cardiology and orthopedics. CONCLUSIONS: As the largest randomized trial of scribes to date, the MISSION Act scribes trial provides important evidence on the costs and benefits of scribes. Improving productivity enhances access and scribes may give VA a new tool to improve productivity in specialty care at a lower cost than hiring additional providers.

Impact of Medical Training Programs on Time-to-Fill Physician Vacancies at the Veterans Health Administration.

BACKGROUND: The Department of Veterans Affairs (VA) provides the largest Graduate Medical Education (GME) training platform for health professionals in the United States. Studies on the impact of VA GME programs on physician recruitment were lacking. OBJECTIVES: To examine the impact of the size of residency training programs at a VA facility on the facility's time-to-fill physician vacancies, and whether the impact differs by the socioeconomic deprivation and public school quality of the geographic area. PROJECT DESIGN: We constructed an instrumental variable for training program size by interacting the facility clinicians share with the total training allocation nationally. SUBJECTS: Our evaluation used national data on filled physician vacancies in the VA that were posted between 2020 and 2021. MEASURES: The outcome evaluated was time-to-fill physician vacancies. Our explanatory variable was the facility-year level number of physician residency slots. RESULTS: For positions posted in 2020, an increase of one training slot was significantly associated with a decrease of 1.33 days to fill physician vacancies (95% CI, 0.38-2.28) in facilities in less deprived areas, a decrease of 1.50 days (95% CI, 0.75-2.25) in facilities with better public schools, a decrease of 3.30 days (95% CI, 0.85-5.76) in facilities in both less deprived areas and better public schools. We found similar results for positions posted in 2020 and 2021 when limiting time-to-fill to <500 days. CONCLUSIONS: We found that increasing the size of the residency program at a VA facility could decrease the facility's time-to-fill vacant physician positions in places with less socioeconomic deprivation or better public schools.

Differences in adverse outcomes across race and ethnicity among Veterans with similar predicted risks of an overdose or suicide-related event.

OBJECTIVE: To evaluate the degree to which differences in incidence of mortality and serious adverse events exist across patient race and ethnicity among Veterans Health Administration (VHA) patients receiving outpatient opioid prescriptions and who have similar predicted risks of adverse outcomes. Patients were assigned scores via the VHA Stratification Tool for Opioid Risk Mitigation (STORM), a model used to predict the risk of experiencing overdose- or suicide-related health care events or death. Individuals with the highest STORM risk scores are targeted for case review. DESIGN: Retrospective cohort study of high-risk veterans who received an outpatient prescription opioid between 4/2018-3/2019. SETTING: All VHA medical centers. PARTICIPANTS: In total, 84 473 patients whose estimated risk scores were between 0.0420 and 0.0609, the risk scores associated with the top 5%-10% of risk in the STORM development sample. METHODS: We examined the expected probability of mortality and serious adverse events (SAEs; overdose or suicide-related events) given a patient's risk score and race. RESULTS: Given a similar risk score, Black patients were less likely than White patients to have a recorded SAE within 6 months of risk score calculation. Black, Hispanic, and Asian patients were less likely than White patients with similar risk scores to die within 6 months of risk score calculation. Some of the mortality differences were driven by age differences in the composition of racial and ethnic groups in our sample. CONCLUSIONS: Our results suggest that relying on the STORM model to identify patients who may benefit from an interdisciplinary case review may identify patients with clinically meaningful differences in outcome risk across race and ethnicity.

Effect of a National VHA Medical Scribe Pilot on Provider Productivity, Wait Times, and Patient Satisfaction in Cardiology and Orthopedics.

BACKGROUND: Section 507 of the VA MISSION Act of 2018 mandated a 2-year pilot study of medical scribes in the Veterans Health Administration (VHA), with 12 VA Medical Centers randomly selected to receive scribes in their emergency departments or high wait time specialty clinics (cardiology and orthopedics). The pilot began on June 30, 2020, and ended on July 1, 2022. OBJECTIVE: Our objective was to evaluate the impact of medical scribes on provider productivity, wait times, and patient satisfaction in cardiology and orthopedics, as mandated by the MISSION Act. DESIGN: Cluster randomized trial, with intent-to-treat analysis using difference-in-differences regression. PATIENTS: Veterans using 18 included VA Medical Centers (12 intervention and 6 comparison sites). INTERVENTION: Randomization into MISSION 507 medical scribe pilot. MAIN MEASURES: Provider productivity, wait times, and patient satisfaction per clinic-pay period. KEY RESULTS: Randomization into the scribe pilot was associated with increases of 25.2 relative value units (RVUs) per full-time equivalent (FTE) (p < 0.001) and 8.5 visits per FTE (p = 0.002) in cardiology and increases of 17.3 RVUs per FTE (p = 0.001) and 12.5 visits per FTE (p = 0.001) in orthopedics. We found that the scribe pilot was associated with a decrease of 8.5 days in request to appointment day wait times (p < 0.001) in orthopedics, driven by a 5.7-day decrease in appointment made to appointment day wait times (p < 0.001), and observed no change in wait times in cardiology. We also observed no declines in patient satisfaction with randomization into the scribe pilot. CONCLUSIONS: Given the potential improvements in productivity and wait times with no change in patient satisfaction, our results suggest that scribes may be a useful tool to improve access to VHA care. However, participation in the pilot by sites and providers was voluntary, which could have implications for scalability and what effects could be expected if scribes were introduced to the care process without buy-in. Cost was not considered in this analysis but is an important factor for future implementation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04154462.

Excess Mortality at Veterans Health Administration Facilities During the COVID-19 Pandemic.

IMPORTANCE: The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand the characteristics of facilities that experienced the highest and lowest pandemic-related mortality to inform future mitigation efforts. OBJECTIVE: To identify facility-level excess mortality during the pandemic and to correlate these estimates with facility characteristics and community-wide rates of COVID-19 burden. DESIGN: We used pre-pandemic data to estimate mortality risk prediction models using 5-fold cross-validation and Poisson quasi-likelihood regression. We then estimated excess mortality and observed versus expected (O/E) mortality ratios by the VHA facility from March to December 2020. We examined facility-level characteristics by excess mortality quartile. PARTICIPANTS: Overall, there were 11.4 million VHA enrollees during 2016 and 2020. MAIN MEASURES: Facility-level O/E mortality ratios and excess all-cause mortality. RESULT: VHA-enrolled veterans experienced 52,038 excess deaths from March to December 2020, equating to 16.8% excess mortality. Facility-specific rates ranged from -5.5% to +63.7%. Facilities in the lowest quartile for excess mortality experienced fewer COVID-19 deaths (0.7-1.51, P <0.001) and cases (52.0-63.0, P =0.002) per 1,000 population compared with the highest quartile. The highest quartile facilities had more hospital beds (276.7-187.6, P =0.024) and a higher percent change in the share of visits conducted via telehealth from 2019 to 2020 (183%-133%, P <0.008). CONCLUSIONS: There was a large variation in mortality across VHA facilities during the pandemic, which was only partially explained by the local COVID-19 burden. Our work provides a framework for large health care systems to identify changes in facility-level mortality during a public health emergency.

Effect of a Predictive Analytics-Targeted Program in Patients on Opioids: a Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: Risk of overdose, suicide, and other adverse outcomes are elevated among sub-populations prescribed opioid analgesics. To address this, the Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM)-a provider-facing dashboard that utilizes predictive analytics to stratify patients prescribed opioids based on risk for overdose/suicide. OBJECTIVE: To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans. DESIGN: A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020. PARTICIPANTS: A total of 44,042 patients actively prescribed opioid analgesics with high STORM risk scores (i.e., percentiles 1% to 5%) for an overdose or suicide-related event. INTERVENTION: A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide. MAIN MEASURES: Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality. KEY RESULTS: Mandated review inclusion was associated with a significant decrease in all-cause mortality within 4 months of inclusion (OR: 0.78; 95% CI: 0.65-0.94). There was no detectable effect on SAEs. Stepped-wedge analyses found that mandated review patients were five times more likely to receive a case review than non-mandated patients with similar risk (OR: 5.1; 95% CI: 3.64-7.23) and received more risk mitigation strategies than non-mandated patients (0.498; CI: 0.39-0.61). CONCLUSIONS: Among VHA patients prescribed opioid analgesics, identifying high risk patients and mandating they receive an interdisciplinary case review was associated with a decrease in all-cause mortality. Results suggest that providers can leverage predictive analytic-targeted population health approaches and interdisciplinary collaboration to improve patient outcomes. TRIAL REGISTRATION: ISRCTN16012111.

Racial and ethnic disparities in excess mortality among U.S. veterans during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic disproportionately affected racial and ethnic minorities among the general population in the United States; however, little is known regarding its impact on U.S. military Veterans. In this study, our objectives were to identify the extent to which Veterans experienced increased all-cause mortality during the COVID-19 pandemic, stratified by race and ethnicity. DATA SOURCES: Administrative data from the Veterans Health Administration's Corporate Data Warehouse. STUDY DESIGN: We use pre-pandemic data to estimate mortality risk models using five-fold cross-validation and quasi-Poisson regression. Models were stratified by a combined race-ethnicity variable and included controls for major comorbidities, demographic characteristics, and county fixed effects. DATA COLLECTION: We queried data for all Veterans residing in the 50 states plus Washington D.C. during 2016-2020. Veterans were excluded from analyses if they were missing county of residence or race-ethnicity data. Data were then aggregated to the county-year level and stratified by race-ethnicity. PRINCIPAL FINDINGS: Overall, Veterans' mortality rates were 16% above normal during March-December 2020 which equates to 42,348 excess deaths. However, there was substantial variation by racial and ethnic group. Non-Hispanic White Veterans experienced the smallest relative increase in mortality (17%, 95% CI 11%-24%), while Native American Veterans had the highest increase (40%, 95% CI 17%-73%). Black Veterans (32%, 95% CI 27%-39%) and Hispanic Veterans (26%, 95% CI 17%-36%) had somewhat lower excess mortality, although these changes were significantly higher compared to White Veterans. Disparities were smaller than in the general population. CONCLUSIONS: Minoritized Veterans experienced higher rates excess of mortality during the COVID-19 pandemic compared to White Veterans, though with smaller differences than the general population. This is likely due in part to the long-standing history of structural racism in the United States that has negatively affected the health of minoritized communities via several pathways including health care access, economic, and occupational inequities.

In-home environmental exposures predicted from geospatial characteristics of the built environment and electronic health records of children with asthma.

PURPOSE: Children may be exposed to numerous in-home environmental exposures (IHEE) that trigger asthma exacerbations. Spatially linking social and environmental exposures to electronic health records (EHR) can aid exposure assessment, epidemiology, and clinical treatment, but EHR data on exposures are missing for many children with asthma. To address the issue, we predicted presence of indoor asthma trigger allergens, and estimated effects of their key geospatial predictors. METHODS: Our study samples were comprised of children with asthma who provided self-reported IHEE data in EHR at a safety-net hospital in New England during 2004-2015. We used an ensemble machine learning algorithm and 86 multilevel features (e.g., individual, housing, neighborhood) to predict presence of cockroaches, rodents (mice or rats), mold, and bedroom carpeting/rugs in homes. We reduced dimensionality via elastic net regression and estimated effects by the G-computation causal inference method. RESULTS: Our models reasonably predicted presence of cockroaches (area under receiver operating curves [AUC] = 0.65), rodents (AUC = 0.64), and bedroom carpeting/rugs (AUC = 0.64), but not mold (AUC = 0.54). In models adjusted for confounders, higher average household sizes in census tracts were associated with more reports of pests (cockroaches and rodents). Tax-exempt parcels were associated with more reports of cockroaches in homes. Living in a White-segregated neighborhood was linked with lower reported rodent presence, and mixed residential/commercial housing and newer buildings were associated with more reports of bedroom carpeting/rugs in bedrooms. CONCLUSIONS: We innovatively applied a machine learning and causal inference mixture methodology to detail IHEE among children with asthma using EHR and geospatial data, which could have wide applicability and utility.

County-Level Impact of the COVID-19 Pandemic on Excess Mortality Among U.S. Veterans: A Population-Based Study.

BACKGROUND: As the novel coronavirus (COVID-19) continues to impact the world at large, Veterans of the US Armed Forces are experiencing increases in both COVID-19 and non-COVID-19 mortality. Veterans may be more susceptible to the pandemic than the general population due to their higher comorbidity burdens and older age, but no research has examined if trends in excess mortality differ between these groups. Additionally, individual-level data on demographics, comorbidities, and deaths are provided in near-real time for all enrolees of the Veterans Health Administration (VHA). These data provide a unique opportunity to identify excess mortality throughout 2020 at a subnational level, and to validate these estimates against local COVID-19 burden. METHODS: We queried VHA administrative data on demographics and comorbidities for 11.4 million enrolees during 2016-2020. Pre-pandemic data was used to develop and cross-validate eight mortality prediction models at the county-level including Poisson, Poisson quasi-likelihood, negative binomial, and generalized estimating equations. We then estimated county-level excess Veteran mortality during 2020 and correlated these estimates with local rates of COVID-19 confirmed cases and deaths. FINDINGS: All models demonstrated excellent agreement between observed and predicted mortality during 2016-2019; a Poisson quasi-likelihood with county fixed effects minimized median squared error with a calibration slope of 1.00. Veterans of the U.S. Armed Forces faced an excess mortality rate of 13% in 2020, which corresponds to 50,299 excess deaths. County-level estimates of excess mortality were correlated with both COVID-19 cases (R2=0.77) and deaths per 1,000 population (R2=0.59). INTERPRETATION: We developed sub-national estimates of excess mortality associated with the pandemic and shared our data as a resource for researchers and data journalists. Despite Veterans' greater likelihood of risk factors associated with severe COVID-19 illness, their excess mortality rate was slightly lower than the general population. Consistent access to health care and the rapid expansion of VHA telemedicine during the pandemic may explain this divergence. FUNDING: This work was supported by grants from the Department of Veterans Affairs Quality Enhancement Research Initiative [PEC 16-001]. Dr. Griffith's effort was supported in part by the Agency for Healthcare Research & Quality [K12 HS026395].

Likelihood of COVID-19 reinfection in an urban community cohort in Massachusetts.

Background: Understanding the association of prior SARS-CoV-2 infection with subsequent reinfection has public health relevance. Objective: To explore COVID-19 severity and SARS-CoV-2 infection and reinfection rates. Design: Retrospective cohort study. Setting: Boston, Massachusetts, during the first COVID-19 surge (01/01/2020-05/31/2020; Period-1) and after the first surge (06/01/2020-02/28/2021; Period-2); Period-2 included the second surge (11/01/2020-02/28/2021). Participants: Patients in an academic medical center and six community health centers who received a clinical diagnosis of COVID-19 between 01/01/2020 and 05/31/2020 or SARS-CoV-2 testing between 01/01/2020 and 02/28/2021. Measurements: COVID-19 severity was compared between Period-1 and Period-2. Poisson regression models adjusted for demographic variables, medical comorbidities, and census tract were used to assess reinfection risk among patients with COVID-19 diagnoses or SARS-CoV-2 testing during Period-1 and additional SARS-CoV-2 testing during Period-2. Results: Among 142,047 individuals receiving SARS-CoV-2 testing or clinical diagnoses during the study period, 15.8% were infected. Among COVID-19 patients, 22.5% visited the emergency department, 13% were hospitalized, and 4% received critical care. Healthcare utilization was higher during Period-1 than Period-2 (22.9% vs. 18.9% emergency department use, 14.7% vs. 9.9% hospitalization, 5.5% vs. 2.5% critical care; p < 0.001). Reinfection was assessed among 8961 patients with a SARS-CoV-2 test or COVID-19 diagnosis in Period-1 who underwent additional testing in Period-2. A total of 2.7% (n = 65/2431) with SARS-CoV-2 in Period-1 tested positive in Period-2, compared with 12.6% (n = 821/6530) of those who initially tested negative (IRR of reinfection = 0.19, 95% CI: 0.15-0.25). Conclusions: Prior SARS-CoV-2 infection among this observational cohort was associated with an 81% lower reinfection rate.

Increased Hemoglobin A1c Time in Range Reduces Adverse Health Outcomes in Older Adults With Diabetes.

OBJECTIVE: Short- and long-term glycemic variability are risk factors for diabetes complications. However, there are no validated A1C target ranges or measures of A1C stability in older adults. We evaluated the association of a patient-specific A1C variability measure, A1C time in range (A1C TIR), on major adverse outcomes. RESEARCH DESIGN AND METHODS: We conducted a retrospective observational study using administrative data from the Department of Veterans Affairs and Medicare from 2004 to 2016. Patients were ≥65 years old, had diabetes, and had at least four A1C tests during a 3-year baseline period. A1C TIR was the percentage of days during the baseline in which A1C was in an individualized target range (6.0-7.0% up to 8.0-9.0%) on the basis of clinical characteristics and predicted life expectancy. Increasing A1C TIR was divided into categories of 20% increments and linked to mortality and cardiovascular disease (CVD) (i.e., myocardial infarction, stroke). RESULTS: The study included 402,043 veterans (mean [SD] age 76.9 [5.7] years, 98.8% male). During an average of 5.5 years of follow-up, A1C TIR had a graded relationship with mortality and CVD. Cox proportional hazards models showed that lower A1C TIR was associated with increased mortality (A1C TIR 0 to <20%: hazard ratio [HR] 1.22 [95% CI 1.20-1.25]) and CVD (A1C TIR 0 to <20%: HR 1.14 [95% CI 1.11-1.19]) compared with A1C TIR 80-100%. Competing risk models and shorter follow-up (e.g., 24 months) showed similar results. CONCLUSIONS: In older adults with diabetes, maintaining A1C levels within individualized target ranges is associated with lower risk of mortality and CVD.

Appointment wait time data for primary & specialty care in veterans health administration facilities vs. community medical centers.

The datasets summarized in this article include more than 38 million appointment wait times that U.S. military veterans experienced when seeking medical care since January 2014. Our data include both within Veterans Health Administration (VHA) facilities and community medical centers, and wait times are stratified by primary/specialty care type. Deidentified wait time data are reported at the referral-level, at the VHA facility-level, and at the patient's 3-digit ZIP code-level. As of this writing, no other U.S. health care system has made their wait times publicly available. Our data thus represent the largest, national, and most representative measures of timely access to care for patients of both VHA and community providers. Researchers may use these datasets to identify variations in appointment wait times both longitudinally and cross-sectionally, conduct research on policies and interventions to improve access to care, and to incorporate fine-grained measures of wait times into their analyses.

Provider and Practice Experience Integrating the Dose-HPV Intervention into Clinical Practice.

INTRODUCTION: Few studies have rigorously evaluated the drivers of successful implementation of interventions to improve human papillomavirus (HPV) vaccination rates. The aim of this study was to evaluate the implementation of Development of Systems and Education for HPV Vaccination (DOSE HPV), a performance improvement intervention. METHODS: Primary care providers (PCPs), nurses, and individuals with leadership roles from pediatric and family medicine practices who attended DOSE HPV intervention sessions participated in qualitative interviews immediately following intervention completion. The study team professionally transcribed interviews and performed qualitative coding using inductive methods. Final analysis employed the Promoting Action on Research implementation in Health Services (PARiHS) model. RESULTS: Twenty-six individuals participated: 12 PCPs, 5 nurses, and 9 individuals with dual leadership and PCP roles. Participants described five factors that they felt contributed to program success: (1) evidence-based, goal-directed education; (2) personalized data feedback; (3) clinical leadership support; (4) collaborative facilitation; (5) repeated contacts/longitudinal structure of the intervention. Barriers to implementing the intervention included: (1) inability to standardize workflow across practices; (2) low pediatric volume, (3) competing priorities/lack of incentives, (4) ineffective involvement of nurses, (5) poor communication between clinical leadership and staff. DISCUSSION: Although many HPV testing interventions have been implemented, findings have been mixed. It is clear that having an effective, evidence-based intervention by itself is not enough to get it into practice. Rather, it is crucial to consider implementation factors to ensure consistent implementation and sustainability. Key factors for the success of the DOSE HPV intervention appear to include a collaborative approach, provision of useful evidence to motivate behavior change, and repeated contacts to ensure accountability for implementing changes. Workflow issues, ineffective lines of communication, and competing priorities at both the visit and the patient and population management levels can hinder implementation.

Developing and evaluating a pediatric asthma severity computable phenotype derived from electronic health records.

BACKGROUND: Extensive data available in electronic health records (EHRs) have the potential to improve asthma care and understanding of factors influencing asthma outcomes. However, this work can be accomplished only when the EHR data allow for accurate measures of severity, which at present are complex and inconsistent. OBJECTIVE: Our aims were to create and evaluate a standardized pediatric asthma severity phenotype based in clinical asthma guidelines for use in EHR-based health initiatives and studies and also to examine the presence and absence of these data in relation to patient characteristics. METHODS: We developed an asthma severity computable phenotype and compared the concordance of different severity components contributing to the phenotype to trends in the literature. We used multivariable logistic regression to assess the presence of EHR data relevant to asthma severity. RESULTS: The asthma severity computable phenotype performs as expected in comparison with national statistics and the literature. Severity classification for a child is maximized when based on the long-term medication regimen component and minimized when based only on the symptom data component. Use of the severity phenotype results in better, clinically grounded classification. Children for whom severity could be ascertained from these EHR data were more likely to be seen for asthma in the outpatient setting and less likely to be older or Hispanic. Black children were less likely to have lung function testing data present. CONCLUSION: We developed a pragmatic computable phenotype for pediatric asthma severity that is transportable to other EHRs.

Improving HPV Vaccination Rates: A Stepped-Wedge Randomized Trial.

OBJECTIVES: To evaluate the effectiveness of a stepped-wedge randomized trial of Development of Systems and Education for Human Papillomavirus Vaccination (DOSE HPV), a multilevel intervention. METHODS: DOSE HPV is a 7-session program that includes interprofessional provider education, communication training, data feedback, and tailored systems change. Five primary care pediatric and/or family medicine practices completed interventions between 2016 and 2018; all chose to initiate vaccination at ages 9 to 10. We compared vaccination rates in the preintervention, intervention, and postintervention periods among 9- to 17-year-olds using random-effects generalized linear regression models appropriate for stepped-wedge design, accounting for calendar time and clustering of patients by providers and clinic. Outcomes included (1) the likelihood that eligible patients would receive vaccination during clinic visits; (2) the likelihood that adolescents would complete the series by age 13; and (3) the cumulative effect on population-level vaccine initiation and completion rates. Postintervention periods ranged from 6 to 18 months. RESULTS: In the intervention and postintervention periods, the adjusted likelihood of vaccination at an eligible visit increased by >10 percentage points for ages 9 to 10 and 11 to 12, and completion of the vaccine series by age 13 increased by 4 percentage points (P < .001 for all comparisons). Population-level vaccine initiation coverage increased from 75% (preintervention) to 84% (intervention) to 90% (postintervention), and completion increased from 60% (preintervention) to 63% (intervention) to 69% (postintervention). CONCLUSIONS: Multilevel interventions that include provider education, data feedback, tailored systems changes, and early initiation of the human papillomavirus vaccine series may improve vaccine series initiation and completion beyond the conclusion of the intervention period.

Exploring Opportunities for Household-Level Chronic Care Management Using Linked Electronic Health Records of Adults and Children: A Retrospective Cohort Study.

OBJECTIVE: Linking electronic health records (EHR) of pediatric and adult patients living in the same household has the potential to improve chronic care management efficiencies by facilitating the delivery of services to multiple household members at once. However, little is known about relationship between the chronic medical (CM) and behavioral health (CBH) of adults and children living in common households. METHODS: EHR data for children were linked to the EHR data of adults living at the same address during the same time in a retrospective cohort study from 2006 to 2014 to evaluate associations between adult and child CM and CBH conditions within a Boston safety-net primary care patient sample. RESULTS: Of the 13,845 included children, 61.6% lived with at least one adult with ≥ 1 CM or CBH condition. Compared to children living with an adult(s) without a chronic condition, children living with an adult with a CM or CBH condition had a respective 16.2% and 18.1% increased likelihood of having a chronic condition themselves, with multiple adult chronic conditions in adults increasing children's likelihood. CONCLUSIONS FOR PRACTICE: We found a positive association between the chronic diseases of adult and child household members. Given the clustering of child and adult chronic disease within households, using EHR data to support the care management needs of multiple members of households may be a promising approach to improving child and adult health in safety-net settings.