Implementation of an Antibiotic Stewardship Initiative in a Large Urgent Care Network

Importance

Urgent Care (UC) encounters result in more inappropriate antibiotic prescriptions than other outpatient setting. Few stewardship interventions have focused on UC.

Objective

To evaluate the effectiveness of an antibiotic stewardship initiative to reduce antibiotic prescribing for respiratory conditions in a UC network.

Design, Setting, and Participants

This quality improvement study conducted in a UC network with 38 UC clinics and 1 telemedicine clinic included 493 724 total UC encounters. The study compared the antibiotic prescribing rates of all UC clinicians who encountered respiratory conditions for a 12-month baseline period (July 1, 2018, through June 30, 2019) with an intervention period (July 1, 2019, through June 30, 2020). A sustainability period (July 1, 2020, through June 30, 2021) was added post hoc.

Interventions

Stewardship interventions included (1) education for clinicians and patients, (2) electronic health record (EHR) tools, (3) a transparent clinician benchmarking dashboard, and (4) media. Occurring independently but concurrent with the interventions, a stewardship measure was introduced by UC leadership into the quality measures, including a financial incentive.

Main Outcomes and Measures

The primary outcome was the percentage of UC encounters with an antibiotic prescription for a respiratory condition. Secondary outcomes included antibiotic prescribing when antibiotics were not indicated (tier 3 encounters) and first-line antibiotics for acute otitis media, sinusitis, and pharyngitis. Interrupted time series with binomial generalized estimating equations were used to compare periods.

Results

The baseline period included 207 047 UC encounters for respiratory conditions (56.8% female; mean [SD] age, 30.0 [21.4] years; 92.0% White race); the intervention period included 183 893 UC encounters (56.4% female; mean [SD] age, 30.7 [20.8] years; 91.2% White race). Antibiotic prescribing for respiratory conditions decreased from 47.8% (baseline) to 33.3% (intervention). During the initial intervention month, a 22% reduction in antibiotic prescribing occurred (odds ratio [OR], 0.78; 95% CI, 0.71-0.86). Antibiotic prescriptions decreased by 5% monthly during the intervention (OR, 0.95; 95% CI, 0.94-0.96). Antibiotic prescribing for tier 3 encounters decreased by 47% (OR, 0.53; 95% CI, 0.44-63), and first-line antibiotic prescriptions increased by 18% (OR, 1.18; 95% CI, 1.09-1.29) during the initial intervention month. Antibiotic prescriptions for tier 3 encounters decreased by an additional 4% each month (OR, 0.96; 95% CI, 0.94-0.98), whereas first-line antibiotic prescriptions did not change (OR, 1.00; 95% CI, 0.99-1.01). Antibiotic prescribing for respiratory conditions remained stable in the sustainability period.

Conclusions and relevance

The findings of this quality improvement study indicated that a UC antibiotic stewardship initiative was associated with decreased antibiotic prescribing for respiratory conditions. This study provides a model for UC antibiotic stewardship.

2212. Improving Sexually Transmitted Infection Co-testing in a Large Urgent Care Network

Background

Sexually transmitted infections (STIs) remain a serious public health concern. The state of Utah has the lowest percentage of adults 18-64 years-old ever tested for HIV (26.5%) and the lowest percentage tested for HIV in the previous 12 months (6.5%). Increasing HIV testing in Utah is of the utmost importance. Delayed diagnoses and missed testing opportunities for HIV and other STIs exist. Encounters for evaluation of possible gonorrhea (GC) or chlamydia (CT) infection is a critical opportunity to co-test for HIV and syphilis. With continued growth, urgent care (UC) sites are well-positioned to increase STI diagnosis and treatment. We aimed to develop a multi-faceted quality improvement (QI) bundle to increase STI testing in our UC centers.

Methods

Intermountain Healthcare (IH) is a vertically integrated healthcare network predominantly in Utah and operates a network of 35 UC clinics across the state. In 2020, qualitative interviews to evaluate barriers to STI testing were performed with UC clinicians. Based on these interviews a QI initiative was designed and implemented throughout 2021. The bundle included clinician education, electronic health record (EHR) improvements, and automatic referral for patients with a new diagnosis of HIV to an Infectious Diseases (ID) physician (Methods Image 1). We compared co-testing rates before (July 2018 – December 2020) and after the intervention began (March 2021 – April 2022).

Implementation of Diabetes Prevention in Health Care Organizations: Best Practice Recommendations

Approximately 1 in 3 American adults has prediabetes, a condition characterized by blood glucose levels that are above normal, not in the type 2 diabetes ranges, and that increases the risk of developing type 2 diabetes. Evidence-based treatments can be used to prevent or delay type 2 diabetes in adults with prediabetes. The American Medical Association (AMA) has collaborated with health care organizations across the country to build sustainable diabetes prevention strategies. In 2017, the AMA formed the Diabetes Prevention Best Practices Workgroup (DPBP) with representatives from 6 health care organizations actively implementing diabetes prevention. Each organization had a unique strategy, but all included the National Diabetes Prevention Program lifestyle change program as a core evidence-based intervention. DPBP established the goal of disseminating best practices to guide other health care organizations in implementing diabetes prevention and identifying and managing patients with prediabetes. Workgroup members recognized similarities in some of their basic steps and considerations and synthesized their practices to develop best practice recommendations for 3 strategy maturity phases. Recommendations for each maturity phase are classified into 6 categories: (1) organizational support; (2) workforce and funding; (3) promotion and dissemination; (4) clinical integration and support; (5) evaluation and outcomes; (6) and program. As the burden of chronic disease grows, prevention must be prioritized and integrated into health care. These maturity phases and best practice recommendations can be used by any health care organization committed to diabetes prevention. Further research is suggested to assess the impact and adoption of diabetes prevention best practices.

Measuring Adherence to U.S. Preventive Services Task Force Diabetes Prevention Guidelines Within Two Healthcare Systems

ABSTRACT

Measuring adherence to the 2015 U.S. Preventive Services Task Force (USPSTF) diabetes prevention guidelines can inform implementation efforts to prevent or delay Type 2 diabetes. A retrospective cohort was used to study patients without a diagnosis of diabetes attributed to primary care clinics within two large healthcare systems in our state to study adherence to the following: (1) screening at-risk patients and (2) referring individuals with confirmed prediabetes to participate in an intensive behavioral counseling intervention, defined as a Center for Disease Control and Prevention (CDC)-recognized Diabetes Prevention Program (DPP). Among 461,866 adults attributed to 79 primary care clinics, 45.7% of patients were screened, yet variability at the level of the clinic ranged from 14.5% to 83.2%. Very few patients participated in a CDC-recognized DPP (0.52%; range 0%-3.53%). These findings support the importance of a systematic implementation strategy to specifically target barriers to diabetes prevention screening and referral to treatment.

Trends in Abstinence and Retention Associated with a Medication-Assisted Treatment Program for People with Opioid Use Disorders

BACKGROUND

Medication-assisted treatment (MAT) is an evidence-based program for patients with opioid use disorders. Yet, within the state of Utah, MAT had not been widely available, promoted, or adopted within the public sector. Recognizing the potential benefit, a collective impact approach was used to promote social change and increase the use of MAT in the community for treatment of opioid use disorders.

OBJECTIVE

Conduct a retrospective, observational case series study to measure the effect of a community-based, collective impact approach implementing the MAT program to improve the rate of abstinence and retention among individuals identified with an opioid use disorder in three Utah counties.

METHODS

The study was designed and implemented by the Utah Opioid Community Collaborative (OCC) using a collective impact approach, which included broad sector coordination (public-private collaboration), a common agenda, participation in mutually reinforcing activities, continuous communication, consistent measurement of results, and identification of a backbone organization. The MAT intervention program includes use of medications approved by the U.S. Food and Drug Administration in combination with counseling and behavioral therapies delivered within two community sites. Analysis was performed over time to describe the rate of abstinence and retention associated with participation in the MAT program during 2015 through 2017.

RESULTS

Of the 339 identified with risk of an opioid use disorders, 228 enrolled in the MAT Program. At MAT enrollment, average age was 32.6 ± 8.2 years old and 58.0% were female. At 365 days after MAT enrollment, 84% of participants were abstinent from opioid substances and 62% from all illicit substances.

CONCLUSIONS

Use of a collective impact approach provides a successful mobilization framework in Utah for increasing community engagement and expanding patient access to underresourced MAT programs while suggesting a high rate of abstinence from illicit substances at 12 months.

Rapid Implementation of a Complex, Multimodal Technology Response to COVID-19 at an Integrated Community-Based Health Care System

BACKGROUND

The rapid spread of severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 necessitated a scaled treatment response to the novel coronavirus disease 2019 (COVID-19).

OBJECTIVE

This study aimed to characterize the design and rapid implementation of a complex, multimodal, technology response to COVID-19 led by the Intermountain Healthcare's (Intermountain's) Care Transformation Information Systems (CTIS) organization to build pandemic surge capacity.

METHODS

Intermountain has active community-spread cases of COVID-19 that are increasing. We used the Centers for Disease Control and Prevention Pandemic Intervals Framework (the Framework) to characterize CTIS leadership's multimodal technology response to COVID-19 at Intermountain. We provide results on implementation feasibility and sustainability of health information technology (HIT) interventions as of June 30, 2020, characterize lessons learned and identify persistent barriers to sustained deployment.

RESULTS

We characterize the CTIS organization's multimodal technology response to COVID-19 in five relevant areas of the Framework enabling (1) incident management, (2) surveillance, (3) laboratory testing, (4) community mitigation, and (5) medical care and countermeasures. We are seeing increased use of traditionally slow-to-adopt technologies that create additional surge capacity while sustaining patient safety and care quality. CTIS leadership recognized early that a multimodal technology intervention could enable additional surge capacity for health care delivery systems with a broad geographic and service scope. A statewide central tracking system to coordinate capacity planning and management response is needed. Order interoperability between health care systems remains a barrier to an integrated response.

CONCLUSION

The rate of future pandemics is estimated to increase. The pandemic response of health care systems, like Intermountain, offers a blueprint for the leadership role that HIT organizations can play in mainstream care delivery, enabling a nimbler, virtual health care delivery system that is more responsive to current and future needs.

Leveraging 31 Million Google Street View Images to Characterize Built Environments and Examine County Health Outcomes

OBJECTIVES

Built environments can affect health, but data in many geographic areas are limited. We used a big data source to create national indicators of neighborhood quality and assess their associations with health.

METHODS

We leveraged computer vision and Google Street View images accessed from December 15, 2017, through July 17, 2018, to detect features of the built environment (presence of a crosswalk, non-single-family home, single-lane roads, and visible utility wires) for 2916 US counties. We used multivariate linear regression models to determine associations between features of the built environment and county-level health outcomes (prevalence of adult obesity, prevalence of diabetes, physical inactivity, frequent physical and mental distress, poor or fair self-rated health, and premature death [in years of potential life lost]).

RESULTS

Compared with counties with the least number of crosswalks, counties with the most crosswalks were associated with decreases of 1.3%, 2.7%, and 1.3% of adult obesity, physical inactivity, and fair or poor self-rated health, respectively, and 477 fewer years of potential life lost before age 75 (per 100 000 population). The presence of non-single-family homes was associated with lower levels of all health outcomes except for premature death. The presence of single-lane roads was associated with an increase in physical inactivity, frequent physical distress, and fair or poor self-rated health. Visible utility wires were associated with increases in adult obesity, diabetes, physical and mental distress, and fair or poor self-rated health.

CONCLUSIONS

The use of computer vision and big data image sources makes possible national studies of the built environment's effects on health, producing data and results that may inform national and local decision-making.

Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents' risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

Antibiotic Prescribing Variability in a Large Urgent Care Network: A New Target for Outpatient Stewardship

Improving antibiotic prescribing in outpatient settings is a public health priority. In the United States, urgent care (UC) encounters are increasing and have high rates of inappropriate antibiotic prescribing. Our objective was to characterize antibiotic prescribing practices during UC encounters, with a focus on respiratory tract conditions. This was a retrospective cohort study of UC encounters in the Intermountain Healthcare network. Among 1.16 million UC encounters, antibiotics were prescribed during 34% of UC encounters and respiratory conditions accounted for 61% of all antibiotics prescribed. Of respiratory encounters, 50% resulted in antibiotic prescriptions, yet the variability at the level of the provider ranged from 3% to 94%. Similar variability between providers was observed for respiratory conditions where antibiotics were not indicated and in first-line antibiotic selection for sinusitis, otitis media, and pharyngitis. These findings support the importance of developing antibiotic stewardship interventions specifically targeting UC settings.

Using Google Street View to examine associations between built environment characteristics and U.S. health outcomes

Neighborhood attributes have been shown to influence health, but advances in neighborhood research has been constrained by the lack of neighborhood data for many geographical areas and few neighborhood studies examine features of nonmetropolitan locations. We leveraged a massive source of Google Street View (GSV) images and computer vision to automatically characterize national neighborhood built environments. Using road network data and Google Street View API, from December 15, 2017-May 14, 2018 we retrieved over 16 million GSV images of street intersections across the United States. Computer vision was applied to label each image. We implemented regression models to estimate associations between built environments and county health outcomes, controlling for county-level demographics, economics, and population density. At the county level, greater presence of highways was related to lower chronic diseases and premature mortality. Areas characterized by street view images as 'rural' (having limited infrastructure) had higher obesity, diabetes, fair/poor self-rated health, premature mortality, physical distress, physical inactivity and teen birth rates but lower rates of excessive drinking. Analyses at the census tract level for 500 cities revealed similar adverse associations as was seen at the county level for neighborhood indicators of less urban development. Possible mechanisms include the greater abundance of services and facilities found in more developed areas with roads, enabling access to places and resources for promoting health. GSV images represents an underutilized resource for building national data on neighborhoods and examining the influence of built environments on community health outcomes across the United States.

Practical Tips for Implementing the Diabetes Prevention Program in Clinical Practice

PURPOSE OF REVIEW

The Diabetes Prevention Program (DPP) is an evidence-based lifestyle change program for prediabetes that is associated with a 58% reduction in 3-year diabetes incidence, and it has been supported by the American Medical Association and the Centers for Disease Control and Prevention. However, 9 in 10 patients are unaware they have the condition.

RECENT FINDINGS

With the passage of the Affordable Care Act (ACA) and broadened coverage for preventive services, the DPP has emerged as an accessible intervention in patients at risk. In 2018, Medicare began to cover the DPP, making it widely available for the first time to any patient over the age of 65 meeting eligibility criteria. The DPP is an evidence-based, widely available, frequently covered benefit, for lifestyle change for patients with prediabetes. To take advantage of this intervention, providers need to develop prediabetes screening and DPP referral workflows.

"Pharming out" support: a promising approach to integrating clinical pharmacists into established primary care medical home practices

Objective

Embedding clinical pharmacists into ambulatory care settings needs to be assessed in the context of established medical home models.

Methods

A retrospective, observational study examined the effectiveness of the Intermountain Healthcare Collaborative Pharmacist Support Services (CPSS) program from 2012–2015 among adult patients diagnosed with diabetes mellitus (DM) and/or high blood pressure (HBP). Patients who attended this program were considered the intervention (CPSS) cohort. These patients were matched using propensity scores with a reference group (no-CPSS cohort) to determine the effect of achieving disease management goals and time to achievement.

Results

A total of 17,684 patients had an in-person office visit with their provider and 359 received CPSS (the matched no-CPSS cohort included 999 patients). CPSS patients were 93% more likely to achieve a blood pressure goal < 140/90 mmHg, 57% more likely to achieve HbA1c values < 8%, and 87% more likely to achieve both disease management goals compared with the reference group. Time to goal achievement demonstrated increasing separation between the study cohorts across the entire study period (P < .001), and specifically, at 180 days post-intervention (HBP: 48% vs 27% P < .001 and DM: 39% vs 30%, P < .05).

Conclusions

CPSS participation is associated with significant improvement in achievement of disease management goals, time to achievement, and increased ambulatory encounters compared with the matched no-CPSS cohort.

A Formative Evaluation of a Diabetes Prevention Program Using the RE-AIM Framework in a Learning Health Care System, Utah, 2013-2015

Introduction

Evaluation of interventions can help to close the gap between research and practice but seldom takes place during implementation. Using the RE-AIM framework, we conducted a formative evaluation of the first year of the Intermountain Healthcare Diabetes Prevention Program (DPP).

Methods

Adult patients who met the criteria for prediabetes (HbA1c of 5.70%–6.49% or fasting plasma glucose of 100–125 mg/dL) were attributed to a primary care provider from August 1, 2013, through July 31, 2014. Physicians invited eligible patients to participate in the program during an office visit. We evaluated 1) reach, with data on patient eligibility, participation, and representativeness; 2) effectiveness, with data on attaining a 5% weight loss; 3) adoption, with data on providers and clinics that referred patients to the program; and 4) implementation, with data on patient encounters. We did not measure maintenance.

Results

Of the 6,862 prediabetes patients who had an in-person office visit with their provider, 8.4% of eligible patients enrolled. Likelihood of participation was higher among patients who were female, aged 70 years or older, or overweight; had depression and higher weight at study enrollment; or were prescribed metformin. DPP participants were more likely than nonparticipants to achieve a 5% weight loss (odds ratio, 1.70; 95% confidence interval, 1.29–2.25; P < .001). Providers from 7 of 8 regions referred patients to the DPP; 174 providers at 53 clinics enrolled patients. The mean number of DPP counseling encounters per patient was 2.3 (range, 1–16).

Conclusion

The RE-AIM framework was useful for estimating the formative impact (ie, reach, effectiveness, adoption, and implementation fidelity) of a DPP-based lifestyle intervention deployed in a learning health care system.

Association of Integrated Team-Based Care With Health Care Quality, Utilization, and Cost

IMPORTANCE

The value of integrated team delivery models is not firmly established.

OBJECTIVE

To evaluate the association of receiving primary care in integrated team-based care (TBC) practices vs traditional practice management (TPM) practices (usual care) with patient outcomes, health care utilization, and costs.

DESIGN

A retrospective, longitudinal, cohort study to assess the association of integrating physical and mental health over time in TBC practices with patient outcomes and costs.

SETTING AND PARTICIPANTS

Adult patients (aged ≥18 years) who received primary care at 113 unique Intermountain Healthcare Medical Group primary care practices from 2003 through 2005 and had yearly encounters with Intermountain Healthcare through 2013, including some patients who received care in both TBC and TPM practices.

EXPOSURES

Receipt of primary care in TBC practices compared with TPM practices for patients treated in internal medicine, family practice, and geriatrics practices.

MAIN OUTCOMES AND MEASURES

Outcomes included 7 quality measures, 6 health care utilization measures, payments to the delivery system, and program investment costs.

RESULTS

During the study period (January 2010-December 2013), 113,452 unique patients (mean age, 56.1 years; women, 58.9%) accounted for 163,226 person-years of exposure in 27 TBC practices and 171,915 person-years in 75 TPM practices. Patients treated in TBC practices compared with those treated in TPM practices had higher rates of active depression screening (46.1% for TBC vs 24.1% for TPM; odds ratio [OR], 1.91 [95% CI, 1.75 to 2.08), adherence to a diabetes care bundle (24.6% for TBC vs 19.5% for TPM; OR, 1.26 [95% CI, 1.11 to 1.42]), and documentation of self-care plans (48.4% for TBC vs 8.7% for TPM; OR, 5.59 [95% CI, 4.27 to 7.33]), lower proportion of patients with controlled hypertension (<140/90 mm Hg) (85.0% for TBC vs 97.7% for TPM; OR, 0.87 [95% CI, 0.80 to 0.95]), and no significant differences in documentation of advanced directives (9.6% for TBC vs 9.9% for TPM; OR, 0.97 [95% CI, 0.91 to 1.03]). Per 100 person-years, rates of health care utilization were lower for TBC patients compared with TPM patients for emergency department visits (18.1 for TBC vs 23.5 for TPM; incidence rate ratio [IRR], 0.77 [95% CI, 0.74 to 0.80]), hospital admissions (9.5 for TBC vs 10.6 for TPM; IRR, 0.89 [95% CI, 0.85 to 0.94]), ambulatory care sensitive visits and admissions (3.3 for TBC vs 4.3 for TPM; IRR, 0.77 [95% CI, 0.70 to 0.85]), and primary care physician encounters (232.8 for TBC vs 250.4 for TPM; IRR, 0.93 [95% CI, 0.92 to 0.94]), with no significant difference in visits to urgent care facilities (55.7 for TBC vs 56.2 for TPM; IRR, 0.99 [95% CI, 0.97 to 1.02]) and visits to specialty care physicians (213.5 for TBC vs 217.9 for TPM; IRR, 0.98 [95% CI, 0.97 to 0.99], P > .008). Payments to the delivery system were lower in the TBC group vs the TPM group ($3400.62 for TBC vs $3515.71 for TPM; β, -$115.09 [95% CI, -$199.64 to -$30.54]) and were less than investment costs of the TBC program.

CONCLUSIONS AND RELEVANCE

Among adults enrolled in an integrated health care system, receipt of primary care at TBC practices compared with TPM practices was associated with higher rates of some measures of quality of care, lower rates for some measures of acute care utilization, and lower actual payments received by the delivery system.

Incidental Risk of Type 2 Diabetes Mellitus among Patients with Confirmed and Unconfirmed Prediabetes

OBJECTIVE

To determine the risk of type 2 diabetes (T2DM) diagnosis among patients with confirmed and unconfirmed prediabetes (preDM) relative to an at-risk group receiving care from primary care physicians over a 5-year period.

STUDY DESIGN

Utilizing data from the Intermountain Healthcare (IH) Enterprise Data Warehouse (EDW) from 2006-2013, we performed a prospective analysis using discrete survival analysis to estimate the time to diagnosis of T2DM among groups.

POPULATION STUDIED

Adult patients who had at least one outpatient visit with a primary care physician during 2006-2008 at an IH clinic and subsequent visits through 2013. Patients were included for the study if they were (a) at-risk for diabetes (BMI ≥ 25 kg/m2 and one additional risk factor: high risk ethnicity, first degree relative with diabetes, elevated triglycerides or blood pressure, low HDL, diagnosis of gestational diabetes or polycystic ovarian syndrome, or birth of a baby weighing >9 lbs); or (b) confirmed preDM (HbA1c ≥ 5.7-6.49% or fasting blood glucose 100-125 mg/dL); or (c) unconfirmed preDM (documented fasting lipid panel and glucose 100-125 mg/dL on the same day).

PRINCIPAL FINDINGS

Of the 33,838 patients who were eligible for study, 57.0% were considered at-risk, 38.4% had unconfirmed preDM, and 4.6% had confirmed preDM. Those with unconfirmed and confirmed preDM tended to be Caucasian and a greater proportion were obese compared to those at-risk for disease. Patients with unconfirmed and confirmed preDM tended to have more prevalent high blood pressure and depression as compared to the at-risk group. Based on the discrete survival analyses, patients with unconfirmed preDM and confirmed preDM were more likely to develop T2DM when compared to at-risk patients.

CONCLUSIONS

Unconfirmed and confirmed preDM are strongly associated with the development of T2DM as compared to patients with only risk factors for disease.

Diabetes self-management education improves quality of care and clinical outcomes determined by a diabetes bundle measure

PURPOSE

The purpose of this study was to determine the impact of diabetes self-management education (DSME) in improving processes and outcomes of diabetes care as measured by a five component diabetes bundle and HbA1c, in individuals with type 2 diabetes mellitus (T2DM).

METHODS

A retrospective analysis was performed for adult T2DM patients who received DSME training in 2011-2012 from an accredited American Diabetes Association center at Intermountain Healthcare (IH) and had an HbA1c measurement within the prior 3 months and 2-6 months after completing their first DSME visit. Control patients were selected from the same clinics as case-patients using random number generator to achieve a 1 to 4 ratio. Case and control patients were included if 1) pre-education HbA1c was between 6.0%-14.0%; 2) their main provider was a primary care physician; 3) they met the national Healthcare Effectiveness Data and Information Set criteria for inclusion in the IH diabetes registry. The IH diabetes bundle includes retinal eye exam, nephropathy screening or prescription of angiotensin converting enzyme or angiotensin receptor blocker; blood pressure <140/90 mmHg, LDL <100 mg/dL, HbA1c <8.0%.

RESULTS

DSME patients had a significant difference in achievement of the five element IH diabetes bundle and in HbA1c % compared to those without DSME. After adjusting for possible confounders in a multivariate logistic regression model, DSME patients had a 1.5 fold difference in improvement in their diabetes bundle and almost a 3 fold decline in HbA1c compared to the control group.

CONCLUSION

Standardized DSME taught within an IH American Diabetes Association center is strongly associated with a substantial improvement in patients meeting all five elements of a diabetes bundle and a decline in HbA1c beyond usual care. Given the low operating cost of the DSME program, these results strongly support the value adding benefit of this program in treating T2DM patients.

Computerized clinical decision support improves warfarin management and decreases recurrent venous thromboembolism

BACKGROUND

An explicit approach to warfarin dose adjustment using computerized clinical decision support (CDS) improves warfarin management. We report metrics of quality for warfarin management before and after implementation of CDS in a large health care system.

METHODS

A total of 2591 chronically anticoagulated patients were eligible for inclusion. We compared interpatient time in therapeutic range (TTR) and international normalized ratio (INR) variability before and after implementation of CDS. We report outcomes of major bleeding, thrombosis, and health care utilization.

RESULTS

Implementation of CDS significantly improved TTR (from 63.99% to 65.13%; P = .04) and reduced out-of-range INRs (from 42.39% to 39.97%; P < .001). Venous thromboembolism (relative risk [RR] 0.41; P < .001) emergency department utilization (RR 0.62; P < .001), and hospitalization (RR 0.62; P < .001) were reduced after CDS implementation. Major hemorrhage was more frequent after CDS implementation (RR 1.42; P = .01).

CONCLUSION

The CDS warfarin management was associated with improved TTR and decreased INR variability in a large cohort of chronically anticoagulated patients. Clinically relevant outcomes were broadly improved, although more bleeding events were observed.

Secretory phospholipase A(2)-IIA and cardiovascular disease: a mendelian randomization study

OBJECTIVES

This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease.

BACKGROUND

Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy.

METHODS

We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable.

RESULTS

PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE.

CONCLUSIONS

Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.

Randomized cross-over trial of short-term water-only fasting: metabolic and cardiovascular consequences

BACKGROUND AND AIMS

Routine, periodic fasting is associated with a lower prevalence of coronary artery disease (CAD). Animal studies show that fasting may increase longevity and alter biological parameters related to longevity. We evaluated whether fasting initiates acute changes in biomarker expression in humans that may impact short- and long-term health.

METHODS AND RESULTS

Apparently-healthy volunteers (N = 30) without a recent history of fasting were enrolled in a randomized cross-over trial. A one-day water-only fast was the intervention and changes in biomarkers were the study endpoints. Bonferroni correction required p ≤ 0.00167 for significance (p < 0.05 was a trend that was only suggestively significant). The one-day fasting intervention acutely increased human growth hormone (p = 1.1 × 10⁻⁴), hemoglobin (p = 4.8 × 10⁻⁷), red blood cell count (p = 2.5 × 10⁻⁶), hematocrit (p = 3.0 × 10⁻⁶), total cholesterol (p = 5.8 × 10⁻⁵), and high-density lipoprotein cholesterol (p = 0.0015), and decreased triglycerides (p = 1.3 × 10⁻⁴), bicarbonate (p = 3.9 × 10⁻⁴), and weight (p = 1.0 × 10⁻⁷), compared to a day of usual eating. For those randomized to fast the first day (n = 16), most factors including human growth hormone and cholesterol returned to baseline after the full 48 h, with the exception of weight (p = 2.5 × 10⁻⁴) and (suggestively significant) triglycerides (p = 0.028).

CONCLUSION

Fasting induced acute changes in biomarkers of metabolic, cardiovascular, and general health. The long-term consequences of these short-term changes are unknown but repeated episodes of periodic short-term fasting should be evaluated as a preventive treatment with the potential to reduce metabolic disease risk. Clinical trial registration (ClinicalTrials.gov): NCT01059760 (Expression of Longevity Genes in Response to Extended Fasting [The Fasting and Expression of Longevity Genes during Food abstinence {FEELGOOD} Trial]).

Repeated measurement of the intermountain risk score enhances prognostication for mortality

Background

The Intermountain Risk Score (IMRS), composed of the complete blood count (CBC) and basic metabolic profile (BMP), predicts mortality and morbidity in medical and general populations. Whether longitudinal repeated measurement of IMRS is useful for prognostication is an important question for its clinical applicability.

Methods

Females (N = 5,698) and males (N = 5,437) with CBC and BMP panels measured 6 months to 2.0 years apart (mean 1.0 year) had baseline and follow-up IMRS computed. Survival analysis during 4.0±2.5 years (maximum 10 years) evaluated mortality (females: n = 1,255 deaths; males: n = 1,164 deaths) and incident major events (myocardial infarction, heart failure [HF], and stroke).

Results

Both baseline and follow-up IMRS (categorized as high-risk vs. low-risk) were independently associated with mortality (all p<0.001) in bivariable models. For females, follow-up IMRS had hazard ratio (HR) = 5.23 (95% confidence interval [CI] = 4.11, 6.64) and baseline IMRS had HR = 3.66 (CI = 2.94, 4.55). Among males, follow-up IMRS had HR = 4.28 (CI = 3.51, 5.22) and baseline IMRS had HR = 2.32 (CI = 1.91, 2.82). IMRS components such as RDW, measured at both time points, also predicted mortality. Baseline and follow-up IMRS strongly predicted incident HF in both genders.

Conclusions

Repeated measurement of IMRS at baseline and at about one year of follow-up were independently prognostic for mortality and incident HF among initially hospitalized patients. RDW and other CBC and BMP values were also predictive of outcomes. Further research should evaluate the utility of IMRS as a tool for clinical risk adjustment.

The intermountain risk score predicts incremental age-specific long-term survival and life expectancy

The Intermountain Risk Score (IMRS) encapsulates the mortality risk information from all components of the complete blood count (CBC) and basic metabolic profile (BMP), along with age. To individualize the IMRS more clearly, this study evaluated whether IMRS weightings for 1-year mortality predict age-specific survival over more than a decade of follow-up. Sex-specific 1-year IMRS values were calculated for general medical patients with CBC and BMP laboratory tests drawn during 1999-2005. The population was divided randomly 60% (N = 71,921, examination sample) and 40% (N = 47,458, validation sample). Age-specific risk thresholds were established, and both survival and life expectancy were compared across low-, moderate-, and high-risk IMRS categories. During 7.3 ± 1.8 years of follow-up (range, 4.5-11.1 years), the average IMRS of decedents was higher than censored in all age/sex strata (all P < 0.001). For examination and validation samples, every age stratum had incrementally lower survival for higher risk IMRS, with hazard ratios of 2.5-8.5 (P < 0.001). Life expectancies were also significantly shorter for higher risk IMRS (all P < 0.001): For example, among 50-59 year-olds, life expectancy was 7.5, 6.8, and 5.9 years for women with low-, moderate-, and high-risk IMRS (with mortality in 5.7%, 16.3%, and 37.0% of patients, respectively). In Men, life expectancy was 7.3, 6.8, and 5.4 for low-, moderate-, and high-risk IMRS (with patients having 7.3%, 19.5%, and 40.0% mortality), respectively. IMRS significantly stratified survival and life expectancy within age-defined subgroups during more than a decade of follow-up. IMRS may be used to stratify age-specific risk of mortality in research, clinical/preventive, and quality improvement applications. A web calculator is located at http://intermountainhealthcare.org/IMRS.

Genome-wide significance and replication of the chromosome 12p11.22 locus near the PTHLH gene for peripartum cardiomyopathy

BACKGROUND

Peripartum (PP) cardiomyopathy (CM) is a rare condition of unknown etiology that occurs in late pregnancy or early postpartum. Initial evidence suggests that genetic factors may influence PPCM. This study evaluated and replicated genome-wide association of single nucleotide polymorphisms with PPCM.

METHODS AND RESULTS

Genome-wide single nucleotide polymorphisms in women with verified PPCM diagnosis (n=41) were compared separately with local control subjects (n=49 postmenopausal age-discordant women with parity ≥1 and no heart failure) and iControls (n=654 women ages 30 to 84 years with unknown phenotypes). A replication study of independent population samples used new cases (PPCM2, n=30) compared with new age-discordant control subjects (local2, n=124) and with younger control subjects (n=89) and obstetric control subjects (n=90). A third case set of pregnancy-associated CM cases not meeting strict PPCM definitions (n=29) was also studied. In the genome-wide association study, 1 single nucleotide polymorphism (rs258415) met genome-wide significance for PPCM versus local control subjects (P=2.06×10(-8); odds ratio [OR], 5.96). This was verified versus iControls (P=7.92×10(-19); OR, 8.52). In the replication study for PPCM2 cases, rs258415 (ORs are per C allele) replicated at P=0.009 versus local2 control subjects (OR, 2.26). This replication was verified for PPCM2 versus younger control subjects (P=0.029; OR, 2.15) and versus obstetric control subjects (P=0.013; OR, 2.44). In pregnancy-associated cardiomyopathy cases, rs258415 had a similar effect versus local2 control subjects (P=0.06; OR, 1.79), younger control subjects (P=0.14; OR, 1.65), and obstetric control subjects (P=0.038; OR, 1.99).

CONCLUSIONS

Genome-wide association with PPCM was discovered and replicated for rs258415 at chromosome 12p11.22 near PTHLH. This study indicates a role of genetic factors in PPCM and provides a new locus for further pathophysiological and clinical investigation.