Publications

BACKGROUND: Veterans commonly receive care from both Veterans Health Administration (VA) and non-VA sources (i.e., dual use). A major challenge in comparing health outcomes between dual users and VA-predominant users is applying an accurate method of risk adjustment.

OBJECTIVE: To determine how different comorbidity indices affect the association between patterns of dual use and health outcomes.

DESIGN: Retrospective cohort.

PARTICIPANTS: A total of 316,775 community-dwelling Veterans (≥65 years) with type 2 diabetes who were enrolled in VA and fee-for-service Medicare from 2008 to 2010.

METHODS: We determined the associations between dual use and death or diabetes-related hospitalization in FY 2010 using multivariable models incorporating claims-based (Elixhauser) or medication-based (RxRisk-V) risk adjustment. Dual use was classified using four previously identified groups of health services users: 1) VA-predominant, 2) VA + Medicare visits and labs, 3) VA + Medicare test strips, and 4) VA + Medicare medications.

KEY RESULTS: Controlling for Elixhauser comorbidities, dual-use groups 2-4 had significantly decreased odds of death or hospitalization compared to VA-predominant users. Controlling for RxRisk-V comorbidities, groups 2-4 had increased odds of death compared to VA-predominant users, but variable odds of hospitalization, with group 2 having increased odds (OR 1.06, CI 1.04-1.09), while groups 3 (OR 0.96, CI 0.94-0.99) and 4 (OR 0.93, CI 0.89-0.97) had decreased odds.

CONCLUSIONS: The method of risk adjustment drastically influences the direction of effect in health outcomes among dual users of VA and Medicare. These findings underscore the need for standardized and reliable risk adjustment methods that are not susceptible to measurement differences across different health systems.

Weight management medications (WMM) are underutilized as an adjunct to behavioral and lifestyle interventions. In fiscal years 2014-2015, a total of approximately 2500 veterans-a mere 2% of veterans receiving care from the Veterans Health Administration (VHA)-eligible for a WMM received a prescription for one. A State of the Art Conference on Weight Management workgroup, focused on pharmacotherapy, developed evidence-based recommendations and strategies to foster the appropriate use of WMM in the VHA. The workgroup identified patient, prescriber, and health system barriers to and facilitators for prescribing WMM. Barriers included patient and provider concerns about medication safety and efficacy, limited involvement of primary care, restrictive medication criteria for use (CFU), and skepticism among providers regarding the safety and efficacy of WMM and the perception of obesity as a disease. Potential facilitators for removing barriers included patient and provider education about WMM and the health benefits of weight loss, increased engagement of primary care providers in weight management, relaxation of the CFU, and creation of a system to help patients navigate through weight management treatment options. Several research questions were framed with regard to WMM in general, and specifically to the care of obese veterans. While some of the workgroup's conclusions reflect issues specific to the VHA, many are likely to be applicable to other health organizations.

Telemedicine, the use of audiovisual technology to provide health care from a remote location, is increasingly used in intensive care units (ICUs). However, studies evaluating the impact of ICU telemedicine show mixed results, with some studies demonstrating improved patient outcomes, while others show limited benefit or even harm. Little is known about the mechanisms that influence variation in ICU telemedicine effectiveness, leaving providers without guidance on how to best use this potentially transformative technology. The Contributors to Effective Critical Care Telemedicine (ConnECCT) study aims to fill this knowledge gap by identifying the clinical and organizational factors associated with variation in ICU telemedicine effectiveness, as well as exploring the clinical contexts and provider perceptions of ICU telemedicine use and its impact on patient outcomes, using a range of qualitative methods. In this report, we describe the study protocol, data collection methods, and planned future analyses of the ConnECCT study. Over the course of 1 year, the study team visited purposefully sampled health systems across the United States that have adopted telemedicine. Data collection methods included direct observations, interviews, focus groups, and artifact collection. Data were collected at the ICUs that provide in-person critical care as well as at the supporting telemedicine units. Iterative thematic content analysis will be used to identify and define key constructs related to telemedicine effectiveness and describe the relationship between them. Ultimately, the study results will provide a framework for more effective implementation of ICU telemedicine, leading to improved clinical outcomes for critically ill patients.

BACKGROUND: In October 2015, the Centers for Medicare and Medicaid Services (CMS) implemented the Sepsis CMS Core Measure (SEP-1) program, requiring hospitals to report data on the quality of care for their patients with sepsis.

OBJECTIVE: We sought to understand hospital perceptions of and responses to the SEP-1 program.

DESIGN: A thematic content analysis of semistructured interviews with hospital quality officials.

SETTING: A stratified random sample of short-stay, nonfederal, general acute care hospitals in the United States.

PATIENTS: Hospital quality officers, including nurses and physicians.

MEASUREMENTS: We completed 29 interviews before reaching content saturation.

RESULTS: Hospitals reported a variety of actions in response to SEP-1, including new efforts to collect data, improve sepsis diagnosis and treatment, and manage clinicians' attitudes toward SEP-1. These efforts frequently required dedicated resources to meet the program's requirements for treatment and documentation, which were thought to be complex and not consistently linked to patient-centered outcomes. Most respondents felt that SEP-1 was likely to improve sepsis outcomes. At the same time, they described specific changes that could improve its effectiveness, including allowing hospitals to focus on the treatment processes most directly associated with improved patient outcomes and better aligning the measure's sepsis definitions with current clinical definitions.

CONCLUSIONS: Hospitals are responding to the SEP-1 program across a number of domains and in ways that consistently require dedicated resources. Hospitals are interested in further revisions to the program to alleviate the burden of the reporting requirements and help them optimize the effectiveness of their investments in quality-improvement efforts.

OBJECTIVE: Although there is growing evidence regarding the utility of telemedicine in providing care for acutely ill children in underserved settings, adoption of pediatric emergency telemedicine remains limited, and little data exist to inform implementation efforts. Among clinician stakeholders, we examined attitudes regarding pediatric emergency telemedicine, including barriers to adoption in rural settings and potential strategies to overcome these barriers.

METHODS: Using a sequential mixed-methods approach, we first performed semistructured interviews with clinician stakeholders using thematic content analysis to generate a conceptual model for pediatric emergency telemedicine adoption. Based on this model, we then developed and fielded a survey to further examine attitudes regarding barriers to adoption and strategies to improve adoption.

RESULTS: Factors influencing adoption of pediatric emergency telemedicine were identified and categorized into 3 domains: contextual factors (such as regional geography, hospital culture, and individual experience), perceived usefulness of pediatric emergency telemedicine, and perceived ease of use of pediatric emergency telemedicine. Within the domains of perceived usefulness and perceived ease of use, belief in the relative advantage of telemedicine was the most pronounced difference between telemedicine proponents and nonproponents. Strategies identified to improve adoption of telemedicine included patient-specific education, clinical protocols for use, decreasing response times, and simplifying the technology.

CONCLUSIONS: More effective adoption of pediatric emergency telemedicine among clinicians will require addressing perceived usefulness and perceived ease of use in the context of local factors. Future studies should examine the impact of specific identified strategies on adoption of pediatric emergency telemedicine and patient outcomes in rural settings.

BACKGROUND: Veterans commonly receive care from both Veterans Health Administration (VA) and non-VA sources (i.e., dual use). A major challenge in comparing health outcomes between dual users and VA-predominant users is applying an accurate method of risk adjustment.

OBJECTIVE: To determine how different comorbidity indices affect the association between patterns of dual use and health outcomes.

DESIGN: Retrospective cohort.

PARTICIPANTS: A total of 316,775 community-dwelling Veterans (≥65 years) with type 2 diabetes who were enrolled in VA and fee-for-service Medicare from 2008 to 2010.

METHODS: We determined the associations between dual use and death or diabetes-related hospitalization in FY 2010 using multivariable models incorporating claims-based (Elixhauser) or medication-based (RxRisk-V) risk adjustment. Dual use was classified using four previously identified groups of health services users: 1) VA-predominant, 2) VA + Medicare visits and labs, 3) VA + Medicare test strips, and 4) VA + Medicare medications.

KEY RESULTS: Controlling for Elixhauser comorbidities, dual-use groups 2-4 had significantly decreased odds of death or hospitalization compared to VA-predominant users. Controlling for RxRisk-V comorbidities, groups 2-4 had increased odds of death compared to VA-predominant users, but variable odds of hospitalization, with group 2 having increased odds (OR 1.06, CI 1.04-1.09), while groups 3 (OR 0.96, CI 0.94-0.99) and 4 (OR 0.93, CI 0.89-0.97) had decreased odds.

CONCLUSIONS: The method of risk adjustment drastically influences the direction of effect in health outcomes among dual users of VA and Medicare. These findings underscore the need for standardized and reliable risk adjustment methods that are not susceptible to measurement differences across different health systems.

OBJECTIVE: To assess changes in cervical cancer screening after the 2009 American College of Obstetricians and Gynecologists' guideline change and to determine predictors associated with underscreening and overscreening among Medicaid-enrolled women.

METHODS: We performed an observational cohort study of Pennsylvania Medicaid claims from 2007 to 2013. We evaluated guideline adherence of 18- to 64-year-old continuously enrolled women before and after the 2009 guideline change. To define adherence, we categorized intervals between Pap tests as longer than (underscreening), within (appropriate screening), or shorter than (overscreening) guideline-recommended intervals (±6-month). We stratified results by age and assessed predictors of underscreening and overscreening through logistic regression.

RESULTS: Among 29,650 women, appropriate cervical cancer screening significantly decreased after the guideline change (from 45% [95% confidence interval (CI) 44-46%] to 11% [95% CI 11-12%] among 17,360 younger than 30 year olds and from 27% [95% CI 26-28%] to 6% [95% CI 6-7%] among 12,290 women 30 years old or older). Overscreening significantly increased (from 6% [95% CI 5-6%] to 67% [95% CI 66-68%] in those younger than 30 years old and from 54% [95% CI 52-55%] to 65% [95% CI 64-67%] in those 30 years old or older), whereas underscreening significantly increased only in those 30 years old or older (from 20% [95% CI 19-21%] to 29% [95% CI 27-30%]). Pap tests after guideline change, pregnancy, Managed Care enrollment (in those younger than 30 years old), and black race (in those younger than 30 years old) were associated with underscreening. Pap tests after guideline change, more visits, more sexually transmitted infection testing, and white race (in those 30 years old or older) were associated with overscreening.

CONCLUSION: We observed high rates of cervical cancer overscreening and underscreening and low rates of appropriate screening after the guideline change. Interventions should target both underscreening and overscreening to address these separate yet significant issues.