The Affordable Care Act Medicaid expansion: A difference-in-differences study of spillover participation in SNAP

The Affordable Care Act’s Medicaid expansion to individuals with adults under 138 percent of the federal poverty level led to insurance coverage for millions of Americans in participating states. This study investigates Medicaid expansion’s potential spillover participation in the Supplemental Nutrition Assistance Program (SNAP; formerly the Food Stamp Program). In addition to providing public insurance, the policy connects individuals to SNAP, affecting social determinants of health such as hunger. We use difference-in-differences regression to estimate the effect of the Medicaid expansion on SNAP participation among approximately 414,000 individuals from across the United States. The Current Population Survey is used to answer the main research question, and the SNAP Quality Control Database allows for supplemental analyses. Medicaid expansion produces a 2.9 percentage point increase (p = 0.002) in SNAP participation among individuals under 138 percent of federal poverty. Subgroup analyses find a larger 5.0 percentage point increase (p = 0.002) in households under 75 percent of federal poverty without children. Able-Bodied Adults Without Dependents (ABAWDs) are a category of individuals with limited access to SNAP. Although they are a subset of adults without children, we found no spillover effect for ABAWDs. We find an increase in SNAP households with $0 income, supporting the finding that spillover was strongest for very-low-income individuals. Joint processing of Medicaid and SNAP applications helps facilitate the connection between Medicaid expansion and SNAP. Our findings contribute to a growing body of evidence that Medicaid expansion does more than improve access to health care by connecting eligible individuals to supports like SNAP. SNAP recipients have increased access to food, an important social determinant of health. Our study supports reducing administrative burdens to help connect individuals to safety net programs. Finally, we note that ABAWDs are a vulnerable group that need targeted program outreach.

FQHC Designation and Safety Net Patient Revenue Associated with Primary Care Practice Capabilities for Access and Quality

BACKGROUND

Concerns exist about the ability of safety net health care organizations to participate in US health care reform. Primary care practices are key to several efforts, but little is known about how capabilities of primary care practices serving a high share of disadvantaged patients compare to other practices.

OBJECTIVE

To assess capabilities around access to and quality of care among primary care practices serving a high share of Medicaid and uninsured patients compared to practices serving a low share of these patients.

DESIGN

We analyzed data from the National Survey of Healthcare Organizations and Systems (response rate 46.8%), conducted 2017-2018.

PARTICIPANTS

A total of 2190 medical practices with at least three adult primary care physicians.

MAIN MEASURES

Our key exposures are payer mix and federally qualified health center (FQHC) designation. We classified practices as safety net if they reported a combined total of at least 25% of annual revenue from uninsured or Medicaid patients; we then further classified safety net practices into those that identified as an FQHC and those that did not.

KEY RESULTS

FQHCs were more likely than other safety net practices and non-safety net practices to offer early or late appointments (79%, 55%, 62%; p=0.001) and weekend appointments (56%, 39%, 42%; p=0.03). FQHCs more often provided medication-assisted treatment for opioid use disorders (43%, 27%, 25%; p=0.004) and behavioral health services (82%, 50%, 36%; p<0.001). FQHCs were more likely to screen patients for social and financial needs. However, FQHCs and other safety net providers had more limited electronic health record (EHR) capabilities (61%, 71%, 80%; p<0.001).

CONCLUSION

FQHCs were more likely than other types of primary care practices (both safety net practices and other practices) to possess capabilities related to access and quality. However, safety net practices were less likely than non-safety net practices to possess health information technology capabilities.

Predicting self-intercepted medication ordering errors using machine learning

Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to miss important risk factors associated with medication ordering errors. Previously, we described a dataset of CPOE-based medication voiding accompanied by univariable and multivariable regression analyses. However, these traditional techniques require expert guidance and may perform poorly compared to newer approaches. In this paper, we update that analysis using machine learning (ML) models to predict erroneous medication orders and identify its contributing factors. We retrieved patient demographics (race/ethnicity, sex, age), clinician characteristics, type of medication order (inpatient, prescription, home medication by history), and order content. We compared logistic regression, random forest, boosted decision trees, and artificial neural network models. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). The dataset included 5,804,192 medication orders, of which 28,695 (0.5%) were voided. ML correctly classified voids at reasonable accuracy; with a positive predictive value of 10%, ~20% of errors were included. Gradient boosted decision trees achieved the highest AUROC (0.7968) and AUPRC (0.0647) among all models. Logistic regression had the poorest performance. Models identified predictive factors with high face validity (e.g., student orders), and a decision tree revealed interacting contexts with high rates of errors not identified by previous regression models. Prediction models using order-entry information offers promise for error surveillance, patient safety improvements, and targeted clinical review. The improved performance of models with complex interactions points to the importance of contextual medication ordering information for understanding contributors to medication errors.

How can healthcare professionals provide guidance and support to parents of adolescents? Results from a primary care-based study

BACKGROUND

This study explored the rewards and difficulties of raising an adolescent and investigated parents' level of interest in receiving guidance from healthcare providers on parenting and adolescent health topics. Additionally, this study investigated whether parents were interested in parenting programs in primary care and explored methods in which parents want to receive guidance.

METHODS

Parents of adolescents (ages 12-18) who attended an outpatient pediatric clinic with their adolescent were contacted by telephone and completed a short telephone survey. Parents were asked open-ended questions regarding the rewards and difficulties of parenting and rated how important it was to receive guidance from a healthcare provider on certain parenting and health topics. Additionally, parents reported their level of interest in a parenting program in primary care and rated how they would like to receive guidance.

RESULTS

Our final sample included 104 parents, 87% of whom were interested in a parenting program within primary care. A variety of parenting rewards and difficulties were associated with raising an adolescent. From the list of parenting topics, communication was rated very important to receive guidance on (65%), followed by conflict management (50%). Of health topics, parents were primarily interested in receiving guidance on sex (77%), mental health (75%), and alcohol and drugs (74%). Parents in the study wanted to receive guidance from a pediatrician or through written literature.

CONCLUSIONS

The current study finds that parents identify several rewarding and difficult aspects associated with raising an adolescent and are open to receiving guidance on a range of parenting topics in a variety of formats through primary care settings. Incorporating such education into healthcare visits could improve parents' knowledge. Healthcare providers are encouraged to consider how best to provide parenting support during this important developmental time period.

Hospital Readmissions After Implementation of a Discharge Care Program for Patients with COVID-19 Illness

BACKGROUND

The surge of coronavirus 2019 (COVID-19) hospitalizations in New York City required rapid discharges to maintain hospital capacity.

OBJECTIVE

To determine whether lenient provisional discharge guidelines with remote monitoring after discharge resulted in safe discharges home for patients hospitalized with COVID-19 illness.

DESIGN

Retrospective case series SETTING: Tertiary care medical center PATIENTS: Consecutive adult patients hospitalized with COVID-19 illness between March 26, 2020, and April 8, 2020, with a subset discharged home INTERVENTIONS: COVID-19 Discharge Care Program consisting of lenient provisional inpatient discharge criteria and option for daily telephone monitoring for up to 14 days after discharge MEASUREMENTS: Fourteen-day emergency department (ED) visits and hospital readmissions RESULTS: Among 812 patients with COVID-19 illness hospitalized during the study time period, 15.5% died prior to discharge, 24.1% remained hospitalized, 10.0% were discharged to another facility, and 50.4% were discharged home. Characteristics of the 409 patients discharged home were mean (SD) age 57.3 (16.6) years; 245 (59.9%) male; 27 (6.6%) with temperature ≥ 100.4 °F; and 154 (37.7%) with oxygen saturation < 95% on day of discharge. Over 14 days of follow-up, 45 patients (11.0%) returned to the ED, of whom 31 patients (7.6%) were readmitted. Compared to patients not referred, patients referred for remote monitoring had fewer ED visits (8.3% vs 14.1%; OR 0.60, 95% CI 0.31-1.15, p = 0.12) and readmissions (6.9% vs 8.3%; OR 1.15, 95% CI 0.52-2.52, p = 0.73).

LIMITATIONS

Single-center study; assignment to remote monitoring was not randomized.

CONCLUSIONS

During the COVID-19 surge in New York City, lenient discharge criteria in conjunction with remote monitoring after discharge were associated with a rate of early readmissions after COVID-related hospitalizations that was comparable to the rate of readmissions after other reasons for hospitalization before the COVID pandemic.

The Systematic Review Data Repository (SRDR): descriptive characteristics of publicly available data and opportunities for research

BACKGROUND

Conducting systematic reviews ("reviews") requires a great deal of effort and resources. Making data extracted during reviews available publicly could offer many benefits, including reducing unnecessary duplication of effort, standardizing data, supporting analyses to address secondary research questions, and facilitating methodologic research. Funded by the US Agency for Healthcare Research and Quality (AHRQ), the Systematic Review Data Repository (SRDR) is a free, web-based, open-source, data management and archival platform for reviews. Our specific objectives in this paper are to describe (1) the current extent of usage of SRDR and (2) the characteristics of all projects with publicly available data on the SRDR website.

METHODS

We examined all projects with data made publicly available through SRDR as of November 12, 2019. We extracted information about the characteristics of these projects. Two investigators extracted and verified the data.

RESULTS

SRDR has had 2552 individual user accounts belonging to users from 80 countries. Since SRDR's launch in 2012, data have been made available publicly for 152 of the 735 projects in SRDR (21%), at a rate of 24.5 projects per year, on average. Most projects are in clinical fields (144/152 projects; 95%); most have evaluated interventions (therapeutic or preventive) (109/152; 72%). The most frequent health areas addressed are mental and behavioral disorders (31/152; 20%) and diseases of the eye and ocular adnexa (23/152; 15%). Two-thirds of the projects (104/152; 67%) were funded by AHRQ, and one-sixth (23/152; 15%) are Cochrane reviews. The 152 projects each address a median of 3 research questions (IQR 1-5) and include a median of 70 studies (IQR 20-130).

CONCLUSIONS

Until we arrive at a future in which the systematic review and broader research communities are comfortable with the accuracy of automated data extraction, re-use of data extracted by humans has the potential to help reduce redundancy and costs. The 152 projects with publicly available data through SRDR, and the more than 15,000 studies therein, are freely available to researchers and the general public who might be working on similar reviews or updates of reviews or who want access to the data for decision-making, meta-research, or other purposes.

Implicit gender bias among US resident physicians

BACKGROUND

The purpose of this study was to characterize implicit gender bias among residents in US Emergency Medicine and OB/GYN residencies.

METHODS

We conducted a survey of all allopathic Emergency Medicine and OB/GYN residency programs including questions about leadership as well as an implicit association test (IAT) for unconscious gender bias. We used descriptive statistics to analyze the Likert-type survey responses and used standard IAT analysis methods. We conducted univariate and multivariate analyses to identify factors that were associated with implicit bias. We conducted a subgroup analysis of study sites involved in a multi-site intervention study to determine if responses were different in this group.

RESULTS

Overall, 74% of the programs had at least one respondent. Out of 14,234 eligible, 1634 respondents completed the survey (11.5%). Of the five sites enrolled in the intervention study, 244 of 359 eligible residents completed the survey (68%). Male residents had a mean IAT score of 0.31 (SD 0.23) and females 0.14 (SD 0.24), both favoring males in leadership roles and the difference was statistically significant (p < 0.01). IAT scores did not differ by postgraduate year (PGY). Multivariable analysis of IAT score and participant demographics confirmed a significant association between female gender and lower IAT score. Explicit bias favoring males in leadership roles was associated with increased implicit bias favoring males in leadership roles (r = 0.1 p < 0.001).

CONCLUSIONS

We found that gender bias is present among US residents favoring men in leadership positions, this bias differs between male and female residents, and is associated with discipline. Implicit bias did not differ across training years, and is associated with explicit bias.

Inpatient burden of juvenile dermatomyositis among children in the United States

BACKGROUND

Juvenile dermatomyositis (JDM) is a rare autoimmune disease that causes significant morbidity and quality of life impairment. Little is known about the inpatient burden of JDM in the US. Our goal was to determine the prevalence and risk factors for hospitalization with juvenile dermatomyositis and assess inpatient burden of JDM.

METHODS

Data on 14,401,668 pediatric hospitalizations from the 2002-2012 Nationwide Inpatient Sample (NIS) was analyzed. ICD-9-CM coding was used to identify hospitalizations with a diagnosis of JDM.

RESULTS

There were 909 and 495 weighted admissions with a primary or secondary diagnosis of JDM, respectively. In multivariable logistic regression models with stepwise selection, female sex (logistic regression; adjusted odds ratio [95% confidence interval]) (2.22 [2.05-2.42]), non-winter season (fall: 1.18[1.06-1.33]; spring (1.13 [1.01-1.27]; summer (1.53 [1.37-1.71]), non-Medicaid administered government insurance coverage (2.59 [2.26-2.97]), and multiple chronic conditions (2-5: 1.41[1.30-1.54]; 6+: 1.24[1.00-1.52]) were all associated with higher rates of hospitalization for JDM. The weighted total length of stay (LOS) and inflation-adjusted cost of care for patients with a primary inpatient diagnosis of JDM was 19,159 days and $49,339,995 with geometric means [95% CI] of 2.50 [2.27-2.76] days and $7350 [$6228-$8674], respectively. Costs of hospitalization in primary JDM and length of stay and cost in secondary JDM were significantly higher compared to those without JDM. Notably, race/ethnicity was associated with increased LOS (log-linear regression; adjusted beta [95% confidence interval]) (Hispanic: 0.28 [0.14-0.41]; other non-white: 0.59 [0.31-0.86]) and cost of care (Hispanic: 0.30 [0.05-0.55]).

CONCLUSION

JDM contributes to both increased length of hospitalization and inpatient cost of care. Non-Medicaid government insurance was associated with higher rates of hospitalization for JDM while Hispanic and other non-white racial/ethnic groups demonstrated increased LOS and cost of care.

Registration of published randomized trials: a systematic review and meta-analysis

BACKGROUND

Prospective trial registration is a powerful tool to prevent reporting bias. We aimed to determine the extent to which published randomized controlled trials (RCTs) were registered and registered prospectively.

METHODS

We searched MEDLINE and EMBASE from January 2005 to October 2017; we also screened all articles cited by or citing included and excluded studies, and the reference lists of related reviews. We included studies that examined published RCTs and evaluated their registration status, regardless of medical specialty or language. We excluded studies that assessed RCT registration status only through mention of registration in the published RCT, without searching registries or contacting the trial investigators. Two independent reviewers blinded to the other's work performed the selection. Following PRISMA guidelines, two investigators independently extracted data, with discrepancies resolved by consensus. We calculated pooled proportions and 95% confidence intervals using random-effects models.

RESULTS

We analyzed 40 studies examining 8773 RCTs across a wide range of clinical specialties. The pooled proportion of registered RCTs was 53% (95% confidence interval 44% to 58%), with considerable between-study heterogeneity. A subset of 24 studies reported data on prospective registration across 5529 RCTs. The pooled proportion of prospectively registered RCTs was 20% (95% confidence interval 15% to 25%). Subgroup analyses showed that registration was higher for industry-supported and larger RCTs. A meta-regression analysis across 19 studies (5144 RCTs) showed that the proportion of registered trials significantly increased over time, with a mean proportion increase of 27%, from 25 to 52%, between 2005 and 2015.

CONCLUSIONS

The prevalence of trial registration has increased over time, but only one in five published RCTs is prospectively registered, undermining the validity and integrity of biomedical research.

Socialization, legitimation and the transfer of biomedical knowledge to low- and middle-income countries: analyzing the case of emergency medicine in India

BACKGROUND

Medical specialization is a key feature of biomedicine, and is a growing, but weakly understood aspect of health systems in many low- and middle-income countries (LMICs), including India. Emergency medicine is an example of a medical specialty that has been promoted in India by several high-income country stakeholders, including the Indian diaspora, through transnational and institutional partnerships. Despite the rapid evolution of emergency medicine in comparison to other specialties, this specialty has seen fragmentation in the stakeholder network and divergent training and policy objectives. Few empirical studies have examined the influence of stakeholders from high-income countries broadly, or of diasporas specifically, in transferring knowledge of medical specialization to LMICs. Using the concepts of socialization and legitimation, our goal is to examine the transfer of medical knowledge from high-income countries to LMICs through domestic, diasporic and foreign stakeholders, and the perceived impact of this knowledge on shaping health priorities in India.

METHODS

This analysis was conducted as part of a broader study on the development of emergency medicine in India. We designed a qualitative case study focused on the early 1990s until 2015, analyzing data from in-depth interviewing (n = 87), document review (n = 248), and non-participant observation of conferences and meetings (n = 6).

RESULTS

From the early 1990s, domestic stakeholders with exposure to emergency medicine in high-income countries began to establish Emergency Departments and initiate specialist training in the field. Their efforts were amplified by the active legitimation of emergency medicine by diasporic and foreign stakeholders, who formed transnational partnerships with domestic stakeholders and organized conferences, training programs and other activities to promote the field in India. However, despite a broad commitment to expanding specialist training, the network of domestic, diasporic and foreign stakeholders was highly fragmented, resulting in myriad unstandardized postgraduate training programs and duplicative policy agendas. Further, the focus in this time period was largely on training specialists, resulting in more emphasis on a medicalized, tertiary-level form of care.

CONCLUSIONS

This analysis reveals the complexities of the roles and dynamics of domestic, diasporic and foreign stakeholders in the evolution of emergency medicine in India. More research and critical analyses are required to explore the transfer of medical knowledge, such as other medical specialties, models of clinical care, and medical technologies, from high-income countries to India.

Bias caused by sampling error in meta-analysis with small sample sizes

BACKGROUND

Meta-analyses frequently include studies with small sample sizes. Researchers usually fail to account for sampling error in the reported within-study variances; they model the observed study-specific effect sizes with the within-study variances and treat these sample variances as if they were the true variances. However, this sampling error may be influential when sample sizes are small. This article illustrates that the sampling error may lead to substantial bias in meta-analysis results.

METHODS

We conducted extensive simulation studies to assess the bias caused by sampling error. Meta-analyses with continuous and binary outcomes were simulated with various ranges of sample size and extents of heterogeneity. We evaluated the bias and the confidence interval coverage for five commonly-used effect sizes (i.e., the mean difference, standardized mean difference, odds ratio, risk ratio, and risk difference).

RESULTS

Sampling error did not cause noticeable bias when the effect size was the mean difference, but the standardized mean difference, odds ratio, risk ratio, and risk difference suffered from this bias to different extents. The bias in the estimated overall odds ratio and risk ratio was noticeable even when each individual study had more than 50 samples under some settings. Also, Hedges' g, which is a bias-corrected estimate of the standardized mean difference within studies, might lead to larger bias than Cohen's d in meta-analysis results.

CONCLUSIONS

Cautions are needed to perform meta-analyses with small sample sizes. The reported within-study variances may not be simply treated as the true variances, and their sampling error should be fully considered in such meta-analyses.

Surgeon leadership style and risk-adjusted patient outcomes

BACKGROUND

There are many reasons to believe that surgeon personality traits and related leadership behaviors influence patient outcomes. For example, participation in continuing education, effective self-reflection, and openness to feedback are associated with certain personalities and may also lead to improvement in outcomes. In this context, we sought to determine if an individual surgeon's thinking and behavior traits correlate with patient level outcomes after bariatric surgery.

METHODS

Practicing surgeons from the Michigan Bariatric Surgery Collaborative (MBSC) were administered the Life Styles Inventory (LSI) assessment. The results of this assessment were then collapsed into three major styles that corresponded with particular patterns of an individual's thinking and behavior: constructive (achievement, self-actualizing, humanistic-encouraging, affiliative), passive/defensive (approval, conventional, dependent, avoidance), and aggressive/defensive (perfectionistic, competitive, power, oppositional). We compared patients level outcomes for surgeons in the lowest, middle, and highest quintiles for each style. We then used patient level risk-adjusted rates of complications after bariatric surgery to quantify the impact surgeon style on post-operative outcomes.

RESULTS

We found that patients undergoing bariatric surgery performed by surgeons with high levels of constructive (achievement, self-actualizing, humanistic-encouraging, affiliative) and passive/defensive (approval, conventional, dependent, avoidance) styles had lower rates of adverse events compared with surgeons with low levels of the respective styles [High constructive: 14.7% (13.8-15.6%), low constructive: 17.7% (16.8-18.6%); high passive: 14.8% (13.4-16.1%), low passive: 18.7% (17.3-19.9%)]. Conversely, surgeons identified with high aggressive styles (perfectionistic, competitive, power, oppositional) had similar rates of post-operative adverse events compared with surgeons with low levels [high aggressive: 15.2% (14.3-16.1%), low aggressive: 14.9% (14.2-15.6%)].

CONCLUSION

Our analysis demonstrates that surgeons' leadership styles are correlated with surgical outcomes for individual patients. This finding underscores the need for professional development for surgeons to cultivate strengths in the constructive domains including intentional self-improvement, development of interpersonal skills, and the receptiveness to feedback.

Adolescents and Long-Acting Reversible Contraception: Lessons from Mexico

Objectives We describe current use of long acting reversible contraception LARC (tier 1), hormonal (tier 2), barrier and traditional contraceptive methods (tier 3) by adolescent women in Mexico. We test whether knowledge of contraceptive methods is associated with current use of LARC. Methods We used the 1992, 1997, 2006, 2009 and 2014 waves of a nationally representative survey (ENADID). We used information from n = 10,376 (N = 3,635,558) adolescents (15-19 years) who reported ever using any contraceptive method. We used descriptive statistics and logistic regression models to test the association of knowledge of method tiers with use of tier 1 (LARC) versus tier 2, tier 3, and no contraceptive use. Results Over time, LARC use in the overall sample was flat (21 % in 1992, 23 % in 2014; p = 0.130). Among adolescents who have had a pregnancy, LARC use has increased (24 % in 1992 to 37 % in 2014). Among adolescents who did not report a pregnancy, current LARC use has remained low (1 % in 1992 and 2 % in 2014). We found positive association between LARC use and knowledge of tier 1 methods. In the overall sample LARC use is strongly correlated with exposure to marriage compared to use of tier 2 or tier 3 methods. Discussion Among adolescents in Mexico who are currently using modern methods, LARC use is relatively high, but remains primarily tied to having had a pregnancy. Our study highlights the need to expand access to LARC methods outside the post-partum hospital setting.

Challenges and Strategies for Prevention of Multidrug-Resistant Organism Transmission in Nursing Homes

PURPOSE OF REVIEW

Nursing home residents are at high risk for colonization and infection with bacterial pathogens that are multidrug-resistant organisms (MDROs). We discuss challenges and potential solutions to support implementing effective infection prevention and control practices in nursing homes.

RECENT FINDINGS

Challenges include a paucity of evidence that addresses MDRO transmission during the care of nursing home residents, limited staff resources in nursing homes, insufficient infection prevention education in nursing homes, and perceptions by nursing home staff that isolation and contact precautions negatively influence the well being of their residents. A small number of studies provide evidence that specifically address these challenges. Their outcomes support a paradigm shift that moves infection prevention and control practices away from a pathogen-specific approach and toward one that focuses on resident risk factors.

Recommendations for patient engagement in guideline development panels: A qualitative focus group study of guideline-naïve patients

Background

Patient and consumer engagement in clinical practice guideline development is internationally advocated, but limited research explores mechanisms for successful engagement.

Objective

To investigate the perspectives of potential patient/consumer guideline representatives on topics pertaining to engagement including guideline development group composition and barriers to and facilitators of engagement.

Setting and participants

Participants were guideline-naïve volunteers for programs designed to link community members to academic research with diverse ages, gender, race, and degrees of experience interacting with health care professionals.

Methods

Three focus groups and one key informant interview were conducted and analyzed using a qualitative descriptive approach.

Results

Participants recommended small, diverse guideline development groups engaging multiple patient/consumer stakeholders with no prior relationships with each other or professional panel members. No consensus was achieved on the ideal balance of patient/consumer and professional stakeholders. Pre-meeting reading/training and an identified contact person were described as keys to successful early engagement; skilled facilitators, understandable speech and language, and established mechanisms for soliciting patient opinions were suggested to enhance engagement at meetings.

Conclusions

Most suggestions for effective patient/consumer engagement in guidelines require forethought and planning but little additional expense, making these strategies easily accessible to guideline developers desiring to achieve more meaningful patient and consumer engagement.

The Potential Cost-Effectiveness of HIV Vaccines: A Systematic Review

OBJECTIVE

The aim of this paper was to review and compare HIV vaccine cost-effectiveness analyses and describe the effects of uncertainty in model, methodology, and parameterization.

METHODS

We systematically searched MEDLINE (1985 through May 2016), EMBASE, the Tufts CEA Registry, and reference lists of articles following Cochrane guidelines and PRISMA reporting. Eligibility criteria included peer-reviewed manuscripts with economic models estimating cost-effectiveness of preventative HIV vaccines. Two reviewers independently assessed study quality and extracted data on model assumptions, characteristics, input parameters, and outcomes.

RESULTS

The search yielded 71 studies, of which 11 met criteria for inclusion. Populations included low-income (n=7), middle-income (n=4), and high-income countries (n=2). Model structure varied including decision tree (n=1), Markov (n=5), compartmental (n=4), and microsimulation (n=1). Most measured outcomes in quality adjusted life-years (QALYs) gained (n=6) while others used unadjusted (n=3) or disability adjusted life-years (n=2). HIV vaccine cost ranged from $1.54 -$75 USD in low-income countries, $55-$100 in middle-income countries, and $500-$1,000 in the United States. Base case ICERs ranged from dominant (cost-offsetting) to $91,000 per QALY gained.

CONCLUSION

Most models predicted HIV vaccines would be cost-effective. Model assumptions about vaccine price, HIV treatment costs, epidemic context, and willingness to pay influenced results more consistently than assumptions on HIV transmission dynamics.

Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews

BACKGROUND

Drug information compendia and drug-drug interaction information databases are critical resources for clinicians and pharmacists working to avoid adverse events due to exposure to potential drug-drug interactions (PDDIs). Our goal is to develop information models, annotated data, and search tools that will facilitate the interpretation of PDDI information. To better understand the information needs and work practices of specialists who search and synthesize PDDI evidence for drug information resources, we conducted an inquiry that combined a thematic analysis of published literature with unstructured interviews.

METHODS

Starting from an initial set of relevant articles, we developed search terms and conducted a literature search. Two reviewers conducted a thematic analysis of included articles. Unstructured interviews with drug information experts were conducted and similarly coded. Information needs, work processes, and indicators of potential strengths and weaknesses of information systems were identified.

RESULTS

Review of 92 papers and 10 interviews identified 56 categories of information needs related to the interpretation of PDDI information including drug and interaction information; study design; evidence including clinical details, quality and content of reports, and consequences; and potential recommendations. We also identified strengths/weaknesses of PDDI information systems.

CONCLUSIONS

We identified the kinds of information that might be most effective for summarizing PDDIs. The drug information experts we interviewed had differing goals, suggesting a need for detailed information models and flexible presentations. Several information needs not discussed in previous work were identified, including temporal overlaps in drug administration, biological plausibility of interactions, and assessment of the quality and content of reports. Richly structured depictions of PDDI information may help drug information experts more effectively interpret data and develop recommendations. Effective information models and system designs will be needed to maximize the utility of this information.

Using qualitative comparative analysis in a systematic review of a complex intervention

BACKGROUND

Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review.

METHODS

We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions.

RESULTS

Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA.

CONCLUSIONS

QCA was suitable for use within a systematic review of medication adherence interventions and offered insights beyond the single dimension stratifications used in the original completed review. Future prospective use of QCA during a review is needed to determine the optimal way to efficiently integrate QCA into existing approaches to evidence synthesis of complex interventions.

Differences in severity at admission for heart failure between rural and urban patients: the value of adding laboratory results to administrative data

BACKGROUND

Rural/urban variations in admissions for heart failure may be influenced by severity at hospital presentation and local practice patterns. Laboratory data reflect clinical severity and guide hospital admission decisions and treatment for heart failure, a costly chronic illness and a leading cause of hospitalization among the elderly. Our main objective was to examine the role of laboratory test results in measuring disease severity at the time of admission for inpatients who reside in rural and urban areas.

METHODS

We retrospectively analyzed discharge data on 13,998 hospital discharges for heart failure from three states, Hawai'i, Minnesota, and Virginia. Hospital discharge records from 2008 to 2012 were derived from the State Inpatient Databases of the Healthcare Cost and Utilization Project, and were merged with results of laboratory tests performed on the admission day or up to two days before admission. Regression models evaluated the relationship between clinical severity at admission and patient urban/rural residence. Models were estimated with and without use of laboratory data.

RESULTS

Patients residing in rural areas were more likely to have missing laboratory data on admission and less likely to have abnormal or severely abnormal tests. Rural patients were also less likely to be admitted with high levels of severity as measured by the All Patient Refined Diagnosis Related Groups (APR-DRG) severity subclass, derivable from discharge data. Adding laboratory data to discharge data improved model fit. Also, in models without laboratory data, the association between urban compared to rural residence and APR-DRG severity subclass was significant for major and extreme levels of severity (OR 1.22, 95% CI 1.03-1.43 and 1.55, 95% CI 1.26-1.92, respectively). After adding laboratory data, this association became non-significant for major severity and was attenuated for extreme severity (OR 1.12, 95% CI 0.94-1.32 and 1.43, 95% CI 1.15-1.78, respectively).

CONCLUSION

Heart failure patients from rural areas are hospitalized at lower severity levels than their urban counterparts. Laboratory test data provide insight on clinical severity and practice patterns beyond what is available in administrative discharge data.