Publications

Introduction

Recurrent tuberculosis (TB) occurring >2 years after completing treatment for a prior TB episode is most often due to reinfection with a new strain of .

Objectives

We determined the prevalence and outcome of late recurrent TB among hospitalized patients in Kampala, Uganda.

Methods

We conducted a retrospective analysis of patients admitted to Mulago Hospital who had cough of >2 weeks' duration and completed TB treatment >2 years prior to admission. All patients had mycobacterial culture performed on two sputum specimens and vital status ascertained 2-months post-enrollment. We performed modeling to identify predictors of recurrent TB and of survival.

Results

Among 234 patients, 84 (36%) had recurrent TB. Independent predictors included younger age (aOR=0.64, 95% CI=0.42-0.97, p=0.04), chest pain >2 weeks (aOR=3.32, 95% CI=1.38-8.02, p=0.007), severe weight loss ≥5 kilograms (aOR=4.88, 95% CI=1.66-14.29, p=0.004) and presence of ≥1 WHO danger sign of severe illness (aOR=3.55, 95% CI=1.36-9.29, p=0.01). Two-month mortality was 17.8% (95% CI=10.5-29.2%), and was higher among patients not initiated on TB treatment (aHR=16.67, 95% CI=1.18-200, p=0.04), not on ART if HIV-positive (aHR=16.99, 95% CI=1.17-246.47, p=0.04) and with a history of smoking (aHR=1.20, 95% CI=1.03-1.40, p=0.02).

Conclusion

The high prevalence of late recurrent TB likely reflects high levels of TB transmission in Kampala. Increased use of empiric TB treatment and early ART treatment initiation if HIV-positive should be considered in patients with a prior history of TB, particularly if young, with weight loss ≥5kgs, chest pain >2 weeks or ≥1 WHO danger sign of severe illness.

BACKGROUND

New payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs.

OBJECTIVES

To understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations.

METHODS

We interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis.

RESULTS

We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs' decision making in terms of achieving a balance between the components of the Triple Aim-improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs' decisions and ACOs' insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients' interest in personalized medicine.

CONCLUSIONS

As new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations.

BACKGROUND

The growth of "big data" and the emphasis on patient-centered health care have led to the increasing use of two key technologies: personalized medicine and digital medicine. For these technologies to move into mainstream health care and be reimbursed by insurers, it will be essential to have evidence that their benefits provide reasonable value relative to their costs. These technologies, however, have complex characteristics that present challenges to the assessment of their economic value. Previous studies have identified the challenges for personalized medicine and thus this work informs the more nascent topic of digital medicine.

OBJECTIVES

To examine the methodological challenges and future opportunities for assessing the economic value of digital medicine, using personalized medicine as a comparison.

METHODS

We focused specifically on digital biomarker technologies and multigene tests. We identified similarities in these technologies that can present challenges to economic evaluation: multiple results, results with different types of utilities, secondary findings, downstream impact (including on family members), and interactive effects.

RESULTS

Using a structured review, we found that there are few economic evaluations of digital biomarker technologies, with limited results.

CONCLUSIONS

We conclude that more evidence on the effectiveness of digital medicine will be needed but that the experiences with personalized medicine can inform what data will be needed and how such analyses can be conducted. Our study points out the critical need for typologies and terminology for digital medicine technologies that would enable them to be classified in ways that will facilitate research on their effectiveness and value.

INTRODUCTION

Elderly Veterans enrolled in VA Home Based Primary Care (HBPC) programs suffer from many diseases including malnutrition. Nutrition screening tools exist in the VA system but they are inconsistently utilized across ambulatory care programs and are neither research validated nor comparable with non-VA populations. The Mini-Nutritional Assessment short-form (MNA-SF) has been validated in international studies in a variety of settings. The primary aim of this study was to find the prevalence of malnutrition among Veterans enrolled in HBPC programs. The secondary objective was to determine the feasibility of adopting a validated nutrition screening tool (Mini-Nutritional Assessment short-form (MNA-SF)).

METHODS

2252 veterans age 65 and older from 18 HBPC programs from across the country participated in the study. The study period was between April and September 2012. WinPepi (version 11.25) was used for descriptive analysis.

RESULTS

We found that the prevalence of malnutrition was 15% (344/2252) and the prevalence of at risk for malnutrition was 40.3% (909/2252).

DISCUSSION

The MNA-SF is an efficient nutrition screening tool and it can be successfully used for the elderly veterans. The prevalence of malnutrition among veterans was high compared to the community dwelling U.S. civilian elderly population. By preventing and treating malnutrition, health care systems should be able to reduce overall health care costs.

PROBLEM

Academic medical centers (AMCs) and their academic departments are increasingly assuming leadership in the education, science, and implementation of quality improvement (QI) and patient safety efforts. Fostering, recognizing, and promoting faculty leading these efforts is challenging using traditional academic metrics for advancement.

APPROACH

The authors adapted a nationally developed QI portfolio, adopted it into their own department's advancement process in 2012, and tracked its utilization and impact over the first two years of implementation.

OUTCOMES

Sixty-seven QI portfolios were submitted with 100% of faculty receiving their requested academic advancement. Women represented 60% of the submitted portfolios, while the Divisions of General Internal Medicine and Hospital Medicine accounted for 60% of the submissions. The remaining 40% were from faculty in 10 different specialty divisions. Faculty attitudes about the QI portfolio were overwhelmingly positive, with 83% agreeing that it "was an effective tool for helping to better recognize faculty contributions in QI work" and 85% agreeing that it "was an effective tool for elevating the importance of QI work in our department."

NEXT STEPS

The QI portfolio was one part of a broader effort to create opportunities to recognize and support faculty involved in improvement work. Further adapting the tool to ensure that it complements-rather than duplicates-other elements of the advancement process is critical for continued utilization by faculty. This will also drive desired dissemination to other departments locally and other AMCs nationally who are similarly committed to cultivating faculty career paths in systems improvement.

Background

Risk factors may differentially influence development of estrogen receptor (ER)-positive vs -negative breast cancer. We examined associations with strong, prevalent risk factors by ER subtype.

Methods

Of 1 279 443 women age 35 to 74 years participating in the Breast Cancer Surveillance Consortium, 14 969 developed ER-positive and 3617 developed ER-negative invasive breast cancer. We calculated hazard ratios (HRs) using Cox regression and compared ER subtype hazard ratios at representative ages or by menopausal status using Wald tests. All statistical tests were two-sided.

Results

For women age 40 years, compared with no prior biopsy, ER-positive vs ER-negative HRs were 1.53 (95% CI = 1.30 to 1.81) vs 1.26 (95% CI = 0.90 to 1.76) for nonproliferative disease, 1.63 (95% CI = 1.23 to 2.17) vs 1.41 (95% CI = 0.78 to 2.57) for proliferative disease without atypia, and 4.47 (95% CI = 2.88 to 6.96) vs 0.20 (95% CI = 0.02 to 2.51) for proliferative disease with atypia. Benign disease proliferation risk was stronger for ER-positive than ER-negative cancer for women age 35 years (Wald P = .04), age 40 years (Wald P = .04), and age 50 years (Wald P = .06). Among pre/perimenopausal women, body mass index (BMI) had a stronger association with ER-negative than ER-positive cancer (obese II/III vs. normal weight: HR = 1.52, 95% CI = 1.19 to 1.94; vs 1.21, 95% CI = 1.08 to 1.36). Increasing BMI similarly increased ER-positive and ER-negative cancer risk among postmenopausal hormone users (Wald P = .15) and nonusers (Wald P = .08). Associations with ER subtype varied by race/ethnicity across all ages (P < .001) and by family history of breast cancer and breast density for specific ages.

Conclusions

Strength of risk factor associations differed by ER subtype. Separate risk models for ER subtypes may improve identification of women for targeted prevention strategies.