Faculty Bibliography

Health system leaders sometimes adopt quality metrics without robust supporting evidence of improvements in quality and/or quantity of life, which may impair rather than facilitate improved health outcomes. In brief, there is now no easy way to measure how much "health" is conferred by a health system. However, we argue that this goal is achievable. Health-weighted composite quality metrics have the potential to measure "health" by synthesizing individual evidence-based quality metrics into a summary measure, utilizing relative weightings that reflect the relative amount of health benefit conferred by each constituent quality metric. Previously, it has been challenging to create health-weighted composite quality metrics because of methodological and data limitations. However, advances in health information technology and mathematical modeling of disease progression promise to help mitigate these challenges by making patient-level data (eg, from the electronic health record and mobile health (mHealth) more accessible and more actionable for use. Accordingly, it may now be possible to use health information technology to calculate and track a health-weighted composite quality metric for each patient that reflects the health benefit conferred to that patient by the health system. These health-weighted composite quality metrics can be employed for a multitude of important aims that improve health outcomes, including quality evaluation, population health maximization, health disparity attenuation, panel management, resource allocation, and personalization of care. We describe the necessary attributes, the possible uses, and the likely limitations and challenges of health-weighted composite quality metrics using patient-level health data.

Aim: Advance directives are often under-informed due to a lack of disease-specific prognostic information. Without well-informed advance directives patients may receive default care that is incongruent with their preferences. We aimed to further inform advance care planning in patients with severe chronic obstructive pulmonary disease by estimating outcomes with alternative advance directives. Methods: We designed a Markov microsimulation model estimating outcomes for patients choosing between the Full Code advance directive (permitting invasive mechanical ventilation), and the Do Not Intubate directive (only permitting noninvasive ventilation). Results: Our model estimates Full Code patients have marginally increased one-year survival after admission for severe respiratory failure, but are more likely to be residing in a nursing home and have frequent rehospitalizations for respiratory failure. Conclusion: Patients with severe chronic obstructive pulmonary disease may consider these potential tradeoffs between survival, rehospitalizations and institutionalization when making informed advance care plans and end-of-life decisions. We highlight outcomes research needs for variables most influential to the model's outcomes, including the risk of complications of invasive mechanical ventilation and failing noninvasive mechanical ventilation.

BACKGROUND: Decision support systems for differential diagnosis have traditionally been evaluated on the basis of criteria how sensitively and specifically they are able to identify the correct diagnosis established by expert clinicians. DISCUSSION: This article questions whether evaluation criteria pertaining to identifying the correct diagnosis are most appropriate or useful. Instead it advocates evaluation of decision support systems for differential diagnosis based on the criterion of maximizing value of information. SUMMARY: This approach quantitatively and systematically integrates several important clinical management priorities, including avoiding serious diagnostic errors of omission and avoiding harmful or expensive tests.

BACKGROUND: and OBJECTIVE: Asymptomatic stenosis of the carotid arteries is associated with stroke. Carotid revascularization can reduce the future risk of stroke but can also trigger an immediate stroke. The objective was to model the generic relationship between immediate risk, long-term benefit, and life expectancy for any one-time prophylactic treatment and then apply the model to the use of revascularization in the management of asymptomatic carotid disease. METHODS: In the "payoff time" framework, the possibility of losing quality-adjusted life-years (QALYs) because of revascularization failure is conceptualized as an "investment" that is eventually recouped over time, on average. Using this framework, we developed simple mathematical forms that define relationships between the following: perioperative probability of stroke (P); annual stroke rate without revascularization (r0); annual stroke rate after revascularization, conditional on not having suffered perioperative stroke (r1); utility levels assigned to the asymptomatic state (ua) and stroke state (us); and mortality rates (lambda). RESULTS: In patients whose life expectancy is below a critical life expectancy $$(\hbox{ CLE }=\frac{P}{(1-P){r}_{0}-{r}_{1}})$$ , the "investment" will never pay off, and revascularization will lead to loss of QALYs, on average. CLE is independent of utilities assigned to the health states if a rank ordering exists in which ua > us. For clinically relevant values (P = 3%, r0 = 1%, r1 = 0.5%), the CLE is approximately 6.4 years, which is longer than published guidelines regarding patient selection for revascularization. CONCLUSIONS: In managing asymptomatic carotid disease, the payoff time framework specifies a CLE beneath which patients, on average, will not benefit from revascularization. This formula is suitable for clinical use at the patient's bedside and can account for patient variability, the ability of clinicians who perform revascularization, and the particular revascularization technology that is chosen.

PURPOSE OF REVIEW: To summarize recent cost-effectiveness analyses (CEAs) that evaluate optimal treatment strategies for persons living with HIV/AIDS (PLWHA). RECENT FINDINGS: Efforts to attain universal coverage of current treatment guidelines (e.g., initiation at CD4 cell count <350 cells/mul) are generally very costeffective. Expansion of access beyond current guidelines will additionally improve clinical outcomes and aversion of new HIV infections; however, cost-effectiveness is more uncertain. Increasing access to antiretroviral therapy (ART) offers greater health benefit than investing the same funds in intensive laboratory monitoring for those on ART, particularly in those settings in which universal coverage has not yet been attained. Recommended ART regimens (e.g., tenofovir) have favorable cost-effectiveness when compared with substitution of newer, more expensive agents (e.g., rilpivirine, darunavir) or substitution of older, cheaper alternatives that are more toxic (e.g., stavudine). SUMMARY: There is increasing use of CEA to evaluate decisions regarding HIV treatment in order to buy the most 'health' with limited resources. Expansion of ART access provides substantial clinical and preventive benefit and offers favorable cost-effectiveness. Intensive laboratory monitoring may not be the highest priority in settings in which resources are constrained. Further work on the economic impact, clinical effectiveness, and feasibility of ART treatment for all (e.g., no CD4 cell initiation criteria) is needed.

BACKGROUND: New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically. METHODS: A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC. RESULTS: Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34% reduction in new HIV infections over the next 20 years. The cost-per-infection averted of the portfolio was estimated to be $106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately $100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately $250 million per year, on average). CONCLUSIONS: Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs.

BACKGROUND: Hospital care on weekends has been associated with reduced quality and poor clinical outcomes, suggesting that decreases in overall intensity of care may have important clinical effects. We describe a new measure of hospital intensity of care based on utilization of the electronic health record (EHR). METHODS: We measured global intensity of care at our academic medical center by monitoring the use of the EHR in 2011. Our primary measure, termed EHR interactions, was the number of accessions of a patient's electronic record by a clinician, adjusted for hospital census, per unit of time. Our secondary measure was percent of total available central processing unit (CPU) power used to access EHR servers at a given time. RESULTS: EHR interactions were lower on weekend days as compared to weekdays at every hour (P < 0.0001), and the daytime peak in intensity noted each weekday was blunted on weekends. The relative rate and 95% confidence interval (CI) of census-adjusted record accessions per patient on weekdays compared with weekends were: 1.76 (95% CI: 1.74-1.77), 1.52 (95% CI: 1.50-1.55), and 1.14 (95% CI: 1.12-1.17) for day, morning/evening, and night hours, respectively. Percent CPU usage correlated closely with EHR interactions (r = 0.90). CONCLUSIONS: EHR usage is a valid and easily reproducible measure of intensity of care in the hospital. Using this measure we identified large, hour-specific differences between weekend and weekday intensity. EHR interactions may serve as a useful measure for tracking and improving temporal variations in care that are common, and potentially deleterious, in hospital systems. Journal of Hospital Medicine 2013;8:513-518. (c) 2013 Society of Hospital Medicine.