Michael N. Cantor

Using trigger phrases to detect adverse drug reactions in ambulatory care notes

Background: As medical care moves towards an outpatient focus, monitoring systems for ambulatory patients are increasingly important. Because adverse outcomes due to medications are an important problem in outpatients, the authors developed an automated monitoring system for detecting adverse drug reactions (ADRs) in ambulatory patients. Methods: The authors obtained a set of approximately 110 000 ambulatory care notes from the medicine clinic at Bellevue Hospital Centre for 2003–4, and manually analysed a representative sample of 1250 notes to obtain a gold standard. To detect ADRs in the text of electronic ambulatory notes, the authors used a “trigger phrases” methodology, based on a simple grammar populated with a limited set of keywords. Results: Under current functionality, this system detected 38 of 54 cases in the authors’ gold standard set, of which 17 were true positives, for a sensitivity of 31%, a specificity of 98%, and a positive predictive value of 45%. Their proxy measure correlated with 70% of the ADRs in the gold standard. These values are comparable or superior to other systems described in the literature. Conclusions: These results show that an automated system can detect ADRs with moderate sensitivity and high specificity, and has the potential to serve as the basis for a larger scale reporting system.

Barriers to Implementing a Surgical Beta-Blocker Protocol

Article-at-a-Glance Background Experience with a quality improvement (QI) program undertaken to increase the use of beta-adrenergic blockade in at-risk patients at both a major academic medical center and a community hospital suggests barriers to implementation. Methods A retrospective and prospective cohort study was performed to establish the incidence and effectiveness of beta-blockade use pre- and postimplementation of a standardized screening tool and a major education program as part of a QI project. Data gathering involved a baseline phase pre-intervention; 6 weeks postintervention; and 3–6months postintervention. Results During phase I (baseline) 56% of eligible patients received beta-blockers, but targeted measures (a pre-induction heart rate Conclusion Implementation of a quality program for beta-blockade is significantly affected by the presence or absence of ongoing physician and staff education beyond the study period.

Translational informatics: an industry perspective

Translational informatics (TI) is extremely important for the pharmaceutical industry, especially as the bar for regulatory approval of new medications is set higher and higher. This paper will explore three specific areas in the drug development lifecycle, from tools developed by precompetitive consortia to standardized clinical data collection to the effective delivery of medications using clinical decision support, in which TI has a major role to play. Advancing TI will require investment in new tools and algorithms, as well as ensuring that translational issues are addressed early in the design process of informatics projects, and also given higher weight in funding or publication decisions. Ultimately, the source of translational tools and differences between academia and industry are secondary, as long as they move towards the shared goal of improving health.

Integrating Data On Social Determinants Of Health Into Electronic Health Records

As population health becomes more of a focus of health care, providers are realizing that data outside of traditional clinical findings can provide a broader perspective on potential drivers of a patients health status and can identify approaches to improving the effectiveness of care. However, many challenges remain before data related to the social determinants of health, such as environmental conditions and education levels, are as readily accessible and actionable as medical data are. Key challenges are a lack of consensus on standards for capturing or representing social determinants of health in electronic health records and insufficient evidence that once information on them has been collected, social determinants can be effectively addressed through referrals or other action tools. To address these challenges and effectively use social determinants in health care settings, we recommend creating national standards for representing data related to social determinants of health in electronic health records, incentivizing the collection of the data through financial or quality measures, and expanding the body of research that measures the impact of acting on the information collected.

FACETS: using open data to measure community social determinants of health

Objective To develop a dataset based on open data sources reflective of community-level social determinants of health (SDH). Materials and Methods We created FACETS (Factors Affecting Communities and Enabling Targeted Services), an architecture that incorporates open data related to SDH into a single dataset mapped at the census-tract level for New York City. Results FACETS (https://github.com/mcantor2/FACETS) can be easily used to map individual addresses to their census-tract-level SDH. This dataset facilitates analysis across different determinants that are often not easily accessible. Discussion Wider access to open data from government agencies at the local, state, and national level would facilitate the aggregation and analysis of community-level determinants. Timeliness of updates to federal non-census data sources may limit their usefulness. Conclusion FACETS is an important first step in standardizing and compiling SDH-related data in an open architecture that can give context to a patients condition and enable better decision-making when developing a plan of care.

Partner meeting venue typology and sexual risk behaviors among French men who have sex with men

Previous research has given considerable attention to venues where men who have sex with men (MSM) meet their sex partners. However, no previous study examined a vast range of sexual risk behaviors. The objective of this study was to examine the association between the types of venues for meeting sexual partners, condomless anal intercourse, engagement in group sex, and HIV and sexually transmitted infection (STI) risk among a sample of MSM. Users of a popular geosocial-networking app in Paris were provided an advertisement with text encouraging them to complete an anonymous web-based survey (n = 580), which included questions about sex-seeking venues, condomless anal intercourse, HIV status and STI history, and sociodemographic characteristics. A log-binomial model was used to assess association between venues (i.e. public venues [gay clubs, bars, and discos], cruising venues [such as gay saunas, beaches, and parks], and internet-based venues [internet chat sites and geosocial-networking apps]), condomless anal intercourse, engagement in group sex, and HIV infection as well as infection with other STIs, after adjustment for sociodemographics. In multivariable models, attending cruising venues was associated with condomless receptive anal intercourse (adjusted relative risk [aRR] = 1.47; 95% confidence interval [CI] = 1.20–1.81), any kind of condomless anal intercourse (aRR = 1.34; 95% CI = 1.14–1.58), an STI (aRR = 1.50; 95% CI = 1.09–2.05), engagement in group sex (aRR = 1.42; 95% CI = 1.27–1.59), and multiple partners for both condomless insertive (aRR = 2.00; 95% CI = 1.38–2.88), and receptive (aRR = 1.70; 95% CI = 1.23–2.36) anal intercourse, STI infection (aRR = 1.50, 95% CI = 1.09–2.05) and HIV infection (aRR = 1.76; 95% CI = 1.05–2.96). No associations were found with other venue types and sexual risk behaviors, STIs, and HIV infection, except for group sex, which was associated with all venue types. Use of cruising where the primary aim is to have sex was found to be associated with risky sexual behavior. Risky behavior reduction strategies such as preexposure prophylaxis campaigns should be targeted to MSM who frequent cruising venues.

Repurposing historical control clinical trial data to provide safety context.

Billions of dollars spent, millions of subject-hours of clinical trial experience and an abundance of archived study-level data, yet why are historical data underutilized? We propose that historical data can be aggregated to provide safety, background incidence rate and context to improve the evaluation of new medicinal products. Here, we describe the development and application of the eControls database, which is derived from the control arms of studies of licensed products, and discuss the challenges and potential solutions to the proper application of historical data to help interpret product safety.

Health Care Quality A Question of Supply and Demand

Providing quality health care is the goal of every provider in the system, from individual physicians to large integrated networks. In spite of all the resources and personhours put into developing and implementing quality improvement initiatives, one major issue persists: those who benefit most from increased quality—patients—just do not seem to care. We have a major imbalance in the supply and demand for quality in the US health care system, and we need to improve patients’ understanding of and ability to act on quality measures to bring the situation back into balance. The emphasis on the supply side in quality improvement is notable for programs that lead to improvements in quality measures (eg, Get with the Guidelines) or reducing low-value interventions, both of which should ultimately improve outcomes and care for patients. These initiatives become more important as quality and cost data become publicly available. Unfortunately, most patients do not pay attention to public reporting data when choosing their health care providers, mainly because they believe the data are not relevant to them or, more importantly for the supply side, because the data are not presented in a meaningful way. A recent report revealed that most patients focus on bedside manner and personality traits rather than quantitative outcomes when defining quality, and that they trust word-of-mouth recommendations over publicly reported data when choosing health care providers. As doctors, we base our referrals or recommendations on subjective criteria such as relationships and reputations, so it is not surprising that patients take a similar approach. Along this line of reasoning, one could question whether quality even matters at the patient level. Obviously the concept of health care quality and the intention of quality improvement programs matter to patients—the expectation of high-quality care is at least implicit in all patient interactions with the health care system. However, in addition to their complexity, current quality measures have the challenge of being population-based, while patients base their health care decisions on individuallevel characteristics. In reality, most patients likely will have similar outcomes no matter which doctor they see because most patients have common manifestations of common diseases and most doctors are competent. The differences in how they get to the outcomes may be more costly or take longer, but most patients will not know any better because they do not have any alternative for comparison. When many negative individual outcomes coalesce into a trend, reputations, ratings, and patients may suffer; however, the lack of market forces in health care allow even the lowest quality providers to stay in business. If we care about quality and want patients to make educated decisions when choosing their health care providers, we must make the vast supply of quality measures meaningful and important. We have to create demand for objectively high quality care. To accomplish this goal, we must focus on 2 areas: transparency and communication. Health care is like no other market, and at least in the United States, it suffers from a major lack of transparency. Although quality information is available, as already noted, it is often difficult to find, incomprehensible, or not applicable to patients, which is why patients go to informal sites such as Yelp. Luckily, we have 2 excellent models to build on to help fix quality reporting in the United States. One highly successful model is that of fantasy sports. The Internet has allowed fantasy sports leagues to take off, and their success has spurred an entire industry and a slew of new “advanced metrics” to measure player performance. These advanced metrics are often the results of highly complex statistical manipulations based on multiple inputs, but as millions of fantasy owners can attest, they are packaged in a way that is meaningful and understandable. Health care quality reporting agencies could learn from sports statistics suppliers such as the Elias Sports Bureau to figure out new ways to make quality numbers accessible. People who have grown up on PER (player efficiency rating) and VORP (value over replacement player) and know the minute details of the performance of their favorite quarterback should have the same quality of information about the internist treating their 557514 AJMXXX10.1177/1062860614557514American Journal of Medical QualityCantor research-article2014

Barriers to implementing a surgical beta blocker protocol: the Beth Israel cardiac risk reduction initiative

BACKGROUND Experience with a quality improvement (QI) program undertaken to increase the use of beta-adrenergic blockade in at-risk patients at both a major academic medical center and a community hospital suggests barriers to implementation. METHODS A retrospective and prospective cohort study was performed to establish the incidence and effectiveness of beta-blockade use pre- and postimplementation of a standardized screening tool and a major education program as part of a QI project. Data gathering involved a baseline phase pre-intervention; 6 weeks postintervention; and 3-6 months postintervention. RESULTS During phase I (baseline) 56% of eligible received beta-blockers, but targeted measures (a pre-induction heart rate < 70 or a systolic blood pressure [BP] < 110 mmHg) were achieved in only 11% of patients. Phase II saw a significant overall increase in beta-blocker administration (79%) and efficacy (50%). However, during phase III (3-6 months postimplementation), the rate of beta-blocker administration fell to 61% overall, while overall efficacy remained stable at 52%. Significant differences between the academic and community hospitals were observed throughout the study. CONCLUSION Implementation of a quality program for beta-blockade is significantly affected by the presence or absence of ongoing physician and staff education beyond the study period.