Increasing Safe Outpatient Management of Emergency Department Patients With Pulmonary Embolism: A Controlled Pragmatic Trial.

Background: Many low-risk patients with acute pulmonary embolism (PE) in the emergency department (ED) are eligible for outpatient care but are hospitalized nonetheless. One impediment to home discharge is the difficulty of identifying which patients can safely forgo hospitalization. Objective: To evaluate the effect of an integrated electronic clinical decision support system (CDSS) to facilitate risk stratification and decision making at the site of care for patients with acute PE. Design: Controlled pragmatic trial. (ClinicalTrials.gov: NCT03601676). Setting: All 21 community EDs of an integrated health care delivery system (Kaiser Permanente Northern California). Patients: Adult ED patients with acute PE. Intervention: Ten intervention sites selected by convenience received a multidimensional technology and education intervention at month 9 of a 16-month study period (January 2014 to April 2015); the remaining 11 sites served as concurrent controls. Measurements: The primary outcome was discharge to home from either the ED or a short-term (<24-hour) outpatient observation unit based in the ED. Adverse outcomes included return visits for PE-related symptoms within 5 days and recurrent venous thromboembolism, major hemorrhage, and all-cause mortality within 30 days. A difference-in-differences approach was used to compare pre-post changes at intervention versus control sites, with adjustment for demographic and clinical characteristics. Results: Among 881 eligible patients diagnosed with PE at intervention sites and 822 at control sites, adjusted home discharge increased at intervention sites (17.4% pre- to 28.0% postintervention) without a concurrent increase at control sites (15.1% pre- and 14.5% postintervention). The difference-in-differences comparison was 11.3 percentage points (95% CI, 3.0 to 19.5 percentage points; P = 0.007). No increases were seen in 5-day return visits related to PE or in 30-day major adverse outcomes associated with CDSS implementation. Limitation: Lack of random allocation. Conclusion: Implementation and structured promotion of a CDSS to aid physicians in site-of-care decision making for ED patients with acute PE safely increased outpatient management. Primary Funding Source: Garfield Memorial National Research Fund and The Permanente Medical Group Delivery Science and Physician Researcher Programs.

Emergency Department Prescription Opioids as an Initial Exposure Preceding Addiction.

STUDY OBJECTIVE: Opioid abuse and overdose constitute an ongoing health emergency. Many presume opioids have little potential for iatrogenic addiction when used as directed, particularly in short courses, as is typical of the emergency department (ED) setting. We preliminarily explore the possibility that initial exposure to opioids by EDs could be related to subsequent opioid misuse. METHODS: This cross-sectional study surveyed a convenience sample of patients reporting heroin or nonmedical opioid use at an urban, academic ED. We estimated the proportion whose initial exposure to opioids was a legitimate medical prescription and the proportion of those prescriptions that came from an ED. Secondary measurements included the proportion of patients receiving nonopioid substances before initial opioid exposure, the source of opioids between initial exposure and onset of regular nonmedical use, and time from initial prescription to opioid use disorder. RESULTS: Of 59 subjects, 35 (59%; 95% confidence interval [CI] 47% to 71%) reported they were first exposed to opioids by a legitimate medical prescription, and for 10 of 35 (29%; 95% CI 16% to 45%), the prescription came from an ED. Most medically exposed subjects (28/35; 80%; 95% CI 65% to 91%) reported nonopioid substance use or treatment for nonopioid substance use disorders preceding the initial opioid exposure. Emergency providers were a source of opioids between exposure and onset of regular nonmedical use in 11 of 35 cases (31%; 95% CI 18% to 48%). Thirty-one of the 35 medically exposed subjects reported the time of onset of nonmedical use; median time from exposure to onset of nonmedical use was 6 months for use to get high (N=25; interquartile range [IQR] 2 to 36), 12 months for regular use to get high (N=24; IQR 2 to 36), 18 months for use to avoid withdrawal (N=26; IQR 2 to 38), and 24 months for regular use to avoid withdrawal (N=27; IQR 2 to 48). Eleven subjects (36%; 95% CI 21% to 53%) began nonmedical use within 2 months, and 9 of 11 (82%; 95% CI 53% to 96%) reported nonopioid substance use or treatment for alcohol abuse before initial opioid exposure. CONCLUSION: Although short-term opioid administration by emergency providers is unlikely to cause addiction by itself, ED opioid prescriptions may contribute to the development of addiction in some patients. There is an urgent need for further research to estimate long-term risks of short-course opioid therapy so that the risk of iatrogenic addiction can be appropriately balanced with the benefit of analgesia.

Patient perceptions of a personal health record: a test of the diffusion of innovation model.

BACKGROUND: Personal health records (PHRs) have emerged as an important tool with which patients can electronically communicate with their doctors and doctor's offices. However, there is a lack of theoretical and empirical research on how patients perceive the PHR and the differences in perceptions between users and non-users of the PHR. OBJECTIVE: To apply a theoretical model, the diffusion of innovation model, to the study of PHRs and conduct an exploratory empirical study on the applicability of the model to the study of perceptions of PHRs. A secondary objective was to assess whether perceptions of PHRs predict the perceived value of the PHR for communicating with the doctor's office. METHODS: We first developed a survey capturing perceptions of PHR use and other factors such as sociodemographic characteristics, access and use of technology, perceived innovativeness in the domain of information technology, and perceptions of privacy and security. We then conducted a cross-sectional survey (N = 1500). Patients were grouped into five groups of 300: PHR users (innovators, other users, and laggards), rejecters, and non-adopters. We applied univariate statistical analysis (Pearson chi-square and one-way ANOVA) to assess differences among groups and used multivariate statistical techniques (factor analysis and multiple regression analysis) to assess the presence of factors identified by the diffusion of innovation model and the predictors of our dependent variable (value of PHR for communicating with the doctor's office). RESULTS: Of the 1500 surveys, 760 surveys were returned for an overall response rate of 51%. Computer use among non-adopters (75%) was lower than that among PHR users (99%) and rejecters (92%) (P < .001). Non-adopters also reported a lower score on personal innovativeness in information technology (mean = 2.8) compared to 3.6 and 3.1, respectively, for users and rejecters (P < .001). Four factors identified by the diffusion of innovation model emerged in the factor analysis: ease of use, relative advantage, observability, and trialability. PHR users perceived greater ease of use and relative advantage of the PHR than rejecters and non-adopters (P < .001). Multiple regression analysis showed the following factors as significant positive predictors of the value of PHR for communicating with the doctor's office: relative advantage, ease of use, trialability, perceptions of privacy and security, age, and computer use. CONCLUSION: Our study found that the diffusion of innovation model fits the study of perceptions of the PHR and provides a suitable theoretical and empirical framework to identify the factors that distinguish PHR users from non-users. The ease of use and relative advantage offered by the PHR emerged as the most important domains among perceptions of PHR use and in predicting the value of the PHR. Efforts to improve uptake and use of PHRs should focus on strategies that enhance the ease of use of PHRs and that highlight the relative advantages of PHRs.

E-cigarettes: a rapidly growing Internet phenomenon.

Electronic cigarettes (e-cigarettes) aerosolize nicotine and produce a vapor that emulates that of cigarettes but purportedly has fewer traditional toxins than secondhand smoke. Although e-cigarettes are widely sold online and by retailers, new research suggests that they may contain unexpected toxins and may provide unreliable nicotine delivery. Many countries have already banned or strictly regulated e-cigarettes. Currently in the United States, e-cigarettes are exempt from regulation as drug-delivery devices. Meanwhile, the presence of e-cigarettes on the Internet, including in Web searches, virtual user communities, and online stores where people sell e-cigarettes on commission, is increasing rapidly. Physicians should be aware of the popularity, questionable efficacy claims, and safety concerns of e-cigarettes so that they may counsel patients against use and advocate for research to inform an evidence-based regulatory approach.

Bridging the digital divide: mobile access to personal health records among patients with diabetes.

OBJECTIVES: Some patients lack regular computer access and experience a digital divide that causes them to miss internet-based health innovations. The diffusion of smartphones has increased internet access across the socioeconomic spectrum, and increasing the channels through which patients can access their personal health records (PHRs) could help bridge the divide in PHR use. We examined PHR use through a computer-based Web browser or mobile device. STUDY DESIGN: Cross-sectional historical cohort analysis. METHODS: Among adult patients in the diabetes registry of an integrated healthcare delivery system, we studied the devices used to access their PHR during 2016. RESULTS: Among 267,208 patients with diabetes, 68.1% used the PHR in 2016; 60.6% of all log-ins were via computer and 39.4% were via mobile device. Overall, 63.9% used it from both a computer and mobile device, 29.6% used only a computer, and 6.5% used only a mobile device. After adjustment, patients who were black, Hispanic, or Asian; lived in lower socioeconomic status (SES) neighborhoods; or had lower engagement were all significantly more likely to use the PHR only from a mobile device (P <.05). Patients using the PHR only via mobile device used it less frequently. CONCLUSIONS: Mobile-ready PHRs may increase access among patients facing a digital divide in computer use, disproportionately reaching racial/ethnic minorities and lower SES patients. Nonetheless, even with a mobile-optimized and app-accessible PHR, differences in PHR use by race/ethnicity and SES remain. Continued efforts are needed to increase equitable access to PHRs among patients with chronic conditions.

Tele-Triage Outcomes For Patients With Chest Pain: Comparing Physicians And Registered Nurses.

We took advantage of a change in protocol in an integrated delivery system's telephone consultation service-routing callers complaining of chest pain to physicians instead of registered nurses, whenever feasible-to explore whether tele-triage outcomes differed by staffing type. Comparing outcomes of 11,315 physician-directed calls to those of an equal number of nurse-directed calls in 2013, we found that the physician-directed calls were briefer (eight minutes versus thirteen minutes), produced fewer ED referrals (10 percent versus 16 percent), and resulted in higher patient adherence to the providers' site-of-care recommendation (86 percent versus 82 percent). Mortality rates at seven days were low for both physician- and nurse-directed calls (0.1 percent). We suspect that providers' immediate access to callers' comprehensive electronic health records and patients' rapid access to outpatient care likely contributed to the program's success. Our findings suggest that tele-triage can be used to safely and effectively manage an emergent complaint, and that physicians' expertise may bring additional efficiency to the process.

Risk stratifying emergency department patients with acute pulmonary embolism: Does the simplified Pulmonary Embolism Severity Index perform as well as the original?

INTRODUCTION: The Pulmonary Embolism Severity Index (PESI) is a validated prognostic score to estimate the 30-day mortality of emergency department (ED) patients with acute pulmonary embolism (PE). A simplified version (sPESI) was derived but has not been as well studied in the U.S. We sought to validate both indices in a community hospital setting in the U.S. and compare their performance in predicting 30-day all-cause mortality and classification of cases into low-risk and higher-risk categories. MATERIALS AND METHODS: This retrospective cohort study included adults with acute objectively confirmed PE from 1/2013 to 4/2015 across 21 community EDs. We evaluated the misclassification rate of the sPESI compared with the PESI. We assessed accuracy of both indices with regard to 30-day mortality. RESULTS: Among 3006 cases of acute PE, the 30-day all-cause mortality rate was 4.4%. The sPESI performed as well as the PESI in identifying low-risk patients: both had similar sensitivities, negative predictive values, and negative likelihood ratios. The sPESI, however, classified a smaller proportion of patients as low risk than the PESI (27.5% vs. 41.0%), but with similar low-risk mortality rates (<1%). Compared with the PESI, the sPESI overclassified 443 low-risk patients (14.7%) as higher risk, yet their 30-day mortality was 0.7%. The sPESI underclassified 100 higher-risk patients (3.3%) as low risk who also had a low mortality rate (1.0%). CONCLUSIONS: Both indices identified patients with PE who were at low risk for 30-day mortality. The sPESI, however, misclassified a significant number of low-mortality patients as higher risk, which could lead to unnecessary hospitalizations.

Health care-associated infections: a meta-analysis of costs and financial impact on the US health care system.

IMPORTANCE: Health care-associated infections (HAIs) account for a large proportion of the harms caused by health care and are associated with high costs. Better evaluation of the costs of these infections could help providers and payers to justify investing in prevention. OBJECTIVE: To estimate costs associated with the most significant and targetable HAIs. DATA SOURCES: For estimation of attributable costs, we conducted a systematic review of the literature using PubMed for the years 1986 through April 2013. For HAI incidence estimates, we used the National Healthcare Safety Network of the Centers for Disease Control and Prevention (CDC). STUDY SELECTION: Studies performed outside the United States were excluded. Inclusion criteria included a robust method of comparison using a matched control group or an appropriate regression strategy, generalizable populations typical of inpatient wards and critical care units, methodologic consistency with CDC definitions, and soundness of handling economic outcomes. DATA EXTRACTION AND SYNTHESIS: Three review cycles were completed, with the final iteration carried out from July 2011 to April 2013. Selected publications underwent a secondary review by the research team. MAIN OUTCOMES AND MEASURES: Costs, inflated to 2012 US dollars. RESULTS: Using Monte Carlo simulation, we generated point estimates and 95% CIs for attributable costs and length of hospital stay. On a per-case basis, central line-associated bloodstream infections were found to be the most costly HAIs at $45,814 (95% CI, $30,919-$65,245), followed by ventilator-associated pneumonia at $40,144 (95% CI, $36,286-$44,220), surgical site infections at $20,785 (95% CI, $18,902-$22,667), Clostridium difficile infection at $11,285 (95% CI, $9118-$13,574), and catheter-associated urinary tract infections at $896 (95% CI, $603-$1189). The total annual costs for the 5 major infections were $9.8 billion (95% CI, $8.3-$11.5 billion), with surgical site infections contributing the most to overall costs (33.7% of the total), followed by ventilator-associated pneumonia (31.6%), central line-associated bloodstream infections (18.9%), C difficile infections (15.4%), and catheter-associated urinary tract infections (<1%). CONCLUSIONS AND RELEVANCE: While quality improvement initiatives have decreased HAI incidence and costs, much more remains to be done. As hospitals realize savings from prevention of these complications under payment reforms, they may be more likely to invest in such strategies.

The digital divide in adoption and use of a personal health record.

BACKGROUND: Personal health records (PHRs) offer the potential to improve the patient experience and the quality of patient care. However, the "digital divide," the population-level gap in Internet and computer access, may prevent certain groups from accessing the PHR. METHODS: We conducted a cross-sectional analysis of a PHR within a northeastern health system. We compared adopters (ie, those activating a PHR account online) with nonadopters (ie, those who see a physician offering the PHR but do not activate an account). We further categorized adopters by intensity of PHR use, measured by number of log-ins and number of messages sent to physicians' practices. RESULTS: As of September 30, 2009, among 75,056 patients, 43% had adopted the PHR since 2002. Blacks and Hispanics were less likely to adopt the PHR compared with whites (odds ratio [OR], 0.50; 95% confidence interval [CI], 0.45-0.55; and 0.64; 0.57-0.73, respectively), and those with lower annual income were less likely to adopt the PHR than were those with higher income. Compared with nonadopters, adopters were more likely to have more than 2 comorbidities (OR, 1.27; 95% CI, 1.17-1.30). Use of an aggressive marketing strategy for PHR enrollment increased adoption nearly 3-fold (OR, 2.92; 95% CI, 1.58-5.40). Intensity of use was best predicted by increasing number of comorbidities, followed by race/ethnicity (whites more than blacks and Hispanics) and insurance status. We found no association between income and log-in frequency or secure messages sent. CONCLUSIONS: Despite increasing Internet availability, racial/ethnic minority patients adopted a PHR less frequently than white patients, and patients with the lowest annual income adopted a PHR less often than those with higher incomes. Among adopters, however, income did not have an effect on PHR use.