Hospital influenza pandemic stockpiling needs: A computer simulation.

BACKGROUND: A severe influenza pandemic could overwhelm hospitals but planning guidance that accounts for the dynamic interrelationships between planning elements is lacking. We developed a methodology to calculate pandemic supply needs based on operational considerations in hospitals and then tested the methodology at Mayo Clinic in Rochester, MN. METHODS: We upgraded a previously designed computer modeling tool and input carefully researched resource data from the hospital to run 10,000 Monte Carlo simulations using various combinations of variables to determine resource needs across a spectrum of scenarios. RESULTS: Of 10,000 iterations, 1,315 fell within the parameters defined by our simulation design and logical constraints. From these valid iterations, we projected supply requirements by percentile for key supplies, pharmaceuticals, and personal protective equipment requirements needed in a severe pandemic. DISCUSSION: We projected supplies needs for a range of scenarios that use up to 100% of Mayo Clinic-Rochester's surge capacity of beds and ventilators. The results indicate that there are diminishing patient care benefits for stockpiling on the high side of the range, but that having some stockpile of critical resources, even if it is relatively modest, is most important. CONCLUSIONS: We were able to display the probabilities of needing various supply levels across a spectrum of scenarios. The tool could be used to model many other hospital preparedness issues, but validation in other settings is needed.

Employment and residential characteristics in relation to automated external defibrillator locations.

BACKGROUND: Survival from out-of-hospital cardiac arrest (OHCA) is generally poor and varies by geography. Variability in automated external defibrillator (AED) locations may be a contributing factor. To inform optimal placement of AEDs, we investigated AED access in a major US city relative to demographic and employment characteristics. METHODS AND RESULTS: This was a retrospective analysis of a Philadelphia AED registry (2,559 total AEDs). The 2010 US Census and the Local Employment Dynamics database by ZIP code was used. Automated external defibrillator access was calculated as the weighted areal percentage of each ZIP code covered by a 400-m radius around each AED. Of 47 ZIP codes, only 9% (4) were high-AED-service areas. In 26% (12) of ZIP codes, less than 35% of the area was covered by AED service areas. Higher-AED-access ZIP codes were more likely to have a moderately populated residential area (P = .032), higher median household income (P = .006), and higher paying jobs (P =. 008). CONCLUSIONS: The locations of AEDs vary across specific ZIP codes; select residential and employment characteristics explain some variation. Further work on evaluating OHCA locations, AED use and availability, and OHCA outcomes could inform AED placement policies. Optimizing the placement of AEDs through this work may help to increase survival.

Use of social media across US hospitals: descriptive analysis of adoption and utilization.

BACKGROUND: Use of social media has become widespread across the United States. Although businesses have invested in social media to engage consumers and promote products, less is known about the extent to which hospitals are using social media to interact with patients and promote health. OBJECTIVE: The aim was to investigate the relationship between hospital social media extent of adoption and utilization relative to hospital characteristics. METHODS: We conducted a cross-sectional review of hospital-related activity on 4 social media platforms: Facebook, Twitter, Yelp, and Foursquare. All US hospitals were included that reported complete data for the Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems survey and the American Hospital Association Annual Survey. We reviewed hospital social media webpages to determine the extent of adoption relative to hospital characteristics, including geographic region, urban designation, bed size, ownership type, and teaching status. Social media utilization was estimated from user activity specific to each social media platform, including number of Facebook likes, Twitter followers, Foursquare check-ins, and Yelp reviews. RESULTS: Adoption of social media varied across hospitals with 94.41% (3351/3371) having a Facebook page and 50.82% (1713/3371) having a Twitter account. A majority of hospitals had a Yelp page (99.14%, 3342/3371) and almost all hospitals had check-ins on Foursquare (99.41%, 3351/3371). Large, urban, private nonprofit, and teaching hospitals were more likely to have higher utilization of these accounts. CONCLUSIONS: Although most hospitals adopted at least one social media platform, utilization of social media varied according to several hospital characteristics. This preliminary investigation of social media adoption and utilization among US hospitals provides the framework for future studies investigating the effect of social media on patient outcomes, including links between social media use and the quality of hospital care and services.

Hidden in plain sight: a crowdsourced public art contest to make automated external defibrillators more visible.

OBJECTIVES: We sought to explore the feasibility of using a crowdsourcing study to promote awareness about automated external defibrillators (AEDs) and their locations. METHODS: The Defibrillator Design Challenge was an online initiative that asked the public to create educational designs that would enhance AED visibility, which took place over 8 weeks, from February 6, 2014, to April 6, 2014. Participants were encouraged to vote for AED designs and share designs on social media for points. Using a mixed-methods study design, we measured participant demographics and motivations, design characteristics, dissemination, and Web site engagement. RESULTS: Over 8 weeks, there were 13 992 unique Web site visitors; 119 submitted designs and 2140 voted. The designs were shared 48 254 times on Facebook and Twitter. Most designers-voters reported that they participated to contribute to an important cause (44%) rather than to win money (0.8%). Design themes included: empowerment, location awareness, objects (e.g., wings, lightning, batteries, lifebuoys), and others. CONCLUSIONS: The Defibrillator Design Challenge engaged a broad audience to generate AED designs and foster awareness. This project provides a framework for using design and contest architecture to promote health messages.

Using a mobile app and mobile workforce to validate data about emergency public health resources.

BACKGROUND: Social media and mobile applications that allow people to work anywhere are changing the way people can contribute and collaborate. OBJECTIVE: We sought to determine the feasibility of using mobile workforce technology to validate the locations of automated external defibrillators (AEDs), an emergency public health resource. METHODS: We piloted the use of a mobile workforce application, to verify the location of 40 AEDs in Philadelphia county. AEDs were pre-identified in public locations for baseline data. The task of locating AEDs was posted online for a mobile workforce from October 2011 to January 2012. Participants were required to submit a mobile phone photo of AEDs and descriptions of the location. RESULTS: Thirty-five of the 40 AEDs were identified within the study period. Most, 91% (32/35) of the submitted AED photo information was confirmed project baseline data. Participants also provided additional data such as business hours and other nearby AEDs. CONCLUSIONS: It is feasible to engage a mobile workforce to complete health research-related tasks. Participants were able to validate information about emergency public health resources.

Where are lifesaving automated external defibrillators located and how hard is it to find them in a large urban city?

OBJECTIVES: Automated external defibrillators (AEDs) are lifesaving, but little is known about where they are located or how to find them. We sought to locate AEDs in high employment areas of Philadelphia and characterize the process of door-to-door surveying to identify these devices. METHODS: Block groups representing approximately the top 3rd of total primary jobs in Philadelphia were identified using the US Census Local Employment Dynamics database. All buildings within these block groups were surveyed during regular working hours over six weeks during July-August 2011. Buildings were characterized as publically accessible or inaccessible. For accessible buildings, address, location type, and AED presence were collected. Total devices, location description and prior use were gathered in locations with AEDs. Process information (total people contacted, survey duration) was collected for all buildings. RESULTS: Of 1420 buildings in 17 block groups, 949 (67%) were accessible, but most 834 (88%) did not have an AED. 283 AEDs were reported in 115 buildings (12%). 81 (29%) were validated through visualization and 68 (24%) through photo because employees often refused access. In buildings with AEDs, several employees (median 2; range 1-8) were contacted to ascertain information, which required several minutes (mean 4; range 1-55). CONCLUSIONS: Door-to-door surveying is a feasible, but time-consuming method for identifying AEDs in high employment areas. Few buildings reported having AEDs and few permitted visualization, which raises concerns about AED access. To improve cardiac arrest outcomes, efforts are needed to improve the availability of AEDs, awareness of their location and access to them.

Value-induced bias in medical decision making.

BACKGROUND: People who exhibit value-induced bias- distorting relevant probabilities to justify medical decisions- may make suboptimal decisions. OBJECTIVE: The authors examined whether and in what conditions people exhibit value-induced bias. DESIGN: Volunteers on the Web imagined having a serious illness with 2 possible diagnoses and a treatment with the same "small probability'' of success for each diagnosis. The more serious diagnosis was designed as a clear-cut decision to motivate most subjects to choose treatment; the less serious diagnosis was designed to make the treatment a close-call choice. Subjects were randomized to estimate the probability of treatment success before or after learning their diagnosis. The "after group'' had the motivation and ability to distort the probability of treatment success to justify their treatment preference. In study 1, subjects learned they had the more serious disease. Consistent with value-induced bias, the after group was expected to give higher probability judgments than the ;;before group.'' In study 2, subjects learned they had the less serious disease, and the after group was expected to inflate the probability if they desired treatment and to reduce it if they did not, relative to the before group. RESULTS: In study 1, there was no difference in the mean probability judgment between groups, suggesting no distortion of probability. In study 2, the slope of probability judgment regressed on desire for treatment was steeper for the after group, indicating that distortion of probability did occur. CONCLUSION: In close-call but not clear-cut medical decisions, people may distort relevant probabilities to justify their preferred choices.

In a mailed physician survey, questionnaire length had a threshold effect on response rate.

OBJECTIVE: To examine the association between questionnaire length and response rate in a mailed survey of generalist physicians randomly selected from the American Medical Association master file. STUDY DESIGN AND SETTING: In a pilot study, otherwise similar questionnaires of 30 different lengths (849 to 1,867 words) were mailed to 192 physicians in April 1999. In the main study, questionnaires of 16 different lengths (564 to 988 words) were mailed to 1,700 physicians between June 1999 and January 2000. RESULTS: In the pilot study, response rate decreased from 60% for questionnaires 849 words in length to 16.7% for questionnaires over 1,800 words in length. Logistic regression revealed an odds ratio of 0.887 (95%CI 0.813, 0.968; p=0.006) for word count, expressed in units of 100 words. In the main study, response rate varied between 51.5% and 71.4%. Logistic regression showed no association between response and word count (OR 0.988; 95%CI 0.896, 1.090; p=0.81). CONCLUSION: There appears to have been a threshold in these studies of approximately 1,000 words. Questionnaires above the threshold had lower response rates than those below it (38.0% vs. 59.4%).

The validity of person tradeoff measurements: randomized trial of computer elicitation versus face-to-face interview.

Can person tradeoff (PTO) value judgments be elicited by a computer, or is a face-to-face interview needed? The authors randomly assigned 95 subjects to interview or computer methods for the PTO, a valuation measure that is often difficult for subjects. They measured relative values of foot numbness, leg paralysis, and quadriplegia (all 3 pairs) at 2 reference group sizes (10 or 100). Relative values did not differ between computer and interview. Overall, 21% of responses were equality responses, 13% were high extreme values, and 5% violated ordinal criteria. The groups did not differ in these measures. The authors also assessed consistency across reference group size (10 v. 100). Although relative values were significantly lower for 100 than for 10, mode did not influence the size of this effect. Subjects made, on average, equally consistent judgments for the 3 comparisons. A computerized PTO elicitation protocol produced results of similar quality to that of a face-to-face interview.

Public response to cost-quality tradeoffs in clinical decisions.

PURPOSE: To explore public attitudes toward the incorporation of cost-effectiveness analysis into clinical decisions. METHODS: The authors presented 781 jurors with a survey describing 1 of 6 clinical encounters in which a physician has to choose between cancer screening tests. They provided cost-effectiveness data for all tests, and in each scenario, the most effective test was more expensive. They instructed respondents to imagine that he or she was the physician in the scenario and asked them to choose which test to recommend and then explain their choice in an open-ended manner. The authors then qualitatively analyzed the responses by identifying themes and developed a coding scheme. Two authors separately coded the statements with high overall agreement (kappa = 0.76). Categories were not mutually exclusive. RESULTS: Overall, 410 respondents (55%) chose the most expensive option, and 332 respondents (45%) choose a less expensive option. Explanatory comments were given by 82% respondents. Respondents who chose the most expensive test focused on the increased benefit (without directly acknowledging the additional cost) (39%), a general belief that life is more important than money (22%), the significance of cancer risk for the patient in the scenario (20%), the belief that the benefit of the test was worth the additional cost (8%), and personal anecdotes/preferences (6%). Of the respondents who chose the less expensive test, 40% indicated that they did not believe that the patient in the scenario was at significant risk for cancer, 13% indicated that they thought the less expensive test was adequate or not meaningfully different from the more expensive test, 12% thought the cost of the test was not worth the additional benefit, 9% indicated that the test was too expensive (without mention of additional benefit), and 7% responded that resources were limited. CONCLUSIONS: Public response to cost-quality tradeoffs is mixed. Although some respondents justified their decision based on the cost-effectiveness information provided, many focused instead on specific features of the scenario or on general beliefs about whether cost should be incorporated into clinical decisions.

Life insurance and breast cancer risk assessment: adverse selection, genetic testing decisions, and discrimination.

Life insurance industry access to genetic information is controversial. Consumer groups argue that access will increase discrimination in life insurance premiums and discourage individuals from undergoing genetic testing that may provide health benefits. Conversely, life insurers argue that without access to risk information available to individuals, they face substantial financial risk from adverse selection. Given this controversy, we conducted a retrospective cohort study to evaluate the impact of breast cancer risk information on life insurance purchasing, the impact of concerns about life insurance discrimination on use of BRCA1/2 testing, and the incidence of life insurance discrimination following participation in breast cancer risk assessment and BRCA1/2 testing. Study participants were 636 women who participated in genetic counseling and/or genetic testing at a University based clinic offering breast cancer risk assessment, genetic counseling, and BRCA1/2 testing between January 1995 and May 2000. Twenty-seven women (4%) had increased and six (1%) had decreased their life insurance since participation in breast cancer risk assessment. The decision to increase life insurance coverage was associated with predicted breast cancer risk (adjusted OR 1.03 for each 1% absolute increase in risk, 95% CI 1.01-1.10) and being found to carry a mutation in BRCA1/2 (OR 5.10, 95% CI 1.90-13.66). Concern about life insurance discrimination was inversely associated with the decision to undergo BRCA1/2 testing (RR 0.67, 95% CI 0.52-0.85). No respondent reported having life insurance denied or canceled. In this cohort of women, these results indicate that information about increased breast cancer risk is associated with increase in life insurance purchasing, raising the possibility of adverse selection. Although fear of insurance discrimination is associated with the decision not to undergo BRCA1/2 testing, there was no evidence of actual insurance discrimination from BRCA1/2 testing.

When money is saved by reducing healthcare costs, where do US primary care physicians think the money goes?

BACKGROUND: Physician willingness to reduce medical costs is mixed. Some physicians might be unwilling to reduce medical costs because they are concerned about where the savings would go. OBJECTIVE: To determine whether primary care physicians might be less willing to choose a less expensive, less effective cancer screening alternative if they believe that the money saved goes to insurance companies. DESIGN: Anonymous mailed survey. PARTICIPANTS: A total of 865 US primary care physicians. MAIN OUTCOME MEASURES: Responses to one of several clinical vignettes presenting a choice between a less expensive, less effective cancer screening option and a more expensive, more effective alternative and responses to where physicians thought the savings might go if they chose the cheaper alternative. RESULTS: Fifty-three percent of physicians chose the most expensive screening alternative. In aggregate, physicians responded that more of any money saved would go to the managers or owners of insurance companies than to increased clinical services or reduced insurance premiums. Physicians choosing the more expensive screening test were more likely to believe that money saved from choosing the less expensive test would go to insurance company profits and salaries rather than to increased clinical services or reduced premiums (P < .001). CONCLUSIONS: Although US primary care physicians vary in where they think money saved in healthcare goes, most believe that more of it goes to the salaries of insurance company executives and the profits of insurance company owners than to improved clinical services or reduced premiums. The more physicians believe that this is where the money goes, the less willing they are to reduce healthcare costs.

Incremental and average cost-effectiveness ratios: will physicians make a distinction?

Physicians are increasingly asked to use cost-effectiveness information when evaluating alternative health care interventions. Little is known about how the way such information is presented can influence medical decision making. We presented physicians with hypothetical screening scenarios with multiple options, varying the type of cost-effectiveness ratios provided as well as whether the scenarios described cancer screening settings that were familiar or unfamiliar. Half the scenarios used average cost-effectiveness ratios, as commonly reported, calculating benefits and costs relative to a no-screening option. The other half used the preferred incremental cost-effectiveness ratios, with each option's benefits and costs calculated relative to the next best alternative. Relative to average cost-effectiveness ratios, incremental cost-effectiveness information significantly reduced preference for the most expensive screening strategies in two of three unfamiliar scenarios. No such difference was found for familiar scenarios, for which physicians likely have established practice patterns. These results suggest that, in unfamiliar settings, average cost-effectiveness ratios as reported in many analyses reported in the literature can hide the often high price for achieving incremental health care goals, potentially causing physicians to choose interventions with poor cost effectiveness.

The influence of cost-effectiveness information on physicians' cancer screening recommendations.

Physicians are increasingly faced with choices in which one screening strategy is both more effective and more expensive than another. One way to make such choices is to examine the cost-effectiveness of the more costly strategy over the less costly one. However, little is known about how cost-effectiveness information influences physicians' screening decisions. We surveyed 900 primary care US physicians, and presented each with a hypothetical cancer-screening scenario. We created three familiar screening scenarios, involving cervical, colon, and breast cancer. We also created three unfamiliar screening scenarios. Physicians were randomized to receive one of nine questionnaires, each containing one screening scenario. Three questionnaires posed one of the familiar screening scenarios without cost-effectiveness information, three posed one of the familiar scenarios with cost-effectiveness information, and three posed one of the unfamiliar scenarios with cost-effectiveness information. The cost-effectiveness information for familiar scenarios was drawn from the medical literature. The cost-effectiveness information for unfamiliar scenarios was fabricated to match that of a corresponding familiar scenario. In all questionnaires, physicians were asked what screening alternative they would recommend. A total of 560 physicians responded (65%). For familiar scenarios, providing cost-effectiveness information had at most a small influence on physicians' screening recommendations; it reduced the proportion of physicians recommending annual Pap smears (p=0.003), but did not significantly alter the aggressiveness of colon cancer and breast cancer screening (both p's<0.1). For all three unfamiliar scenarios, physicians were significantly less likely to recommend expensive screening strategies than in corresponding familiar scenarios (all p's<0.001). Physicians' written explanations revealed a number of factors that moderated the influence of cost-effectiveness information on their screening recommendations. Providing physicians with cost-effectiveness information had only a moderate influence on their screening recommendations for cervical, colon, and breast cancer. Significantly, fewer physicians recommended aggressive screening for unfamiliar cancers than for familiar ones, despite similar cost-effectiveness. Physicians are relatively reluctant to abandon common screening strategies, even when they learn that they are expensive, and are hesitant to adopt unfamiliar screening strategies, even when they learn that they are inexpensive.

The role of physicians' recommendations in medical treatment decisions.

BACKGROUND: A shift away from the medical paternalism of the past has occurred, and today, the law and ethics advocate that physicians share decision-making responsibility with their patients. It is unclear, however, what the appropriate role of physicians' recommendations ought to be in this new shared decision-making paradigm. One way to approach this question is to assess the influence of physicians' recommendations. OBJECTIVE: In this study, the authors examine the influence of physicians' recommendations on hypothetical treatment decisions. Do physicians' recommendations influence treatment decisions in scenarios where the decision that maximizes health is obvious and apparent to subjects? Do recommendations pull subjects away from the treatment choice that they otherwise prefer (based on their decision when unaware of the physicians' recommendation)? DESIGN: An experimental web questionnaire presented hypothetical medical treatment scenarios in which the treatment choice that maximized health was obvious. Across scenarios, the authors varied physicians' recommendations in 3 ways: (1) physicians' recommendations supporting what maximized health, (2) physicians' recommendations that went against what maximized health, and (3) no physicians' recommendation. The participants were 102 volunteers. RESULTS: Hypothetical treatment decisions were significantly influenced by physicians'recommendations (P < 0.0001), and physicians'recommendations against the decision that maximized health pulled subjects away from the treatment decision that they made when no recommendation was given (P < 0.0001). CONCLUSION: Physicians' recommendations can lead people to make decisions that go against what is best and against what they would otherwise prefer. Physicians must take care in making recommendations and should incorporate patient preferences into their recommendations.