Lauren A. Mayer

Informed public choices for low-carbon electricity portfolios using a computer decision tool.

Reducing CO2 emissions from the electricity sector will likely require policies that encourage the widespread deployment of a diverse mix of low-carbon electricity generation technologies. Public discourse informs such policies. To make informed decisions and to productively engage in public discourse, citizens need to understand the trade-offs between electricity technologies proposed for widespread deployment. Building on previous paper-and-pencil studies, we developed a computer tool that aimed to help nonexperts make informed decisions about the challenges faced in achieving a low-carbon energy future. We report on an initial usability study of this interactive computer tool. After providing participants with comparative and balanced information about 10 electricity technologies, we asked them to design a low-carbon electricity portfolio. Participants used the interactive computer tool, which constrained portfolio designs to be realistic and yield low CO2 emissions. As they changed their portfolios, the tool updated information about projected CO2 emissions, electricity costs, and specific environmental impacts. As in the previous paper-and-pencil studies, most participants designed diverse portfolios that included energy efficiency, nuclear, coal with carbon capture and sequestration, natural gas, and wind. Our results suggest that participants understood the tool and used it consistently. The tool may be downloaded from http://cedmcenter.org/tools-for-cedm/informing-the-public-about-low-carbon-technologies/ .

Use of CAHPS Patient Experience Surveys to Assess the Impact of Health Care Innovations

BACKGROUND The Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys are the standard for collecting information about patient experience of care in the United States. However, despite their widespread use, including in pay-for-performance and public reporting efforts and various provisions of the Affordable Care Act, knowledge about the use of CAHPS in assessing the impact of quality improvement efforts is limited. A study was conducted to examine the use of patient experience surveys in assessing the impact of innovations implemented in health care settings. METHODS Innovation profiles identified on the Agency for Healthcare Research and Quality (AHRQ) Health Care Innovations Exchange website that included patient experience (including patient satisfaction) as an outcome (N = 201), were analyzed with a variety of qualitative analysis methods. RESULTS Fewer than half of the innovations used a patient experience measure, most commonly employing global measures such as an overall rating. Most innovations assessed patient experience at a single time point, with only one third using techniques such as pre-post comparisons, time trends, or comparisons to control groups. Ten domains of measures addressed reports of patient experience, all of which could be assessed by existing CAHPS instruments. Similarly, CAHPS measures are available to assess all of the organizational processes that are addressed by innovations in the profiles and for which patients are the best source of information. While 120 of the innovations that use patient experience measures report using surveys to collect these data, only 6 reported using a CAHPS measure. CONCLUSIONS Although innovations targeting quality improvement are often evaluated using surveys, there is considerable untapped potential for using CAHPS measures or surveys to assess their effectiveness.

Less Use of Extreme Response Options by Asians to Standardized Care Scenarios May Explain Some Racial/Ethnic Differences in CAHPS Scores

Background:Asian Americans (hereafter “Asians”) generally report worse experiences with care than non-Latino whites (hereafter “whites”), which may reflect differential use of response scales. Past studies indicate that Asians exhibit lower Extreme Response Tendency (ERT)—they less frequently use responses at extreme ends of the scale than whites. Objective:To explore whether lower ERT is observed for Asians than whites in response to standardized vignettes depicting patient experiences of care and whether ERT might in part explain Asians reporting worse care than whites. Procedure:A representative US sample (n=575 Asian; n=505 white) was presented with 5 written vignettes describing doctor-patient encounters with differing levels of physician responsiveness. Respondents evaluated the encounters using modified CAHPS communication questions. Results:Case-mix–adjusted repeated-measures multivariate models show that Asians provided more positive responses than whites to several vignettes with less-responsive physicians but less positive responses than whites for the vignette with the most physician responsiveness (P<0.01 for each). While all respondents provided more positive ratings for vignettes with greater physician responsiveness, the increase was 15% less for Asian than white respondents. Conclusions:Asians exhibit lower ERT than whites in response to standardized scenarios. Because CAHPS reponses are predominantly near the positive end of the scale and the most responsive scenario is most typical of the score observed in real-world settings, lower ERT in Asians may partially explain observations of lower observed mean CAHPS scores for Asians in real-world settings. Case-mix adjustment for Asian race/ethnicity or its correlates may improve quality of care measurement.

Testing the scenario hypothesis

Decision support tools are known to influence and facilitate decisionmaking through the thoughtful construction of the decision environment. However, little research has empirically evaluated the effects of using scenarios and forecasts. In this research, we asked participants to recommend a fisheries management strategy that achieved multiple objectives in the face of significant uncertainty. A decision support tool with one of two conditionsScenario or Forecastencouraged participants to explore a large set of diversified decision options. We found that participants in the two conditions explored the options similarly, but chose differently. Participants in the Scenario Condition chose the strategies that performed well over the full range of uncertainties (robust strategies) significantly more frequently than did those in the Forecast Condition. This difference seems largely to be because participants in the Scenario Condition paid increased attention to worst-case futures. The results offer lessons for designing decision support tools.

Developing communications about CCS: three lessons learned

To curb the risks of climate change, the Intergovernmental Panel on Climate Change posits that global CO2 emissions from the energy supply sector must be reduced to 90% below 2010 levels between 2040 and 2070. Electricity generation is the largest contributor to emissions from the energy supply sector. Carbon capture and storage (CCS) holds the promise of helping to reduce CO2 emissions from coal-fired power plants, as part of a low-carbon portfolio that could also include energy efficiency, natural gas, renewables and nuclear power. To inform people’s decisions about whether or not to support the implementation of CCS, our team created brochures about 10 low-carbon technologies as well as a computer tool that helped users to develop technically realistic low-carbon portfolios. Here, we highlight three main lessons we learned in developing these communications about CCS: (1) when learning about CCS people also want to know about other alternatives; (2) using simple wording improves understanding, even about complex technologies; and (3) the time to communicate about CCS is now.