3

Measures of Quality

The committee was charged with identifying measures of quality for the Leading Health Indicators (LHIs), and in this chapter it provides a starter set of measures identified by developing detailed versions of the logic models introduced in Chapter 1 for four of the LHI topic areas: tobacco; environmental quality (the air quality LHI); obesity, nutrition, and physical activity; and maternal, infant, and child health.

As noted earlier, the committee believes that the purpose of measurement is threefold. Assessment can be conducted simply for the purpose of monitoring and reporting about the health of a population; this can be done to provide a comparison with other jurisdictions or nations, or to mobilize interested parties. Measures can be used in the work of quality improvement, whether organization-wide or in a specific program. And measures can be used for accountability, for example, to report back to funders, partners, legislators, and communities. More extensive discussion of the three purposes of measurement is provided in the Institute of Medicine (IOM) report For the Public’s Health: The Role of Measurement in Action and Accountability (2011a, p. 3, et seq.).

In addition to the criteria outlined in Chapter 2, several other issues are important when selecting measures of quality. The level of measurement is important, for example. Some of the LHIs are national in scope and dependent on national-level data, but they may be of secondary importance in some local jurisdictions. One of the challenges in measurement is the paucity of truly granular health data at the local level and the capability to access and analyze the data that are available. A variety of novel strategies for data collection and analysis are needed to expand the data sources available to local public health planners and their system partners. Data relevant to health are also available from non-health sources, such as police records and school data, as well as other non-



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3 Measures of Quality The committee was charged with identifying measures of quality for the Leading Health Indicators (LHIs), and in this chapter it provides a starter set of measures identified by developing detailed versions of the logic models introduced in Chapter 1 for four of the LHI topic areas: to- bacco; environmental quality (the air quality LHI); obesity, nutrition, and physical activity; and maternal, infant, and child health. As noted earlier, the committee believes that the purpose of meas- urement is threefold. Assessment can be conducted simply for the pur- pose of monitoring and reporting about the health of a population; this can be done to provide a comparison with other jurisdictions or nations, or to mobilize interested parties. Measures can be used in the work of quality improvement, whether organization-wide or in a specific pro- gram. And measures can be used for accountability, for example, to re- port back to funders, partners, legislators, and communities. More extensive discussion of the three purposes of measurement is provided in the Institute of Medicine (IOM) report For the Public’s Health: The Role of Measurement in Action and Accountability (2011a, p. 3, et seq.). In addition to the criteria outlined in Chapter 2, several other issues are important when selecting measures of quality. The level of measure- ment is important, for example. Some of the LHIs are national in scope and dependent on national-level data, but they may be of secondary im- portance in some local jurisdictions. One of the challenges in measure- ment is the paucity of truly granular health data at the local level and the capability to access and analyze the data that are available. A variety of novel strategies for data collection and analysis are needed to expand the data sources available to local public health planners and their system partners. Data relevant to health are also available from non-health sources, such as police records and school data, as well as other non- 45

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46 TOWARD QUALITY MEASURES FOR POPULATION HEALTH traditional sources such as Google Maps for parks and Chamber of Commerce and trade groups for businesses and tax revenues. As one ex- ample of evolution in analytical capabilities, Srebotnjak and colleagues (2010) developed a novel methodology to estimate health trends (e.g., diagnosed diabetes) in counties and other small population areas. Their modeling approach allows health officials and researchers to use Behav- ioral Risk Factor Surveillance System (BRFSS) data for small-area esti- mation and validation. Advances in information and communication technology offer novel opportunities for data generation, such as crowd- sourcing data collection and analysis to support health improvement (e.g., through health behavior change) in the community (see, for exam- ple, Piniewski et al., 2011). A real-life application is offered by the expe- rience with Global Positioning System (GPS)-equipped inhalers (i.e., the Asthmapolis sensor and mobile application system that produces “timely, comprehensive and objective data on the burden of asthma”1 but also supports remote monitoring of broncho-dilator use; see Van Sickle et al. [2013]). There are several challenges in creating novel data sources, in- cluding balancing business potential with public use, and addressing concerns about real and perceived threats to privacy, technical obstacles related to gleaning useful information from “big” data, and the cost of establishing and sustaining long-term data generation and analysis ef- forts. However, the potential of disruptive innovation to dramatically increase access to population health data is undeniable. The committee did not conduct a systematic and comprehensive re- view of all potential measures related to the LHIs for several reasons. Such an undertaking would require time and resources (including a wider range of expertise) to research all effective interventions for a given out- come, and to identify and evaluate all candidate measures. The commit- tee also believes that describing a framework and process for a continually updated set of measures could be of more lasting value than identifying a static set of measures. Finally, many measures of quality relate to the specific interventions implemented and are context specific. For this reason, too, describing a process seemed more useful than providing specific examples that would result from applying that process. As discussed earlier, the LHIs are heterogeneous, and organizing them to support quality improvement is not a straightforward process. There are at least three ways to conceptually organize the Healthy People 2020 LHIs other than the alphabetical order presented in the Healthy People publications. They may be organized roughly according to the 1 Available at http://asthmapolis.com/public-health (accessed June 26, 2013).

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MEASURES OF QUALITY 47 ecological model,2 based on the type of “determinant” of health/level in the ecological model they occupy. They may be divided by locus of in- tervention (clinical/individual vs. population-based), al-though some LHIs fall somewhere in between. LHIs do not fit neatly into one level of the ecological model, and may be altered by interventions at both the individual and at the population level. Finally, the LHIs may be orga- nized according to the committee’s logic model provided above: re- sources and capacity, interventions, healthy conditions, and healthy outcomes, with a focus on the latter two categories, which can “house” most of the LHIs (see Figure 3-1). Table 3-1 provides a list of the LHIs organized according to the logic model (and shown in bold type), and showing areas for potential measures of quality related to the LHIs. The non-bolded entries represent non-LHI measures that are directly linked to an LHI (e.g., an intermedi- ate outcome linked to the LHIs representing an ultimate health outcome) or found along the pathway that includes an LHI (e.g., morbidity from childhood disease is an ultimate outcome linked to the LHI childhood vaccines). The entries marked with an asterisk represent measures that are endorsed by the National Quality Forum (NQF), that met the criteria for inclusion in the County Health Rankings, or that met other criteria such as face validity in the case of measures that emerge from the evi- dence-based interventions recommended by the Guide to Community Preventive Services (population-based interventions) and the U.S. Pre- ventive Services Task Force (USPSTF) (for interventions in the clinical FIGURE 3-1 Health outcome logic model. 2 The ecological model is a diagram adapted from Dahlgren and Whitehead (1991) by an IOM committee and in Healthy People 2020 planning by the Department of Health and Human Services (HHS) to show the array of determinants of health, or the ecology of health, beginning with individual level factors at the center (biology/genetics), then on to behavior, family, social networks, and communities, followed by broad policies pertain- ing to the determinants of health (education, income, etc.) at the state and national level (see HHS, 2008; IOM, 2003a).

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48 TOWARD QUALITY MEASURES FOR POPULATION HEALTH setting). The table is not intended to be comprehensive or exhaustive, but the committee hopes that it illustrates a step in the process of identifying measures of quality related to the LHI. A subsequent step would be the application of the criteria outlined in Chapter 2. TABLE 3-1 The LHIs (in Bold Typeface) Organized According to the Logic Model and Showing Areas for and Examples of Potential Measures of Quality (in Regular Typeface) Resources and Capacity; Healthy Conditions Outcome Interventions  Title X, Medicaid family Females receiving Infant deaths planning waivers reproductive health (MICH-1.3)  Family planning services services (FP-7.1) Preterm births  Teen birth rate* (MICH-9.1)  Children using  Low birth age-appropriate weight* restraints in motor vehicles  Children in poverty*  Funding for vaccine and Childhood vaccines  Morbidity from services for un- or under- (IID-8) childhood insured diseases  School entry laws  Mortality from childhood diseases  Education funding Students graduating  Multiple, includ-  Good schools with a regular ing summary  Research diploma 4 years measure of popu- after starting 9th lation health grade (AH-5.1)*a (HALY/HALE)  Health literacy  Unemployment rate

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MEASURES OF QUALITY 49 TABLE 3-1 Continued Resources and Capacity; Healthy Conditions Outcome Interventions  Funding for HIV screen- Persons living with  HIV incidence ing services HIV who know their  HIV mortality  Communication and ed- serostatus (HIV-13) ucation efforts  Increasing alcohol taxes; Adolescents (12-17 Fatal injuries enhanced enforcement of years old) using al- (IVP-1.1) laws prohibiting sales to cohol or any illicit minors* drugs (SA-13.1)  Research Adults engaging in binge drinking (SA-14.3)  Incentives to use public Air Quality Index  Cardiovascular transportation, CAFE (EH-1) and respiratory standards Daily particulate mat- mortalityc  Research (on ways to ter days (PM2.5)*  (also Infant reduce children’s ETS deaths) exposure) Children exposed to  State and local smoke- secondhand smoke free policies (TU-11.1)  Excise taxes  Increased unit price on Adolescents who tobacco products*b smoke (TU-2.2) Adults who smoke (TU-1.1)*  Passage and enforcement  Access to mental Suicides of mental health parity health services. (MHMD-1) laws  Youth access to  Coverage of mental unsecured fire- Adolescents experi- health services arms*d encing major de- pressive episodes (MHMD-4.1)

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50 TOWARD QUALITY MEASURES FOR POPULATION HEALTH TABLE 3-1 Continued Resources and Capacity; Healthy Conditions Outcome Interventions  Effective law  Schools imple- Homicides (IVP-29) enforcement menting school-  Use of evidence-based based interven- substance use prevention tions aimed at re- services in schools and ducing youth communities violence*  State policies regarding firearmse  Ratio of population to Persons using the  HALY/HALE dentists* oral health care  OH3.1, OH3.2,  Increased reimbursement system (OH-7) OH3.3, OH1.1f levels for adult and child  Preventable oral health services hospitalization under Medicaid Persons with a usual primary care provider (AHS-3) Persons with medical insurance (AHS-1.1)  Percent of population under age 65 without health insurance*  The Affordable Care Act  Local public health mon- Adults with hyper-  HALY/HALE itoring of hypertension tension under  Cardiovascular rates and support to pro- control (HDS-12) and stroke vider community mortality

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MEASURES OF QUALITY 51 TABLE 3-1 Continued Resources and Capacity; Healthy Conditions Outcome Interventions  Local health plan and Adults receiving  Colorectal cancer purchaser monitoring of colorectal cancer mortality colorectal cancer screening (C-16) screening rates  Reimbursement of preventive services  Access to recreational Adults meeting  HALY/HALE facilities* physical activity  Diabetic screening* guidelines (PA-2.4)  Proportion of clinicians screening for obesity at Total vegetable in- age 6 and older and of- take (NWS-15.1) fering or referring to comprehensive, intensive Adult diabetic popu- behavioral interventionsg lation with poor glu-  Behavioral interventions cose control (D-5.1) to reduce screen time (Community Guide) Adults who are  Increased physical ac- obese (NWS-9) tivity in school  “Urban design and land Children and ado- use policies and practic- lescents who are es that support physical obese (NWS-10.4) activity in small geo-  Limited access to graphic areas (generally healthy foods* a few blocks)”*h  Fast food restau- rants* NOTE: Items marked with an asterisk (*) represent measures that are endorsed by NQF, met the criteria for inclusion in the County Health Rankings, or met other criteria (e.g., face validity in the case of measures that emerge from the evidence-based interventions recommended by the Guide to Community Preven- tive Services [population-based interventions] and the U.S. Preventive Services Task Force [for interventions in the clinical setting]). a “The averaged freshman graduation rate measures the percentage of public high school students who graduate on time with a regular diploma” (Department of Education, Na- tional Center for Education Statistics, 2012, http://nces.ed.gov/programs/coe/analysis/ 2012-section5.asp [accessed June 1, 2013]).

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52 TOWARD QUALITY MEASURES FOR POPULATION HEALTH TABLE 3-1 Continued b Tworek et al., 2010. c See Henschel et al., 2012, for a review of published studies of air pollution interventions which showed that improving air quality is associated with improved health outcomes (decreased respiratory and cardiovascular morbidity and mortality). d Baxley and Miller, 2006. e Fleegler et al., 2013, found that “a higher number of firearm laws in a state was asso- ciated with a lower rate of firearm fatalities in the state” controlling for a range of fac- tors, but also concluded that additional research is needed to examine the nature of the association. f OH-1.1: Reduce (by 10%, from 33.3% to 30.0%) the proportion of young children aged 3 to 5 years with dental caries experience in their primary teeth; OH-3.1: Reduce (by 10%, from 27.8% to 25%) the proportion of adults aged 35 to 44 years with untreated dental decay; OH-3.2: Reduce (by 10%, from 17.1% to 15.4%) the proportion of older adults aged 65 to 74 years with untreated coronal caries; and OH-3.3: Reduce (by 10%, from 37.9% to 34.1%) the proportion of older adults aged 75 years and older with un- treated root surface caries. g “The DGAs (2005 Dietary Guidelines for Americans) provide science based guidelines for food policy, food benefits, and nutrition education provided through the Federal nutri- tion assistance programs. The 2005 DGA Advisory Committee Report stated that ‘greater consumption of fruits and vegetables (5-13 servings or 2½-6½ cups per day depending on calorie needs) is associated with a reduced risk of stroke and perhaps other cardiovascular diseases, with a reduced risk of cancers in certain sites (oral cavity and pharynx, larynx, lung, esophagus, stomach, and colon-rectum), and with a reduced risk of type 2 diabetes (vegetables more than fruit). Moreover, increased consumption of fruits and vegetables may be a useful component of programs designed to achieve and sustain weight loss’” (USDA, 2008). h Guide to Community Preventive Services, 2004. The committee considered the quality improvement needs at all geo- graphic levels, with the recognition that as one localizes quality im- provement it becomes more important to have measures most relevant to the interventions chosen (which are intrinsically more process-oriented or structurally oriented) and which are more likely to be measurable and changeable at local levels. To reconcile these somewhat different objec- tives, the committee suggests that a well-developed portfolio of measures will have a core set of standard measures to be used at all levels (nation- al, state, local), and a menu of additional options (largely process measures appropriate to specific settings) to be used as needed at the lo- cal level. The priority areas or drivers of improvement of quality in public health identified in the work of the OASH (Honoré and Scott, 2010) are metrics and information technology; evidence-based practices, research, and evaluation; systems thinking; sustainability and stewardship; policy;

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MEASURES OF QUALITY 53 and workforce and education. As with the quality characteristics, these drivers cannot be linked directly to LHIs, but instead refer to the sys- tem’s underlying structural inputs illustrated by the Resources and Ca- pacity box in Figure 3-1. For public health agencies, these may be linked with domains and measures employed in the Public Health Accreditation Board voluntary accreditation process. The drivers also seem somewhat related to the notion of foundational capabilities (part of a minimum package of public health services) proposed by a recent IOM report (2012). Those capabilities include the research infrastructure, infor- mation systems, and skills and workforce development for policy analy- sis and communication. That committee recommended that the minimum package, including the foundational capabilities, be used to establish new and robust approaches to demonstrating accountability, including linking funding inputs to outcomes in order to demonstrate value to funders and the public. Below, the committee provides a “starter set” of measures of quality that could be considered in the development of a robust portfolio of measures for the nation, and for state and local jurisdictions. The com- mittee used two approaches. 1. The committee found that many of the LHIs included or led to one or more measures that can be used to measure quality (see Table 3-1). 2. The committee developed case studies that applied the report’s health outcome logic model to the LHI topic areas of a. tobacco use; b. nutrition, physical activity, and obesity; c. environmental quality; and d. maternal, infant, and child health. Finding 3-1: The committee finds that a. Many of the Leading Health Indicators are measures of health outcomes or of conditions that can directly affect health outcomes and are, therefore, measures of the quality of the multisectoral health system. b. The LHIs that meet the definition above of a quality measure can be used for assessment, improvement, and accountability. To be used thus, they must be relevant and measurable at the national, state, and local levels.

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54 TOWARD QUALITY MEASURES FOR POPULATION HEALTH c. The LHIs reflect conditions or outcomes that direct- ly contribute to the Healthy People 2020 foundation measures (e.g., general health status, health-related quality of life) and the ecologic model that underlies it. FOUR CASE STUDIES The committee has developed concrete illustrations of the function- ing of the logic model for four LHI topics and also more detailed expla- nation of activities for each LHI topic to help in the selection of metrics. Each case study lists the LHIs under the topic, provides a brief digest of the evidence and causal pathway(s) to which the LHI is an endpoint (ul- timate outcome) or an intermediate outcome, provides a detailed logic model to illustrate the possible measures under Healthy Conditions and Health Outcomes, depicts the likely relationships among them, and offers both a list of possible measures and a shorter list of candidate measures (endorsed by NQF; based on evidence from the Guide to Community Preventive Services, the USPSTF, or equivalent, and for which data sources are available). The 1997 IOM report Improving Health in the Community: A Role for Performance Monitoring provides additional lists of potential measures organized by topic. The detailed examples and their associated logic models provide an overview of resources, interventions, conditions, and outcomes that are related to specific and important health determinants and outcomes, and highlight the importance of the LHIs as components of these models. By explicitly describing these relationships, these models provide ideas for potential measures for assessing (1) the effectiveness of resources, pro- grams, and actions on conditions that promote health, and (2) the impact of these conditions on outcomes. As the committee’s Recommendation 1-1 states, these conditions and outcomes are a reflection of the quality of the multisectoral health system. Similar models can be developed for other health determinants (or healthy conditions) and outcomes related to other Leading Health Indicators, or to other Healthy People objectives. These models can also facilitate the development of more detailed and quantitative systems models, such as Prevention Impacts Simulation Model (PRISM) and Population Health Model (POHEM), described ear- lier in this report, that can identify which components of these models make greater potential contributions to improved health conditions and outcomes. As mentioned above, evidence from studies and meta- analyses, such as those of the Guide to Clinical Preventive Services and Guide to Community Preventive Services, and practical knowledge sup-

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MEASURES OF QUALITY 55 port some of the logical relationships and connections in these models, but evidence to support—or refute—other relationships is sorely needed. Thus, another use of these models is to highlight relationships supported by scientific evidence that can already serve as the foundation for measures of health system quality, while also identifying other relation- ships in need of further study. By way of illustration, the committee used the tobacco model to identify potential measures of quality. Outcome-related quality measures can be generated from “tobacco-related disease, functional losses, and mortality.” Obvious examples include lung cancer incidence and mortali- ty, and the prevalence of and mortality from chronic obstructive pulmo- nary disease, to which tobacco use is a major contributor. There are several potential healthy condition-related quality measures that are sug- gested by the model. “Prevalence of tobacco use” is most closely related to outcomes and is the most obvious choice for a quality measure. The seven conditions shown that directly affect “prevalence of tobacco use” could next be reviewed for those which have the greatest potential im- pact, the best supporting scientific evidence for their effectiveness, and available data to track them (see Recommendation 2-2). Depending on need, one or more of these seven conditions could be selected to monitor performance of the health system. Most of the process measures in the model are supported by evidence and recommended by either the Clini- cal Guide or the Community Guide. Again, these require review using the selection criteria described in Recommendation 2-2. Because these actions and processes can be implemented at the state and local level, selecting one or more of them as the basis for a measure of state or local health system performance could provide more immediate feedback to local public health practitioners and stakeholders than relying on quality measures of conditions and outcomes, which change over a much longer time frame. The case studies gave the committee an opportunity to consider the nine characteristics of public health quality and the six drivers of public health quality improvement as they relate primarily to the Resources and Capacity component of the logic model. As discussed in Chapter 1, in general, the nine characteristics cannot be directly linked with quality measures, since they primarily describe the system itself (e.g., population-centered, transparent, health-promoting) and the interventions undertaken to address health issues (a program or process or policy may be risk-reducing, or may be a manifestation of the system’s vigilance, or efficiency). Below, the committee provides tobacco use as an example for applying the nine characteristics of quality and the six drivers. Addi-

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66 TOWARD QUALITY MEASURES FOR POPULATION HEALTH Environmental Quality There are two LHIs under Environmental Quality: (1) LHI 7: Air Quality Index (AQI) exceeding 100 (EH-1) and (2) LHI 8: Children aged 3 to 11 years exposed to secondhand smoke (TU-11.1). The set of objec- tives under the Environmental Quality topic includes the subtitles Out- door Air Quality, Water Quality, Toxics and Waste, Healthy Homes and Healthy Communities, and Infrastructure and Surveillance. The objec- tives under Healthy Homes and Healthy Communities cover radon, mold, pesticides, and lead. This is an area where measures of the built environment, based on the evolving evidence base on effective interven- tions, would be useful in the future. Examples could include walkability, the proportion of the population close to public transit, the density of green and recreational spaces, etc. The LHIs in this area are limited and are only proxies for a broader range of environmental quality issues. A review of the literature substantiates the associations between air pollution and poor health outcomes (for example, Henschel et al., 2012). Air Quality Index (AQI) “reports five most common ambient air pollu- tants that are regulated under the Clean Air Act: ground-level ozone, par- ticle pollution (or particulate matter), carbon monoxide, sulfur dioxide, and nitrogen dioxide” (EPA, 20123). Although the AQI data (collected through the Environmental Protection Agency’s monitoring networks) are of high quality, the AQI has considerable geospatial limitations. For example, rural areas are generally not well represented. Also, given the placement of monitors (away from sources of high air pollution), the data collected may not be informative about the cumulative burden of air pol- lution in a certain area (California Department of Public Health, 2010). The Guide to Community Preventive Services has recommended multi- trigger and multi-component interventions for asthma control, which would suggest that a composite measure of asthma-aggravating aspects of the environment could be helpful (housing quality in a given area, combined with air quality, and other factors). For air quality, an envi- ronmental quality index that can be used for rural and urban areas would be most useful at the local level. At the federal and state level, metrics such as proportion of vehicles that meet a miles-per-gallon threshold could be used. The logic model provides an illustration of some of the potential areas for measurement related to the AQI indicator. (Children’s exposure to secondhand smoke is covered to some extent in the Tobacco Use logic 3 See http://www.epa.gov/o3healthtraining/aqi.html (accessed June 27, 2013).

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MEASURES OF QUALITY 67 model earlier in this chapter.) The available literature shows that the AQI is not the only available indicator in this area. The environment is one area where the local, state, and federal needs for quality measures (and the ability to act) may diverge greatly. In other words, the system inputs for environmental quality can be expanded beyond just air quality to also include water, housing, transportation, land use, and food, although data availability and measures may vary widely in each domain. For example, the built environment is an important determinant of health and of great local relevance, but it is harder to identify suitable measures of the built environment. There are several reasons for this. First, although the asso- ciation between the built environment and health outcomes has support in the literature, the evidence base regarding effective interventions is incomplete and evolving. The Community Guide does provide recom- mendation on several types of interventions on the built environment (e.g., community scale urban design and land use) that are likely to have effects on physical activity. In the area of indoor air quality, specifically, children’s exposure to secondhand smoke (SHS) (the second LHI in this topic), the UK Nation- al Institute for Clinical Excellence has found review-level evidence of effectiveness for the several classes of interventions (Taylor et al., 2005). A Cochrane review has also found sufficient evidence of effectiveness for legislative bans on smoking in workplaces and other in- door spaces, with evidence of great effectiveness of bans in hospitals (Callinan et al., 2010). Little evidence is available on policies banning smoking in multi-unit housing, although such policies have been enacted in some jurisdiction on the assumption that they could potentially lower SHS exposure for children. NQF has endorsed one measure pertinent to secondhand smoke ex- posure of children inside the home. This is a measure developed by the Maternal and Child Health Bureau of HRSA. Each community, state, or measure-endorsing entity could use the logic model described below to generate a portfolio of measures for comparison and improvement in the area of environmental quality. The logic model can also be used to assess local resources and capacities to implement interventions to improve air quality.

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68 TOWARD QUALITY MEASURES FOR POPULATION HEALTH Air Quality: Example Measures of Quality The list below provides a partial set of potential measures. Figure 3-4 illustrates how the logic model can be applied to this LHI topic. Measures of Outcome Mortality due to respiratory complications Asthma incidence in children Inhaler use (as proxy for frequency of asthma attacks) Hospital visits for asthma attacks Emergency visits with respiratory related complications Measures of Healthy Conditions (e.g., Intermediate Outcome) Concentration of air pollutants in the air Number of clean air days Indoor air quality at home and workplace Mass transit system coverage and use Measures of Resources (Structure) or Interventions (Process) Implementation of pollution reduction technology Proportion of vehicles on the road that meet Corporate Average Fuel Economy (CAFE) standards The following are measures that have been endorsed by NQF (meas- ure steward provided in parentheses). They pertain largely to the clinical care setting and to a far lesser extent to the population level.  Asthma Emergency Department Visits (Alabama Medicaid Agency)  Relative Resource Use for People with Asthma (NCQA)

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Resources & Capacity MEASURES OF QUALITY FIGURE 3-4 Applying the logic model to the LHI topic Environmental Quality (Air Quality Index LHI only).* * Examples of reducing point source emissions include reduces power consumption through conservations measures; replace- ment of coal and other fossil fuel power generation with water-, wind-, and solar-based power generation; and use of low-sulfur coal, and scrubbers to reduce pollutants in power plant emissions. Examples of reducing mobile sources of air pollution include improvements in fuel efficiency through Corporate Average Fuel Economy standards and reductions in diesel fuel–related emis- 69 sions through the use of low-sulfur diesel fuel and particulate filters.

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70 TOWARD QUALITY MEASURES FOR POPULATION HEALTH Maternal, Infant, and Child Health The two LHIs under this topic are LHI 11, infant deaths (MICH-1.3) and LHI 12, preterm births (MICH-9.1). Infant mortality is one of the four LHIs that is also an ultimate health outcome. Preterm birth is an in- termediate outcome in the causal network that ends with infant death and is strongly associated with poor birth outcomes and development. Ac- cording to 2010 data, 11.99 percent of American babies are born before 37 weeks of gestation (Martin et al., 2012). Although the preterm birth rate has decreased slightly every year for the past several years, the Unit- ed States continues to lag behind its peers and ranked 130th out of 184 countries in a recent World Health Organization report (WHO et al., 2012). The U.S. infant mortality rate in 2009 was 6.39 deaths per 1,000 births. A report from the Organisation for Economic Co-operation and Development (OECD) showed that between 2005 and 2009 the United States had the highest infant mortality of 17 peer nations, and that it ranked 31st among 40 OECD countries (OECD, 2011). Within the Unit- ed States, ethnic and racial disparities in neonatal and infant mortality are deep and persist across levels of educational attainment (Mathews and McDorman, 2012). In 2008, infant mortality among non-Hispanic blacks was 12.67 per 1,000 live births, compared to 5.52 among non-Hispanic whites (Mathews and MacDorman, 2012). Moreover, despite considera- ble decreases in infant mortality across all socioeconomic groups be- tween 1969 and 2001, socioeconomic deprivation remains associated with higher neonatal and postneonatal mortality (Singh and Kogan, 2007). Infant deaths may serve as a quality measure because they are a re- flection of the ability of the health system (broadly conceived to include public health, health care delivery, social services, and others) to influ- ence factors linked with infant survival at various points in the causal network. Reviewing the literature on infant deaths, including the exten- sive information provided in Healthy People 2020, the committee found that the top causes include, in order: birth defects, prematurity and low birth weight, and Sudden Infant Death Syndrome (SIDS) (Heron, 2012). Given this broad and interrelated array of causal factors, a variety of system resources and capacity are relevant to both infant mortality and preterm birth. For example, access to health care services is an important factor in preventing preterm birth, but insurance coverage of maternity services is not enough. More than half of women who receive Medicaid coverage of pregnancy and birth lose that coverage within 60 days of giving birth (Johnson, 2012). The loss of coverage has serious conse-

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MEASURES OF QUALITY 71 quences for women with medical risks who had previous adverse preg- nancy outcomes such as preterm birth or low birth weight, in part be- cause of the likelihood that they will have similar poor outcomes with subsequent births. A range of social, physical environmental, and economic conditions and changes in behavioral risk factors relate to infant mortality and pre- term birth. However, there are considerable gaps in the evidence base. The existing evidence-based interventions to address one or more of the causes of infant mortality and preterm birth include: folic acid supple- mentation, tobacco use cessation counseling, tobacco use interventions used in combination (excise taxes, campaigns, education) and worksite programs to control and reduce obesity (Community Preventive Services Task Force, 2013). In addition to those lifestyle factors, preterm birth and infant death are also related to teenage and unintended pregnancy, socio- economic status, educational status of the parents, sleep position, obesity, nutritional status, and infections in the mother, including sexually trans- mitted diseases (STDs). Clinical interventions that have been effective in addressing causes of infant mortality related to preterm birth include ap- propriate use of surfactant for preterm neonates experiencing respiratory distress. A perinatal conceptual risk framework has been proposed, which involves recognizing that although many of the existing interventions occur at the level of the most proximal determinants—risk factors for poor pregnancy outcomes—the foundations for those poor outcomes are laid much earlier in life (Johnson et al., 2006; Misra et al., 2003). Such a life-course framework calls for undertaking strategies at the population and individual levels that intervene much earlier in life, years before a woman conceives, as well as during the interconception periods, with the intent of influencing such factors as nutritional status, tobacco use, and sexual behavior, among many others. Such an array of interventions would require changes in policies, including reorientation of federal and state investments, and the implementation of evidence-based interven- tions on many fronts. Several recent efforts have sought to improve in- fant health and survival, including the Association of State and Territorial Health Officials Healthy Babies Initiative, which has carried out efforts to improve birth outcomes in a number of states (ASTHO, 2012); the Peer-to-Peer State Medicaid Learning Project, operated by CDC and the Commonwealth Fund (Johnson, 2012), and the Strong Start for Mothers and Newborns Initiative, which is a joint effort of CMS, HRSA, and the Administration on Children and Families. The Strong Start initiative aims to reduce preterm birth and improve infant and ma-

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72 TOWARD QUALITY MEASURES FOR POPULATION HEALTH ternal outcomes through two strategies: the reduction of elective deliver- ies before 39 weeks, and the testing of approaches to reducing prematuri- ty among Medicaid and Children’s Health Insurance Program recipients at risk of premature birth. Maternal, Infant, and Child Health: Example Measures of Quality The list below provides a partial set of potential measures. Figure 3-5 (page 75) illustrates how the logic model can be applied to this LHI topic. Measures Related to Healthy Outcomes Infant mortality rate Percent of overweight and obesity in pregnant women and women of childbearing age Number of stillbirths and miscarriages Number of preterm births Number of children with congenital conditions Percent of early elective deliveries Measures Related to Healthy Conditions Prevalence of infant exposure to environmental tobacco smoke in the home (HHS, 2006) The existence of laws related to indoor air quality, such as municipal ordinances prohibiting or restricting smoking in multi-family housing (Environmental Law Institute, 2013) Prevalence of back-to-sleep practices (data from Pregnancy Risk As- sessment Monitoring System); Rate of elective deliveries occurring prior to 39 weeks (objective of the National Priorities Partnership) The rate of overweight and obesity in women of childbearing age and in pregnant women Percentage of women of childbearing age receiving family planning services Percent of pregnant women receiving prenatal care Number of women that adhere to dietary and nutritional guidelines during pregnancy Percentage of women smoking during pregnancy Percentage of women who consume alcohol during pregnancy

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MEASURES OF QUALITY 73 Percentage of teenage pregnancies Percentage of unwanted pregnancies Percentage of women breastfeeding a minimum of 12 months (American Academy of Pediatrics) or 2 years (World Health Organization) Percentage of infants and children exposed to secondhand smoke Percentage of vaccinated (up to date) infants and children Percentage of mothers following nutritional guidelines Percentage of infants visiting the emergency room Measures Related to Resources and Interventions Availability of prenatal care Availability of family planning services The following are measures that have been endorsed by NQF (meas- ure stewards provided in parentheses). They pertain largely to the clinical care setting and to a far lesser extent to the population level (e.g., AHRQ).  Percentage of low-birth-weight births (CDC)  Low-birth-weight rate (AHRQ)  Healthy-term newborn (California Maternal Quality Care Collaborative)  Prenatal and postpartum care (NCQA)  Infant under 1,500 g not delivered at appropriate level of care (CA Maternal Quality Care Collaborative)  SIDS counseling  Exclusive breast milk feeding during the newborn’s entire hospi- talization (Joint Commission)  Frequency of ongoing prenatal care (NCQA)  Prenatal and postpartum care—timeliness of prenatal care and postpartum care at 21 and 56 days after delivery (NCQA) Given the role of smoking in influencing several factors that lead to infant death, quality measures related to tobacco use may be useful.  Medical assistance with smoking and tobacco use cessation (three-component—advice to quit, discussion of medications, discussion of strategies for cessation) (NCQA)

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74 TOWARD QUALITY MEASURES FOR POPULATION HEALTH  Percentage of patients aged 18 years and older who were screened for tobacco use at least once during the 2-year meas- urement period and who received tobacco cessation counseling intervention if identified as a tobacco user (AMA-convened Phy- sician Consortium for Performance Improvement)  The HRSA Maternal and Child Health Bureau measures children exposed to secondhand smoke inside their homes (fits under Healthy Conditions).

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Resources & Capacity MEASURES OF QUALITY Implement policies to Reduced exposure of reduce exposure of children children to secondhand to secondhand smoke smoke FIGURE 3-5 Applying the logic model to the LHI topic Maternal, Infant, and Child Health. 75

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