Electronic Health Records for Population Health Management: Comparison of Electronic Health Record-Derived Hypertension Prevalence Measures Against Established Survey Data.

BACKGROUND: Hypertension is the most prevalent risk factor for mortality globally. Uncontrolled hypertension is associated with excess morbidity and mortality, and nearly one-half of individuals with hypertension do not have the condition under control. Data from electronic health record (EHR) systems may be useful for community hypertension surveillance, filling a gap in local public health departments' community health assessments and supporting the public health data modernization initiatives currently underway. To identify patients with hypertension, computable phenotypes are required. These phenotypes leverage available data elements-such as vitals measurements and medications-to identify patients diagnosed with hypertension. However, there are multiple methodologies for creating a phenotype, and the identification of which method most accurately reflects real-world prevalence rates is needed to support data modernization initiatives. OBJECTIVE: This study sought to assess the comparability of 6 different EHR-based hypertension prevalence estimates with estimates from a national survey. Each of the prevalence estimates was created using a different computable phenotype. The overarching goal is to identify which phenotypes most closely align with nationally accepted estimations. METHODS: Using the 6 different EHR-based computable phenotypes, we calculated hypertension prevalence estimates for Marion County, Indiana, for the period from 2014 to 2015. We extracted hypertension rates from the Behavioral Risk Factor Surveillance System (BRFSS) for the same period. We used the two 1-sided t test (TOST) to test equivalence between BRFSS- and EHR-based prevalence estimates. The TOST was performed at the overall level as well as stratified by age, gender, and race. RESULTS: Using both 80% and 90% CIs, the TOST analysis resulted in 2 computable phenotypes demonstrating rough equivalence to BRFSS estimates. Variation in performance was noted across phenotypes as well as demographics. TOST with 80% CIs demonstrated that the phenotypes had less variance compared to BRFSS estimates within subpopulations, particularly those related to racial categories. Overall, less variance occurred on phenotypes that included vitals measurements. CONCLUSIONS: This study demonstrates that certain EHR-derived prevalence estimates may serve as rough substitutes for population-based survey estimates. These outcomes demonstrate the importance of critically assessing which data elements to include in EHR-based computer phenotypes. Using comprehensive data sources, containing complete clinical data as well as data representative of the population, are crucial to producing robust estimates of chronic disease. As public health departments look toward data modernization activities, the EHR may serve to assist in more timely, locally representative estimates for chronic disease prevalence.

Toxicology Test Results for Public Health Surveillance of the Opioid Epidemic: Retrospective Analysis.

Background: Addressing the opioid epidemic requires timely insights into population-level factors, such as trends in prevalence of legal and illegal substances, overdoses, and deaths. Objective: This study aimed to examine whether toxicology test results of living individuals from a variety of sources could be useful in surveilling the opioid epidemic. Methods: A retrospective analysis standardized, merged, and linked toxicology results from 24 laboratories in Marion County, Indiana, United States, from September 1, 2018, to August 31, 2019. The data set consisted of 33,787 Marion County residents and their 746,681 results. We related the data to general Marion County demographics and compared alerts generated by toxicology results to opioid overdose-related emergency department visits. Nineteen domain experts helped prototype analytical visualizations. Main outcome measures included test positivity in the county and by ZIP code; selected demographics of individuals with toxicology results; and correlation of toxicology results with opioid overdose-related emergency department visits. Results: Four percent of Marion County residents had at least 1 toxicology result. Test positivity rates ranged from 3% to 19% across ZIP codes. Males were underrepresented in the data set. Age distribution resembled that of Marion County. Alerts for opioid toxicology results were not correlated with opioid overdose-related emergency department visits. Conclusions: Analyzing toxicology results at scale was impeded by varying data formats, completeness, and representativeness; changes in data feeds; and patient matching difficulties. In this study, toxicology results did not predict spikes in opioid overdoses. Larger, more rigorous and well-controlled studies are needed to assess the utility of toxicology tests in predicting opioid overdose spikes.

Identification of Hypertension in Electronic Health Records Through Computable Phenotype Development and Validation for Use in Public Health Surveillance: Retrospective Study.

BACKGROUND: Electronic health record (EHR) systems are widely used in the United States to document care delivery and outcomes. Health information exchange (HIE) networks, which integrate EHR data from the various health care providers treating patients, are increasingly used to analyze population-level data. Existing methods for population health surveillance of essential hypertension by public health authorities may be complemented using EHR data from HIE networks to characterize disease burden at the community level. OBJECTIVE: We aimed to derive and validate computable phenotypes (CPs) to estimate hypertension prevalence for population-based surveillance using an HIE network. METHODS: Using existing data available from an HIE network, we developed 6 candidate CPs for essential (primary) hypertension in an adult population from a medium-sized Midwestern metropolitan area in the United States. A total of 2 independent clinician reviewers validated the phenotypes through a manual chart review of 150 randomly selected patient records. We assessed the precision of CPs by calculating sensitivity, specificity, positive predictive value (PPV), F1-score, and validity of chart reviews using prevalence-adjusted bias-adjusted κ. We further used the most balanced CP to estimate the prevalence of hypertension in the population. RESULTS: Among a cohort of 548,232 adults, 6 CPs produced PPVs ranging from 71% (95% CI 64.3%-76.9%) to 95.7% (95% CI 84.9%-98.9%). The F1-score ranged from 0.40 to 0.91. The prevalence-adjusted bias-adjusted κ revealed a high percentage agreement of 0.88 for hypertension. Similarly, interrater agreement for individual phenotype determination demonstrated substantial agreement (range 0.70-0.88) for all 6 phenotypes examined. A phenotype based solely on diagnostic codes possessed reasonable performance (F1-score=0.63; PPV=95.1%) but was imbalanced with low sensitivity (47.6%). The most balanced phenotype (F1-score=0.91; PPV=83.5%) included diagnosis, blood pressure measurements, and medications and identified 210,764 (38.4%) individuals with hypertension during the study period (2014-2015). CONCLUSIONS: We identified several high-performing phenotypes to identify essential hypertension prevalence for local public health surveillance using EHR data. Given the increasing availability of EHR systems in the United States and other nations, leveraging EHR data has the potential to enhance surveillance of chronic disease in health systems and communities. Yet given variability in performance, public health authorities will need to decide whether to seek optimal balance or declare a preference for algorithms that lean toward sensitivity or specificity to estimate population prevalence of disease.

Institutional factors associated with hospital partnerships for population health: A pooled cross-sectional analysis.

BACKGROUND: Hospitals are increasingly engaging in partnerships to address population health in response to national policies, such as value-based payment models. However, little is known about how institutional factors influence hospital partnerships for population health. PURPOSE: Guided by institutional theory, we examine the association between institutional pressures (coercive, normative, and mimetic isomorphism) and hospital partnerships for population health. METHODOLOGY: A pooled cross-sectional analysis used an unbalanced panel of 10,777 hospital-year observations representing respondents to a supplemental question of the American Hospital Association's annual survey (2015-2017). The analysis included descriptive and bivariate statistics, and regression models that adjusted for repeated observations to examine the relationship between key independent variables and partnerships over time. FINDINGS: In regression analyses, we found the most support for measures of coercive (e.g., regulatory factors) isomorphism, with nonprofit status, participation in accountable care organizations, and acceptance of bundled payments, all being consistently and significantly associated with partnerships across all organization types. Modest increases were observed from 2015 to 2017 for hospital partnerships with public health organizations (+2.8% points, p < .001), governmental organizations (+2.0% points, p = .009), schools (+4.1% points, p < .001), and businesses (+2.2% points, p = .007). PRACTICE IMPLICATIONS: Our results suggest that institutional factors, particularly those related to regulatory policies and programs, may influence hospital partnerships to support population health. Findings from this study can assist hospital leaders in assessing the factors that can support or impede the creation of partnerships to support their population health efforts.

Supporting Health Equity Through Data-Driven Decision-Making: A Local Health Department Response to COVID-19.

COVID-19 highlights preexisting inequities that affect health outcomes and access to care for Black and Brown Americans. The Marion County Public Health Department in Indiana sought to address inequities in COVID-19 testing by using surveillance data to place community testing sites in areas with the highest incidence of disease. Testing site demographic data indicated that targeted testing reached populations with the highest disease burden, suggesting that local health departments can effectively use surveillance data as a tool to address inequities. (Am J Public Health. 2021;111(S3):S197-S200. https://doi.org/10.2105/AJPH.2021.306421).

Impact of Medicaid expansion on smoking prevalence and quit attempts among those newly eligible, 2011-2019.

INTRODUCTION: Low-income populations have higher rates of smoking and are disproportionately affected by smoking-related illnesses. This study assessed the long-term impact of increased coverage for tobacco cessation through Medicaid expansion on past-year quit attempts and prevalence of cigarette smoking. METHODS: Using data from CDC's annual Behavioral Risk Factor Surveillance System 2011-2019, we conducted difference-in-difference regression analyses to compare changes in smoking prevalence and past-year quit attempts in expansion states versus non-expansion states. Our sample included non-pregnant adults (18-64 years old) without dependent children with incomes at or below 100% of the Federal Poverty Level (FPL). RESULTS: Regression analyses indicate that Medicaid expansion was associated with reduced smoking prevalence in the first two years post-expansion (ß=-0.019, p=0.04), but that this effect was not maintained at longer follow-up periods (ß=-0.006, p=0.49). Results of regression analyses also suggest that Medicaid expansion does not significantly impact quit attempts in the short-term (ß=-0.013, p=0.52) or at longer term follow-up (ß=-0.026, p=0.08). CONCLUSIONS: Expanded coverage for tobacco cessation services through Medicaid alone may not be enough to increase quit-attempts or sustain a reduction in overall prevalence of smoking in newly eligible populations over time. Medicaid programs should consider additional strategies, such as public education campaigns and removal of barriers, to support cessation among enrollees.

Hospital Partnerships for Population Health: A Systematic Review of the Literature.

EXECUTIVE SUMMARY: The U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health. National policies such as the Affordable Care Act and value-based payment reforms incentivize healthcare systems to engage in strategies to improve population health. Healthcare systems are increasingly expanding or developing new partnerships with community-based organizations to support these efforts. We conducted a systematic review of peer-reviewed literature in the United States to identify examples of hospital-community partnerships; the main purposes or goals of partnerships; study designs used to assess partnerships; and potential outcomes (e.g., process- or health-related) associated with partnerships. Using robust keyword searches and a thorough reference review, we identified 37 articles published between January 2008 and December 2019 for inclusion. Most studies employed descriptive study designs (n = 21); health needs assessments were the most common partnership focus (n = 15); and community/social service (n = 21) and public health organizations (n = 15) were the most common partner types. Qualitative findings suggest hospital-community partnerships hold promise for breaking down silos, improving communication across sectors, and ensuring appropriate interventions for specific populations. Few studies in this review reported quantitative findings. In those that did, results were mixed, with the strongest support for improvements in measures of hospitalizations. This review provides an initial synthesis of hospital partnerships to address population health and presents valuable insights to hospital administrators, particularly those leading population health efforts.

Public Health Informatics in Local and State Health Agencies: An Update From the Public Health Workforce Interests and Needs Survey.

OBJECTIVE: To characterize public health informatics (PHI) specialists and identify the informatics needs of the public health workforce. DESIGN: Cross-sectional study. SETTING: US local and state health agencies. PARTICIPANTS: Employees from state health agencies central office (SHA-COs) and local health departments (LHDs) participating in the 2017 Public Health Workforce Interests and Needs Survey (PH WINS). We characterized and compared the job roles for self-reported PHI, "information technology specialist or information system manager" (IT/IS), "public health science" (PHS), and "clinical and laboratory" workers. MAIN OUTCOME MEASURE: Descriptive statistics for demographics, income, education, public health experience, program area, job satisfaction, and workplace environment, as well as data and informatics skills and needs. RESULTS: A total of 17 136 SHA-CO and 26 533 LHD employees participated in the survey. PHI specialist was self-reported as a job role among 1.1% and 0.3% of SHA-CO and LHD employees. The PHI segment most closely resembled PHS employees but had less public health experience and had lower salaries. Overall, fewer than one-third of PHI specialists reported working in an informatics program area, often supporting epidemiology and surveillance, vital records, and communicable disease. Compared with PH WINS 2014, current PHI respondents' satisfaction with their job and workplace environment moved toward more neutral and negative responses, while the IT/IS, PHS, and clinical and laboratory subgroups shifted toward more positive responses. The PHI specialists were less likely than those in IT/IS, PHS, or clinical and laboratory roles to report gaps in needed data and informatics skills. CONCLUSIONS: The informatics specialists' role continues to be rare in public health agencies, and those filling that role tend to have less public health experience and be less well compensated than staff in other technically focused positions. Significant data and informatics skills gaps persist among the broader public health workforce.

Electronic Health Record (EHR)-Based Community Health Measures: An Exploratory Assessment of Perceived Usefulness by Local Health Departments.

BACKGROUND: Given the widespread adoption of electronic health record (EHR) systems in health care organizations, public health agencies are interested in accessing EHR data to improve health assessment and surveillance. Yet there exist few examples in the U.S. of governmental health agencies using EHR data routinely to examine disease prevalence and other measures of community health. The objective of this study was to explore local health department (LHD) professionals' perceptions of the usefulness of EHR-based community health measures, and to examine these perceptions in the context of LHDs' current access and use of sub-county data, data aggregated at geographic levels smaller than county. METHODS: To explore perceived usefulness, we conducted an online survey of LHD professionals in Indiana. One hundred and thirty-three (133) individuals from thirty-one (31) LHDs participated. The survey asked about usefulness of specific community health measures as well as current access to and uses of sub-county population health data. Descriptive statistics were calculated to examine respondents' perceptions, access, and use. A one-way ANOVA (with pairwise comparisons) test was used to compare average scores by LHD size. RESULTS: Respondents overall indicated moderate agreement on which community health measures might be useful. Perceived usefulness of specific EHR-based community health measures varied by size of respondent's LHD [F(3, 88) = 3.56, p = 0.017]. Over 70% of survey respondents reported using community health data, but of those < 30% indicated they had access to sub-county level data. CONCLUSION: Respondents generally preferred familiar community health measures versus novel, EHR-based measures that are not in widespread use within health departments. Access to sub-county data is limited but strongly desired. Future research and development is needed as LHD staff gain access to EHR data and apply these data to support the core function of health assessment.

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting.

BACKGROUND: Infectious diseases can appear and spread rapidly. Timely information about disease patterns and trends allows public health agencies to quickly investigate and efficiently contain those diseases. But disease case reporting to public health has traditionally been paper-based, resulting in somewhat slow, burdensome processes. Fortunately, the expanding use of electronic health records and health information exchanges has created opportunities for more rapid, complete, and easily managed case reporting and investigation. To assess how this new service might impact the efficiency and quality of a public health agency's case investigations, we compared the timeliness of usual case investigation to that of case investigations based on case report forms that were partially pre-populated with electronic data. INTERVENTION: Between September 2013-March 2014, chlamydia disease report forms for certain clinics in Indianapolis were electronically pre-populated with clinical, lab and patient data available through the Indiana Health Information Exchange, then provided to the patient’s doctor. Doctors could then sign the form and deliver it to public health for investigation and population-level disease tracking. Methods: We utilized a novel matched case analysis of timeliness changes in receipt and processing of communicable disease report forms. Each Chlamydia cases reported with the pre-populated form were matched to cases reported in usual ways. We assessed the time from receipt of the case at the public health agency: 1) inclusion of the case into the public health surveillance system and 2) to close to case. A hierarchical random effects model was used to compare mean difference in each outcome between the target cases and the matched cases, with random intercepts for case. RESULTS: Twenty-one Chlamydia cases were reported to the public health agency using the pre-populated form. Sixteen of these pre-populated form cases were matched to at least one other case, with a mean of 23 matches per case. The mean Reporting Lag for the pre-populated form cases was 2.5 days, which was 2.7 days shorter than the mean Reporting Lag for the matched controls (p = <0.001). The mean time to close a pre-populated form case was 4.7 days, which was 0.2 days shorter than time to close for the matched controls (p = 0.792). CONCLUSIONS: Use of pre-populated forms significantly decreased the time it took for the local public health agency to begin documenting and closing chlamydia case investigations. Thoughtful use of electronic health data for case reporting may decrease the per-case workload of public health agencies, and improve the timeliness of information about the pattern and spread of disease.

Completeness and timeliness of notifiable disease reporting: a comparison of laboratory and provider reports submitted to a large county health department.

BACKGROUND: Most public health agencies expect reporting of diseases to be initiated by hospital, laboratory or clinic staff even though so-called passive approaches are known to be burdensome for reporters and produce incomplete as well as delayed reports, which can hinder assessment of disease and delay recognition of outbreaks. In this study, we analyze patterns of reporting as well as data completeness and timeliness for traditional, passive reporting of notifiable disease by two distinct sources of information: hospital and clinic staff versus clinical laboratory staff. Reports were submitted via fax machine as well as electronic health information exchange interfaces. METHODS: Data were extracted from all submitted notifiable disease reports for seven representative diseases. Reporting rates are the proportion of known cases having a corresponding case report from a provider, a faxed laboratory report or an electronic laboratory report. Reporting rates were stratified by disease and compared using McNemar's test. For key data fields on the reports, completeness was calculated as the proportion of non-blank fields. Timeliness was measured as the difference between date of laboratory confirmed diagnosis and the date the report was received by the health department. Differences in completeness and timeliness by data source were evaluated using a generalized linear model with Pearson's goodness of fit statistic. RESULTS: We assessed 13,269 reports representing 9034 unique cases. Reporting rates varied by disease with overall rates of 19.1% for providers and 84.4% for laboratories (p < 0.001). All but three of 15 data fields in provider reports were more often complete than those fields within laboratory reports (p <0.001). Laboratory reports, whether faxed or electronically sent, were received, on average, 2.2 days after diagnosis versus a week for provider reports (p <0.001). CONCLUSIONS: Despite growth in the use of electronic methods to enhance notifiable disease reporting, there still exists much room for improvement.

Notifiable condition reporting practices: implications for public health agency participation in a health information exchange.

BACKGROUND: The future of notifiable condition reporting in the United States is undergoing a transformation with the increasing development of Health Information Exchanges which support electronic data-sharing and -transfer networks and the wider adoption of electronic laboratory reporting. Communicable disease report forms originating in clinics are an important source of surveillance data for public health agencies. However, problems of poor data quality and delayed submission of reports to public health agencies are common. In addition, studies of barriers and facilitators to reporting have assumed that the primary reporter is the treating physician, although the extent to which a provider is involved in the reporting workflow is unclear. We sought to better understand the barriers to and burden of notifiable condition reporting from the perspectives of the three primary groups involved in reporting workflow: providers, clinic staff who bear the principal responsibility for reporting, and the public health workers who receive and process reports from clinics. In addition, we sought to situate these findings within the context of the future of notifiable disease reporting and the potential impacts of electronic lab and medical records on the surveillance system. METHODS: Seven ambulatory care clinics and 3 public health agencies that are part of a Health Information Exchange in the state of Indiana, USA, participated in the study. Data were obtained from a survey of clinic physicians (N = 29), interviews with clinic reporters (N = 11), and interviews with public health workers (N = 9). Survey data were summarized descriptively and interview transcripts underwent qualitative analysis. RESULTS: In both clinics and public health agencies, the laboratory report initiates reporting workflow. Provider involvement with reporting primarily revolves around ordering medications to treat a condition confirmed by the lab result. In clinics, reporting is typically the responsibility of clinic reporters who vary in frequency of reporting. We found an association between frequency of reporting, reporting knowledge and perceptions of reporting burden. In both clinics and public health agencies, interruptions and delays in reporting workflow are encountered due to inaccurate or missing information and impact reporting timeliness, data quality and report completeness. Both providers and clinic reporters lack clarity regarding how data submitted by their reports are used by public health agencies. It is possible that the value of reporting may be diminished when those responsible do not perceive receiving benefit in return. This may account for the low awareness of or recollection of public health communications with clinics that we observed. Despite the high likelihood that public health advisories and guidance are based, in part, on data submitted by clinics, a direct concordance may not be recognized. CONCLUSIONS: Unlike most studies of notifiable condition reporting, this study included the clinic reporters who bear primary responsibility for completing and submitting reports to public health agencies. A primary barrier to this reporting is timely and easy access to data. It is possible that expanded adoption of electronic health record and laboratory reporting systems will improve access to this data and reduce reporting the burden. However, a complete reliance on automatic electronic extraction of data requires caution and necessitates continued interfacing with clinic reporters for the foreseeable future-particularly for notifiable conditions that are high-impact, uncommon, prone to false positive readings by labs, or are hard to verify. An important finding of this study is the association between frequency of reporting, reporting knowledge and perceptions of reporting burden. Increased automation could result in even lower reporting knowledge and familiarity with reporting requirements which could actually increase reporters' perception of notifiable condition reporting as burdensome. Another finding was of uncertainty regarding how data sent to public health agencies is used or provides clinical benefit. A strong recommendation generated by these findings is that, given their central role in reporting, clinic reporters are a significant target audience for public health outreach and education that aims to alleviate perceived reporting burden and improve reporting knowledge. In particular, communicating the benefits of public health's use of the data may reduce a perceived lack of information reciprocity between clinical and public health organizations.

Characterizing Informatics Roles and Needs of Public Health Workers: Results From the Public Health Workforce Interests and Needs Survey.

OBJECTIVE: To characterize public health workers who specialize in informatics and to assess informatics-related aspects of the work performed by the public health workforce. METHODS (DESIGN, SETTING, PARTICIPANTS): Using the nationally representative Public Health Workforce Interests and Needs Survey (PH WINS), we characterized and compared responses from informatics, information technology (IT), clinical and laboratory, and other public health science specialists working in state health agencies. MAIN OUTCOME MEASURES: Demographics, income, education, and agency size were analyzed using descriptive statistics. Weighted medians and interquartile ranges were calculated for responses pertaining to job satisfaction, workplace environment, training needs, and informatics-related competencies. RESULTS: Of 10,246 state health workers, we identified 137 (1.3%) informatics specialists and 419 (4.1%) IT specialists. Overall, informatics specialists are younger, but share many common traits with other public health science roles, including positive attitudes toward their contributions to the mission of public health as well as job satisfaction. Informatics specialists differ demographically from IT specialists, and the 2 groups also differ with respect to salary as well as their distribution across agencies of varying size. All groups identified unmet public health and informatics competency needs, particularly limited training necessary to fully utilize technology for their work. Moreover, all groups indicated a need for greater future emphasis on leveraging electronic health information for public health functions. CONCLUSIONS: Findings from the PH WINS establish a framework and baseline measurements that can be leveraged to routinely monitor and evaluate the ineludible expansion and maturation of the public health informatics workforce and can also support assessment of the growth and evolution of informatics training needs for the broader field. Ultimately, such routine evaluations have the potential to guide local and national informatics workforce development policy.

Measuring Population Health Using Electronic Health Records: Exploring Biases and Representativeness in a Community Health Information Exchange.

Assessment is a core function of public health. Comprehensive clinical data may enhance community health assessment by providing up-to-date, representative data for use in public health programs and policies, especially when combined with community-level data relevant to social determinants. In this study we examine routinely collected and geospatially-enhanced EHR data to assess population health at various levels of geographic granularity available from a regional health information exchange. We present preliminary findings and discuss important biases in EHR data. Future work is needed to develop methods for correcting for those biases to support routine epidemiology work of public health.

Estimating increased electronic laboratory reporting volumes for meaningful use: implications for the public health workforce.

OBJECTIVE: To provide formulas for estimating notifiable disease reporting volume from 'meaningful use' electronic laboratory reporting (ELR). METHODS: We analyzed two years of comprehensive ELR reporting data from 15 metropolitan hospitals and laboratories. Report volumes were divided by population counts to derive generalizable estimators. RESULTS: Observed volume of notifiable disease reports in a metropolitan area were more than twice national averages. ELR volumes varied by institution type, bed count, and by the level of effort required of health department staff. CONCLUSIONS: Health departments may experience a significant increase in notifiable disease reporting following efforts to fulfill meaningful use requirements, resulting in increases in workload that may further strain public health resources. Volume estimators provide a method for predicting ELR transaction volumes, which may support administrative planning in health departments.

The common ground preparedness framework: a comprehensive description of public health emergency preparedness.

Currently, public health emergency preparedness (PHEP) is not well defined. Discussions about public health preparedness often make little progress, for lack of a shared understanding of the topic. We present a concise yet comprehensive framework describing PHEP activities. The framework, which was refined for 3 years by state and local health departments, uses terms easily recognized by the public health workforce within an information flow consistent with the National Incident Management System. To assess the framework's completeness, strengths, and weaknesses, we compare it to 4 other frameworks: the RAND Corporation's PREPARE Pandemic Influenza Quality Improvement Toolkit, the National Response Framework's Public Health and Medical Services Functional Areas, the National Health Security Strategy Capabilities List, and the Centers for Disease Control and Prevention's PHEP Capabilities.

Dietary behaviors associated with fruit and vegetable consumption, Marion County, Indiana, 2005.

INTRODUCTION: Eating inadequate amounts of fruits and vegetables is associated with diminished health, and most Americans fall short of the Centers for Disease Control and Prevention's recommendation to eat at least 2 servings of fruit and 3 servings of vegetables each day. This study assessed behaviors associated with fruit and vegetable consumption in adults. METHODS: A cross-sectional, random-digit-dialed telephone survey of 4,784 adults living in Marion County (Indianapolis), Indiana, measured demographic characteristics, personal health data, food consumption, food label use, and other eating habits. Multivariate logistic regressions were used to assess the association between selected dietary behaviors and fruit and vegetable consumption, controlling for demographic characteristics. RESULTS: Behaviors associated with adequate versus inadequate consumption of fruits and vegetables were frequent snacking on healthy foods (odds ratio [OR], 2.54), eating meals at home (OR, 2.09), using nutrition labels when making purchases (OR, 1.52), and using "heart healthy" symbols and other food information labels when ordering from restaurants (OR, 1.41). Frequent red meat consumption was negatively associated with adequate consumption of fruits and vegetables (OR, 0.64). CONCLUSION: Healthful snacking, food label use, and eating meals prepared at home may improve dietary quality. Our measure of adequacy may also be useful in future studies assessing dietary behavior and diet composition.

Effectiveness and cost of risperidone and olanzapine for schizophrenia: a systematic review.

Risperidone and olanzapine are novel antipsychotic medications that compete as first-line agents in treating patients with schizophrenia. The objective of this paper is to review the available evidence regarding the effectiveness and cost of risperidone versus olanzapine. We reviewed both randomised and peer-reviewed non-randomised head-to-head (olanzapine versus risperidone) studies in populations with schizophrenia. The studies were selected through a MEDLINE search. Risperidone and olanzapine provide control of positive, negative and global symptoms of schizophrenia. Each drug has a distinct adverse effect profile. Five randomised trials comparing risperidone with olanzapine suggested grossly similar efficacy in the first 2 months of treatment, with some results indicating advantages for olanzapine over the longer term. Only two of the trials included measures of service utilisation. One had 28-week follow-up, and the other followed patients for 12 months but had small sample sizes. Both experimental and naturalistic studies indicated that the acquisition cost of olanzapine is about 50% greater than for risperidone at dose levels commonly used for the treatment of schizophrenia. The only experiment with 12-month total treatment cost data found essentially equivalent costs for patients assigned to olanzapine or risperidone, showing that there are circumstances where total cost is similar in spite of the higher drug acquisition cost of olanzapine. Most retrospective studies also reported comparable total cost. Few studies gave enough information to evaluate cost effectiveness. The clear difference in acquisition cost of these two medications was rarely reflected in overall treatment cost in the studies we reviewed. Overall, our review of the literature highlights that there is inadequate evidence to distinguish the relative total cost of care associated with risperidone versus olanzapine, although accumulating evidence suggests the difference is small. This population-based conclusion does not indicate which medication is more costly or more cost effective for a particular patient; this depends on each patient's response to each medication.

Medication use patterns and 2-year outcome in first-admission bipolar disorder with psychotic features.

OBJECTIVE: This study examined the patterns and predictors of medication use and 24-month course/outcome in first-admission patients with bipolar disorder (BD) with psychotic features. METHOD: An epidemiologic sample of 155 first-admission patients with research diagnoses of BD with psychotic features received intensive clinical assessments at baseline, 6- and 24-month follow-ups and telephone assessments at 3-month intervals. Use of antipsychotics, antimanic agents (lithium and anticonvulsants), and antidepressants was determined from self-reports corroborated by external sources where possible. Outcome was assessed with the Global Assessment of Functioning (GAF), consensus evaluations of illness course, and time in remission. RESULTS: More patients received antipsychotics (80.0%) than antimanics (52.3%) at discharge. At the 24-month point, 44.6% reported using no medications; 19.4 and 38.8% received antipsychotics and antimanics, respectively. Health insurance and early regular antimanic use were the strongest predictors of regular antimanic use during the 6-24-month follow-up. Early and later regular use of antimanics and less use of antipsychotics were associated with higher GAF scores and greater time in remission. Conversely, failure to use antimanics regularly was associated with the worst outcome on these two measures. Early functioning as measured by the GAF strongly predicted outcome for all three measures. Younger and non-White subjects were significantly less likely to attain complete remission during the 6-24-month follow-up. CONCLUSIONS: The findings confirm clinical trial data that for some outcome measures use of antimanics is associated with good outcome in bipolar populations while failure to use these medications regularly was common among subjects with the worst outcomes. In addition, our findings that higher educational attainment and having health insurance predicted regular antimanic use and (for the latter) better outcome underscore the effect of socioeconomic influences while achieving a complete remission seems unrelated to medication use but strongly predicted by age and ethnicity. Finally, the fact that early regular treatment and early high functioning strongly predicted better outcome supports the need for the early diagnosis and treatment of patients with this disorder.