Search

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 )

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.

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 (β=-0.019, p=0.04), but that this effect was not maintained at longer follow-up periods (β=-0.006, p=0.49). Results of regression analyses also suggest that Medicaid expansion does not significantly impact quit attempts in the short-term (β=-0.013, p=0.52) or at longer term follow-up (β=-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.

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.

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.

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.

Objective To assess the equivalence of hypertension prevalence estimates between longitudinal electronic health record (EHR) data from a community-based health information exchange (HIE) and the Behavioral Risk Factor Surveillance System (BRFSS). Introduction Hypertension (HTN) is a highly prevalent chronic condition and strongly associated with morbidity and mortality. HTN is amenable to prevention and control through public and population health programs and policies. Therefore, public and population health programs require accurate, stable estimates of disease prevalence, and estimating HTN prevalence at the community-level is acutely important for timely detection, intervention, and effective evaluation. Current surveillance methods for HTN rely upon community-based surveys, such as the BRFSS. While BRFSS is the standard at the state- and national-level, they are expensive to collect, released once per year, and their confidence intervals are too wide for precise estimates at the local level. More timely, frequently updated, and locally precise prevalence estimates could greatly improve the timeliness and precision of public health interventions. The current study evaluated EHR data from a large, mature HIE as an alternative to community-based surveys for timely, accurate, and precise HTN prevalence estimation. Methods Two years (2014-2015) of EHR data were obtained from the Indiana Network for Patient Care for two major health systems in Marion County, Indiana, representing approximately 75% of the total county population (n=530,244). These data were linked and evaluated for prevalent HTN. Six HTN phenotypes were defined using structured data variables including clinical diagnoses (ICD9/10 codes), blood pressure (BP) measurements (HTN = ≥140mmhg systolic or ≥90mmHg diastolic), and dispensed HTN medications (Table 1). Phenotypes were validated using a random sample of 600 records, comparing EHR phenotype HTN to HTN as determined through manual chart review by a Registered Nurse. Each phenotype was further evaluated against BRFSS estimates for Marion County, and stratified by sex, race, and age to compare EHR-generated HTN prevalence measures to those known and in current use for chronic disease surveillance. Comparisons were made using the two one-sided statistical test (TOST) of equivalence, wherein the null hypothesis is the BRFSS and EHR prevalence estimates are different by +/-5% and the alternative is estimates differ by less than +/-5%. Rejection of the null resulted in the conclusion of equivalence of the estimates for use in population/public health. Results In general, the performance of the EHR phenotypes was characterized by high specificity (>87%) and low to moderate sensitivity (range 25.4%-95.3%). The false positive rate was lowest among the phenotype defining HTN by both clinical diagnosis and BP measurements (0.3%), and sensitivity was greatest for the phenotype combining all three structured data elements (95.2%). The prevalence of HTN in Marion County, Indiana (2014-2015) for the EHR sample (n=530,244) ranged between 13.7% and 36.2%, compared to 28.4% in the BRFSS sample (Table 1). Only one EHR phenotype (≥1 HTN BP measurement) demonstrated equivalence with BRFSS prevalence at the county level (difference 0.9%, 90% CI for difference -2.3%-4.0%). HTN prevalence by sex, race, age, sex and age, and sex and race (n=120 comparisons) failed to demonstrate equivalence between EHR and BRFSS measures in all but two comparisons, both among females aged 18-39 years. Differences between EHR and BRFSS HTN prevalence at the subgroup level varied but were particularly pronounced among older adults. As suspected, HTN prevalence precision was improved in the EHR sample with the largest subgroup 95% CI width of 0.7% for male African Americans compared to the BRFSS sample 95% CI width of 29.6%. Conclusions The applicability of the tested HTN phenotypes will vary based upon which EHR structured data elements are available to public health (i.e., ICD10, vitals, medications). We found that HTN surveillance using a community-based HIE was not a valid replacement for the BRFSS, although the HIE-based estimates could be readily generated and had much narrower confidence intervals. References Mozaffarian D, et al. Heart Disease and Stroke Statistics — 2016 Update. Circulation. 2016; 133: e38-e360. Yoon S, Fryar C, Carroll M. HTN Prevalence and Control Among Adults: United States, 2011–2014. NCHS Data Brief No. 220. 2015; Hyattsville, MD: National Center for Health Statistics, Centers for Disease Control and Prevention, US Dept of Health and Human Services.

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

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 =

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

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.

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.

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.

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.

BACKGROUND:Clinicians treating schizophrenia face increasingly diverse ethnic populations. Ethnic groups may have different approaches to the management of schizophrenia, which could impact antipsychotic medication adherence.OBJECTIVE:To examine the association between adherence and ethnicity or the specific medication used after controlling for other factors.METHODS:Texas Medicaid claims were retrieved for persons aged 21–65 years, diagnosed with schizophrenia or schizoaffective disorder, after initiating treatment with olanzapine (n = 1875), risperidone (n = 982), or haloperidol (n = 726) between January 1997 and August 1998. The association between ethnicity (African American, Mexican American, white) or medication and days' use of the medication in the year following initiation was assessed using multivariate linear regression. Covariates included other patient demographics, region, comorbid mental health conditions, and prior medication and healthcare resource use.RESULTS:African American and Mexican American patients were significantly less adherent than white patients (19 d less, p < 0.001 for African Americans; 18 d less, p = 0.003 for Mexican Americans). For patients of all ethnicities, olanzapine was associated with 23 more adherent days than risperidone and 55 more adherent days than haloperidol (p < 0.001 for each comparison).CONCLUSIONS:When other factors were controlled for, ethnicity was a significant predictor of medication adherence following initiation on an antipsychotic medication, and patients of all ethnicities were most adherent when taking olanzapine, less adherent when taking risperidone, and least adherent when taking haloperidol.

This article presents an analytic tool populated with data from published studies to illustrate the likely impacts of a switch from typical to atypical antipsychotic drugs over a 3-year period on individual, family, and societal outcomes for a U.S. schizophrenia population. Data taken from clinical trials and observational data studies are used. Changes in annual health care costs, schizophrenia symptom days, extrapyramidal symptom (EPS) days, suicide rates, and employment days are estimated. For each 1,000 people treated with typical drugs, the base case scenario gives estimates of annual medical care costs of dollar 28.9 million with 80,253 moderate/severe schizophrenia symptom days and 92,006 EPS days. In the base case scenario, after switching to atypical drugs, schizophrenia symptom days are estimated to decrease up to 33 percent, EPS days up to 50 percent, and total medical care costs up to 19 percent over the 3-year period. Suicide rates fall and employment rates increase. The direction of the impacts remain the same for a wide range of input parameter values used in sensitivity analyses. Thus, switching to atypical drugs will likely reduce total medical care costs and decrease other disease burdens for people with schizophrenia, their families, and society.

Disease prevention and management (DPM) represents a relatively recent paradigm shift in the provision of healthcare, from a focus on individual components of healthcare, to a more holistic view of patient care. The purpose of this article is to provide practical guidelines that can be used in designing, implementing and evaluating DPM programmes. There are 6 steps in the design phase: (i) conducting an epidemiological diagnosis; (ii) reviewing the scientific literature; (iii) identifying the goal and outcome objectives; (iv) specifying strategy objectives and strategy activities; (v) selecting a study design; and (vi) considering the characteristics of effective outcomes measures. The implementation and evaluation phases include collecting the data, examining the data and reporting the results. Concepts and principles presented here are based on key methodological features of population research.

OBJECTIVE: We evaluated relationships between breech presentation and infant, maternal, and pregnancy characteristics of singleton births. STUDY DESIGN: A population-based case-control study (3588 breech cases, 8183 controls) was conducted with data from the 1987 to 1988 Washington State birth certificate. RESULTS: Low birth weight, short gestational age, primiparity, and older maternal age were associated with increased risk of breech birth, and after we controlled for these factors, the following were also associated with breech birth: hydrocephalus, established maternal diabetes, congenital malformation of the infant, smoking during pregnancy, and late or no prenatal care. In addition, black and Filipino women had decreased risk of breech presentation compared with white women. CONCLUSION: Several different maternal and infant characteristics appear to increase risk of breech birth, suggesting that there may be several different biologic mechanisms leading to breech presentation. (AM J OBSTET GYNECOL 1996;174:28-32.)

Many data privacy models have been created in the last few years using the k-anonymization methodology including l-diversity, p-sensitive k-anonymity, and t-closeness. While these methods differ in their approaches and quality of the results, they all focus on ensuring the anonymization of the data while at the same time attempt to protect the quality of the data by minimizing the loss of the information contained in the original data set. In this paper, we propose an automated k-anonymity approach that uses clustering to maximize the utility of the data while ensuring that the data privacy is maintained. Our method employs data constraint rules, which are defined by the data research expert to represent especially informative distributions in categorical attributes or inflections points in a continuous attribute. The values of the data constraints are an integral component of our utility function, which is used to maximize the utility of the anonymized dataset. Finally, we present our experimental results that show that our approach meets or exceeds existing methods that do not incorporate data constraint rules.

As medical data continues to transition to an electronic format, opportunities arise for researchers to use this microdata to discover patterns and increase knowledge in order to improve patient care. Now more than ever, it is critical to protect the identities of the patients contained in these databases. Even after removing obvious "identifier" attributes, such as social security numbers or first and last names, that clearly identify a specific person, it is possible to join "quasi-identifier" attributes from two or more publicly available databases to identify individuals. K-anonymity is an established approach that has been used to ensure that no one individual can be distinguished within a group of at least k individuals. The majority of the proposed approaches implementing k-anonymity have focused on improving the efficiency of algorithms implementing k-anonymity; less emphasis has been put towards ensuring the "utility" of anonymized data from a researchers' perspective. We propose a data utility measurement, called the research value (RV), which evaluates how well common cutoffs for numerical data or groupings in categorical data are preserved during the anonymization process. The proposed algorithm utilizing the new utility function scales efficiently when the number of attributes is large, while still ensuring that the generalization process is dictated by the data content expert's assessment of the utility of the generalized data.

The authors examined gaps in the use of antipsychotic medications during the one-year period after discharge in an epidemiological sample of 189 first-admission patients with schizophrenia between July 1989 and January 1996. Sixty-three percent of the patients had one or more such gaps, and 51 percent had gaps of 30 days or longer, with an average total time off medication of about seven months. Most gaps occurred soon after discharge, and 73 percent were initiated by the patient. These data, which were obtained before the widespread use of atypical antipsychotic agents, provide a benchmark against which to examine the impact of the newer medications on adherence and continuity of treatment in the critical early stages of schizophrenia.

Second-generation antipsychotics may enhance the rehabilitation of individuals with schizophrenia. The authors hypothesized that clients receiving second-generation antipsychotics would use vocational rehabilitation services more effectively and would have better employment outcomes than those receiving first-generation antipsychotics.Ninety unemployed clients with schizophrenia and related disorders who were beginning a vocational rehabilitation program were followed for nine months. Three groups were defined according to the medication in use at study entry: olanzapine (N=39), risperidone (N=27), or first-generation antipsychotics only (N=24). Participants were interviewed monthly.The olanzapine and risperidone groups did not differ on any employment outcomes. On most vocational indicators, clients receiving second-generation agents did not differ from those receiving first-generation agents. However, at nine months the second-generation group had a significantly higher rate of participation in vocational training; a trend was found toward a higher rate of paid employment. All groups showed substantial improvement in employment outcomes after entering a vocational program.The hypothesis that second-generation antipsychotics promote better employment outcomes than first-generation antipsychotics was not upheld. However, second-generation agents appear to be associated with increased participation in vocational rehabilitation.

This study compares the effects of atypical and conventional antipsychotic medications on treatment continuation and outcomes in a first admission sample of patients with schizophrenia treated in usual practice settings. In a sample of 189 participants with a research diagnosis of DSM-IV schizophrenia drawn from the Suffolk County Mental Health Project, we compared the effects of atypical and conventional agents on change of medication, medication gaps, and rehospitalization. For these analyses we used the method of survival analysis for recurrent events, in which the episodes of treatment rather than individual subjects are the units of analysis. In addition, we compared improvement in positive and negative symptoms from intake to 24- or 48-month followups for subjects who stayed on one type of medication or changed to atypicals from conventional antipsychotics. Atypical agents were associated with lower risk of medication change, medication gaps, and rehospitalization. Both conventional and atypical agents were associated with improvement of positive symptoms at followup, but only subjects on atypical agents at followup experienced a significant improvement in negative symptoms. We conclude that in usual practice settings, as in randomized clinical trials, atypical agents are associated with improved treatment continuation and outcomes.

To describe the prescription of antipsychotic agents in the United States and to investigate the association between demographic characteristics, clinical diagnosis, and antipsychotic prescribed.Four years (1997-2000) of data from the National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Care Survey (NHAMCS) were combined for analysis. Distributions for patient age, race, gender, primary diagnosis, and provider's medical specialty were assessed. Logistic regression models were developed to estimate the probability of receiving either (1) a second-generation vs a first-generation antipsychotic, or (2) olanzapine vs risperidone, given differences in gender, race, age, and primary diagnosis.Nearly 35.9 million ambulatory healthcare visits resulted in antipsychotic prescription during 1997-2000, or nearly 1% of all healthcare visits for the period. Nearly 30% of these visits were to nonpsychiatric physicians. The use of first-generation antipsychotics declined during this period, while the use of second-generation antipsychotics increased. Risperidone and olanzapine accounted for the majority of second-generation antipsychotic use. While the mean ages of patients using risperidone and olanzapine were similar, the age distributions differed, with risperidone showing more frequent use among the young (18 years) and the old (65 years). Patients of nonwhite race were more likely to receive olanzapine than risperidone.Results from this national survey indicate that second-generation antipsychotics are being used with increasing frequency and are widely used outside of the psychiatric specialty. Differences in age distribution, racial representation, and diagnostic representation are associated with drug selection, reinforcing the importance of accounting for case-mix factors when researching these antipsychotics in observational studies.

Background Culture and ethnicity have been suggested to influence the presentation of patients with schizophrenia. These factors are thought to affect the diagnoses, courses of treatment, and medical utilization patterns of patients with schizophrenia. Specifically, the differences between whites, African Americans, and Mexican Americans are of particular importance, as these groups comprise the majority of the population in the United States today. The traditional course of treatment for many patients with schizophrenia is the drug haloperidol. However, research has shown that some ethnic groups (African Americans and Mexican Americans) may respond better to atypical drugs, such as olanzapine, but may be less likely to receive these drugs. A better response to the course of treatment results in improved medical utilization patterns. The purpose of this study was to examine if ethnicity helped predict whether Texas Medicaid patients were prescribed haloperidol versus olanzapine when other factors were controlled for. Method The study population consisted of 726 patients whose index drug was haloperidol and 1875 patients whose index drug was olanzapine. Patients had an ICD-9-CM diagnosis of schizophrenia or schizoaffective disorder. Texas medical and prescription claims data were used in a logistic regression analysis to determine significant predictors of the type of antipsychotic (haloperidol vs. olanzapine) patients were prescribed. Variables included in the analysis were ethnicity, gender, age, region, other mental illness comorbidities, and previous utilization of medications and resources. Data were collected from Jan. 1, 1996, to Aug. 31, 1998. Results The results show that when other demographic and utilization factors were controlled for, African Americans were less likely than whites to receive olanzapine rather than haloperidol. Conclusion Ethnicity is a significant predictor of the type of antipsychotic that is prescribed.

Cognitive impairments in schizophrenia appear to be associated with social problem solving, social and vocational functioning, and psychosocial skill acquisition. The present study examined the relationship of cognitive functioning, as well as clinical symptoms, to vocational outcomes among individuals with schizophrenia. One hundred and twelve participants with DSM-IV schizophrenia spectrum diagnoses underwent a comprehensive neuropsychiatric evaluation after enrolling in one of several employment programs. The neuropsychological evaluation examined verbal learning and memory, attention, speed of information processing, and executive functioning. Clinical symptoms were evaluated with the Positive and Negative Syndrome Scale (PANSS). Vocational outcomes were assessed 4 months after baseline assessment and included both measures of employment outcome (e.g., earnings) and of work performance as assessed by the Work Behavior Inventory (WBI). Negative symptoms, learning and memory performance, processing speed, and executive functioning were related to hours, weeks, and wages earned on the job. Stepwise multiple regression analyses found that among baseline clinical and cognitive predictors, only verbal learning and memory and cognitive disorganization symptoms were significant predictors of work behaviors 4 months later. Learning and memory were the only significant predictors of integrated employment at 4 months. These results suggest specific aspects of cognition may be modestly predictive of vocational outcomes.

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.

ObjectiveThe objective of this study was to assess the impact of medication treatment on Medicaid costs for persons with schizophrenia.MethodsMichigan Medicaid claims from January 1995 through September 1998 were analyzed for persons with schizophrenia diagnoses who initiated olanzapine (n = 458), risperidone (n = 481), or haloperidol (n = 252) treatment between January 1996 and September 1997. Total and component Medicaid payments were compared for the year after treatment initiation, with simultaneous adjustment for patient demographics, comorbid conditions, prior medication use, prior service use, and prior year costs.ResultsSignificant baseline differences existed between the groups in prior medication and service use. Adherence to index medication varied between the groups (O = 60%; R = 54%; H = 37%; P < = .01 for each pairwise comparison). Average postperiod costs were $14,512 per subject. After baseline adjustment, there were no significant differences in mean total cost. Excluding index medication costs, the olanzapine group's average cost was significantly lower than risperidone (–$1,791, P = .002) and haloperidol (–$2,080, P = .003), whereas the risperidone and haloperidol groups were not significantly different. The differences were driven by significantly lower cost for inpatient services for other medications among the olanzapine group.ConclusionTotal costs of schizophrenia care associated with olanzapine, risperidone, or haloperidol were similar, but component costs differed. Relative to risperidone or haloperidol, olanzapine may have a higher acquisition cost, but may decrease inpatient costs and be associated with more optimal medication use patterns. Use of risperidone may also increase pharmacy costs and be associated with greater persistence, relative to haloperidol.

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. Electronic supplementary material The online version of this article (doi:10.1186/s12889-017-4156-4) contains supplementary material, which is available to authorized users.