Search

Objective. To document the process used in assessing the public health impact of proposed health insurance benefit mandates in California as part of the California Health Benefits Review Program (CHBRP) to serve as a guide for other states interested in incorporating a public health impact analysis into their state mandated benefit review process. Background. As of September 2004, of the 26 states that require reviews of mandated benefit legislation, 25 required an assessment of the cost impact, 12 required an assessment of the medical efficacy, and only 6 had language requiring an assessment of the public health impact. Methodology. This paper presents the methodology used to calculate the overall public health impact of each mandate. This includes a discussion of data sources, required data elements, and the methods used to quantify the impact of a mandated health insurance benefit on: overall public health, on gender and racial disparities in health outcomes, on premature death, and on the economic loss associated with disease. In addition we identify the limitations of this type of analysis. Conclusions. The approach that California has adopted to review proposed health benefit mandates represents a leap forward in its consideration of the impact of such mandates on the health of the population. the approach is unique in its specific requirements to address public health impacts as well as the attempt to quantify these impacts by the CHBRP team. The requirement to make available this information to the state government has the potential, ultimately, to increase the availability of health insurance products in California that will maximize public health. [ABSTRACT FROM AUTHOR]

Objective: To describe the process of implementing a Youth Participatory Action Research (YPAR) project at a continuation high school (CHS) and share the results of a youth‐designed research project that explores barriers to high school completion. Data Sources and Study Setting: YPAR was implemented across three cohorts at a CHS in the central coast of California from 2019 to 2022. Student survey respondents were enrolled CHS students between March and April 2021. Study Design: A modified YPAR curriculum integrating research methodology and social justice topics was used to guide student‐led research that resulted in a cross‐sectional survey. Data Collection: Field notes maintained by the first author documented the process of implementing YPAR including the curriculum, conversations, and research decisions and procedures. A student‐designed survey disseminated to all enrolled students resulted in 76 (66%) participant responses. The survey included 18 close‐ended questions and three narrative responses. Principal Findings: This study details how YPAR methodologies can be translated to a high school credit recovery program. For example, student cohorts were needed to maintain continuity over time. A student‐designed survey revealed that 72% of student respondents reported taking care of family members and illuminated high rates of depression symptoms. Conclusions: This study offers a detailed description of how we implemented YPAR at a credit recovery program and provides student‐driven perspectives on educational reform and evaluation. This project addresses the implementation and challenges of using YPAR to engage youth in transformational resistance to rapidly study and improve CHS' policy and practice. [ABSTRACT FROM AUTHOR]

Objective: To develop easy to use and validated predictive models to identify beneficiaries experiencing homelessness from administrative data. Data Sources: We pooled enrollment and claims data from enrollees of the California Whole Person Care (WPC) Medicaid demonstration program that coordinated the care of a subset of Medicaid beneficiaries identified as high utilizers in 26 California counties (25 WPC Pilots). We also used public directories of social service and health care facilities. Study Design: Using WPC Pilot‐reported homelessness status, we trained seven supervised learning algorithms with different specifications to identify beneficiaries experiencing homelessness. The list of predictors included address‐ and claims‐based indicators, demographics, health status, health care utilization, and county‐level homelessness rate. We then assessed model performance using measures of balanced accuracy (BA), sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (area under the curve [AUC]). Data Collection/Extraction Methods: We included 93,656 WPC enrollees from 2017 to 2018, 37,441 of whom had a WPC Pilot‐reported homelessness indicator. Principal Findings: The random forest algorithm with all available indicators had the best performance (87% BA and 0.95 AUC), but a simpler Generalized Linear Model (GLM) also performed well (74% BA and 0.83 AUC). Reducing predictors to the top 20 and top five most important indicators in a GLM model yields only slightly lower performance (86% BA and 0.94 AUC for the top 20 and 86% BA and 0.91 AUC for the top five). Conclusions: Large samples can be used to accurately predict homelessness in Medicaid administrative data if a validated homelessness indicator for a small subset can be obtained. In the absence of a validated indicator, the likelihood of homelessness can be calculated using county rate of homelessness, address‐ and claim‐based indicators, and beneficiary age using a prediction model presented here. These approaches are needed given the rising prevalence of homelessness and the focus of Medicaid and other payers on addressing homelessness and its outcomes. [ABSTRACT FROM AUTHOR]

Objective: To evaluate whether the expansion of Federally Qualified Health Centers (FQHCs) improved late prenatal care initiation, low birth weight, and preterm birth among Medicaid‐covered or uninsured individuals. Data Sources and Study Setting: We identified all FQHCs in California using the Health Resources and Services Administration's Uniform Data System from 2000 to 2019. We used data from the U.S. Census American Community Survey to describe area characteristics. We measured outcomes in California birth certificate data from 2007 to 2019. Study Design: We compared areas that received their first FQHC between 2011 and 2016 to areas that received it later or that had never had an FQHC. Specifically, we used a synthetic control with a staggered adoption approach to calculate non‐parametric estimates of the average treatment effects on the treated areas. The key outcome variables were the rate of Medicaid or uninsured births with late prenatal care initiation (>3 months' gestation), with low birth weight (<2500 grams), or with preterm birth (<37 weeks' gestation). Data Collection/Extraction Methods: The analysis was limited to births covered by Medicaid or that were uninsured, as indicated on the birth certificate. Principal Findings: The 55 areas in California that received their first FQHC in 2011–2016 were more populous; their residents were more likely to be covered by Medicaid, to be low‐income, or to be Hispanic than residents of the 48 areas that did not have an FQHC by the end of the study period. We found no statistically significant impact of the first FQHC on rates of late prenatal care initiation (ATT: −10.4 [95% CI −38.1, 15.0]), low birth weight (ATT: 0.2 [95% CI −7.1, 5.4]), or preterm birth (ATT: −7.0 [95% CI −15.5, 2.3]). Conclusions: Our results from California suggest that access to primary and prenatal care may not be enough to improve these outcomes. Future work should evaluate the impact of ongoing initiatives to increase access to maternal health care at FQHCs through targeted workforce investments. [ABSTRACT FROM AUTHOR]

Objective: To operationalize an intersectionality framework using a novel statistical approach and with these efforts, improve the estimation of disparities in access (i.e., wait time to treatment entry) to opioid use disorder (OUD) treatment beyond race. Data source Sample of 941,286 treatment episodes collected in 2015–2017 in the United States from the Treatment Episodes Data Survey (TEDS‐A) and a subset from California (n = 188,637) and Maryland (n = 184,276), states with the largest sample of episodes. Study design This retrospective subgroup analysis used a two‐step approach called virtual twins. In Step 1, we trained a classification model that gives the probability of waiting (1 day or more). In Step 2, we identified subgroups with a higher probability of differences due to race. We tested three classification models for Step 1 and identified the model with the best estimation. Data collection: Client data were collected by states during personal interviews at admission and discharge. Principal findings: Random forest was the most accurate model for the first step of subgroup analysis. We found large variation across states in racial disparities. Stratified analysis of two states with the largest samples showed critical factors that augmented disparities beyond race. In California, factors such as service setting, referral source, and homelessness defined the subgroup most vulnerable to racial disparities. In Maryland, service setting, prior episodes, receipt of medication‐assisted opioid treatment, and primary drug use frequency augmented disparities beyond race. The identified subgroups had significantly larger racial disparities. Conclusions: The methodology used in this study enabled a nuanced understanding of the complexities in disparities research. We found state and service factors that intersected with race and augmented disparities in wait time. Findings can help decision makers target modifiable factors that make subgroups vulnerable to waiting longer to enter treatment. [ABSTRACT FROM AUTHOR]

Objective. To examine whether known Medicaid enrollees misreport their health insurance coverage in surveys and the extent to which misreports of lack of coverage bias estimates of uninsurance. Data Source. Primary survey data from the Medicaid Undercount Experiment. Study Design. Analyze new data from surveys of Medicaid enrollees in California, Florida, and Pennsylvania and summarize existing research examining bias in coverage estimates due to misreports among Medicaid enrollees. Data Collection Method. Subjects were randomly drawn from Medicaid administrative records and were surveyed by telephone. Principal Findings and Conclusions. Cumulative evidence shows that a small percentage of Medicaid enrollees mistakenly report being uninsured, resulting in modest upward bias in estimates of uninsurance. A somewhat larger percentage of enrollees report having some other type of coverage than no coverage, biasing Medicaid enrollment estimates downward but not biasing estimates of uninsurance significantly upward. Implications for policy makers' confidence in survey estimates of coverage are discussed. [ABSTRACT FROM AUTHOR]

Objective: To estimate novel measures of generalist physicians' network connectedness to HIV specialists and their associations with two dimensions of HIV quality of care. Data Sources: Medicare and Medicaid claims and the American Medical Association Masterfile data on people living with HIV (PLWH) and the physicians providing their HIV care in California between 2007 and 2010. Study Design: I construct regional patient-sharing physician networks from the shared treatment of PLWH and calculate (a) measures of network connectedness to all physician types and (b) specialty-weighted measures to describe connectedness to HIV specialists. Two HIV quality of care outcomes are then evaluated: medication quality (prescribing antiretroviral drugs from at least two drug classes) and monitoring quality (at least two annual HIV virus monitoring scans). Linear probability models estimate the associations between network statistics and the two dimensions of HIV quality of care, and a policy simulation demonstrates the importance of these statistical relationships. These analyses include 16 124 PLWH, 3240 generalists, and 1031 HIV specialists. Data Collection/Extraction Methods: PLWH are identified from claims for patients with any indication of HIV using an existing algorithm from the literature. Principal Findings: Generalists' network connectedness to HIV specialists is positively related with their own HIV medication quality; one additional HIV specialist connection is associated with a 1.46 percentage point (SE 0.42, P < .01) increase in generalist's medication quality. Based on the estimated associations, a simulated policy that increases connectedness between generalists and HIV specialists reduces the annual rate of HIV infections by up to 6%, roughly 290 fewer infections per year. Only network connectedness to all physician types is associated with improved monitoring quality. Conclusions: Network connectedness to HIV specialists is positively associated with generalists' HIV medication quality, which suggests that specialists provide clinical support through patient-sharing for complex treatment protocol. [ABSTRACT FROM AUTHOR]

Determines the effects of competition for both Medicare and patients enrolled in health maintenance organizations on the quality decisions of hospitals in Southern California. Analysis of secondary discharge data from the Office of Statewide Health Planning and Development for the State of California; Formulation of competition measures; Increase in the degree of competition associated with hospital mortality rates.

Objective: The California Delivery System Reform Incentive Payment Program (DSRIP) provided incentive payments to Designated Public Hospitals (DPHs) to improve quality of care. We assessed the program's impact on reductions in sepsis mortality, central line–associated bloodstream infections (CLABSIs), venous thromboembolisms (VTEs), and hospital‐acquired pressure ulcers (HAPUs). Data Sources: We used 2009‐2014 discharge data from California hospitals. Study Design: We used a pre‐post study design with a comparison group. We constructed propensity scores and used them to assign inverse probability weights according to their similarity to DPH discharges. Interaction term coefficients of time trends and treatment group provided significance testing. Data Extraction: We used Patient Safety Indicators for CLABSI, HAPU, and VTE, and constructed a sepsis mortality measure. Principal Findings: Discharges from DPHs and non‐DPHs both saw decreases in the four outcomes over the DSRIP period (2010‐2014). The difference‐in‐difference estimator (DD) for sepsis was only significant during two time periods, comparing 2010 with 2012 (DD: −2.90 percent, 95% CI: −5.08, −0.72 percent) and 2010 with 2014 (DD: −5.74, 95% CI: −8.76 percent, −2.72 percent); the DD estimator was not significant comparing 2010 with 2012 (DD: −1.30, 95% CI: −3.18 percent, 0.58 percent) or comparing 2010 with 2013 (DD: −3.05 percent, 95% CI: −6.50 percent, 0.40 percent). For CLABSI, we did not find any meaningful differences between DPHs and non‐DPHs across the four time periods. For HAPU and VTE, the only significant DD estimator compared 2014 with 2010. Conclusions: We did not find that DPHs participating in DSRIP outperformed non‐DPHs during the DSRIP program. Our results were robust to multiple sensitivity analyses. Given multiple concurrent inpatient safety initiatives, it was challenging to assign improvements over time periods to DSRIP. [ABSTRACT FROM AUTHOR]

Objective: To estimate the net effect of living in a gentrified neighborhood on probability of having serious psychological distress.Data Sources: We pooled 5 years of secondary data from the California Health Interview Survey (2011-2015) and focused on southern California residents.Study Design: We compared adults (n = 43 815) living in low-income and gentrified, low-income and not gentrified, middle- to high-income and upscaled, and middle- to high-income and not upscaled neighborhoods. We performed a probit regression to test whether living in a gentrified neighborhood increased residents' probabilities of having serious psychological distress in the past year and stratified analyses by neighborhood tenure, homeownership status, and low-income status. Instrumental variables estimation and propensity scores were applied to reduce bias arising from residential selection and simultaneity. An endogenous treatment effects model was also applied in sensitivity analyses.Data Collection/extraction Methods: Adults who completed the survey on their own and lived in urban neighborhoods with 500 or more residents were selected for analyses. Survey respondents who scored 13 and above on the Kessler 6 were categorized as having serious psychological distress in the past year. We used eight neighborhood change measures to classify respondents' neighborhoods.Principal Findings: Living in a gentrified and upscaled neighborhood was associated with increased likelihood of serious psychological distress relative to living in a low-income and not gentrified neighborhood. The average treatment effect was 0.0141 (standard error = 0.007), which indicates that the prevalence of serious psychological distress would have been 1.4 percentage points less if none of the respondents lived in gentrified neighborhoods. Gentrification appears to have a negative impact on the mental health of renters, low-income residents, and long-term residents. This effect was not observed among homeowners, higher-income residents, and recent residents.Conclusions: Gentrification levies mental health costs on financially vulnerable community members and can worsen mental health inequities. [ABSTRACT FROM AUTHOR]

Objective: To develop a nurse staffing prediction model and evaluate deviation from predicted nurse staffing as a contributor to patient outcomes.Data Sources: Secondary data collection conducted 2017-2018, using the California Office of Statewide Health Planning and Development and the California Perinatal Quality Care Collaborative databases. We included 276 054 infants born 2008-2016 and cared for in 99 California neonatal intensive care units (NICUs).Study Design: Repeated-measures observational study. We developed a nurse staffing prediction model using machine learning and hierarchical linear regression and then quantified deviation from predicted nurse staffing in relation to health care-associated infections, length of stay, and mortality using hierarchical logistic and linear regression.Data Collection Methods: We linked NICU-level nurse staffing and organizational data to patient-level risk factors and outcomes using unique identifiers for NICUs and patients.Principal Findings: An 11-factor prediction model explained 35 percent of the nurse staffing variation among NICUs. Higher-than-predicted nurse staffing was associated with decreased risk-adjusted odds of health care-associated infection (OR: 0.79, 95% CI: 0.63-0.98), but not with length of stay or mortality.Conclusions: Organizational and patient factors explain much of the variation in nurse staffing. Higher-than-predicted nurse staffing was associated with fewer infections. Prospective studies are needed to determine causality and to quantify the impact of staffing reforms on health outcomes. [ABSTRACT FROM AUTHOR]

Objective: To estimate the impact of opting-out from Medicare supervision requirements for certified registered nurse anesthetists (CRNAs) on anesthesiologists' work patterns.Data Sources/study Setting: Secondary data from two national surveys of anesthesiologists and the Area Health Resource File.Study Design: We use a matching difference-in-difference regression which contrasts the change in work patterns for anesthesiologists in California, which dropped supervision requirements, to the change for similar anesthesiologists. Key outcome variables include the number of weekly hours worked, the type of work done, and type of care delivery teams.Data Collection/extraction Methods: Self-reported national survey data drawn from members of the American Society of Anesthesiologists.Principal Findings: Anesthesiologists in California saw no change in time spent working or time spent supervising CRNAs. There was a decrease in direct care clinical work hours along with a shift in working more in intraoperative care, a decrease in postoperative care, and an increase in the percentage of cases supervising residents.Conclusions: Anesthesiologists had small but real responses to California's decisions to opt-out of the physician supervision requirement for CRNAs, doing more work in intraoperative care and less outside of the operating room. Total hours worked saw no change. [ABSTRACT FROM AUTHOR]

Objective: To examine whether hospitals are more likely to temporarily close their emergency departments (EDs) to ambulances (through ambulance diversions) if neighboring diverting hospitals are public vs private.Data Sources/study Setting: Ambulance diversion logs for California hospitals, discharge data, and hospital characteristics data from California's Office of Statewide Health Planning and Development and the American Hospital Association (2007).Study Design: We match public and private (nonprofit or for-profit) hospitals by distance and size. We use random-effects models examining diversion probability and timing of private hospitals following diversions by neighboring public vs matched private hospitals.Data Collection/extraction Methods: N/A.Principal Findings: Hospitals are 3.6 percent more likely to declare diversions if neighboring diverting hospitals are public vs private (P < 0.001). Hospitals declaring diversions have lower ED occupancy (P < 0.001) after neighboring public (vs private) hospitals divert. Hospitals have 4.2 percent shorter diversions if neighboring diverting hospitals are public vs private (P < 0.001). When the neighboring hospital ends its diversion first, hospitals terminate diversions 4.2 percent sooner if the neighboring hospital is public vs private (P = 0.022).Conclusions: Sample hospitals respond differently to diversions by neighboring public (vs private) hospitals, suggesting that these hospitals might be strategically declaring ambulance diversions to avoid treating low-paying patients served by public hospitals. [ABSTRACT FROM AUTHOR]

Objective: To assess hospital unit culture and clinician attitudes associated with varying rates of primary cesarean delivery.Data Sources/study Setting: Intrapartum nurses, midwives, and physicians recruited from 79 hospitals in California participating in efforts to reduce cesarean overuse.Study Design: Labor unit culture and clinician attitudes measured using a survey were linked to the California Maternal Data Center for birth outcomes and hospital covariates.Methods: Association with primary cesarean delivery rates was assessed using multivariate Poisson regression adjusted for hospital covariates.Principal Findings: 1718 respondents from 70 hospitals responded to the Labor Culture Survey. The "Unit Microculture" subscale was strongly associated with primary cesarean rate; the higher a unit scored on 8-items describing a culture supportive of vaginal birth (eg, nurses are encouraged to spend time in rooms with patients, and doulas are welcomed), the cesarean rate decreased by 41 percent (95% CI = -47 to -35 percent, P < 0.001). Discordant attitudes between nurses and physicians were associated with increased cesarean rates.Conclusions: Hospital unit culture, clinician attitudes, and consistency between professions are strongly associated with primary cesarean rates. Improvement efforts to reduce cesarean overuse must address culture of care as a key part of the change process. [ABSTRACT FROM AUTHOR]

Objective: To sample 40 physician organizations stratified on the basis of longitudinal cost of care measures for qualitative interviews in order to describe the range of care delivery structures and processes that are being deployed to influence the total costs of caring for patients.Data Sources: Three years of physician organization-level total cost of care data (n = 156 in California) from the Integrated Healthcare Association's value-based pay-for-performance program.Study Design: We fit total cost of care data using mixture and K-means clustering algorithms to segment the population of physician organizations into sampling strata based on 3-year cost trajectories (ie, cost curves).Principal Findings: A mixture of multivariate normal distributions can classify physician organization cost curves into clusters defined by total cost level, shape, and within-cluster variation. K-means clustering does not accommodate differing levels of within-cluster variation and resulted in more clusters being allocated to unstable cost curves. A mixture of regressions approach focuses overly on anomalous trajectories and is sensitive to model coding.Conclusions: Statistical clustering can be used to form sampling strata when longitudinal measures are of primary interest. Many clustering algorithms are available; the choice of the clustering algorithm can strongly impact the resulting strata because various algorithms focus on different aspects of the observed data. [ABSTRACT FROM AUTHOR]

Objective: To investigate the potential spillover effects of the Hospital Readmissions Reduction Program (HRRP) on readmissions for nontargeted conditions and patient populations. We examine HRRP effects on nontargeted conditions separately and on non-Medicare populations in Florida and California.Data Sources: From 2007-2013, 100 percent Medicare inpatient claims data, 2007-2013 State Inpatient Database (SID) for Florida, and 2007-2011 SID for California.Study Design: We conducted an interrupted time series analysis to estimate the change in 30-day all-cause unplanned readmission trends after the start of HRRP using logistic regression.Principal Findings: Hospitals with the largest reductions in targeted Medicare readmissions experienced higher reductions in nontargeted Medicare readmissions. Among nontargeted conditions, reductions were higher for neurology and surgery conditions than for the cardiovascular and cardiorespiratory conditions, which are clinically similar to the targeted conditions. For non-Medicare patients, readmission trends for targeted conditions in Florida and California did not change after HRRP.Conclusions: Our findings are consistent with positive spillover benefits associated with HRRP. The extent of these benefits, however, varies across condition and patient groups. The observed patterns suggest a complex response, including a role of nonfinancial factors, in driving lower readmissions. [ABSTRACT FROM AUTHOR]

Objective: To estimate the effect of out-of-pocket (OOP) cost on nonadherence to classes of cardiometabolic medications among patients with diabetes.Data Sources/setting: Electronic health records from a large, health care delivery system for 223,730 patients with diabetes prescribed 842,899 new cardiometabolic medications during 2006-2012.Study Design: Observational, new prescription cohort study of the effect of OOP cost on medication initiation and adherence.Data Collection: Adherence and OOP costs were based on pharmacy dispensing records and benefits.Principal Findings: Primary nonadherence (never dispensed) increased monotonically with OOP cost after adjusting for demographics, neighborhood socioeconomic status, Medicare, medical financial assistance, OOP maximum, deductibles, mail order pharmacy incentive and use, drug type, generic or brand, day's supply, and comorbidity index; 7 percent were never dispensed the new medication when OOP cost ≥$11, 5 percent with OOP cost of $1-$10, and 3 percent when the medication was free of charge (p < .0001). Higher OOP cost was also strongly associated with inadequate secondary adherence (≥20 percent of time without adequate medication). There was no clinically significant or consistent relationship between OOP costs and early nonpersistence (dispensed once, never refilled) or later stage nonpersistence (discontinued within 24 months).Conclusions: Cost-sharing may deter clinically vulnerable patients from initiating essential medications, undermining adherence and risk factor control. [ABSTRACT FROM AUTHOR]

Objective: Out-of-network emergency department (ED) use, or use that occurs outside the contracted network, may lead to increased care fragmentation and cost. We examined factors associated with out-of-network ED use among Medicaid beneficiaries.Data Sources and Study Setting: Enrollment, claims, and encounter data for adult Medi-Cal health plan members with 1+ ED visits and complete Medicaid eligibility during the study period from 2013 to 2014.Study Design: We analyzed the data to identify factors associated with out-of-network ED use classified by mode of arrival (ambulance vs. nonambulance).Data Extraction Methods: We extracted encounter, ambulance, and ED census data and linked them together based on ED visit date.Principal Findings: Of 11,143 ED visits, 6,808 (61.1 percent) were out-of-network. The number of hours the study ED was on ambulance diversion increased the odds of out-of-network visits for the 3,365 (30.2 percent) ED visits arriving by ambulance. For all visit types, assignment to a primary care clinic at the in-network hospital and having had any primary care visit during the study period decreased the odds of out-of-network ED care. Individuals were more likely to go out-of-network for ED care if they lived in neighborhoods containing out-of-network EDs.Conclusions: There are a number of factors related to out-of-network ED use, including the proximity and density of out-of-network EDs, race and ethnicity, a prior history of out-of-network ED use, and individuals' connection to primary care. EDs that serve Medicaid beneficiaries may need to explore alternative sites and modalities of care as alternatives to the ED, and consider their ability to absorb large numbers of out-of-network visits given already limited capacity. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects on hospitals of early California actions to expand insurance coverage for low-income uninsured adults after passage of the Affordable Care Act.Data Sources/study Setting: Data from the California Office of Statewide Health Planning and Development and the California Department of Health were merged with U.S. census data for 294 short-term general hospitals during the period 2009-2012.Study Design: A difference-in-difference analysis was conducted with hospitals in counties that did not implement insurance expansions used as a comparison group. Variables examined included payer mix, costs of unreimbursed care, and hospital operating margin. Sensitivity analyses were conducted as well as a triple difference analysis. Effects were estimated for hospitals overall and by ownership type.Principal Findings: California insurance expansions primarily benefited for-profit hospitals, with these facilities experiencing significant decreases in self-pay patients, increases in county-covered patients, and reductions in charity care. Most models yielded no significant change in payer mix and conflicting changes in unreimbursed care for nonprofit hospitals.Conclusions: California hospitals that treated the most uninsured prior to insurance expansions did not as a group experience substantial benefit in terms of reduced uninsured burden or better financial performance after program expansions occurred. [ABSTRACT FROM AUTHOR]

Objective: To pilot public health interventions at women potentially interested in maternity care via campaigns on social media (Twitter), social networks (Facebook), and online search engines (Google Search).Data Sources/study Setting: Primary data from Twitter, Facebook, and Google Search on users of these platforms in Los Angeles between March and July 2014.Study Design: Observational study measuring the responses of targeted users of Twitter, Facebook, and Google Search exposed to our sponsored messages soliciting them to start an engagement process by clicking through to a study website containing information on maternity care quality information for the Los Angeles market.Principal Findings: Campaigns reached a little more than 140,000 consumers each day across the three platforms, with a little more than 400 engagements each day. Facebook and Google search had broader reach, better engagement rates, and lower costs than Twitter. Costs to reach 1,000 targeted users were approximately in the same range as less well-targeted radio and TV advertisements, while initial engagements-a user clicking through an advertisement-cost less than $1 each.Conclusions: Our results suggest that commercially available online advertising platforms in wide use by other industries could play a role in targeted public health interventions. [ABSTRACT FROM AUTHOR]

Objective: To assess the coverage effects of California's 2011 Low-Income Health Program (LIHP), enacted as an "early expansion" under the Affordable Care Act (ACA), and to demonstrate the feasibility of using Census data to measure county-level coverage changes.Data Sources/study Setting: 2008-2012 American Community Survey (ACS). The sample contained California adults ages 19-64 years (n = 237,876) and children 0-18 years (n = 113,159) with incomes below 200 percent of the federal poverty level.Study Design: Differences-in-differences analysis comparing public coverage, private insurance, and the uninsured rate in counties that expanded the LIHP in 2011 versus California counties not expanding during this time. Additional analyses tested for heterogeneous impacts of the LIHP and spillover effects on children.Principal Findings: Compared to nonexpansion counties, public coverage for adults increased by 1.8 percentage points (p = .02) in expanding counties, while the uninsured rate declined by 2.1 percentage points (p = .01). There was no significant change in private coverage. Public coverage gains were largest for Latinos and those with limited English proficiency. The expansion produced a positive spillover effect on children's Medicaid enrollment.Conclusions: California's 2011 expansion produced significant increases in public coverage for low-income individuals, particularly Latinos. Substate coverage analyses with the ACS can add valuable detail to future assessments of the ACA. [ABSTRACT FROM AUTHOR]

Objective: To characterize the health risk of enrollees in California's state-based insurance marketplace (Covered California) by metal tier, region, month of enrollment, and plan.Data Source/study Setting: 2014 Open-enrollment data from Covered California linked with 2012 hospitalization and emergency department (ED) visit records from statewide all-payer administrative databases.Data Collection/extraction Methods: Chronic Illness and Disability Payment System (CDPS) health risk scores derived from an individual's age and sex from the enrollment file and the diagnoses captured in the hospitalization and ED records. CDPS scores were standardized by setting the average to 1.00.Principal Findings: Among the 1,286,089 enrollees, 120,573 (9.4 percent) had at least one ED visit and/or a hospitalization in 2012. Higher risk enrollees chose plans with greater actuarial value. The standardized CDPS health risk score was 11 percent higher in the first month of enrollment (1.08; 99 percent CI: 1.07-1.09) than the last month (0.97; 99 percent CI: 0.97-0.97). Four of the 12 plans enrolled 91 percent of individuals; their average health risk scores were each within 3 percent of the marketplace's statewide average.Conclusions: Providing health plans with a means to assess the health risk of their year 1 enrollees allowed them to anticipate whether they would receive or contribute payments to a risk-adjustment pool. After receiving these findings as a part of their negotiations with Covered California, health plans covering the majority of enrollees decreased their initially proposed 2015 rates, saving consumers tens of millions of dollars in potential premiums. [ABSTRACT FROM AUTHOR]

Objective To determine whether, following implementation of California's minimum nurse staffing legislation, changes in acuity-adjusted nurse staffing and quality of care in California hospitals outpaced similar changes in hospitals in comparison states without such regulations. Data Sources/Study Setting Data from the American Hospital Association Annual Survey of Hospitals, the California Office of Statewide Health Planning and Development, the Hospital Cost Report Information System, and the Agency for Healthcare Research and Quality's Health Care Cost and Utilization Project's State Inpatient Databases from 2000 to 2006. Study Design We grouped hospitals into quartiles based on their preregulation staffing levels and used a difference-in-difference approach to compare changes in staffing and in quality of care in California hospitals to changes over the same time period in hospitals in 12 comparison states without minimum staffing legislation. Data Collection/Extraction Methods We merged data from the above data sources to obtain measures of nurse staffing and quality of care. We used Agency for Healthcare Research and Quality's Patient Safety Indicators to measure quality. Principal Findings With few exceptions, California hospitals increased nurse staffing levels over time significantly more than did comparison state hospitals. Failure to rescue decreased significantly more in some California hospitals, and infections due to medical care increased significantly more in some California hospitals than in comparison state hospitals. There were no statistically significant changes in either respiratory failure or postoperative sepsis. Conclusions Following implementation of California's minimum nurse staffing legislation, nurse staffing in California increased significantly more than it did in comparison states' hospitals, but the extent of the increases depended upon preregulation staffing levels; there were mixed effects on quality. [ABSTRACT FROM AUTHOR]

Objective To analyze the impact of hospital mergers on treatment intensity and health outcomes. Data Hospital inpatient data from California for 1990 through 2006, encompassing 40 mergers. Study Design I used a geographic-based IV approach to determine the effect of a zip code's exposure to a merger. The merged facility's market share represents exposure, instrumented with combined premerge shares. Additional specifications include Herfindahl Index ( HHI), instrumented with predicted change in HHI. Results The primary specification results indicate that merger completion is associated with a 3.7 percent increase in the utilization of bypass surgery and angioplasty and a 1.7 percent increase in inpatient mortality above averages in 2000 for the average zip code. Isolating the competition mechanism mutes the treatment intensity result slightly, but it more than doubles the merger exposure effect on inpatient mortality to a 3.9 percent increase. The competition mechanism is associated with a sizeable increase in number of procedures. Conclusions Unlike previous studies, this analysis finds that hospital mergers are associated with increased treatment intensity and higher inpatient mortality rates among heart disease patients. Access to additional outcome measures such as 30-day mortality and readmission rates might shed additional light on whether the relationship between these outcomes is causal. [ABSTRACT FROM AUTHOR]

To evaluate the effectiveness of different approaches to outreach on public health insurance enrollment in 25 California counties with a Children's Health Initiative. Administrative enrollment databases. The use of eight enrollment strategies were identified in each quarter from 2001 to 2007 for each of 25 counties (county quarter). Strategies were categorized as either technology or nontechnology. New enrollments were obtained for Medi-Cal, Healthy Families, and Healthy Kids. Bivariate and multivariate analyses assessed the link between each strategy and new enrollments rates of children. Methods Surveys of key informants determined whether a specific outreach strategy was used in each quarter. These were linked to new enrollments in each county quarter. Between 2001 and 2007, enrollment grew in all three children's health programs. We controlled for the effects of counties, seasons, and county-specific child poverty rates. There was an increase in enrollment rates of 11 percent in periods when technology-based systems were in use compared with when these approaches were inactive. Non-technology-based approaches, including school-linked approaches, yielded a 12 percent increase in new enrollments rates. Deploying seven to eight strategies yielded 54 percent more new enrollments per 10,000 children compared with periods with none of the specific strategies. National health care reform provides new opportunities to expand coverage to millions of Americans. An investment in technology-based enrollment systems will maximize new enrollments, particularly into Medicaid; nontechnological approaches may help identify harder-to-reach populations. Moreover, incorporating several strategies, whether phased in or implemented simultaneously, will enhance enrollments. [ABSTRACT FROM AUTHOR]

Objective. Little is known about how cancer physicians communicate with limited English proficient (LEP) patients. We studied physician-reported use and availability of interpreters. Data Sources. A 2004 survey was fielded among physicians identified by a population-based sample of breast cancer patients. Three hundred and forty-eight physicians completed mailed surveys (response rate: 77 percent) regarding the structure and organization of care. Study Design and Settings. We used logistic regression to analyze use and availability of interpreters. Principal Findings. Most physicians reported treating LEP patients. Among physicians using interpreters within the last 12 months, 42 percent reported using trained medical interpreters, 21 percent telephone interpreter services, and 75 percent reported using untrained interpreters to communicate with LEP patients. Only one-third of physicians reported good availability of trained medical interpreters or telephone interpreter services when needed. Compared with HMO physicians, physicians in solo practice and single-specialty medical groups were less likely to report using trained medical interpreters or telephone interpreter services, and they were less likely to report good availability of these services. Conclusions. There were important practice setting differences predicting use and availability of trained medical interpreters and telephone interpretation services. These findings may have troubling implications for effective physician–patient communication critically needed during cancer treatment. [ABSTRACT FROM AUTHOR]

Objective. To determine whether variation in the representation of minority physicians across geographical areas in California affects the location decisions of minority physicians. Data Sources. We analyzed data on 9,806 residents and 53,606 patient-care physicians from the 1997–2003 American Medical Association Masterfiles for California along with data from the California Department of Finance, RAND, and other sources. Study Design. We estimated departure models using linear probability models and destination models using conditional logit. Each model controlled for physician and county characteristics. Parameters of interest include the interactions of physician race/ethnicity with area-level minority physician representation for the corresponding race/ethnicity. Principal Findings. Departure models show that black and Hispanic physicians are more likely to remain in an area as the level of representation of physicians from their respective groups worsens. The destination models show that black, Asian, and Hispanic physicians tend to move to areas where the level of representation is similar to that of their previous location. Conclusions. Black and Hispanic physicians are influenced by the level of representation of physicians from their respective groups in their location decisions and tend to locate where needed. [ABSTRACT FROM AUTHOR]

Objective. To study the impact of the number of choices and age on measures of performance in choosing a Medicare prescription drug plan. Data Source/Study Setting. One hundred ninty-two healthy individuals age 18 and older, half age 65 or older, in Claremont, California. Study Design. Participants were randomly assigned to 3, 10, or 20 hypothetical drug plans and asked four factual questions. Statistical models controlled for experimental group, age, gender, race, education, income, marital status, and health status. Primary Findings. Older age and greater number of plans were significantly associated with fewer correct answers. Although older adults were less likely to identify the plan that minimized total annual cost, they were more likely to state that they were “very confident” they chose the correct plan. Conclusions. The results raise concerns about the difficulties that older adults may have in navigating the wide range of drug plan choices available. [ABSTRACT FROM AUTHOR]

Objective. To analyze corporate governance arrangements and quality and financial performance outcomes among large multi-facility nursing home corporations (chains) that pursue stakeholder value (profit maximization) strategies. Study Design. To establish a foundation of knowledge about the focal phenomenon and processes, we conducted an historical (1993–2005) case study of one of the largest chains (Sun Helathcare Inc.) that triangulated qualitative and quantitative data sources. Data Sources. Two main sets of information were compared: (1) corporate sources including Sun's Security Exchange Commission (SEC) Form 10-K annual reports, industry financial reports, and the business press; and (2) external sources including, legal documents, press reports, and publicly available California facility cost reports and quality data. Principal Findings. Shareholder value was pursued at Sun through three inter-linked strategies: (1) rapid growth through debt-financed mergers; (2) labor cost constraint through low nurse staffing levels; and (3) a model of corporate governance that views sanctions for fraud and poor quality as a cost of business. Conclusions. Study findings and evidence from other large nursing home chains underscore calls from the Institute of Medicine and other bodies for extended oversight of the corporate governance and performance of large nursing home chains. [ABSTRACT FROM AUTHOR]

Objective. To assess the effect of hospital competition and health maintenance organization (HMO) penetration on mortality after hospitalization for six medical conditions in California. Data Source. Linked hospital discharge and vital statistics data for short-term general hospitals in California in the period 1994–1999. The study sample included adult patients hospitalized for one of the following conditions: acute myocardial infarction ( N=227,446), hip fracture ( N=129,944), stroke ( N=237,248), gastrointestinal hemorrhage (GIH, N=216,443), congestive heart failure (CHF, N=355,613), and diabetes ( N=154,837). Study Design. The outcome variable was 30-day mortality. We estimated multivariate logistic regression models for each study condition with hospital competition, HMO penetration, hospital characteristics, and patient severity measures as explanatory variables. Principal Findings. Higher hospital competition was associated with lower 30-day mortality for three to five of the six study conditions, depending on the choice of competition measure, and this finding was robust to a variety of sensitivity analyses. Higher HMO penetration was associated with lower mortality for GIH and CHF. Conclusions. Hospitals that faced more competition and hospitals in market areas with higher HMO penetration provided higher quality of care for adult patients with medical conditions in California. Studies using linked hospital discharge and vital statistics data from other states should be conducted to determine whether these findings are generalizable. [ABSTRACT FROM AUTHOR]

An important aspect of the mandate assessments requested by the California legislature is a review of the scientific and medical literature on the medical effectiveness of the proposed health insurance benefit mandate. Although such a review bears many similarities to effectiveness reviews that might be undertaken for publication as research studies, several important differences arise from the requirements of the California legislation. Our reviews are intended to assist the legislators in deciding whether to support a specific mandate to modify health insurance benefits in a particular way. Thus, our assessments focus on how the scientific literature bears on the proposed mandate, which may involve a complicated chain of potential effects leading from altered coverage to ultimate impact on health. Evidence may be available for only some of the links in the chain. Furthermore, not all the evidence may be directly applicable to the diverse population of California or the subpopulation affected by the mandate. The mandate reviews, including the medical effectiveness analyses, may be used in a potentially contentious decision making setting. The legislative calendar requires that they need to be timely, yet they must be as valid, credible, and based on the best information available as possible. The focus on applicability also implies the need for informed, technical decisions concerning the relevance of the articles for the report, and these decisions need to be made as transparent as possible. These goals and constraints yield an approach that differs somewhat from an investigator-initiated review of the literature. [ABSTRACT FROM AUTHOR]

The California Health Benefits Review Program (CHBRP)—established in 2003 in response to new state legislation aimed at enhancing the evaluation of potential changes in health benefit packages—represents a unique marriage of academic analysis and real-time legislative decision making. CHBRP is based within the University of California (UC) Office of the President and provides analyses to the legislature within a 60-day timeframe on the potential consequences of specific benefit changes under consideration as part of legislative mandates. The consequences examined include current known medical effectiveness of the services for which coverage is to be mandated as well as potential costs and impact on public health considerations associated with the mandate. Teams throughout the University system specialize in analyzing medical effectiveness, costs, and public health impacts and work with a statewide faculty task force and a private actuarial firm to generate literature reviews and analyses in response to legislative requests. These teams work on multiple requests simultaneously, all within the constraints of the legislative calendar. In its first 2 years, CHBRP generated 22 such analyses. [ABSTRACT FROM AUTHOR]

Objective. To summarize for the California Legislature the evidence on the medical effectiveness of pediatric asthma self-management training and education (PASMTE), including the use of peak flow meters, spacers, and nebulizers and the impact that mandated coverage of these services and devices under Assembly Bill (AB) 2185 would have on total health care expenditures, monthly premiums, health services utilization, and the public's health. Medical Effectiveness Findings. The review of the literature finds that PASMTE is medically effective and has favorable effects on the health of children with symptomatic asthma, as well as reduces asthma-related emergency room visits and hospitalizations. There was inadequate evidence to assess the effectiveness of the three medical devices independently of PASMTE. Cost and Utilization Findings. One-hundred percent of children in health maintenance organization (HMO) plans in California are already covered for PASMTE, with fewer having coverage for the specific medical devices. However, despite full coverage of PASMTE in HMOs, these services are underutilized. We expect that the enactment of AB 2185 would increase utilization of PASMTE among children who are currently covered by 10 percent as a result of increased awareness of current coverage by all HMOs and increased awareness of the importance of these services. We estimate that this increased utilization by children who are already covered may result in a total statewide premiums increase of $170,000 or 0.006 percent, equal to one to two cents per member per month (PMPM). Public Health Findings. It is estimated that the public health impact of the mandate, as a result of new utilization of PASMTE by 10 percent of children who are already covered, would reduce the number of school days missed because of asthma per year by 158,000; the number of children reporting restricted activity days by 6,020; the number of emergency department visits by 350; and the number of hospitalizations by 1,105. Legislative Action. AB 2185 passed the legislature after being amended six times. The bill as it was signed into law did not mandate coverage for PASMTE, as all HMOs in California presently reported covering these services. However, the bill retained the mandate for coverage of the three medical devices, as their coverage was not as universal across health plans. [ABSTRACT FROM AUTHOR]

Objective. To assess the impact of changes in relative health maintenance organization (HMO) penetration on changes in the physician-to-population ratio in California counties when changes in the economic conditions in California counties relative to the U.S. average are taken into account. Data Sources. Data on physicians who practiced in California at any time from 1988 to 1998 were obtained from the AMA Masterfile. The analysis was restricted to active, patient care physicians, excluding medical residents. Data on other covariates in the model were obtained from the Bureau of Economic Analysis, InterStudy, the Area Resource File, and the California state government. Data were merged using county FIPS codes. Study Design. Changes in the physician-to-population ratio in California counties include the effects of both intrastate migration and interstate migration. A reduced-form model was estimated using the Arellano–Bond dynamic panel estimator. Economic conditions in California relative to the U.S. were measured as the ratio of county-level real per capita income to national-level real per capita income. Relative HMO penetration in California was measured as the ratio of county-level HMO penetration to HMO penetration in the U.S. relative HMO penetration was instrumented using five identifying variables to address potential endogeneity. Omitted-variable bias was controlled for by first differencing the model. The model also incorporated eight other covariates that may be associated with the demand for physicians: the percentage of the population enrolled in Medicaid, beds in short-term hospitals per 100,000 population, the percentage of the population that is black, the percentage of the population that is Hispanic, the percentage of the population that is Asian, the percentage of the population that is below age 18, the percentage of the population that is aged 65 and older, and the percentage of the population that are new legal immigrants in a given year. All of the above variables were lagged one period. The lagged physician-to-population ratio was also included to control for the supply of physicians. Separate equations were estimated for primary care physicians and specialist physicians. Principal Findings. Changes in lagged relative HMO penetration are negatively associated with changes in specialist physicians per 100,000 population. However, this effect of HMO penetration is attenuated and at times reversed in areas where the magnitude of the difference in relative economic conditions is sufficiently large. We did not find any statistically significant effects for primary care physicians. Conclusions. Consistent with prior studies, we find that changes in physician supply are associated with changes in relative HMO penetration. Relative economic conditions are an important moderator of the effect of changes in relative HMO penetration on physician migration. [ABSTRACT FROM AUTHOR]

Objective. To further understand barriers to care as experienced by health care consumers, and to demonstrate the importance of conjoining qualitative and quantitative health services research. Data Sources. Transcripts from focus groups conducted in San Diego with English- and Spanish-speaking parents of children with special health care needs. Study Design. Participants were asked about the barriers to care they had experienced or perceived, and their strategies for overcoming these barriers. Using elementary anthropological discourse analysis techniques, a process-based conceptual model of the parent experience was devised. Principal Findings. The analysis revealed a parent-motivated model of barriers to care that enriched our understanding of quantitative findings regarding the population from which the focus group sample was drawn. Parent-identified barriers were grouped into the following six temporally and spatially sequenced categories: necessary skills and prerequisites for gaining access to the system; realizing access once it is gained; front office experiences; interactions with physicians; system arbitrariness and fragmentation; outcomes that affect future interaction with the system. Key to the successful navigation of the system was parents' functional biomedical acculturation; this construct likens the biomedical health services system to a cultural system within which all parents/patients must learn to function competently. Conclusions. Qualitative analysis of focus group data enabled a deeper understanding of barriers to care—one that went beyond the traditional association of marker variables with poor outcomes (“what”) to reveal an understanding of the processes by which parents experience the health care system (“how,”“why”) and by which disparities may arise. Development of such process-oriented models furthers the provision of patient-centered care and the creation of interventions, programs, and curricula to enhance such care. Qualitative discourse analysis, for example using this project's widely applicable protocol for generating experientially based models, can enhance our knowledge of the parent/patient experience and aid in the development of more powerful conceptualizations of key health care constructs. [ABSTRACT FROM AUTHOR]

Objective. To compare the extent with which child-only and family coverage (child and parent insured) ensure health care access and use for low income children in California and discuss the policy implications of extending the State Children's Health Insurance Program (California's Healthy Families) to uninsured parents of child enrollees. Data Sources/Setting. We used secondary data from the 2001 California Health Interview Survey (CHIS), a representative telephone survey. Study Design. We conducted a cross-sectional study of 5,521 public health insurance–eligible children and adolescents and their parents to examine the effects of insurance (family coverage, child-only coverage, and no coverage) on measures of health care access and utilization including emergency room visits and hospitalizations. Data Collection. We linked the CHIS adult, child, and adolescent datasets, including the adolescent insurance supplement. Findings. Among the sampled children, 13 percent were uninsured as were 22 percent of their parents. Children without insurance coverage were more likely than children with child-only coverage to lack a usual source of care and to have decreased use of health care. Children with child-only coverage fared worse than those with family coverage on almost every access indicator, but service utilization was comparable. Conclusions. While extending public benefits to parents of children eligible for Healthy Families may not improve child health care utilization beyond the gains that would be obtained by exclusively insuring the children, family coverage would likely improve access to a regular source of care and private sector providers, and reduce perceived discrimination and breaks in coverage. These advantages should be considered by states that are weighing the benefits of expanding health insurance to parents. [ABSTRACT FROM AUTHOR]

Objective. To describe the insurance status of workers at small businesses, and to describe the status of uninsured persons by the employment characteristics (employment status, firm size, and whether the employer offers insurance) of the head of household. Data Sources. Data from the March and February 2001 Current Population Survey, and a survey of 2,830 small businesses in San Diego County conducted in 2001. Study Design. The survey of small businesses was undertaken as part of a project testing the response of employers to offers of subsidized coverage. Employers were asked whether they offered insurance, and about the insurance status of their employees. The merged February–March 2001 CPS was used to identify the employment status, firm size, and employer-offering status for uninsured persons in the U.S. Data Collection. Telephone interviews with small businesses in San Diego County. Principal Findings. Only 21 percent of the uninsured in the U.S. are full-time employees (or their dependents) in small businesses (<100 employees) that do not offer insurance. The employment status of the uninsured is heterogeneous: many work for large employers, small employers who do offer insurance, or are self-employed, part-time workers, or have no workers in the household. Although there are many small businesses in San Diego that do not offer coverage, most of them have very few uninsured workers. Over 50 percent of businesses that do not offer coverage have either zero or one uninsured worker. There are very few small businesses that do not offer coverage and that have substantial numbers of uninsured workers. These businesses are not quite as rare as a needle in a haystack, but they are very difficult to find. Conclusions. If all small businesses that do not offer insurance now could be persuaded to start offering coverage, and if all the full-time workers (and their dependents) in those businesses accepted insurance, the number of uninsured would decline by 21 percent—a significant decline, but leaving 80 percent of the problem untouched. If the prime target for programs of subsidized insurance are small businesses that do not offer coverage now and that have substantial numbers of uninsured workers, the target is very small. [ABSTRACT FROM AUTHOR]

To estimate the effect of changes in premiums for individual insurance on decisions to purchase individual insurance and how this price response varies among subgroups of the population. Survey responses from the Current Population Survey ( ), the Survey of Income and Program Participation ( ), the National Health Interview Survey ( ), and data about premiums and plans offered in the individual insurance market in California, 1996–2001. A logit model was used to estimate the decisions to purchase individual insurance by families without access to group insurance. This was modeled as a function of premiums, controlling for family characteristics and other characteristics of the market. A multinomial model was used to estimate the choice between group coverage, individual coverage, and remaining uninsured for workers offered group coverage as a function of premiums for individual insurance and out-of-pocket costs of group coverage. The elasticity of demand for individual insurance by those without access to group insurance is about −.2 to −.4, as has been found in earlier studies. However, there are substantial differences in price responses among subgroups with low-income, young, and self-employed families showing the greatest response. Among workers offered group insurance, a decrease in individual premiums has very small effects on the choice to purchase individual coverage versus group coverage. Subsidy programs may make insurance more affordable for some families, but even sizeable subsidies are unlikely to solve the problem of the uninsured. We do not find evidence that subsidies to individual insurance will produce an unraveling of the employer-based health insurance system. [ABSTRACT FROM AUTHOR]

Objective. To assess revascularization and mortality after acute myocardial infarction (AMI) for all Medicare patients in fee-for-service (FFS) and health maintenance organization (HMO) settings in California. Data Sources/Study Setting. Hospital discharge abstract and death certificate data linked with Medicare enrollment files for patients aged 65 and over with Medicare coverage (69,040) discharged from a California-licensed hospital in 1994–1996. Study Design. Risk-adjusted results were assessed for HMOs and FFS, as well as for FFS beneficiaries from areas served by each plan. Data Collection/Extraction Methods. Risk models were based on all sampled patients. The HMO patients were aggregated into 17 pseudoplans: 5 individual plans, 4 large plans split geographically (10 observations), and 2 “pseudoplans” of small HMOs. Observed versus expected 30-day mortality rates, lengths-of-stay (LOS) during the index hospitalization and any transfers, revascularization (coronary artery bypass graft [CABG] surgery and/or percutaneous transluminal coronary angioplasty [PTCA]) during the index hospitalization or 30 days after admission, were calculated for each pseudoplan. Principal Findings. Risk-adjusted death rate was slightly higher in FFS than in HMO settings (p<.01 with one risk adjustment model, n.s. with another). Three pseudoplans had significantly (p<.01) better than expected mortality rates. One pseudoplan was significantly worse (p<.05) with one risk adjustment model but not the other. The LOS and revascularization rates varied widely, but were not associated with outcomes. Plans with among the best results had the lowest LOS and revascularization rates. These pseudoplans were less likely to have their patients initially admitted to a hospital with revascularization capability, but the hospitals they used had higher CABG volumes. Even if CABG facilities were available during the index admission, in these plans with better than expected mortality rates, revascularization was often postponed or carried out elsewhere. Conclusions. For Medicare patients having an AMI in the mid-1990s in California, risk-adjusted outcomes were no different, or slightly better on average, for those in HMOs than in FFS. Not all plans performed equally well, so understanding what leads to differences in quality is more important than simple comparisons of HMOs versus FFS. [ABSTRACT FROM AUTHOR]

Objective: To compare and contrast methods and findings from two approaches to valuation used in the same survey: measurement of "attitudes" using simple rankings and ratings versus measurement of "preferences" using conjoint analysis. Conjoint analysis, a stated preference method, involves comparing scenarios composed of attribute descriptions by ranking, rating, or choosing scenarios. We explore possible explanations for our findings using focus groups conducted after the quantitative survey.Methods: A self-administered survey, measuring attitudes and preferences for HIV tests, was conducted at HIV testing sites in San Francisco in 1999-2000 (n = 365, response rate = 96 percent). Attitudes were measured and analyzed using standard approaches. Conjoint analysis scenarios were developed using a fractional factorial design and results analyzed using random effects probit models. We examined how the results using the two approaches were both similar and different.Results: We found that "attitudes" and "preferences" were generally consistent, but there were some important differences. Although rankings based on the attitude and conjoint analysis surveys were similar, closer examination revealed important differences in how respondents valued price and attributes with "halo" effects, variation in how attribute levels were valued, and apparent differences in decision-making processes.Conclusions: To our knowledge, this is the first study to compare attitude surveys and conjoint analysis surveys and to explore the meaning of the results using post-hoc focus groups. Although the overall findings for attitudes and preferences were similar, the two approaches resulted in some different conclusions. Health researchers should consider the advantages and limitations of both methods when determining how to measure what people value. [ABSTRACT FROM AUTHOR]

Objective: To examine preferences for HIV test methods using conjoint analysis, a method used to measure economic preferences (utilities).Data Sources: Self-administered surveys at four publicly funded HIV testing locations in San Francisco, California, between November 1999 and February 2000 (n = 365, 96 percent response rate).Study Design: We defined six important attributes of HIV tests and their levels (location, price, ease of collection, timeliness/accuracy, privacy/anonymity, and counseling). A fractional factorial design was used to develop scenarios that consisted of combinations of attribute levels. Respondents were asked 11 questions about whether they would choose "Test A or B" based on these scenarios.Data Analysis: We used random effects probit models to estimate utilities for testing attributes. Since price was included as an attribute, we were able to estimate willingness to pay, which provides a standardized measure for use in economic evaluations. We used extensive analyses to examine the reliability and validity of the results, including analyses of: (1) preference consistency, (2) willingness to trade among attributes, and (3) consistency with theoretical predictions.Principal Findings: Respondents most preferred tests that were accurate/timely and private/anonymous, whereas they had relatively lower preferences for in-person counseling. Respondents were willing to pay an additional $35 for immediate, highly accurate results; however, they had a strong disutility for receiving immediate but less accurate results. By using conjoint analysis to analyze new combinations of attributes, we found that respondents would most prefer instant, highly accurate home tests, even though they are not currently available in the U.S. Respondents were willing to pay $39 for a highly accurate, instant home test.Conclusions: The method of conjoint analysis enabled us to estimate utilities for specific attributes of HIV tests as well as the overall utility obtained from various HIV tests, including tests that are under consideration but not yet available. Conjoint analysis offers an approach that can be useful for measuring and understanding the value of other health care goods, services, and interventions. [ABSTRACT FROM AUTHOR]

Objective: To predict the true cost of developing and maintaining an electronic immunization registry, and to set the framework for developing future cost-effective and cost-benefit analysis.Data Sources/study Setting: Primary data collected at three immunization registries located in California, accounting for 90 percent of all immunization records in registries in the state during the study period.Study Design: A parametric cost analysis compared registry development and maintenance expenditures to registry performance requirements.Data Collection/extraction Methods: Data were collected at each registry through interviews, reviews of expenditure records, technical accomplishments development schedules, and immunization coverage rates.Principal Findings: The cost of building immunization registries is predictable and independent of the hardware/software combination employed. The effort requires four man-years of technical effort or approximately $250,000 in 1998 dollars. Costs for maintaining a registry were approximately $5,100 per end user per three-year period.Conclusions: There is a predictable cost structure for both developing and maintaining immunization registries. The cost structure can be used as a framework for examining the cost-effectiveness and cost-benefits of registries. The greatest factor effecting improvement in coverage rates was ongoing, user-based administrative investment. [ABSTRACT FROM AUTHOR]

Objective: To investigate the impact of quality information on the willingness of consumers to enroll in health plans that restrict provider access.Data Sources and Setting: A survey administered to respondents between the ages of 25 and 64 in the West Los Angeles area with private health insurance.Study Design: An experimental approach is used to measure the effect of variation in provider network features and information about the quality of network physicians on hypothetical plan choices. Conditional logit models are used to analyze the experimental choice data. Next, choice model parameter estimates are used to simulate the impact of changes in plan features on the market shares of competing health plans and to calculate the quality level required to make consumers indifferent to changes in provider access.Principal Findings: The presence of quality information reduced the importance of provider network features in plan choices as hypothesized. However, there were not statistically meaningful differences by type of quality measure (i.e., consumer assessed versus expert assessed). The results imply that large quality differences are required to make consumers indifferent to changes in provider access. The impact of quality on plan choices depended more on the particular measure and less on the type of measure. Quality ratings based on the proportion of survey respondents "extremely satisfied with results of care" had the greatest impact on plan choice while the proportion of network doctors "affiliated with university medical centers" had the least. Other consumer and expert assessed measures had more comparable effects.Conclusions: Overall the results provide empirical evidence that consumers are willing to trade high quality for restrictions on provider access. This willingness to trade implies that relatively small plans that place restrictions on provider access can successfully compete against less restrictive plans when they can demonstrate high quality. However, the results of this study suggest that in many cases, the level of quality required for consumers to accept access restrictions may be so high as to be unattainable. The results provide empirical support for the current focus of decision support efforts on consumer assessed quality measures. At the same time, however, the results suggest that consumers would also value quality measures based on expert assessments. This finding is relevant given the lack of comparative quality information based on expert judgment and research suggesting that consumers have apprehensions about their ability to meaningfully interpret performance-based quality measures. [ABSTRACT FROM AUTHOR]