Hospital Revisits Within 30 Days After Conventional and Robotically Assisted Hysterectomy.

OBJECTIVES: To compare the rates of hospital readmissions, emergency department, and outpatient clinic visits after discharge for robotically assisted (RA) versus nonrobotic hysterectomy in women age 30 or more with nonmalignant conditions. DATA SOURCES: Discharges for 2011 for 8 states (CA, FL, GA, IA, MO, NE, NY, TN) (>86,000 inpatient hysterectomies) were drawn from the statewide databases of the Healthcare Cost and Utilization Project. Data from 4 of these states were used to study revisits after 29,000 outpatient hysterectomies. METHODS: Matched pairs of patients were constructed with propensity scores derived from each patient's age group, severity of illness, insurance coverage, and type of procedure. Both the full set of revisits and a set limited to diagnoses for revisits judged in other research to be related to the initial surgery (about 70% of all revisits) were analyzed. The analyses were repeated with an instrumental variables regression design. KEY RESULTS: Using the propensity score matched pairs, revisits, and specifically readmissions, after inpatient hysterectomy were greater for RA versus non-RA patients (relative risk of readmission=124%, P<0.01). Similar results were found for readmissions after outpatient hysterectomy, and readmissions after inpatient hysterectomy for the restricted set of related revisits. In the method with instrumental variables, RA was associated with an increase of 32% in the likelihood of any revisit (P<0.01). CONCLUSIONS: Using 2 different methods to control for selection, this study found higher rates of revisits among women undergoing RA versus non-RA hysterectomy for benign conditions. While selection bias cannot be ruled out completely in an observational study, the study supports broader use of revisits for analyses of outcomes of hysterectomy.

Predicting inpatient hospital payments in the United States: a retrospective analysis.

BACKGROUND: The Affordable Care Act (ACA) has increased rates of public and private health insurance in the United States. Increasing coverage could raise hospital revenue and reduce the need to shift costs to insured patients. The consequences of ACA on hospital revenues could be examined if payments were known for most hospitals in the United States. Actual payment data are considered confidential, however, and only charges are widely available. Payment-to-charge ratios (PCRs), which convert hospital charges to an estimated payment, have been estimated for hospitals in 10 states. Here we evaluated whether PCRs can be predicted for hospitals in states that do not provide detailed financial data. METHODS: We predicted PCRs for 5 payer categories for over 1,000 community hospitals in 10 states as a function of state, market, hospital, and patient characteristics. Data sources included the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases, HCUP Hospital Market Structure file, Medicare Provider of Service file, and state information from several sources. We performed out-of-sample prediction to determine the magnitude of prediction errors by payer category. RESULTS: Many individual, hospital, and state factors were significant predictors of PCRs. Root mean squared error of prediction ranged from 32 to over 100 % of the mean and varied considerably by which states were included or predicted. The cost-to-charge ratio (CCR) was highly correlated with PCRs for Medicare, Medicaid, and private insurance but not for self-pay or other insurance categories. CONCLUSIONS: Inpatient payments can be estimated with modest accuracy for community hospital stays funded by Medicare, Medicaid, and private insurance. They improve upon CCRs by allowing separate estimation by payer type. PCRs are currently the only approach to estimating fee-for-service payments for privately insured stays, which represent a sizable proportion of stays for individuals under age 65. Additional research is needed to improve the predictive accuracy of the models for all payers.

Factors associated with adoption of robotic surgical technology in US hospitals and relationship to radical prostatectomy procedure volume.

OBJECTIVE: Robotic technology has diffused rapidly despite high costs and limited additive reimbursement by major payers. We aimed to identify the factors associated with hospitals' decisions to adopt robotic technology and the consequences of these decisions. METHODS: This observational study used data on hospitals and market areas from 2005 to 2009. Included were hospitals in census-based statistical areas within states in the State Inpatient Database that participated in the American Hospital Association annual surveys and performed radical prostatectomies. The likelihood that a hospital would acquire a robotic facility and the rates of radical prostatectomy relative to the prevalence of robots in geographic market areas were assessed using multivariable analysis. RESULTS: Hospitals in areas where a higher proportion of other hospitals had already acquired a robot were more likely to acquire one (P=0.012), as were those with more than 300 beds (P<0.0001) and teaching hospitals (P<0.0001). There was a significant association between years with a robot and the change in the number of radical prostatectomies (P<0.0001). More radical prostatectomies were performed in areas where the number of robots per 100,000 men was higher (P<0.0001). Adding a single robot per 100,000 men in an area was associated with a 30% increase in the rate of radical prostatectomies. CONCLUSIONS: Local area robot competition was associated with the rapid spread of robot technology in the United States. Significantly more radical prostatectomies were performed in hospitals with robots and in market areas of hospitals with robotic technology.

Geographic variation in cesarean delivery in the United States by payer.

BACKGROUND: The rate of cesarean delivery in the United States is variable across geographic areas. The aims of this study are two-fold: (1) to determine whether the geographic variation in cesarean delivery rate is consistent for private insurance and Medicaid (2) to identify the patient, population, and market factors associated with cesarean rate and determine if these factors vary by payer. METHODS: We used the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) to measure the cesarean rate at the Core-Based Statistical Area (CBSA) level. We linked the hospitalization data to data from other national sources to measure population and market characteristics. We calculated unadjusted and risk-adjusted CBSA cesarean rates by payer. For the second aim, we estimated a hierarchical logistical model with the hospitalization as the unit of analysis to determine the factors associated with cesarean delivery. RESULTS: The average CBSA cesarean rate for women with private insurance was higher (18.9 percent) than for women with Medicaid (16.4 percent). The factors predicting cesarean rate were largely consistent across payers, with the following exceptions: women under age 18 had a greater likelihood of cesarean section if they had Medicaid but had a greater likelihood of vaginal birth if they had private insurance; Asian and Native American women with private insurance had a greater likelihood of cesarean section but Asian and Native American women with Medicaid had a greater likelihood of vaginal birth. The percent African American in the population predicted increased cesarean rates for private insurance only; the number of acute care beds per capita predicted increased cesarean rate for women with Medicaid but not women with private insurance. Further we found the number of obstetricians/gynecologists per capita predicted increased cesarean rate for women with private insurance only, and the number of midwives per capita predicted increased vaginal birth rate for women with private insurance only. CONCLUSIONS: Factors associated with geographic variation in cesarean delivery, a frequent and high-resource inpatient procedure, vary somewhat by payer. Using this information to identify areas for intervention is key to improving quality of care and reducing healthcare costs.

Association between the unemployment rate and inpatient cost per discharge by payer in the United States, 2005-2010.

BACKGROUND: Several reports have linked the 2007-2009 Great Recession in the United States with a slowdown in health care spending and decreased utilization. However, little is known regarding how the recent economic downturn affected hospital costs per inpatient stay for different segments of the population. The purpose of this study was to examine the association between changes in the unemployment rate and inpatient cost per discharge for Medicare and commercial discharges. METHODS: We used retrospective data at the Core Based Statistical Area (CBSA)-level from 46 states that contributed to the Healthcare Cost and Utilization Project State Inpatient Databases from 2005 to 2010. Unemployment data was derived from the American Community Survey. An instrumental variable two-stage least squares approach with fixed- or random-effects was used to examine the association between unemployment rate and inpatient cost per discharge by payer because of potential endogeneity. RESULTS: The marginal effect of unemployment was associated with an increase in inpatient cost per discharge for both payers. A one percentage point increase in the unemployment rate was associated with a $37 increase for commercial discharges and a $49 increase for Medicare discharges. CONCLUSIONS: We find evidence that the inpatient cost per discharge is countercyclical across different segments of the population. The underlying mechanisms by which unemployment affects hospital resource use however, might differ between payer groups.

Hospital utilization, costs, and mortality for adults with multiple chronic conditions, Nationwide Inpatient Sample, 2009.

OBJECTIVE: Our objective was to provide a national estimate across all payers of the distribution and cost of selected chronic conditions for hospitalized adults in 2009, stratified by demographic characteristics. ANALYSIS: We analyzed the Nationwide Inpatient Sample (NIS), the largest all-payer inpatient database in the United States. Use, cost, and mortality estimates across payer, age, sex, and race/ethnicity are produced for grouped or multiple chronic conditions (MCC). The 5 most common dyads and triads were determined. RESULTS: In 2009, there were approximately 28 million adult discharges from US hospitals other than those related to pregnancy and maternity; 39% had 2 to 3 MCC, and 33% had 4 or more. A higher number of MCC was associated with higher mortality, use of services, and average cost. The percentages of Medicaid, privately insured patients, and ethnic/racial groups with 4 or more MCC were highly sensitive to age. SUMMARY: This descriptive analysis of multipayer inpatient data provides a robust national view of the substantial use and costs among adults hospitalized with MCC.

Hospital cost and quality performance in relation to market forces: an examination of U.S. community hospitals in the "post-managed care era".

Managed care substantially transformed the U.S. healthcare sector in the last two decades of the twentieth century, injecting price competition among hospitals for the first time in history. However, total HMO enrollment has declined since 2000. This study addresses whether managed care and hospital competition continued to show positive effects on hospital cost and quality performance in the "post-managed care era." Using data for 1,521 urban hospitals drawn from the Healthcare Cost and Utilization Project, we examined hospital cost per stay and mortality rate in relation to HMO penetration and hospital competition between 2001 and 2005, controlling for patient, hospital, and other market characteristics. Regression analyses were employed to examine both cross-sectional and longitudinal variation in hospital performance. We found that in markets with high HMO penetration, increase in hospital competition over time was associated with decrease in mortality but no change in cost. In markets without high HMO penetration, increase in hospital competition was associated with increase in cost but no change in mortality. Overall, hospitals in high HMO penetration markets consistently showed lower average costs, and hospitals in markets with high hospital competition consistently showed lower mortality rates. Hospitals in markets with high HMO penetration also showed lower mortality rates in 2005 with no such difference found in 2001. Our findings suggest that while managed care may have lost its strength in slowing hospital cost growth, differences in average hospital cost associated with different levels of HMO penetration across markets still persist. Furthermore, these health plans appear to put quality of care on a higher priority than before.

Likelihood of hospital readmission after first discharge: Medicare Advantage vs. fee-for-service patients.

This study tests whether the likelihood of hospital readmission within 30 days of discharge is different for enrollees in Medicare Advantage plans versus the standard fee-for-service program. A key requirement is to control for self-selection into Advantage plans. The study uses statewide inpatient databases maintained by the Agency for Healthcare Research and Quality for five states in 2006. The type of Medicare coverage is known, along with an encrypted patient identifier. We identify eligible first discharges and the first readmission within 30 days. We use selected area characteristics as instrumental variables for enrollment in Advantage plans and apply a bivariate probit analysis. Descriptively, there is a slightly lower likelihood of readmission for Advantage plan enrollees. However, the Advantage plan patients are younger and less severely ill. After risk adjustment and control for self-selection, the enrollees in Advantage plans have a substantially higher likelihood of readmission. Recognizing caveats and limitations, the study supports informing Medicare beneficiaries about the rates of readmission for Advantage plans in their area. Analytical methods to adjust for self-selection into particular plans or plan types should be considered when possible.

Do Medicare Advantage enrollees tend to be admitted to hospitals with better or worse outcomes compared with fee-for-service enrollees?

The hospitals selected by or for Medicare beneficiaries might depend on whether the patient is enrolled in a Medicare Advantage (MA) plan. A theoretical model of profit maximization by MA plans takes into account the tradeoffs of consumer preferences for annual premium versus outcomes of care in the hospital and other attributes of the plan. Hospital discharge databases for 13 states in 2006, maintained by the Agency for Healthcare Research and Quality, are the main source of data. Risk-adjusted mortality rates are available for all non-maternity adult patients in each of 15 clinical categories in about 1,500 hospitals. All-adult postoperative safety event rates covering 9 categories of events are calculated for surgical cases in about 900 hospitals. Instrumental variables are used to address potential endogeneity of the choice of a MA plan. The key findings are these: enrollees in MA plans tend to be treated in hospitals with lower resource cost and higher risk-adjusted mortality compared to Fee-for-Service (FFS) enrollees. The risk-adjusted mortality measure is about 1.5 percentage points higher for MA plan enrollees than the overall mean of 4%. However, the rate of safety events in surgical patients favors MA plan enrollees--the rate is 1 percentage point below the average of 3.5%. These discrepant results are noteworthy and are plausibly due to greater discretion by the health plan in approving patients for elective surgery and as well as selecting hospitals for surgical patients. Emergency patients are generally excluded for the safety outcome measures. In addition, the current mortality measures may not adequately represent all surgical patients. Such caveats should be prominently highlighted when presenting comparative data. With that proviso, the study justifies informing Medicare beneficiaries about the mortality and safety outcome measures for hospitals being used by a MA plan compared to hospitals used by FFS enrollees.

Do patient safety events increase readmissions?

OBJECTIVE: Adverse safety events in the hospital could impose extra costs not only due to longer stays and corrective treatments, but also due to deaths and readmissions. The effects of safety events on readmissions have rarely been analyzed. Large, all-payer and all-diagnosis databases permit new tests. This study will simultaneously test the effects of safety events on risks of deaths and readmission. STUDY DESIGN: The population is a selection of almost 1.5 million adult surgery patients initially treated in 1088 short stay hospitals. These are patients at risk for at least 1 of 9 types of patient safety event, as specified in software in the public domain from the Agency for Healthcare Research and Quality. The main data sources are 7 statewide databases of hospitalizations in 2004, maintained by Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. We control for many factors affecting readmission or death, particularly the severity of illness, chronic comorbidities, age, and payer group. Separate models are used for each type of safety event and a composite model is used for any safety event. PRINCIPAL FINDINGS: Among the patients at risk for any of the patient safety events, 2.6% had at least one safety event. The 3-month readmission rate was about 17% for those with no safety event, but about 25% when a safety event was recorded. The corresponding rates for readmission within 1 month were 11% and 16%. The in-hospital death rate was 1.3% with no safety event, but 9.2% with a safety event. After risk adjustment, the relative risk of readmission within 3 months was about 1.20 (P < 0.01), ranging from 1.14 to 1.56 for specific types of events. The risk-adjusted result for readmission within 1 month associated with at least one safety event was 1.17 (P < 0.01). However, the models for specific safety events gave a significantly high risk of readmission within 1 month for only 2 of the more common types of safety events. CONCLUSIONS: Hospital readmissions are one way that safety events can have costly consequences. More attention is warranted to assess the full extra cost of safety events, the factors influencing the rate of safety events, and strategies for health plans to improve incentives for safety.

Costly hospital readmissions and complex chronic illness.

People with multiple chronic conditions account for a large and disproportionate share of total health care costs. One aspect of the high cost for such patients is a relatively high number of hospital admissions per year. This study aims to clarify how the rate of hospital readmissions and hospital cost per person in a year depend on a patient's number of different chronic conditions ("complexity"), severity of illness, principal diagnosis at discharge, payer group, and other variables. We use a database of all hospital discharges for adults in six states. The number of different chronic conditions has a smoothly increasing effect on readmissions and cost per year, and there are notable differences by payer group. We offer illustrations of the potential savings from reducing total inpatient cost and readmissions in narrowly targeted populations with the most complex problems. The study's methods and descriptive data potentially could be useful for health plans and their sponsors (employers, government) when they design strategies to address the high cost of complex chronic illness.

Hospital inpatient costs for adults with multiple chronic conditions.

This article offers national estimates of the proportions of hospital inpatient cases and cost for adult, nonmaternal patients who have multiple chronic conditions. The authors employ a refined classification of chronic versus acute conditions, collapsed to no more than one condition per distinct category of condition. The number of different chronic conditions provides a simple measure of complexity, differing from measures of severity of illness that pertain to a particular episode of treatment. A multivariate regression finds that the number of chronic conditions is an independent influence on hospital cost per case, controlling for other key determinants. Patients with complex illness (e.g., 3+ or 5+ chronic conditions) have a disproportionately large effect on hospital cost per year. The identification of patients in the hospital with complex illness can help in targeting new covered services in a health plan or in risk adjusting health plan premiums. Current policies and demonstrations for the Medicare program may not be sufficient to address complex illness.

Renewed growth in hospital inpatient cost since 1998: variation across metropolitan areas and leading clinical conditions.

OBJECTIVE: To use disaggregated data about metropolitan statistical areas (MSAs) and clinical conditions to better describe the variation in cost increases and explore some of the hypothesized influences. STUDY DESIGN: The study uses the state inpatient databases from the Healthcare Cost and Utilization Project, containing all discharges from hospitals in 172 MSAs in 1998 and 2001. The discharge summary information was combined with standardized hospital accounting files, surveys of managed care plans, MSA demographics, and state data pertaining to caps on medical malpractice awards. METHODS: The analysis used descriptive comparisons and multivariate regressions of admission rate and cost per case in 9 leading disease categories across the MSAs. The increase in hospital input prices and changes in severity of illness were controlled. RESULTS AND CONCLUSION: Metropolitan statistical areas with higher HMO market penetration continued to show lower admission rates, no less so in 2001 than in 1998. A cap on malpractice awards appeared to restrain admissions, but the net effect on hospital cost per adult eroded for those states with the most experience with award caps. Higher admission rates and increase in cost were found in several disease categories.

Preventable hospitalization and medicaid managed care: does race matter?

This study examines the preventable hospitalization patterns of Medicaid patients by race/ethnicity to determine whether Medicaid managed care (MMC) has been more effective in some subgroups than others. It uses logistic models for three states, comparing preventable hospitalizations with marker admissions (urgent admissions, insensitive to primary care). Hospital discharge data from the Healthcare Cost and Utilization Project State Inpatient database of the Agency for Health Care Research and Quality for New York, Pennsylvania, and Wisconsin residents aged 20-64 years is used. In a more urban state, New York, MMC was effective for Whites but not for minorities. In a more rural state, Wisconsin, MMC was effective for minorities. Overall, the evidence is not strong that any particular racial group consistently benefited from MMC, or that any state consistently showed a favorable impact of MMC across racial groups. However, racial/ethnic disparity associated with the risk of preventable hospitalization is significantly lower among Medicaid patients than among private fee-for-service patients.

Factors associated with high-quality/low-cost hospital performance.

This study explores organizational and market characteristics associated with superior hospital performance in both quality and cost of care, using the Healthcare Cost and Utilization Project State Inpatient Databases for ten states in 1997 and 2001. After controlling for a variety of patient factors, we found that for-profit ownership, hospital competition, and the number of HMOs were positively associated with the likelihood of attaining high-quality/low-cost performance. Furthermore, we examined interactions between organizational and market characteristics and identified a number of significant interactions. For example, the positive likelihood associated with for-profit hospitals diminished in markets with high HMO penetration.

Multiple hospitalizations for patients with diabetes.

OBJECTIVE: To describe the extent to which hospitalizations for patients with diabetes reflect multiple stays by the same individuals and to examine how multiple hospitalizations vary by patient demographic and socioeconomic characteristics. RESEARCH DESIGN AND METHODS: Using the Healthcare Cost and Utilization Project complete discharge data for five states (California, Missouri, New York, Tennessee, and Virginia) in 1999, we identified 648,748 nonneonatal, nonmaternal patients who had one or more hospitalizations listing diabetes. Multiple hospitalizations were measured as percent of patients with multiple stays, percent of total stays represented by multiple stays, and average number of stays per patient. Total hospital costs were also examined. Stratified analysis and regression were performed to assess differences by age, sex, race/ethnicity, payer, location, and income. RESULTS: Among patients with diabetes who had been hospitalized, 30% had two or more stays accounting for >50% of total hospitalizations and hospital costs. Controlled for patient age, sex, and clinical characteristics, the likelihood of having multiple hospitalizations was higher for Hispanics and non-Hispanic blacks compared with non-Hispanic whites, as well as for patients covered by Medicare or Medicaid and those living in low-income areas. The prevalence of diabetes complications and multiple conditions differed by age, race/ethnicity, and payer among patients with multiple stays. CONCLUSIONS: Multiple hospitalizations are common among patients with diabetes but vary by age, race/ethnicity, payer, and income, with those populations traditionally considered to be more vulnerable experiencing higher likelihoods of multiple stays. Significant opportunities exist to reduce the proportion of multiple hospitalizations for patients with diabetes. Clinical and policy interventions to improve the quality of care and outcomes for these patients should be designed accordingly and have the potential to pay major dividends.

The rate and cost of hospital readmissions for preventable conditions.

The study estimates the rate and cost of preventable readmissions within 6 months after a first preventable admission, by age-group, and by payer and race within age-group. The descriptive results are contrasted with several hypotheses. The hospital discharge data are for residents of New York, Pennsylvania, Tennessee, and Wisconsin in 1999, from files of the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality. About 19 percent of persons with an initial preventable admission had at least one preventable readmission rate within 6 months. Hospital cost for preventable readmissions during 6 months was about 730 million US dollars. There were substantial differences in readmission rates by payer group and by race. Some evidence suggests that preventable readmissions may partly reflect complexity of underlying problems. Interventions to reduce cost might focus on identifying high-risk patients before discharge and devising new approaches to follow-up.

Managed care and preventable hospitalization among Medicaid adults.

OBJECTIVE: The study examines the association between managed care enrollment and preventable hospitalization patterns of adult Medicaid enrollees hospitalized in four states. DATA SOURCES/STUDY SETTING: Hospital discharge data from the Healthcare Cost and Utilization Project (HCUP) database of the Agency for Healthcare Research and Quality (AHRQ) for New York (NY), Pennsylvania (PA), Wisconsin (WI), and Tennessee (TN) residents in the age group 20-64 hospitalized in those states, linked to the Area Resource File (ARF) and American Hospital Association (AHA) survey files for 1997. STUDY DESIGN: The study uses separate logistic models for each state comparing preventable admissions with marker admissions (urgent, insensitive to primary care). The model controls for socioeconomic and demographic variables, and severity of illness. PRINCIPAL FINDINGS: Consistently in different states, private health maintenance organization (HMO) enrollment was associated with fewer preventable admissions than marker admissions, compared to private fee-for-service (FFS). However, Medicaid managed care enrollment was not associated with a reduction in preventable admissions, compared to Medicaid FFS. CONCLUSIONS: Our analysis suggests that the preventable hospitalization pattern for private HMO enrollees differs significantly from that for commercial FFS enrollees. However, little difference is found between Medicaid HMO enrollees and Medicaid FFS patients. The findings did not vary by the level of Medicaid managed care penetration in the study states.

Practical options for estimating cost of hospital inpatient stays.

Analysts often estimate the cost of hospital services by applying cost/charge (c/c) ratios from federal or state data sources to the charges provided on hospital discharge records. Recently, a number of sources of discharge data are not permitting the release of hospital identities. This study compares several sources of c/c data for use in the restricted environment. Accounting data from four state systems and from files of the federal Centers for Medicare and Medicaid Services (formerly HCFA) are employed. In one analysis hospitals are grouped by selected characteristics. C/c varies by state and characteristics. Some HCFA and state measures track each other closely. A wider analysis of hospital-specific data for 51 states offers a separate test and extension of the initial results. The study supports a practical policy option of releasing grouped c/c ratios attached to discharge records when identity must be masked. Key words: hospital cost, cost to charge ratios, privacy protections.

Variation in hospital inpatient prices across small geographic areas.

OBJECTIVES: To examine whether market competition may influence the difference in the inpatient price per discharge between public (Medicare) and private payers across small geographic areas. STUDY DESIGN: Retrospective multivariate analysis. METHODS: Data came from the 2006 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs) in 162 counties from 6 states where an HCUP price-to-charge ratio (PCR) was available. The SIDs were linked with the Area Resource File, American Hospital Association Annual Survey Database, and US Census Bureau data files. Hospital inpatient prices were estimated by applying the HCUP PCR to total hospital charges. Payer-specific price comparisons were made for all discharges, an acute condition (acute myocardial infarction), and an elective condition (knee arthroplasty). Ordinary least squares models were used to examine the effect of market competition on the inpatient price per discharge by payer. RESULTS: Greater geographic variation was found in the inpatient price per discharge among private than public payers for most hospital services. Hospitals in more concentrated markets were associated with a higher price per discharge among knee arthroplasty discharges for both payers. CONCLUSIONS: Hospitals charged significantly higher prices to private than public payers. Because the payment policies from Medicare ultimately affect private payers, public policy efforts that take into consideration market-based approaches or payment reform may help to reduce price variations.