High hospital admission rates and inappropriate care

Hospital-level variation in risk-standardized admission rates for emergency care-sensitive conditions among older and younger Veterans

OBJECTIVES

Research examining emergency department (ED) admission practices within the Department of Veterans Affairs (VA) is limited. This study investigates facility-level variation in risk-standardized admission rates (RSARs) for emergency care-sensitive conditions (ECSCs) among older (≥65 years) and younger (<65 years) Veterans across VA EDs.

METHODS

Veterans presenting to a VA ED for an ECSC between October 1, 2016 and September 30, 2019 were identified and the 10 most common ECSCs established. ECSC-specific RSARs were calculated using hierarchical generalized linear models, adjusting for Veteran and encounter characteristics. The interquartile range ratio (IQR ratio) and coefficient of variation were measures of dispersion for each condition and were stratified by age group. Associations with facility characteristics were also examined in condition-specific multivariable models.

RESULTS

The overall cohort included 651,336 ED visits across 110 VA facilities for the 10 most common ECSCs-chronic obstructive pulmonary disease (COPD), heart failure, pneumonia, volume depletion, tachyarrhythmias, acute diabetes mellitus, gastrointestinal (GI) bleeding, asthma, sepsis, and myocardial infarction (MI). After adjusting for case mix, the ECSCs with the greatest variation (IQR ratio, coefficient of variation) in RSARs were asthma (1.43, 32.12), COPD (1.39, 24.64), volume depletion (1.38, 23.67), and acute diabetes mellitus (1.28, 17.52), whereas those with the least variation were MI (1.01, 0.87) and sepsis (1.02, 2.41). Condition-specific RSARs were not qualitatively different between age subgroups. Association with facility characteristics varied across ECSCs and within condition-specific age subgroups.

CONCLUSIONS

We identified unexplained facility-level variation in RSARs for Veterans presenting with the 10 most common ECSCs to VA EDs. The magnitude of variation did not appear to be qualitatively different between older and younger Veteran subgroups. Variation in RSARs for ECSCs may be an important target for systems-based levers to improve value in VA emergency care.

Has the Efficiency of China's Healthcare System Improved after Healthcare Reform? A Network Data Envelopment Analysis and Tobit Regression Approach

Background: A healthcare system refers to a typical network production system. Network data envelopment analysis (DEA) show an advantage than traditional DEA in measure the efficiency of healthcare systems. This paper utilized network data envelopment analysis to evaluate the overall and two substage efficiencies of China’s healthcare system in each of its province after the implementation of the healthcare reform. Tobit regression was performed to analyze the factors that affect the overall efficiency of healthcare systems in the provinces of China. Methods: Network DEA were obtained on MaxDEA 7.0 software, and the results of Tobit regression analysis were obtained on StataSE 15 software. The data for this study were acquired from the China health statistics yearbook (2009–2018) and official websites of databases of Chinese national bureau. Results: Tobit regression reveals that regions and government health expenditure effect the efficiency of the healthcare system in a positive way: the number of high education enrollment per 100,000 inhabitants, the number of public hospital, and social health expenditure effect the efficiency of healthcare system were negative. Conclusion: Some provincial overall efficiency has fluctuating increased, while other provincial has fluctuating decreased, and the average overall efficiency scores were fluctuations increase.

Distribution of the Indicator of the Appropriate Admission of Patients with Circulatory System Diseases to County Hospitals in Rural China: A Cross-Sectional Study

Background: The inappropriate admission of patients with circulatory system diseases (CSDs) have contributed to the rapid increase in hospitalisation rates in China. The purpose of this study is to identify the key indicators of appropriate admission and their distribution by analysing CSD cases. Methods: A total of 794 records of inpatient CSD cases were collected from county hospitals in five counties in midwestern rural China through stratified random sampling and evaluated by using the Rural Appropriateness Evaluation Protocol (RAEP). RAEP has two parts: Indicator A, which represents requirement for services, and Indicator B, which represents diseases severity. Indicator distribution was analysed through frequency analysis. A three-level logistic regression model was used to examine the sociodemographic determinants of the positive indicators of appropriate CDSs admissions. Result: The inappropriate admission rate of CSDs was 33.4% and varied between counties. A2 (Varying dosage/drug under supervision, 58.22%), A8 (Stopping/continuing oxygen inhalation, 38.19%), A7 (Electrocardiogram per 2 hours, 34.22%), A3 (Calculation of intake and output volume, 31.19%) and B14 (Abnormal blood condition, 27.98%) were the top five positive indicators of CSDs. Indicator A (requirements for services) was more active than Indicator B (disease severity). The limitation of the role of Indicator B over time may be attributed to the different policies and environments of rural China and stimulated the increase in inappropriate admission rates. The results of three-level logistic regression suggested that the influence of gender, year, region and disease type on positive indicators should receive increased attention in the evaluation of CSDs admissions. Conclusion: This study found that A2, A8, A7, A3 and B14 were the key indicators and were helpful to determine the appropriate admission of CSDs in rural China. Managers may focus on these indicators, particularly the use of indicator A.

Is There a Difference in the Utilisation of Inpatient Services Between Two Typical Payment Methods of Health Insurance? Evidence from the New Rural Cooperative Medical Scheme in China

This study aimed to evaluate the effects of the differences between two typical payment methods for the new rural cooperative medical scheme (NRCMS) in China on the utilisation of inpatient services. Interrupted time-series analysis (ITSA) and propensity score matching (PSM) were used to measure the difference between two typical payment methods for the NRCMS with regard to the utilisation of inpatient services. After the reform was formally implemented, the level and slope difference after reform compared with pre-intervention (distribution of inpatients in county hospitals (DIC), distribution of inpatients in township hospitals (DIT) and the actual compensation ratio of inpatients (ARCI)) were not statistically significant. Kernel matching obtained better results in reducing the mean and median of the absolute standardised bias of covariates of appropriateness of admission (AA), appropriateness of disease (AD). The difference in AA and AD of the matched inpatients between two groups was −0.03 (p-value = 0.042, 95% CI: −0.08 to 0.02) and 0.21 (p-value < 0.001, 95% CI: −0.17 to 0.25), respectively. The differences in the utilisation of inpatient services may arise owing to the system designs of different payment methods for NRCMS in China. The causes of these differences can be used to guide inpatients to better use medical services, through the transformation and integration of payment systems.

Determinants of inappropriate admissions of children to county hospitals: a cross-sectional study from rural China

BACKGROUND

The incidence of inappropriate admissions in China has become the shackle of its' service supply system. This research aims to assess the level of children's inappropriate admissions to county hospitals in rural China and identify the characteristics and determinants of children's inappropriate admissions.

METHODS

A retrospective review was conducted on data of children aged 0-14 years. A total of 771 children medical records in four county hospitals was collected by stratified random sampling in Midwestern China and was evaluated through the Rural Appropriateness Evaluation Protocol. A questionnaire survey was conducted among doctors whose names were shown in medical records. Chi-square test was used to analyse the characteristics of inappropriate admissions, and a binary logistic regression model was used to examine the determinants of inappropriate admissions.

RESULTS

Inappropriate admissions indicate that patients who could have been treated as outpatients received services as inpatients. The average rate for inappropriate admissions of children in county hospitals was 61.35%. The highest rate of inappropriate admissions was found among children aged 1-5 years (68.42%). Inappropriate admissions mostly occurred in children with respiratory diseases (72.45%), circulatory diseases (72.22%) and certain infectious diseases and parasitic diseases (70.37%). Binary logistic regression analysis showed that county, normal health status, treating department, disease, the length of hospital stay and the doctor's self-evaluation on the understanding about the degree of the patient's feelings were determinants for children's inappropriate admissions.

CONCLUSIONS

County hospitals have a high rate of inappropriate admissions of children. The relationship of children's inappropriate admissions to age distribution and the insurance compensation is affected by disease and hospitalisation expenses, respectively. The determinants of children's inappropriate admissions are directly related to the weak level of primary care services in the health service system, the initial requirements requested by children's admission decision makers and the interests among medical institutions and doctors.

Determinants of Inappropriate Admissions in County Hospitals in Rural China: A Cross-Sectional Study

Inappropriate admissions have contributed to the rapid increase in hospitalisations in rural China. This study characterised the degree and determinants of inappropriate admissions in county hospitals. We used expert consultation to develop an appropriateness evaluation protocol that included nine requirements for services and 21 indicators of disease severity. A total of 2230 medical records from 2014 were collected from five county hospitals by stratified cluster sampling and evaluated for appropriateness using the protocol in 2016. The determinants of inappropriate admissions were analysed by two-level logistic regression. The overall inappropriate admission rate was 15.2%. Patients aged.

Where to go if not the hospital? Reviewing geriatric bed utilization in an acute care hospital in Singapore

AIM

Singapore is one of the fastest-aging countries in the world, and the demand for acute hospital care for older adults is expected to triple in the next 25 years. Hence, it is crucial to understand the opportunities in reducing potentially avoidable bed days (PABD), which are days spent in acute hospitals delivering only non-acute services. We aimed to access the prevalence, causes and consequences of PABD among geriatric patients.

METHODS

We examined all hospitalizations from 1 August through 31 December 2013 in the geriatric wards of an acute hospital in Singapore. PABD were identified using a modified Appropriateness Evaluation Protocol. Non-acute services were classified as subacute care, rehabilitative care, long-term care or social care. Hospitalization patterns were determined based on the presence or absence of non-acute services, and multinomial logistic regression was used to determine predictors of different patterns.

RESULTS

Of the 273 bed days used by 254 patients, 49% were potentially avoidable. The most common non-acute services provided were rehabilitative care (19%), subacute care (12%) and long-term care (8%). New acute issues arose after the admission conditions subsided in 2.4% of hospitalizations, 61% of which were nosocomial infections. Being socially at risk as assessed on admission predicted the development of new acute issues (sensitivity = 62%; specificity = 88%).

CONCLUSIONS

In the present study, almost half of the bed days were potentially avoidable. New acute issues can arise after PABD, which are dangerous to these frail older adults. Proactive discharge planning and increasing access to intermediate and long-term care services are required to reduce PABD. Geriatr Gerontol Int 2017; 17: 1575-1583.

Variation in US hospital emergency department admission rates by clinical condition

BACKGROUND

Variation in hospitalization rates have been described for decades, yet little is known about variation in emergency department (ED) admission rates across clinical conditions. We sought to describe variation in ED risk-standardized admission rates (RSAR) and the consistency between condition-specific ED admission rates within hospitals.

METHODS

Cross-sectional analysis of the 2009 National Emergency Department Sample, an all-payer administrative, claims dataset. We identify the 15 most frequently admitted conditions using Clinical Classification Software. To identify conditions with the highest ED RSAR variation, we compared both the ratio of the 75th percentile to the 25th percentile hospital and coefficient of variation between conditions. We calculate Spearman correlation coefficients to assess within-hospital correlation of condition-specific ED RSARs.

RESULTS

Of 21,885,845 adult ED visits, 4,470,105 (20%) resulted in admission. Among the 15 most frequently admitted conditions, the 5 with the highest magnitude of variation were: mood disorders (ratio of 75th:25th percentile, 6.97; coefficient of variation, 0.81), nonspecific chest pain (2.68; 0.66), skin and soft tissue infections (1.82; 0.51), urinary tract infections (1.58; 0.43), and chronic obstructive pulmonary disease (1.57; 0.33). For these 5 conditions, the within-hospital RSAR correlations between each pair of conditions were >0.4, except for mood disorders, which was poorly correlated with all other conditions (r<0.3).

CONCLUSIONS

There is significant condition-specific variation in ED admission rates across US hospitals. This variation appears to be consistent between conditions with high variation within hospitals.

Has access to care changed in minority communities? A study of preventable hospitalizations over time in selected States

This study assesses the changes in access to care in minority communities by examining the association between preventable hospitalization rates and racial/ethnic composition of the community during 1995-2005. Using hospital discharge data from Healthcare Cost and Utilization Project State Inpatient Database of the Agency for Healthcare Research and Quality in 5 states and focusing on the nonelderly adults and elderly age groups, the study includes a multivariate cross-sectional design using preventable hospitalization rates by primary care service area as the outcome and racial/ethnic compositions of total hospital discharges by resident population in the primary care service area as the primary explanatory variables. The study indicates increases in barriers faced by minority adults in accessing primary care over time, with no similar evidence for the elderly subgroup.

Geographic variation in fee-for-service medicare beneficiaries' medical costs is largely explained by disease burden

Control for area differences in population health (casemix adjustment) is necessary to measure geographic variations in medical spending. Studies use various casemix adjustment methods, resulting in very different geographic variation estimates. We study casemix adjustment methodological issues and evaluate alternative approaches using claims from 1.6 million Medicare beneficiaries in 60 representative communities. Two key casemix adjustment methods-controlling for patient conditions obtained from diagnoses on claims and expenditures of those at the end of life-were evaluated. We failed to find evidence of bias in the former approach attributable to area differences in physician diagnostic patterns, as others have found, and found that the assumption underpinning the latter approach-that persons close to death are equally sick across areas-cannot be supported. Diagnosis-based approaches are more appropriate when current rather than prior year diagnoses are used. Population health likely explains more than 75% to 85% of cost variations across fixed sets of areas.

Changes in preventable hospitalization patterns among the adults: a small area analysis of US states

The study examines the variation and changes in preventable hospitalization (PH) rates across small areas over 1995-2005 in 5 US states for adults (aged 18-64 years). Using hospital discharge data from the Agency for Healthcare Research and Quality and contextual data from Health Resources and Services Administration, the study examines the role of managed care, primary care physician supply, and sociodemographic factors on adult PH rates. A stronger influence of minority and uninsured status, weaker contributions of managed care enrollment in the commercial as well as in the Medicaid markets, and weaker contributions of primary care density may have caused slower than expected reduction in adult PH rates.

Organizational boundaries of medical practice: the case of physician ownership of ancillary services

Physician ownership of in-office ancillary services (IOASs) has come under increasing scrutiny. Advocates of argue that IOASs allow physicians to supervise the quality and coordination of care. Critics have argued that IOASs create financial incentives for physicians to increase ancillary service volume. In this paper we develop a conceptual framework to evaluate the tradeoffs associated with physician ownership of IOASs. There is some evidence supporting the existence of scope and transaction economies in IOASs. Improvement in flow and continuity of care are likely to generate scope economies and improvements in quality monitoring and reductions in consumer transaction costs are likely to generate transaction economies. Other factors include the capture of upstream and downstream profits, but these incentives are likely to be small compared to scope and transaction economies. Policy debates on the merits of IOASs should include an explicit assessment of these tradeoffs.This research was supported in part by funding from the American Association of Orthopaedic Surgeons (AAOS).

Bringing responsibility for small area variations in hospitalization rates back to the hospital: the propensity to hospitalize index and a test of the Roemer's Law

OBJECTIVE

To assign responsibility for variations in small area hospitalization rates to specific hospitals and to evaluate the Roemer's Law in a way that does not artificially induce correlation between bed supply and utilization.

DATA SOURCES/STUDY SETTING

We used data on hospitalizations and outpatient treatment for 15 medical conditions of nonmanaged care Part B eligible Medicare enrollees of 65 years and older in Massachusetts in 2000.

STUDY DESIGN

We used a Bayesian model to estimate each hospital's pool of potential patients and the fraction of the pool hospitalized (its propensity to hospitalize, PTH). To evaluate the Roemer's Law, we calculated the correlation between hospitals' PTH and beds per potential patient. Patient severity was measured using All Patient Refined Diagnosis Related Groups.

RESULTS

We show that our approach does not artificially induce a correlation between beds and utilization whereas the traditional approach does. Nevertheless, our approach indicates a strong relationship between PTH and beds (r=0.56). Eighteen (of 66) hospitals had a high PTH that differed significantly from 16 hospitals with a low PTH. Average patient severity in the high PTH hospitals was lower than in the low PTH hospitals. Although the difference was not statistically significant (P=0.12), there was a medium effect size (0.58).

DISCUSSION

Variation across hospitals in the PTH index, the strong relationship between beds and the PTH, and the lack of relationship between severity and the PTH suggest the importance of policies that limit bed growth of high PTH hospitals and create incentives for high PTH hospitals to reduce hospitalizations.

Reducing hospital admissions

Guidance should be evidence based and take a holistic view of patient care

Wide geographic variation between Pennsylvania counties in the population rates of hospital admissions for pneumonia among children with and without comorbid chronic conditions

OBJECTIVES

To compare county rates of hospital admissions for pediatric pneumonia and to assess the contribution of comorbid chronic conditions to county and state pediatric pneumonia admission rates.

METHODS

We performed retrospective analyses of data for all Pennsylvania-resident children 2 months through 17 years of age who were admitted to acute care hospitals with a principal diagnosis of pneumonia in 2003 or 2004. We divided the admissions into 2 groups (all pneumonia and pneumonia excluding coded comorbid chronic conditions) and calculated admission rates for each Pennsylvania county.

RESULTS

There were 5429 pediatric pneumonia admissions during the 12-month study period, of which 4948 (91.1%) were included in the study. The Pennsylvania state admission rate for all pneumonia was 156.3 admissions per 100000 children. County admission rates for all pneumonia ranged from 77.0 admissions per 100000 children to 457.6 admissions per 100000 children. Similar geographic patterns were seen among the 2851 admissions that remained in the second group after the exclusion of 2097 records (42.4%) coded for comorbid chronic conditions. The Pennsylvania state admission rate for pneumonia without chronic conditions was 90.0 admissions per 100000 children. County admission rates for pneumonia without comorbid chronic conditions ranged from 18.3 admissions per 100000 children to 350.3 admissions per 100000 children. Sixty-two (93%) of 67 counties remained in the same or an adjacent admission rate quintile after children with comorbid chronic conditions were excluded. On average, the county admission rates for pneumonia without comorbid chronic conditions were 58.1% of their admission rates for all pneumonia.

CONCLUSIONS

County pediatric pneumonia admission rates vary widely, even among geographically contiguous and demographically similar counties. Excluding children with comorbid chronic conditions, to control for varying community disease burdens, did not alter substantially the county rank order or the pattern or degree of variations in admission rates in our study.

The effects of HMO penetration on preventable hospitalizations

OBJECTIVE

To examine the effects of health maintenance organization (HMO) penetration on preventable hospitalizations.

DATA SOURCE

Hospital inpatient discharge abstracts for 932 urban counties in 22 states from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID), hospital data from American Hospital Association (AHA) annual survey, and population characteristics and health care capacity data from Health Resources and Services Administration (HRSA) Area Resource File (ARF) for 1998.

METHODS

Preventable hospitalizations due to 14 ambulatory care sensitive conditions were identified using the Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators. Multiple regressions were used to determine the association between preventable hospitalizations and HMO penetration while controlling for demographic and socioeconomic characteristics and health care capacity of the counties.

PRINCIPAL FINDINGS

A 10 percent increase in HMO penetration was associated with a 3.8 percent decrease in preventable hospitalizations (95 percent confidence interval, 2.0 percent-5.6 percent). Advanced age, female gender, poor health, poverty, more hospital beds, and fewer primary care physicians per capita were significantly associated with more preventable hospitalizations.

CONCLUSIONS

Our study suggests that HMO penetration has significant effects in reducing preventable hospitalizations due to some ambulatory care sensitive conditions.

Do pediatric hospitalizations have a unique geography?

BACKGROUND

In the U.S. small-area health services research studies are often based on the hospital service areas (HSAs) defined by the Dartmouth Atlas of Healthcare project. These areas are based on the geographic origins of Medicare Part A hospital patients, the great majority of whom are seniors. It is reasonable to question whether the geographic system so defined is appropriate for health services research for all ages, particularly for children, who have a very different system of healthcare financing and provision in the U.S.

METHODS

This article assesses the need for a unique system of HSAs to support pediatric small-area analyses. It is a cross-sectional analysis of California hospital discharges for two age groups - non-newborns 0-17 years old, and seniors. The measure of interest was index of localization, which is the percentage of HSA residents hospitalized in their home HSA. Indices were computed separately for each age group, and index agreement was assessed for 219 of the state's HSAs. We examined the effect of local pediatric inpatient volume and pediatric inpatient resources on the divergence of the age group indices. We also created a new system of HSAs based solely on pediatric patient origins, and visually compared maps of the traditional and the new system.

RESULTS

The mean localization index for pediatric discharges was 20 percentage points lower than for Medicare cases, indicating a poorer fit of the traditional geographic system for children. The volume of pediatric cases did not appear to be associated with the magnitude of index divergence between the two age groups. Pediatric medical and surgical case subgroups gave very similar results, and both groups differed substantially from seniors. Location of children's hospitals and local pediatric bed supply were associated with Medicare-pediatric divergence. There was little visual correspondence between the maps of traditional and pediatric-specific HSAs.

CONCLUSION

Children and seniors have significantly different geographic patterns of hospitalization in California. Medicare-based HSAs may not be appropriate for all age groups and service types throughout the U.S.

Evaluation of quality improvement interventions to reduce inappropriate hospital use

OBJECTIVE

To assess the impact of process analyses and modifications on inappropriate hospital use.

DESIGN

Pre-post comparison of inappropriate hospital use after process modifications.

SETTING

The Department of Internal Medicine of the Geneva University Hospitals, Switzerland.

PARTICIPANTS

A random sample of 498 patients.

INTERVENTIONS

Two processes of care (i.e. non-urgent admissions and transfer to a rehabilitation hospital), which influenced inappropriate hospital use, were identified and modified. The impact of these modifications was then assessed.

MAIN OUTCOME MEASURES

The proportion of inappropriate hospital admissions and inappropriate hospital days.

RESULTS

As a baseline assessment before quality improvement interventions, the appropriateness of hospital use (admissions and hospital days) was evaluated using the Appropriateness Evaluation Protocol (AEP) in a sample of 500 patients (5665 days). After modification of the two processes through a quality improvement program, inappropriate hospital use was reassessed in a sample of 498 patients (6095 days). Inappropriate hospital admissions decreased from 15 to 9% (P = 0.002) and inappropriate hospital days from 28 to 25% (P = 0.12).

CONCLUSION

Using the AEP as a criterion, the quality improvement interventions significantly reduced inappropriate hospital use due to the process of non-urgent admissions, but the reduction of inappropriate hospital days specifically attributed to the transfer to the rehabilitation hospital did not reach statistical significance.

Appropriateness of the decision to transfer nursing facility residents to the hospital

OBJECTIVES

To develop and test a standardized instrument, the purpose of which is to assess (1) whether skilled nursing facilities (SNFs) transfer residents to emergency departments (ED) inappropriately, (2) whether residents are admitted to hospitals inappropriately, (3) and factors associated with inappropriate transfers.

DESIGN

A structured implicit review (SIR) of medical records.

SETTING AND PARTICIPANTS

Using nested random sampling in eight community SNFs, we identified SNF and hospital records of 100 unscheduled transfers to one of 10 hospitals.

MEASUREMENTS

Seven trained physician reviewers assessed appropriateness using a SIR form designed for this study (2 independent reviews per record, 200 total reviews). We measured interrater reliability with kappa statistics and used bivariate analysis to identify factors associated with assessment that transfer was inappropriate.

RESULTS

In 36% of ED transfers and 40% of hospital admissions, both reviewers agreed that transfer/admit was inappropriate, meaning the resident could have been cared for safely at a lower level of care. Agreement was high for both ED (percent agreement 84%, kappa .678) and hospital (percent agreement 89%, kappa .779). When advance directives were considered, both reviewers rated 44% of ED transfers and 45% of admissions inappropriate. Factors associated with inappropriateness included the perceptions that: (1) poor quality of care contributed to transfer need, (2) needed services would typically be available in outpatient settings, and (3) the chief complaint did not warrant hospitalization.

CONCLUSIONS

Inappropriate transfers are a potentially large problem. Some inappropriate transfers may be associated with poor quality of care in SNFs. This study demonstrates that structured implicit review meets criteria for reliable assessment of inappropriate transfer rates. Structured implicit review may be a valuable tool for identifying inappropriate transfers from SNFs to EDs and hospitals.

Do market-level hospital and physician resources affect small area variation in hospital use?

This study evaluates the effect of market-level physician and hospital resources on hospital use. It is anticipated that higher hospital discharges are associated with (1) greater hospital and physician resources, (2) more differentiated hospital and physician resources, and (3) higher levels of teaching intensity in the community. Data on 14 modified diagnostically related groups (DRGs) and 58 hospital market communities in Michigan are analyzed during a 7-year period. Findings indicate that physician resources, hospital resources, differentiation of hospital and physician resources, and teaching intensity contribute only modestly to discharges, holding constant the socioeconomic attributes of the community and adjusting for the variation in hospital use over time. With the inclusion of hospital and physician resource variables, socioeconomic factors remain important determinants of the variation across market communities. Findings are discussed in terms of their implications for health care organizations, managed care programs, and cost control efforts in general.

Geographic variations in utilization rates in Veterans Affairs hospitals and clinics

BACKGROUND

In the United States, geographic variation in hospital use is common. It is uncertain whether there are similar geographic variations in the health care system of the Department of Veterans Affairs (VA), which differs from the private sector because it predominantly serves men with annual incomes below $20,000, has a central system of administration, and uses salaried physicians. Thus, it might be less likely to have geographic variations.

METHODS

We used VA data bases to obtain information on patients treated for eight diseases (chronic obstructive pulmonary disease, pneumonia, congestive heart failure, angina, diabetes, chronic renal failure, bipolar disorder, and major depression). We analyzed their use of hospital and outpatient services by assessing the risk-adjusted numbers of hospital days (the average number of days a patient spent in the hospital per 12 months of follow-up, regardless of the number of hospital stays), hospital-discharge rates, and clinic-visit rates from 1991 through 1995 for the entire system and within the 22 geographically based health care networks.

RESULTS

We found substantial geographic variation in hospital use for all eight cohorts of patients and all the years studied. Variations in the numbers of hospital days per person-year among the networks were greatest among patients with chronic obstructive pulmonary disease (ranging from a factor of 2.7 to a factor of 3.1) during a given year and smallest among patients with angina (ranging from a factor of 1.5 to a factor of 2.1). Levels of hospital use were highest in the Northeast and lowest in the West. The variation in the rates of clinic visits for principal medical care among the networks ranged from a factor of approximately 1.6 to a factor of 4.0; variations in the rates were greatest among patients with chronic renal failure and smallest among patients with chronic obstructive pulmonary disease. There was no clear geographic pattern in the rates of outpatient-clinic use.

CONCLUSIONS

There are significant geographic variations in the use of hospital and outpatient services in the VA health care system. Because VA physicians are unable to increase their income by changing their patterns of practice, our findings suggest that their practice styles are similar to those of other physicians in their geographic regions.

A regional evaluation of variation in low-severity hospital admissions

OBJECTIVE

Determine patient and hospital-level variation in proportions of low-severity admissions.

DESIGN

Retrospective cohort study.

SETTING

Thirty hospitals in a large metropolitan region.

PATIENTS

A total of 43,209 consecutive eligible patients discharged in 1991 through 1993 with congestive heart failure (n = 25,213) or pneumonia (n = 17,995).

MEASUREMENTS AND MAIN RESULTS

Admission severity of illness was measured from validated multivariable models that estimated the risk of in-hospital death; models were based on clinical data abstracted from patients' medical records. Admissions were categorized as "low severity" if the predicted risk of death was less than 1%. Nearly 15% of patients (n = 6,382) were categorized as low-severity admissions. Compared with other patients, low-severity admissions were more likely (p < .001) to be nonwhite and to have Medicaid or be uninsured. Low-severity admissions had shorter median length of stay (4 vs 7 days; p < .001), but accounted for 10% of the total number of hospital days. For congestive heart failure, proportions of low-severity admissions across hospitals ranged from 10% to 25%; 12 hospitals had rates that were significantly different (p < .01) than the overall rate of 17%. For pneumonia, proportions ranged from 3% to 22%; 12 hospitals had rates different from the overall rate of 12%. Variation across hospitals remained after adjusting for patient sociodemographic factors.

CONCLUSIONS

Rates of low-severity admissions for congestive heart failure and pneumonia varied across hospitals and were higher among nonwhite and poorly insured patients. Although the current study does not identify causes of this variability, possible explanations include differences in access to ambulatory services, decisions to admit patients for clinical indications unrelated to the risk of hospital mortality, and variability in admission practices of individual physicians and hospitals. The development of protocols for ambulatory management of low-severity patients and improvement of access to outpatient care would most likely decrease the utilization of more costly hospital services.