Impact of age and procedure on resource use for patients with ischemic heart disease

OBJECTIVES: Impact of age on healthcare expenditures should be assessed by targeting on specific diseases and controlling for procedures and severity of illness. Relationship between age and resource use in patients receiving acute care medicine for ischemic heart disease (IHD) was examined. METHODS: We analyzed 19,874 IHD patients treated in 82 academic and 92 community hospitals. Length of stay (LOS), total charges (TC), and high outliers of LOS and TC were analyzed for every age group (under 65 years, 65-74 years, 75 years or older). Independent effects of age on LOS, TC, and high outliers of LOS and TC were determined using multivariate analysis. RESULTS: 7863 (39.6%) patients were under 65 years, 7181 (36.1%) between 65 years and 74 years, and 4830 (24.3%) aged 75 years or older. Proportion of angina or non-medical treatment was significantly different among three age categories (angina 72%, 75%, 71.4%; non-medical 37.3%, 40.9%, 38.9%, respectively). Significant association with LOS or TC was identified in patients receiving coronary artery bypass graft surgery with percutaneous intracoronary intervention, who were most associated with TC high outlier. CONCLUSIONS: Age had a modest impact on resource use, as compared with procedures. Policy makers need to acknowledge the impact of procedures on healthcare spending.     

Factors and perspectives affecting nursing resource consumption in community hospitals.

The consumption of professional and non-professional nursing resources on medical/surgical nursing units varies sharply among community hospitals. In an effort to explain the variation, this study examines several factors: socio-economic characteristics of the population; supply of registered nurses; hospital characteristics such as size, complexity and diversity of services; patient characteristics such as case mix index and nursing care acuity index; and production system characteristics such as efficiency of technical support systems and the structure of nursing care delivery. Nursing skill mix varies more than the staffing levels among hospitals. The research suggests that factors associated with a clinical-rational model such as nursing acuity index and the efficiency of clinical/support systems explains little, whereas factors associated with economic-rational model of hospital revenues--like case mix, number of hospital services, poverty (through Medicaid program) and age distribution (through Medicare program)--do significantly affect nursing resource consumption. The results point to the presence of resource allocation to nursing based on hospital revenues rather than patient care needs.     

Relationship between hospital structural level and length of stay outliers. Implications for hospital payment systems

BACKGROUND: Hospital structural level has been suggested as a factor that could explain part of the resource use variation left unexplained by diagnosis related groups (DRGs). However, the relationship between hospital structural level and the presence of cases of extreme resource use (outliers) is not known. Some prospective payment systems pay these cases separately. OBJECTIVES: To analyze the relationship between different hospital structural levels, defined according to hospital size, teaching activity and location, and the presence of length of stay (LOS) outliers. RESEARCH DESIGN: A logit model was used to analyze the patient discharge records of the acute care public hospitals' Minimum Data Set in Catalonia (Spain) in 1998. The final population contained 631,096 discharges grouped in 329 adjacent DRGs. MEASURES: LOS outliers were defined as cases with a LOS exceeding the geometric mean plus two standard deviations of all the stays in the same DRG. The 64 public hospitals of the Catalan health system were classified into large urban teaching hospitals, medium-sized teaching and community hospitals, and small community hospitals according to their structural complexity. The model also controlled for patient and health care process characteristics. RESULTS: Outliers accounted for 4.5% of total discharges distributed as follows: large urban teaching hospitals (5.6%), medium-sized teaching and community hospitals (4.6%), small community hospitals (3.6%). The probability of a patient being an outlier was higher in hospitals with greater structural complexity: large urban teaching hospitals (OR = 1.59), medium teaching and community hospitals (OR = 1.30) and small community hospitals (OR = 1). Adjustment through the control variables reduced differences among hospitals: large urban teaching hospitals (OR = 1.32), medium-sized teaching and community hospitals (OR = 1.22), and small community hospitals (OR = 1), but the differences remained significant (P < 0.01). CONCLUSIONS: Hospital structural level influences the presence of outliers even when controlling for patient and process characteristics. Thus, some outliers are due to hospital structural level and are not justified by patient characteristics.     

Hospital characteristics,rather than surgical volume,predict length of stay following colorectal cancer surgery

Objective : Length of hospital stay (LOS) is considered a vital component for successful colorectal surgery treatment. Evidence of an association between hospital surgery volume and LOS has been mixed. Data modelling techniques may give inconsistent results that adversely impact conclusions. This study applied techniques to overcome possible modelling drawbacks. Method : An additive quantile regression model formulated to isolate hospital contextual effects was applied to every colorectal surgery for cancer conducted in Victoria, Australia, between 2005 and 2015, involving 28,343 admissions in 90 Victorian hospitals. The model compared hospitals’ operational efficiencies regarding LOS. Results : Hospital LOS operational efficiencies for colorectal cancer surgery varied markedly between the 90 hospitals and were independent of volume. This result was adjusted for pertinent patient and hospital characteristics. Conclusion : No evidence was found that higher annual surgery volume was associated with lower LOS for patients undergoing colorectal cancer surgery. Our model showed strong evidence that differences in LOS efficiency between hospitals was driven by hospital contextual effects that were not predicted by provider volume. Further study is required to elucidate these inherent differences between hospitals. Implications for public health : Our model indicated improved efficiency would benefit the patient and medical system by lowering LOS and reducing expenditure by more than $3 million per year.     

Coding Response to a Case-Mix Measurement System Based on Multiple Diagnoses

Objective. To examine the hospital coding response to a payment model using a case-mix measurement system based on multiple diagnoses and the resulting impact on a hospital cost model.
Data Sources. Financial, clinical, and supplementary data for all Ontario short stay hospitals from years 1997 to 2002.
Study Design. Disaggregated trends in hospital case-mix growth are examined for five years following the adoption of an inpatient classification system making extensive use of combinations of secondary diagnoses. Hospital case mix is decomposed into base and complexity components. The longitudinal effects of coding variation on a standard hospital payment model are examined in terms of payment accuracy and impact on adjustment factors.
Principal Findings. Introduction of the refined case-mix system provided incentives for hospitals to increase reporting of secondary diagnoses and resulted in growth in highest complexity cases that were not matched by increased resource use over time. Despite a pronounced coding response on the part of hospitals, the increase in measured complexity and case mix did not reduce the unexplained variation in hospital unit cost nor did it reduce the reliance on the teaching adjustment factor, a potential proxy for case mix. The main implication was changes in the size and distribution of predicted hospital operating costs.
Conclusions. Jurisdictions introducing extensive refinements to standard diagnostic related group (DRG)-type payment systems should consider the effects of induced changes to hospital coding practices. Assessing model performance should include analysis of the robustness of classification systems to hospital-level variation in coding practices. Unanticipated coding effects imply that case-mix models hypothesized to perform well ex ante may not meet expectations ex post.     

Hospital volume and outcomes for inpatients with acute myocardial infarction in Shanxi,China: A cross‐sectional study

In this cross‐sectional study, we assessed the relationship between hospital volume and clinical outcomes for inpatients with acute myocardial infarction (AMI) in tertiary A hospitals in Shanxi, China (N = 12 931). In‐hospital mortality, length of stay (LOS), and total cost were measured. The crude in‐hospital mortality rate was 1.69%. Adjusted in‐hospital mortality was significantly lower for medium‐volume hospitals (odds ratio (OR) = 0.605, 95% confidence interval (CI) = 0.411‐0.900) compared with low‐volume hospitals. LOS in medium‐ and high‐volume hospitals were 0.915 (95% CI = 0.880‐0.951) and 1.069 (95% CI = 1.041‐1.098) days longer than in low‐volume hospitals, respectively. The cost of inpatients attending low‐ and high‐volume hospitals (OR = 1.180, 95% CI = 1.140‐1.221) was higher than that of medium‐volume hospitals (OR = 0.897, 95% CI = 0.868‐0.926). These results inform health care policy in countries with strained medical resources.     

Association of hospital resource use with comorbidity status and patient age among hip fracture patients in Japan

OBJECTIVES: This study examined the association of resource use with comorbidity status and patient age among hip fracture patients who underwent surgical treatment. DESIGN: We used a database from the Voluntary Hospitals of Japan Quality Indicator Project that involved 10 privately owned leading teaching hospitals in Japan. SETTING: Four of these hospitals in Japan. PARTICIPANTS: We selected 778 operable hip fracture patients aged 65 or older who were admitted to these hospitals between January 1996 and August 2000 (mean age: 80.3 +/- 7.3 years). MEASUREMENTS: A linear mixed model was performed to identify factors associated with the resource use, such as total length of stay (LOS), LOS before surgery, LOS after surgery, total hospital charges, charges for diagnostic examinations, charges for surgery, and length of theater time, among operable hip fracture patients. RESULTS: The mean LOS was 45.9 days, and the mean total hospital charges were US dollars 14,495.0. Results from linear mixed models revealed that higher age was significantly associated with shorter length of theater time (P < 0.01), and that the presence of comorbidity among hip fracture patients was significantly associated with longer total LOS (P < 0.01), longer LOS after surgery (P < 0.001), higher charges for diagnostic examinations (P < 0.001), and shorter length of theater time (P < 0.01). CONCLUSION: These results suggest that the presence of comorbidity among operable hip fracture patients requires greater resource use during their hospital stay, but higher age is not significantly associated with greater resource use at all.     

Beyond DRG: The effect of socio-economic indicators on inpatient resource allocation in Australia

Financing in Australia's public hospital works through the Australian Refined Diagnosis Related Groups (AR-DRGs) with separations to specific DRG groups based on medical diagnosis or surgical procedure, patient's age, mode of separation, clinical complexity and complications. This paper aims at assessing how the AR-DRGs reflect the efficiency and equity of the hospitals resource allocation. Using administrative data of all acute public hospital admissions and length of stay (LOS) as a proxy for hospital costs, this paper showed that patients’ socio-economic (SES) characteristics are a strong determinant of health care utilization. Our results revealed that the lower the SES, the longer the LOS and hence more utilization of the inpatient resources. Therefore, omitting SES from the risk adjusters list and solely focusing on DRG- based compensation penalizes hospitals catering to lower SES populations. Our findings further support the idea of smaller/remote hospitals based on block funding.     

Hospital-acquired, laboratory-confirmed bloodstream infection: increased hospital stay and direct costs.

OBJECTIVES: To determine increased hospital stay and direct costs attributable to hospital-acquired, laboratory-confirmed bloodstream infection (BSI), and to evaluate the matching variable length of stay (LOS). DESIGN: Retrospective (historical) cohort study with 1:2 matching in intensive care units and surgical wards. SETTING: A 2,000-bed university hospital in Rome, Italy. PATIENTS: All patients admitted between January 1994 and June 1995 who had hospital-acquired, laboratory-confirmed BSI were considered cases; all others were eligible as controls. METHODS: Two controls (A and B) were selected per case in a stepwise fashion. Controls in group A were selected according to the following six criteria: ward, gender, age, diagnosis, central venous catheter, and LOS equal to the interval from admission to infection in a matched case +/- 20% (LOS +/- 20%). Controls in group B were selected according to the first five criteria, but excluded LOS +/- 20%. RESULTS: One hundred five of 108 patients were each matched with two controls. The matching appropriateness score was greater than 90%. With the use of controls in groups A and B, the case-fatality rates attributable to hospital-acquired, laboratory-confirmed BSI were 35.2% and 40.9%, respectively; the estimated risk ratios for death were 2.60 and 3.52 (P = .0001), respectively. The increased hospital stay per case attributable to hospital-acquired, laboratory-confirmed BSI was 19.1 (mean) and 13.0 (median) days for matched pairs in control group A and 19.9 (mean) and 15.0 (median) days for matched pairs in control group B. With controls in group A, the cost of increased hospital stay per patient attributable to hospital-acquired, laboratory-confirmed BSI was Euro 15,413. The additional cost per patient due to treatment was Euro 943, making the overall direct cost Euro 16,356 per case. CONCLUSIONS: This study should make it possible to estimate the cost of hospital-acquired, laboratory-confirmed BSI in most hospitals after adjusting for incidence rate. It also confirmed the use of LOS +/- 20% as a matching variable to limit overestimation of increased hospital stay. To our knowledge, this is among the first such studies in Europe.     

The effects of case mix on hospital costs and revenues in managed care environments

Due to competition and managed care, hospitals have argued that the rate of increase in hospital cost is greater than the rate of increase in hospital revenue. It is important to pay hospitals based on the expected resource use of patients that hospitals treat. However, managed care organizations pay hospitals based on negotiated prices that do not consider the expected resource use of patients. The purpose of this paper is to provide a better understanding of those factors affecting hospital cost and revenue in California using the hospital financial and utilization data for selected years from 1986 to 1998. By developing case mix indexes (CMIs) using all hospital discharges in California, this study found that the coefficients for CMIs in total and inpatient hospital revenue models were greater than those in hospital cost models. Over time, however, the differences in coefficients for CMIs in hospital revenue and cost models become smaller and smaller. Thus, this study shows that the difference between hospital revenues and hospital costs, looking at hospital case mix, has decreased, although hospital revenues are still greater than hospital costs.     

用信息理论计算病例组合指数

目的 分析医院住院病人多产出组成，并进行定量测量。方法 根据信息理论，采用病例组合指数，考虑到疾病分类的权重，将18种疾病分类的出院人数转变为一个病例组合指数，从而用一个自变量代替了18个自为量。结果 医院级别不同，病例组合指数不同，且与医院病种复杂程度相符合。结论 病例组合指数作为综合衡量每个医院病种复杂性的量工，大大地减少了自为量的个数，解决了以往岭回归模型中存在的一些问题。     

Socioeconomic Status of Newborns and Hospital Efficiency: Implications for Hospital Payment Methods

ObjectivesStudies have shown a consistent impact of socioeconomic status at birth for both mother and child; however, no study has looked at its impact on hospital efficiency and financial balance at birth, which could be major if newborns from disadvantaged families have an average length of stay (LOS) longer than other newborns. Our objective was therefore to study the association between socioeconomic status and hospital efficiency and financial balance in that population.MethodsA study was carried out using exhaustive national hospital discharge databases. All live births in a maternity hospital located in mainland France between 2012 and 2014 were included. Socioeconomic status was estimated with an ecological indicator and efficiency by variations in patient LOS compared with different mean national LOS. Financial balance was assessed at the admission level through the ratio of production costs and revenues and at the hospital level by the difference in aggregated revenues and production costs for said hospital. Multivariate regression models studied the association between those indicators and socioeconomic status.ResultsA total of 2 149 454 births were included. LOS was shorter than the national means for less disadvantaged patients and longer for the more disadvantaged patients, which increased when adjusted for gestational age, birth weight, and severity. A 1% increase in disadvantaged patients in a hospital’s case mix significantly increased the probability that the hospital would be in deficit by 2.6%.ConclusionsReforms should be made to hospital payment methods to take into account patient socioeconomic status so as to improve resource allocation efficiency.     

Factors influencing hospital high length of stay outliers

ABSTRACT: BACKGROUND: The study of length of stay (LOS) outliers is important for the management and financing of hospitals. Our aim was to study variables associated with high LOS outliers and their evolution over time. METHODS: We used hospital administrative data from inpatient episodes in public acute care hospitals in the Portuguese National Health Service (NHS), with discharges between years 2000 and 2009, together with some hospital characteristics. The dependent variable, LOS outliers, was calculated for each diagnosis related group (DRG) using a trim point defined for each year by the geometric mean plus two standard deviations. Hospitals were classified on the basis of administrative, economic and teaching characteristics. We also studied the influence of comorbidities and readmissions. Logistic regression models, including a multivariable logistic regression, were used in the analysis. All the logistic regressions were fitted using generalized estimating equations (GEE). RESULTS: In near nine million inpatient episodes analysed we found a proportion of 3.9 % high LOS outliers, accounting for 19.2 % of total inpatient days. The number of hospital patient discharges increased between years 2000 and 2005 and slightly decreased after that. The proportion of outliers ranged between the lowest value of 3.6 % (in years 2001 and 2002) and the highest value of 4.3 % in 2009. Teaching hospitals with over 1,000 beds have significantly more outliers than other hospitals, even after adjustment to readmissions and several patient characteristics. CONCLUSIONS: In the last years both average LOS and high LOS outliers are increasing in Portuguese NHS hospitals. As high LOS outliers represent an important proportion in the total inpatient days, this should be seen as an important alert for the management of hospitals and for national health policies. As expected, age, type of admission, and hospital type were significantly associated with high LOS outliers. The proportion of high outliers does not seem to be related to their financial coverage; they should be studied in order to highlight areas for further investigation. The increasing complexity of both hospitals and patients may be the single most important determinant of high LOS outliers and must therefore be taken into account by health managers when considering hospital costs.     

Measuring outpatient resource use and case mix in ophthalmology in north east England

OBJECTIVES: To test the extent to which two existing ambulatory case mix measures (Ambulatory Visit Groups and Ambulatory Patient Groups) and other variables can explain resource use variations in ophthalmic outpatient visits. DESIGN: Three week prospective study of three consultant outpatient clinics. SETTING: One ophthalmic hospital (Sunderland Eye Infirmary, Sunderland, Tyne and Wear) and three outreach clinics (South Tyneside District Hospital, South Shields, Tyne and Wear; Dryburn Hospital, Durham, Co Durham; and Hartlepool General Hospital, Hartlepool, Cleveland). SUBJECTS: 325 patients who visited ophthalmic outpatient clinics. MAIN OUTCOME MEASURES: Mean consultation time and mean cost distributions by case mix group, analysed by analysis of variance. RESULTS: Ambulatory case mix measures can explain some of the variation in resource use for outpatient visits, but different measures differ in the extent to which they can do so. Clinicians' behaviour also accounts for a significant amount of such variation. Simpler measures of visit type, without diagnostic or procedure information, do not explain resource use variations. CONCLUSIONS: Existing measures perform reasonably well, but their data requirements may preclude their introduction in the National Health Service. Caution is required in advocating simpler measures, however. The influence of clinical practice on resource use variations is important; in this study, most differences between clinicians were not attributable to differences in case mix.

 

     

Improving the forecasting of hospital services: A comparison between projections and actual utilization of hospital services

ObjectivesTo compare projected and observed hospital inpatient use in Belgium and to draw lessons from that comparison.MethodsIn 2005, projections for hospital service use were generated up to 2015, based on demographic change, substitution from inpatient to day care, and, the evolution of the average length of stay (LOS). The accuracy of the forecasts was assessed by comparing projected and observed population size, admissions and inpatient days, average LOS and percentage change in case mix.ResultsThe demographic growth was underestimated. Overall, the baseline projection for hospital admissions was remarkably close to the observed figures but the underlying case mix diverged importantly. With substitution between inpatient and day care, the number of admissions was underestimated by 15%–40%. The number of days was projected to increase in every scenario, whereas a decreasing trend was observed mainly due to the faster decline in average LOS than projected.ConclusionHospital capacity planning is an important component of evidence informed policymaking. Projection results benefit from a well-designed methodology: choice of forecast groups, estimation models, selection criteria, and a sensitivity analysis of the results. To cope with the dynamic and continuously evolving context in which hospitals operate, regular updates to incorporate new data and to reassess estimated trends should be an integral part of the projection framework.     

Resource utilization among patients with sepsis syndrome.

OBJECTIVE: To assess the resource utilization associated with sepsis syndrome in academic medical centers. DESIGN: Prospective cohort study. SETTING: Eight academic, tertiary-care centers. PATIENTS: Stratified random sample of 1,028 adult admissions with sepsis syndrome and all 248,761 other adult admissions between January 1993 and April 1994. The main outcome measures were length of stay (LOS) in total and after onset of sepsis syndrome (post-onset LOS) and total hospital charges. RESULTS: The mean LOS for patients with sepsis was 27.7 +/- 0.9 days (median, 20 days), with sepsis onset occurring after a mean of 8.1 +/- 0.4 days (median, 3 days). For all patients without sepsis, the LOS was 7.2 +/- 0.03 days (median, 4 days). In multiple linear regression models, the mean for patients with sepsis syndrome was 18.2 days, which was 11.0 days longer than the mean for all other patients (P < .0001), whereas the mean difference in total charges was $43,000 (both P < .0001). These differences were greater for patients with nosocomial as compared with community-acquired sepsis, although the groups were similar after adjusting for pre-onset LOS. Eight independent correlates of increased post-onset LOS and 12 correlates of total charges were identified. CONCLUSIONS: These data quantify the resource utilization associated with sepsis syndrome, and demonstrate that resource utilization is high in this group. Additional investigation is required to determine how much of the excess post-onset LOS and charges are attributable to sepsis syndrome rather than the underlying medical conditions.     

Strategic responses by hospitals to increased financial risk in the 1980s.

OBJECTIVE. This research addresses the following types of responses by hospitals to increased financial risk: (a) increases in prices to privately insured patients (testing separately the effects of risk from the effects of "cost-shifting" that depends on level of Medicare payment in relation to case mix-adjusted cost); (b) changes in service mix offered and selectivity in acceptance of patients to reduce risk; and (c) efforts to reduce variation in resource use for those patients admitted. DATA SOURCES. The database includes a national panel of over 400 hospitals providing information from patient discharge abstracts, hospital financial reports, and county level information over the period 1980-1987. STUDY DESIGN. Econometric methods suitable to panel data are implemented, with tests for pooling, hospital-specific fixed effects, and possible problems of selection bias. PRINCIPAL FINDINGS. The prices paid by private insurers to a particular hospital were affected by the changes in risk imposed by Medicare prospective payment, the generosity of Medicare payment, state rate regulation, and ability of the hospital to bear risk. The risk-weighted measure of case mix did not respond to changes in payment policy, but other variables reflecting the management of care after admission to reduce risk did change in the predicted directions. CONCLUSIONS. Some of the findings in this article are relevant to current Medicare policies that involve risk-sharing, for instance, special allowances for "outlier" patients with unusually high cost, and for sole community hospitals. The first type of allowance appears successful in preserving access to care, while the second type is not well justified by the findings. State rate regulation programs were associated not only with lower hospital prices but also with less risk reduction behavior by hospitals. The design of regulation as a sort of risk-pooling arrangement across payers and hospitals may be attractive to hospitals and help explain their support for regulation is some states.     

Does severity explain differences in hospital length of stay for pneumonia patients?

OBJECTIVES: In the USA, the role of patient severity in determining hospital resource use has been questioned since Medicare adopted prospective hospital payment based on diagnosis-related groups (DRGs). Exactly how to measure severity, however, remains unclear. We examined whether assessments of severity-adjusted hospital lengths of stay (LOS) varied when different measures were used for severity adjustment. METHODS: The complete study sample included 18,016 patients receiving medical treatment for pneumonia at 105 acute care hospitals. We studied 11 severity measures, nine based on patient demographic and diagnosis and procedure code information and two derived from clinical findings from the medical record. For each severity measure, LOS was regressed on patient age, sex, DRG, and severity score. Analyses were performed on trimmed and untrimmed data. Trimming eliminated cases with LOS more than three standard deviations from the mean on a log scale. RESULTS: The trimmed data set contained 17,976 admissions with a mean (S.D.) LOS of 8.9 (6.1) days. Average LOS ranged from 5.0-11.8 days among the 105 hospitals. Using trimmed data, the 11 severity measures produced R-squared values ranging from 0.098-0.169 for explaining LOS for individual patients. Across all severity measures, predicted average hospital LOS varied much less than the observed LOS, with predicted mean hospital LOS ranging from about 8.4-9.8 days. DISCUSSION: No severity measure explained the two-fold differences among hospitals in average LOS. Other patient characteristics, practice patterns, or institutional factors may cause the wide differences across hospitals in LOS.     

Hospital Length of Stay: Social Work Services as an Important Factor

In earlier studies it was found that the severity of patients' psychosocial problems was a significant predictor of length of stay (LOS). This current study compared predictors of LOS for samples of patients referred to social services in three large urban hospitals in June–October 2002 (n?=?176) and 2006 (n?=?147), and examined changes in patient characteristics and the nature of social work practice. A significant relationship between psychosocial severity and LOS was again found, confirming the important role that social services can potentially play in controlling hospital costs. Some significant changes were also found in the pattern of social work practice; this was generally in the direction of more community consultation and collaboration, suggesting a greater emphasis on multidisciplinary teamwork.