Variation In Length Of Hospital Research Articles

Pediatric Complex Chronic Condition System Version 3

Since implementation of the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the US, thousands of new or related codes have been added to represent clinical conditions. The widely used pediatric complex chronic condition (CCC) system required a major update from version 2 (V2) to version 3 (V3) to capture the range of clinical conditions represented in the ICD-10-CM. To update the CCC V3 system, creating V3, with new, missing, or retired codes; to reconceptualize the system's use of technology codes; and to compare CCC V3 with V2. This repeated cross-sectional study examined US hospitalization data from the Pediatric Health Information System (PHIS) and the Medicaid Merative MarketScan Research Databases from January 1, 2009, to December 31, 2019, for all patients aged 0 to 18 years. Data were analyzed from March 1, 2023, to April 1, 2024. The CCCs were identified in both data sources using the CCC V2 and V3 systems. The (1) percentage of pediatric hospitalizations associated with a CCC, (2) numbers of CCC body-system categories per patient, and (3) explanatory power for hospital length of stay and in-hospital mortality were compared over time for V3 vs V2. Among 7 186 019 hospitalizations within PHIS, 54.3% patients were male, the median age was 4 years (IQR, 1-11 years), and 51.2% were aged 0 to 4 years). The CCC V2 identified 2 878 476 (40.1%) patients as having any CCC compared with 2 753 412 (38.3%) identified by V3. In addition, V2 identified 100 065 (1.4%) patients with transplant status compared with 146 683 (2.0%) by V3, and V2 identified 914 835 (12.7%) as having technology codes compared with 805 585 (11.2%) by V3. The 2 systems were similar in accounting for the number of CCC body-system categories per patient and in explaining variation in hospital length of stay and in-hospital mortality. For both V2 and V3, 10.0% of the variance in hospital length of stay and 12.0% of the variance in in-hospital mortality was explained by the presence of a CCC. Similar patterns were observed when analyzing the 2 999 420 Medicaid Merative MarketScan Research Databases' hospitalizations (52.3% of patients were male, the median age was 1 year [IQR, 0-12 years], and 62.0% were 0 to 4 years old), except that the percentages of identified CCCs were all lower: V2 identified 758 110 hospitalizations (25.3%) with any CCC compared with 718 100 (23.9%) identified by V3. These results suggest that, moving forward, V3 should be used to identify CCCs, and ongoing, frequent updates to V3, using a transparent, structured process, will enable V3 to accurately reflect the evolving spectrum of clinical conditions represented in the ICD-10-CM.

Association Between Race and Receipt of Home- and Community-Based Rehabilitation After Traumatic Brain Injury Among Older Medicare Beneficiaries

Non-Hispanic Black (hereafter Black) patients with traumatic brain injury (TBI) experience worse long-term outcomes and residual disability compared with non-Hispanic White (hereafter White) patients. Receipt of appropriate rehabilitation can improve function among older adults after TBI. To assess the association between race and receipt of home- and community-based rehabilitation among a nationally representative sample of older Medicare beneficiaries with TBI. This cohort study analyzed a random sample of Medicare administrative claims data for community-dwelling Medicare beneficiaries aged 65 years or older who were hospitalized with a primary diagnosis of TBI and discharged alive to a nonhospice setting from 2010 through 2018. Claims data for Medicare beneficiaries of other races and ethnicities were excluded due to the small sample sizes within each category. Data were analyzed January 21 to August 30, 2022. Black or White race. Monthly use rates of home-based or outpatient rehabilitation were calculated over the 6 months after discharge from the hospital. The denominator for rate calculations accounted for variation in length of hospital and rehabilitation facility stays and loss to follow-up due to death. Rates over time were modeled using generalized estimating equations, controlling for TBI acuity, demographic characteristics, comorbidities, and socioeconomic factors. Among 19 026 Medicare beneficiaries (mean [SD] age, 81.6 [8.1] years; 10 781 women [56.7%]; and 994 Black beneficiaries [5.2%] and 18 032 White beneficiaries [94.8%]), receipt of 1 or more home health rehabilitation visits did not differ by race (Black vs White, 47.4% vs 46.2%; P = .46), but Black beneficiaries were less likely to receive 1 or more outpatient rehabilitation visits compared with White beneficiaries (3.4% vs 7.1%; P < .001). In fully adjusted regression models, Black beneficiaries received less outpatient therapy over the 6 months after TBI (rate ratio, 0.60; 95% CI, 0.38-0.93). However, Black beneficiaries received more home health rehabilitation therapy over the 6 months after TBI than White beneficiaries (rate ratio, 1.15; 95% CI, 1.00-1.32). This cohort study found relative shifts in rehabilitation use, with markedly lower outpatient therapy use and modestly higher home health care use among Black patients compared with White patients with TBI. These disparities may contribute to reduced functional recovery and residual disability among racial and ethnic minority groups. Additional studies are needed to assess the association between the amount of outpatient rehabilitation care and functional recovery after TBI in socioeconomically disadvantaged populations.

A panel data model of length of stay in hospitals for hip replacements

Inequality between private and public patients in Australia has been an ongoing concern due to its two tiered insurance system. This article investigates the variations in hospital length of stay for hip replacements using the Victorian Admitted Episodes Dataset from 2003/2004 to 2014/2015, employing a Bayesian hierarchical random coefficients model with trend. We find systematic differences in the length of stay between public and private hospitals, after observable patient complexity is controlled. This suggests shorter stays in public hospitals due to pressure from the Activity-based funding scheme, and longer stays in private system due to potential moral hazard. Our counterfactual analysis shows that public patients stay 1.8 days shorter than private patients in 2014, which leads to the “quicker but sicker” concern that is commonly voiced by the public. We also identify widespread variations among individual hospitals. Sources for such variation warrant closer investigation by policy makers.

A Description of Children Dependent on Long Term Ventilation via Tracheostomy and Their Hospital Resource Use

PurposeTo describe the proportion of children with an index hospitalization in 2014 who had established long-term invasive ventilator dependence (LTVD), and determine regional variation in hospital length of stay, charges, and readmissions. Design and methodsMulticenter, longitudinal, retrospective cohort study using a recently established algorithm to identify children with LTVD from the Pediatric Health Information System database with an index hospitalization at least once during 2014, excluding normal newborn care or chemotherapy, and the subset with established LTVD. Hospitals were grouped by geographic regions. Analysis included descriptive statistics and multi-variable mixed modeling for length of stay, charges, and readmissions. ResultsOf the 615,883 unique children discharged from 45 children's hospitals in 2014, 2235 (0.4%) had established LTVD. Of these, 342 (15%) were hospitalized in the Northeast, 677 (30%) Midwest, 733 (32%) South and 481 (22%) West. Most had at least two complex chronic conditions (97%) and used a medical device for at least two body systems (71%). No statistically significant regional variation was found for length of stay, charges, or readmissions after adjustment for child demographics, admission type, disposition, primary diagnosis, ICU stay, and number of chronic conditions. ConclusionsThis study characterized the population of children with LTVD hospitalized in 2014. No regional variation was found for length of stay, charges, or readmissions. Practice implicationsChildren with established LTVD make up a small subset of all children admitted to children's hospitals however, they require substantial, costly, multifaceted care as most have additional complex chronic conditions and require multiple medical devices.

Variation in Hospital Length of Stay Based on Hospital Volume: A Retrospective Cohort Study of Emergency Abdominal Surgery in Ireland

Objectives: Emergency abdominal surgery (EAS) refers to high risk intra-abdominal surgical procedures associated with increased mortality risk and long length of hospital stay. The variation between hospital volume and hospital length of stay (LOS) of patients undergoing EAS is poorly understood. Our objective was to explore this relationship across public hospitals in Ireland. Methods: Data for all adult episode discharges from public Irish hospitals in 2014-2017 were obtained from National Quality Assurance Improvement System (NQAIS) Clinical with EAS identified by primary procedure codes. Hospitals were categorised into low (n&lt;200), medium (n=200-400), and high (n&gt;400) volume groups based on the number of EAS episodes during the study period. Negative binomial regression models were applied to standardise for patient case mix. Several adjusted LOS measures were compared across the three volume groups. Sensitivity analysis was conducted to test the robustness of our findings. Results: 8120 hospital episodes across 24 public hospitals providing EAS services were analysed. 7 were categorised as low, 9 as medium, and 8 as high-volume hospitals. High volume hospitals had a significantly longer adjusted LOS (24.7 days) relative to low and medium volume hospitals (18.2 and 18.6 days). Sensitivity analysis consisted of the exclusion of the following hospital episodes: in-hospital death, cancer diagnosis, Charlson comorbidity index (CCI) &gt;0, admission from other hospitals, and discharge to other hospitals. No single variable influenced the observed LOS variation, although when the more complex episodes were excluded, the post-operative LOS at low and medium volume hospitals was significantly shorter compared to high volume hospitals (by 1.1-6.1 days). Intensive care unit (ICU) LOS was similar in all three hospital volume groups although low volume hospitals appeared to have more ICU admissions and longer stay (by up to 1.6 days). Conclusions: Our findings indicate that patients treated at low volume hospitals have shorter LOS and may be discharged earlier than from high volume hospitals. This finding is surprising, suggesting that concentration of services to larger clinical departments may not necessarily reduce LOS and improve the efficiency of resource utilisation and service delivery.

The impact of primary care management and comorbidities of COPD on length of hospital stay

IntroductionHealth Resource Groups (HRGs) are bundles of care that absorb similar financial resources. Variations in hospital length of stay (LOS) of patients with the same admission diagnosis and assigned HRG may reflect differences in pre-admission primary care services received by patients.&#x0D; Objectives and ApproachWe investigated whether within HRGs, variations of LOS of chronic obstructive pulmonary disease (COPD) admissions were associated with differences in COPD management services received in primary care. Individual-level primary and secondary care data from the Secure Anonymised Information Linkage (SAIL) databank of Wales was used for admissions in 2015 with high-volume (n&gt;30) HRGs. Effects of selected COPD primary care quality surrogate measures and comorbidities on LOS were analysed using a linear regression model adjusted for a modified Charlson co-morbidity index. The effect of completed pulmonary rehabilitation (PR) was analysed in a separate dataset for the Cwm Taf Health Board.&#x0D; ResultsWe included 77,791 COPD patients, with mean age of 73.4 [SD=11.0], and 51.6% of which were males. Patients who were referred for a PR course prior to admission stayed 0.58 less days (95% CI = [0.18, 0.98], p&lt;0.01), while those who completed a PR course stayed 0.76 less days ([0.25, 1.27], p&lt;0.01). Non-significant associations were found where female patients stayed 0.34 days longer than males ([-0.01, 0.68], p=0.05), patients given flu vaccination stayed 0.39 less days ([-0.07, 0.86], p=0.10), and patients with anxiety diagnosis stayed 0.43 more days ([-0.03, 0.88], p=0.06).&#x0D; Conclusion/ImplicationsLOS for COPD could potentially be reduced with further targeted services provided in primary care. Countries using HRGs with access to linked primary and secondary care data can unlock care insights, enabling live monitoring of the effectiveness of primary care interventions. This approach can be also used for other conditions.

Variation in length of hospital stay after lung cancer surgery in the Netherlands.

Length of stay (LOS) in the hospital after lung cancer surgery is influenced by patient characteristics, tumour characteristics, surgical technique and perioperative care. Our objective was to determine whether there were variation in LOS between hospitals that could not be accounted for by these known parameters. Residual variation in LOS would suggest important differences in perioperative care protocols and discharge criteria. This study analysed data from the Netherlands National Cancer Registry (NNCR) on 10195 anatomical lung resections for primary lung cancer from 2010 to 2015. Multivariable analysis was performed for multiple factors, using hierarchical linear regression analysis of the mean LOS. Information on comorbidity and socio-economic status was not available. Association between LOS and postoperative mortality was evaluated in multivariable logistic regression. The median LOS was 7 days (interquartile range 5-10 days), and the mean LOS was 8.3 days. LOS was negatively affected by larger resections, open surgery and advancing age. Histology and tumour stage had little influence. Overall, 30-day and 90-day mortality were 2.1% and 3.8%, respectively; 1.7% and 3.3% (not significant) in the group of hospitals with shorter LOS. After case-mix correction, residual between-hospital variation in the mean LOS was observed, ranging from 1.5 days shorter to almost 2.5 days longer. A clinically relevant between-hospital variation in LOS after lung cancer surgery is observed in the Netherlands. Although residual confounding by comorbidity or socio-economic status cannot be excluded, this variation is deemed to be largely due to differences in perioperative care protocols. Evaluation of best practices can help to improve perioperative care for lung surgery patients and optimize LOS.

Predicting hospital length of stay and short-term function after hip or knee arthroplasty: are both performance and comorbidity measures useful?

Variations in hospital length of stay (LOS) and function are present after hip or knee arthroplasty. Comorbidity and performance measures have been associated with post-operative outcomes. It is however not known if both independently contribute to outcome prediction. The objective of this study was to evaluate the combined predictive ability of comorbidity scores (American Society of Anesthesiologists classification system (ASA), Charlson comorbidity index (CCI), 2008 version of the CCI (CCI08)) and a performance measure (Timed-Up-and-Go (TUG)) on LOS and short-term function in patients undergoing knee or hip arthroplasty. One hundred eight patients undergoing hip or knee arthroplasty were assessed preoperatively with the ASA, CCI, CCI08, and TUG. LOS was determined through administrative data. The Older Americans Resources and Services ADL questionnaire (OARS) was used to assess function two and sixweeks after surgery. Logistic regression was used to assess the relationship between pre-operative assessments and LOS and OARS scores. Both the ASA and TUG significantly contributed to LOS prediction. Odds ratio (OR) was 3.57 (95% confidence interval (CI) 1.26-10.07) for the ASA, and 2.18 (95% CI 1.67-4.15) for a one-standard deviation (SD) increase of 4.45s of the TUG. Only the TUG was predictive of twoweeks function and trending towards significance for sixweeks function. One SD TUG increase yielded an OR of 2.14 (95% CI 1.53-3.79) for twoweek function. The TUG and ASA can be used pre-operatively in combination to predict LOS, and TUG can also be used to predict short-term post-operative function.

A Panel Data Analysis of Hospital Variations in Length of Stay for Hip Replacements: Private Versus Public

Inequality between private and public patients in Australia has been an ongoing concern due to its two tiered insurance system. This paper investigates the variations in hospital length of stay for hip replacements using Victorian Admitted Episodes Dataset from 2003/2004 to 2014/2015, employing a Bayesian hierarchical random coefficient model with trend allowing for structural break. We find systematic differences in the length of stay between public and private hospitals, after observable patient complexity is controlled. This suggests shorter stay in public hospitals due to pressure from Activity-based funding scheme, and longer stay in private system due to potential moral hazard. Our counterfactual analysis shows that public patients stay 1.4 days shorter than private in 2014, which leads to the 'quicker but sicker' concern that is commonly voiced by the public. We also identify widespread variations among individual hospitals. Sources for such variation warrant closer investigation by policy makers.

Understanding variation in length of hospital stay for COPD exacerbation: European COPD audit.

Chronic obstructive pulmonary disease (COPD) care across Europe has high heterogeneity with respect to cost and the services available. Variations in length of stay (LOS) may be attributed to patient characteristics, resource and organisational characteristics, and/or the so-called hospital cluster effect.The European COPD Audit in 13 countries included data from 16 018 hospitalised patients. The recorded variables included information on patient and disease characteristics, and resources available. Variables associated with LOS were evaluated by a multivariate, multilevel analysis.Mean±sd LOS was 8.7±8.3 days (median 7 days, interquartile range 4–11 days). Crude variability between countries was reduced after accounting for clinical factors and the clustering effect. The main factors associated with LOS being longer than the median were related to disease or exacerbation severity, including GOLD class IV (OR 1.77) and use of mechanical ventilation (OR 2.15). Few individual resource variables were associated with LOS after accounting for the hospital cluster effect.This study emphasises the importance of the patients' clinical severity at presentation in predicting LOS. Identifying patients at risk of a long hospital stay at admission and providing targeted interventions offers the potential to reduce LOS for these individuals. The complex interactions between factors and systems were more important that any single resource or organisational factor in determining differences in LOS between hospitals or countries.

Ethnic variations in length of hospital stay in patients with atrial fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia seen in clinical practice, which places affected patients at an increased risk of mortality, heart failure and thromboembolic events [1,2]. It is a major global burden on the health care system with evidence suggesting an increasing incidence and prevalence [3–5]. A systematic review of world-wide population-based studies (n=184) has revealed that the age-adjusted prevalence and incidence rates of AF have increased in 2010 compared to 1990 [5].

무릎관절치환술 환자의 중증도 보정 재원일수 모형 개발

This study was conducted to develop a severity-adjusted LOS(Length of Stay) model for knee replacement patients and identify factors that can influence the LOS by using the Korean National Hospital Discharge in-depth Injury Survey data. The comorbidity scoring systems and data-mining methods were used to design a severity-adjusted LOS model which covered 4,102 knee replacement patients. In this study, a decision tree model using CCS comorbidity scoring index was chosen for the final model that produced superior results. Factors such as presence of arthritis, patient sex and admission route etc. influenced patient length of stay. And there was a statistically significant difference between real LOS and adjusted LOS resulted from health-insurance type, bed size, and hospital location. Therefore the policy alternative on excessive medical utilization is needed to reduce variation in length of hospital stay in patients who undergo knee replacement.

Variation in length of stay within and between hospitals

Background and objective: Variation in the delivery of health care services and the lack of association between greater utilization and higher quality care signal inefficient, low value care. The extent to which patient and hospital variables can explain variation in hospital length of stay is unclear. Methods: We examined hospital inpatient length of stay using data from 684 hospitals and 5.4 million discharges in the 2007 Healthcare Cost and Utilization Project’s Nationwide Inpatient Sample. We used a mixed effects model with a random effect for hospitals to quantify variation in length of stay due to differences within and between hospitals. Results: The interquartile range of hospital mean LOS was 3.4 days (3.3-6.7). Fifty-nine percent of the overall variation in length of stay remained unexplained after adjustment for discharge-level disease status, illness-severity, regional poverty, hospital-level contextual factors (e.g. proportion of patients from low-income ZIP-codes, proportion uninsured), and structural variables (e.g. teaching status, urban or rural location). Seventy-seven percent of the explainable variation was due to differences between hospitals. Conclusion: These findings indicate that wide variability in length of stay persists after adjustment for patient and hospital variables, signaling an opportunity for improved productivity and efficiency in the delivery of health care.

Inter-hospital variation in length of hospital stay after ST-elevation myocardial infarction: results from the Belgian STEMI registry

Objective The aim of this paper was to assess the determinants of and variations in length of hospital stay (LOS) in Belgium after ST-elevation myocardial infarction (STEMI).Methods and results Data on LOS were collected from 2079 STEMI patients who were discharged alive from 33 Belgian hospitals (21 with PCI facilities) during 2010-2011. Early discharge was defi ned as hospital discharge within 4 days after admission, and the hospitals were clustered according to their LOS for low-risk patients. Determinants of LOS were calculated by means of a negative binomial regression model. LOS was, on average, 6.5 days with a median of 5 days (IQR 4). Baseline risk profi les and reperfusion treatment explained only 13% of the LOS variation. Additional analysis revealed major in-hospital variations independent of the case mix of patients. For comparable baseline risk profi les, the average LOS in a cluster of 11 hospitals with short discharge policies was 5.3 ± 5.6 days, with an early discharge rate of 58%, while in the cluster of 11 hospitals with long discharge policies, the average LOS was 7.9 ± 8.5 days with an early discharge rate of 22% (P < 0.0001). Among the clustered hospitals, there were no differences with regard to logistics (PCI facility, academic affi liation) or volume of STEMI patients. The 1-month mortality rate was less than 0.5% in the different clusters of hospitals (p= NS).Conclusions Length of hospital stay is not only determined by baseline risk profi les of patients but is also highly dependent on hospital discharge policy, which seems to be unrelated to medical or logistical factors.

Inter-hospital variation in length of hospital stay after ST-elevation myocardial infarction: results from the Belgian STEMI registry.

Length of hospital stay is not only determined by baseline risk profiles of patients but is also highly dependent on hospital discharge policy, which seems to be unrelated to medical or logistical factors.

Socio-Demographic Variation in Hospital Length of Stay and Clinical Outome in Patients Hospitalized With Acute Coronary Syndrome

Socio-Demographic Variation in Hospital Length of Stay and Clinical Outome in Patients Hospitalized With Acute Coronary Syndrome

CT13 PREVENTION OF ATRIAL FIBRILLATION AFTER CABG WITH OMEGA‐3 POLYUNSATURATED FATTY ACIDS

Purpose Atrial fibrillation (AF) is a common complication of cardiothoracic surgery, occurring in more than 30% of patients undergoing CABG. Postoperative AF results in thromboembolic events, haemodynamic compromise and an increase in length and cost of hospitalisation. Any intervention that reduces the incidence of postoperative AF should result in fewer complications in addition to being of important economic benefit. Increased consumption of oily fish or Omega‐3 Polyunsaturated Fatty Acid (PUFA) supplements substantially lowers the risk of sudden cardiac death and myocardial infarction both in primary and secondary prevention trials, through a reduction in fatal arrhythmias. Omega‐3 PUFAs may also play a role in the treatment of AF as shown by cell culture research, animal models and a recent prospective observation study in 5000 elderly adults. With respect to postoperative AF, a recent Italian randomized controlled study in 160 patients showed that Omega‐3 PUFA administration during hospitalisation in patients undergoing CABG reduced the incidence of postoperative AF by 54% and led to a shorter hospital stay.Methodology We have undertaken a randomized, placebo controlled, prospective trial of Omega‐3 PUFAs in patients undergoing CABG to examine its effect on the incidence of AF within 30 days and variations in length of hospital stay. We have also developed a clinically relevant measurement of the concentrations of the PUFA arachidonic acid and the omega‐3 fatty acids eicosapentaenoic acid and docosahexaenoic acid in patients with and without atrial fibrillation.Results We are presenting interim results of the first 80 patients enrolled in the trial.

Variation in hospital length of stay: do physicians adapt their length of stay decisions to what is usual in the hospital where they work?

To test the hypothesis that physicians who work in different hospitals adapt their length of stay decisions to what is usual in the hospital under consideration. Secondary data were used, originating from the Statewide Planning and Research Cooperative System (SPARCS). SPARCS is a major management tool for assisting hospitals, agencies, and health care organizations with decision making in relation to financial planning and monitoring of inpatient and ambulatory surgery services and costs in New York state. Data on length of stay for surgical interventions and medical conditions (a total of seven diagnosis-related groups [DRGs]) were studied, to find out whether there is more variation between than within hospitals. Data (1999, 2000, and 2001) from all hospitals in New York state were used. The study examined physicians practicing in one hospital and physicians practicing in more than one hospital, to determine whether average length of stay differs according to the hospital of practice. Multilevel models were used to determine variation between and within hospitals. A t-test was used to test whether length of stay for patients of each multihospital physician differed from the average length of stay in each of the two hospitals. There is significantly (p<.05) more variation between than within hospitals in most of the study populations. Physicians working in two hospitals had patient lengths of stay comparable with the usual practice in the hospital where the procedure was performed. The proportion of physicians working in one hospital did not have a consistent effect for all DRGs on the variation within hospitals. Physicians adapt to their colleagues or to the managerial demands of the particular hospital in which they work. The hospital and broader work environment should be taken into account when developing effective interventions to reduce variation in medical practice.

Primary health care and hospital interactions: Effects for hospital length of stay

Norwegian healthcare services are divided between primary and secondary care providers. A growing problem is that every third patient of 75 years of age or more experiences an extended stay in a somatic hospital while waiting to be sent to primary healthcare services. The interaction between these two levels of healthcare services is analysed to examine the effect on a patient's length of stay in hospital. Recent studies have asserted that research on length of stay in hospital should include influential factors such as system variation and system characteristics, in addition to standardizing for case-mix. New organizational routines are identified in 50 Norwegian somatic hospitals. A multivariate linear regression is used in both a static and a dynamic model to explain variations in hospital length of stay and in additional length of stay (5% of stays are defined as outliers). The study shows that newly specialized structures constructed to enhance the interaction between the two levels have had no effect. Length of stay is dependent on the capacity of the primary healthcare provider and on the share of elderly in the hospital catchment area, the type of patients, the procedure performed, and the characteristics of the hospital. Variation in length of stay between hospitals is primarily explained by the capacity of primary healthcare providers. However, some support is found in the dynamic model that introduces the proposition that a hospital-owned hotel would decrease the length of stay of patients in hospital.

Variation in hospital length of stay in patients with acute myocardial infarction undergoing primary angioplasty and the need to change the diagnostic-related group system

Our findings show significant variation in length of hospital stay among patients with acute myocardial infarction treated with primary percutaneous coronary intervention; length of stay can be predicted from baseline clinical and angiographic characteristics. Our investigation suggests the need for a multi-tier diagnostic-related group system for patients with acute myocardial infarction treated with percutaneous coronary intervention.