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Journal articles on the topic 'Hospital utilization'

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Published: 4 June 2021

Last updated: 29 July 2024

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1

INGLIS, ABBY L., JOANNA COAST, SELENA F. GRAY, TIM J. PETERS, and STEPHEN J. FRANKEL. "Appropriateness of Hospital Utilization." Medical Care 33, no. 9 (September 1995): 952–57. http://dx.doi.org/10.1097/00005650-199509000-00006.

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2

Black, Charlyn D., Noralou P. Roos, and Charles A. Burchill. "Utilization of Hospital Resources." Medical Care 33, SUPPLEMENT (December 1995): DS55—DS72. http://dx.doi.org/10.1097/00005650-199512001-00008.

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3

Weinkam, J. J., W. Rosenbaum, and T. D. Sterling. "Smoking and hospital utilization." Social Science & Medicine 24, no. 11 (January 1987): 983–86. http://dx.doi.org/10.1016/0277-9536(87)90292-9.

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4

Lally, John, Yim Lun Wong, Hitesh Shetty, Anita Patel, Vivek Srivastava, Matthew T. M. Broadbent, and Fiona Gaughran. "Acute hospital service utilization by inpatients in psychiatric hospitals." General Hospital Psychiatry 37, no. 6 (November 2015): 577–80. http://dx.doi.org/10.1016/j.genhosppsych.2015.07.006.

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5

Kahn, Jeremy M., Rachel M. Werner, Shannon S. Carson, and Theodore J. Iwashyna. "Variation in Long-Term Acute Care Hospital Use After Intensive Care." Medical Care Research and Review 69, no. 3 (February 6, 2012): 339–50. http://dx.doi.org/10.1177/1077558711432889.

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Long-term acute care hospitals (LTACs) are an increasingly common discharge destination for patients recovering from intensive care. In this article the authors use U.S. Medicare claims data to examine regional- and hospital-level variation in LTAC utilization after intensive care to determine factors associated with their use. Using hierarchical regression models to control for patient characteristics, this study found wide variation in LTAC utilization across hospitals, even controlling for LTAC access within a region. Several hospital characteristics were independently associated with increasing LTAC utilization, including increasing hospital size, for-profit ownership, academic teaching status, and colocation of the LTAC within an acute care hospital. These findings highlight the need for research into LTAC admission criteria and the incentives driving variation in LTAC utilization across hospitals.

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6

AL- Modaifi Al-Zahrani, Jamilah Ghurmallah Mohammed, Seita M. ALMANDEEL, and Abdullah Abdulmohsen Al-Sabaani Alshehri. "Health Care Professionals’ Perception of Appropriateness of Hospital Resources Utilization: A Cross-Sectional Study in Asser Region, Saudi Arabia." International Journal of Health Sciences and Research 13, no. 3 (March 6, 2023): 69–74. http://dx.doi.org/10.52403/ijhsr.20230307.

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Background: The most expensive component of modern health care services is Hospital resources. The inappropriate use of these hospital resources is the main challenge faced by various hospitals globally. Aim: The study aimed to assess the utilization of hospital resources in all healthcare sectors (M.O.H., military, and private) in the Aseer-region of Saudi Arabia hospitals. It also determines the most influencing factors behind inappropriateness in resource utilization. Method: A structured, self-administered questionnaire was distributed among 380 healthcare workers to assess socio-demographic, utilization data, and influencing factors behind inappropriate resource utilization. The data obtained were analyzed using SPSS software at a level of significance p<0.05. Results: The study showed that nearly half of healthcare professionals found resources utilized inappropriately among different healthcare sectors and more determined in central hospital departments as emergency department & intensive care unit. The study illustrated a difference in the resource utilization pattern due to the difference in hospital ownership type between the three healthcare sectors. Conclusion: Utilizing hospital resources at an optimal level will continue to be challenging due to conflicts among medical requirements and patient preferences. Key words: Healthcare Professionals; Hospital ; resources utilization; patient.

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7

Anderson, Geoffrey M. "Hospital Restructuring and the Epidemiology of Hospital Utilization." Medical Care 35, Supplement (October 1997): OS93—OS101. http://dx.doi.org/10.1097/00005650-199710001-00012.

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8

Lagoe, Ronald, Bella Lagoe, and Shelly Littau. "Hospital Utilization after the Epidemic." Case Reports in Clinical Medicine 10, no. 04 (2021): 92–98. http://dx.doi.org/10.4236/crcm.2021.104011.

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9

Brennan, Patrick J. "Hospital-Resource Utilization and Tuberculosis." Infection Control and Hospital Epidemiology 19, no. 10 (October 1998): 744–46. http://dx.doi.org/10.2307/30141418.

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10

Smith, Dean G., and Brenda W. Perry. "Toward Effective Hospital Utilization Management." Quality Assurance and Utilization Review 7, no. 4 (December 1992): 125–29. http://dx.doi.org/10.1177/0885713x9200700407.

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11

Brennan, Patrick J. "Hospital-Resource Utilization and Tuberculosis." Infection Control and Hospital Epidemiology 19, no. 10 (October 1998): 744–46. http://dx.doi.org/10.1086/647717.

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12

Caicoya, M., and C. Natal. "PID4: HOSPITAL ANTIBIOTICS UTILIZATION EVALUATION." Value in Health 3, no. 5 (September 2000): 322. http://dx.doi.org/10.1016/s1098-3015(11)70686-6.

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13

Lagoe, Ronald, and Shelly Littau. "Monitoring Changes in Hospital Utilization." Case Reports in Clinical Medicine 13, no. 04 (2024): 115–21. http://dx.doi.org/10.4236/crcm.2024.134014.

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14

Little, Andrew S., and Kristina Chapple. "Predictors of resource utilization in transsphenoidal surgery for Cushing disease." Journal of Neurosurgery 119, no. 2 (August 2013): 504–11. http://dx.doi.org/10.3171/2013.1.jns121375.

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Object The short-term cost associated with subspecialized surgical care is an increasingly important metric and economic concern. This study sought to determine factors associated with hospital charges in patients undergoing transsphenoidal surgery for Cushing disease in an effort to identify the drivers of resource utilization. Methods The authors analyzed the Nationwide Inpatient Sample (NIS) hospital discharge database from 2007 to 2009 to determine factors that influenced hospital charges in patients who had undergone transsphenoidal surgery for Cushing disease. The NIS discharge database approximates a 20% sample of all inpatient admissions to nonfederal US hospitals. A multistep regression model was developed that adjusted for patient demographics, acuity measures, comorbidities, hospital characteristics, and complications. Results In 116 hospitals, 454 transsphenoidal operations were performed. The mean hospital charge was $48,272 ± $32,060. A multivariate regression model suggested that the primary driver of resource utilization was length of stay (LOS), followed by surgeon volume, hospital characteristics, and postoperative complications. A 1% increase in LOS increased hospital charges by 0.60%. Patient charges were 13% lower when performed by high-volume surgeons compared with low-volume surgeons and 22% lower in large hospitals compared with small hospitals. Hospital charges were 12% lower in cases with no postoperative neurological complications. The proposed model accounted for 46% of hospital charge variance. Conclusions This analysis of hospital charges in transsphenoidal surgery for Cushing disease suggested that LOS, hospital characteristics, surgeon volume, and postoperative complications are important predictors of resource utilization. These findings may suggest opportunities for improvement.

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15

Cardiff, Karen, Geoffrey Anderson, and Samuel Sheps. "Evaluation of a Hospital-Based Utilization Management Program." Healthcare Management Forum 8, no. 1 (April 1995): 38–45. http://dx.doi.org/10.1016/s0840-4704(10)60894-0.

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The objective of this study was to evaluate the impact of a utilization management (UM) program designed to decrease inappropriate use of acute care hospital beds while maintaining quality of care. The measure used to define appropriateness was the ISD-A, a diagnosis-independent measurement tool which relies on severity of illness and intensity of service criteria. The outcome measures for the study included appropriate admission to hospital and continued days of stay in hospital, 30-day readmission rates and physician perceptions of the impact of the intervention on quality of care, access to services and patient discharge patterns. The sample frame for the study included two control and two intervention community hospitals, involving 1,800 patient charts. Readmission rates were determined by analyzing all separations from medical services (N=42,014) in the two experimental and two control hospitals. All physicians with admitting privileges (N=312) at the intervention hospitals were surveyed; obstetricians, pediatricians, and psychiatrists were excluded from the survey. The results of the study demonstrated that the proportion of inappropriate admissions did not decrease significantly in any of the hospitals, but there were significant decreases in inappropriate continued stay in the intervention hospitals (p < 0.05). Both intervention and one of the control hospitals had lower 30-day readmission rates in the “after” period than in the “before” period (p < 0.05). Eighty-six percent believed that there had been no adverse impact on access to care and, although 25% thought the program may have led to premature discharge, this was not supported by the readmission data.

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Begum, Farhana, and Shahinul Alam. "Consumer subsequent plan for selection of hospital in the perspective of hospital services and expenditure." South East Asia Journal of Public Health 6, no. 1 (December 10, 2016): 14–19. http://dx.doi.org/10.3329/seajph.v6i1.30339.

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Further utilization of hospital facility is influenced by the provision of hospital care and cost of services. This study was conducted among patients of public and private hospitals of Dhaka city, Bangladesh to explore the relationship of further utilization of hospital care and cost of services incurred during previous visits. A total 199 patients of 2 private and 2 public hospitals were included. Of them, 100 (50.25%) were from public and 99 (49.74 %) from private hospitals. Male: female ratio of the respondents was 111:88. The level of services was scored by patients on a 1-5 Likert scale on the aspects of services of doctors, nurses, other staffs; medicine supply; cleanliness; and investigation facilities. Poor people usually sought the services from public hospitals. About three-quarter of the respondents (76.9 %) mentioned that they would avail the facility of same hospital for their further ailment. Seventeen patients (17%) who were treated in government hospitals will not further utilize the services, and this was significantly higher (p-0.02) in the case of patients from private hospitals (29.3%). Regression analysis explored that quality of services (p=-0.000) and cost of services (p=0.001) influenced the plan of future consumption of hospital facility and quality of services having stronger influences. This study concludes that further utilization of the hospital facility was strongly influenced by the quality of services and next to that is cost of services. So we recommend for best and successive utilization of hospital services to improve facilities and minimization of cost are the essential needs.South East Asia Journal of Public Health Vol.6(1) 2016: 14-19

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17

Sharfeldin, Asmaa. "Inappropriateness of Hospital Admission, Hospital Stay and Bed Utilization at Monufia University Hospitals, Egypt." Egyptian Family Medicine Journal 3, no. 2 (February 1, 2019): 113–28. http://dx.doi.org/10.21608/efmj.2019.70445.

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18

Collins, Brian K., and Tyrone F. Borders. "Utilization of Hospital Services among Older Rural Persons: A Comparison of Critical Access Hospitals and Community Hospitals." Journal of Health and Human Services Administration 28, no. 1 (March 2005): 135–52. http://dx.doi.org/10.1177/107937390502800101.

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Critical access hospitals (CAHs) are intended to improve the accessibility of local emergency and short-term inpatient services, but limited research has evaluated their effects on hospital service utilization. This article asks whether the utilization of hospital and emergency room services differs between older persons residing in rural areas with a CAH versus a community hospital. Information about the utilization of hospital and emergency room services as well as demographic, health insurance, and health status factors were abstracted from a large population-based survey of community-dwelling elders (age 65 and older) residing in West Texas. The frequencies of hospital inpatient and emergency department admission do not differ between older persons who reside in counties with a CAH and a community hospital. These findings support the broad goals of the program and illustrate how Medicare can effectively support healthcare systems under fiscal stress.

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19

Sharp, John W., Ellen Coleman, Nedra Starling, Janet Cline, and Susan J. Rehm. "Hospital Utilization for AIDS: Are All Hospital Days Necessary?" QRB - Quality Review Bulletin 17, no. 4 (April 1991): 113–19. http://dx.doi.org/10.1016/s0097-5990(16)30438-9.

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20

Chen, Ming, Amie Goodin, Hong Xiao, Qiong Han, Driss Raissi, and Joshua Brown. "Hospitalization metrics associated with hospital-level variation in inferior vena cava filter utilization for patients with venous thromboembolism in the United States: Implications for quality of care." Vascular Medicine 23, no. 4 (May 20, 2018): 365–71. http://dx.doi.org/10.1177/1358863x18768685.

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Variation in the use of inferior vena cava filters (IVCFs) across hospitals has been observed, suggesting differences in quality of care. Hospitalization metrics associated with venous thromboembolism (VTE) patients have not been compared based on IVCF utilization rates using a national sample. We conducted a descriptive retrospective study using the Nationwide Readmissions Database (NRD) to delineate the variability of hospitalization metrics across the hospital quartiles of IVCF utilization for VTE patients. The NRD included all-payer administrative inpatient records drawn from 22 states. Adult (≥ 18 years) patients with VTE hospitalizations with or without IVCF were identified from January 1, 2013 through December 31, 2014 and hospitals were divided into quartiles based on the IVCF utilization rate as a proportion of VTE patients. Primary outcome measures were observed rates of in-hospital mortality, 30-day all-cause readmissions and VTE-related readmissions, cost, and length of stay. Patient case-mix characteristics and hospital-level factors by hospital quartiles of IVCF utilization rates, were compared. Overall, 12.29% of VTE patients had IVCF placement, with IVCF utilization ranging from 0% to 46.84%. The highest quartile had fewer pulmonary embolism patients relative to deep vein thrombosis patients, and older patient ages were present in higher quartiles. The highest quartile of hospitals placing IVCFs were more often private, for-profit, and non-teaching. Patient and hospital characteristics and hospitalization metrics varied by IVCF utilization rates, but hospitalization outcomes for non-IVCF patients varied most between quartiles. Future work investigating the implications of IVCF utilization rates as a measure of quality of care for VTE patients is needed.

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21

Vyas, Arpita K., Yiu Ming Chan, and Lavi Oud. "Variation in Utilization of Intensive Care for Pediatric Diabetic Ketoacidosis." Journal of Intensive Care Medicine 35, no. 11 (August 13, 2019): 1314–22. http://dx.doi.org/10.1177/0885066619868972.

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Objective: To examine the hospital-level variation in intensive care unit (ICU) utilization and quantify the relative contribution of patient and hospital characteristics versus individual hospital factors to the variation in ICU admission rates among pediatric hospitalizations with diabetic ketoacidosis (DKA). Methods: The Texas Inpatient Public Use Data File was used to identify hospitalizations of state residents aged 1 month to 19 years with a primary diagnosis of DKA between 2005 and 2014. Multilevel, mixed-effects logistic regression modeling was performed to examine the association of patient- and hospital-level factors with ICU admission. Risk and reliability adjustment was then performed to assess hospital-level variation in ICU utilization. Intraclass correlation coefficient was used to quantify variation in use of ICU attributable to individual hospitals. The association between adjusted rates of ICU admission and total hospital charges and length of stay was examined using linear regression. Results: Of the 23 585 DKA hospitalizations, 14 638 (62.1%) were admitted to ICU. On multilevel analysis, the odds of ICU admission progressively decreased with rising volume of DKA hospitalizations (adjusted odds ratio: 0.08 [highest vs lowest quartile]; 95% confidence interval [CI]: 0.03-0.24). The crude median (interquartile range [IQR]; range) of ICU admissions across hospitals was 82.6% (73%-90%; 11.1%-100%). The median (IQR) risk- and reliability-adjusted ICU admission rate was 81.0% (73.0%-86.9%), ranging from 11.2% to 94%. Following risk and reliability adjustment, the intraclass correlation coefficient was 0.005 (95% CI: 0.004-0.006). For each 10% increase in adjusted ICU admission rate, total hospital charges rose by 7% (95% CI: 3%-11%). There was no association between ICU admission rates and hospital length of stay. Conclusion: Although high variation in ICU utilization was noted across hospitals among pediatric DKA hospitalizations, the proportion of variation attributable to individual hospitals was negligible, once adjusted for patient mix and hospital characteristics.

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22

Pokras, R., L. J. Kozak, E. McCarthy, and E. J. Graves. "Trends in hospital utilization, 1965-86." American Journal of Public Health 80, no. 4 (April 1990): 488–90. http://dx.doi.org/10.2105/ajph.80.4.488.

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23

ARORA, PRADEEP, ANNAMARIA T. KAUSZ, GREGORIO T. OBRADOR, ROBIN RUTHAZER, SAMINA KHAN, CONSTANCE S. JENULESON, KLEMENS B. MEYER, and BRIAN J. G. PEREIRA. "Hospital Utilization among Chronic Dialysis Patients." Journal of the American Society of Nephrology 11, no. 4 (April 2000): 740–46. http://dx.doi.org/10.1681/asn.v114740.

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Abstract. Factors driving inpatient and outpatient utilization were studied among patients who began dialysis for chronic renal failure at the New England Medical Center (NEMC) between 1992 and 1997. Clinical, laboratory, and hospital resource utilization data were obtained from patient records and electronic databases. There were 2.2 hospitalizations and 14.8 hospital days per patient year at risk (PYAR). The number of hospitalizations and hospital days per PYAR were higher in the first 3 mo of initiating dialysis (4.3 and 28.3, respectively) compared to after 3 mo (1.9 and 12.9, respectively). Factors associated with increased risk of hospital days within the first 3 mo included non-health maintenance organization insurance, ischemic heart disease, late referral to the nephrologist, and use of temporary vascular access for the first dialysis. Patients with ischemic heart disease and who received dialysis during the years 1992-1994 compared with 1996-1997 had an increased risk of hospital days after 3 mo of initiating dialysis. There were 16.6 outpatient visits per PYAR, with significant differences in utilization between the first 3 mo and after 3 mo of initiating dialysis. Thus, hospital utilization was significantly higher in the first 3 mo compared to after 3 mo, and factors associated with hospital utilization depended on duration of dialysis. In particular, delayed referral to the nephrologist and lack of permanent vascular access were independently associated with increased risk of hospital utilization in the first 3 mo of dialysis. Greater attention to timely referral to the nephrologist and timely placement of vascular access could result in reduced utilization and cost savings.

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24

Alexander, Michael R., Janice L. Stumpf, Timothy T. Nostrant, Ujjaini Khanderia, Frederic E. Eckhauser, and Carol L. Colvin. "Albumin Utilization in a University Hospital." DICP 23, no. 3 (March 1989): 214–17. http://dx.doi.org/10.1177/106002808902300304.

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The inappropriate use of high-priced agents such as human serum albumin significantly contributes to the rising cost of medical care. A utilization review was conducted at the University of Michigan Hospital in order to identify the appropriateness of use of this agent. Criteria were developed and prescribing was retrospectively evaluated for 81 patients. Of the 935 units administered to these patients, 692 (74 percent) were judged to be inappropriate. This inappropriate use accounted for a projected annual expenditure of nearly $281 000. Interventions have previously demonstrated success in improving prescribing.

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25

Zisselman, Marc H., Barry W. Rovner, Karen G. Kelly, and Celia Woods. "Benzodiazepine Utilization in a University Hospital." American Journal of Medical Quality 9, no. 3 (September 1994): 138–41. http://dx.doi.org/10.1177/0885713x9400900306.

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26

Roos, Noralou P. "Predicting Hospital Utilization by the Elderly." Medical Care 27, no. 10 (October 1989): 905–19. http://dx.doi.org/10.1097/00005650-198910000-00001.

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27

McCULLOUGH, J., T. A. STEEPER, D. P. CONNELLY, B. JACKSON, S. HUNTINGTON, and E. P. SCOTT. "Platelet Utilization in a University Hospital." Survey of Anesthesiology 32, no. 5 (October 1988): 333. http://dx.doi.org/10.1097/00132586-198810000-00062.

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28

BARBADORO, P., A. MARIGLIANO, A. RICCIARDI, M. M. D'ERRICO, and E. PROSPERO. "Trend of hospital utilization for encephalitis." Epidemiology and Infection 140, no. 4 (June 21, 2011): 753–64. http://dx.doi.org/10.1017/s0950268811001002.

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SUMMARYEncephalitis generally results in a serious illness requiring hospitalization. The aim of this study was to describe the epidemiology of hospitalization for encephalitis in Italy, taking into account the geographical distribution, aetiology, seasonality and evolution of hospitalization rates over recent years. The mean hospitalization rate was 5·88/100 000. For most of these hospitalizations (n=13 119, 55·6%), no specific cause of encephalitis was reported. The most common aetiological category was ‘viral’, which accounted for 40·1% (n=4205) of such hospitalizations (rate 1·05/100 000). Within this category, herpes virus was the leading causative agent (n=1579, 0·39/100 000). This report highlights a significant increase of ‘viral encephalitis not otherwise specified’ (ICD-9 code 049·9) vs. a reduction of all other causes. A seasonal pattern was noted in people aged ⩾65 years in this group. Specific surveillance of encephalitis without known origin should be reinforced in order to identify the potential role of emerging pathogens and to design preventive interventions.

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29

Breslow, Michael J., Robert Herbert, Peter Pronovost, David Foster, Baltimore, and United States. "Unexplained Variation in Hospital ICU Utilization." Anesthesiology 2001, no. 3 (September 1, 2001): B15. http://dx.doi.org/10.1097/00000542-200109001-00015.

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30

Rosenman, Marc B., Terry Vik, Siu L. Hui, and Philip P. Breitfeld. "Hospital Resource Utilization in Childhood Cancer." Journal of Pediatric Hematology/Oncology 27, no. 6 (June 2005): 295–300. http://dx.doi.org/10.1097/01.mph.0000168724.19025.a4.

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31

Swales, Thomas P., Lynn D. Sivinski, Matthew T. Karafa, Lee Friedman, S. Charles Schulz, and Alfred A. Rimm. "Medicare hospital utilization increasing for schizophrenia." Schizophrenia Research 24, no. 1-2 (January 1997): 259. http://dx.doi.org/10.1016/s0920-9964(97)82747-8.

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32

Riyaz, AMM. "Utilization Management for Effective Hospital Services." Sri Lankan Journal of Medical Administration 14 (March 26, 2013): 21. http://dx.doi.org/10.4038/sljma.v14i0.5349.

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33

Mott, Peter D. "Hospital Utilization by Health Maintenance Organizations." Medical Care 24, no. 5 (May 1986): 398–406. http://dx.doi.org/10.1097/00005650-198605000-00003.

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34

Langan, Russell C., Chun-Chih Huang, Weisheng Renee Mao, Katherine Harris, Will Chapman, Charles Fehring, Kesha Oza, et al. "Pancreaticoduodenectomy hospital resource utilization in octogenarians." American Journal of Surgery 211, no. 1 (January 2016): 70–75. http://dx.doi.org/10.1016/j.amjsurg.2015.04.014.

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35

McCullough, Jeffrey. "Platelet Utilization in a University Hospital." JAMA: The Journal of the American Medical Association 259, no. 16 (April 22, 1988): 2414. http://dx.doi.org/10.1001/jama.1988.03720160034026.

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36

Lagoe, Ronald, and Shelly Littau. "Hospital Utilization and Health Care Planning." Case Reports in Clinical Medicine 11, no. 12 (2022): 520–26. http://dx.doi.org/10.4236/crcm.2022.1112070.

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37

Sillehu, Sahrir, Agung Dwi Laksono, Ratna Dwi Wulandari, and Abu Khoiri. "HOSPITAL UTILIZATION IN MALUKU PROVINCE, INDONESIA." Indonesian Journal of Public Health 18, no. 3 (November 16, 2023): 470–80. http://dx.doi.org/10.20473/ijph.v18i3.2023.470-480.

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Introduction: Maluku is a region characterized by an archipelago with approximately 1,340 islands and an area of 712,479.69 km2. Most of the site is water (92.4%), while the land area is only around 7.6%. Aims: This study aimed to analyze the determinant of hospital utilization in Maluku Province, Indonesia. Methods: This cross-sectional study surveyed 788 respondents. The variables examined included hospital utilization, age group, gender, education level, work type, marital status, health insurance, transportation cost, and time travel. The author used binary logistic regression in the final stage. Results: The results show that the 30-39 age group was 2.293 times more likely than the ≥ 50 age group to utilize the hospital (OR 2.293; 95% CI 1.177 – 4.466). Married people were more likely to use the hospital 1.764 times than those with the never-married category (OR 1.764; 95% CI 1.074 – 2.898). Christians were 1.599 times more likely than Muslims to utilize the hospital (OR 1.599; 95% CI 1.146 – 2.231). Conclusion: The study concluded that three variables are determinants of hospital utilization among people in Maluku Province, Indonesia. The three were age group, marital status, and religion. The study's results were significant for local policymakers to provide specific directions to accelerate the increase in hospital utility in Maluku Province in Indonesia.

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McCullough, J. "Platelet utilization in a university hospital." JAMA: The Journal of the American Medical Association 259, no. 16 (April 22, 1988): 2414–18. http://dx.doi.org/10.1001/jama.259.16.2414.

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39

Chen, Honglin, Iris Chi, and Ruotong Liu. "Hospital Utilization Among Chinese Older Adults: Patterns and Predictors." Journal of Aging and Health 31, no. 8 (June 17, 2018): 1454–78. http://dx.doi.org/10.1177/0898264318780546.

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Objectives: Our study aimed to explore patterns and predictors of hospital utilization among Chinese older adults in the context of a rapidly aging population and increasing health care costs in contemporary China. Methods: This study used a national representative sample aged 60 years or older ( N = 11,511) from the China Longitudinal Aging Social Survey in 2014. We applied Andersen’s social behavioral model and stepwise logistic regression to identify predictors of hospital utilization. Results: About 25% of the respondents were hospitalized in the previous year. Level of literacy, rural residence, social support, intergenerational relationships, and negative perceptions of aging were significant factors predicting hospital utilization. However, major variations existed across provinces in the use of hospitals. Discussion: Conclusions regarding how to integrate the complex range of hospital services more effectively and evenly are described. Social services should be developed in response to the hospital services utilization needs of older people.

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40

Cole, Evan S., Carla Willis, William C. Rencher, and Mei Zhou. "Long-term acute care hospitals and Georgia Medicaid: Utilization, outcomes, and cost." SAGE Open Medicine 4 (January 1, 2016): 205031211667092. http://dx.doi.org/10.1177/2050312116670928.

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Objectives: Because most research on long-term acute care hospitals has focused on Medicare, the objective of this research is to describe the Georgia Medicaid population who received care at a long-term acute care hospital, the type and volume of services provided by these long-term acute care hospitals, and the costs and outcomes of these services. For those with select respiratory conditions, we descriptively compare costs and outcomes to those of patients who received care for the same services in acute care hospitals. Methods: We describe Georgia Medicaid recipients admitted to a long-term acute care hospital between 2011 and 2012. We compare them to a population of Georgia Medicaid recipients admitted to an acute care hospital for one of five respiratory diagnosis-related groups. Measurements used include patient descriptive information, admissions, diagnosis-related groups, length of stay, place of discharge, 90-day episode costs, readmissions, and patient risk scores. Results: We found that long-term acute care hospital admissions for Medicaid patients were fairly low (470 90-day episodes) and restricted to complex cases. We also found that the majority of long-term acute care hospital patients were blind or disabled (71.2%). Compared to patients who stayed at an acute care hospital, long-term acute care hospital patients had higher average risk scores (13.1 versus 9.0), lengths of stay (61 versus 38 days), costs (US$143,898 versus US$115,056), but fewer discharges to the community (28.4% versus 51.8%). Conclusion: We found that the Medicaid population seeking care at long-term acute care hospitals is markedly different than the Medicare populations described in other long-term acute care hospital studies. In addition, our study revealed that Medicaid patients receiving select respiratory care at a long-term acute care hospital were distinct from Medicaid patients receiving similar care at an acute care hospital. Our findings suggest that state Medicaid programs should carefully consider reimbursement policies for long-term acute care hospitals, including bundled payments that cover both the original hospitalization and long-term acute care hospital admission.

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Yu, Kaylee G., Jay J. Shen, Pearl C. Kim, Sun Jung Kim, Se Won Lee, David Byun, Ji Won Yoo, and Jinwook Hwang. "Trends of Hospital Palliative Care Utilization and Its Associated Factors Among Patients With Systemic Lupus Erythematosus in the United States From 2005 to 2014." American Journal of Hospice and Palliative Medicine® 37, no. 3 (December 3, 2019): 164–71. http://dx.doi.org/10.1177/1049909119891999.

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Objective: To investigate trends and associated factors of utilization of hospital palliative care among patients with systemic lupus erythematosus (SLE) and analyze its impact on length of hospital stay, hospital charges, and in-hospital mortality. Methods: Using the 2005-2014 National Inpatient Sample in the United States, the compound annual growth rate was used to investigate the temporal trend of utilization of hospital palliative care. Multivariate multilevel logistic regression analyses were performed to analyze the association with patient-related factors, hospital factors, length of stay, in-hospital mortality, and hospital charges. Results: The overall proportion of utilization of hospital palliative care for the patient with SLE was 0.6% over 10 years. It increased approximately 12-fold from 0.1% (2005) to 1.17% (2014). Hospital palliative care services were offered more frequently to older patients, patients with high severity illnesses, and in urban teaching hospitals or large size hospitals. Patients younger than 40 years, the lowest household income group, or Medicare beneficiaries less likely received palliative care during hospitalization. Hospital palliative care services were associated with increased length of stay (β = 1.407, P < .0001) and in-hospital mortality (odds ratio, 48.18; 95% confidence interval, 41.59-55.82), and reduced hospital charge (β = −0.075, P = .009). Conclusion: Hospital palliative care service for patients with SLE gradually increased during the past decade in US hospitals. However, this showed disparities in access and was associated with longer hospital length of stay and higher in-hospital mortality. Nevertheless, hospital palliative care services yielded a cost-saving effect.

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McLafferty, Sara. "Predicting the effect of hospital closure on hospital utilization patterns." Social Science & Medicine 27, no. 3 (January 1988): 255–62. http://dx.doi.org/10.1016/0277-9536(88)90129-3.

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Reddy, Sudheer, Lane Koenig, Berna Demiralp, Jennifer T. Nguyen, and Qian Zhang. "Assessing the Utilization of Total Ankle Replacement in the United States." Foot & Ankle International 38, no. 6 (March 1, 2017): 641–49. http://dx.doi.org/10.1177/1071100717695111.

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Background: Total ankle arthroplasty (TAR) has been shown to be a cost-effective procedure relative to conservative management and ankle arthrodesis. Although its use has grown considerably over the last 2 decades, it is less common than arthrodesis. The purpose of this investigation was to analyze the cost and utilization of TAR across hospitals. Methods: Our analytical sample consisted of Medicare claims data from 2011 and 2012 for Inpatient Prospective Payment System hospitals. Outcome variables of interest were the likelihood of a hospital performing TAR, the volume of TAR cases, TAR hospital costs, and hospital profit margins. Data from the 2010 Cost Report and Medicare inpatient claims were utilized to compute average margins for TAR cases and overall hospital margins. TAR cost was calculated based on the all payer cost-to-charge ratio for each hospital in the Cost Report. Nationwide Inpatient Sample data were used to generate descriptive statistics on all TAR patients across payers. Results: Medicare participants accounted for 47.5% of the overall population of TAR patients. Average implant cost was $13 034, accounting for approximately 70% of the total all-payer cost. Approximately, one-third of hospitals were profitable with respect to primary TAR. Profitable hospitals had lower total costs and higher payments leading to a difference in profit of approximately $11 000 from TAR surgeries between profitable and nonprofitable hospitals. No difference was noted with respect to length of stay or number of cases performed between profitable and nonprofitable hospitals. TAR surgeries were more likely to take place in large and major teaching hospitals. Among hospitals performing at least 1 TAR, the margin on TAR cases was positively associated with the total number of TARs performed by a hospital. Conclusion: There is an overall significant financial burden associated with performing TAR with many health systems failing to demonstrate profitability despite its increased utilization. While additional factors such as improved patient outcomes may be driving utilization of TAR, financial barriers may exist that can affect utilization of TAR across health systems. Level of Evidence: Level III, comparative study

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Warren, Bobby, Rebekah Moehring, Michael Yarrington, Deverick Anderson, and Christopher Polage. "Blood Culture Utilization at Six Southeastern US Hospitals." Antimicrobial Stewardship & Healthcare Epidemiology 1, S1 (July 2021): s34—s35. http://dx.doi.org/10.1017/ash.2021.64.

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Group Name: Duke Center for Antimicrobial Stewardship and Infection PreventionBackground: Blood cultures are an essential diagnostic test, but over- and underutilization may cause harm. Methods: We analyzed blood culture utilization at 6 hospitals in the southeastern United States including 1 academic hospital (A) and 5 community hospitals (B–F) from May 2019 to April 2020. We measured blood culture utilization rate (BCUR) per 1,000 patient days and blood cultures per encounter. We counted blood cultures by laboratory accession number and measured utilization per 1,000 patient days and encounter. A likely contaminant was defined as 1 of 2 blood cultures collected in the same calendar day positive for a common skin commensal (CSC), as defined by the NHSN, and not identified from subsequent cultures. A likely pathogen was defined as a culture with a pathogen not on the CSC list or a CSC not meeting the contaminant definition. Hospital-level BCUR included samples for culture collected in the emergency department (ED) and inpatient areas divided by inpatient days. Results: The analysis included 117,897 blood cultures and 662,723 patient days with a median BCUR of 209.7 per hospital and median blood culture per encounter of 2 (Table 1). One community hospital (C) demonstrated a substantially higher BCUR than others. Cultures were frequently collected in the ED (54%; range, 36%–78%); most encounters with cultures in the ED were subsequently admitted to an inpatient unit (84%; range, 73%–89%). Higher BCURs were observed in intensive care and oncology units. The proportion of first blood cultures drawn after initiation of antibiotics was 6% (range, 3%–9%. Mondays had higher BCURs than other days of the week (Figure 1). The average BCUR by month was 176.1 (range, 164.3–181.4) with no seasonal patterns observed. Overall, 7.7% (range, 4.5%–9.1%) of blood cultures identified a likely pathogen and 2.1% (range, 1.3%–3.2%) identified a likely contaminant. The 3 hospitals with BCURs >200 also had contaminant rates >2% and >60% ED cultures. Conclusions: Blood culture utilization varied by hospital, unit, and day of the week. We observed higher rates of likely contaminants among hospitals with higher BCURs and ED culture rates. Comparisons may assist in identifying opportunities to optimize practice around blood-culture ordering and collection.Funding: NoDisclosures: None

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Roimi, Michael, Rom Gutman, Jonathan Somer, Asaf Ben Arie, Ido Calman, Yaron Bar-Lavie, Udi Gelbshtein, et al. "Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study." Journal of the American Medical Informatics Association 28, no. 6 (February 26, 2021): 1188–96. http://dx.doi.org/10.1093/jamia/ocab005.

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Abstract Objective The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patient characteristics. Materials and Methods We develop a model of patient clinical course based on an advanced multistate survival model. The model predicts the patient's disease course in terms of clinical states—critical, severe, or moderate. The model also predicts hospital utilization on the level of entire hospitals or healthcare systems. We cross-validated the model using a nationwide registry following the day-by-day clinical status of all hospitalized COVID-19 patients in Israel from March 1 to May 2, 2020 (n = 2703). Results Per-day mean absolute errors for predicted total and critical care hospital bed utilization were 4.72 ± 1.07 and 1.68 ± 0.40, respectively, over cohorts of 330 hospitalized patients; areas under the curve for prediction of critical illness and in-hospital mortality were 0.88 ± 0.04 and 0.96 ± 0.04, respectively. We further present the impact of patient influx scenarios on day-by-day healthcare system utilization. We provide an accompanying R software package. Discussion The proposed model accurately predicts total and critical care hospital utilization. The model enables evaluating impacts of patient influx scenarios on utilization, accounting for the state of currently hospitalized patients and characteristics of incoming patients. We show that accurate hospital load predictions were possible using only a patient’s age, sex, and day-by-day clinical state (critical, severe, or moderate). Conclusions The multistate model we develop is a powerful tool for predicting individual-level patient outcomes and hospital-level utilization.

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Sharma, Narayan, René Schwendimann, Olga Endrich, Dietmar Ausserhofer, and Michael Simon. "Variation of Daily Care Demand in Swiss General Hospitals: Longitudinal Study on Capacity Utilization, Patient Turnover and Clinical Complexity Levels." Journal of Medical Internet Research 23, no. 8 (August 19, 2021): e27163. http://dx.doi.org/10.2196/27163.

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Background Variations in hospitals’ care demand relies not only on the patient volume but also on the disease severity. Understanding both daily severity and patient volume in hospitals could help to identify hospital pressure zones to improve hospital-capacity planning and policy-making. Objective This longitudinal study explored daily care demand dynamics in Swiss general hospitals for 3 measures: (1) capacity utilization, (2) patient turnover, and (3) patient clinical complexity level. Methods A retrospective population-based analysis was conducted with 1 year of routine data of 1.2 million inpatients from 102 Swiss general hospitals. Capacity utilization was measured as a percentage of the daily maximum number of inpatients. Patient turnover was measured as a percentage of the daily sum of admissions and discharges per hospital. Patient clinical complexity level was measured as the average daily patient disease severity per hospital from the clinical complexity algorithm. Results There was a pronounced variability of care demand in Swiss general hospitals. Among hospitals, the average daily capacity utilization ranged from 57.8% (95% CI 57.3-58.4) to 87.7% (95% CI 87.3-88.0), patient turnover ranged from 22.5% (95% CI 22.1-22.8) to 34.5% (95% CI 34.3-34.7), and the mean patient clinical complexity level ranged from 1.26 (95% CI 1.25-1.27) to 2.06 (95% CI 2.05-2.07). Moreover, both within and between hospitals, all 3 measures varied distinctly between days of the year, between days of the week, between weekdays and weekends, and between seasons. Conclusions While admissions and discharges drive capacity utilization and patient turnover variation, disease severity of each patient drives patient clinical complexity level. Monitoring—and, if possible, anticipating—daily care demand fluctuations is key to managing hospital pressure zones. This study provides a pathway for identifying patients’ daily exposure to strained hospital systems for a time-varying causal model.

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de Man, Yvonne, Stef Groenewoud, Mariska G. Oosterveld-Vlug, Linda Brom, Bregje D. Onwuteaka-Philipsen, Gert P. Westert, and Femke Atsma. "Regional variation in hospital care at the end-of-life of Dutch patients with lung cancer exists and is not correlated with primary and long-term care." International Journal for Quality in Health Care 32, no. 3 (March 18, 2020): 190–95. http://dx.doi.org/10.1093/intqhc/mzaa004.

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Abstract Objective To examine the regional variation in hospital care utilization in the last 6 months of life of Dutch patients with lung cancer and to test whether higher degrees of hospital utilization coincide with less general practitioner (GP) and long-term care use. Design Cross-sectional claims data study. Setting The Netherlands. Participants Patients deceased in 2013–2015 with lung cancer (N = 25 553). Main Outcome Measures We calculated regional medical practice variation scores, adjusted for age, gender and socioeconomic status, for radiotherapy, chemotherapy, CT-scans, emergency room contacts and hospital admission days during the last 6 months of life; Spearman Rank correlation coefficients measured the association between the adjusted regional medical practice variation scores for hospital admissions and ER contacts and GP and long-term care utilization. Results The utilization of hospital services in high-using regions is 2.3–3.6 times higher than in low-using regions. The variation was highest in 2015 and lowest in 2013. For all 3 years, hospital care was not significantly correlated with out-of-hospital care at a regional level. Conclusions Hospital care utilization during the last 6 months of life of patients with lung cancer shows regional medical practice variation over the course of multiple years and seems to increase. Higher healthcare utilization in hospitals does not seem to be associated with less intensive GP and long-term care. In-depth research is needed to explore the causes of the variation and its relation to quality of care provided at the level of daily practice.

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Demkowicz, Ryan, Josephine Dermawan, Sindu Shetty, Richard Scarborough, Haiyan Lu, Luis Sardina, and Yap-Yee Chong. "Blood Utilization at Regional Hospitals." American Journal of Clinical Pathology 152, Supplement_1 (September 11, 2019): S151. http://dx.doi.org/10.1093/ajcp/aqz131.000.

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Abstract Introduction Transfusion medicine is unique to lab medicine. While it still involves testing and reporting of results, it is one of the few areas where the laboratory is providing treatment. The risk of providing a blood product must be weighed against the benefit before the decision is made to transfuse a patient. Our study looked at blood utilization at our regional hospitals to assess if there were areas where we need to improve this decision process. Methods Chart reviews were performed for patients who received packed red blood cells (RBCs) in the regional hospitals over a 2-month period. Using the AABB and Choosing Wisely recommendations, we created two screening criteria: hemoglobin (Hb) >8 g/dL or greater than 1 unit RBC ordered when Hb is >6 g/dL to screen for outliers among RBC orders. A more in-depth chart review including information on clinical diagnosis, indications, bleeding status, and blood loss during surgery was performed on cases that met these criteria. Using this information, a decision was made on the appropriateness of the transfusion. Results In total, 1,592 RBC units were screened at eight regional hospitals. Sixty-eight (4%) were flagged as inappropriate, 57 (83.8%) due to multiple units, and 11 (16.2%) for an Hb >8 g/dL. The percentage of inappropriate transfusions at a hospital ranged from 5.2% to 13.6%. However, all hospitals except one were under 5.5%. Discussion In general, regional physicians are transfusing RBCs appropriately. When a unit is ordered inappropriately, it is most likely due to ordering multiple units upfront. To further improve blood utilization, these data were presented to hospital administration and a new alert in the EMR was created. A repeat study will be performed to see if the alerts and awareness of these data has had an effect on blood utilization.

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Mojtahedi, Zahra, Ji Won Yoo, Karen Callahan, Neeraj Bhandari, Donghui Lou, Katayoon Ghodsi, and Jay J. Shen. "Inpatient Palliative Care Is Less Utilized in Rare, Fatal Extrahepatic Cholangiocarcinoma: A Ten-Year National Perspective." International Journal of Environmental Research and Public Health 18, no. 19 (September 23, 2021): 10004. http://dx.doi.org/10.3390/ijerph181910004.

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Background—Extrahepatic cholangiocarcinoma (ECC) is a rare, morbid, fatal cancer with distressing symptoms. Maintaining a high quality of life while reducing hospital charges and length of stay (LOS) for the end-of-life period remains a major challenge for the healthcare system. Palliative care utilization has been shown to address these challenges; moreover, its use has increased in recent years among cancer patients. However, the utilization of palliative care in rare cancers, such as ECC, has not yet been explored. Objectives—To investigate palliative care utilization among ECC patients admitted to US hospitals between 2007 and 2016 and its association with patient demographics, clinical characteristics, hospital charges, and LOS. Methods—De-identified patient data of each hospitalization were retrieved from the National Inpatient Sample (NIS) database. Codes V66.7 (ICD-9-CM) or Z51.5 (ICD-10-CM) were used to find palliative care utilization. Multivariate adjusted logistic regression analyses were conducted to assess factors associated with palliative care use, LOS, hospital charges, and in-hospital death. Results—Of 4426 hospitalizations, only 6.7% received palliative care services. Palliative care utilization did not significantly increase over time (p = 0.06); it reduced hospital charges by USD 25,937 (p < 0.0001) and LOS by 1.3 days (p = 0.0004) per hospitalization. Palliative care was positively associated with female gender, severe disease, and age group ≥80 (p ≤ 0.05). The average LOS was 8.5 days for each admission. Conclusions—Hospital admissions with palliative care utilization had lower hospital charges and LOS in ECC. However, ECC patients received less palliative care compared with more common cancers sharing similar symptoms (e.g., pancreatic cancer). ECC patients also had longer LOS compared with the national average. Further research is warranted to develop interventions to increase palliative care utilization among ECC hospital patients.

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Takvorian, Samuel U., Laura Yasaitis, Manqing Liu, Daniel J. Lee, Rachel M. Werner, and Justin E. Bekelman. "Association of hospital type with prices, spending, and acute care utilization among privately insured patients undergoing cancer surgery." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19376-e19376. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19376.

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e19376 Background: With annual cancer spending estimated to surpass $170 billion in 2020, national attention has focused on the prices and utilization of cancer care. This is particularly important for privately insured patients, for whom healthcare prices are negotiated between insurers and providers and price transparency is lacking. Among privately insured patients undergoing common cancer surgery, we examined the relation between hospital type and prices, spending, and utilization. Methods: We conducted a retrospective study using Health Care Cost Institute’s multipayer national commercial claims data. The study population included patients with breast, colon or lung cancer undergoing cancer surgery from 2011-2014. The exposure was hospital type at which surgery was performed: National Cancer Institute (NCI), academic, or community. Spending outcomes were surgery-specific prices paid and 90-day total episode spending. Utilization outcomes were length of stay (LOS), emergency department (ED) use, and hospital readmission within 90 days. We estimated mean risk-adjusted spending and utilization outcomes for each hospital type using generalized linear mixed-effects models, adjusting for patient, hospital and region characteristics. Results: We identified 66,878 patients with incident breast (53.5%), colon (32.0%), or lung (14.5%) cancer undergoing cancer surgery at 2,995 hospitals (8.3% at NCI; 16.3% academic; 75.4% community). Treatment at NCI cancer centers was associated with higher surgical prices paid ($18,310 at NCI v $14,703 at community hospitals; diff +$3,607; p < 0.001) and 90-day total episode spending ($46,462 v $41,274; diff +$5,188; p = 0.008). There were no significant differences in LOS, ED use or hospital readmission within 90 days. Conclusions: Among privately insured patients undergoing cancer surgery, NCI cancer centers had higher surgical prices and episode spending without differences in utilization, compared to community hospitals. A better understanding of the drivers of prices and spending at NCI cancer centers is needed. [Table: see text]

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