Literature DB >> 15466064

Equivalent lengths of stay of pediatric patients hospitalized in rural and nonrural hospitals.

Scott A Lorch1, Xuemei Zhang, Paul R Rosenbaum, Orit Evan-Shoshan, Jeffrey H Silber.   

Abstract

BACKGROUND: Many children receive their care at local hospitals outside of a large urban area. There may be differences in the length of stay (LOS) between children hospitalized in rural versus urban hospitals. This study compared the differences in LOS, conditional LOS (CLOS), odds of prolonged stay, and 21-day readmission rates for children with 19 medical conditions and 9 surgical procedures admitted to rural, community, and large urban hospitals.
METHODS: Discharge records for the hospitalizations of children 1 to 17 years of age were obtained from the New York Department of Public Health Statewide Planning and Research Cooperative System and the Pennsylvania Health Care Cost Containment Council for April 1996 to July 1998. The 19 medical and 9 surgical conditions were identified with the principal condition and procedure codes. Hospitals were classified into 1 of 5 geographic categories on the basis of United States rural-urban continuum codes, ie, large urban, suburban, moderate urban, small urban, or rural. LOS was defined as the period of time between hospital admission and discharge. Readmission rates were calculated for 21 days after discharge from the hospital. A prolonged stay for each condition was defined as any admission lasting beyond the prolongation point, or the day at which the rate of discharge began to decline, as determined with the Hollander-Proschan statistic. This aspect of LOS describes the ability of providers to treat uncomplicated cases of that specific principle diagnosis. CLOS, as a marker for the management of complicated cases, was defined as the LOS beyond the prolongation point. Cox and logistic regression models were developed to describe the geographic effects on the 4 outcome variables, after severity adjustment with 32 demographic and 11 comorbidity variables and adjustment for hospital clustering.
RESULTS: Medical (N = 114,787) and surgical (N = 29,156) admissions to rural hospitals (N = 12,367) had similar outcomes, compared with all geographic categories except the large urban category. Medical patients admitted to rural hospitals had a shorter LOS (12% increase in discharge rate), a shorter CLOS (12% increase in discharge rate), and lower odds of prolonged stay (odds ratio: 0.80), compared with those in large urban hospitals. Surgical patients admitted to rural hospitals had a shorter LOS (12% increase in discharge rate) and lower odds of prolonged stay (odds ratio: 0.81), compared with those in large urban hospitals. For individual conditions, rural hospitals in general had similar or improved LOS, compared with all other hospitals in the 2 states. The addition of hospital-level variables failed to change the results of the primary models.
CONCLUSIONS: In their treatment of pediatric hospitalized patients, rural hospitals were not significantly different from hospitals in all geographic regions other than large urban areas. Rural hospitals appear to deliver similar care, compared with nonrural hospitals, for many of the common pediatric conditions included in this study. Additional research is needed to apply these results to other regions or states with different geographic distributions of hospitals and children, in order to determine the overall impact on the regionalization of pediatric care.

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Year:  2004        PMID: 15466064     DOI: 10.1542/peds.2004-0891

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  10 in total

1.  Use of prolonged travel to improve pediatric risk-adjustment models.

Authors:  Scott A Lorch; Jeffrey H Silber; Orit Even-Shoshan; Andrea Millman
Journal:  Health Serv Res       Date:  2008-12-30       Impact factor: 3.402

2.  Measuring hospital quality using pediatric readmission and revisit rates.

Authors:  Naomi S Bardach; Eric Vittinghoff; Renée Asteria-Peñaloza; Jeffrey D Edwards; Jinoos Yazdany; Henry C Lee; W John Boscardin; Michael D Cabana; R Adams Dudley
Journal:  Pediatrics       Date:  2013-08-26       Impact factor: 7.124

3.  Characteristics of Rural Children Admitted to Pediatric Hospitals.

Authors:  Alon Peltz; Chang L Wu; Marjorie Lee White; Karen M Wilson; Scott A Lorch; Cary Thurm; Matt Hall; Jay G Berry
Journal:  Pediatrics       Date:  2016-04-11       Impact factor: 7.124

4.  Health insurance and length of stay for children hospitalized with community-acquired pneumonia.

Authors:  Susmita Pati; Scott A Lorch; Grace E Lee; Seth Sheffler-Collins; Samir S Shah
Journal:  J Hosp Med       Date:  2011-10-03       Impact factor: 2.960

5.  Global quantitative indices reflecting provider process-of-care: data-base derivation.

Authors:  John L Moran; Patricia J Solomon
Journal:  BMC Med Res Methodol       Date:  2010-04-19       Impact factor: 4.615

6.  Hospitalization of rural and urban infants during the first year of life.

Authors:  Kristin N Ray; Scott A Lorch
Journal:  Pediatrics       Date:  2012-11-05       Impact factor: 7.124

7.  Pediatric high-impact conditions in the United States: retrospective analysis of hospitalizations and associated resource use.

Authors:  Rebecca L Miller; Achamyeleh Gebremariam; Folafoluwa O Odetola
Journal:  BMC Pediatr       Date:  2012-06-08       Impact factor: 2.125

8.  An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions.

Authors:  Heather L Tubbs-Cooley; Jeannie P Cimiotti; Jeffrey H Silber; Douglas M Sloane; Linda H Aiken
Journal:  BMJ Qual Saf       Date:  2013-05-07       Impact factor: 7.035

9.  Nursing Resources Linked to Postsurgical Outcomes for Patients With Opioid Use Disorder: An Observational Study.

Authors:  Rachel French; Matthew D McHugh; Linda H Aiken; Peggy Compton; Salimah H Meghani; J Margo Brooks Carthon
Journal:  Ann Surg Open       Date:  2022-07-22

10.  Predicting length of stay from an electronic patient record system: a primary total knee replacement example.

Authors:  Evelene M Carter; Henry W W Potts
Journal:  BMC Med Inform Decis Mak       Date:  2014-04-04       Impact factor: 2.796

  10 in total

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