Objectives: This report presents national estimates of the use of non-Federal short-stay hospitals in the United States during 2002 and trend data for selected variables. Numbers and rates of discharges, diagnoses, and procedures are shown by age and sex. Average lengths of stay are presented for all discharges and for selected diagnostic categories by age and sex.
Methods: The estimates are based on medical abstract data collected through the 2002 National Hospital Discharge Survey. The survey has been conducted annually since 1965 by the National Center for Health Statistics. Diagnoses and procedures presented are coded using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM).
Results: Trends in the utilization of non-Federal short-stay hospitals show that the average age and age distribution of inpatients has changed dramatically from 1970 through 2002. In 1970, the average age of all inpatients was 40.7 years compared with 52.1 years in 2002. The percent of discharges aged 65 years and over comprised 20 percent of hospital discharges in 1970 whereas they comprised 38 percent in 2002. During this same period, the percent of inpatients under 15 years of age declined from 13 to 8 percent and inpatients 15-44 years of age declined from 43 to 32 percent. The percent of inpatients aged 45-64 years was more stable during these 23 years. In 2002, there were an estimated 33.7 million hospital discharges, excluding newborn infants. The discharge rate was 1,174.6 per 10,000 population. The rate of respiratory disease diagnoses among persons 65 years and over was significantly higher than for other age groups and has risen since 1975. There were 42.5 million procedures performed on inpatients during 2002. About one-quarter of all procedures performed on females were obstetrical. Almost one-quarter of all procedures performed on males were cardiovascular.
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J Spinal Cord Med
January 2025
The Hopkins Centre, Griffith University, Brisbane, Australia.
Objectives: To determine rates of opioid and concomitant antidepressant, anticonvulsant and benzodiazepine dispensing in the post-discharge period, after acute spinal cord injury (SCI).
Design: Single-center prospective cohort study with 12-month linked pharmaceutical data.
Setting: Community pharmaceutical dispensing.
Iowa Orthop J
January 2025
Department of Orthopedic Surgery, NYU Langone Health, New York, New York, USA.
Background: Quadriceps weakness following total knee arthroplasty (TKA) delays rehabilitation and increases fall risk. The combined impact of tourniquets and adductor canal blocks (ACBs) on postoperative quadriceps strength has not been defined. This study evaluated the early effects of tourniquet and/or ACB usage on quadriceps strength following TKA.
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December 2024
Cardiology, Wexham Park Hospital, Frimley Health NHS Foundation Trust, Slough, GBR.
Introduction Surgical inpatients frequently require peripherally inserted central catheters (PICCs) for parenteral feeding and administration of medication. PICCs may cause upper limb deep venous thrombosis (ULDVT), which impacts patient morbidity. We investigated the risk and prevention of PICC-ULDVT in hospitalised surgical inpatients.
View Article and Find Full Text PDFJ Opioid Manag
January 2025
Internal Medicine Clinical Pharmacist, Mayo Clinic St. Mary's Hospital, Rochester, Minnesota.
Pharmacists nationwide may play a critical role in expanding naloxone access after several states enacted legislation to allow pharmacist prescribing of opioid antagonists. This created a unique opportunity for inpatient pharmacists to participate in combating the opioid epidemic by prescribing naloxone at hospital discharge. A multifaceted intervention was developed to identify and educate hospitalized patients eligible for naloxone prescribing.
View Article and Find Full Text PDFHealth Aff (Millwood)
January 2025
Jordan Everson, Office of the Assistant Secretary for Technology Policy, Washington, D.C.
Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES. We analyzed data from the 2023 American Hospital Association Annual Survey Information Technology Supplement to identify how AI and predictive models are used and evaluated for accuracy and bias in hospitals. Hospitals use AI and predictive models to predict health trajectories or risks for inpatients, identify high-risk outpatients to inform follow-up care, monitor health, recommend treatments, simplify or automate billing procedures, and facilitate scheduling.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!