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1.
Int J Med Inform ; 170: 104938, 2023 02.
Article in English | MEDLINE | ID: mdl-36455477

ABSTRACT

INTRODUCTION: Large healthcare datasets can provide insight that has the potential to improve outcomes for patients. However, it is important to understand the strengths and limitations of such datasets so that the insights they provide are accurate and useful. The aim of this study was to identify data inconsistencies within the Hospital Episodes Statistics (HES) dataset for autistic patients and assess potential biases introduced through these inconsistencies and their impact on patient outcomes. The study can only identify inconsistencies in recording of autism diagnosis and not whether the inclusion or exclusion of the autism diagnosis is the error. METHODS: Data were extracted from the HES database for the period 1st April 2013 to 31st March 2021 for patients with a diagnosis of autism. First spells in hospital during the study period were identified for each patient and these were linked to any subsequent spell in hospital for the same patient. Data inconsistencies were recorded where autism was not recorded as a diagnosis in a subsequent spell. Features associated with data inconsistencies were identified using a random forest classifiers and regression modelling. RESULTS: Data were available for 172,324 unique patients who had been recorded as having an autism diagnosis on first admission. In total, 43.7 % of subsequent spells were found to have inconsistencies. The features most strongly associated with inconsistencies included greater age, greater deprivation, longer time since the first spell, change in provider, shorter length of stay, being female and a change in the main specialty description. The random forest algorithm had an area under the receiver operating characteristic curve of 0.864 (95 % CI [0.862 - 0.866]) in predicting a data inconsistency. For patients who died in hospital, inconsistencies in their final spell were significantly associated with being 80 years and over, being female, greater deprivation and use of a palliative care code in the death spell. CONCLUSIONS: Data inconsistencies in the HES database were relatively common in autistic patients and were associated a number of patient and hospital admission characteristics. Such inconsistencies have the potential to distort our understanding of service use in key demographic groups.


Subject(s)
Autistic Disorder , Data Accuracy , Humans , Female , Male , Autistic Disorder/diagnosis , Autistic Disorder/epidemiology , Hospitalization , Health Facilities , Records
3.
Diabetes Educ ; 31(6): 818-21, 823, 2005.
Article in English | MEDLINE | ID: mdl-16288089

ABSTRACT

Good blood glucose control in hospitalized adults leads to reduced mortality. Intravenous (IV) insulin has been shown to be an effective way to achieve tight control of blood glucose. Managing IV insulin is a labor-intensive task for nurses and is generally done in intensive care units with high nurse-to-patient ratios. In this 3-month study, intermediate-care general medicine units with a nurse-to-patient ratio of 1 to 5 or 6 were evaluated for effectiveness of monitoring IV insulin. The project, which relied on intensive in-service education, an audit tool, and continuous positive feedback for nurses, yielded positive results.


Subject(s)
Blood Glucose/metabolism , Diabetes Mellitus/drug therapy , Inpatients , Insulin/administration & dosage , Algorithms , Blood Glucose/drug effects , Diabetes Mellitus/nursing , Humans , Injections, Intravenous , Insulin/therapeutic use , Intermediate Care Facilities
4.
Clin J Oncol Nurs ; 8(6): 629-37, 2004 Dec.
Article in English | MEDLINE | ID: mdl-15637958

ABSTRACT

Breast cancer is the most common cancer found in women in the United States. Endocrine therapy is the standard of care for most women with hormone receptor-positive tumors in adjuvant and metastatic settings. The selective estrogen response modifier tamoxifen has been the standard treatment for postmenopausal patients for many years. Numerous new endocrine therapy agents provide women with novel treatment options, including the nonsteroidal aromatase inhibitors anastrozole and letrozole, the steroidal aromatase inhibitor exemestane, and the estrogen receptor antagonist fulvestrant. Clinical trials have begun to define the role of these agents and their unique side-effect profiles. Nurses are vital in supporting patients in the decision-making process, managing side effects of treatment, and making observations to enhance understanding of the patient experience with new treatments. This article will assist nurses in educating patients about endocrine therapy options and their associated potential short- and long-term side effects, as well as treatment demands.


Subject(s)
Antineoplastic Agents, Hormonal/therapeutic use , Breast Neoplasms/drug therapy , Breast Neoplasms/psychology , Estradiol/analogs & derivatives , Quality of Life , Safety , Algorithms , Anastrozole , Antineoplastic Agents, Hormonal/classification , Antineoplastic Agents, Hormonal/pharmacology , Aromatase Inhibitors/therapeutic use , Breast Neoplasms/nursing , Decision Trees , Drug Administration Schedule , Drug Monitoring/methods , Drug Monitoring/nursing , Estradiol/therapeutic use , Female , Fulvestrant , Humans , Letrozole , Neoplasm Recurrence, Local/drug therapy , Nitriles/therapeutic use , Nurse's Role , Oncology Nursing/methods , Patient Education as Topic , Patient Selection , Postmenopause , Selective Estrogen Receptor Modulators/therapeutic use , Social Support , Tamoxifen/therapeutic use , Treatment Outcome , Triazoles/therapeutic use
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