Primary Osteoporosis Management by the Marche Region Health Care System

Osteoporosis is an illness that affects the skeleton and is characterized by progressive loss of bone mass as well as by micro architectural deterioration of bone tissue of the same. This condition exposes the person to fracture risk, a particularly feared event not only in terms of individual health but even in terms of economic burden. The fractures, in fact, are accompanied by autonomy loss, institutionalization risk, comorbidity and mortality. On an economic level, the reduction of the same absorbs many more resources than anti-osteoporosis drug therapies even in the event that all patients are reached with ascertained osteoporosis and with 100% adherence to medication. In the elderly, in addition to incurring in loss of bone density risk there is an increase of fall risk. Both of these factors add up causing an increase of fracture risk. Due to the demographic increase and life expectancy, osteoporosis and fracturing events will tend to increase, causing an increase in costs. Today, the data collected in Italy regarding osteoporosis prevalence and fragility fractures incidences are not entirely exhaustive. Concerning fractures, data is reliably collected using the "Diagnosis Related Group Classification" and refers to those of the femur. Detect and describe the pathway that the patient with primary osteoporosis follows in the Marche Region. Through the regional Single Booking Center (CUP) and the websites of the Italian League of Osteoporosis (LIOS) and the Italian Society of Osteoporosis, Mineral Metabolism and Skeleton Diseases (SIOMMMS), eleven services have been identified, belonging to the four health care companies of the Marche Region (Asur, Inrca-Irccs, AO Ospedali Riuniti Marche Nord, AOU Ospedali Riuniti Ancona), which can be contacted for an osteoporosis checkup. A questionnaire was therefore prepared based on the recommendations contained in the SIOMMMS (2012), SIMFER and SIGN (2015) guidelines and sent to the above-mentioned services. The questionnaires are seven, duly completed and used for processing data. In the Marche Region, the medical specialties that deal with osteoporosis are various, demonstrating the fact that this is a "border illness". Concerning the interception of the patient, his sending to a specialized service, the diagnostic approach and the use of risk-scoring tools, there is a substantial homogeneity throughout the regional territory. The patient is sent to the specialized center by the general practitioner (GP) or other specialist, based on the presence of risk factors for osteoporosis alone or on the basis of their presence in association with BMD measurement (body mass density measurement) already known. For the purposes of diagnosis, the investigations required are the dual-energy x-ray absorptiometry (DXA) and the blood test while the use of risk-scoring tools are mainly dictated by the need to define the threshold of pharmacological intervention and give the patient perception of its own fracture risk. The most used algorithm is DeFRA. During the evaluation of the patient, all services detect pain and fall risk. The approach to osteoporosis and fall risk is purely pharmacological. From a non-pharmacological point of view, attention is paid in informing the patient about the modifiable risk factors for osteoporosis and falls. Only some services carry out interventions aimed at promoting adherence to treatment, resorting to different actions. In conclusion, the main critical issues relating to taking care of a fracture risk patient are: accessibility to information, early and exhaustive interception of the population at risk, detection of the fracture risk in relation to bone demineralization and fall risk, adherence to therapy.

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Risco de quedas em idosos residentes na comunidade: revisão sistemática da literatura

Revista Gaúcha de Enfermagem ◽

10.1590/1983-1447.2016.04.55030 ◽

2016 ◽

Vol 37 (4) ◽

Cited By ~ 7

Author(s):

Luís Manuel Mota Sousa ◽

Cristina Maria Alves Marques-Vieira ◽

Maria Nilza Guimarães Nogueira de Caldevilla ◽

Cristina Maria Alves Dias Henriques ◽

Sandy Silva Pedro Severino ◽

...

Keyword(s):

Risk Factors ◽

Risk Assessment ◽

Health Care ◽

Primary Health Care ◽

Fall Risk ◽

Community Health Services ◽

Community Dwelling ◽

Accidental Fall ◽

Primary Health ◽

Fall Risk Factors

RESUMO Objetivo Identificar fatores de risco de queda em idosos residentes na comunidade para atualização da taxonomia II da NANDA Internacional. Método Revisão sistemática da literatura, com pesquisa na plataforma EBSCOHost®, na CINAHL e MEDLINE, no período de dezembro de 2010 a dezembro de 2014. Utilizaram-se os descritores (Fall* OR Accidental Fall) AND (Community Dwelling OR Community Health Services OR Primary health care) AND (Risk OR Risk Assessment OR Fall Risk Factors) AND (Fall* OR Accidental Fall) AND (Community Dwelling OR older) AND Nurs* AND Fall Risk Factors. Resultados Obteve-se uma amostra de 62 estudos e um total de 50 fatores de risco, dos quais, apenas 38 estão presentes na classificação. Conclusões São propostas duas novas categorias de fatores: os psicológicos e socioeconômicos. Foram identificados novos fatores de risco de queda dos idosos residentes na comunidade, o que contribui para a atualização deste diagnóstico na taxonomia II da NANDA Internacional.

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An Overview of Fall Prevention Strategies Among Adult Patients in Hospital Settings

Croatian Nursing Journal ◽

10.24141/2/4/2/7 ◽

2020 ◽

Vol 4 (2) ◽

pp. 205-217

Author(s):

Mladen Jurišković ◽

Martina Smrekar

Keyword(s):

Risk Factors ◽

Health Care ◽

Fall Prevention ◽

Health Care Professionals ◽

Fall Risk ◽

Medical Expenditure ◽

Hospital System ◽

Effective Strategies ◽

Hospitalised Patients ◽

Prevention Interventions

Falls present a major challenge for health care systems: they correlate with poor patient outcomes, extend the length of hospitalization, and increase overall medical expenditure. According to existing literature, risk factors for the occurrence of falls include the male gender, urinary incontinence, muscle weakness, agitation or confusion, and dementia. Studies have shown that the combined practice of identifying risk factors and implementing appropriate fall prevention interventions leads to a reduction in the incidence of falls among hospital patients. As the largest group of health professionals committed to providing high-quality care, nurses play an important role in preventing falls among patient populations. In order to prevent falls and maintain patient safety, it is important to identify the most effective strategies for fall prevention. This study presents an overview of previously published strategies and intervention practices on fall prevention in hospital settings around the world. The most common interventions include fall risk assessment, environment/equipment modifications, patient education/family education on fall prevention interventions, staff education on fall reporting and fall prevention, fall risk alerts, medication management, physical fitness of patients, assistance with transfer and toileting and effective team communication and leadership. Ultimately, it is incumbent upon nurses, other health-care professionals and the entire hospital system to develop effective strategies in order to prevent falls among hospitalised patients.

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Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

JMIR Medical Informatics ◽

10.2196/16970 ◽

2020 ◽

Vol 8 (4) ◽

pp. e16970 ◽

Cited By ~ 1

Author(s):

Hayao Nakatani ◽

Masatoshi Nakao ◽

Hidefumi Uchiyama ◽

Hiroyoshi Toyoshiba ◽

Chikayuki Ochiai

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Health Care ◽

Electronic Medical Records ◽

Language Processing ◽

Medical Records ◽

Fall Risk ◽

Data Set ◽

Inpatient Falls ◽

Risk Factors For Falls

Background Falls in hospitals are the most common risk factor that affects the safety of inpatients and can result in severe harm. Therefore, preventing falls is one of the most important areas of risk management for health care organizations. However, existing methods for predicting falls are laborious and costly. Objective The objective of this study is to verify whether hospital inpatient falls can be predicted through the analysis of a single input—unstructured nursing records obtained from Japanese electronic medical records (EMRs)—using a natural language processing (NLP) algorithm and machine learning. Methods The nursing records of 335 fallers and 408 nonfallers for a 12-month period were extracted from the EMRs of an acute care hospital and randomly divided into a learning data set and test data set. The former data set was subjected to NLP and machine learning to extract morphemes that contributed to separating fallers from nonfallers to construct a model for predicting falls. Then, the latter data set was used to determine the predictive value of the model using receiver operating characteristic (ROC) analysis. Results The prediction of falls using the test data set showed high accuracy, with an area under the ROC curve, sensitivity, specificity, and odds ratio of mean 0.834 (SD 0.005), mean 0.769 (SD 0.013), mean 0.785 (SD 0.020), and mean 12.27 (SD 1.11) for five independent experiments, respectively. The morphemes incorporated into the final model included many words closely related to known risk factors for falls, such as the use of psychotropic drugs, state of consciousness, and mobility, thereby demonstrating that an NLP algorithm combined with machine learning can effectively extract risk factors for falls from nursing records. Conclusions We successfully established that falls among hospital inpatients can be predicted by analyzing nursing records using an NLP algorithm and machine learning. Therefore, it may be possible to develop a fall risk monitoring system that analyzes nursing records daily and alerts health care professionals when the fall risk of an inpatient is increased.

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Prevalence and Fracture Risk of Osteoporosis in Patients with Rheumatoid Arthritis: A Multicenter Comparative Study of the FRAX and WHO Criteria

Journal of Clinical Medicine ◽

10.3390/jcm7120507 ◽

2018 ◽

Vol 7 (12) ◽

pp. 507 ◽

Cited By ~ 10

Author(s):

Sang Choi ◽

Seong-Ryul Kwon ◽

Ju-Yang Jung ◽

Hyoun-Ah Kim ◽

Sung-Soo Kim ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Risk Factors ◽

High Risk ◽

Fracture Risk ◽

Disease Duration ◽

Osteoporotic Fractures ◽

World Health ◽

Pharmacological Intervention ◽

Who Criteria ◽

Independent Risk Factors

(1) Background: We evaluated the prevalence and fracture risk of osteoporosis in patients with rheumatoid arthritis (RA), and compared the fracture risk assessment tool (FRAX) criteria and bone mineral density (BMD) criteria established by the World Health Organization (WHO). (2) Methods: This retrospective cross-sectional study, which included 479 RA patients in 5 hospitals, was conducted between January 2012 and December 2016. The FRAX criteria for high-risk osteoporotic fractures were calculated including and excluding the BMD values, respectively. The definition of high risk for fracture by FRAX criteria and BMD criteria by WHO was 10-year probability of ≥ 20% for major osteoporotic fracture or ≥ 3% for hip fracture, and T score ≤ −2.5 or Z score ≤ −2.0, respectively. (3) Results: The mean age was 61.7 ± 11.9 years. The study included 426 female patients (88.9%), 353 (82.9%) of whom were postmenopausal. Osteoporotic fractures were detected in 81 (16.9%) patients. The numbers of candidates for pharmacological intervention using the FRAX criteria with and without BMD and the WHO criteria were 226 (47.2%), 292 (61%), and 160 (33.4%), respectively. Only 69.2%–77% of the patients in the high-risk group using the FRAX criteria were receiving osteoporosis treatments. The following were significant using the WHO criteria: female (OR 3.55, 95% CI 1.46–8.63), age (OR 1.1, 95% CI 1.08–1.13), and BMI (OR 0.8, 95% CI 0.75–0.87). Glucocorticoid dose (OR 1.09, 95% CI 1.01–1.17), age (OR 1.09, 95% CI 1.06–1.12), and disease duration (OR 1.01, 95% CI 1–1.01) were independent risk factors for fracture. (4) Conclusions: The proportion of RA patients with a high risk of osteoporotic fractures was 33.4%–61%. Only 69.2%–77% of candidate patients were receiving osteoporotic treatments while applying FRAX criteria. Independent risk factors for osteoporotic fractures in RA patients were age, the dose of glucocorticoid, and disease duration.

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Missed opportunities for prevention of hip fracture in older patients

Vojnosanitetski pregled ◽

10.2298/vsp1205420d ◽

2012 ◽

Vol 69 (5) ◽

pp. 420-424 ◽

Cited By ~ 5

Author(s):

Emilija Dubljanin-Raspopovic ◽

Ljiljana Denic-Markovic ◽

Goran Tulic ◽

Mirko Grajic ◽

Sanja Tomanovic ◽

...

Keyword(s):

Risk Factors ◽

Clinical Practice ◽

Hip Fracture ◽

Fracture Risk ◽

Fall Risk ◽

Risk Level ◽

Bone Density Measurement ◽

Prevention Strategies ◽

Fall Risk Factors ◽

Bone Mineral Density Testing

Background/Aim. Osteoporotic fractures are a major cause of morbidity in the population. Therefore, fracture prevention strategies should be a major concern, and one of the priorities in the primary health care system. The aim of the study was to assess fracture and fall risk factors, and fracture risk level in patients with acute hip fracture, and to evaluate if there had been adequate osteoporosis treatment prior to fracture in this group of patients. Methods. Fracture and fall risk factors were assessed in 342 patients, ? 65 years old, hospitalized due to acute hip fracture at the Clinic for Orthopedic Surgery and Traumatology, Clinical Centre of Serbia in a 12-month period. Fall risk factors were assessed with the Fracture Risk Assessment (FRAX?) algorithm, and patients were classified in respect to fracture risk level. Results. Hip fracture occurred in the majority of the patients in the high risk group (74.2%), where no additional bone mineral density testing was needed. Less than 10% of the patients had a diagnosis of osteoporosis before injury, while less than 2% were treated. Cognitive impairment (95.3%), visual impairment (58.2%), lower index of daily activities (51.8%), and depression (47.1%) were the most frequently observed fall risk factors. Conclusion. The results of our investigation reveal insufficient identification of clinical fracture risk factors in the primary care setting, inadequate treatment of osteoporosis and, consequently, ineffective prevention of hip fractures in the geriatric population. The introduction of FRAX? into clinical practice enables more effective acknowledgment of patients with elevated fracture risk, even if bone density measurement is not available. The results of this study have a special significance for everyday clinical practice, because they impose a need for reviewing the existing approaches to osteoporosis prevention, and precise definiment of hip prevention strategies.

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Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study (Preprint)

10.2196/preprints.16970 ◽

2019 ◽

Author(s):

Hayao Nakatani ◽

Masatoshi Nakao ◽

Hidefumi Uchiyama ◽

Hiroyoshi Toyoshiba ◽

Chikayuki Ochiai

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Health Care ◽

Electronic Medical Records ◽

Language Processing ◽

Medical Records ◽

Fall Risk ◽

Data Set ◽

Inpatient Falls ◽

Risk Factors For Falls

BACKGROUND Falls in hospitals are the most common risk factor that affects the safety of inpatients and can result in severe harm. Therefore, preventing falls is one of the most important areas of risk management for health care organizations. However, existing methods for predicting falls are laborious and costly. OBJECTIVE The objective of this study is to verify whether hospital inpatient falls can be predicted through the analysis of a single input—unstructured nursing records obtained from Japanese electronic medical records (EMRs)—using a natural language processing (NLP) algorithm and machine learning. METHODS The nursing records of 335 fallers and 408 nonfallers for a 12-month period were extracted from the EMRs of an acute care hospital and randomly divided into a learning data set and test data set. The former data set was subjected to NLP and machine learning to extract morphemes that contributed to separating fallers from nonfallers to construct a model for predicting falls. Then, the latter data set was used to determine the predictive value of the model using receiver operating characteristic (ROC) analysis. RESULTS The prediction of falls using the test data set showed high accuracy, with an area under the ROC curve, sensitivity, specificity, and odds ratio of mean 0.834 (SD 0.005), mean 0.769 (SD 0.013), mean 0.785 (SD 0.020), and mean 12.27 (SD 1.11) for five independent experiments, respectively. The morphemes incorporated into the final model included many words closely related to known risk factors for falls, such as the use of psychotropic drugs, state of consciousness, and mobility, thereby demonstrating that an NLP algorithm combined with machine learning can effectively extract risk factors for falls from nursing records. CONCLUSIONS We successfully established that falls among hospital inpatients can be predicted by analyzing nursing records using an NLP algorithm and machine learning. Therefore, it may be possible to develop a fall risk monitoring system that analyzes nursing records daily and alerts health care professionals when the fall risk of an inpatient is increased.

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Burnout and Wellness: The Anesthesiologist’s Perspective

American Journal of Lifestyle Medicine ◽

10.1177/1559827620911645 ◽

2020 ◽

pp. 155982762091164 ◽

Cited By ~ 2

Author(s):

Bryan T. Romito ◽

Ejike N. Okoro ◽

Jenny R. B. Ringqvist ◽

Kristina L. Goff

Keyword(s):

Risk Factors ◽

Health Care ◽

Health Care Providers ◽

Treatment Strategies ◽

Workplace Stress ◽

Personal Accomplishment ◽

Burnout Syndrome ◽

Future Research ◽

Care Providers ◽

Medical Specialties

Burnout syndrome results from unmanaged chronic workplace stress. It is characterized by emotional exhaustion, lack of a sense of personal accomplishment, and depersonalization. Burnout is associated with the development of poor work-related outcomes, mental health disorders, substance abuse, and cardiovascular disease. Burnout in physicians and other health care providers can negatively affect patient care. The prevalence of burnout in anesthesiology is among the highest of all medical specialties, with rates approaching 40%. Unique risk factors for the development of burnout in anesthesiologists may include environmental social isolation, long work hours, lack of control over one’s career, and the presence of certain personality traits that select for a career in anesthesia. System-based interventions targeting workplace contributions to burnout and individual resilience and mindfulness training can be helpful in reducing burnout symptoms. Future research efforts examining both the health care environmental structure and the specific burnout risk factors for anesthesiologists will help produce targeted treatment strategies for members of the anesthesiology community.

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Knowledge, Attitudes on Fall and Awareness of Hospitalized Patient’s Fall Risk Factors Among the Nurses Working in Tertiary Care Hospitals.

10.21203/rs.3.rs-28988/v1 ◽

2020 ◽

Author(s):

Kavin Mozhi James ◽

Divya Ravikumar ◽

Sindhura Myneni ◽

Poonguzhali Sivagnanam ◽

Poongodi Chellapandian ◽

...

Keyword(s):

Risk Factors ◽

Health Care ◽

Patient Safety ◽

Fall Risk ◽

Tertiary Care ◽

Favorable Attitude ◽

Survey Method ◽

Fall Risk Factors ◽

Level Of Knowledge ◽

Tertiary Care Hospitals

Abstract Back ground: Fall is the most common patient safety incident in health care organization. This study was initiated to obtain information regarding knowledge & attitude on fall and awareness of fall risk factors among nurses to device evidence based and multidisciplinary educational and training programme to improve patient safety and thereby reducing morbidity and mortality associated with fall. Methods: A descriptive cross sectional survey study was conducted among 339 registered nurses working in Tertiary care hospitals across Chennai, Tamil Nadu, India. Modified version of previously validated standard questionnaire was administered by the investigators through online survey method to explore the level of knowledge &attitude on fall and awareness of inpatient fall risk factors among Nurses. Results: In this study, 15.6% of participants had adequate knowledge on fall, 57.2% had favorable attitude towards fall and 38.3% adequate awareness on fall risk factors. Years of experience in nursing has statistical significant association with level of knowledge on fall. The participant’s attitude towards fall had statistical significant relationship with age, education, experience in nursing and previous patient fall experience. The correlation between fall knowledge, attitude of fall and awareness of fall risk factors were highly significant. Majority of the participants expressed their favorable attitude towards need for fall preventive education. Conclusion: In our study, it is evident that there is a void which has to be filled to improve the knowledge, attitude and awareness on fall and its risk factors .There is a need for extensive education and holistic, multifactorial and interdisciplinary training program to be undertaken through various health care organizations.

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The Preschool Stuttering Screen for Health Care Professionals

Perspectives on Fluency and Fluency Disorders ◽

10.1044/ffd21.2.59 ◽

2011 ◽

Vol 21 (2) ◽

pp. 59-62

Author(s):

Joseph Donaher ◽

Christina Deery ◽

Sarah Vogel

Keyword(s):

Risk Factors ◽

Health Care ◽

Differential Diagnosis ◽

Preschool Children ◽

Health Care Professionals ◽

Healthcare Professionals ◽

Evidence Based ◽

Developmental Profile

Healthcare professionals require a thorough understanding of stuttering since they frequently play an important role in the identification and differential diagnosis of stuttering for preschool children. This paper introduces The Preschool Stuttering Screen for Healthcare Professionals (PSSHP) which highlights risk factors identified in the literature as being associated with persistent stuttering. By integrating the results of the checklist with a child’s developmental profile, healthcare professionals can make better-informed, evidence-based decisions for their patients.

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