Objectives:This study aimed to survey the geriatric nursing competencies of clinical nursing staff in Chongqing City,China,and provide suggestions to enhance these competencies.Methods:This study was conducted in 204 ...Objectives:This study aimed to survey the geriatric nursing competencies of clinical nursing staff in Chongqing City,China,and provide suggestions to enhance these competencies.Methods:This study was conducted in 204 hospitals in Southwest China from December 24,2022 to January 7,2023.The“Geriatric Nursing Competence of Clinical Nurse Investigation Tool”was used to explore factors that influence geriatric nurses’competencies via stratified sampling.The survey was conducted by distributing and collecting questionnaires through the online platform Wenjuanxing.Results:A total of 10,692 nurses answered the questionnaires.Of these questionnaires,9,442 were valid.The total geriatric nursing competence score of the clinical nursing staff was 2.29±0.81,the secondary hospital score was 2.23±0.78,and the tertiary hospital’s overall mean score was 2.33±0.83.The factors that influenced secondary hospitals included the department of medicine,age of nurses and total length of career(P<0.05).The factors that influenced tertiary hospitals included the department of medicine,age of nurses,nurses’professional title,and geriatric practical advanced nurses’certification(P<0.05).Conclusions:Geriatric nursing competence among clinical nursing staff is imbalanced at a lower-middle level and is influenced by various factors.Thefindings highlight the need for further clinical training in geriatric nursing.The training of geriatric nurses should focus on necessary clinical skills and on preparing them to adequately manage comprehensive geriatric syndromes.展开更多
Background： China began to implement the national medical and health system and public hospital reforms in 2009 and 2012, respectively. Anhui Province is one of the four pilot provinces, and the medical reform measur...Background： China began to implement the national medical and health system and public hospital reforms in 2009 and 2012, respectively. Anhui Province is one of the four pilot provinces, and the medical reform measures received wide attention nationwide. The effectiveness of the above reform needs to get attention. This study aimed to master the efficiency and productivity of county-level public hospitals based on the data envelopment analysis （DEA） model and Malmquist index in Anhui, China, and then provide improvement measures for the future hospital development. Methods： We chose 12 country-level hospitals based on geographical distribution and the economic development level inAnhui Province. Relevant data that were collected in the field and then sorted were provided by the administrative departments of the hospitals. DEA models were used to calculate the dynamic efficiency and Malmquist index factors for the 12 institutions. Results： During 2010-2015, the overall average relative service efficiency of 12 county-level public hospitals was 0.926, and the number of hospitals achieved an effective DEA for each year from 2010 to 2015 was 4, 6, 7, 7, 6, and 8, respectively, as measured using DEA. During this same period, the average overall production efficiency was 0.983, and the total productivity factor had declined. The overall production efficiency of five hospitals was 〉1, and the rest are 〈1 between 2010 and 2015. Conclusions： In 2010-2015, the relative service efficiency of 12 county-level public hospitals in Anhui Province showed a decreasing trend, and the service efficiency of each hospital changed. In the past 6 years, although some hospitals have been effective, the efficiency of the county-level public hospitals in Anhui Province has not improved significantly, and the total factor productivity has not been effectively improved. County-level public hospitals need to combine their own reality to find their own deficiencies.展开更多
China will encourage more private and foreign investment in hospitals and clinics The State Council on December 3 announced new policies to encourage private and foreign capital in China’s medical sector to meet the
基金supported by a key Program of the Chongqing Scientific and Technological Commission(Grant Number.CSTB2022TIAD-KPX0165).
文摘Objectives:This study aimed to survey the geriatric nursing competencies of clinical nursing staff in Chongqing City,China,and provide suggestions to enhance these competencies.Methods:This study was conducted in 204 hospitals in Southwest China from December 24,2022 to January 7,2023.The“Geriatric Nursing Competence of Clinical Nurse Investigation Tool”was used to explore factors that influence geriatric nurses’competencies via stratified sampling.The survey was conducted by distributing and collecting questionnaires through the online platform Wenjuanxing.Results:A total of 10,692 nurses answered the questionnaires.Of these questionnaires,9,442 were valid.The total geriatric nursing competence score of the clinical nursing staff was 2.29±0.81,the secondary hospital score was 2.23±0.78,and the tertiary hospital’s overall mean score was 2.33±0.83.The factors that influenced secondary hospitals included the department of medicine,age of nurses and total length of career(P<0.05).The factors that influenced tertiary hospitals included the department of medicine,age of nurses,nurses’professional title,and geriatric practical advanced nurses’certification(P<0.05).Conclusions:Geriatric nursing competence among clinical nursing staff is imbalanced at a lower-middle level and is influenced by various factors.Thefindings highlight the need for further clinical training in geriatric nursing.The training of geriatric nurses should focus on necessary clinical skills and on preparing them to adequately manage comprehensive geriatric syndromes.
基金This research＇was supported by the grants from the National Natural Science Foundation of China （No. 71473003）, and National Natural Science Foundation of China （71774001）.
文摘Background： China began to implement the national medical and health system and public hospital reforms in 2009 and 2012, respectively. Anhui Province is one of the four pilot provinces, and the medical reform measures received wide attention nationwide. The effectiveness of the above reform needs to get attention. This study aimed to master the efficiency and productivity of county-level public hospitals based on the data envelopment analysis （DEA） model and Malmquist index in Anhui, China, and then provide improvement measures for the future hospital development. Methods： We chose 12 country-level hospitals based on geographical distribution and the economic development level inAnhui Province. Relevant data that were collected in the field and then sorted were provided by the administrative departments of the hospitals. DEA models were used to calculate the dynamic efficiency and Malmquist index factors for the 12 institutions. Results： During 2010-2015, the overall average relative service efficiency of 12 county-level public hospitals was 0.926, and the number of hospitals achieved an effective DEA for each year from 2010 to 2015 was 4, 6, 7, 7, 6, and 8, respectively, as measured using DEA. During this same period, the average overall production efficiency was 0.983, and the total productivity factor had declined. The overall production efficiency of five hospitals was 〉1, and the rest are 〈1 between 2010 and 2015. Conclusions： In 2010-2015, the relative service efficiency of 12 county-level public hospitals in Anhui Province showed a decreasing trend, and the service efficiency of each hospital changed. In the past 6 years, although some hospitals have been effective, the efficiency of the county-level public hospitals in Anhui Province has not improved significantly, and the total factor productivity has not been effectively improved. County-level public hospitals need to combine their own reality to find their own deficiencies.
文摘China will encourage more private and foreign investment in hospitals and clinics The State Council on December 3 announced new policies to encourage private and foreign capital in China’s medical sector to meet the
