Journal of Korean Academy of Nursing

Original Articles

Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network: Wonjung Noh, GyeongAe Seomun; J Korean Acad Nurs 2015;45(3):429-438. Published online June 30, 2015; DOI: https://doi.org/10.4040/jkan.2015.45.3.429

Purpose

This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN).

Methods

This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0.

Results

We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit.

Conclusion

KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

Citations

Citations to this article as recorded by

Analyzing the performance of health technologies distribution models in primary care services
Elisabetta Garagiola, Alessandro Creazza, Emanuele Porazzi
Measuring Business Excellence.2021; 25(4): 452. CrossRef
Literature review of managerial levers in primary care
Elisabetta Garagiola, Alessandro Creazza, Emanuele Porazzi
Journal of Health Organization and Management.2020; 34(5): 505. CrossRef

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Development of a Prediction Model for Postpartum Depression: Based on the Mediation Effect of Antepartum Depression: Eun Joo Lee, Jeong Sook Park; J Korean Acad Nurs 2015;45(2):211-220. Published online April 30, 2015; DOI: https://doi.org/10.4040/jkan.2015.45.2.211

Abstract PDF

Purpose

This study was done to develop a prediction model for postpartum depression by verifying the mediation effect of antepartum depression. A hypothesized model was developed based on literature reviews and predictors of postpartum depression by Beck.

Methods

Data were collected from 186 pregnant women who had a gestation period of more than 32 weeks and were patients at a maternity hospital, two obstetrics and gynecology specialized hospitals, or the outpatient clinic of K medical center. Data were analysed with descriptive statistics, correlation and exploratory factor analysis using the SPSS/WIN 18.0 and AMOS 18.0 programs.

Results

The final modified model had good fit indices. Parenting stress, antepartum depression and postpartum family support had statistically significant effects on postpartum depression, and defined 74.7% of total explained variance of postpartum depression. Antepartum depression had significant mediation effects on postpartum depression from stress in pregnancy and self-esteem.

Conclusion

The results of this study suggest that it is important to develop nursing interventions including strategies to reduce parenting stress and improve postpartum family support in order to prevent postpartum depression. Especially, it is necessary to detect and treat antepartum depression early to prevent postpartum depression as antepartum depression can affect postpartum depression by mediating antepartum factors.

Citations

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Domestic Violence Experience, Past Depressive Disorder, Unplanned Pregnancy, and Suicide Risk in the First Year Postpartum: Mediating Effect of Postpartum Depression
Mi-Sun Lee, Jung Jae Lee, Hooyeon Lee
Psychiatry Investigation.2024; 21(10): 1129. CrossRef
High-risk Pregnancy Nursing: Analyzing the Impact of Prenatal Stress, Maternal-Fetal Attachment, and Social Support on Prenatal Depression
Jae Hui Choe, Sun Jeong Yun, Hye Young Kim
The Open Nursing Journal.2024;[Epub] CrossRef
Are the effects of stress on antenatal depression mediated by self-esteem and moderated by social support?: a cross-sectional study
Eunjoo Lee
Women's Health Nursing.2024; 30(4): 299. CrossRef
Postpartum Depression and Health: Role of Perceived Social Support among Pakistani Women
Samrah Jamshaid, Najma Iqbal Malik, Irfan Ullah, Sundas Saboor, Fauzia Arain, Domenico De Berardis
Diseases.2023; 11(2): 53. CrossRef
Do taegyo practices, self-esteem, and social support affect maternal-fetal attachment in high-risk pregnant women? A cross-sectional survey
Da-In Kang, Euna Park
Korean Journal of Women Health Nursing.2022; 28(4): 338. CrossRef
Body Appreciation, Depressive Symptoms, and Self-Esteem in Pregnant and Postpartum Brazilian Women
Juliana Fernandes Filgueiras Meireles, Clara Mockdece Neves, Ana Carolina Soares Amaral, Fabiane Frota da Rocha Morgado, Maria Elisa Caputo Ferreira
Frontiers in Global Women's Health.2022;[Epub] CrossRef
Depression and stress in Korean parents: A cohort study
Hyeji Yoo, Sukhee Ahn, Jiwon Oh, Seyeon Park, Jisoon Kim, Minseon Koh
Applied Nursing Research.2021; 62: 151519. CrossRef
Factors influencing prenatal and postpartum depression in Korea: a prospective cohort study
Hyeji Yoo, Sukhee Ahn, Seyeon Park, Jisoon Kim, Jiwon Oh, Minseon Koh
Korean Journal of Women Health Nursing.2021; 27(4): 326. CrossRef
Edinburgh Postnatal Depression Scale used in South Korea
Rora Oh, Young-Ho Khang, Yu-Mi Kim
Journal of the Korean Medical Association.2021; 64(10): 699. CrossRef
Relation between Mother’s Taekyo, Prenatal and Postpartum Depression, and Infant’s Temperament and Colic: A Longitudinal Prospective Approach
Kyung-Sook Bang, Insook Lee, Sungjae Kim, Yunjeong Yi, Iksoo Huh, Sang-Youn Jang, Dasom Kim, Sujin Lee
International Journal of Environmental Research and Public Health.2020; 17(20): 7691. CrossRef
Longitudinal Relationship Study of Depression and Self-Esteem in Postnatal Korean Women Using Autoregressive Cross-Lagged Modeling
Jeong-Won Han, Da-Jung Kim
International Journal of Environmental Research and Public Health.2020; 17(10): 3743. CrossRef
The Effects of Neuroticism on Postpartum Depression: A Dual Mediating Effect of Gratitude and Parenting Stress
Yuji Lee, Myoung-Ho Hyun
Stress.2019; 27(2): 191. CrossRef
Adverse Childhood Experiences and Postpartum Depression in Home Visiting Programs: Prevalence, Association, and Mediating Mechanisms
Joshua P. Mersky, Colleen E. Janczewski
Maternal and Child Health Journal.2018; 22(7): 1051. CrossRef
Development and Validation of a Postpartum Care Mobile Application for First-time Mothers
Ju Yeon Lee, Hye Young Kim
Korean Journal of Women Health Nursing.2017; 23(3): 210. CrossRef

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Predictive Bayesian Network Model Using Electronic Patient Records for Prevention of Hospital-Acquired Pressure Ulcers: In Sook Cho, Eunja Chung; J Korean Acad Nurs 2011;41(3):423-431. Published online June 13, 2011; DOI: https://doi.org/10.4040/jkan.2011.41.3.423

Abstract PDF

Purpose

The study was designed to determine the discriminating ability of a Bayesian network (BN) for predicting risk for pressure ulcers.

Methods

Analysis was done using a retrospective cohort, nursing records representing 21,114 hospital days, 3,348 patients at risk for ulcers, admitted to the intensive care unit of a tertiary teaching hospital between January 2004 and January 2007. A BN model and two logistic regression (LR) versions, model-I and -II, were compared, varying the nature, number and quality of input variables. Classification competence and case coverage of the models were tested and compared using a threefold cross validation method.

Results

Average incidence of ulcers was 6.12%. Of the two LR models, model-I demonstrated better indexes of statistical model fits. The BN model had a sensitivity of 81.95%, specificity of 75.63%, positive and negative predictive values of 35.62% and 96.22% respectively. The area under the receiver operating characteristic (AUROC) was 85.01% implying moderate to good overall performance, which was similar to LR model-I. However, regarding case coverage, the BN model was 100% compared to 15.88% of LR.

Conclusion

Discriminating ability of the BN model was found to be acceptable and case coverage proved to be excellent for clinical use.

Citations

Citations to this article as recorded by

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Korean Journal of Adult Nursing.2024; 36(3): 191. CrossRef
Evaluation of the risk prediction model of pressure injuries in hospitalized patient: A systematic review and meta‐analysis
Yuxia Ma, Xiang He, Tingting Yang, Yifang Yang, Ziyan Yang, Tian Gao, Fanghong Yan, Boling Yan, Juan Wang, Lin Han
Journal of Clinical Nursing.2024;[Epub] CrossRef
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Chaoran Qu, Weixiang Luo, Zhixiong Zeng, Xiaoxu Lin, Xuemei Gong, Xiujuan Wang, Yu Zhang, Yun Li
Heliyon.2022; 8(11): e11361. CrossRef
Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit
Mireia Ladios-Martin, José Fernández-de-Maya, Francisco-Javier Ballesta-López, Adrián Belso-Garzas, Manuel Mas-Asencio, María José Cabañero-Martínez
American Journal of Critical Care.2020; 29(4): e70. CrossRef
Development and Evaluation of Electronic Health Record Data-Driven Predictive Models for Pressure Ulcers
Seul Ki Park, Hyeoun-Ae Park, Hee Hwang
Journal of Korean Academy of Nursing.2019; 49(5): 575. CrossRef
Development and Comparison of Predictive Models for Pressure Injuries in Surgical Patients
Seul Ki Park, Hyeoun-Ae Park, Hee Hwang
Journal of Wound, Ostomy & Continence Nursing.2019; 46(4): 291. CrossRef
Automated Pressure Injury Risk Assessment System Incorporated Into an Electronic Health Record System
Yinji Jin, Taixian Jin, Sun-Mi Lee
Nursing Research.2017; 66(6): 462. CrossRef
Recommendation of Personalized Surveillance Interval of Colonoscopy via Survival Analysis
Jayeon Gu, Eun Sun Kim, Seoung Bum Kim
Journal of Korean Institute of Industrial Engineers.2016; 42(2): 129. CrossRef
Medical Data Based Clinical Pathway Analysis and Automatic Ganeration System
Hanna Park, In Ho Bae, Yong Oock Kim
The Journal of Korea Information and Communications Society.2014; 39C(6): 497. CrossRef
Reusability of EMR Data for Applying Cubbin and Jackson Pressure Ulcer Risk Assessment Scale in Critical Care Patients
Eunkyung Kim, Mona Choi, JuHee Lee, Young Ah Kim
Healthcare Informatics Research.2013; 19(4): 261. CrossRef
Using EHR data to predict hospital-acquired pressure ulcers: A prospective study of a Bayesian Network model
Insook Cho, Ihnsook Park, Eunman Kim, Eunjoon Lee, David W. Bates
International Journal of Medical Informatics.2013; 82(11): 1059. CrossRef

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