Reliability Verification and Practical Effectiveness Evaluation of the Nursing Administration Analysis Formulae Based on PSYCHOMS

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1 Health, 204, 6, Published Online Deceber 204 in SciRes. Reliability Verification and Practical Effectiveness Evaluation of the Nursing Adinistration Analysis Forulae Based on PSYCHOMS Misao Miyagawa, Kaori Katou 2, Yuko Yasuhara 3, Kazuyuki Matsuoto 4, Motoyuki Suzuki 5, Takako Takebayashi 6, Tetsuya Tanioka 3, Rozzano Locsin 3 Departent of Nursing, Faculty of Health and Welfare, Tokushia Bunri University, Tokushia, Japan 2 The Major in Nursing School of Health Sciences, The University of Tokushia, Tokushia, Japan 3 Institute of Health Biosciences, The University of Tokushia Graduate School, Tokushia, Japan 4 Faculty of Engineering, The University of Tokushia, Tokushia, Japan 5 Faculty of inforation Science and Technology, Osaka Institute of Technology, Osaka, Japan 6 Uibenoori Hospital, Kochi, Japan Eail: iyagawa@tks.bunri-u.ac.jp, c @tokushia-u.ac.jp, yasuhara@edsci.tokushia-u.ac.jp, atuoto@is.tokushia-u.ac.jp, oto@.ieice.org, ttakebayashi@uibeno-ori.co, tanioka.tetsuya@tokushia-u.ac.jp, locsin@edsci.tokushia-u.ac.jp Received 7 October 204; revised 23 Noveber 204; accepted 0 Deceber 204 Copyright 204 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Coons Attribution International License (CC BY). Abstract In psychiatric hospitals, the ratios between patients versus physician and patients versus nurse are low as copared to those in general hospitals. Furtherore, usages of electronic edical records are also low so that nurse adinistrators are liited in their ability to copile, analyze, and generate patient care staffing inforation for their adinistrative use. Psychiatric nurse adinistrators anticipate the developent of a nursing adinistration analysis syste that could perfor personnel data siulation, anage inforation on nursing staff, and anage ward/ practice operations. Responding to this situation, the authors developed a nursing adinistration analysis syste utilizing forulae fro the Psychiatric Outcoe Manageent Syste, PSYCHOMS to aid nurse adinistrators. Such forulae are awaiting patent approval. The purpose of this study was to exaine the validity of the forulae and the Structured Query Language (SQL) stateent, and its practical effectiveness of analyzing data. The study findings showed that two kinds of coputation expressions a classification and extraction were able to display required inforation desired by nurse adinistrators. Moreover, significant inforation critical to assigning staff was validated to ensure high quality of nursing care according to the function and characteristic of the hospital ward. How to cite this paper: Miyagawa, M., Katou, K., Yasuhara, Y., Matsuoto, K., Suzuki, M., Takebayashi, T., Tanioka, T. and Locsin, R. (204) Reliability Verification and Practical Effectiveness Evaluation of the Nursing Adinistration Analysis Forulae Based on PSYCHOMS. Health, 6,

2 Keywords Analysis Forulae, Nursing Adinistration Analysis, Psychiatric Hospital, PSYCHOMS. Introduction Efforts have been extensive in iproving the quality of care and hospitalization of psychiatric patients particularly in their treatent, and the quality of care available counity ental health and social welfare services []-[4]. It is known that Japanese psychiatric hospitals are overcrowded, involving long patient hospitalization stays, thereby increasing their likelihood of having coplicating diseases because of aging. As a vision of the refor for ental health welfare of 2004, psychiatric and ental health treatents towards counity care of the entally ill were prooted instead of continuing inpatient psychiatric hospitalization [5]. In order to iprove the quality of life of psychiatric patients through accurate and appropriate ental health services, nurse adinistrators ust be able to deterine how to provide high-quality nursing care and integrated rehabilitation which are ost effective and efficient [6]-[8]. However, in psychiatric hospitals, there are few physicians and nurses as copared to the general hospital. Patient and physician ratio is 48 patients to one physician, while patients and nurse ratio is 5 patients to one nurse. However, in general hospitals in Japan, the average ratio of patients to physician is 6 patients to one physician, and 7 patients to one nurse [9]. In addition, the proble of long-stay hospitalization is still a pressing issue in Japan [0] []. Therefore, as the supporting syste for providing axiu efficiency of edical services using liited huan and aterial resources, the Psychiatric Outcoe Manageent Syste (PSYCHOMS registered tradeark) was developed guided by perspectives fro a nursing standpoint. Analyzing the current situation in psychiatric hospitals, foring strategies and using these in actual nursing practice are keys for achieving and aintaining high-quality huan health care [2] [3], thereby supporting the critical nature of nurse adinistrators work of analyzing inforation/data. While the scope of nursing adinistration has expanded in recent years, and the inforation required for nursing adinistration has increased draatically in both volue and diversity [4], the clinical site has also changed radically with each daily practice. Nursing adinistrators are asked to ake tiely and infored decisions according to data derived fro situations founded on increasing evidences which are exact and central to the undertaking at hand. However, nurse adinistrators are liited in their ability to copile and analyze inforation for nursing adinistration. Nurse adinistrators in psychiatric wards would greatly benefit fro the developent of a nursing adinistration analysis syste that could perfor personnel arrangeent siulation, anage inforation on nursing staff and ward operations [5]. PSYCHOMS can allow nurse adinistrators to ake these appropriate and critical decisions. Within the PSYCHOMS, the nursing adinistration analysis forula was developed to benefit nurse adinistrators [6]. This is currently under consideration for patent approval [7]. The purpose of this study was to exaine the validity of the forulae and the Structured Query Language (SQL) stateent, and its practical effectiveness of analyzing data. 2. Methods 2.. Setting of the Study Inforation on the psychiatric hospital A for analysis: the specialties of psychiatric hospital A where analytical inforation was acquired include the Departent of Psychiatry and Psychosoatic Medicine. In-patient wards are for psychiatric acute ward ( ward, 60 beds), psychiatric chronic wards (3 wards, 80 beds), neurological diseases treatent ward ( ward, 60 beds), and deentia treatent ward ( ward, 55 beds) Analysis Forulae This analysis forula [6] [7] uses two different approaches: ) data are classified into types of inforation as desired by the nursing adinistrator, 2) extracted data required by the nursing adinistrator. This forula can be classified inforation registered in the database based upon categories (S_category) and conditions 304

3 (S_condition) established by the user, fro which the inforation is extracted that correspond to the condition. Analysis forulae are indicated below: inf ( x) = S category ( i x) S condition( j x) i= inf 2 = _ inf 3 = 2 _ () (2) (3) inf ( ): analytical (classification/extraction) inforation; x: the selected condition; i: the factor eeting the condition; j: the factor eeting the condition x; : the total nuber (record); S_category: the selected category; S_condition: the selected condition; EF (): the first analytical result; EF (2): the second analytical result; EF (n ): the n st analytical result. inf n( x) = EF ( n ) S _ condition( j x) (4) In addition, the operator in forulae ()-(4) represents the extraction of overlapping parts of records in the forer and latter parts and on the right side of the equation. To view classified data, when there are ultiple categories and/or conditions, records atching each category and condition ust all be extracted fro the data tables of the database Methods of Verification Test ) To build the database, using the data for nursing adinistration of the hospital A. 2) To output data fro the created database, using SQL search stateents, being based on the following analysis fraework (Figure ). 3) To evaluate quantitatively the output data of the practical effectiveness using the nursing adinistration analysis forulae, fro the viewpoint of psychiatric nurse adinistrators. There were eight evaluators: 2 nurse adinistrators, 3 nursing adinistration researchers, and 3 persons experienced in software prograing. The period was fro August 204 to October Ethical Considerations Ethical consideration for this study was assured by obtaining perission to conduct this study fro the Clinical Research and Ethical Review Board of Tokushia University (receipt nuber: 50-). Figure. Analysis fraework: analytical process and estiated results. 305

4 3. Results 3.. Analysis : Collation of Nursing Staff Assignent in Psychiatric Chronic Wards and Staff Nurses Copetence Levels Step : Display the nuber of nursing stuff applicable to a career ladder level of each psychiatric chronic ward (Table ). Forula inf ( x) = S category ( i x) S condition( j x) i= () SQL stateent SELECT: ward_function, hospital_ward, career_ladder_level_by_self, career_ladder_level_by_a_head_nurse, COUNT(*) FROM: nursing_staff_adinistration_database WHERE: ward_function = psychiatric_chronic_wards GROUP BY: ward_function, hospital_ward, career_ladder_level_by_self, career_ladder_level_by_a_head_ nurse Step 2: Display the nursing staff nae which shows the career ladder level by self and by a head nurse. The difference can be seen in the classified result of Step (Table 2). Forula inf 2 = _ Data table () is a table holding all the records of the staff applicable to inf (x). (2) SQL stateent SELECT: ward_function, hospital_ward, nursing_staff_nae, career_ladder_level_by_self, career_ladder_ level_by_a_head_nurse FROM: data_table () WHERE: career_ladder_level_by_self <> career_ladder_level_by_a_head_nurse Step 3: Display the applicable staff s years of clinical experience is displayed fro the extracted result of Step 2 (Table 3). Forula inf 3 = 2 _ (3) Data table (2) is a table holding all the records of the staff applicable to inf 2 (x). SQL stateent SELECT: ward_function, hospital_ward, nursing_staff_nae, staff s_ years_of_clinical_experience FROM: data table (2) WHERE: staff s_ years_of_clinical_experience 3.2. Evaluation of the Analysis Result The copetency of staff assigned to 3 psychiatric chronic wards was classified according to their career ladder levels. Then the staff naes and their years of clinical experience with a difference of their career ladder by self and by a head nurse, were extracted. This result can be useful as an evaluation indicator in order to quantitatively/ qualitatively provide staff assignent according to the characteristic of the wards. 306

5 Table. Classified results of the collation of nursing staff assignent and stuff nurses copetence levels in each psychiatric chronic ward. Ward function Hospital ward nae level І level by self level П level Ш- level by a head nurse level І level П level Ш- Psychiatric chronic wards Ward Ward Ward The nuber shows the nuber of nurses in the career ladder level. Table 2. The extracted results of the nursing staff nae which career level by self and by a head nurse differ in classified result of Step. Ward function Hospital ward nae level by self < level by a head nurse level by self > level by a head nurse Psychiatric chronic wards Ward 5 Ward 6 nurse A nurse B nurse C nurse D nurse E Table 3. The extracted results of the applicable staff s years of clinical experience is displayed fro the extracted result of Step 2. Ward function Hospital ward nae level by self < level by a head nurse level by self > level by a head nurse Psychiatric chronic wards Ward 5 nurse A (0 years) nurse B (6 years) nurse C (8 years) nurse D (8 years) Ward 6 nurse E (7 years) 3.3. Analysis 2: Collation of Preceptor Nurse s Ladder Level and His or Her Skill Step : Display the extraction of preceptor nurse s nae in all wards of the A hospital (Table 4). Forula inf SQL stateent SELECT: hospital_ward, nursing_staff_nae FROM: nursing_staff_adinistration_database WHERE: role = preceptor ( x) = S category ( i x) S condition( j x) i= () Step 2: Display the preceptor nurse s career ladder level fro the result of Step (Table 5). Forula inf 2 = _ Data table () is a table holding all the records of the staff applicable to inf (x). (2) SQL stateent SELECT: hospital_ward, nursing_staff_nae, preceptor_nurse s_career_ladder_level FROM: data_table () 307

6 Step 3: Extracted result of the achieveent situation toward the career ladder level fro the result of Step 2 (Table 6). Forula inf 3 = 2 _ (3) Data table (2) is a table holding all the records of the staff applicable to inf 2 (x). SQL stateent SELECT: hospital_ward, nursing_staff_nae, career_ladder_level_by_a_head_nurse, achieveent_situation_ toward_the_career_ladder_level FROM: data_table (2) 3.4. Evaluation of the Analysis Result 2 By having extracted the data of the preceptor nurse, it was shown clearly that the preceptor nurse was not assigned in all the wards, and was found that all preceptor nurses did not achieve the career ladder level Ш-. These inforation serves as data for work on the policy not only based on the education for novice nurse but also the education of the nurse who plays a role of their leader level, or one who offers high quality nursing care. Table 4. The extracted result of preceptor nurse s nae in all wards of the A hospital. Hospital ward nae Ward Ward 3 Ward 5 Ward 6 Preceptor nurse F nurse G nurse H, nurse I nurse J, nurse K Table 5. The extracted result of the preceptor nurse s career ladder level. Hospital ward nae Preceptor nurse level Ward nurse F П Ward 3 nurse G П Ward 5 Ward 6 nurse H П nurse I Ш- nurse J П nurse K Ш- Table 6. The extracted result of achieveent toward the career ladder level. Hospital ward nae Nuber of preceptor nurse Nae of preceptor nurse position Achieveent situation toward the career ladder level Ward nurse F Π unachieved Ward 3 nurse G П unachieved Ward 5 2 Ward 6 2 nurse H П unachieved nurse I Ш- unachieved nurse J П unachieved nurse K III- unachieved The nuber shows an applicable nurse s nuber. 308

7 4. Discussion The contents of care required in psychiatric hospitals differ in accordance with the function of each respective ward [8]-[2]. Therefore, in order to provide appropriate service to patients, a nursing adinistrator ust ake efforts to organize inforation concerning the degree of busyness and the abilities of nursing staff as well as to correctly understand the characteristics and appropriate placeent of nursing staff in each ward. The reuse of stored data will give a powerful tool for anageent of nursing schedule and lead to iproveent of hospital services [22] [23]. However, the inforation that the nursing adinistrator requires is not only an aggregation of quantitative data, coefficient of correlation or analytical results of the difference between the averages, but also any ethod assebling this inforation should also extract and show what inforation is included in outliers. As shown in Analysis, the nursing adinistrator requires, fro the results of quantitative analysis, inforation concerning in whose cases the career ladder level placeent by one s own assessent is different fro that by the chief nurse, and where the difference between one s self-assessent and the assessents by others lies. Analytical results were divided into whether career ladder levels in the chief nurse s assessent are higher or lower than those in the self-assessent of nursing staff. These results are shown in the screen display of a coputer, which shows that necessary inforation was successfully obtained. In Analysis 2, the practical abilities of nurses playing the role of preceptor are extracted. In hospital A, the nurses who attain career ladder level Ш- are qualified as preceptors. However, fro the results of Analysis 2, all six preceptor nurses did not achieve the ites required in ladder level III- and did not fulfill the necessary requireents. In previous studies, research showed the iproveent of nursing outcoes with data ining using the data saved in the database of the hospital [22] [23]. What nursing adinistrators require is a ethod of objective assessent of the abilities of staff and inforation useful in deriving what ongoing education is necessary for the iproveent of the quality of nursing [24] [25]. Also, when nurses are educated about perforance and quality easures, are engaged in identifying outcoes and collecting eaningful data, are active participants in disseinating quality reports, and are able to recognize the value of these activities, data becoe one with practice [26]. Because inforation is quantitatively handled in statistical processing, it is difficult for the nursing adinistrator at the nursing site to calculate necessary inforation by cobining qualitative and quantitative inforation. As a result of analysis based on the developed calculation forula, it was possible to show necessary inforation by ixing both calculation ethods of analysis and extraction as well as by cobining quantitative and qualitative data. Nursing adinistrators who really understand the necessity of inforation analysis input various data into spreadsheet software. However, they lack a coprehension of what can be read out fro the input data. Or they cannot ake full use of the analytical ethod, so that the actual situation is that the vast aounts of inforation collected often cannot be used [27] [28]. The syste is developed by focusing on support for the idea of nursing adinistration analysis. For exaple, in order to analyze the actual condition of a ward, it is necessary to ake analyses, fro various perspectives, such as what happens to B under the conditions of A? and what happens to C? For this purpose, it is required to rearrange and filter the data using spreadsheet software in each case. In the calculation forula that Miyagawa et al. [6] proposed, the nursing adinistrator can classify data and extract necessary inforation by intuitively cobining the data of A and B on a screen display. The nursing adinistrator, even if he/she is unfailiar with statistical processing, can obtain the inforation necessary for cobination fro the inforation input in the database. There are soe copetent nursing adinistrators acquired the degree of aster of business adinistration or the PhD in nursing, having capability of inforation analysis or statistical analysis. Moreover, nursing inforatics is established as one of the fields of nursing science, and this specialist offer inforation that nursing adinistrator s needs. However, in Japan, there is little such in the present condition [29]. Therefore, we developed the ethodology which can do analysis intuitively, even if the nurse adinistrator is not well versed in inforation analysis. It was thought that this ethodology is effective in order to support a nursing adinistration s decision-aking. The ajor liitation of the study is evaluated results in the one hospital. It is necessary to perfor subsequent experiental study on several hospitals, and to iprove developed forulae in order to use by an electronic nursing syste. 309

8 5. Conclusion Inforation required for nursing adinistration was able to be analyzed and displayed according to the need of each nurse adinistrator. Especially, it has verified that inforation iportant for the nursing staff assignent for assuring the quality of nursing care according to a ward function or the characteristic was acquired. Acknowledgeents We would like to express our deep gratitude to the participants of this study, our faily ebers, and ebers of Professor Dr. Tanioka s laboratory. In particular, we wish to thank the Prof. Dr. Fuji Ren, and the nurse adinistrators who cooperated this study. Also, this study was supported by a grant fro the Strategic Inforation and Counication R & D Prootion Progra (SCOPE) in Japan (No ). References [] Ikebuchi, E., Satoh, S. and Anzai, N. (2008) What Ipedes Discharge Support for Persons with Schizophrenia in Psychiatric Hospitals? Seishin Shinkeigaku Zasshi, 0, (In Japanese) [2] Ryu, Y., Mizuno, M., Sakua, K., Munakata, S., Takebayashi, T., Murakai, M., et al. (2006) Deinstitutionalization of Long-Stay Patients with Schizophrenia: The 2-Year Social and Clinical Outcoe of a Coprehensive Intervention Progra in Japan. Australian and New Zealand Journal of Psychiatry, 40, [3] Hansson, L. and Markströ, U. (204) The Effectiveness of an Anti-Stiga Intervention in a Basic Police Officer Training Prograe: A Controlled Study. BMC Psychiatry, 25, [4] Kunitoh, N. (203) Fro Hospital to the Counity: The Influence of Deinstitutionalization on Discharges Long-Stay Psychiatric Patients. Psychiatry and Clinical Neurosciences, 67, [5] Shift fro Hospitalized Medical Treatent to Living in the Counity Visions in Refor of Mental Health and Medical Welfare. [6] Tanioka, T., Kataoka, M., Yasuhara, Y., Miyagawa, M. and Ueta, I. (20) The Role of Nurse Adinistrators and Managers in Quality Psychiatric Care. Journal of Medical Investigation, 58, [7] Tanioka, T., Chiba, S., Onishi, Y., Kataoka, M., Kawaura, A., Tootake, M., et al. (203) Factors Associated with Discharge of Long-Ter Inpatients with Schizophrenia in Japan: A Retrospective Study. Issues in Mental Health Nursing, 34, [8] Pitkänen, A., Hätönen, H., Kuosanen, L. and Väliäki, M. (2008) Patients Descriptions of Nursing Interventions Supporting Quality of Life in Acute Psychiatric Wards: A Qualitative Study. International Journal of Nursing Studies, 45, [9] Ministry of Health, Labor and Welfare, Japan, Handout. (In Japanese) [0] Oshia, I., Mino, Y. and Inoata, Y. (2007) How Many Long-Stay Schizophrenia Patients Can Be Discharged in Japan? Psychiatry and Clinical Neuroscience, 6, [] Bartusch, S.M., Elgeti, H., Bastiaan, P., Macheidt, W. and Ziegenbein, M. (2006) Hannover Study on Long-Stay Hospitalization Part І: Prediction of Long-Stay Hospitalization in Cases of Chronic Mental Illness. Clinical Practice & Epideiology in Mental Health, 22, 2-0. [2] Callaly, T. and Arya, D. (2005) Organizational Change Manageent in Mental Health. Australasian Psychiatry, 3, [3] Shur, R. and Sions, N. (2008) Quality Issues in Health Care Research and Practice. Nursing Econoics, 26, [4] Taguchi, M. and Tsuruta, K. (2009) Study of Data Ites Used by Nurse Adinistrators in Operating Facilities. Japanese Red Cross College of Nursing Bulletin, 23, (In Japanese) [5] Miyagawa, M., Yasuhara, Y., Tanioka, T. and Locsin, R. (203) Clarification of a Deand Function Required for a Staff Assignents Support Progra for Nursing Adinistrator Use in Psychiatric Hospitals. Inforation, 7, [6] Miyagawa, M., Tanioka, T., Yasuhara, Y., Matsuoto, K., Ito, H., Suzuki, M., et al. (204) Methodology for Developing a Nursing Adinistration Analysis Syste. Intelligent Inforation Manageent, 6, [7] Tanioka, T., Yasuhara (Sakaa), Y., Miyagawa, M. and Itou, H. (204) Analysis Progra for the Nursing Adinistration and the Variance of the Clinical Pathways. Patent-Pending in Japan, Japan Patent No [8] Fukao, K., Hinoki, S., Inoue, T. and Sawa, A. (2006) Function of Eergency Wards of the Hospital in Coprehensive 3020

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