• 沒有找到結果。

第五章 結論與建議

第四節 後續研究以及未來展望

一、心房顫動警示系統正式上線的後續研究

此試驗為心房顫動警示系統正式上線前的前導研究,在蒐集使用者意見以及

74

模型推導之後,作為之後正式上線的調整與參考。在調整後正式上線,可以進一 步驗證此警示系統是否能增加使用者開立抗凝血劑之比例,或是進一步影響患者 之中風或生存預後。亦可進一步分析使用者對於警示系統的反應時間或是反應動 作和其背景特徵或是使用環境之關聯。正式上線後,亦可擴大受測者範圍,包括 使用相同資訊系統的不同院區,或是不同資訊系統,類似的警示系統設計研究。

二、警示系統科技接受模型和題項之後續研究

對於本研究發展之警示系統科技接受模型,可用不同的疾病和其警示系統來 進一步驗證。可發展不同疾病的知識量表,以此警示系統科技接受模型進一步驗 證,或是找尋其他的前置變項,例如患者的背景資料、疾病嚴重程度、家屬因素…

等。另一方面,亦可進一步研究主觀規範除了可直接影響使用意願之外,是否亦 可影響認知有用性(Kim & Park, 2012)。

三、Jessa 心房顫動知識問卷的後續研究

此 Jessa 心房顫動知識問卷為華文世界第一份經過正式授權,雙向翻譯,官 方認可之中文化心房顫動知識評量問卷。可先於一般無就診心臟科民眾、一般就 診心臟科,無心房顫動患者、就診心臟科且有心房顫動的患者,做信效度和區辨 度測驗。並且可以用前/後測的方式來做為後續心房顫動衛教、不同科別治療、

藥物和非藥物治療心房顫動之患者心房顫動知識增長評量。或是評量不同的衛教 方式、不同的衛教媒介、或是不同的介入方式,來評量心房顫動患者其心房顫動 知識的變化,甚至預後的改善。

75

參考文獻

中文部分

王嵩竑。(2008)。護理人員對無線射頻辨識系統接受度模式建構與比較分析:知 覺創新特性模式與科技接受模式觀點。元培學報,(15),頁 47-80。

石崇良、蘇喜。(2004)。運用資訊提升病人安全。臺灣醫學,8(6),807-816。

吳曉雲、邱艷芬。(2011)。心臟衰竭患者的疾病知識與自我照顧行為。護理暨健 康照護研究,7(4),頁 329-338。

李作英、王如華、徐姍姍、陳麗芳、張雪吟。(1998)。護理資訊化-個人數位處理 器(PDA)在臨床護理之運用。護理雜誌,45(1),頁 69-76。

李婉怡、趙珮如。(2004)。醫療產業員工對電子病歷之科技接受模式探討-以中南 部地區為例。醫務管理期刊,5(2),頁 243-269。

李榮信。(2010)。以計劃行為理論探討醫療服務人員知識分享行為。成功大學高 階管理碩士在職專班(EMBA)學位論文,頁 1-73。

李碧霞、呂昌明。(1995)。孕產婦授乳意圖,授乳行為及其影響因素之研究。護 理研究,3(3),頁 278-290。

周君倚、陸洛。(2014)。以科技接受模式探討數位學習系統使用態度-以成長需求 為調節變項。資訊管理,21(1),頁 83-106。

林盈利、陳清埤、余昭宏、林益卿。(2012)。心房顫動與抗血栓治療。家庭醫學 與基層醫療,27(6),頁 202-206。

林璟淑、李亭亭。(2005)。由 Lewin 的改變理論談護理資訊系統之推展。護理雜 誌,52(1),頁 50-54。

林璟淑、廖彥琦。(2003)。護理人員對運用個人數位助理(PDA)於護理作業之態度 與滿意度調查。新臺北護理期刊,5(2),頁 3-12。

76

洪新原、梁定澎、張嘉銘。(2005)。科技接受模式之彙總研究。資訊管理學報,

12(4),頁 211-234。

張怡秋、劉忠峰、蕭世榮、陳瑩玲。(2005)。護理站導入無線區域網路之關鍵因 素研究。資訊管理學報,12(4),頁 107-119。

張顯洋。(2001)。個人數位秘書 PDA 在臨床護理工作的應用—以慈濟醫學中心護 囑資訊系統之整合研究為例。Hospital,34(1),頁 8-15。

陳朝欽、雷孟桓。(2012)。新型口服抗凝血劑─心房顫動中風預防的新曙光。內科 學誌,23(2),頁 77-97。

陳福基、蕭世榮、陳啟元、杜素珍。(2005)。影響醫院接受行動護理站因素之研 究-以南部某區域教學醫院為例。資訊管理學報,12(S),頁 67-89。

曾旭民、詹碧端、姜靜穎。(2009)。應用科技接受模型探討護理人員對行動護理 站接受度的影響因素。醫療資訊雜誌,18(1),頁 23-38。

曾志仁、邱政元、蔡亭儀、梁竣傑、許瑋庭。(2012)。使用電子病歷保障病人隱 私之探討—以中山醫學大學附設醫院病歷電子化為例。電腦稽核(25),頁 112-119。

劉家昌、林益卿、黃馨葆。(2017)。新型口服抗凝血藥物在預防心房纖維顫動患 者中風預防的使用。家庭醫學與基層醫療,32(11),頁 314-321。

蔡昆原、劉見祥、劉建財。(2009)。我國電子病歷發展現況與展望。醫療品質雜 誌,3(6),頁 4-14。

梁定澎。(2012) 。資訊管理理論。前程文化出版總經銷。新北市。

鄧景宜、賀倫惠、陳瑋佳。(2009)。健康專業服務的改善:應用理性行為理論解釋 護理人員通報病患安全事件意願的影響因素。管理評論,28(1),頁 45-60。

77

英文部分

Ahlan, A. R., & Ahmad, B. I. e. (2015). An overview of patient acceptance of Health Information Technology in developing countries: a review and conceptual model.

International Journal of Information Systems and Project Management, 3(1), 29-48.

Ajzen, I. (2006). Constructing a theory of planned behavior questionnaire. In: Amherst, MA.

Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes.

Psychological Bulletin, 82(2), 261.

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour.

Ajzen, I., & Fishbein, M. (1988). Theory of reasoned action-Theory of planned behavior. University of South Florida.

Arnould, E., Price, L., & Zinkhan, G. (2004). Consumers. McGraw-‐Hill. Irwin, New York.

Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (pls) Approach to Casual Modeling: Personal Computer Adoption Ans Use as an Illustration.

Bates, D. W., & Gawande, A. A. (2003). Improving safety with information technology.

New England Journal of Medicine, 348(25), 2526-2534.

Bates, D. W., Leape, L. L., Cullen, D. J., Laird, N., Petersen, L. A., Teich, J. M., . . . Shea, B. (1998). Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA, 280(15), 1311-1316.

78

Bates, D. W., Miller, E. B., Cullen, D. J., Burdick, L., Williams, L., Laird, N., . . . Vander Vliet, M. (1999). Patient risk factors for adverse drug events in hospitalized patients. Archives of Internal Medicine, 159(21), 2553-2560.

Bates, D. W., Teich, J. M., Lee, J., Seger, D., Kuperman, G. J., Ma'Luf, N., . . . Leape, L. (1999). The impact of computerized physician order entry on medication error prevention. Journal of the American Medical Informatics Association, 6(4), 313-321.

Becker, T. E., Randall, D. M., & Riegel, C. D. (1995). The multidimensional view of commitment and the theory of reasoned action: A comparative evaluation. Journal of Management, 21(4), 617-638.

Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods & Research, 21(2), 205-229.

Bostrom, R. P., & Heinen, J. S. (1977). MIS problems and failures: a socio-technical perspective, part II: the application of socio-technical theory. MIS quarterly, 11-28.

Camm, A. J., Breithardt, G., Crijns, H., Dorian, P., Kowey, P., Le Heuzey, J.-Y., . . . Schwartz, P. J. (2011). Real-life observations of clinical outcomes with rhythm-and rate-control therapies for atrial fibrillation: RECORDAF (Registry on Cardiac Rhythm Disorders Assessing the Control of Atrial Fibrillation). Journal of the American College of Cardiology, 58(5), 493-501.

Chien, K.-L., Su, T.-C., Hsu, H.-C., Chang, W.-T., Chen, P.-C., Chen, M.-F., & Lee, Y.-T. (2010). Atrial fibrillation prevalence, incidence and risk of stroke and all-cause death among Chinese. International Journal of Cardiology, 139(2), 173-180.

Chin, W. W. (1998). The partial least squares approach to structural equation modeling.

Modern methods for business research, 295(2), 295-336.

79

Choi, J., Chun, J., Lee, K., Lee, S., Shin, D., Hyun, S., . . . Kim, D. (2004). MobileNurse:

hand-held information system for point of nursing care. Computer Methods and Programs in Biomedicine, 74(3), 245-254.

Connolly, S. J., Ezekowitz, M. D., Yusuf, S., Eikelboom, J., Oldgren, J., Parekh, A., . . . Varrone, J. (2009). Dabigatran versus warfarin in patients with atrial fibrillation.

New England Journal of Medicine, 361(12), 1139-1151.

Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology,

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.

Dessau, R. B., & Steenberg, P. (1993). Computerized surveillance in clinical microbiology with time series analysis. Journal of Clinical Microbiology, 31(4), 857-860.

Desteghe, L., Engelhard, L., Raymaekers, Z., Kluts, K., Vijgen, J., Dilling-Boer, D., . . . Heidbuchel, H. (2016). Knowledge gaps in patients with atrial fibrillation revealed by a new validated knowledge questionnaire. Int J Cardiol, 223, 906-914.

doi:10.1016/j.ijcard.2016.08.303

80

Erickson, S. M., Wolcott, J., Corrigan, J. M., & Aspden, P. (2003). Patient safety:

achieving a new standard for care: National Academies Press.

Evans, R. S., Pestotnik, S. L., Classen, D. C., Clemmer, T. P., Weaver, L. K., Orme Jr, J. F., . . . Burke, J. P. (1998). A computer-assisted management program for antibiotics and other antiinfective agents. New England Journal of Medicine, 338(4), 232-238.

Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.

Fiszman, M., Chapman, W. W., Aronsky, D., Evans, R. S., & Haug, P. J. (2000).

Automatic detection of acute bacterial pneumonia from chest X-ray reports.

Journal of the American Medical Informatics Association, 7(6), 593-604.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.

Granger, C. B., Alexander, J. H., McMurray, J. J., Lopes, R. D., Hylek, E. M., Hanna, M., . . . Avezum, A. (2011). Apixaban versus warfarin in patients with atrial fibrillation. New England Journal of Medicine, 365(11), 981-992.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998).

Multivariate data analysis . Uppersaddle River. Multivariate Data Analysis (5th ed) Upper Saddle River.

Hirschhorn, L. R., Currier, J. S., & Platt, R. (1993). Electronic surveillance of antibiotic exposure and coded discharge diagnoses as indicators of postoperative infection and other quality assurance measures. Infection Control and Hospital Epidemiology, 14(1), 21-28.

81

Hripcsak, G., Friedman, C., Alderson, P. O., DuMouchel, W., Johnson, S. B., &

Clayton, P. D. (1995). Unlocking clinical data from narrative reports: a study of natural language processing. Annals of Internal Medicine, 122(9), 681-688.

Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of management information systems, 16(2), 91-112.

Investigation, A. F. (1994). Risk factors for stroke and efficacy of antithrombotic therapy in atrial fibrillation: analysis of pooted data from five randominized controlled trials: J. Archives of Internal Medicine, 154(13), 1449-1414.

Jha, A. K., Kuperman, G. J., Rittenberg, E., Teich, J. M., & Bates, D. W. (2001).

Identifying hospital admissions due to adverse drug events using a computer‐

based monitor. Pharmacoepidemiology and Drug Safety, 10(2), 113-119.

Kaushal, R., Shojania, K. G., & Bates, D. W. (2003). Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Archives of Internal Medicine, 163(12), 1409-1416.

Kim, J., & Park, H. A. (2012). Development of a health information technology acceptance model using consumers' health behavior intention. J Med Internet Res, 14(5), e133. doi:10.2196/jmir.2143

Lane, D. A., Ponsford, J., Shelley, A., Sirpal, A., & Lip, G. Y. (2006). Patient knowledge and perceptions of atrial fibrillation and anticoagulant therapy: effects of an educational intervention programme: the West Birmingham Atrial Fibrillation Project. International Journal of Cardiology, 110(3), 354-358.

Lee, C.-H., Liu, P.-Y., Tsai, L.-M., Tsai, W.-C., Ho, M.-T., Chen, J.-H., & Lin, L.-J.

(2007). Characteristics of hospitalized patients with atrial fibrillation in Taiwan: a

82

nationwide observation. The American journal of medicine, 120(9), 819. e811-819. e817.

Lierman, L. M., Young, H. M., Kasprzyk, D., & Benoliel, J. Q. (1990). Predicting breast self-examination using the theory of reasoned action. Nursing Research, 39(2), 97-102.

Lip, G. Y., Nieuwlaat, R., Pisters, R., Lane, D. A., & Crijns, H. J. (2010). Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest Journal, 137(2), 263-272.

McCabe, P. J., Schad, S., Hampton, A., & Holland, D. E. (2008). Knowledge and self-management behaviors of patients with recently detected atrial fibrillation. Heart Lung, 37(2), 79-90. doi:10.1016/j.hrtlng.2007.02.006

Miller, M. R., Elixhauser, A., Zhan, C., & Meyer, G. S. (2001). Patient Safety Indicators:

using administrative data to identify potential patient safety concerns. Health Services Research, 36(6 Pt 2), 110.

Nunnally, J. (1978). Psychometric theory (2nd edit.) mcgraw-hill. Hillsdale, NJ.

Obamiro, K. O., Chalmers, L., & Bereznicki, L. R. (2016). Development and Validation of an Oral Anticoagulation Knowledge Tool (AKT). PLoS One, 11(6), e0158071.

doi:10.1371/journal.pone.0158071

Ohsawa, M., Okayama, A., Okamura, T., Itai, K., Nakamura, M., Tanno, K., . . . Sakata, K. (2007). Mortality risk attributable to atrial fibrillation in middle-aged and elderly people in the Japanese general population. Circulation Journal, 71(6), 814-819.

83

Patel, M. R., Mahaffey, K. W., Garg, J., Pan, G., Singer, D. E., Hacke, W., . . . Piccini, J. P. (2011). Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. New England Journal of Medicine, 365(10), 883-891.

Rolls, C. A., Obamiro, K. O., Chalmers, L., & Bereznicki, L. R. (2017). The relationship between knowledge, health literacy, and adherence among patients taking oral anticoagulants for stroke thromboprophylaxis in atrial fibrillation.

Cardiovascular Therapeutics, 35(6).

Rozich, J., Haraden, C., & Resar, R. (2003). Adverse drug event trigger tool: a practical methodology for measuring medication related harm. Quality and safety in Health Care, 12(3), 194-200.

Scarpa, R., Smeltzer, S. C., & Jasion, B. (1992). Attitudes of nurses toward computerization: a replication. In.

Schumock, G., Thornton, J., & Witte, K. (1991). Comparison of pharmacy-based concurrent surveillance and medical record retrospective reporting of adverse drug reactions. American Journal of Hospital Pharmacy, 48(9), 1974-1976.

Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet research, 14(3), 213-223.

Short, D., Frischer, M., & Bashford, J. (2004). Barriers to the adoption of computerised decision support systems in general practice consultations: a qualitative study of GPs’ perspectives. International Journal of Medical Informatics, 73(4), 357-362.

Singer, D. E., Chang, Y., Fang, M. C., Borowsky, L. H., Pomernacki, N. K., Udaltsova, N., & Go, A. S. (2009). Should patient characteristics influence target anticoagulation intensity for stroke prevention in nonvalvular atrial fibrillation?

Circulation: Cardiovascular Quality and Outcomes, 2(4), 297-304.

84

Steffel, J., Verhamme, P., Potpara, T. S., Albaladejo, P., Antz, M., Desteghe, L., . . . Group, E. S. C. S. D. (2018). The 2018 European Heart Rhythm Association Practical Guide on the use of non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation: executive summary. EP Europace, euy054-euy054.

doi:10.1093/europace/euy054

Straub, D., Boudreau, M.-C., & Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information systems, 13(1), 24.

Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model.

Management science, 42(1), 85-92.

Tanizaki, Y., Kiyohara, Y., Kato, I., Iwamoto, H., Nakayama, K., Shinohara, N., . . . Fujishima, M. (2000). Incidence and risk factors for subtypes of cerebral infarction in a general population. Stroke, 31(11), 2616-2622.

Teich, J. M., Merchia, P. R., Schmiz, J. L., Kuperman, G. J., Spurr, C. D., & Bates, D.

W. (2000). Effects of computerized physician order entry on prescribing practices.

Archives of Internal Medicine, 160(18), 2741-2747.

van Walraven, C., Hart, R. G., Singer, D. E., Laupacis, A., Connolly, S., Petersen, P., . . . Hellemons, B. (2002). Oral anticoagulants vs aspirin in nonvalvular atrial fibrillation: an individual patient meta-analysis. JAMA, 288(19), 2441-2448.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.

Waegemann, C. (1999). Current Status of EPR Developments in the US. Toward an electronic health record, 99, 116-118.

85

Wilson, E. V., & Lankton, N. K. (2004). Modeling patients' acceptance of provider-delivered e-health. Journal of the American Medical Informatics Association, 11(4), 241-248.

Wu, J.-H., Wang, S.-C., & Lin, L.-M. (2007). Mobile computing acceptance factors in the healthcare industry: A structural equation model. International Journal of Medical Informatics, 76(1), 66-77.

Yap, K. B., Ng, T. P., & Ong, H. Y. (2008). Low prevalence of atrial fibrillation in community-dwelling Chinese aged 55 years or older in Singapore: a population-based study. Journal of Electrocardiology, 41(2), 94-98.

Zhou, Z., & Hu, D. (2008). An epidemiological study on the prevalence of atrial fibrillation in the Chinese population of mainland China. Journal of Epidemiology, 18(5), 209-216.

86

附錄 研究問卷

醫學知識差異影響心房顫動警示系統之科技接受模 型問卷—

院內專科護理師、藥師、醫師版

各位醫療同仁,您好!

衷心感謝,各位醫療同仁撥冗填寫這份問卷。本調查問卷目的 在探討『醫學知識差異影響心房顫動警示系統之科技接受模型—以 中文版 Jessa 心房顫動知識問卷為例』 ,問卷總共分為三個部分,採 不記名方式作答,相關個人資料絕不對外公開,且問卷資料僅用於 本次研究,本研究必定善盡保密之責,請放心依實際情形回答。

感謝您對研究協助與支持,敬祝您健康喜樂、工作順利。

國立台東大學資訊管理學研究所

研究生:邱威儒 敬上

電子信箱:[email protected]

87

88

89

3. 以下消炎劑之一:例如阿司匹林(Aspirin),布洛芬(Ibuprofen) 4. 我不知道

90

91

4. 關於新型血液稀釋劑(非維生素 K 拮抗劑口服抗凝血劑;新型口服抗凝血劑)

的問題

( )4.1 每天在同一時間服用血液稀釋劑是重要的。

1. 是 2. 不是

3. 不,只要是在兩餐之間就好 4. 我不知道

( )4.2 如果我忘記服用血液稀釋劑怎麼辦?

1. 我仍然應該服用這次劑量,除非到我的下一次劑量的時間少於我這 次錯過劑量後的時間

2. 我應該跳過一個劑量,等到下次時間到再服用 3. 下次服藥時應服用兩粒

4. 我不知道

( )4.3 我的血液稀釋劑附有一張卡片(或是藥袋的說明):

1. 讓我表明我服用血液稀釋劑

2. 我必須給我其他的診所醫生和次專科醫師看

2. 我必須給我其他的診所醫生和次專科醫師看