MHA

MHA FPX 5066 Assessment 2 MHA FPX 5066 Assessment 2 Student Name Capella University MHA-FPX 5066 Cornerstones of Health Informatics for Organizational Operations Prof. Name Date Download Free Sample Get Capella University Free MHA Samples MHA FPX 5010 MHA FPX 5020 MHA FPX 5042 MHA FPX 5040 MHA FPX 5016 MHA FPX 5012 MHA FPX 5014 MHA FPX 5017 Get Free Samples of any Class/Assignment

MHA FPX 5066 Assessment 1 Strategic Workflow Plan MHA FPX 5066 Assessment 1 Strategic Workflow Plan Student Name Capella University MHA-FPX 5066 Cornerstones of Health Informatics for Organizational Operations Prof. Name Date Objective The primary objective of this paper is to conduct an analysis of the current Health Information Management (HIM) technology workflow at Valley City Regional Hospital. It aims to identify existing practices, recommend improvements for maintaining workflow efficiency, ensure compliance with state and federal guidelines, and propose methods for evaluating the effectiveness of workflow strategies. Current HIM Technology Infrastructure Valley City Regional Hospital’s HIM workflow currently lacks standardized procedures, resulting in varied approaches across different departments. The system encounters frequent updates and new requirements, leading to uncertainty regarding compliance standards. Additionally, there are noticeable deficiencies in the workflow structure. Best Practices for Maintaining Workflow Implementing secure messaging systems can significantly enhance workflow efficiency by reducing risks and ensuring compliance with HIPAA regulations. Moreover, written or visual workflow plans, prioritization of tasks, and providing access to necessary resources are essential practices. Regular evaluations and clear role assignments further contribute to improving operational efficiency. HIM Workflow in Various Hospital Departments Different departments within the hospital operate with distinct workflows. For example, in the admission process, orders are transmitted via secure messaging, with automated alerts sent to unit managers. Similarly, the laboratory and pharmacy departments have tailored workflows to suit their specific functions. Efficient hospital discharge procedures involve coordinated efforts among physicians, nurses, and discharge planners, facilitated by secure messaging systems. Duties and Responsibilities of Key Personnel Various stakeholders play vital roles in HIM implementation. Board members offer support, while the CEO sets the vision. Implementation managers coordinate tasks, and quality officers align decisions with clinical requirements. Clinical champions, super-users, and patient representatives provide frontline support and feedback. Common Workflow Standards Supported by Best Practices Adhering to common workflow standards is crucial for effective HIM implementation. These standards include initial process evaluation, creating flowcharts, utilizing common metrics, and ensuring Electronic Health Record (EHR) flexibility. Regular feedback from end-users and collaboration between vendors and healthcare providers are also essential. State and Federal Guidelines State and federal regulations, such as Meaningful Use requirements, significantly influence healthcare workflows. Compliance with these regulations ensures improved quality, patient engagement, and care coordination, thereby qualifying healthcare facilities for incentives. MHA FPX 5066 Assessment 1 Strategic Workflow Plan Evaluating Workflow Effectiveness Analyzing workflow effectiveness necessitates a multidisciplinary approach. Utilizing analytic reports, direct staff interactions, and tools like flowcharts help assess productivity, revenue cycles, and patient satisfaction levels. Conclusion Effective HIM technology implementation hinges on adherence to best practices, compliance with regulations, and continual evaluation of workflow effectiveness. By integrating these elements, Valley City Regional Hospital can enhance operational efficiency and deliver quality patient care. References Gravity Flow. (2019, June 14). 7 workflow best practices for avoiding bottlenecks and delays. Retrieved from https://gravityflow.io/articles/workflow-automation-best-practices/ Hopkins, B. (2019, August 23). 3 ways to improve healthcare workflow. Medical Group Management Association – MGMA. Retrieved from https://www.mgma.com/resources/operations-management/three-ways-to-improve-healthcare-workflow How to improve hospital workflows. (2020, August 10). HIPAA Journal. Retrieved from https://www.hipaajournal.com/improve-hospital-workflows/ Kent, J. (n.d.). Workflow Standards Key for Improved EHR Usability, Safety. HealthITAnalytics.com. Retrieved from https://healthitanalytics.com/news/workflow-standards-key-for-improved-ehr-usability-safety Khan, S. (2017, December 17). How can healthcare workflow analysis help hospitals in deploying their EHR system successfully? The Healthcare Guys. Retrieved from https://www.healthcareguys.com/2017/12/17/how-can-healthcare-workflow-analysis-help-hospitals-in-deploying-their-ehr-system-successfully/ MHA FPX 5066 Assessment 1 Strategic Workflow Plan Medicare & Medicaid EHR Incentive Program. (2010). Centers for Medicare & Medicaid Services | CMS. Retrieved from https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads/mu_stage1_reqoverview.pdf Download Free Sample Get Capella University Free MHA Samples MHA FPX 5010 MHA FPX 5020 MHA FPX 5042 MHA FPX 5040 MHA FPX 5016 MHA FPX 5012 MHA FPX 5014 MHA FPX 5017 Get Free Samples of any Class/Assignment

MHA FPX 5006 Assessment 4 Operating Budget Proposal MHA FPX 5006 Assessment 4 Operating Budget Proposal Student Name Capella University MHA-FPX 5006 Health Care Finance and Reimbursement Prof. Name Date Operating Budget Proposal Healthcare institutions must develop operational budget plans to accurately forecast revenues and expenditures. This process ensures that medical objectives are met while achieving anticipated profitability (Saviano et al., 2018). Presented here is a comprehensive operating budget proposal for a healthcare organization, including expenses for acquiring a billing system and MRI equipment to enhance operations. Environmental Factors Affecting the Operational Budget Various environmental factors, whether direct or indirect, impact a healthcare organization’s annual budget. Internal strategic elements such as employees, organizational structure, finances, and values significantly influence budget considerations. Effective governance, financial stability, and workforce competence are crucial for meeting organizational goals (Krastanov et al., 2019). Additionally, changes in laws and regulations, like those introduced in the Affordable Care Act, can significantly influence financial prospects for healthcare organizations (Chen & Grabowski, 2019). Proposed Organizational Budget for Improvement The proposed budget includes expenses for acquiring a billing system and MRI equipment to enhance organizational operations. The MRI machine aims to enhance patient care by providing precise imaging, reducing misdiagnoses. Moreover, owning an MRI machine can attract more patients to the hospital, thereby increasing revenue (Faria et al., 2018). The billing system is expected to streamline billing processes, reduce documentation, and improve customer service (Rosenbach et al., 2017). Budget Alignment with Organizational Target Profit Margin The budget aligns with the organization’s goals of increasing revenue and improving patient care. Investments in MRI equipment and billing systems are essential for achieving these objectives. Additional funds are allocated for training and equipment management to ensure that new purchases contribute effectively to organizational goals (Adhikara et al., 2022). Measurement of Financial Performance Implementing performance measurement tools is crucial for evaluating the hospital’s financial success. By tracking qualitative and quantitative metrics, the organization can assess its economic position and make necessary adjustments to improve financial performance (Wang et al., 2018). Regular cost-benefit analyses help monitor monthly changes and establish revenue targets, contributing to the organization’s overall financial stability (Lim et al., 2018). Conclusion A comprehensive operating budget must consider all environmental factors affecting the organization and provide mechanisms for assessing financial performance. By analyzing various financial sectors and adopting long-term budgeting strategies, healthcare organizations can navigate economic uncertainties and ensure sustainable growth (Saviano et al., 2018). References Adhikara, M. A., Diana, N., & Basjir, M. (2022). Organizational Performance in Environmental Uncertainty on the Indonesian Healthcare Industry: A Path Analysis. Academic Journal of Interdisciplinary Studies, 11(2), 365-365. Al Ahbabi, A. R., & Nonane, H. (2019). Conceptual building of sustainable financial management & sustainable financial growth. Available at SSRN 3472313. Berwick, D. M., & Gilfillan, R. (2021). Reinventing the Center for Medicare and Medicaid Innovation. JAMA, 325(13), 1247–1248. Brooks-LaSure, C., Fowler, E., Sihamoni, M., & Tsai, D. (2021). Innovation at the Centers for Medicare and Medicaid Services: a vision for the next 10 years. Health Affairs Blog. August, 12. Cascardo D. (2017). Preparing to Meet the New CMS Emergency Preparedness Rule. The Journal of Medical Practice Management: MPM, 32(5), 301–303. Chen, M., & Grabowski, D. C. (2019). Hospital Readmissions Reduction Program: Intended and Unintended Effects. Medical Care Research and Review: MCRR, 76(5), 643–660. MHA FPX 5006 Assessment 4 Operating Budget Proposal Faria, R., Soares, M. O., Spackman, E., Ahmed, H. U., Brown, L. C., Kaplan, R., Emberton, M., & Sculpher, M. J. (2018). Optimizing the Diagnosis of Prostate Cancer in the Era of Multiparametric Magnetic Resonance Imaging: A Cost-effectiveness Analysis Based on the Prostate MR Imaging Study (PROMIS). European Urology, 73(1), 23–30. Gai, Y., & Pachamanova, D. (2019). Impact of the Medicare hospital readmissions reduction program on vulnerable populations. BMC Health Services Research, 19(1), 837. Krastanov, A., Lăzăroiu, G., Vaganova, L., Kolesnikova, J., Danilova, M., & Malavika, D. (2019). The Effectiveness of Marketing Communication and Importance of Its Evaluation in an Online Environment. Sustainability, 11(24), 7016. Lim, J., Lim, K., Heinrichs, J., Al-Aali, K., Aamir, A., & Qureshi, M. (2018). The role of hospital service quality in developing the satisfaction of the patients and hospital performance. Management Science Letters, 8(12), 1353-1362. Rosenbach, N., Koller, J. M., Earl, E. A., Miranda-Dominguez, O., Klein, R. L., Van, A. N., Snyder, A. Z., Nagel, B. J., Nigg, J. T., Nguyen, A. L., Lesnevich, V., Greene, D. J., & Fair, D. A. (2017). Real-time motion analytics during brain MRI improve data quality and reduce costs. Neuroimage, 161, 80–93. Saviano, M., Bassano, C., Picacho, P., Di Nauta, P., & Lettieri, M. (2018). Monitoring Viability and Sustainability in Healthcare Organizations. Sustainability, 10(10), 3548. MHA FPX 5006 Assessment 4 Operating Budget Proposal Wang, T., Wang, Y., & McLeod, A. (2018). Do health information technology investments impact hospital financial performance and productivity? International Journal of Accounting Information Systems, 28, 1-13. Download Free Sample Get Capella University Free MHA Samples MHA FPX 5010 MHA FPX 5020 MHA FPX 5042 MHA FPX 5040 MHA FPX 5016 MHA FPX 5012 MHA FPX 5014 MHA FPX 5017 Get Free Samples of any Class/Assignment

MHA FPX 5017 Assessment 2 Hypothesis Testing for Differences Between Groups MHA FPX 5017 Assessment 2 Hypothesis Testing for Differences Between Groups Student Name Capella University MHA-FPX 5017 Data Analysis for Health Care Decisions Prof. Name Date Hypothesis Testing for Group Differences In inferential statistics, populations of individuals are subject to analysis and testing using hypothesis testing, which aids in comparing datasets and facilitating conclusive decision-making. This process revolves around two types of hypotheses: null and alternative. The null hypothesis posits no significant difference in data compared side by side, while the alternative hypothesis suggests substantial differences within the dataset (Hacker & Hatemi-J, 2022). Research Scenario The comparison of productivity levels between two clinics, Clinic 1 and Clinic 2, is conducted using null and alternative hypotheses. The null hypothesis (H0) proposes no difference in productivity between the two clinics, while the alternative hypothesis (Ha) supports differences in productivity. These hypotheses can be expressed as equations: [H_0: text{Clinic 1} = text{Clinic 2}] [H_a: text{Clinic 1} neq text{Clinic 2}]. Selection of Statistical Tests The determination of a normal distribution between the samples guides the choice of tests. A symmetric distribution ensures symmetrical data presentation, while the current asymmetric appearance signifies unequal variances, favoring the Wilcoxon Signed-Rank test (Chang & Perron, 2017). Two-Sample t-tests Results Both samples possess a sufficient sample size (n = 100) warranting an independent t-test for estimating the normal distribution. Presented below are two independent t-tests, one assuming equal variances and the other assuming unequal variances. Table 1: Two-Sample t-test Assuming Equal Variances   Clinic 1 Clinic 2 Mean 124.32 145.03 Variance 2188.543 1582.514 Observations 100 100 Pooled Variance 1885.529 – Hypothesized Mean Difference 0 – df 198 – t Stat -3.37247 – P(T<=t) one-tail 0.000448 – t Critical one-tail 1.65258 – P(T<=t) two-tail 0.000896 – t Critical two-tail 1.972017 – Table 2: Two-Sample t-test Assuming Unequal Variances   Clinic 1 Clinic 2 Mean 124.32 145.03 Variance 2188.543 1582.514 Observations 100 100 Pooled Variance 1885.529 – Hypothesized Mean Difference 0 – df 193 – t Stat -3.37247 – P(T<=t) one-tail 0.00045 – t Critical one-tail 1.652787 – P(T<=t) two-tail 0.0009 – t Critical two-tail 1.972332 – Interpretation and Recommendation Clinic 2 exhibits a higher mean than Clinic 1 in both scenarios, indicating better performance. With p-values less than the significance level (α = 0.05), the null hypothesis is rejected. Consequently, Clinic 1’s patient visit ratios differ from Clinic 2’s based on the data. MHA FPX 5017 Assessment 2 Hypothesis Testing for Differences Between Groups Recommendation According to the data, Clinic 2 appears to outperform Clinic 1, albeit with a relatively close performance. Remedial actions for underperforming clinics involve analyzing clinical workflows, scheduling and booking software, staff education, billing, and coding practices. A comprehensive analysis identifies deficient areas, enabling administrators to formulate data-driven recommendations for enhancing clinic performance (Aspalter, 2023). References Aspalter, C. (2023). Evaluating and Measuring Exactly the Distances between Aggregate Health Performances: A Global Health Data and Welfare Regime Analysis. Social Development Issues, 45(1), 1-36. Link Chang, S. Y., & Perron, P. (2017). Fractional Unit Root Tests Allowing for a Structural Change in Trend under Both the Null and Alternative Hypotheses. Econometrics, 5(1), 5. DOI MHA FPX 5017 Assessment 2 Hypothesis Testing for Differences Between Groups Hacker, R. S., & Hatemi-J, A. (2022). Model selection in time series analysis: using information criteria as an alternative to hypothesis testing. Journal of Economic Studies, 49(6), 1055-1075. DOI Download Free Sample Get Capella University Free MHA Samples MHA FPX 5010 MHA FPX 5020 MHA FPX 5042 MHA FPX 5040 MHA FPX 5016 MHA FPX 5012 MHA FPX 5014 MHA FPX 5017 Get Free Samples of any Class/Assignment