MHA FPX 5064 Assessment 2 Using Data for Decision Making

MHA FPX 5064 Assessment 2 Using Data for Decision Making

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Capella University

MHA-FPX5064 Health Information Systems Analysis and Design for Administrators

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Types of Internal Data Within a Health Care System

Health care organizations generate and maintain large volumes of internal data that are essential for informed decision-making and the efficient management of clinical operations. A thorough understanding of both internal and external data enables organizations to strengthen analytical practices, improve patient outcomes, and align with strategic goals (Dooling et al., 2015). Internal data primarily include information produced within the organization, often related to patient demographics, clinical treatments, administrative processes, and financial transactions.

Categories of Internal Data

Internal data systems are mostly clinical in nature, encompassing information such as patient records, diagnostic reports, and hospital operations. Common examples of internal data systems include Electronic Health Records (EHRs), Radiology Information Systems (RIS), Cancer Registries, and Patient Financial Systems (Dooling et al., 2015).

Table 1

Examples of Internal Data Systems

Data System Type	Primary Function	Collected Information	Users
Electronic Health Records (EHR)	Centralized patient record system	Demographics, clinical notes, medications, allergies	Clinicians, nurses, administrative staff
Radiology Information System (RIS)	Manages imaging workflows	Imaging orders, scan results, radiologist reports	Radiologists, technicians
Cancer Registry	Tracks cancer-related cases	Tumor characteristics, treatment outcomes	Oncologists, researchers
Patient Financial System	Handles billing and insurance	Payment history, insurance claims, cost analysis	Finance department

During preadmission and admission, patient demographic data, socioeconomic details, consent forms, and financial data are collected and entered into the EHR. The EHR ensures that patient information is accurately shared among authorized healthcare professionals, supporting coordinated care across different providers (Adler-Milstein et al., 2015).

Clinical data—covering medical history, diagnostic results, and provider notes—are also key internal data elements. These records are heavily regulated and require consistent documentation by all healthcare professionals involved in the patient’s care.

At St. Anthony Medical Center, data utilization spans multiple departments. The organization relies heavily on EHR systems, which integrate data from the Maternal Care Information System in the Maternal and Fetal Medicine Department and the Prescription Drug Monitoring Program (PDMP) in the pharmacy. These integrations support real-time data access and improve care coordination across units (Vila Health, n.d.).

Types of External Data Available Within a Health Care System

External data provide health care organizations with the ability to compare internal performance metrics against broader health indicators, regulations, and community trends. Such data help organizations assess quality benchmarks and improve patient outcomes (Palmer et al., 2019).

Sources and Uses of External Data

External data come from national and regional databases, regulatory agencies, and research bodies. Common sources include the Centers for Medicare and Medicaid Services (CMS), The Joint Commission, and the U.S. Department of Health and Human Services (HHS) (Dooling et al., 2015).

Table 2

Examples of External Data Sources and Applications

Source	Purpose	Application in Healthcare
Centers for Medicare and Medicaid Services (CMS)	Regulatory and performance reporting	Benchmarking quality and reimbursement data
The Joint Commission	Accreditation and safety standards	Evaluating compliance and patient safety
Substance Abuse and Mental Health Services Administration (SAMHSA)	Behavioral health statistics	Assessing behavioral health trends
Labor Market Data	Workforce analysis	Identifying shortages and recruitment needs

At St. Anthony Medical Center, external data are widely used across departments. For example, the Behavioral Health Department uses SAMHSA databases to compare patient behavioral health issues with county and national data, while the Human Resources Department utilizes labor market and nursing school data to identify staffing opportunities. These efforts contribute to the organization’s culture of evidence-based improvement (Crapo, 2015).

Strategies for Accessing and Analyzing Available Data

The integration of healthcare data across systems is fundamental to delivering safe, efficient, and patient-centered care. However, variability in data storage and exchange formats can lead to inconsistencies in analysis and interpretation. Differences in data structures across organizations often result in challenges such as data duplication or incomplete patient records (Dash, 2018).

At St. Anthony Medical Center, multiple databases and electronic systems store clinical and administrative data. Inconsistent formatting can hinder comprehensive analysis, potentially affecting the quality of care. To mitigate this, establishing standardized data-sharing practices and interoperability across platforms is essential.

Collaborating with payers, state health departments, and local government agencies allows healthcare systems like Vila Health to securely access population-level datasets and integrate them with existing records. Such integration enhances clinicians’ ability to make evidence-based decisions and supports public health initiatives (Dash, 2018).

Data Needs Within a Health Care System

Interviews with leaders at St. Anthony Medical Center revealed that the main challenge for Vila Health involves achieving full interoperability between newly acquired facilities—Delaware County Health and Red River Health—and existing systems. Leaders emphasized the importance of harmonizing internal and external data, especially concerning care quality, service types, coverage rates, and community demographics.

The organization currently depends on its EHR as the main system for interdepartmental communication. However, various applications used by departments can only read—not fully exchange—EHR data. To meet growing data needs, Vila Health must enhance system interoperability across all facilities.

Strategies for Meeting Data Needs

To overcome interoperability challenges, Vila Health should implement a Health Information Exchange (HIE) system. HIE serves as a secure infrastructure enabling the electronic transfer of health data between providers, hospitals, and patients. This integration enhances data accuracy, supports timely clinical decisions, and minimizes redundant testing (HealthIT, 2020).

The Continuity of Care Record (CCR) and Continuity of Care Document (CCD) standards ensure seamless information exchange across systems (Wen et al., 2010). The adoption of HIE would also help clinicians gain comprehensive access to patient records, reduce adverse health events, and improve overall patient satisfaction (Boussadi & Zapletal, 2017).

Communication Strategies for Disseminating Strategic Information to End Users

Effective communication is vital in ensuring that critical health information reaches clinicians, administrators, and patients accurately and securely. Health organizations must assess the relevance, completeness, and quality of data before dissemination. Defining a clear process for requesting and sharing information promotes transparency and accountability (Dash, 2018).

Developing partnerships with intermediary agencies can help streamline data requests and align goals across departments. Additionally, implementing evaluation programs that measure departmental performance, patient outcomes, and cost efficiency can foster engagement among end users.

To address concerns related to data security and communication barriers—such as language or cultural differences—The Joint Commission mandates healthcare organizations to adopt standardized communication practices that promote clarity and patient understanding (Thomson et al., 2015).

Conclusion

As Vila Health continues to expand, it must prioritize the integration of interoperable data systems that connect internal and external sources across all facilities. Leveraging accurate and standardized data enhances the ability of healthcare providers to make informed decisions and ensures high-quality patient care. By investing in technology such as HIE and emphasizing clear communication strategies, Vila Health can build a robust data-driven environment that supports both clinical excellence and organizational growth.

References

Adler-Milstein, J., Everson, J., & Lee, S. D. (2015). EHR adoption and hospital performance: Time-related effects. Health Services Research, 50(6), 1751–1771. https://doi.org/10.1111/1475-6773.12406

Boussadi, A., & Zapletal, E. (2017). A fast healthcare interoperability resources (FHIR) layer implemented over i2b2. BMC Medical Informatics and Decision Making, 17(1), 120. https://doi.org/10.1186/s12911-017-0513-6

Crapo, J. (2015). Evaluating demographic data in healthcare systems. Health Management Journal, 23(4), 45–52.

Dash, D. (2018). Data across sectors for health datasets available on WPRDC. Targeted News Service.

Dooling, J. A., Houser, S. H., Milaelian, R., & Smith, C. P. (2016). Transitioning to a data-driven, informatics-oriented department. Journal of AHIMA, 87(10), 58–62.

HealthIT.gov. (2020). Health information exchange. https://www.healthit.gov/topic/health-it-and-health-information-exchange

Palmer, E. L., Higgins, J., Hassanpour, S., Sargent, J., Robinson, C. M., Doherty, J. A., & Onega, T. (2019). Assessing data availability and quality within an electronic health record system through external validation against an external clinical data source. BMC Medical Informatics and Decision Making, 19(1), 143. https://doi.org/10.1186/s12911-019-0864-2

MHA FPX 5064 Assessment 2 Using Data for Decision Making

Thomson, K., Outram, S., Gilligan, C., & Levett-Jones, T. (2015). Interprofessional experiences of recent healthcare graduates: A social psychology perspective on the barriers of effective communication, teamwork, and patient-centred care. Journal of Interprofessional Care, 29(6), 634–640. https://doi.org/10.3109/13561820.2015.1040873

Vila Health. (2022). Using data for decision making. Capella University. http://media.capella.edu/CourseMedia/VilaHealth/MHA5064/UsingDataForDecisionMaking/transcript.html

Wen, K., Kreps, G., Zhu, F., & Miller, S. (2010). Consumers’ perceptions about and use of the internet for personal health records and health information exchange. Journal of Medical Internet Research, 12(4), e73. https://doi.org/10.2196/jmir.1668

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