Introduction
Information to Collect
Data on patient health records, demographics, vital statistics, socioeconomic data, and health outcomes will be collected from EHRs, patient questionnaires, public health records, and other databases of health information.
Reasons for Collecting Information
Gathering such data is crucial in determining the main health concerns within the population, ensuring the effectiveness of the current treatment approaches, and enhancing the delivery of healthcare services. It also assists in improving healthcare for regulatory obligations and decision-making.
Use of Information
The obtained data will help confirm and increase the quality of care by detecting what aspects require further improvements, establishing certain standards, and defining measures to fill the gaps in delivering the required care. This will involve evaluating local health data against benchmark data and integrating best practice once practices (Andersson et al., 2018; Shuman & Bebeau, 1996).
Data Collection Plan
Implementation Plan
Data will be collected systematically from EHR systems, patient surveys, and public health databases. This way, the overall information obtained is quite comprehensive, including diverse aspects of health indicators and patient characteristics, which form a good base for analytical work (Roglic, 2016).
Time Period
This is because the report will focus on the trends and results of the interventions, and their analysis should cover data from the past five years. This time frame allows for the patterns and changes in health metrics to be identified over time so that the facility can monitor progress and, more specifically, identify areas of potential improvement (Roglic, 2016).
System Applications
These include Electronic Health Record (EHR) systems, Health Information Exchange (HIE), and other tools such as statistical software and data dashboards. These systems will also help efficiently store, sort, and parse a large amount of data to guarantee the most accurate and relevant information (Andersson et al., 2018).
Information Sharing Among Health Record
The health information life cycle includes several stages: data generation, storage, retrieval, sharing, and disposal. Throughout the creation phase, data will be produced based on the patient’s experience and Diagnostic tasks. All the above data will be entered and saved discretely, then integrated and stored securely within the EHR systems and made accessible to the respective personnel. This integration enables data to be shared across different systems and platforms, making it useful in several clinical and administrative aspects. Last, data destruction will be legal regulatory compliant to delete the patient information when it is no longer required to maintain the confidentiality and privacy of patients (Lessing & Hayman, 2019).
Use of HIE
Implementing HIE will improve treatment quality by offering complete information about the patient’s history. However, in this system, one obtains a complete picture of a disease’s nature and progress, allowing healthcare providers to make more effective decisions and improve patient care. HIEs also enhance the available clinical information to practice by integrating query and research capabilities to access a larger data set for developing reference standards. Furthermore, using population health data is crucial to the success of public health programs as it pinpoints areas and trends that require intervention (Andersson et al., 2018).
Personnel Required
The review will involve a health team composed of data analysts, IT personnel, clinicians, and administration personnel. A particular set of roles pertains to interpreting the data collected and, possibly, even identifying trends. Specialists in information technology will be responsible for facilitating or deciding issues to deal with data collection as they deal with the compatibility of systems. Medical organizations will lend clinical input, thus guaranteeing that the information collected is appropriate and reflects patient care. Personnel from the company’s administration will take charge of managing the practicalities of the project, for example, through organizing and assigning times for the training. These include the ability to analyze data, manage systems, apply clinical specialities, and understand legal requirements (Markama et al., 2022).
Strategies for Implementation
Employees are to be trained on the methods for data collection and system and regulation working standards. This training will be useful so that every team member will know how to use the data collection tools and the measures that must be taken to preserve data accuracy and confidentiality. Instructions will be offered to support personnel in progressing through their ordinary tasks and paperwork through a series of instructions and checklists. Staff training will also include updates and refresher courses to inform the staff of any changes in the procedures or technology. Moreover, a feedback system will help the personnel to reflect on the execution of their responsibilities and report any problems or give recommendations for further improvement of data collection activities (15743-Orders).
Besides training, organizational communication will be enhanced to ensure a proper flow of information to all team members. Weekly check-in sessions will be used to ensure that the goals and objectives of the specific project are being met and if any issues arise regarding its implementation. Incorporating a project management tool will assist in tracking milestones and deadlines toward implementing the data collection plan. With the described strategies, it is possible to provide the facility with the most effective data collection methodologies to improve patient care and enhance organizational learning.
With these well-coordinated and integrated data collection strategies backed up by qualified personnel, this facility will be in a position to collect adequate and reliable health information. The concerns expressed will be useful in pinpointing gaps, developing standards for comparison, and, consequently, improving patient care.
Figure 1 Health Record Information Lifecycle (Source: Self-Created)
Data Security Plan
Measures to Protect PHI
Audits must be implemented to safeguard PHI, encryption, access controls, secure data transfers, and compliance with security standards.
Laws Governing Health Information
It is important to obey HIPAA and other applicable laws regarding the confidentiality, privacy, and security of health information. This entails controlling limits on handling, storing, and transmitting data and information.
Impact of HIPAA
HIPAA affects the employees in the healthcare sector in the following ways: Employees must consistently undergo a refresher course in data privacy and security, and policies and procedures governing PHI must be adhered to strictly at all levels of the organization (Markama et al., 2022).
Benchmarking Plan
Sources of National Data
National data will be collected through a peer-reviewed article from the National Library of Medicine, using databases from CDC, AHRQ, and CMS (Shuman & Bebeau, 1996).
Use of National Data
Local health data will be compared with national data to determine areas that need improvement and improved goals set (Faux et al., 2018).
Ensuring Data Standardization
Understanding data Compendiostatization involves the establishment of a clear definition along with the use of a standard measurement and collection process to facilitate comparability with national standards (Shuman & Bebeau, 1996)
Comparing Data
The collected data will then be compared to national quality standards to focus on areas that need to be improved and to guide students, faculty, and staff for evidence-based action toward improvement (Shuman & Bebeau, 1996).
Quality and Change Management Strategies
Using Data Outcomes
Essentially, the data outcome aims to analyze quality improvement reviews in detail. This allows healthcare providers to systematically review data trends and patterns to flag issues and areas that deserve priority attention. For example, if there is a high proportion of medical errors, the organization can make changes specific to this problem, such as retraining staff or redesigning workflow. Also, constant observation of data results will give an understanding of the impact of the practice changes in providing better patient outcomes in the long run (Elliott et al., 2009).
Best Practices for Workflow
It is crucial to improve data collection and reporting techniques used to execute the desirable improvements in the flow of information and the quality of care. This entails adopting automated data collection systems that minimize data entry mistakes and enhance accuracy. Standardized reporting templates and good organization practices will guarantee coherence and more simplified comprehensiveness of the records to be generated. In addition, continuing education for staff on proper data handling procedures will ensure that the quality of data being collected and analyzed is of the highest quality (Adamcewicz, 2021).
Evidence-Based Practices
As the reviewed literature shows, guidelines sourced from peer-reviewed databases are useful in creating needed changes and enhancing service delivery (Channell, 2021; Dangmei, 2016). For instance, investigations on effective ways of providing care to patients with diabetes or hypertension can be incorporated into clinical practice guidelines to deliver optimal care. To put these practices into practice, it is helpful to act according to the most recent data and incorporate them into existing clinical guidelines. It enhances the quality of patient care and fosters staff engagement in lifelong learning and professional growth (Dangmei, 2016).
Moreover, including healthcare providers in the analysis of research findings can create an understanding of personal stake in patient safety concerns. Fostering cross-functional teamwork guarantees that various ideas are incorporated, providing a broader approach to tackling problems. It is also possible to schedule routine check-ups and report-back sessions to review compliance with the best practices and make additional changes where necessary.
Implementation
Table 1 Implementation Plan
| Steps for Implementation | Time Frame | Description |
| Data Collection Setup and Training | Month 1-2 | Establish data collection systems and conduct training sessions for personnel. |
| Data Collection and Analysis | Month 3-5 | Gather data and perform initial analysis to identify trends and patterns. |
| Benchmarking and Quality Improvement Planning | Month 6-7 | Compare data against national benchmarks and develop quality improvement plans. |
| Implementation of Quality Improvement Strategies | Month 8-9 | Execute the developed strategies to enhance care quality. |
| Evaluation and Adjustments | Month 10-12 | Assess the impact of implemented strategies and make necessary adjustments. |
Expected Time Frames
It is expected to take one year to complete; however, each phase has certain targets to accomplish to ensure an organized implementation process.
Conclusion
The proposed study aimed to have a general patient care upgrade comprehensively collected data, ensure compliance with the set health standards and integrate practices that reflect the set standards. In this way, the study will compare local data to national databases and determine where potential improvements can be made, which will help with decision-making and improve the quality of health services (Andersson et al., 2018; Shuman & Bebeau, 1996).
References
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