One of the roles of an electronic health record is to allow providers to be able to collect, retrieve, as well as report various types of health data. This has created the need for the health information management professional to be able to ensure that the data is accurate and complete ( Bunce, Gold, Davis, Mercer, Jaworski, Hollombe, & Nelson, 2017) . Based on the assessment conducted on Independent Medical Center and the HIM used, some improvements are needed. The current system is fragmented, and the lack of integration reduces the quality of patient data that is generated by the OPUS system ( Adler‐Milstein, Everson, & Lee, 2015) . Without any improvement, the hospital may lag in terms of patient data implementation. The collection, storage, and analysis of data are playing an important role in the delivery and planning of healthcare ( Bowles, 2014) . As the field of health grows, data is continuously being used in order to develop new applications in order to improve the patient experience while also increasing the efficiency of the organization ( Brennan & Bakken, 2015) . Independent Medical Center should improve on some of the practices used in the collection of data, how it is stored and analyzed.
Recommended Changes to the Health Information Management System
In order to ensure there is a meaningful use of data, it is important to ensure that every employee and health practitioners embrace the use of computers in the handling of all patient records. One of the recommended improvement is related to interoperability ( Zhang, Liu. and Xue, 2013) . Interoperability helps in increasing the ease with which data is transported and shared between stakeholders. Modern health information technology is only manageable if the systems used in every department are interoperable ( Bunce et al., 2017) . Independent Medical Center is lagging in this area because all departments have their systems, which makes it hard for information to be accessed across the system.
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Interoperability enables test results, images, and medical histories as well as other important data to be sent from one provider to another ( Brennan & Bakken, 2015) . This is important when the patient is seeing a specialist, changing physicians, or seeing multiple professionals. The hospital also needs to establish better ways to conduct data analysis as raw data does little to impact patient care without any meaningful analysis being conducted ( Adler‐Milstein, Everson, & Lee, 2015) . Therefore, data analytics is important when it comes to health information management. The hospital needs to involve the HIM professional in all the areas where data is being collected, stored, or retrieved. The analysis is important for decision-making purposes.
One of the main areas where the hospital needs to improve its HIM system is in access to patient information by all those involved in the provision of healthcare. For instance, it was established that doctors are not able to access information and if they do, they only get reports and not the full information ( Bowles, 2014) . For example, reports from the diagnostic department are not easily accessible by doctors unless they manually request for the information ( Nwosu, Collins, & Mason, 2018) . Consequently, doctors are not able to access information on available medicine in the hospital pharmacy, which means that there is the risk of the patients getting prescriptions that are not available in the hospital ( Shickel, Tighe, Bihorac, & Rashidi, 2018) . This calls for the integration of all the needs of the healthcare practitioners working in the hospital.
Alignment to Administrative and Clinical Goals
Improvement in the hospital technology base in regards to the EHR system helps in aligning operations to the administrative and clinical goals. The hospital can provide patients with personalized interactions by integrating patient data from all the sources that are available in the hospital ( Bowles, 2014) . The hospital seeks to improve its patient engagement using predictive modeling coupled with analysis based on healthcare data. There is also the ability to make informed business decisions based on data insights ( Nwosu, Collins, & Mason, 2018) . Improvements in the system help in understanding physician activity and align them with the goals of the organization. The aim of the hospital putting up the HIM system is to reduce its administrative costs that have been one of the major problems affecting some hospitals in the country ( Henry, Pylypchuk, Searcy, & Patel, 2016) . Minimizing the administrative costs means that the hospital can invest in other areas such as the addition of new services to its supply chain.
Patient data and the improvement of the current EHR system are essential in supporting clinical decision-making, which helps in reducing the number of medical errors that are made by the doctors ( Bowles, 2014) . The implication is that the hospital will be able to improve customer satisfaction levels. Moreover, there are also gains in terms of the reduction in abuse and fraud especially when it comes to the procurement operations of the hospital. Therefore, there will be fewer financial losses as the hospital will only procure what it needs and will use. The other benefit that comes with the improvement is the enhancement of care coordination and hence customer satisfaction ( Bunce et al., 2017) . The more satisfied the customers are, the more likely it is for the hospital to attract more patients, which improves its financial abilities. Patient wellness is the other main benefit that comes with the improvement of the health information benefit ( Scholte et al., 2016) . These benefits come from improvement in how information is collected and leveraged.
Leveraging of Data Analysis Trends
Data analysis and reporting will be on the rise as the technology improvement will allow the providers to capture new information that is critical to the provision of healthcare ( Brennan & Bakken, 2015) . With the use of the HIM professional hired by the hospital, Independent Medical Center will guide the hospital in making improvements in regards to business intelligence, clinical care, and decision-making throughout the enterprise ( Brennan & Bakken, 2015) . The HIM professional to come up with design requirements, metric, and criteria that meet the requirements for analysis and interpretations. The needs may vary depending on the researcher, clinician, payer, consumer, or executive ( Caine, Kohn, Lawrence, Hanania, Meslin, & Tierney, 2015) . The professional must be able to address what source of the data, whether the data is accurate, if the data is complete, and if it meets the needs of the users. The professionals have to make use of both qualitative and quantitative strategies in analyzing the data needed to provide patients with the best care possible.
Hospitals are facing much pressure to make use of data to change their reimbursement models or improving the patient base ( Henry et al., 2016) . Hospitals need to understand how they can use data to improve efficiency, promote the satisfaction of the customers, as well as to drive better outcomes ( Feder, 2018) . Independent Medical Center can make a difference with data as data is changing the society, especially in the healthcare sector. Gaining meaningful will help the hospital attain a higher quality of care, better decision making, lower costs, as well as discoveries that help in the improvement of care provided to the care ( Caine et al., 2015) .
Recommendations for Best Practices in Data Collection
As an organization that has complied with meaningful use, Independent Medical Center has an already established information system for data collection and reporting ( Brennan & Bakken, 2015) . Consequently, the hospital staff is also used in collecting registration as well as admission data. There is also an existing organizational culture based on the need to collect and analyze patients’ data.
It is important for the hospital to implement systems changes that involve training a large number of people among the employees ( Tapuria, Bruland, Delaney, Kalra, and Curcin, 2018) . This should be coupled with modifying practice management and EHR systems in order to ensure that there are proper and consistent data fields across all the departments that play a role as patient entry points ( Feder, 2018) . For the systems to be interoperable, it is important to develop interfaces that make it possible to relay the data found across the different systems ( Bunce et al., 2017) . For instance, the nursing interface should be integrated with the pharmacy department, the diagnostic department, the billing unit, and the physician department. Moreover, there is a need to ensure that there is a similar way of reporting regardless of the department ( Caine et al., 2015) . Integrating all the subsystems in the hospital will help in ensuring that there is better handling of patient information to produce meaningful results that can impact positively on the delivery of healthcare ( Stadler, Donlon, Siewert, Franken, & Lewis, 2016) . Based on the assessment done on the hospital’s system, it is clear that the independent systems used by every department make it hard for the smooth flow of information in the hospital.
In order to improve EHR documentation, it is important for the hospital to consider both technical and administrative solutions. In regards to administrative solutions, it is important to establish business practices that support quality clinical documentation ( Dunne, Raynor, Cottrell, & Pinnock, 2017) . This integrity can be maintained by having the desire and commitment to conduct business and also provide care in a manner that is ethical. The hospital should also engage professionals who work to enhance functions and capabilities that prevent and also discourage any fraudulent activity ( Caine et al., 2015) . The policies and procedures implemented by the hospital should also prevent any fraud. This also calls for the inclusion of a HIM professional whose role is to ensure that the end product complies with guidelines set in regards to billing, documentation, and payer information ( Dunne et al., 2017) .
Data collection in the hospital setting is something that has to consider privacy and security due to the sensitivity of the information and to ensure compliance with the Federal requirements ( Caine et al., 2015) . With the advances in healthcare and the adoption of technology, there is an increasing amount of information stored online, which raises the question of security. It has been established that the number of attacks against hospitals has been on the rise in the recent past ( Dunne, Raynor, Cottrell, & Pinnock, 2017) . This calls for strategies and technologies that ensure the privacy and security of the data at the hospital. The HIM professional should work towards ensuring the protection of sensitive information to establish trust with the patients ( Feder, 2018) . Patients are less likely to accept to store health information online if there are any questions of safety.
Conclusion
The current OPUS system requires to undergo both technological and logistical improvement despite the certification for meaningful use. The improvement should be in the flow of information from one department to the other and the access that health practitioners have to necessary patient data. Moreover, the improvement to the current HIM system should be in line with administrative and clinical goals. The hospital is bound to benefit in terms of reduction of cost used in running the hospital, enhancement of the quality of care, and minimization of fraud and losses due to the harmonization of all the systems. One of the things that must be addressed is making an interoperable system. An interoperable system is one that has a unique way of reporting data that is adopted by every person in the organization.
References
Adler‐Milstein, J., Everson, J., & Lee, S. Y. D. (2015). EHR adoption and hospital performance: time‐related effects. Health Services Research , 50 (6): 1751-1771.
Bowles, K. (2014). Developing evidence-based tools from EHR data. Nursing Management (Springhouse) , 45(4): 18-20.
Brennan, P. F., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship , 47 (5): 477-484.
Bunce, A. E., Gold, R., Davis, J. V., Mercer, M., Jaworski, V., Hollombe, C., & Nelson, C. (2017). “Salt in the Wound”: safety net clinician perspectives on performance feedback derived from EHR data. The Journal of Ambulatory Care Management , 40 (1): 26.
Caine, K., Kohn, S., Lawrence, C., Hanania, R., Meslin, E. M., & Tierney, W. M. (2015). Designing a patient-centered user interface for access decisions about EHR data: implications from patient interviews. Journal of General Internal Medicine , 30 (1): 7-16.
Dunne, M. J., Raynor, L. A., Cottrell, E. K., & Pinnock, W. J. (2017). Interviews with patients and providers on transgender and gender nonconforming health data collection in the electronic health record. Transgender Health , 2 (1): 1-7.
Feder, S. L. (2018). Data quality in electronic health records research: Quality domains and assessment methods. Western Journal of Nursing Research , 40 (5): 753-766.
Henry, J., Pylypchuk, Y., Searcy, T., & Patel, V. (2016). Adoption of electronic health record systems among US non-federal acute care hospitals: 2008-2015. ONC data brief , 35 : 1-9.
Nwosu, A. C., Collins, B., & Mason, S. (2018). Big Data analysis to improve care for people living with serious illness: The potential to use new emerging technology in palliative care. Palliative Medicine , 32 (1), 164-166.
Shickel, B., Tighe, P. J., Bihorac, A., & Rashidi, P. (2018). Deep EHR: A survey of recent advances in deep learning techniques for electronic health record (EHR) analysis. IEEE Journal of Biomedical and Health Informatics , 22 (5), 1589-1604.
Scholte, M., van Dulmen, S. A., Neeleman-Van der Steen, C. W., van der Wees, P. J., Nijhuis-van der Sanden, M. W., & Braspenning, J. (2016). Data extraction from electronic health records (EHRs) for quality measurement of the physical therapy process: comparison between EHR data and survey data. BMC Medical Informatics and Decision Making , 16 (1): 141.
Stadler, J. G., Donlon, K., Siewert, J. D., Franken, T., & Lewis, N. E. (2016). Improving the efficiency and ease of healthcare analysis through the use of data visualization dashboards. Big Data , 4 (2): 129-135.
Tapuria, A., Bruland, P., Delaney, B., Kalra, D. and Curcin, V. (2018). Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data. Digital Health , 4(1): 1-12.
Zhang, R., Liu, L. and Xue, R. (2013). Role-based and time-bound access and management of EHR data. Security and Communication Networks , 7 (6): 994-1015.
