One of the key advantages of Dr. Jesse Browning’s decision to focus on the use of electronic health records (EHRs) is that they allow for effective data sharing, which serves towards improving the quality of care. EHR systems are used as part of the health care environment for the sole purpose of collecting and sharing relevant data associated with the services offered to patients (Wagholikar et al., 2017). That serves as one of the key factors that would aid in promoting generalized improvements in the overall structure of performance as part of a health care environment. In the following analysis, the focus will be on trying to examine the need to share data as well as reflecting on some of the key types of data that would be shared on the systems. Additionally, the analysis will also seek to examine data interchange standards with the sole focus being towards determining the effective use of EHRs as part of health care service delivery.
Need to Share Data
The need to share data can be seen from multiple perspective, which seek to highlight the importance associated with the adoption of effective data sharing expectations. The following are some of the benefits associated with sharing data:
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The need to share data is driven by the fact that data plays a critical role in the identification of a patient’s medical history. Ultimately, this means that a health care professional would be in a rather effective position through which to make effective decisions on treatment options depending on the historical data collected.
Shared data is equally essential towards identifying contraindications for patients towards specific medication, which would help in averting possible medical errors. Contraindications often arise from a clear lack of understanding of how patients interact with specific drugs and medication. The use of EHR systems allows for an effective avenue through which to provide the health care professional with enough information that would provide a clear guideline on patient interaction with specific medication (Cai, Yan, Li, Huang, & Gao, 2017).
Sharing data also plays a critical role in reframing health care priorities when dealing with specific patients. In some cases, patients often suffer from multiple diseases or conditions, which becomes a challenge for health professionals intending to make a decision on the priority. However, this has been handled effectively through the use of shared data within the EHR systems, which allows for an easier avenue through which to get clear information touching on the different medical conditions.
From the analysis, it becomes clear that indeed there is a need for Wasatch Family Clinic to build on its usage of an EHR system with the sole focus being towards evaluating how it would be able to share data. The shared data would be of great value towards creating a streamlined approach towards improving the quality of health care services offered.
Type of Data to be Shared
The use of the EHR systems allows for the collection, storage, and sharing of different types of health care data. Some of the key types of data to be shared using the new system adopted as part of the Wasatch Family Clinic include:
Demographic Data: This is a type of data that focus on a patient’s personal information including name, gender, age, and weight among other personal information. The demographic data provided helps health care professionals when making effective decisions focusing on their patients.
Clinical Data: Clinical data refers to a type of data that reflects on the clinical approaches taken when dealing with patients. Clinical data can be classified as structured and unstructured data. Structured data include information on diagnosis, procedures, laboratory examinations, and medications given to the patient (Zaidan, Haiqi, Zaidan, Abdulnabi, Kiah, & Muzamel, 2015). On the other hand, unstructured data include documentation, imaging, audio, and video information that focuses on clinical services offered to the patient.
Wellness Data: Wellness data focus on information on a patient’s immediate environment, which is important towards determining the approaches that patients are taking in their bid to protecting themselves from illnesses. Some of the information gathered as part of wellness data include data on individual dimensions of wellness to maximize on quality outcomes.
Administrative Data: Administrative data refer to logistical, financial, and administrative information that reflects on the delivery of care to individual patients. For example, it is important to consider insurance claims when dealing with patients covered by different insurance covers. The claims are under financial information for the patients while ensuring that the health care facility is in a position that guarantees an improved framework of service delivery.
Aggregate Data: Aggregate data focuses on data collected from local, state, national, and international agencies, which are both governmental and non-governmental. The data collected seeks to focus on specific aspects of health including trying to examine the prevalence of specific health conditions and determining the best approaches to dealing with an epidemic. Some of the key agencies that help in the collection of such data include the World Health Organization (WHO) and the Center for Disease Control and Prevention (CDC).
Data Interchange Standards
There are four main data interchange standards that must be considered as part of data sharing with the aim being towards improving on overall quality of care. The four data interchange standards are:
Message Format: The format of the message within the shared data must use common encoding specifications and information models with the aim being towards ensuring that the data can be interpreted with ease. Using a complex encoding specification may result in a situation where the data share is not decoded; thus, cannot be used as part of health care service delivery.
Document Architecture: The architecture of the document shared as part of the data sharing process must be standardized with the intention being towards ensuring that access to data is faster and much more reliable regardless of the health professional using the shared information.
Clinical Templates: Electronic data sharing mechanisms often create templates that health professionals would be able to use as part of maintain moderate optionality regardless of the constraints. That makes it much easier for data interpretation with the aim being towards building on effective use of the data as part of the clinical or health care environment.
User Interface: The user interface allows for the devices used to be much safer, faster, effective in the data sharing process. By having an interface that is easy for all users, the most likely outcome is that it becomes much easier for the individual users to be in a position allowing them to interpret such data effectively.
Summary
One of the key advantages of Dr. Jesse Browning’s decision to focus on the use of electronic health records (EHRs) is that they allow for effective data sharing, which serves towards improving the quality of care. The shared data would be of great value towards creating a streamlined approach towards improving the quality of health care services offered. The main types of data considered when using an EHR system include demographic, clinical, wellness, administrative, and aggregate data. The data interchange standards to consider when sharing data include message format, document architecture, clinical templates, and user interface.
References
Cai, Z., Yan, H., Li, P., Huang, Z. A., & Gao, C. (2017). Towards secure and flexible EHR sharing in mobile health cloud under static assumptions. Cluster Computing , 20 (3), 2415-2422.
Wagholikar, K. B., Jain, R., Oliveira, E., Mandel, J., Klann, J., Colas, R., ... & Murphy, S. N. (2017). Evolving research data sharing networks to clinical app sharing networks. AMIA Summits on Translational Science Proceedings , 2017 , 302.
Zaidan, B. B., Haiqi, A., Zaidan, A. A., Abdulnabi, M., Kiah, M. M., & Muzamel, H. (2015). A security framework for nationwide health information exchange based on telehealth strategy. Journal of medical systems , 39 (5), 51.
