Medical data integration using HL7 standards for patient’s early identification

Integration between information systems is critical, especially in the healthcare domain, since interoperability requirements are related to patients’ data confidentiality, safety, and satisfaction. The goal of this study is to propose a solution based on the integration between queue management solution (QMS) and the electronic medical records (EMR), using Health Level Seven (HL7) protocols and Extensible Markup Language (XML). The proposed solution facilitates the patient’s self-check-in within a healthcare organization in UAE. The solution aims to help in minimizing the waiting times within the outpatient department through early identification of patients who hold the Emirates national ID cards, i.e., whether an Emirati or expatriates. The integration components, solution design, and the custom-designed XML and HL7 messages were clarified in this paper. In addition, the study includes a simulation experiment through control and intervention weeks with 517 valid appointments. The experiment goal was to evaluate the patient’s total journey and each related clinical stage by comparing the “routine-based identification” with the “patient’s self-check-in” processes in case of booked appointments. As a key finding, the proposed solution is efficient and could reduce the “patient’s journey time” by more than 14 minutes and “time to identify” patients by 10 minutes. There was also a significant drop in the waiting time to triage and the time to finish the triage process. In conclusion, the proposed solution is considered innovative and can provide a positive added value for the patient’s whole journey.

Download Full-text

Risk Diagrams Based on Primary Care Electronic Medical Records and Linked Real-Time PCR Data to Monitor Local COVID-19 Outbreaks During the Summer 2020: A Prospective Study Including 7,671,862 People in Catalonia

Frontiers in Public Health ◽

10.3389/fpubh.2021.693956 ◽

2021 ◽

Vol 9 ◽

Author(s):

Marti Catala ◽

Ermengol Coma ◽

Sergio Alonso ◽

Enrique Álvarez-Lacalle ◽

Silvia Cordomi ◽

...

Keyword(s):

Primary Care ◽

Intensive Care ◽

Electronic Medical Records ◽

Early Identification ◽

Medical Records ◽

Hospital Admissions ◽

Nursing Home Residents ◽

Population Based ◽

Local Hospital ◽

Potential Growth

Monitoring transmission is a prerequisite for containing COVID-19. We report on effective potential growth (EPG) as a novel measure for the early identification of local outbreaks based on primary care electronic medical records (EMR) and PCR-confirmed cases. Secondly, we studied whether increasing EPG precedes local hospital and intensive care (ICU) admissions and mortality. Population-based cohort including all Catalan citizens' PCR tests, hospitalization, intensive care (ICU) and mortality between 1/07/2020 and 13/09/2020; linked EMR covering 88.6% of the Catalan population was obtained. Nursing home residents were excluded. COVID-19 counts were ascertained based on EMR and PCRs separately. Weekly empirical propagation (ρ7) and 14-day cumulative incidence (A14) and 95% confidence intervals were estimated at care management area (CMA) level, and combined as EPG = ρ7 × A14. Overall, 7,607,201 and 6,798,994 people in 43 CMAs were included for PCR and EMR measures, respectively. A14, ρ7, and EPG increased in numerous CMAs during summer 2020. EMR identified 2.70-fold more cases than PCRs, with similar trends, a median (interquartile range) 2 (1) days earlier, and better precision. Upticks in EPG preceded increases in local hospital admissions, ICU occupancy, and mortality. Increasing EPG identified localized outbreaks in Catalonia, and preceded local hospital and ICU admissions and subsequent mortality. EMRs provided similar estimates to PCR, but some days earlier and with better precision. EPG is a useful tool for the monitoring of community transmission and for the early identification of COVID-19 local outbreaks.

Download Full-text

Wearable devices in cardiology

Heart and Metabolism - Heart Failure in patients with Diabetes ◽

10.31887/hm.2020.82/mcowie ◽

2020 ◽

pp. 12-16

Keyword(s):

Heart Failure ◽

Electronic Medical Records ◽

Medical Records ◽

Treatment Decision ◽

Wearable Devices ◽

The Body ◽

Added Value ◽

Clinical Value ◽

Treatment Decision Making ◽

Heart Failure Decompensation

Wearables—sensors that are externally applied to the body to measure a signal and transmit or record the data for further analysis—are an industry worth billions of dollars annually. It is technically feasible to measure activity, blood pressure, and pulse, and to detect arrhythmia and potential heart failure decompensation via wearables. Relatively few studies have assessed the clinical value of wearables, and many remain curiosities or consumer “toys.” However, through attention to demonstrating accuracy and added value, it is possible for some technologies to be incorporated into diagnostic and treatment decision-making. Barriers to such transition include patient and physician acceptability, difficulties in incorporating the data into electronic medical records, and lack of reimbursement or regulatory approval. Cardiologists are becoming increasingly familiar with this developing field, but pressure for implementation may come more from the consumer than from the health care system.

Download Full-text