Diabetes and the direct secondary use of electronic health records: Using routinely collected and stored data to drive research and understanding

Fragmented care trajectories in municipal healthcare: Local sensemaking of digital documentation

Objective

Since the 1990s, almost all healthcare organisations have had electronic health records (EHR) to organise and manage treatment, care and work routines. This article aims to understand how healthcare professionals (HCPs) make sense of digital documentation practice.

Methods

Based on a case study design, field observations and semi-structured interviews were conducted in a Danish municipality. A systematic analysis based on Karl Weick's sensemaking theory was applied to investigate what cues HCPs extract from timetables in the EHR and how institutional logics frame the enactment of documentation practice.

Results

The analysis uncovered three themes: making sense of planning, making sense of tasks and making sense of documentation. The themes illustrate that HCPs make sense of the digital documentation practice as a dominant managerial tool designed to control resources and work routines. This sensemaking leads to a task-oriented practice which centres on delivering fragmented tasks according to a timetable.

Conclusion

HCPs mitigate fragmentation by responding to a care professional logic, where they document to share information and carry out invisible work outside of timetables and scheduled tasks. However, HCPs are focused on solving specific tasks by the minute with the possible consequence that continuity and their overview of the service user's care and treatment disappear. In conclusion, the EHR system eliminates a holistic view of care trajectories, leaving it up to HCPs to collaborate in an effort to obtain continuity for the service user.

Evaluating the Representativeness of US Centricity Electronic Medical Records With Reports From the Centers for Disease Control and Prevention: Comparative Study on Office Visits and Cardiometabolic Conditions

Background

Electronic medical record (EMR)–based clinical and epidemiological research has dramatically increased over the last decade, although establishing the generalizability of such big databases for conducting epidemiological studies has been an ongoing challenge. To draw meaningful inferences from such studies, it is essential to fully understand the characteristics of the underlying population and potential biases in EMRs.

Objective

This study aimed to assess the generalizability and representativity of the widely used US Centricity Electronic Medical Record (CEMR), a primary and ambulatory care EMR for population health research, using data from the National Ambulatory Medical Care Surveys (NAMCS) and the National Health and Nutrition Examination Surveys (NHANES).

Methods

The number of office visits reported in the NAMCS, designed to meet the need for objective and reliable information about the provision and the use of ambulatory medical care services, was compared with similar data from the CEMR. The distribution of major cardiometabolic diseases in the NHANES, designed to assess the health and nutritional status of adults and children in the United States, was compared with similar data from the CEMR.

Results

Gender and ethnicity distributions were similar between the NAMCS and the CEMR. Younger patients (aged <15 years) were underrepresented in the CEMR compared with the NAMCS. The number of office visits per 100 persons per year was similar: 277.9 (95% CI 259.3-296.5) in the NAMCS and 284.6 (95% CI 284.4-284.7) in the CEMR. However, the number of visits for males was significantly higher in the CEMR (CEMR: 270.8 and NAMCS: 239.0). West and South regions were underrepresented and overrepresented, respectively, in the CEMR. The overall prevalence of diabetes along with age and gender distribution was similar in the CEMR and the NHANES: overall prevalence, 10.1% and 9.7%; male, 11.5% and 10.8%; female, 9.1% and 8.8%; age 20 to 40 years, 2.5% and 1.8%; and age 40 to 60 years, 9.4% and 11.1%, respectively. The prevalence of obesity was similar: 42.1% and 39.6%, with similar age and female distribution (41.5% and 41.1%) but different male distribution (42.7% and 37.9%). The overall prevalence of high cholesterol along with age and female distribution was similar in the CEMR and the NHANES: overall prevalence, 12.4% and 12.4%; and female, 14.8% and 13.2%, respectively. The overall prevalence of hypertension was significantly higher in the CEMR (33.5%) than in the NHANES (95% CI: 27.0%-31.0%).

Conclusions

The distribution of major cardiometabolic diseases in the CEMR is comparable with the national survey results. The CEMR represents the general US population well in terms of office visits and major chronic conditions, whereas the potential subgroup differences in terms of age and gender distribution and prevalence may differ and, therefore, should be carefully taken care of in future studies.