Considering Work Systems and Processes in Assessing the Impact of a CDSS Intervention: Preliminary Results.

The DetecIP project aims to implement multifactorial dynamic rules within a computerized decision support system (CDSS) for pharmaceutical analysis of orders to reduce the rate and severity of iatrogenic hyperkalemia and acute kidney injury. However, understanding the impact of this intervention (if any) requires that the way in which it influences the work systems and processes also be studied. This study presents the preliminary results of the analysis of the work contexts in which these rules will be implemented. A series of semi-structured interviews exploring the dimensions of the systems engineering initiative for patient safety (SEIPS) were conducted with healthcare professionals involved in the prevention and management of iatrogenic risks in five hospital units. Data were analyzed to identify current barriers and facilitators to the prevention and management of iatrogenic risks. Preliminary results from a geriatric unit and a cardiology unit reveal that, despite overall similarities in work processes, differences in the availability and location of physicians and clinical pharmacists influence how iatrogenic risks are managed. These contextual differences could influence the impact of the new CDSS rules once implemented.

The impact of including a medication review in an integrated care pathway: A pilot study.

AIM: The objective of the present study was to measure the impact of the intervention of combining a medication review with an integrated care approach on potentially inappropriate medications (PIMs) and hospital readmissions in frail older adults. METHODS: A cohort of hospitalized older adults enrolled in the French PAERPA integrated care pathway (the exposed cohort) was matched retrospectively with hospitalized older adults not enrolled in the pathway (unexposed cohort) between January 1st, 2015, and December 31st, 2018. The study was an analysis of French health administrative database. The inclusion criteria for exposed patients were admission to an acute care department in a general hospital, age 75 years or over, at least three comorbidities or the prescription of diuretics or oral anticoagulants, discharge alive and performance of a medication review. RESULTS: For the study population (n = 582), the mean ± standard deviation age was 82.9 ± 4.9 years, and 380 (65.3%) were women. Depending on the definition used, the overall median number of PIMs ranged from 2 [0;3] on admission to 3 [0;3] at discharge. The intervention was not associated with a significant difference in the mean number of PIMs. Patients in the exposed cohort were half as likely to be readmitted to hospital within 30 days of discharge relative to patients in the unexposed cohort. CONCLUSION: Our results show that a medication review was not associated with a decrease in the mean number of PIMs. However, an integrated care intervention including the medication review was associated with a reduction in the number of hospital readmissions at 30 days.

Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study.

BACKGROUND: Despite the many opportunities data reuse offers, its implementation presents many difficulties, and raw data cannot be reused directly. Information is not always directly available in the source database and needs to be computed afterwards with raw data for defining an algorithm. OBJECTIVE: The main purpose of this article is to present a standardized description of the steps and transformations required during the feature extraction process when conducting retrospective observational studies. A secondary objective is to identify how the features could be stored in the schema of a data warehouse. METHODS: This study involved the following 3 main steps: (1) the collection of relevant study cases related to feature extraction and based on the automatic and secondary use of data; (2) the standardized description of raw data, steps, and transformations, which were common to the study cases; and (3) the identification of an appropriate table to store the features in the Observation Medical Outcomes Partnership (OMOP) common data model (CDM). RESULTS: We interviewed 10 researchers from 3 French university hospitals and a national institution, who were involved in 8 retrospective and observational studies. Based on these studies, 2 states (track and feature) and 2 transformations (track definition and track aggregation) emerged. "Track" is a time-dependent signal or period of interest, defined by a statistical unit, a value, and 2 milestones (a start event and an end event). "Feature" is time-independent high-level information with dimensionality identical to the statistical unit of the study, defined by a label and a value. The time dimension has become implicit in the value or name of the variable. We propose the 2 tables "TRACK" and "FEATURE" to store variables obtained in feature extraction and extend the OMOP CDM. CONCLUSIONS: We propose a standardized description of the feature extraction process. The process combined the 2 steps of track definition and track aggregation. By dividing the feature extraction into these 2 steps, difficulty was managed during track definition. The standardization of tracks requires great expertise with regard to the data, but allows the application of an infinite number of complex transformations. On the contrary, track aggregation is a very simple operation with a finite number of possibilities. A complete description of these steps could enhance the reproducibility of retrospective studies.

Accuracy of the French Administrative Database to Describe Patients' Medication and Primary Care Visits: A Validation Study.

OBJECTIVE: To evaluate the accuracy of the French health administrative database to describe patients' medication and primary care visits, in the context of a transitional care intervention including an in-hospital medication reconciliation followed by a structured community follow-up by the patient's general practitioner and pharmacist. DESIGN: A retrospective cohort study of older persons enrolled in the transitional care intervention between January 1st, 2015 and December 31st, 2018. RESULTS: Only 46.1% of the community follow-up were timely billed, in the 3 months after the patient discharge. The sensitivity of the health administrative database to identify medications was 90.0%. Its positive predictive value was 50.1%. CONCLUSION: This study reveals that the French health administrative database was poorly reliable to identify both community follow-up and chronic medications.