Dataset Information

Primary Care Medication Safety Surveillance with Integrated Primary and Secondary Care Electronic Health Records: A Cross-Sectional Study.

ABSTRACT:

Introduction

The extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring.

Objective

The aim of the study was to investigate the feasibility of linked primary and secondary care electronic health record data for surveillance of medication safety, examining not only prescribing but also monitoring, and associations with patient- and general practice-level characteristics.

Methods

A cross-sectional study was conducted using linked records of patients served by one hospital and over 50 general practices in Salford, UK. Statistical analysis consisted of mixed-effects logistic models, relating prescribing safety indicators to potential determinants.

Results

The overall prevalence (proportion of patients with at least one medication safety hazard) was 5.45 % for prescribing indicators and 7.65 % for monitoring indicators. Older patients and those on multiple medications were at higher risk of prescribing hazards, but at lower risk of missed monitoring. The odds of missed monitoring among all patients were 25 % less for males, 50 % less for patients in practices that provide general practitioner training, and threefold higher in practices serving the most deprived compared with the least deprived areas. Practices with more prescribing hazards did not tend to show more monitoring issues.

Conclusions

Systematic collection, collation, and analysis of linked primary and secondary care records produce plausible and useful information about medication safety for a health system. Medication safety surveillance systems should pay close attention to patient age and polypharmacy with respect to both prescribing and monitoring failures; treat prescribing and monitoring as different statistical processes, rather than a combined measure of prescribing safety; and audit the socio-economic equity of missed monitoring.

SUBMITTER: Akbarov A

PROVIDER: S-EPMC4486763 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Primary Care Medication Safety Surveillance with Integrated Primary and Secondary Care Electronic Health Records: A Cross-Sectional Study.

Akbarov Artur A Kontopantelis Evangelos E Sperrin Matthew M Stocks Susan J SJ Williams Richard R Rodgers Sarah S Avery Anthony A Buchan Iain I Ashcroft Darren M DM

Drug safety 20150701 7

<h4>Introduction</h4>The extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring.<h4>Objective</h4>The aim of the stu ...[more]

PMID: 26100143

Similar Datasets

Project description:Safety net health systems face barriers to effective ambulatory medication reconciliation for vulnerable populations. Although some electronic health record (EHR) systems offer safety advantages, EHR use may affect the quality of patient-provider communication.This mixed-methods observational study aimed to develop a conceptual framework of how clinicians balance the demands and risks of EHR and communication tasks during medication reconciliation discussions in a safety net system.This study occurred 3 to 16 (median 9) months after new EHR implementation in five academic public hospital clinics. We video recorded visits between English-/Spanish-speaking patients and their primary/specialty care clinicians. We analyzed the proportion of medications addressed and coded time spent on nonverbal tasks during medication reconciliation as "multitasking EHR use," "silent EHR use," "non-EHR multitasking," and "focused patient-clinician talk." Finally, we analyzed communication patterns to develop a conceptual framework.We examined 35 visits (17%, 6/35 Spanish) between 25 patients (mean age 57, SD 11 years; 44%, 11/25 women; 48%, 12/25 Hispanic; and 20%, 5/25 with limited health literacy) and 25 clinicians (48%, 12/25 primary care). Patients had listed a median of 7 (IQR 5-12) relevant medications, and clinicians addressed a median of 3 (interquartile range [IQR] 1-5) medications. The median duration of medication reconciliation was 2.1 (IQR 1.0-4.2) minutes, comprising a median of 10% (IQR 3%-17%) of visit time. Multitasking EHR use occurred in 47% (IQR 26%-70%) of the medication reconciliation time. Silent EHR use and non-EHR multitasking occurred a smaller proportion of medication reconciliation time, with a median of 0% for both. Focused clinician-patient talk occurred a median of 24% (IQR 0-39%) of medication reconciliation time. Five communication patterns with EHR medication reconciliation were observed: (1) typical EHR multitasking for medication reconciliation, (2) dynamic EHR use to negotiate medication discrepancies, (3) focused patient-clinician talk for medication counseling and addressing patient concerns, (4) responding to patient concerns while maintaining EHR use, and (5) using EHRs to engage patients during medication reconciliation. We developed a conceptual diagram representing the dilemma of the multitasking clinician during medication reconciliation.Safety net visits involve multitasking EHR use during almost half of medication reconciliation time. The multitasking clinician balances the cognitive and emotional demands posed by incoming information from multiple sources, attempts to synthesize and act on this information through EHR and communication tasks, and adopts strategies of silent EHR use and focused patient-clinician talk that may help mitigate the risks of multitasking. Future studies should explore diverse patient perspectives about clinician EHR multitasking, clinical outcomes related to EHR multitasking, and human factors and systems engineering interventions to improve the safety of EHR use during the complex process of medication reconciliation.

Project description:BackgroundGlobally, non-communicable diseases (NCDs) are recognised as a leading cause of morbidity and mortality. Medications and medicines optimisation play an important role in the management of modifiable physiological risk factors and NCDs. The importance of lifestyle interventions in prevention of modifiable risk factors is also well established. The aim of this paper was to describe the quantity of type 2 diabetes mellitus (T2DM), hypertension and dyslipidaemia prescribing in Qatari primary care settings. Its findings will provide necessary information to inform pharmaceutical policy and practice.MethodsThe study was undertaken in Qatar's publicly funded primary health care centres. Data sources for this study comprised electronic medical records. The Anatomical Therapeutic Chemical (ATC) drug classification system was used to classify the medications prescribed. The number and proportion of medications by age, sex, nationality and diagnosis (T2DM, hypertension and dyslipidaemia) were reported.ResultsA total 81,569 individuals were included (18-29 years 2.4%; 30-39 years 11.7%; 40-49 years 25.4%; 50-59 years 31.9% and ≥ 60 years 28.6%). 55.6% participants were male. On average 10.2 medications were prescribed per person and 2.3 medications were included in each prescription. T2DM medications were most prescribed (N = 361,87780,799; 43.2%) followed by hypertension (N = 303,086; 36.2%) and dyslipidaemia (N = 172,163; 20.5%). Of the total medications prescribed, 72% (N = 605,488) were prescribed in individuals aged 50 years and above. Men were prescribed 62% (N = 515,043) medications while women were prescribed 38% (N = 322,083) medications. Southern Asians (N = 330,338; 39%) were prescribed most medication followed by Qataris (N = 181,328; 22%) and Northern African (N = 145,577; 17%).ConclusionsIn Qatar's primary care settings, average medications prescribed per patients were found to be higher compared to other populations. While medications were actively prescribed for the 3 conditions, the study found variations by medication type, age, gender and nationality. Rational guidelines for the utilisation of medications need to be established with the support of real-world evidence.

Project description:ObjectiveTo determine common patterns of recorded primary care for osteoarthritis (OA), and patient and provider characteristics associated with the quality of recorded care.DesignAn observational study nested within a cluster-randomised controlled trial.SettingEight UK general practices who were part of the Management of Osteoarthritis in Consultations study.ParticipantsPatients recorded as consulting within the eight general practices for clinical OA.Primary outcomesAchievement of seven quality indicators of care (pain/function assessment, information provision, exercise/weight advice, analgesics, physiotherapy), recorded through an electronic template or routinely recorded in the electronic healthcare records, was identified for patients aged ≥45 years consulting over a 6-month period with clinical OA. Latent class analysis was used to cluster patients based on care received. Clusters were compared on patient and clinician-level characteristics.Results1724 patients (median by practice 183) consulted with clinical OA. Common patterns of recorded quality care were: cluster 1 (38%, High) received most quality indicators of care; cluster 2 (11%, Moderate) had pain and function assessment, and received or were considered for other indicators; cluster 3 (17%, Low) had pain and function assessment, and received or were considered for paracetamol or topical non-steroidal anti-inflammatory drugs; cluster 4 (35%, None) had no recorded quality indicators. Patients with higher levels of recorded care consulted a clinician who saw more patients with OA, consulted multiple times and had less morbidity. Those in the High cluster were more likely to have recorded diagnosed OA and have knee/hip OA.ConclusionsPatterns of recorded care for OA fell into four natural clusters. Appropriate delivery of core interventions and relatively safe pharmacological options for OA are still not consistently recorded as provided in primary care. Further research to understand clinical recording behaviours and determine potential barriers to quality care alongside effective training for clinicians is needed.Trial registration numberISRCTN06984617; Results.

Project description:Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real-world evidence for assessing device safety and tracking device-related patient outcomes over time. However, distilling this evidence remains challenging, as information is fractured across clinical notes and structured records. Modern machine learning methods for machine reading promise to unlock increasingly complex information from text, but face barriers due to their reliance on large and expensive hand-labeled training sets. To address these challenges, we developed and validated state-of-the-art deep learning methods that identify patient outcomes from clinical notes without requiring hand-labeled training data. Using hip replacements-one of the most common implantable devices-as a test case, our methods accurately extracted implant details and reports of complications and pain from electronic health records with up to 96.3% precision, 98.5% recall, and 97.4% F1, improved classification performance by 12.8-53.9% over rule-based methods, and detected over six times as many complication events compared to using structured data alone. Using these additional events to assess complication-free survivorship of different implant systems, we found significant variation between implants, including for risk of revision surgery, which could not be detected using coded data alone. Patients with revision surgeries had more hip pain mentions in the post-hip replacement, pre-revision period compared to patients with no evidence of revision surgery (mean hip pain mentions 4.97 vs. 3.23; t?=?5.14; p?<?0.001). Some implant models were associated with higher or lower rates of hip pain mentions. Our methods complement existing surveillance mechanisms by requiring orders of magnitude less hand-labeled training data, offering a scalable solution for national medical device surveillance using electronic health records.

Project description:ImportanceRecent reports on waning of COVID-19 vaccine-induced immunity have led to the approval and rollout of additional doses and booster vaccinations. Individuals at increased risk of SARS-CoV-2 infection are receiving additional vaccine doses in addition to the regimen that was tested in clinical trials. Risks and adverse event profiles associated with additional vaccine doses are currently not well understood.ObjectiveTo evaluate the safety of third-dose vaccination with US Food and Drug Administration (FDA)-approved COVID-19 mRNA vaccines.Design, setting, and participantsThis cohort study was conducted using electronic health record (EHR) data from December 2020 to October 2021 from the multistate Mayo Clinic Enterprise. Participants included all 47 999 individuals receiving 3-dose COVID-19 mRNA vaccines within the study setting who met study inclusion criteria. Participants were divided into 2 cohorts by vaccine brand administered and served as their own control groups, with no comparison made between cohorts. Data were analyzed from September through November 2021.ExposuresThree doses of an FDA-authorized COVID-19 mRNA vaccine, BNT162b2 or mRNA-1273.Main outcomes and measuresVaccine-associated adverse events were assessed via EHR report. Adverse event risk was quantified using the percentage of study participants who reported the adverse event within 14 days after each vaccine dose and during a 14-day control period, immediately preceding the first vaccine dose.ResultsAmong 47 999 individuals who received 3-dose COVID-19 mRNA vaccines, 38 094 individuals (21 835 [57.3%] women; median [IQR] age, 67.4 [52.5-76.5] years) received BNT162b2 (79.4%) and 9905 individuals (5099 [51.5%] women; median [IQR] age, 67.7 [59.5-73.9] years) received mRNA-1273 (20.6%). Reporting of severe adverse events remained low after the third vaccine dose, with rates of pericarditis (0.01%; 95% CI, 0%-0.02%), anaphylaxis (0%; 95% CI, 0%-0.01%), myocarditis (0%; 95% CI, 0%-0.01%), and cerebral venous sinus thrombosis (no individuals) consistent with results from earlier studies. Significantly more individuals reported low-severity adverse events after the third dose compared with after the second dose, including fatigue (2360 individuals [4.92%] vs 1665 individuals [3.47%]; P < .001), lymphadenopathy (1387 individuals [2.89%] vs 995 individuals [2.07%]; P < .001), nausea (1259 individuals [2.62%] vs 979 individuals [2.04%]; P < .001), headache (1185 individuals [2.47%] vs 992 individuals [2.07%]; P < .001), arthralgia (1019 individuals [2.12%] vs 816 individuals [1.70%]; P < .001), myalgia (956 individuals [1.99%] vs 784 individuals [1.63%]; P < .001), diarrhea (817 individuals [1.70%] vs 595 individuals [1.24%]; P < .001), fever (533 individuals [1.11%] vs 391 individuals [0.81%]; P < .001), vomiting (528 individuals [1.10%] vs 385 individuals [0.80%]; P < .001), and chills (224 individuals [0.47%] vs 175 individuals [0.36%]; P = .01).Conclusions and relevanceThis study found that although third-dose vaccination against SARS-CoV-2 infection was associated with increased reporting of low-severity adverse events, risk of severe adverse events remained comparable with risk associated with the standard 2-dose regime. These findings suggest the safety of third vaccination doses in individuals who were eligible for booster vaccination at the time of this study.

Dataset Information

Primary Care Medication Safety Surveillance with Integrated Primary and Secondary Care Electronic Health Records: A Cross-Sectional Study.

Introduction

Objective

Methods

Results

Conclusions

Publications

Primary Care Medication Safety Surveillance with Integrated Primary and Secondary Care Electronic Health Records: A Cross-Sectional Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets