E-prescribing: clinical implications for patients with diabetes

Using Technology to Improve Diabetes Care in Hospital: The Challenge and the Opportunity

The past 10 years have seen a revolution in technology improving the lives of people with diabetes. This has implications for diabetes care in hospitalized inpatients. These technological developments have the potential to significantly improve the care of people with diabetes in hospital. Combining point of care glucose monitoring, electronic prescribing, electronic observations with electronic referral, and electronic health records allow teams to daily oversee the whole hospital population. To make the most of these tools as well as developing the use of pumps and glucose sensors in hospital, the diabetes team needs to work in new ways. To date, very little work has described how these should be combined. We describe how this technology can be combined to improve diabetes care in hospital.

The Challenges of Electronic Health Records and Diabetes Electronic Prescribing: Implications for Safety Net Care for Diverse Populations

Widespread electronic health record (EHR) implementation creates new challenges in the diabetes care of complex and diverse populations, including safe medication prescribing for patients with limited health literacy and limited English proficiency. This review highlights how the EHR electronic prescribing transformation has affected diabetes care for vulnerable patients and offers recommendations for improving patient safety through EHR electronic prescribing design, implementation, policy, and research. Specifically, we present evidence for (1) the adoption of RxNorm; (2) standardized naming and picklist options for high alert medications such as insulin; (3) the widespread implementation of universal medication schedule and language-concordant labels, with the expansion of electronic prescription 140-character limit; (4) enhanced bidirectional communication with pharmacy partners; and (5) informatics and implementation research in safety net healthcare systems to examine how EHR tools and practices affect diverse vulnerable populations.

Clinical Psychopharmacology Update: What's in a Name? Confusion Prompts Change for Vortioxetine's Brand Name

Similar names between two unrelated drugs have led the FDA to issue warnings about and now approve a name change for vortioxetine, which was branded as Brintellix® until recently. While the trade name had been screened prior to the product's launch, the FDA received numerous reports of prescribing and dispensing errors, specifically with regard to the anti-coagulant drug Brilinta® (ticagrelor). Starting 1 June 2016, vortioxetine will be marketed under the name Trintellix™ in an effort to reduce confusion. Clinicians are advised that while the name and National Drug Code number with this product will change, it will retain the same formulation, indication, and dosage information. To the extent possible, clinicians can and should take actions to identify and reduce potential medication errors in prescriptions, especially when using electronic records and e-prescription systems.

The eClinical Care Pathway Framework: a novel structure for creation of online complex clinical care pathways and its application in the management of sexually transmitted infections

BACKGROUND

Despite considerable international eHealth impetus, there is no guidance on the development of online clinical care pathways. Advances in diagnostics now enable self-testing with home diagnosis, to which comprehensive online clinical care could be linked, facilitating completely self-directed, remote care. We describe a new framework for developing complex online clinical care pathways and its application to clinical management of people with genital chlamydia infection, the commonest sexually transmitted infection (STI) in England.

METHODS

Using the existing evidence-base, guidelines and examples from contemporary clinical practice, we developed the eClinical Care Pathway Framework, a nine-step iterative process. Step 1: define the aims of the online pathway; Step 2: define the functional units; Step 3: draft the clinical consultation; Step 4: expert review; Step 5: cognitive testing; Step 6: user-centred interface testing; Step 7: specification development; Step 8: software testing, usability testing and further comprehension testing; Step 9: piloting. We then applied the Framework to create a chlamydia online clinical care pathway (Online Chlamydia Pathway).

RESULTS

Use of the Framework elucidated content and structure of the care pathway and identified the need for significant changes in sequences of care (Traditional: history, diagnosis, information versus Online: diagnosis, information, history) and prescribing safety assessment. The Framework met the needs of complex STI management and enabled development of a multi-faceted, fully-automated consultation.

CONCLUSION

The Framework provides a comprehensive structure on which complex online care pathways such as those needed for STI management, which involve clinical services, public health surveillance functions and third party (sexual partner) management, can be developed to meet national clinical and public health standards. The Online Chlamydia Pathway's standardised method of collecting data on demographics and sexual behaviour, with potential for interoperability with surveillance systems, could be a powerful tool for public health and clinical management.

Temporal patterns of hypoglycaemia and burden of sulfonylurea-related hypoglycaemia in UK hospitals: a retrospective multicentre audit of hospitalised patients with diabetes

OBJECTIVES

To determine whether temporal patterns of hypoglycaemia exist in inpatients with diabetes 'at risk' of hypoglycaemia (those on insulin and/or sulfonylureas), and if so whether patterns differ between hospitals and between these treatments.

SETTING

Retrospective multicentre audit of inpatients with diabetes involving 11 acute UK National Health Service (NHS) trusts.

PARTICIPANTS

Capillary blood glucose readings of 3.9 mmol/L or less (hypoglycaemia) for all adult (≥18 years) inpatients with diabetes 'at risk' of hypoglycaemia were extracted from the Abbott PrecisionWeb Point-of-Care Data Management System over a 4-week period. Overall, 2521 readings of 3.9 mmol/L or less (hypoglycaemia) occurring in 866 participants between 1 June 2013 and 29 June 2013 were analysed.

RESULTS

The majority (65%) occurred between 21:00 and 08:59, a pattern common to all Trusts. This was more frequent in sulfonylurea-treated than insulin-treated participants (75.3% vs 59.3%, p=0.0001). Furthermore, hypoglycaemic readings were more frequent between 5:00 and 7:59 in sulfonylurea-treated than insulin-treated participants (46.7% vs 22.7% of readings for respective treatments, p=0.0001). Sulfonylureas accounted for 31.8% of all hypoglycaemic readings. As a group, sulfonylurea-treated participants were older (median age 78 vs 73 years, p=0.0001) and had lower glycated haemoglobin (median 56 (7.3%) vs 69 mmol/mol (8.5%), p=0.0001). Hypoglycaemic readings per participant were as frequent for sulfonylurea-treated participants as for insulin-treated participants (median=2 for both) as were the proportions in each group with ≥5 hypoglycaemic readings (17.3% vs 17.7%).

CONCLUSIONS

In all Trusts, hypoglycaemic readings were more frequent between 21:00 and 08:59 in 'at risk' inpatients with diabetes, with a greater frequency in the early morning period (5:00-7:59) in sulfonylurea-treated inpatients. This may have implications for the continuing use of sulfonylureas in the inpatient setting.

An internal performance assessment of CancerGene Connect: an electronic tool to streamline, measure and improve the genetic counseling process

CancerGene Connect (CGC) is a web-based program that combines the collection of family and medical history, cancer risk assessment, psychosocial assessment, report templates, a result tracking system, and a patient follow up system. The performance of CGC was assessed in several ways: pre-appointment completion data analyzed for demographic and health variables; a time study to assess overall time per case and to compare the data entry by the genetic counselor compared to the patient, and a measured quality assessment of the program via observation and interview of patients. Prior to their appointment, 52.3% of 2,414 patients completed the online patient questionnaire section of CGC. There were significant differences in completion rates among racial and ethnic groups. County hospital patients were less likely to complete the questionnaire than insured patients (p < 0.0001); and likewise uninsured patients and patients with Medicare/Medicaid were less likely to complete the questionnaire than private patients (p < 0.0001). The average genetic counseling time per case was 82 min, with no significant differences whether the counselor or the patient completed CGC. CGC reduces genetic counselor time by approximately 14-46% compared to average time per case using traditional risk assessment and documentation methods previously reported. All surveyed users felt the questionnaire was easy to understand. CGC is an effective tool that streamlines workflow, and provides a standardized data collection tool that can be used to evaluate and improve the genetic counseling process.

E-prescribing errors in community pharmacies: exploring consequences and contributing factors

OBJECTIVE

To explore types of e-prescribing errors in community pharmacies and their potential consequences, as well as the factors that contribute to e-prescribing errors.

METHODS

Data collection involved performing 45 total hours of direct observations in five pharmacies. Follow-up interviews were conducted with 20 study participants. Transcripts from observations and interviews were subjected to content analysis using NVivo 10.

RESULTS

Pharmacy staff detected 75 e-prescription errors during the 45 h observation in pharmacies. The most common e-prescribing errors were wrong drug quantity, wrong dosing directions, wrong duration of therapy, and wrong dosage formulation. Participants estimated that 5 in 100 e-prescriptions have errors. Drug classes that were implicated in e-prescribing errors were antiinfectives, inhalers, ophthalmic, and topical agents. The potential consequences of e-prescribing errors included increased likelihood of the patient receiving incorrect drug therapy, poor disease management for patients, additional work for pharmacy personnel, increased cost for pharmacies and patients, and frustrations for patients and pharmacy staff. Factors that contribute to errors included: technology incompatibility between pharmacy and clinic systems, technology design issues such as use of auto-populate features and dropdown menus, and inadvertently entering incorrect information.

CONCLUSION

Study findings suggest that a wide range of e-prescribing errors is encountered in community pharmacies. Pharmacists and technicians perceive that causes of e-prescribing errors are multidisciplinary and multifactorial, that is to say e-prescribing errors can originate from technology used in prescriber offices and pharmacies.

Capture and documentation of coded data on adverse drug reactions: an overview

Allergic responses to prescription drugs are largely preventable, and incur significant cost to the community both financially and in terms of healthcare outcomes. The capacity to minimise the effects of repeated events rests predominantly with the reliability of allergy documentation in medical records and computerised physician order entry systems (CPOES) with decision support such as allergy alerts. This paper presents an overview of the nature and extent of adverse drug reactions (ADRs) in Australia and other developed countries, a discussion and evaluation of strategies which have been devised to address this issue, and a commentary on the role of coded data in informing this patient safety issue. It is not concerned with pharmacovigilance systems that monitor ADRs on a global scale. There are conflicting reports regarding the efficacy of these strategies. Although in many cases allergy alerts are effective, lack of sensitivity and contextual relevance can often induce doctors to override alerts. Human factors such as user fatigue and inadequate adverse drug event reporting, including ADRs, are commonplace. The quality of and response to allergy documentation can be enhanced by the participation of nurses and pharmacists, particularly in medication reconciliation. The International Classification of Diseases (ICD) coding of drug allergies potentially yields valuable evidence, but the quality of local and national level coded data is hampered by under-documenting and under-coding.

E-prescribing: a focused review and new approach to addressing safety in pharmacies and primary care

E-prescribing, the health information technology (HIT) that enables prescribers to electronically transmit prescriptions to community pharmacies, has been touted as a solution for improving patient safety and overall quality of care. However, the impact of HIT, such as e-prescribing on medication errors in acute care settings, has been widely studied and shows that if poorly designed or implemented, HIT can pose a risk to patient safety by introducing a source of medication errors. Unlike acute care settings, safety issues related to e-prescribing in primary care settings (where e-prescriptions are generated and transmitted) and pharmacies (where e-prescriptions are received) have not received as much attention in the literature. This paper provides a focused review of patient safety issues related to using e-prescribing systems in primary care and pharmacies. In addition, the paper proposes using human factors engineering concepts to study e-prescribing safety in pharmacies and primary care settings to identify safety problems and possible mechanisms for improvement.

Beyond the basics: refills by electronic prescribing

INTRODUCTION

E-prescribing is part of a new generation of electronic solutions for the medical industry that may have great potential for improving work flow and communication between medical practices and pharmacies. In the US, it has been introduced with minimal monitoring of errors and general usability. This paper examines refill functionality in e-prescribing software.

METHODS

A mixed method study including focus groups and surveys was conducted. Qualitative data were collected in on-site focus groups or individual interviews with clinicians and medical office staff at 64 physician office practices. Focus group participants described their experiences with the refill functionality of e-prescribing software, provided suggestions for improving it, and suggested improvements in office procedures and software functionality.

RESULTS

Overall, approximately 50% reduction in time spent each day on refills was reported. Overall reports of refill functionality were positive; but clinicians and staff identified numerous difficulties and glitches associated managing prescription refills. These glitches diminished over time. Benefits included time saved as well as patient convenience. Potential for refilling without thought because of the ease of use was noted. Clinicians and staff appreciated the ability to track whether patients are filling and refilling prescriptions.

DISCUSSION

E-prescribing software for managing medication refills has not yet reached its full potential. To reduce work flow barriers and medication errors, software companies need to develop error reporting systems and response teams to deal effectively with problems experienced by users. Examining usability issues on both the medical office and pharmacy ends is required to identify the behavioral and cultural changes that accompany technological innovation and ease the transition to full use of e-prescribing software.