125 research outputs found

    J Addict Med

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    IntroductionDespite inconclusive evidence that prescription drug monitoring programs (PDMP) reduce opioid-related mortality, guidelines recommend PDMP review with opioid prescribing. Some reported barriers to use include time-consuming processes to obtain data and workflow disruptions.MethodsWe provided access to a PMDP-electronic health record (EHR) integrated program to 123 clinicians in one healthcare system. Remaining clinicians within the healthcare system and metropolitan area did not receive PDMP-EHR integration program access. We identified changes in opioid prescribing by linking prescription data available in the state PMDP database to individual clinicians. The primary outcome was change in receipt of high dose opioid prescriptions (>90 milligram morphine equivalents) by Colorado residents before and after program integration. Secondary outcomes included changes in long-acting opioid receipt and overlapping opioid and benzodiazepine prescription days. Next, we surveyed clinicians to assess their perspectives on PDMP data acquisition before and after PDMP-EHR integration program access.ResultsHigh-dose opioid receipt decreased significantly across all three clinician groups (PDMP-EHR integration program access [27.6%, to 6.9%, p < 0.001]; no program access in the same healthcare system [4.8% to 2.9%, p < 0.001], and no program access across the metropolitan area [13.5% to 6.1%, p < 0.001]). Clinicians reported improved access to PDMP data using the PDMP-EHR integrated program compared to the state PDMP website (98.6%).ConclusionsFurther study of PDMP-EHR integration programs on patient and clinician outcomes may illuminate the role of this technology in public health and in clinical practice.K08 DA049905/DA/NIDA NIH HHSUnited States/U17 CE002719/CE/NCIPC CDC HHSUnited States

    Health Information Technology in the United States, 2008

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    Provides updated survey data on health information technology (HIT) and electronic health records adoption, with a focus on providers serving vulnerable populations. Examines assessments of HIT's effect on the cost and quality of care and emerging issues

    Electronic health records in ambulances: the ERA multiple-methods study

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    Background: Ambulance services have a vital role in the shift towards the delivery of health care outside hospitals, when this is better for patients, by offering alternatives to transfer to the emergency department. The introduction of information technology in ambulance services to electronically capture, interpret, store and transfer patient data can support out-of-hospital care. Objective: We aimed to understand how electronic health records can be most effectively implemented in a pre-hospital context in order to support a safe and effective shift from acute to community-based care, and how their potential benefits can be maximised. Design and setting: We carried out a study using multiple methods and with four work packages: (1) a rapid literature review; (2) a telephone survey of all 13 freestanding UK ambulance services; (3) detailed case studies examining electronic health record use through qualitative methods and analysis of routine data in four selected sites consisting of UK ambulance services and their associated health economies; and (4) a knowledge-sharing workshop. Results: We found limited literature on electronic health records. Only half of the UK ambulance services had electronic health records in use at the time of data collection, with considerable variation in hardware and software and some reversion to use of paper records as services transitioned between systems. The case studies found that the ambulance services’ electronic health records were in a state of change. Not all patient contacts resulted in the generation of electronic health records. Ambulance clinicians were dealing with partial or unclear information, which may not fit comfortably with the electronic health records. Ambulance clinicians continued to use indirect data input approaches (such as first writing on a glove) even when using electronic health records. The primary function of electronic health records in all services seemed to be as a store for patient data. There was, as yet, limited evidence of electronic health records’ full potential being realised to transfer information, support decision-making or change patient care. Limitations: Limitations included the difficulty of obtaining sets of matching routine data for analysis, difficulties of attributing any change in practice to electronic health records within a complex system and the rapidly changing environment, which means that some of our observations may no longer reflect reality. Conclusions: Realising all the benefits of electronic health records requires engagement with other parts of the local health economy and dealing with variations between providers and the challenges of interoperability. Clinicians and data managers, and those working in different parts of the health economy, are likely to want very different things from a data set and need to be presented with only the information that they need

    Embedded Pharmacists in Primary Care

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    As healthcare delivery moves from a provider-centric approach to a more patient-centric approach, systems and payers need to reimagine how care and team-based care is delivered to patients and reimbursed. Thus, the goal should be to see the right patient, by the right provider, in the right place, for the right price, and where appropriate, with the use of the right pharmaceutical(s) – “5 P’s”. There continues to be a reduction in physicians that are pursuing primary care roles in the United States, thus exacerbating the ability to meet patient demand. Most patient encounters begin with or end with the prescribing of medication. Thus, a future where pharmacists are embedded in primary care settings allows these pharmacists to collaborate at the point-of-prescribing (i.e., in-clinic) and provides tremendous benefits to providers and patients. The pharmacist workforce is educated at the doctoral level, yet vastly underutilized and can assist in a collaborative approach in primary care. The collection of articles in the Special Issue “Embedded Pharmacists in Primary Care” highlight examples of models that have included pharmacists in the ambulatory setting providing services in chronic disease management, comprehensive medication management, and care of specific conditions such as diabetes

    From Programme Theory to Logic Models for Multispecialty Community Providers: A Realist Evidence Synthesis

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    Background: The NHS policy of constructing multispecialty community providers (MCPs) rests on a complex set of assumptions about how health systems can replace hospital use with enhanced primary care for people with complex, chronic or multiple health problems, while contributing savings to health-care budgets. Objectives: To use policy-makers’ assumptions to elicit an initial programme theory (IPT) of how MCPs can achieve their outcomes and to compare this with published secondary evidence and revise the programme theory accordingly. Design: Realist synthesis with a three-stage method: (1) for policy documents, elicit the IPT underlying the MCP policy, (2) review and synthesise secondary evidence relevant to those assumptions and (3) compare the programme theory with the secondary evidence and, when necessary, reformulate the programme theory in a more evidence-based way. Data sources: Systematic searches and data extraction using (1) the Health Management Information Consortium (HMIC) database for policy statements and (2) topically appropriate databases, including MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Applied Social Sciences Index and Abstracts (ASSIA). A total of 1319 titles and abstracts were reviewed in two rounds and 116 were selected for full-text data extraction. We extracted data using a formal data extraction tool and synthesised them using a framework reflecting the main policy assumptions. Results: The IPT of MCPs contained 28 interconnected context–mechanism–outcome relationships. Few policy statements specified what contexts the policy mechanisms required. We found strong evidence supporting the IPT assumptions concerning organisational culture, interorganisational network management, multidisciplinary teams (MDTs), the uses and effects of health information technology (HIT) in MCP-like settings, planned referral networks, care planning for individual patients and the diversion of patients from inpatient to primary care. The evidence was weaker, or mixed (supporting some of the constituent assumptions but not others), concerning voluntary sector involvement, the effects of preventative care on hospital admissions and patient experience, planned referral networks and demand management systems. The evidence about the effects of referral reductions on costs was equivocal. We found no studies confirming that the development of preventative care would reduce demands on inpatient services. The IPT had overlooked certain mechanisms relevant to MCPs, mostly concerning MDTs and the uses of HITs. Limitations: The studies reviewed were limited to Organisation for Economic Co-operation and Development countries and, because of the large amount of published material, the period 2014–16, assuming that later studies, especially systematic reviews, already include important earlier findings. No empirical studies of MCPs yet existed. Conclusions: Multidisciplinary teams are a central mechanism by which MCPs (and equivalent networks and organisations) work, provided that the teams include the relevant professions (hence, organisations) and, for care planning, individual patients. Further primary research would be required to test elements of the revised logic model, in particular about (1) how MDTs and enhanced general practice compare and interact, or can be combined, in managing referral networks and (2) under what circumstances diverting patients from in-patient to primary care reduces NHS costs and improves the quality of patient experience

    Personalised antimicrobial management in secondary care

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    Background: The growing threat of Antimicrobial Resistance (AMR) requires innovative methods to promote the sustainable effectiveness of antimicrobial agents. Hypothesis: This thesis aimed to explore the hypothesis that personalised decision support interventions have the utility to enhance antimicrobial management across secondary care. Methods: Different research methods were used to investigate this hypothesis. Individual physician decision making was mapped and patient experiences of engagement with decision making explored using semi-structured interviews. Cross-specialty engagement with antimicrobial management was investigated through cross-sectional analysis of conference abstracts and educational training curricula. Artificial intelligence tools were developed to explore their ability to predict the likelihood of infection and provide individualised prescribing recommendations using routine patient data. Dynamic, individualised dose optimisation was explored through: (i) development of a microneedle based, electrochemical biosensor for minimally invasive monitoring of beta-lactams; and (ii) pharmacokinetic (PK)-pharmacodynamic (PD) modelling of a new PK-PD index using C-Reactive protein (CRP) to predict the pharmacodynamics of vancomycin. Ethics approval was granted for all aspects of work explored within this thesis. Results: Mapping of individual physician decision making during infection management demonstrated several areas where personalised, technological interventions could enhance antimicrobial management. At specialty level, non-infection specialties have little engagement with antimicrobial management. The importance of engaging surgical specialties, who have relatively high rates of antimicrobial usage and healthcare associated infections, was observed. An individualised information leaflet, co-designed with patients, to provide personalised infection information to in-patients receiving antibiotics significantly improved knowledge and reported engagement with decision making. Artificial intelligence was able to enhance the prediction of infection and the prescribing of antimicrobials using routinely available clinical data. Real-time, continuous penicillin monitoring was demonstrated using a microneedle based electrochemical sensor in-vivo. A new PK-PD index, using C-Reactive Protein, was able to predict individual patient response to vancomycin therapy at 96-120 hours of therapy. Conclusion: Through co-design and the application of specific technologies it is possible to provide personalised antimicrobial management within secondary care.Open Acces
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