Cost-effectiveness analysis of a hospital electronic medication management system

Objective To conduct a cost–effectiveness analysis of a hospital electronic medication management system (eMMS).Methods We compared costs and benefits of paper-based prescribing with a commercial eMMS (CSC MedChart) on one cardiology ward in a major 326-bed teaching hospital, assuming a 15-year time horizon and a health system perspective. The eMMS implementation and operating costs were obtained from the study site. We used data on eMMS effectiveness in reducing potential adverse drug events (ADEs), and potential ADEs intercepted, based on review of 1 202 patient charts before (n = 801) and after (n = 401) eMMS. These were combined with published estimates of actual ADEs and their costs.Results The rate of potential ADEs following eMMS fell from 0.17 per admission to 0.05; a reduction of 71%. The annualized eMMS implementation, maintenance, and operating costs for the cardiology ward were A$61 741 (US$55 296). The estimated reduction in ADEs post eMMS was approximately 80 actual ADEs per year. The reduced costs associated with these ADEs were more than sufficient to offset the costs of the eMMS. Estimated savings resulting from eMMS implementation were A$63–66 (US$56–59) per admission (A$97 740–$102 000 per annum for this ward). Sensitivity analyses demonstrated results were robust when both eMMS effectiveness and costs of actual ADEs were varied substantially.Conclusion The eMMS within this setting was more effective and less expensive than paper-based prescribing. Comparison with the few previous full economic evaluations available suggests a marked improvement in the cost–effectiveness of eMMS, largely driven by increased effectiveness of contemporary eMMs in reducing medication errors.     

Effectiveness of Evidence-based Pneumonia CPOE Order Sets Measured by Health Outcomes

Objective

Evidence-based sets of medical orders for the treatment of patients with common conditions have the potential to induce greater efficiency and convenience across the system, along with more consistent health outcomes. Despite ongoing utilization of order sets, quantitative evidence of their effectiveness is lacking. In this study, conducted at Advocate Health Care in Illinois, we quantitatively analyzed the benefits of community acquired pneumonia order sets as measured by mortality, readmission, and length of stay (LOS) outcomes.

Methods

In this study, we examined five years (2007–2011) of computerized physician order entry (CPOE) data from two city and two suburban community care hospitals. Mortality and readmissions benefits were analyzed by comparing “order set” and “no order set” groups of adult patients using logistic regression, Pearson’s chi-squared, and Fisher’s exact methods. LOS was calculated by applying one-way ANOVA and the Mann-Whitney U test, supplemented by analysis of comorbidity via the Charlson Comorbidity Index.

Results

The results indicate that patient treatment orders placed via electronic sets were effective in reducing mortality [OR=1.787; 95% CF 1.170-2.730; P=.061], readmissions [OR=1.362; 95% CF 1.015-1.827; P=.039], and LOS [F (1,5087)=6.885, P=.009, 4.79 days (no order set group) vs. 4.32 days (order set group)].

Conclusion

Evidence-based ordering practices have the potential to improve pneumonia outcomes through reduction of mortality, hospital readmissions, and cost of care. However, the practice must be part of a larger strategic effort to reduce variability in patient care processes. Further experimental and/or observational studies are required to reduce the barriers to retrospective patient care analyses.     

Mobile and Fixed Computer Use by Doctors and Nurses on Hospital Wards: Multi-method Study on the Relationships Between Clinician Role,Clinical Task,and Device Choice

Background

Selecting the right mix of stationary and mobile computing devices is a significant challenge for system planners and implementers. There is very limited research evidence upon which to base such decisions.

Objective

We aimed to investigate the relationships between clinician role, clinical task, and selection of a computer hardware device in hospital wards.

Methods

Twenty-seven nurses and eight doctors were observed for a total of 80 hours as they used a range of computing devices to access a computerized provider order entry system on two wards at a major Sydney teaching hospital. Observers used a checklist to record the clinical tasks completed, devices used, and location of the activities. Field notes were also documented during observations. Semi-structured interviews were conducted after observation sessions. Assessment of the physical attributes of three devices—stationary PCs, computers on wheels (COWs) and tablet PCs—was made. Two types of COWs were available on the wards: generic COWs (laptops mounted on trolleys) and ergonomic COWs (an integrated computer and cart device). Heuristic evaluation of the user interfaces was also carried out.

Results

The majority (93.1%) of observed nursing tasks were conducted using generic COWs. Most nursing tasks were performed in patients’ rooms (57%) or in the corridors (36%), with a small percentage at a patient’s bedside (5%). Most nursing tasks related to the preparation and administration of drugs. Doctors on ward rounds conducted 57.3% of observed clinical tasks on generic COWs and 35.9% on tablet PCs. On rounds, 56% of doctors’ tasks were performed in the corridors, 29% in patients’ rooms, and 3% at the bedside. Doctors not on a ward round conducted 93.6% of tasks using stationary PCs, most often within the doctors’ office. Nurses and doctors were observed performing workarounds, such as transcribing medication orders from the computer to paper.

Conclusions

The choice of device was related to clinical role, nature of the clinical task, degree of mobility required, including where task completion occurs, and device design. Nurses’ work, and clinical tasks performed by doctors during ward rounds, require highly mobile computer devices. Nurses and doctors on ward rounds showed a strong preference for generic COWs over all other devices. Tablet PCs were selected by doctors for only a small proportion of clinical tasks. Even when using mobile devices clinicians completed a very low proportion of observed tasks at the bedside. The design of the devices and ward space configurations place limitations on how and where devices are used and on the mobility of clinical work. In such circumstances, clinicians will initiate workarounds to compensate. In selecting hardware devices, consideration should be given to who will be using the devices, the nature of their work, and the physical layout of the ward.     

Response to Medication Dosing Alerts for Pediatric Inpatients Using a Computerized Provider Order Entry System

Objective

Medication dosing errors are of particular concern in hospitalized children. Avoidance of such errors is essential to quality improvement and patient safety. Computerized provider order entry (CPOE) systems with clinical decision support (CDS) have the potential to reduce medication errors. The objective of this study was to evaluate provider response to the dosing alerts in a CPOE system with CDS for pediatric inpatients and to identify differences in provider response based on clinician specialty.

Patients and methods

We conducted a retrospective analysis of all medication dosing alerts over a 1-year period (January 1 through December 31, 2008) for all pediatric inpatients at Hospital for Special Surgery. Alerts were analyzed with respect to medication dosing, prescriber, and action taken by the prescriber after the alert was triggered (i.e., accepted suggested change, ignored recommendation/overrode, or cancelled the order).

Results

During the study period, 18,163 medication orders were placed and 1,024 dosing alerts were fired. Overdosing of medications accounted for 91% of the alerts and underdosing 9%. The pediatric-trained providers ignored more alerts and cancelled fewer orders than the non-pediatric-trained providers (p<0.001). Both groups changed the order similarly based on CDS recommendations.

Conclusions

Differences in response to CDS were found between pediatric-trained and non-pediatric-trained providers caring for pediatric patients; however, both groups changed orders based on CDS similarly. CPOE with built-in CDS may be of particular value when providers with different specialties and types of training are caring for pediatric patients.     

Interaction Time with Electronic Health Records: A Systematic Review

Background  The amount of time that health care clinicians (physicians and nurses) spend interacting with the electronic health record is not well understood. Objective  This study aimed to evaluate the time that health care providers spend interacting with electronic health records (EHR). Methods  Data are retrieved from Ovid MEDLINE(R) and Epub Ahead of Print, In-Process and Other Non-Indexed Citations and Daily, (Ovid) Embase, CINAHL, and SCOPUS. Study Eligibility Criteria  Peer-reviewed studies that describe the use of EHR and include measurement of time either in hours, minutes, or in the percentage of a clinician''s workday. Papers were written in English and published between 1990 and 2021. Participants  All physicians and nurses involved in inpatient and outpatient settings. Study Appraisal and Synthesis Methods  A narrative synthesis of the results, providing summaries of interaction time with EHR. The studies were rated according to Quality Assessment Tool for Studies with Diverse Designs. Results  Out of 5,133 de-duplicated references identified through database searching, 18 met inclusion criteria. Most were time-motion studies (50%) that followed by logged-based analysis (44%). Most were conducted in the United States (94%) and examined a clinician workflow in the inpatient settings (83%). The average time was nearly 37% of time of their workday by physicians in both inpatient and outpatient settings and 22% of the workday by nurses in inpatient settings. The studies showed methodological heterogeneity. Conclusion  This systematic review evaluates the time that health care providers spend interacting with EHR. Interaction time with EHR varies depending on clinicians'' roles and clinical settings, computer systems, and users'' experience. The average time spent by physicians on EHR exceeded one-third of their workday. The finding is a possible indicator that the EHR has room for usability, functionality improvement, and workflow optimization.     

Research and applications: The safety of electronic prescribing: manifestations,mechanisms, and rates of system-related errors associated with two commercial systems in hospitals

Objectives

To compare the manifestations, mechanisms, and rates of system-related errors associated with two electronic prescribing systems (e-PS). To determine if the rate of system-related prescribing errors is greater than the rate of errors prevented.

Methods

Audit of 629 inpatient admissions at two hospitals in Sydney, Australia using the CSC MedChart and Cerner Millennium e-PS. System related errors were classified by manifestation (eg, wrong dose), mechanism, and severity. A mechanism typology comprised errors made: selecting items from drop-down menus; constructing orders; editing orders; or failing to complete new e-PS tasks. Proportions and rates of errors by manifestation, mechanism, and e-PS were calculated.

Results

42.4% (n=493) of 1164 prescribing errors were system-related (78/100 admissions). This result did not differ by e-PS (MedChart 42.6% (95% CI 39.1 to 46.1); Cerner 41.9% (37.1 to 46.8)). For 13.4% (n=66) of system-related errors there was evidence that the error was detected prior to study audit. 27.4% (n=135) of system-related errors manifested as timing errors and 22.5% (n=111) wrong drug strength errors. Selection errors accounted for 43.4% (34.2/100 admissions), editing errors 21.1% (16.5/100 admissions), and failure to complete new e-PS tasks 32.0% (32.0/100 admissions). MedChart generated more selection errors (OR=4.17; p=0.00002) but fewer new task failures (OR=0.37; p=0.003) relative to the Cerner e-PS. The two systems prevented significantly more errors than they generated (220/100 admissions (95% CI 180 to 261) vs 78 (95% CI 66 to 91)).

Conclusions

System-related errors are frequent, yet few are detected. e-PS require new tasks of prescribers, creating additional cognitive load and error opportunities. Dual classification, by manifestation and mechanism, allowed identification of design features which increase risk and potential solutions. e-PS designs with fewer drop-down menu selections may reduce error risk.     

计算机化医生医嘱录入系统对医护合作性沟通的影响研究

在介绍计算机化医生医嘱录入系统(CPOE)以及医护合作性沟通的基础上,结合中国知网(CNKI)和PubMed数据库的相关文献进行回顾研究。从CPOE的影响及医护沟通自身组织模式的影响两方面进行分析,结果表明CPOE的引入对医护合作沟通的影响是多方面的,不能单纯评论其利弊。     

The impact of computerized physician medication order entry in hospitalized patients--a systematic review

OBJECTIVE: To identify all published studies evaluating computerized physician order entry (CPOE) in the inpatient setting and uniformly classify these studies on outcome measure and study design. DATA SOURCES: All studies that evaluated the effect of CPOE on outcomes pertaining to the medication process in inpatients were electronically searched in MEDLINE (1966 to August 2006), EMBASE (1980 to August 2006) and the Cochrane library. In addition, the bibliographies of retrieved articles were manually searched. Articles were selected if one of their main objectives was CPOE evaluation in an inpatient setting. REVIEW METHOD: Identified titles and abstracts were independently screened by three reviewers to determine eligibility for further review. RESULTS: We found 67 articles, which included articles on CPOE evaluation on some outcome at the time of ordering. Most papers evaluated multiple outcome measures. The outcome measures were clustered in the following categories: adherence (n=22); alerts and appropriateness of alerts (n=7); safety (n=21); time (n=7); costs and (organizational) efficiency (n=23); and satisfaction, usage and usability (n=10). Most studies used a before-after design (n=35) followed by observational studies (n=24) and randomized controlled trials (n=8). CONCLUSION: The impact of CPOE systems was especially positive in the category adherence to guidelines, but also to some extent in alerts and appropriateness of alerts; costs and organizational efficiency; and satisfaction and usability. Although on average, there seems to be a positive effect of CPOE on safety, studies tended to be non-randomized and were focused on medication error rates, not powered to detect a difference in adverse drug event rates. Some recent studies suggested that errors, adverse drug events (ADEs) and even mortality increased after CPOE implementation. Only in the category time the impact has been shown to be negative, but this only refers to the physician's time, not the net time. Except for safety, on the whole spectrum of outcomes, results of RCT studies were in line with non-RCT study results.