Computer alerts for potassium testing: resisting the temptation of a blanket approach.
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This article presents a critical review of the literature relating to medication compliance devices and the findings of a survey that examined the use of such devices by district nursing services. The UKCC (1992) does not regard the loading of compliance devices by nurses as safe practice; however, compliance devices continue to be used by district nurses. The evidence base concerning the value and use of medication compliance devices is examined and significant gaps in the literature relating to the use of such devices are identified. There is an absence of studies that focus on the effect of compliance devices on adherence among older patients and the nature and frequency of drug administration errors involving these devices. The survey findings show that nurse-loaded compliance devices are used in over one-third of the sample. Further research is necessary to assess the clinical effectiveness of, and clinical risk attached to, compliance devices for older patients in the community. It is suggested that this is an issue of serious concern for primary care groups considering the principles of clinical governance.
The Internet is not some passing fancy that you can safely ignore. It is rapidly becoming the way of doing business in a high-tech world. Don't get left behind.
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Healthcare systems in developed countries are experiencing severe financial stress as age demographics shift upward, leading to a larger percentage of older adults needing care. One way to potentially reduce or slow spiraling medical costs is to use technology, not only to cure sickness, but also to promote wellness throughout all stages of life, thereby avoiding or deferring expensive medical treatments. Ubiquitous computing and context-aware algorithms offer a new healthcare opportunity and a new set of research challenges: exploiting emerging consumer electronic devices to motivate healthy behavior as people age by presenting "just-in-time" information at points of decision and behavior.
OBJECTIVE: Suboptimal treatment of hyperlipidemia in patients with coronary artery disease (CAD) is well documented. We report the impact of a computer-assisted physician-directed intervention to improve secondary prevention of hyperlipidemia. DESIGN AND SETTING: Two hundred thirty-five patients under the care of 14 primary care physicians in an academically affiliated practice with an electronic health record were enrolled in this proof-of-concept physician-blinded randomized, controlled trial. Each patient with CAD or risk equivalent above National Cholesterol Education Program-recommended low-density lipoprotein (LDL) treatment goal for greater than 6 months was randomized, stratified by physician and baseline LDL. Physicians received a single e-mail per intervention patient. E-mails were visit independent, provided decision support, and facilitated "one-click" order writing. MEASUREMENTS: The primary outcomes were changes in hyperlipidemia prescriptions, time to prescription change, and changes in LDL levels. The time spent using the system was assessed among intervention patients. RESULTS: A greater proportion of intervention patients had prescription changes at 1 month (15.3% vs 2%, P=.001) and 1 year (24.6% vs 17.1%, P=.14). The median interval to first medication adjustment occurred earlier among intervention patients (0 vs 7.1 months, P=.005). Among patients with baseline LDLs >130 mg/dL, the first postintervention LDLs were substantially lower in the intervention group (119.0 vs 138.0 mg/dL, P=.04). Physician processing time was under 60 seconds per e-mail. CONCLUSION: A visit-independent disease management tool resulted in significant improvement in secondary prevention of hyperlipidemia at 1-month postintervention and showed a trend toward improvement at 1 year.
BACKGROUND: Computerized order entry systems have the potential to prevent medication errors and decrease adverse drug events with the use of clinical-decision support systems presenting alerts to providers. Despite the large volume of medications prescribed in the outpatient setting, few studies have assessed the impact of automated alerts on medication errors related to drug-laboratory interactions in an outpatient primary-care setting. METHODS AND FINDINGS: A primary-care clinic in an integrated safety net institution was the setting for the study. In collaboration with commercial information technology vendors, rules were developed to address a set of drug-laboratory interactions. All patients seen in the clinic during the study period were eligible for the intervention. As providers ordered medications on a computer, an alert was displayed if a relevant drug-laboratory interaction existed. Comparisons were made between baseline and postintervention time periods. Provider ordering behavior was monitored focusing on the number of medication orders not completed and the number of rule-associated laboratory test orders initiated after alert display. Adverse drug events were assessed by doing a random sample of chart reviews using the Naranjo scoring scale. The rule processed 16,291 times during the study period on all possible medication orders: 7,017 during the pre-intervention period and 9,274 during the postintervention period. During the postintervention period, an alert was displayed for 11.8% (1,093 out of 9,274) of the times the rule processed, with 5.6% for only "missing laboratory values," 6.0% for only "abnormal laboratory values," and 0.2% for both types of alerts. Focusing on 18 high-volume and high-risk medications revealed a significant increase in the percentage of time the provider stopped the ordering process and did not complete the medication order when an alert for an abnormal rule-associated laboratory result was displayed (5.6% vs. 10.9%, p = 0.03, Generalized Estimating Equations test). The provider also increased ordering of the rule-associated laboratory test when an alert was displayed (39% at baseline vs. 51% during post intervention, p < 0.001). There was a non-statistically significant difference towards less "definite" or "probable" adverse drug events defined by Naranjo scoring (10.3% at baseline vs. 4.3% during postintervention, p = 0.23). CONCLUSION: Providers will adhere to alerts and will use this information to improve patient care. Specifically, in response to drug-laboratory interaction alerts, providers will significantly increase the ordering of appropriate laboratory tests. There may be a concomitant change in adverse drug events that would require a larger study to confirm. Implementation of rules technology to prevent medication errors could be an effective tool for reducing medication errors in an outpatient setting.
BACKGROUND: Immunization rates have improved in the United States, but are still far from the national 90% goal for the year 2000. There is scant evidence about the effectiveness and costs of automated telephone messages to improve immunization rates among privately insured children. OBJECTIVE: To evaluate the effectiveness and cost-effectiveness of sending letters, automated telephone messages, or both to families of underimmunized 20-month-olds in a health maintenance organization (HMO). METHODS: In this randomized trial, underimmunized 20-month-olds identified by the HMO's computerized immunization tracking system were assigned to one of four interventions: 1) an automated telephone message alone; 2) a letter alone; 3) an automated telephone message followed by a letter 1 week later; and 4) a letter followed by an automated telephone message 1 week later. The primary outcome was receipt of any needed immunization by 24 months of age. Decision analysis was used to evaluate the projected cost-effectiveness of the alternative strategies. RESULTS: A total of 648 children were randomized. A letter followed by a telephone message (58% immunized) was significantly better than either a letter alone (44% immunized) or a telephone message alone (44% immunized). A telephone message followed by a letter (53% immunized) also was more effective than either alone, although the differences were not statistically significant. Among a similar comparison group that received no systematic intervention, 36% were immunized. The estimated cost per child immunized was $7.00 using letters followed by automated telephone messages, $9.80 using automated telephone messages alone, and $10.50 using letters alone. Under alternative cost assumptions for automated telephone messages and mailed messages, the cost per child immunized ranged from $2.20 to $6.50. CONCLUSIONS: For underimmunized 20-month-olds in this HMO setting, letters followed by automated telephone messages were more effective and cost-effective than either message alone. The cost-effectiveness of automated telephone messages and letters may vary widely depending on the setting, and choices among strategies should be tailored to the populations being served.
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Much has been written and discussed about low clinical and decision-support tools can help providers deliver quality care to their patients. But there are theories--and then there are realities--about what will actually work in the real world and how useful they will be. When incorporating decision-support tools into electronic health records, the results may not always be predictable.
To determine the impact of information technology on embedding the latent tuberculosis infection (LTBI) screening guidelines in an electronic medical record (EMR) in a large health care system. The long-term goal of the study is to test clinician adherence to LTBI screening guidelines using an EMR system. However, preliminary results are presented on the potential impact on providers on implementing the alerts on targeted high-risk patients.
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