Background: Computerized decision support reduces medication errors in inpatients, but limited evidence supports its effectiveness in reducing the coprescribing of interacting medications, especially in the outpatient setting. The usefulness of academic detailing to enhance the effectiveness of medication interaction alerts also is uncertain.
concordance between these scores when both measures could be computed. Results: We identified 122,270 eligible patients. Of these, 59.7% (n=73,023) had sufficient data to calculate the lab-based risk score and 88.1% (102,795) clinic-based risk score. Neither score could be calculated for 14.5% (n=17,732). The most common reason for not being able to calculate was missing data on cholesterol. Using the laboratory-based score only, we found 12.9% of the population were at high risk (risk >20%), 24.5% moderate risk (10-20%), and 62.6% low risk (<10%). For those with both risk scores (n=71,280), the lab-based risk score was lower than the clinic-based score for 84.3% of patients (60,060/71,280). The lab-based score was 3.1% lower on average, but the two risk scores were within ±5% for 77.0% of patients (54,874/71,280). The risk scores differed by more than 10% for only 8.7% of patients (n=6236), and in most cases (6098 of 6236), the clinic-based score was higher. Conclusion: Electronic data can be used to classify CVD risk for most adults age 30-74. Risk scores based on BMI tend to estimate risk as higher than scores based on laboratory data. However, the risk scores do not differ by more than 5% for most patients.
Background/Aims: Adherence to certain effective and widely prescribed cardiovascular (CVD) medications is poor. The purpose of this analysis is to demonstrate the effective implementation of a cost-effective and easily disseminable population-level HIT adherence intervention. Methods: PATIENT is a pragmatic trial designed to improve adherence to antihypertensives and statins in high-risk patients in three Kaiser Permanente (KP) regions. The 1-year intervention (Dec. 2011-2012) enrolled 21,752 adults, aged 40-80, with diabetes or CVD and at least 1 dispensing of a target medication in the past year (based on pharmacy dispensing data). Participants were randomized to one of 3 arms: usual care (UC), automated telephone reminders (IVR), or an enhanced IVR arm (IVR+) that added mailed educational materials, reminder mailings and live outreach calls to IVR calls. Results: Through the first 10 months of intervention we attempted 42,010 automated reminder calls (˜ 2.9 per intervention participant). Of these, 56% (23,596) of calls successfully reached the target participant and an additional 29% (12,271) resulted in messages left. These figures were higher for calls made to those nearly due for a refill (65% and 26% of 20,182) than for calls made to those overdue (48% and 32% of 21,828). Of calls where we reached the participant, 30% resulted in a transfer to the regional pharmacy automated refill line and an additional 2.5% resulted in transfers to a live pharmacist. Among the 7,258 IVR+ patients, 3,748 medication reminder letters were mailed, 2,146 live reminder calls were made, and we have sent 36,823 educational mailings (˜4.9 per participant). Key implementation challenges that emerged related to 1) complexities in coding the intervention call flag algorithm from the EMR and 2) customization of the intervention to fit regional work-flow and support program sustainability. Close partnering with pharmacy staff was crucial in overcoming early hurdles. Outcome data (not yet available) will be presented at the meeting. Conclusions: We successfully implemented a large, multi-modal, HIT, medication adherence intervention at 3 KP regions. A high proportion of members were reached and actively participated in the intervention. Key challenges/solutions are detailed in a manual of operations to facilitate the implementation of similar interventions in other settings.
Introduction: Patient adherence to chronic therapy is the necessary link between effective treatments and improved patient outcomes. However, the frequent failure of patients to adhere to long-term medication regimens is a challenge in chronic disease management. Though many prior interventions aimed at improving patient medication adherence have been successful, they are often costly and have limited disseminability. Methods: The PATIENT ( P romoting A dherence T o I mprove the E ffective n ess of CVD T herapies) study is a randomized control trial to compare the impact of two low-cost, low-intensity health information technology-based interventions (which include automated prescription refill reminder calls and mailed education materials) on patient adherence to selected chronic CVD medications. The primary goal throughout the development of this intervention was for it to be disseminable at the end of the grant period. We implemented several strategies aimed at increasing the likelihood of long-term implementation and dissemination of the intervention. These strategies included establishing an advisory board that included a diverse group of health plan clinicians and staff, conducting stakeholder interviews and participant focus groups, presenting at health plan meetings and carrying out a pilot of the intervention prior to the start of the main trial. Results: Our efforts in prioritizing the disseminability of the intervention highlighted several important lessons. First, it was important to develop all aspects of the intervention in partnership with health plan stakeholders, as their feedback was critical in the development of a protocol that would be ultimately congruent with local policies. Second, conversations with stakeholders highlighted the ways in which each of the sites were similar to and different from one another, thereby identifying which components of the intervention should be consistent across sites but also underscoring the need for there to be some regional customization. Preliminary results from the pilot of the intervention indicate that these efforts have been worthwhile: 62% of participants reported that the automated phone calls were helpful and the majority (80%) are willing to take a similar call in the future; similarly, the majority of participants reported that the mailed health education materials were useful (∼64%) and easy to understand (∼71%). Conclusions: The PATIENT intervention, if successful, could have significant public health applications as flexible and generalizable components of disease management programs. Understanding the barriers to and facilitators of successful implementation is critical to the widespread implementation of the intervention. Lessons learned from the developing and implementing the present study may aid others in similar efforts and in different settings.
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