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Pilot study of decision support tools on breast cancer chemoprevention for high-risk women and healthcare providers in the primary care setting.

ABSTRACT: BACKGROUND:Breast cancer chemoprevention can reduce breast cancer incidence in high-risk women; however, chemoprevention is underutilized in the primary care setting. We conducted a pilot study of decision support tools among high-risk women and their primary care providers (PCPs). METHODS:The intervention included a decision aid (DA) for high-risk women, RealRisks, and a provider-centered tool, Breast Cancer Risk Navigation (BNAV). Patients completed validated surveys at baseline, after RealRisks and after their PCP clinical encounter or at 6-months. Referral for high-risk consultation and chemoprevention uptake were assessed via the electronic health record. The primary endpoint was accuracy of breast cancer risk perception at 6-months. RESULTS:Among 40 evaluable high-risk women, median age was 64.5?years and median 5-year breast cancer risk was 2.19%. After exposure to RealRisks, patients demonstrated an improvement in accurate breast cancer risk perceptions (p?=?0.02), an increase in chemoprevention knowledge (p?

SUBMITTER: Kukafka R

PROVIDER: S-EPMC6296071 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Pilot study of decision support tools on breast cancer chemoprevention for high-risk women and healthcare providers in the primary care setting.

Kukafka Rita R Fang Jiaqi J Vanegas Alejandro A Silverman Thomas T Crew Katherine D KD

BMC medical informatics and decision making 20181217 1

<h4>Background</h4>Breast cancer chemoprevention can reduce breast cancer incidence in high-risk women; however, chemoprevention is underutilized in the primary care setting. We conducted a pilot study of decision support tools among high-risk women and their primary care providers (PCPs).<h4>Methods</h4>The intervention included a decision aid (DA) for high-risk women, RealRisks, and a provider-centered tool, Breast Cancer Risk Navigation (BNAV). Patients completed validated surveys at baseline ...[more]

PMID: 30558581

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Project description:BackgroundMinistries of health in low- and middle-income countries often lack timely quality data for data-driven decision making in healthcare networks. We describe the design and implementation of decision-support electronic tools by the Ministry of Health of the State of Chiapas, in Mexico, as part of Salud Mesoamerica Initiative.MethodsThree electronic decision-support tools were designed through an iterative process focused on streamlined implementation: 1) to collect and report health facility data at health facilities; 2) to compile and analyze data at health district and central level; and, 3) to support stratified sampling of health facilities. Data was collected for five composite indicators measuring availability of equipment, medicines, and supplies for maternal and child health. Quality Assurance Teams collected data, evaluated results and supported quality improvement. Data was also analyzed at the central level and health districts for decision-making.ResultsData from 300 health facilities in four health districts was collected and analyzed (November 2014-June 2015). The first wave revealed gaps on availability of equipment and supplies in more than half of health facilities. Electronic tools provided the ministry of health officers new ways to visualize data, identify patterns and make hypothesis on root-causes. Between the first and second measurement, the number of missing items decreased, and actions performed by quality improvement teams became more proactive. In the final measurement, 89.7-100% of all health facilities achieved all the required items for each indicator.ConclusionsOur experience could help guide others seeking to implement electronic decision-support tools in low- and middle-income countries. Electronic decision-support tools supported data-driven decision-making by identifying gaps on heatmaps and graphs at the health facility, subdistrict, district or state level. Through a rapid improvement process, the Ministry of Health met targets of externally verified indicators. Using available information technology resources facilitated prompt implementation and adoption of technology.

Project description:Computer-based decision support systems are a promising method for incorporating research evidence into clinical practice. However, evidence is still scant on how such information technology solutions work in primary healthcare when support is provided across many health problems. In Finland, we designed a trial where a set of evidence-based, patient-specific reminders was introduced into the local Electronic Patient Record (EPR) system. The aim was to measure the effects of such reminders on patient care. The hypothesis was that the total number of triggered reminders would decrease in the intervention group compared with the control group, indicating an improvement in patient care.From July 2009 to October 2010 all the patients of one health center were randomized to an intervention or a control group. The intervention consisted of patient-specific reminders concerning 59 different health conditions triggered when the healthcare professional (HCP) opened and used the EPR. In the intervention group, the triggered reminders were shown to the HCP; in the control group, the triggered reminders were not shown. The primary outcome measure was the change in the number of reminders triggered over 12 months. We developed a unique data gathering method, the Repeated Study Virtual Health Check (RSVHC), and used Generalized Estimation Equations (GEE) for analysing the incidence rate ratio, which is a measure of the relative difference in percentage change in the numbers of reminders triggered in the intervention group and the control group.In total, 13,588 participants were randomized and included. Contrary to our expectation, the total number of reminders triggered increased in both the intervention and the control groups. The primary outcome measure did not show a significant difference between the groups. However, with the inclusion of patients followed up over only six months, the total number of reminders increased significantly less in the intervention group than in the control group when the confounding factors (age, gender, number of diagnoses and medications) were controlled for.Computerized, tailored reminders in primary care did not decrease during the 12 months of follow-up time after the introduction of a patient-specific decision support system.ClinicalTrial.gov NCT00915304.

Dataset Information

Pilot study of decision support tools on breast cancer chemoprevention for high-risk women and healthcare providers in the primary care setting.

Publications

Pilot study of decision support tools on breast cancer chemoprevention for high-risk women and healthcare providers in the primary care setting.

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