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Background Opioid pain relievers are commonly prescribed following dental extractions, but evidence shows that non-opioid analgesics often provide adequate pain relief with fewer risks. The current study examined clinical decision support (CDS) as a tool for de-implementing opioid prescribing in dentistry. Methods This prospective, cluster-randomized trial examined CDS for dental pain management at 22 HealthPartners Dental Group clinics in Minnesota. Dental providers ( n  = 49) were randomized to deliver care using CDS, CDS with patient education materials (CDS-E), or standard practice (SP). Randomization was stratified by provider type (dentist vs. oral surgeon) and baseline opioid prescribing volume. Patient records of dental extractions were examined for January 2019 through May 2021, representing a 12-month baseline and 15-month intervention period ( N  = 12,924). Opioid prescription at the visit (no vs. yes) was the primary outcome. Data were analyzed using generalized linear mixed models, adjusting for patient sex and age, extraction complexity, and baseline prescribing strata (volume and provider type). Results Patients were 56.2% female, with a mean age of 46.7 (SD = 20.0) years. Providers were 8% oral surgeons, 57% female, and with a mean age of 43.7 (SD = 11.2) years. There were significant decreases in opioid prescribing during the study ( P  < 0.001), representing a continuation of pre-existing trends to reduce opioid prescribing in these dental practices. There were no significant differences in opioid prescribing between CDS and SP (OR = 1.29; 97.5% CI = 0.93, 1.79; P  = 0.08), or CDS-E and SP arms (OR = 1.27; 97.5% CI = 0.86, 1.79; P  = 0.18). The direction of the association favored greater reductions in opioid prescribing in the SP arm. Despite training and implementation support, utilization of the CDS was low, particularly among oral surgeons, who were significantly more likely than other dentists to prescribe opioids. Among non-oral surgeon providers with the opportunity to access it, CDS utilization was not significantly associated with opioid prescribing. Conclusions Equipping dentists with CDS resources, whether alone or accompanied by patient education materials, did not accelerate reductions in opioid prescribing beyond those observed in standard practice. Strategies are needed to enhance CDS utilization for patient care and safety surrounding analgesia following dental extractions. Trial registration Clinicaltrials.gov, NCT03584789.

Background Electronic health record (EHR)-linked clinical decision support (CDS) may impact primary care clinicians’ (PCCs’) clinical care opinions. As part of a clinic cluster-randomized control trial (RCT) testing a cancer prevention and screening CDS system with patient and PCC printouts (with or without shared decision-making tools [SDMT]) for patients due for breast, cervical, colorectal, and lung cancer screening and/or human papillomavirus (HPV) vaccination compared to usual care (UC), we surveyed PCCs at study clinics pre- and post-CDS implementation. Our primary aim was to learn if PCCs' opinions changed over time within study arms. Secondary aims including examining whether PCCs' opinions in study arms differed both pre- and post-implementation, and gauging PCCs’ opinions on the CDS in the two intervention arms. Methods This study was conducted within a healthcare system serving an upper Midwestern population. We administered pre-implementation (11/2/2017–1/24/2018) and post-implementation (2/2/2020–4/9/2020) cross-sectional electronic surveys to PCCs practicing within a RCT arm: UC; CDS; or CDS + SDMT. Bivariate analyses compared responses between study arms at both time periods and longitudinally within study arms. Results Pre-implementation (53%, n  = 166) and post-implementation (57%, n  = 172) response rates were similar. No significant differences in PCC responses were seen between study arms on cancer prevention and screening questions pre-implementation, with few significant differences found between study arms post-implementation. However, significantly fewer intervention arm clinic PCCs reported being very comfortable with discussing breast cancer screening options with patients compared to UC post-implementation, as well as compared to the same intervention arms pre-implementation. Other significant differences were noted within arms longitudinally. For intervention arms, these differences related to CDS areas like EHR alerts, risk calculators, and ordering screening. Most intervention arm PCCs noted the CDS provided overdue screening alerts to which they were unaware. Few PCCs reported using the CDS, but most would recommend it to colleagues, expressed high CDS satisfaction rates, and thought patients liked the CDS’s information and utility. Conclusions While appreciated by PCCs with high satisfaction rates, the CDS may lower PCCs’ confidence regarding discussing patients’ breast cancer screening options and may be used irregularly. Future research will evaluate the impact of the CDS on cancer prevention and screening rates. Trial registration clinicaltrials.gov , NCT02986230, December 6, 2016.

Background Few studies have assessed the impact of clinical decision support (CDS), with or without shared decision-making tools (SDMTs), on patients’ perceptions of cancer screening or prevention in primary care settings. This cross-sectional survey was conducted to understand primary care patient’s perceptions on cancer screening or prevention. Methods We mailed surveys (10/2018–1/2019) to 749 patients aged 18 to 75 years within 15 days after an index clinical encounter at 36 primary care clinics participating in a clinic-randomized control trial of a CDS system for cancer prevention. All patients were overdue for cancer screening or human papillomavirus vaccination. The survey compared respondents’ answers by study arm: usual care; CDS; or CDS + SDMT. Results Of 387 respondents (52% response rate), 73% reported having enough time to discuss cancer prevention options with their primary care provider (PCP), 64% reported their PCP explained the benefits of the cancer screening choice very well, and 32% of obese patients reported discussing weight management, with two-thirds reporting selecting a weight management intervention. Usual care respondents were significantly more likely to decide on colorectal cancer screening than CDS respondents ( p  < 0.01), and on tobacco cessation than CDS + SDMT respondents ( p  = 0.02) and both CDS and CDS + SDMT respondents ( p  < 0.001). Conclusions Most patients reported discussing cancer prevention needs with PCPs, with few significant differences between the three study arms in patient-reported cancer prevention care. Upcoming research will assess differences in screening and vaccination rates between study arms during the post-intervention follow-up period. Trial registration clinicaltrials.gov , NCT02986230 , December 6, 2016.

Clinical decision support (CDS) has the potential to improve clinical decision-making consistent with evidence-based care. CDS can be designed to save health care providers time and help them provide safe and personalized analgesic prescribing. The aim of this report is to describe the development of a CDS system designed to provide dentists with personalized pain management recommendations to reduce opioid prescribing following extractions. The use of CDS is also examined. This study was conducted in HealthPartners, which uses an electronic health record (EHR) system that integrates both medical and dental information upon which the CDS application was developed based on SMART (Substitutable Medical Applications and Reusable Technologies) on FHIR (Fast Healthcare Interoperability Resources). The various tools used to bring relevant medical conditions, medications, patient history, and other relevant data into the CDS interface are described. The CDS application runs a drug interaction algorithm developed by our organization and provides patient-specific recommendations. The CDS included access to the state Prescription Monitoring Program database. The pain management CDS was implemented as part of a study examining opioid prescribing among patients undergoing dental extraction procedures from February 17, 2020, to May 14, 2021. Provider-level use of CDS at extraction encounters ranged from 0% to 87.4% with 12.1% of providers opening the CDS for no encounters, 39.4% opening the CDS for 1%-20% of encounters, 36.4% opening it for 21%-50% of encounters, and 12.1% opening it for 51%-87% of encounters. The pain management CDS is an EHR-embedded, provider-facing tool to help dentists make personalized pain management recommendations following dental extractions. The SMART on FHIR-based pain management CDS adapted well to the point-of-care dental setting and led to the design of a scalable CDS tool that is EHR vendor agnostic. ClinicalTrials.gov NCT03584789; https://clinicaltrials.gov/study/NCT03584789.

Background Cancer is the leading cause of death in the United States, with the burden expected to rise in the coming decades, increasing the need for effective cancer prevention and screening options. The United States Preventive Services Task Force has suggested that a shared decision-making process be used when clinicians and patients discuss cancer screening. The electronic medical record (EMR) often provides only reminders or alerts to primary care providers (PCPs) when screenings are due, a strategy with limited efficacy. Methods We administered a cross-sectional electronic survey to PCPs ( n  = 165, 53% response rate) at 36 Essentia Health primary care clinics participating in a large, National Cancer Institute-funded study on a cancer prevention clinical decision support (CDS) tool. The survey assessed PCP demographics, perceptions of the EMR’s ability to help assess and manage patients’ cancer risk, and experience and comfort level discussing cancer screening and prevention with patients. Results In these predominantly rural clinics, only 49% of PCPs thought the EMR was well integrated to help assess and manage cancer risk. Both advanced care practitioners and physicians agreed that cancer screening and informed discussion of cancer risks are important; however, only 53% reported their patients gave cancer screening a high priority relative to other health issues. Conclusions The impact of EMR-linked CDS delivered to both patients and PCPs may improve cancer screening, but only if it is easy to use and saves PCPs time.

Background Patient reported outcome measures (PROMs) are increasingly being incorporated into clinical and surgical care for assessing outcomes. This study examined outcomes important to patients in their decision to have hip or knee replacement surgery, their perspectives on PROMs and shared decision-making, and factors they considered important for postoperative care. Methods A cross-sectional study employing survey methods with a stratified random sample of adult orthopedic patients who were scheduled for or recently had hip or knee replacement surgery. Results In a representative sample of 226 respondents, patients identified personalized outcomes important to them that they wanted from their surgery including the ability to walk without pain/discomfort, pain relief, and returning to an active lifestyle. They preferred a personalized outcome (54%) that they identified, compared to a PROM score, for tracking progress in their care and thought it important that their surgeon know their personal outcomes (63%). Patients also wanted to engage in shared decision-making (79%) about their post-surgical care and identified personal factors important to their aftercare, such as living alone and caring for pets. Conclusions Patients identified unique personalized outcomes they desired from their care and that they wanted their orthopedic surgeons to know about. Asking patients to identify their personalized outcomes could add value for both patients and surgeons in clinical care, facilitating more robust patient involvement in shared decision-making.

OBJECTIVE: To assess two physician learning interventions designed to improve safety and quality of diabetes care delivered by primary care physicians (PCPs). RESEARCH DESIGN AND METHODS: This group randomized clinical trial included 57 consenting PCPs and their 2,020 eligible adult patients with diabetes. Physicians were randomized to no intervention (group A), a simulated case-based physician learning intervention (group B), or the same simulated case-based learning intervention with physician opinion leader feedback (group C). Dependent variables included A1C values, LDL cholesterol values, pharmacotherapy intensification rates in patients not at clinical goals, and risky prescribing events. RESULTS: Groups B and C had substantial reductions in risky prescribing of metformin in patients with renal impairment (P = 0.03). Compared with groups A and C, physicians in group B achieved slightly better glycemic control (P = 0.04), but physician intensification of oral glucose-lowering medications was not affected by interventions (P = 0.41). Lipid management improved over time (P < 0.001) but did not differ across study groups (P = 0.67). CONCLUSIONS: A simulated, case-based learning intervention for physicians significantly reduced risky prescribing events and marginally improved glycemic control in actual patients. The addition of opinion leader feedback did not improve the learning intervention. Refinement and further development of this approach is warranted.

Hypertension is a leading cause of cardiovascular disease. The results were previously reported of a trial of home blood pressure (BP) telemonitoring and pharmacist management intervention in which the interventions stopped after 12 months. There were significantly greater reductions in systolic BP (SBP) in the intervention group than in the usual care group at 6, 12, and 18 months (-10.7, -9.7, and -6.6 mm Hg, respectively). To examine the durability of the intervention effect on BP through 54 months of follow-up and to compare BP measurements performed in the research clinic and in routine clinical care. Follow-up of a cluster randomized clinical trial among 16 primary care clinics and 450 patients with uncontrolled hypertension in a large health system from March 2009 to November 2015. A home BP telemonitoring intervention with pharmacist management or usual care. Change from baseline to 54 months in SBP and diastolic BP (DBP) measured as the mean of 3 measurements obtained at each research clinic visit. Among 450 patients, 228 (mean [SD] age, 62.0 [11.7] years; 54.8% male) were randomized to the telemonitoring intervention and 222 (mean [SD] age, 60.2 [12.2] years; 55.9% male) to usual care. Research clinic BP measurements were obtained from 326 of 450 (72.4%) study patients at the 54-month follow-up visit, including 162 (mean [SD] age, 62.0 [11.1] years; 54.9% male) randomized to the telemonitoring intervention and 164 (mean [SD] age, 60.0 [11.2] years; 57.3% male) to usual care. Routine clinical care BP measurements were obtained from 439 of 450 (97.6%) study patients at 6248 visits during the follow-up period. Based on research clinic measurements, baseline mean SBP was 148 mm Hg in both groups. In the intervention group, mean SBP at 6-, 12-, 18-, and 54-month follow-up was 126.7, 125.7, 126.9, and 130.6 mm Hg, respectively. In the usual care group, mean SBP at 6-, 12-, 18-, and 54-month follow-up was 136.9, 134.8, 133.0, and 132.6 mm Hg, respectively. The differential reduction by study group in SBP from baseline to 54 months was -2.5 mm Hg (95% CI, -6.3 to 1.2 mm Hg; P = .18). The DBP followed a similar pattern, with a differential reduction by study group from baseline to 54 months of -1.0 mm Hg (95% CI, -3.2 to 1.2 mm Hg; P = .37). The SBP and DBP results from routine clinical measurements suggested significantly lower BP in the intervention group for up to 24 months. This intensive intervention had sustained effects for up to 24 months (12 months after the intervention ended). Long-term maintenance of BP control is likely to require continued monitoring and resumption of the intervention if BP increases. ClinicalTrials.gov Identifier: NCT00781365.

Randomized Trial of Quality Improvement Intervention to Improve Diabetes Care in Primary Care Settings Patrick J. O’Connor , MD, MPH 1 , Jay Desai , MPH 2 , Leif I. Solberg , MD 1 , Laurel A. Reger , MBA 2 , A. Lauren Crain , PHD 1 , Stephen E. Asche , MS 1 , Teresa L. Pearson , RN, MS, CDE 1 , Cynthia K. Clark , MA 3 , William A. Rush , PHD 1 , Linda M. Cherney , RD, MPH 1 , JoAnn M. Sperl-Hillen , MD 1 and Donald B. Bishop , PHD 2 1 HealthPartners Research Foundation, Minneapolis, Minnesota 2 Minnesota Department of Health, St. Paul, Minnesota 3 Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia Address correspondence and reprint requests to Dr. Patrick O’Connor, Senior Clinical Investigator, HealthPartners Research Foundation, P.O. Box 1524, MS21111R, Minneapolis, MN 55440-1524. E-mail: patrick.j.oconnor{at}healthpartners.com Abstract OBJECTIVE —To assess the impact of a quality improvement (QI) intervention on the quality of diabetes care at primary care clinics. RESEARCH DESIGN AND METHODS —Twelve primary care medical practices were matched by size and location and randomized to intervention or control conditions. Intervention clinic staff were trained in a seven-step QI change process to improve diabetes care. Surveys and medical record reviews of 754 patients, surveys of 329 clinic staff, interviews with clinic leaders, and analysis of training session videotapes evaluated compliance with and impact of the intervention. Mixed-model nested analyses compared differences in the quality of diabetes care before and after intervention. RESULTS —All intervention clinics completed at least six steps of the seven-step QI change process in an 18-month period and, compared with control clinics, had broader staff participation in QI activities ( P = 0.04), used patient registries more often ( P = 0.03), and had better test rates for HbA 1c (A1C), LDL, and blood pressure ( P = 0.02). Other processes of diabetes care were unchanged. The intervention did not improve A1C ( P = 0.54), LDL ( P = 0.46), or blood pressure ( P = 0.69) levels or a composite of these outcomes ( P = 0.35). CONCLUSIONS —This QI change process was successfully implemented but failed to improve A1C, LDL, or blood pressure levels. Data suggest that to be successful, such a QI change process should direct more attention to specific clinical actions, such as drug intensification and patient activation. IDEAL, Improving Care for Diabetes Through Empowerment, Active Collaboration, and Leadership QI, quality improvement Footnotes T.L.P. has been a member of advisory boards for and has received honorarium from LifeScan, NovoNordisk, and AmerisourceBergen. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Accepted May 3, 2005. Received January 30, 2005. DIABETES CARE

ABSTRACT Background It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others. Objective We conducted a mediation analysis to determine which of seven factors had the greatest effect on change in systolic blood pressure (BP) after 6 months in a trial to improve hypertension control. Design The study was a preplanned secondary analysis of a cluster-randomized clinical trial. Eight clinics in an integrated health system were randomized to provide usual care to their patients ( n  = 222), and eight were randomized to provide a telemonitoring intervention ( n  = 228). Participants Four hundred three of 450 trial participants completing the 6-month follow-up visit were included. Interventions Intervention group participants received home BP telemonitors and transmitted measurements to pharmacists, who adjusted medications and provided advice to improve adherence to medications and lifestyle modification via telephone visits. Main measures Path analytic models estimated indirect effects of the seven potential mediators of intervention effect (defined as the difference between the intervention and usual care groups in change in systolic BP from baseline to 6 months). The potential mediators were change in home BP monitor use, number of BP medication classes, adherence to BP medications, physical activity, salt intake, alcohol use, and weight. Key Results The difference in change in systolic BP was 11.3 mmHg. The multivariable mediation model explained 47 % (5.3 mmHg) of the intervention effect. Nearly all of this was mediated by two factors: an increase in medication treatment intensity (24 %) and increased home BP monitor use (19 %). The other five factors were not significant mediators, although medication adherence and salt intake improved more in the intervention group than in the usual care group. Conclusions Most of the explained intervention effect was attributable to the combination of self-monitoring and medication intensification. High adherence at baseline and the relatively low intensity of resources directed toward lifestyle change may explain why these factors did not contribute to the improvement in BP.