De-implementing opioid prescribing in a dental group practice: Lessons learned.

BACKGROUND: Drug overdose has become a leading cause of accidental death in the United States. Between 2000 and 2015, the rate of deaths from drug overdoses increased 137%, including a 200% increase in the rate of overdose deaths involving opioids (including opioid pain relievers and heroin). Unnecessary opioid prescribing is one of the factors driving this epidemic. OBJECTIVES: The primary objective of this paper is to share lessons learned while conducting a randomized trial to de-implement opioids for post-extraction pain management utilizing clinical decision support (CDS) with and without patient education. The lessons learned from conducting this trial in a real-world setting can be applied to future dissemination and implementation oral health research. METHODS: The sources informing lessons learned were generated from qualitative interviews conducted with 20 of the forty-nine dental providers involved in the study following the implementation phase of the trial. Ongoing policy, social and environmental factors were tracked throughout the study. RESULTS: Dental providers in the trial identified the impact of training that involved health professionals sharing information about the personal impact of pain and opioid use. Additionally, they found utility in being presented with a dashboard detailing their prescribing patterns related to other dentists. For the 30 general dentists with access to the CDS, use of its portal varied widely, with most using it 10%-49% of the time related to extractions. CONCLUSIONS: In the context of a downward trend in opioid prescribing and considering the influence of the COVID pandemic during the trial, dental providers indicated benefit in training about negative personal impacts of prescribing opioids, and personally relevant feedback about their prescribing patterns. Only modest use of the CDS was realized. Implementation of this trial was impacted by governmental and health system policies and the COVID pandemic, prompt the consideration of implications regarding continuing ways to limit opioid prescribing among dental providers.

Factor Analysis in Distinguishing Coronavirus Disease 2019 From Other Influenza-like Illness Using a Validated Patient-Reported Outcome Instrument FLU-PRO Plus: A Prospective Real-world Cohort Study.

BACKGROUND/OBJECTIVE: InFLUenza Patient-reported Outcome (FLU-PRO Plus) is a 34-item patient-reported outcome instrument designed to capture the intensity and frequency of viral respiratory symptoms. This study evaluates whether FLU-PRO Plus responses could discriminate between symptoms of coronavirus disease 2019 (COVID-19) and influenza-like illness (ILI) with no COVID diagnosis, as well as forecast disease progression. METHODS: FLU-PRO Plus was administered daily for 14 days. Exploratory factor analysis was used to reduce the FLU-PRO Plus responses on the first day to 3 factors interpreted as "symptom clusters." The 3 clusters were used to predict COVID-19 versus ILI diagnosis in logistic regression. Correlation between the clusters and quality of life (QoL) measures was used to assess concurrent validity. The timing of self-reported return to usual health in the 14-day period was estimated as a function of the clusters within COVID-19 and ILI groups. RESULTS: Three hundred fourteen patients completed day 1 FLU-PRO Plus, of which 65% had a COVID-19 diagnosis. Exploratory factor analysis identified 3 symptom clusters: (1)general Body, (2) tracheal/bronchial, and (3) nasopharyngeal. Higher nasopharyngeal scores were associated with higher odds of COVID-19 compared with ILI diagnosis [adjusted odds ratio = 1.61 (1.21, 2.12)]. Higher tracheal/bronchial scores were associated with lower odds of COVID-19 [0.58 (0.44, 0.77)]. The 3 symptom clusters were correlated with multiple QoL measures ( r = 0.14-0.56). Higher scores on the general body and tracheal/bronchial symptom clusters were associated with prolonged time to return to usual health [adjusted hazard ratios: 0.76 (0.64, 0.91), 0.80 (0.67, 0.96)]. CONCLUSION: Three symptom clusters identified from FLU-PRO Plus responses successfully discriminated patients with COVID-19 from non-COVID ILI and were associated with QoL and predicted symptom duration.

Human Papillomavirus vaccination clinical decision support for young adults in an upper midwestern healthcare system: a clinic cluster-randomized control trial.

INTRODUCTION: Human papillomavirus (HPV) vaccination rates are low in young adults. Clinical decision support (CDS) in primary care may increase HPV vaccination. We tested the treatment effect of algorithm-driven, web-based, and electronic health record-linked CDS with or without shared decision-making tools (SDMT) on HPV vaccination rates compared to usual care (UC). METHODS: In a clinic cluster-randomized control trial conducted in a healthcare system serving a largely rural population, we randomized 34 primary care clinic clusters (with three clinics sharing clinicians randomized together) to: CDS; CDS+SDMT; UC. The sample included young adults aged 18-26 due for HPV vaccination with a study index visit from 08/01/2018-03/15/2019 in a study clinic. Generalized linear mixed models tested differences in HPV vaccination status 12 months after index visits by study arm. RESULTS: Among 10,253 patients, 6,876 (65.2%) were due for HPV vaccination, and 5,054 met study eligibility criteria. In adjusted analyses, the HPV vaccination series was completed by 12 months in 2.3% (95% CI: 1.6%-3.2%) of CDS, 1.6% (95% CI: 1.1%-2.3%) of CDS+SDMT, and 2.2% (95% CI: 1.6%-3.0%) of UC patients, and at least one HPV vaccine was received by 12 months in 13.1% (95% CI: 10.6%-16.1%) of CDS, 9.2% (95% CI: 7.3%-11.6%) of CDS+SDMT, and 11.2% (95% CI: 9.1%-13.7%) of UC patients. Differences were not significant between arms. Females, those with prior HPV vaccinations, and those seen at urban clinics had significantly higher odds of HPV vaccination in adjusted models. DISCUSSION: CDS may require optimization for young adults to significantly impact HPV vaccination. TRIAL REGISTRATION: clinicaltrials.gov NCT02986230, 12/6/2016.

FINDINGS AND FUTURE DIRECTIONS FROM A SMOKING CESSATION TRIAL UTILIZING A CLINICAL DECISION SUPPORT TOOL.

BACKGROUND: Tobacco smoking is the leading cause of disease, death, and disability in the United States. Dental practitioners are advised to provide evidence-based smoking cessation interventions to their patients, yet dental practitioners frequently fail to deliver brief smoking cessation advice. OBJECTIVES: To test whether giving dental practitioners a clinical decisions support (CDS) system embedded in their electronic dental record would increase the rate at which patients who smoke (1) report receiving a brief intervention or referral to treatment during a recent dental visit, (2) taking action related to smoking cessation within 7 days of visit, and (3) stop smoking for 1 day or more or reduce the amount smoked by 50% within 6 months. METHODS: Two-group, parallel arm, cluster-randomized trial. From March through December 2019, 15 nonacademic primary care dental clinics were randomized via covariate adaptive randomization to either a usual care arm or the CDS arm. Adult smokers completed an initial telephone survey within 7 days of their visit and another survey after 6 months. RESULTS: Forty-three patients from 5 CDS and 13 patients from 2 usual care clinics completed the 7-day survey. While the proportion of patients who reported receipt of a brief intervention or referral to treatment was significantly greater in the CDS arm than the usual care arm (84.3% vs 58.6%; P = .005), the differences in percentage of patients who took any action related to smoking cessation within 7 days (44.4% vs 22.3%; P = .077), or stopped smoking for one day or more and/or reduced amount smoked by 50% within 6 months (63.1% vs 46.2%; P = .405) were large but not statistically significant. CONCLUSIONS: Despite interruption by COVID-19, these results demonstrate a promising approach to assist dental practitioners in providing their patients with smoking cessation screening, brief intervention and referral to treatment.