Background

A learning health system (LHS) is a health system in which patients and clinicians work together to choose care on the basis of best evidence and to drive discovery as a natural outgrowth of every clinical encounter to ensure the right care at the right time. An LHS for dentistry is now feasible, as an increased number of oral health care encounters are captured in electronic health records (EHRs).

Methods

The authors used EHRs data to track periodontal health outcomes at 3 large dental institutions. The 2 outcomes of interest were a new periodontitis case (for patients who had not received a diagnosis of periodontitis previously) and tooth loss due to progression of periodontal disease.

Results

The authors assessed a total of 494,272 examinations (new periodontitis outcome: n = 168,442; new tooth loss outcome: n = 325,830), representing a total of 194,984 patients. Dynamic dashboards displaying performance on both measures over time allow users to compare demographic and risk factors for patients. The incidence of new periodontitis and tooth loss was 4.3% and 1.2%, respectively.

Conclusions

Periodontal disease, diagnosis, prevention, and treatment are particularly well suited for an LHS model. The results showed the feasibility of automated extraction and interpretation of critical data elements from the EHRs. The 2 outcome measures are being implemented as part of a dental LHS. The authors are using this knowledge to target the main drivers of poorer periodontal outcomes in a specific patient population, and they continue to use clinical health data for the purpose of learning and improvement.

Practical implications

Dental institutions of any size can conduct contemporaneous self-evaluation and immediately implement targeted strategies to improve oral health outcomes.

BACKGROUND: Preventable medical errors in hospital settings are the third leading cause of deaths in the United States. However, less is known about harm that occurs in patients in outpatient settings, where the majority of care is delivered. We do not know the likelihood that a patient sitting in a dentist chair will experience harm. Additionally, we do not know if patients of certain race, age, sex, or socioeconomic status disproportionately experience iatrogenic harm. METHODS: We initiated the Dental Practice Study (DPS) with the aim of determining the frequency and types of adverse events (AEs) that occur in dentistry on the basis of retrospective chart audit. This article discusses the 6-month pilot phase of the DPS during which we explored the feasibility and efficiency of our multistaged review process to detect AEs. RESULTS: At sites 1, 2, and 3, respectively, 2 reviewers abstracted 21, 11, and 23 probable AEs, respectively, from the 100 patient charts audited per site. At site 2, a third reviewer audited the same 100 charts and found only 1 additional probable AE. Of the total 56 probable AEs (from 300 charts), the expert panel confirmed 9 AE cases. This equals 3 AEs per 100 patients per year. Patients who experienced an AE tended to be male and older and to have undergone more procedures within the study year. CONCLUSIONS: This article presents an overview of the DPS. It describes the methods used and summarizes the results of its pilot phase. To minimize threats to dental patient safety, a starting point is to understand their basic epidemiology, both in terms of their frequency and the extent to which they affect different populations.