Identifying populations with chronic pain in primary care: developing an algorithm and logic rules applied to coded primary care diagnostic and medication data.

BACKGROUND: Estimates of chronic pain prevalence using coded primary care data are likely to be substantially lower than estimates derived from community surveys. Most primary care studies have estimated chronic pain prevalence using data searches confined to analgesic medication prescriptions. Increasingly, following recent NICE guideline recommendations, patients and doctors opt for non-drug treatment of chronic pain thus excluding these patients from prevalence estimates based on medication codes. We aimed to develop and test an algorithm combining medication codes with selected diagnostic codes to estimate chronic pain prevalence using coded primary care data. METHODS: Following a scoping review 4 criteria were developed to identify cohorts of people with chronic pain. These were (1) people with one of 12 ('tier 1') conditions that almost always results in the individual having chronic pain (2) people with one of 20 ('tier 2') conditions included when there are also 3 or more prescription-only analgesics issued in the last 12 months (3) chronic neuropathic pain, or (4) 4 or more prescription-only analgesics issued in the last 12 months. These were translated into 8 logic rules which included 1,932 SNOMED CT codes. RESULTS: The algorithm was run on primary care data from 41 GP Practices in Lambeth. The total population consisted of 386,238 GP registered adults ≥ 18 years as of the 31st March 2021. 64,135 (16.6%) were identified as people with chronic pain. This definition demonstrated notably high rates in Black ethnicity females, and higher rates in the most deprived, and older population. CONCLUSIONS: Estimates of chronic pain prevalence using structured healthcare data have previously shown lower prevalence estimates for chronic pain than reported in community surveys. This has limited the ability of researchers and clinicians to fully understand and address the complex multifactorial nature of chronic pain. Our study demonstrates that it may be possible to establish more representative prevalence estimates using structured data than previously possible. Use of logic rules offers the potential to move systematic identification and population-based management of chronic pain into mainstream clinical practice at scale and support improved management of symptom burden for people experiencing chronic pain.

Hospital case-volume is associated with case-fatality after aneurysmal subarachnoid hemorrhage.

BACKGROUND: Inverse association between hospital case-volume and case-fatality has been observed for various nonsurgical interventions and surgical procedures. AIMS: To study the impact of hospital case-volume on outcome after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: We included aSAH patients who underwent aneurysm coiling or clipping from tertiary care medical centers across three continents using the Dr Foster Stroke GOAL database 2007-2014. Hospitals were categorized by annual case-volume (low volume: <41/year; intermediate: 41-70/year; high: >70/year). Primary outcome was 14-day in-hospital case-fatality. We calculated proportions, and used multiple logistic regression to adjust for age, sex, differences in comorbidity or disease severity, aneurysm treatment modality, and hospital. RESULTS: We included 8525 patients (2363 treated in low volume hospitals, 3563 treated in intermediate volume hospitals, and 2599 in high-volume hospitals). Crude 14-day case-fatality for hospitals with low case-volume was 10.4% (95% confidence interval (CI) 9.2-11.7%), for intermediate volume 7.0% (95% CI 6.2-7.9%; adjusted odds ratio (OR) 0.63 (95%CI 0.47-0.85)) and for high volume 5.4% (95% CI 4.6-6.3%; adjusted OR 0.50 (95% CI 0.33-0.74)). In patients with clipped aneurysms, adjusted OR for 14-day case-fatality was 0.46 (95% CI 0.30-0.71) for hospitals with intermediate case-volume and 0.42 (95% CI 0.25-0.72) with high case-volume. In patients with coiled aneurysms, adjusted OR was 0.77 (95% CI 0.55-1.07) for hospitals with intermediate case-volume and 0.56 (95% CI 0.36-0.87) with high case-volume. CONCLUSIONS: Even within a subset of large, tertiary care centers, intermediate and high hospital case-volume is associated with lower case-fatality after aSAH regardless of treatment modality, supporting centralization to higher volume centers.

Variation in Prosthetic Joint Infection and treatment strategies during 4.5 years of follow-up after primary joint arthroplasty using administrative data of 41397 patients across Australian, European and United States hospitals.

BACKGROUND: To identify best practices and quality improvement initiatives, we aimed to assess whether the incidence of Periprosthetic Joint Infection (PJI) and treatment strategies differed across patients treated in Australian, European and United States (US) hospitals. METHODS: Routinely collected administrative data for 41397 patients undergoing a primary total hip or knee arthroplasty between July 2007-December 2010 across 22 hospitals were included. Patients were followed for 2 years looking for PJI occurrence, defined as early (within 4 weeks) and late PJI, and surgical treatment during 2.5 years after PJI diagnosis. Logistic and Poisson regression models were used to test for differences in PJI occurrence and treatment strategies across the three geographical regions, adjusted for age, sex, joint and Elixhauser comorbidity groups. RESULTS: PJI occurrence varied from 1.4% in European to 1.7% in Australian patients, which were significantly higher than US patients after adjustment for patient characteristics (OR 1.24 [1.01-1.52] and 1.40 [1.03-1.91] respectively). Early PJIs varied between 0.3% in European to 0.6% in Australian patients, but adjusted rates were similar. Revision following PJI was significantly lower in Australian than in US patients (OR 0.46 [0.25-0.86]) as were the total number of revisions (RR 0.51 [0.36-0.71]) and number of surgical procedures (RR 0.60 [0.44-0.81]) used to treat PJI. CONCLUSION: The overall PJI rate was significantly higher in Australian patients, but fewer procedures were needed to treat these PJIs. Future research should reveal whether this reflects PJIs caught earlier or less severe when diagnosed, and whether this is associated with the longer length of stay after primary arthroplasty in Australian hospitals.