The development of an electronic database for Acute Pain Service outcomes

A Road Map to Creating a High-Quality Clinical Database in Plastic Surgery

BACKGROUND

Detailed in-house databases are a staple of surgical research and a crucial source of data for many studies from which clinical guidelines are built. Despite the importance of generating a clear and thorough developmental design, the literature on database creation and management is limited. In this article, the authors present their stepwise single-institution process of developing a clinical facial fracture database.

METHODS

The authors outline the process of development of a large single-institution clinical pediatric facial fracture database. The authors highlight critical steps from conception, regulatory approval, data safety/integrity, human resource allocation, data collection, quality assurance, and error remediation. The authors recorded patient characteristics, comorbidities, details of the sustained fracture, associated injuries, hospitalization information, treatments, outcomes, and follow-up information on Research Electronic Data Capture. Protocols were created to ensure data quality assurance and control. Error identification analysis was subsequently performed on the database to evaluate the completeness and accuracy of the data.

RESULTS

A total of 4451 records from 3334 patients between 2006 and 2021 were identified and evaluated to generate a clinical database. Overall, there were 259 incorrect entries of 120,177 total entries, yielding a 99.8% completion rate and a 0.216% error rate.

CONCLUSIONS

The quality of clinical research is intrinsically linked to the quality and accuracy of the data collection. Close attention must be paid to quality control at every stage of a database setup. More studies outlining the process of database design are needed to promote transparent, accurate, and replicable research practices.

Associations of Healthcare Utilization and Costs with Increasing Pain and Treatment Intensity Levels in Osteoarthritis Patients: An 18-Year Retrospective Study

Introduction

Osteoarthritis (OA) is a complex disease, and prior studies have documented the health and economic burdens of patients with OA compared to those without OA. Our goal was to use two strategies to further stratify OA patients based on both pain and treatment intensity to examine healthcare utilization and costs using electronic records from 2001 to 2018 at a large integrated health system.

Methods

Adult patients with ≥1 pain numerical rating scale (NRS) and diagnosis of OA were included. Pain episodes of ≥90 days were defined as mild (0–3), moderate (4–6), or severe (7–10) based on initial NRS. Patients were initially classified as mild and moved to moderate-severe OA if any of eight treatment-based criteria were met. Outpatient visits (OP), emergency department visits (ED), inpatient days, and healthcare costs (both all-cause and OA-specific) were compared among pain levels and OA severity levels as frequencies and per-member-per-year rates, using generalized linear regression models adjusting for age, sex, and body mass index, with contrasts of p < 0.05 considered significant.

Results

We identified 127,656 patients, 92,576 with pain scores. Moderate and severe pain were associated with significantly higher rates of OA-related utilization and costs, and all-cause ED visits and pharmacy costs. Moderate-severe OA patients had significantly higher OA-related utilization and costs, and all-cause OP, ED and pharmacy costs.

Conclusions

Pain and treatment intensity were both strongly associated with OA-related utilization but not consistently with all-cause utilization. Our results provide promising evidence of better criteria and approaches for predicting disease burden and costs in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40744-022-00448-7.

Determining chronic pain data elements as a first step towards improving quality of care and research in chronic pain

Background:

Chronic pain is a significant clinical problem in the world. There is still no quite effective treatment for this pain due to its complex nature. Timely retrieval of accurate and comprehensive information through organized clinical and epidemiological studies is an essential prerequisite for providing high quality clinical care and more accurate health planning. We aimed to determine minimum set of data needed as a first step in design and development of a chronic pain registry system.

Materials and Methods:

This descriptive-applied study was carried out in three phases; identifying necessary minimum data, preparing a primary minimum dataset, and surveying expertsby questionnaire.

Result:

The literature review revealed that, theprimary minimum dataset consisted of 51 elements, which were reduced to 41 after applying the experts’ opinion. This dataset covered six areas:demographic information(8 elements), initial pain assessment(12 elements), medical history (8 elements), mental health and well-being(6 elements), diagnostic measures(3elements), and diagnosis and treatment plan (4 elements).

Conclusion:

Determining minimum set of chronic pain data will be an effective step towards integrating and improving information management of patients with chronic pain. It will also allow for proper storage and retrieval of information related to these patients.

The experience of setting up a resident-managed Acute Pain Service: a descriptive study

Background

The benefits of an Acute Pain Service (APS) for pain management have been widely reported, but its diffusion is still limited. There are two APS models: anesthesiologist-based and a nurse-based model. Here we describe the development of a different APS model managed by anesthesia residents, and we report the first year of activity in a tertiary Italian university hospital (Careggi University Hospital, Florence, IT).

Methods

Patients were included in the APS were those undergoing abdominal and urologic surgery causing moderate or severe postsurgical pain. The service was provided for patients, beginning upon their exit from the operating room, for 4, 12, 24 and 48 h for iv, and up to 72 h for epidural therapy. Vital signs, static/dynamic VAS, presence of nausea/vomiting, sedation level, and Bromage scale in case of epidural catheter, were monitored.

Results

From September 2013 to April 2015, a total of 1054 patients who underwent major surgery were included in the APS: 542 from abdominal surgery and 512 from urological surgery. PCA and epidural analgesia were more adopted in general surgical patients than in urology (48 % vs 36 % and 15 % vs 2 %, respectively; P < 0.0001). Patients who underwent to abdominal surgery had a significantly higher self-administration of morphine (30.3 vs 22.7 mg; P = 0.0315). Elastomeric pump was the analgesic of choice in half of the urologic patients compared to a quarter of the general surgical patients (P < 0.0001). Among the different surgical techniques, epidural analgesia was used more in open (16.5 %) than in videolaparoscopic (1.9 %) and robotic technique (1.1 %), whereas PCA was predominant in videolaparoscopic (46.5 %) and robotic technique (55.5 %) than in open technique (31.4 %).

Conclusions

The creation of APS, managed by anesthesia residents, may represent an alternative between specialist-based and nurse-based models.

Developments in the use of e-health for chronic pain management

SUMMARY Recognition that changes are required in how chronic conditions are managed, combined with advances in technology, has led to the emergence of e-health as a possible solution. This selective review seeks to illustrate some of the ways in which e-health has been applied to chronic pain. Examples of technology use are provided within the areas of information provision, assessment and monitoring, and remote therapy, and the various strengths and weaknesses associated with each method are highlighted. One of the main concerns is that, despite enthusiastic promises, evidence of e-health for pain management is often based on small numbers and few randomized controlled trials. However, the situation is improving, especially within the field of internet-based interventions where the number of higher quality trials is increasing, and results to date are encouraging. A sense of cautious optimism seems reasonable when considering the potential of e-health for the management of chronic pain.