Randomized controlled trial of a clinical decision support system for painful polyneuropathy

Development and Validation of a Treatment Algorithm for Osteoarthritis Pain Management in Patients With End-Stage Kidney Disease Undergoing Hemodialysis

Background

Although osteoarthritis is common in the hemodialysis population and leads to poor health outcomes, pain management is challenged by the absence of clinical guidance. A treatment algorithm was developed and validated to aid hemodialysis clinicians in managing osteoarthritis pain.

Objective

The objective was to develop and validate a treatment algorithm for managing osteoarthritis pain in patients undergoing hemodialysis.

Design

A validation study was conducted based on Lynn's method for content validation.

Setting

To develop and validate a treatment algorithm, interviews were conducted virtually by the primary researcher with clinicians from various institutions across the Greater Toronto and Hamilton Area in Ontario.

Patients

The treatment algorithm was developed and validated for the management of osteoarthritis pain in patients on hemodialysis. Patients were not involved in the development or validation of the tool.

Measurements

The algorithm was measured for content and face validity. Content validity was measured by calculating the content validity index of each component (I-CVI) of the algorithm and the overall scale validity index (S-CVI). Face validity was assessed by calculating the percentage of positive responses to the face validity statements.

Methods

A draft algorithm was developed based on literature searches and expert opinion and validated by interviewing nephrology and pain management clinicians. Through consecutive rounds of 1:1 interviews, content and face validity were assessed by asking participants to rate the relevance of each component of the algorithm and indicate their level of agreeability with a series of statements. Following each round, the I-CVI of the algorithm as well as the S-CVI was calculated and the percentage of positive responses to the statements was determined. The research team revised the algorithm in response to the findings. The final algorithm provides a stepwise approach to the non-pharmacologic and pharmacologic management of pain, including topical, oral, and opioid use.

Results

A total of 18 clinicians from 7 institutions across the Greater Toronto and Hamilton Area were interviewed (10 pharmacists, 5 nurse practitioners, and 3 physicians). The average S-CVI of the algorithm across all 3 rounds was 0.93. At least 78% of participants provided positive responses to the face validity statements.

Limitations

An algorithm was developed based on input from clinicians working in the province of Ontario, limiting the generalizability of the algorithm across provinces. In addition, the algorithm did not include the perspectives of primary care providers or patients/caregivers.

Conclusions

An algorithm for the management of osteoarthritis pain in the hemodialysis population was developed and validated through expert review to standardize practices and encourage clinicians to use evidence-based treatments and address the psychosocial symptoms of pain. As the algorithm possesses a high degree of content and face validity, it may improve osteoarthritis pain management among patients undergoing hemodialysis. Future research will assess the implementation of the algorithm across hemodialysis settings.

Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake

BACKGROUND

Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake.

METHODS

Medline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression.

RESULTS

Among 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake: (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS.

CONCLUSIONS AND RELEVANCE

System uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects.

REGISTRATION

Pre-registered on PROSPERO, CRD42018092337.

The Role of Electronic Medical Records in Reducing Unwarranted Clinical Variation in Acute Health Care: Systematic Review

BACKGROUND

The use of electronic medical records (EMRs)/electronic health records (EHRs) provides potential to reduce unwarranted clinical variation and thereby improve patient health care outcomes. Minimization of unwarranted clinical variation may raise and refine the standard of patient care provided and satisfy the quadruple aim of health care.

OBJECTIVE

A systematic review of the impact of EMRs and specific subcomponents (PowerPlans/SmartSets) on variation in clinical care processes in hospital settings was undertaken to summarize the existing literature on the effects of EMRs on clinical variation and patient outcomes.

METHODS

Articles from January 2000 to November 2020 were identified through a comprehensive search that examined EMRs/EHRs and clinical variation or PowerPlans/SmartSets. Thirty-six articles met the inclusion criteria. Articles were examined for evidence for EMR-induced changes in variation and effects on health care outcomes and mapped to the quadruple aim of health care.

RESULTS

Most of the studies reported positive effects of EMR-related interventions (30/36, 83%). All of the 36 included studies discussed clinical variation, but only half measured it (18/36, 50%). Those studies that measured variation generally examined how changes to variation affected individual patient care (11/36, 31%) or costs (9/36, 25%), while other outcomes (population health and clinician experience) were seldom studied. High-quality study designs were rare.

CONCLUSIONS

The literature provides some evidence that EMRs can help reduce unwarranted clinical variation and thereby improve health care outcomes. However, the evidence is surprisingly thin because of insufficient attention to the measurement of clinical variation, and to the chain of evidence from EMRs to variation in clinical practices to health care outcomes.