Managing Pain with Algorithms: An Opportunity for Improvement? Or: The Development and Utilization of Algorithms to Manage Acute Pain

Standardising analgesic administration for nurses: a prospective intervention study

Background Uncontrolled pain reduces quality of life, delays recovery from surgery and can potentially contribute to the development of chronic pain. Strategies to improve pain management are desirable in view of these detrimental outcomes, yet frequently they are predominately medically based despite nurses playing key roles in pain assessment and analgesic administration. Objective To develop an algorithm-based guidance addressing nurses' pain assessment and analgesic administration and investigating its impact on quality of pain management. Setting Two orthopaedic units in a university hospital. Method An interdisciplinary expert panel consisting of physicians, nurses and clinical pharmacists developed an algorithm-based guidance in analgesic administration for nurses. The guidance was based on current guidelines addressing the appropriate use of analgesics. In a prospective intervention study, clinical pharmacists acted as independent monitors who assessed nurses' pain assessment and analgesic administration before (control period: usual care without any further support) and after implementation of the algorithm-based guidance (intervention period). We evaluated patient-nurse contacts for guideline adherence. We predefined guideline adherence (main outcome) as fulfilling all three of the following criteria: (A) nurses' pain intensity assessment, (B) their assessment of the patients' need for analgesics, and (C) analgesic administration depending on patients' individual pain intensity (including choice of prescribed analgesics). Main outcome measure Adherence to pain management guidelines. Results We analysed 706 patient-nurse contacts with 162 patients in the control and 748 contacts with 168 patients in the intervention period. Without support, guidelines were followed in 6 % of the patient contacts. We achieved an increase to 54 % (p < 0.001) after guidance implementation (main outcome). Guideline adherence decreased with rising pain intensity (slope coefficient -0.763, p < 0.001). Conclusion Especially in patients suffering from severe pain, current guidelines were not strictly followed by nurses when administering analgesics. Guideline adherence improved eightfold by implementing an algorithm-based guidance.

Results of implementing a pain management algorithm in intensive care unit patients: The impact on pain assessment, length of stay, and duration of ventilation

PURPOSE

This study aimed to measure the impact of implementing a pain management algorithm in adult intensive care unit (ICU) patients able to express pain. No controlled study has previously evaluated the impact of a pain management algorithm both at rest and during procedures, including both patients able to self-report and express pain behavior, intubated and nonintubated patients, throughout their ICU stay.

MATERIALS AND METHODS

The algorithm instructed nurses to assess pain, guided them in pain treatment, and was implemented in 3 units. A time period after implementing the algorithm (intervention group) was compared with a time period the previous year (control group) on the outcome variables: pain assessments, duration of ventilation, length of ICU stay, length of hospital stay, use of analgesic and sedative medications, and the incidence of agitation events.

RESULTS

Totally, 650 patients were included. The number of pain assessments was higher in the intervention group compared with the control group. In addition, duration of ventilation and length of ICU stay decreased significantly in the intervention group compared with the control group. This difference remained significant after adjusting for patient characteristics.

CONCLUSION

Several outcome variables were significantly improved after implementation of the algorithm compared with the control group.

Implementation of a pain management algorithm in intensive care units and evaluation of nurses' level of adherence with the algorithm

OBJECTIVES

To implement a pain management algorithm in intensive care units (ICU) and to evaluate nurses' level of adherence with the algorithm.

BACKGROUND

Many ICU patients experience pain. Therefore, an evidence-based algorithm for pain management was developed.

METHODS

A pain management algorithm was implemented in three units over three weeks. Nurses' level of adherence with the algorithm and associations between level of adherence and patient and unit characteristics over 22 weeks were evaluated using multivariate regression analysis.

RESULTS

Nurses' level of adherence was 74.6%. Adherence rates were lower on the evening and night shifts compared to the day shift. Males were assessed significantly less frequently than females. Patients with "injury, poisoning, or certain other consequences of external causes" were assessed significantly less frequently than patients with "diseases of the respiratory system."

CONCLUSIONS

ICU nurses can use a pain management algorithm consistently. Findings from this study suggest that a pain management algorithm is a useful tool to increase ICU nurses' adherence with pain assessment.

One Hospital's Initiatives to Encourage Safe Opioid Use

Pain is the leading reason people seek health care. In an effort to aggressively manage pain in the hospitalized patient, we have seen an increase in the use of opioids. Unfortunately, there has been a similar increase in the number of opioid-related adverse events. As a result, The Joint Commission issued a Sentinel Event Alert in August 2012 with suggested evidenced-based actions to help avoid these adverse events. This article describes one hospital's initiatives to provide opioids safely.