Earlier research has demonstrated a relationship between the presence of psychiatric disorders and increased likelihood of receiving any analgesics among veterans residing in PAC.9 Our study adds to the literature by quantifying opioid response using readily available administrative data and examining associations with psychiatric diagnoses. These findings highlight the possibility that attempting to treat high levels of pain by escalating the opioid dosage in patients with a comorbid psychiatric diagnosis should be re-addressed, particularly if there is no meaningful pain reduction at lower opioid dosages. Our sample had a variety of admission diagnoses and medical comorbidities, however, we did not identify a relationship with opioid responsiveness, including an active cancer diagnosis. Although SUDs were highly prevalent in our sample, there was no relationship with opioid responsiveness. This suggests that lack of response to opioids is not merely a matter of drug tolerance or an indication of drug-seeking behavior.
Factors Impacting Response
Many factors could affect whether an individual obtains an adequate analgesic response to opioids or other pain medications, including variations in genes encoding opioid receptors and hepatic enzymes involved in drug metabolism and an individual’s opioid exposure history.13 The phenomenon of requiring more drug to produce the same relief after repeated exposures (ie, tolerance) is well known.14 Opioid-induced hyperalgesia is a phenomenon whereby a patient’s overall pain increases while receiving opioids, but each opioid dose might be perceived as beneficial.15 Increasingly, psychosocial distress is an important factor in opioid response. Adverse selection is the process culminating in those with psychosocial distress and/or SUDs being prescribed more opioids for longer durations.16 Our data suggests that this process could play a role in PAC settings. In addition, exaggerating pain to obtain additional opioids for nonmedical purposes, such as euphoria or relaxation, also is possible.17
When clinically assessing an individual whose pain is not well controlled despite escalating opioid dosages, prescribers must consider which of these factors likely is predominant. However, the first step of determining who has a poor opioid response is not straightforward. Directly asking patients is challenging; many individuals perceive opioids to be helpful while simultaneously reporting inadequately controlled pain.7,8 The primary value of this study is the possibility of providing prescribers a quick, simple method of assessing a patient’s response to opioids. Using this method, individuals who are responding poorly to opioids, including those who might exaggerate pain for secondary gain, could be identified. Health care professionals could consider revisiting pain management strategies, assess for the presence of OUD, or evaluate other contributors to inadequately controlled pain. Although we only collected data regarding response to opioids in this study, any pain medication administered as needed (ie, nonsteroidal anti-inflammatory drugs, acetaminophen) could be analyzed using this methodology, allowing identification of other helpful pain management strategies. We began the validation process with extensive chart review, but further validation is required before this method can be applied to routine clinical practice.
Patients who report uncontrolled pain despite receiving opioids are a clinically challenging population. The traditional strategy has been to escalate opioids, which is recommended by the World Health Organization stepladder approach for patients with cancer pain and limited life expectancy.18 Applying this approach to a general population of patients with chronic pain is ineffective and dangerous.19 The CDC and the VA/US Department of Defense (VA/DoD) guidelines both recommend carefully reassessing risks and benefits at total daily dosages > 50 OME and avoid increasing dosages to > 90 OME daily in most circumstances.5,20 Our finding that participants taking higher dosages of opioids were not more likely to have better control over their pain supports this recommendation.
Limitations
This study has several limitations, the most significant is its small sample size because of the exploratory nature of the project. Results are based on a small pilot sample enriched to include individuals with at least moderate pain who receive opioids frequently at 1 VA CLC-PAC unit; therefore, the results might not be representative of all veterans or a more general population. Our small sample size limits power to detect small differences. Data collected should be used to inform formal power calculations before subsequent larger studies to select adequate sample size. Validation studies, including samples from the same population using different dates, which reproduce findings are an important step. Moreover, we only had data on a single dimension of pain (intensity/severity), as measured by the pain scale, which nursing staff used to make a real-time clinical decision of whether to administer an as-needed opioid. Future studies should consider using pain measures that provide multidimensional assessment (ie, severity, functional interference) and/or were developed specifically for veterans, such as the Defense and Veterans Pain Rating Scale.21
Our study was cross-sectional in nature and addressed a single 24-hour period of data per participant. The years of data collection (2016 and 2017) followed a decline in overall opioid prescribing that has continued, likely influenced by CDC and VA/DoD guidelines.22 It is unclear whether our observations are an accurate reflection of individuals’ response over time or whether prescribing practices in PAC have shifted.
We did not consider the type of pain being treated or explore clinicians’ reasons for prescribing opioids, therefore limiting our ability to know whether opioids were indicated. Information regarding OUD and other SUDs was limited to what was documented in the chart during the CLC-PAC unit admission. We did not have information on length of exposure to opioids. It is possible that opioid tolerance could play a role in reducing opioid responsiveness. However, simple tolerance would not be expected to explain robust correlations with psychiatric comorbidities. Also, simple tolerance would be expected to be overcome with higher opioid dosages, whereas our study demonstrates less responsiveness. These data suggests that some individuals’ pain might be poorly opioid responsive, and psychiatric factors could increase this risk. We used a novel data source in combination with chart review; to our knowledge, barcode medication administration data have not been used in this manner previously. Future work needs to validate this method, using larger sample sizes and several clinical sites. Finally, we used regression models that controlled for average pre-opioid pain rating scores, which is only 1 covariate important for examining effects. Larger studies with adequate power should control for multiple covariates known to be associated with pain and opioid response.
Conclusions
Opioid responsiveness is important clinically yet challenging to assess. This pilot study identifies a way of classifying pain as relatively opioid nonresponsive using administrative data but requires further validation before considering scaling for more general use. The possibility that a substantial percentage of residents in a CLC-PAC unit could be receiving increasing dosages of opioids without adequate benefit justifies the need for more research and underscores the need for prescribers to assess individuals frequently for ongoing benefit of opioids regardless of diagnosis or mechanism of pain.
Acknowledgments
The authors thank Andrzej Galecki, Corey Powell, and the University of Michigan Consulting for Statistics, Computing and Analytics Research Center for assistance with statistical analysis.