Flipping the script: The effects of opioid prescription monitoring on specialty-specific provider behavior.

Mandatory access Prescription Drug Monitoring Programs (MA-PDMPs) aim to curb the epidemic at a common point of initiation of use, the prescription. However, there is recent concern about whether opioid policies have been too restrictive and reduced appropriate access to patients with the most need for opioid pharmaceuticals. We assess MA-PDMP's effect on specialty-specific opioid prescribing behavior of Medicare providers. Our findings suggest that requiring providers to query a PDMP differentially affects opioid prescribing across provider specialties. We find a three to four percent decrease in prescribing for Primary Care and Internal Medicine providers. This result is driven by healthcare providers at the lower end of the prescribing distribution. There is also suggestive evidence of an increase in opioid use disorder treatment drugs prescribed by these same providers. We also find no evidence for the hypothesis that MA-PDMPs restrict prescribing by providers who treat patients with potentially high levels of pain, few drug substitutes, or urgency for pain treatment (e.g., Oncology/Palliative care). This result is not dependent on whether a state provides exemptions for these providers. Our results indicate that MA-PDMPs may help close provider-patient informational gaps while retaining a provider's ability to supply these drugs to patients with a need for opioids.

Health care provider decision-making and the quality of maternity care: An analysis of postpartum care in Kenyan hospitals.

Evidence suggests that health care providers' non-adherence to clinical guidelines is widespread and contributes to poor patient outcomes across low- and middle-income countries. Through observations of maternity care in Kenya, we found limited adherence to guideline-recommended active monitoring of patients for signs of postpartum hemorrhage, the leading cause of maternal mortality, despite providers' having the necessary training and equipment. Using survey vignettes conducted with 144 maternity providers, we documented evidence consistent with subjective risk and perceived uncertainty driving providers' decisions to actively monitor patients. Motivated by these findings, we introduced a simple model of providers' decision-making about whether to monitor a patient, which may depend on their perceptions of risk, diagnostic uncertainty, and the value of new information. The model highlights key trade-offs between gathering diagnostic information through active monitoring versus waiting for signs and symptoms of hemorrhage to manifest. Our work provides a template for understanding provider decision-making and could inform interventions to encourage more proactive obstetric care.

Docs with their eyes on the clock? The effect of time pressures on primary care productivity.

This paper examines how time pressure, an important constraint faced by medical care providers, affects productivity in primary care. We generate empirical predictions by incorporating time pressure into a model of physician behavior by Tai-Seale and McGuire (2012). We use data from the electronic health records of a large integrated delivery system and leverage unexpected schedule changes as variation in time pressure. We find that greater time pressure reduces the number of diagnoses recorded during a visit and increases both scheduled and unscheduled follow-up care. We also find some evidence of increased low-value care, decreased preventive care, and decreased opioid prescribing.

Diagnosing and Treating Chronic Pain: Are We Doing This Right?

The diagnosis, treatment, and management of chronic pain is complex, nuanced, and challenging in primary care settings. These challenges often give rise to internal provider conflicts around appropriate management strategies, perhaps avoiding diagnosis all together. Factors that contribute to internal provider conflict include knowledge, responsibility, and uncertainties surrounding chronic pain management. This piece acknowledges the complexity and competing priorities of chronic pain management from a provider perspective. We advocate for coordinated and committed care of patients with chronic pain and a sense of shared responsibility among providers to adequately address patient needs.

Primary Care Physicians' Support of Shared Decision Making for Different Cancer Screening Decisions.

BACKGROUND: Despite its widespread advocacy, shared decision making (SDM) is not routinely used for cancer screening. To better understand the implementation barriers, we describe primary care physicians' (PCPs') support for SDM across diverse cancer screening contexts. METHODS: Surveys were mailed to a random sample of USA-based PCPs. Using multivariable logistic regression analyses, we tested for associations of PCPs' support of SDM with the US Preventive Service Task Force (USPSTF) assigned recommendation grade, assessed whether the decision pertained to not screening older patients, and the PCPs' autonomous v. controlled motivation-orientation for using SDM. RESULTS: PCPs (n = 278) were, on average, aged 52 years, 38% female, and 69% white. Of these, 79% endorsed discussing screening benefits as very important to SDM; 64% for discussing risks; and 31% for agreeing with patient's opinion. PCPs were most likely to rate SDM as very important for colorectal cancer screening in adults aged 50-75 years (69%), and least likely for colorectal cancer screening in adults aged >85 years (34%). Regression results indicated the importance of PCPs' having autonomous or self-determined reasons for engaging in SDM (e.g., believing in the benefits of SDM) (OR = 2.29, 95% CI, 1.87 to 2.79). PCPs' support for SDM varied by USPSTF recommendation grade (overall contrast, X2 = 14.7; P = 0.0054), with support greatest for A-Grade recommendations. Support for SDM was lower in contexts where decisions pertained to not screening older patients (OR = 0.45, 95% CI, 0.35 to 0.56). LIMITATIONS: It is unknown whether PCPs' perceptions of the importance of SDM behaviors differs with specific screening decisions or the potential limited ability to generalize findings. CONCLUSIONS: Our results highlight the need to document SDM benefits and consider the specific contextual challenges, such as the level of uncertainty or whether evidence supports recommending/not recommending screening, when implementing SDM across an array of cancer screening contexts.

The Role of Physicians' First Impressions in the Diagnosis of Possible Cancers without Alarm Symptoms.

BACKGROUND: First impressions are thought to exert a disproportionate influence on subsequent judgments; however, their role in medical diagnosis has not been systematically studied. We aimed to elicit and measure the association between first impressions and subsequent diagnoses in common presentations with subtle indications of cancer. METHODS: Ninety UK family physicians conducted interactive simulated consultations online, while on the phone with a researcher. They saw 6 patient cases, 3 of which could be cancers. Each cancer case included 2 consultations, whereby each patient consulted again with nonimproving and some new symptoms. After reading an introduction (patient description and presenting problem), physicians could request more information, which the researcher displayed online. In 2 of the possible cancers, physicians thought aloud. Two raters coded independently the physicians' first utterances (after reading the introduction but before requesting more information) as either acknowledging the possibility of cancer or not. We measured the association of these first impressions with the final diagnoses and management decisions. RESULTS: The raters coded 297 verbalizations with high interrater agreement (Kappa = 0.89). When the possibility of cancer was initially verbalized, the odds of subsequently diagnosing it were on average 5 times higher (odds ratio 4.90 [95% CI 2.72 to 8.84], P < 0.001), while the odds of appropriate referral doubled (OR 1.98 [1.10 to 3.57], P = 0.002). The number of cancer-related questions physicians asked mediated the relationship between first impressions and subsequent diagnosis, explaining 29% of the total effect. CONCLUSION: We measured a strong association between family physicians' first diagnostic impressions and subsequent diagnoses and decisions. We suggest that interventions to influence and support the diagnostic process should target its early stage of hypothesis generation.

Bayesian Solutions for Handling Uncertainty in Survival Extrapolation.

OBJECTIVE: Survival extrapolation using a single, best-fit model ignores 2 sources of model uncertainty: uncertainty in the true underlying distribution and uncertainty about the stability of the model parameters over time. Bayesian model averaging (BMA) has been used to account for the former, but it can also account for the latter. We investigated BMA using a published comparison of the Charnley and Spectron hip prostheses using the original 8-year follow-up registry data. METHODS: A wide variety of alternative distributions were fitted. Two additional distributions were used to address uncertainty about parameter stability: optimistic and skeptical. The optimistic (skeptical) model represented the model distribution with the highest (lowest) estimated probabilities of survival but reestimated using, as prior information, the most optimistic (skeptical) parameter estimated for intermediate follow-up periods. Distributions were then averaged assuming the same posterior probabilities for the optimistic, skeptical, and noninformative models. Cost-effectiveness was compared using both the original 8-year and extended 16-year follow-up data. RESULTS: We found that all models obtained similar revision-free years during the observed period. In contrast, there was variability over the decision time horizon. Over the observed period, we detected considerable uncertainty in the shape parameter for Spectron. After BMA, Spectron was cost-effective at a threshold of £20,000 with 93% probability, whereas the best-fit model was 100%; by contrast, with a 16-year follow-up, it was 0%. CONCLUSIONS: This case study casts doubt on the ability of the single best-fit model selected by information criteria statistics to adequately capture model uncertainty. Under this scenario, BMA weighted by posterior probabilities better addressed model uncertainty. However, there is still value in regularly updating health economic models, even where decision uncertainty is low.

Value of Information Analysis Informing Adoption and Research Decisions in a Portfolio of Health Care Interventions.

Background: Value of information (VOI) analysis quantifies the value of additional research in reducing decision uncertainty. It addresses adoption and research decisions simultaneously by comparing the expected benefits and costs of research studies. Nevertheless, the application of this approach in practice remains limited. Objectives: To apply VOI analysis in health care interventions to guide adoption decisions, optimize trial design, and prioritize research. Methods: The analysis was from the perspective of Queensland Health, Australia. It included four interventions: clinically indicated catheter replacement, tissue adhesive for securing catheters, negative pressure wound therapy (NPWT) in caesarean sections, and nutritional support for preventing pressure ulcers. For each intervention, cost-effectiveness analysis was performed, decision uncertainty characterized, and VOI calculated using Monte Carlo simulations. The benefits and costs of additional research were considered together with the costs and consequences of acting now versus waiting for more information. All values are reported in 2014 Australian dollars (AU$). Results: All interventions were cost-effective, but with various levels of decision uncertainty. The current evidence is sufficient to support the adoption of clinically indicated catheter replacement. For the tissue adhesive, an additional study before adoption is worthwhile with a four-arm trial of 220 patients per arm. Additional research on NPWT before adoption is worthwhile with a two-arm trial of 200 patients per arm. Nutritional support should be adopted with a two-arm trial of 1200 patients per arm. Based on the expected net monetary benefits, the studies were ranked as follows: 1) NPWT (AU$1.2 million), 2) tissue adhesive (AU$0.3 milliion), and 3) nutritional support (AU$0.1 million). Conclusions: VOI analysis is a useful and practical approach to inform adoption and research decisions. Efforts should be focused on facilitating its integration into decision making frameworks.

Data-Driven Markov Decision Process Approximations for Personalized Hypertension Treatment Planning.

Background: Markov decision process (MDP) models are powerful tools. They enable the derivation of optimal treatment policies but may incur long computational times and generate decision rules that are challenging to interpret by physicians. Methods: In an effort to improve usability and interpretability, we examined whether Poisson regression can approximate optimal hypertension treatment policies derived by an MDP for maximizing a patient's expected discounted quality-adjusted life years. Results: We found that our Poisson approximation to the optimal treatment policy matched the optimal policy in 99% of cases. This high accuracy translates to nearly identical health outcomes for patients. Furthermore, the Poisson approximation results in 104 additional quality-adjusted life years per 1000 patients compared to the Seventh Joint National Committee's treatment guidelines for hypertension. The comparative health performance of the Poisson approximation was robust to the cardiovascular disease risk calculator used and calculator calibration error. Limitations: Our results are based on Markov chain modeling. Conclusions: Poisson model approximation for blood pressure treatment planning has high fidelity to optimal MDP treatment policies, which can improve usability and enhance transparency of more personalized treatment policies.

Risk Stratification and Shared Decision Making for Colorectal Cancer Screening: A Randomized Controlled Trial.

BACKGROUND: Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer (CRC) screening, yet providers often fail to comply with patient preferences that differ from their own. PURPOSE: To determine whether risk stratification for advanced colorectal neoplasia (ACN) influences provider willingness to comply with patient preferences when selecting a desired CRC screening option. DESIGN: Randomized controlled trial. SETTING/PARTICIPANTS: Asymptomatic, average-risk patients due for CRC screening in an urban safety net health care setting. INTERVENTION: Patients were randomized 1:1 to a decision aid alone (n= 168) or decision aid plus risk assessment (n= 173) arm between September 2012 and September 2014. OUTCOMES: The primary outcome was concordance between patient preference and test ordered; secondary outcomes included patient satisfaction with the decision-making process, screening intentions, test completion rates, and provider satisfaction. RESULTS: Although providers perceived risk stratification to be useful in selecting an appropriate screening test for their average-risk patients, no significant differences in concordance were observed between the decision aid alone and decision aid plus risk assessment groups (88.1% v. 85.0%,P= 0.40) or high- and low-risk groups (84.5% v. 87.1%,P= 0.51). Concordance was highest for colonoscopy and relatively low for tests other than colonoscopy, regardless of study arm or risk group. Failure to comply with patient preferences was negatively associated with satisfaction with the decision-making process, screening intentions, and test completion rates. LIMITATIONS: Single-institution setting; lack of provider education about the utility of risk stratification into their decision making. CONCLUSIONS: Providers perceived risk stratification to be useful in their decision making but often failed to comply with patient preferences for tests other than colonoscopy, even among those deemed to be at low risk of ACN.

Factors Affecting Physicians' Intentions to Communicate Personalized Prognostic Information to Cancer Patients at the End of Life: An Experimental Vignette Study.

PURPOSE: To explore the effects of personalized prognostic information on physicians' intentions to communicate prognosis to cancer patients at the end of life, and to identify factors that moderate these effects. METHODS: A factorial experiment was conducted in which 93 family medicine physicians were presented with a hypothetical vignette depicting an end-stage gastric cancer patient seeking prognostic information. Physicians' intentions to communicate prognosis were assessed before and after provision of personalized prognostic information, while emotional distress of the patient and ambiguity (imprecision) of the prognostic estimate were varied between subjects. General linear models were used to test the effects of personalized prognostic information, patient distress, and ambiguity on prognostic communication intentions, and potential moderating effects of 1) perceived patient distress, 2) perceived credibility of prognostic models, 3) physician numeracy (objective and subjective), and 4) physician aversion to risk and ambiguity. RESULTS: Provision of personalized prognostic information increased prognostic communication intentions (P < 0.001, η(2) = 0.38), although experimentally manipulated patient distress and prognostic ambiguity had no effects. Greater change in communication intentions was positively associated with higher perceived credibility of prognostic models (P = 0.007, η(2) = 0.10), higher objective numeracy (P = 0.01, η(2) = 0.09), female sex (P = 0.01, η(2) = 0.08), and lower perceived patient distress (P = 0.02, η(2) = 0.07). Intentions to communicate available personalized prognostic information were positively associated with higher perceived credibility of prognostic models (P = 0.02, η(2) = 0.09), higher subjective numeracy (P = 0.02, η(2) = 0.08), and lower ambiguity aversion (P = 0.06, η(2) = 0.04). CONCLUSIONS: Provision of personalized prognostic information increases physicians' prognostic communication intentions to a hypothetical end-stage cancer patient, and situational and physician characteristics moderate this effect. More research is needed to confirm these findings and elucidate the determinants of prognostic communication at the end of life.

Estimating Cost-Effectiveness in Type 2 Diabetes: The Impact of Treatment Guidelines and Therapy Duration.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) clinical guidelines focus on optimizing glucose control, with therapy escalation classically initiated within a "failure-based" regimen. Within many diabetes models, HbA1c therapy escalation thresholds play a pivotal role, controlling duration of therapy and, consequently, incremental costs and benefits. The objective of this study was to assess the relationship between therapy escalation threshold and time to therapy escalation on predicted cost-effectiveness of T2DM treatments. METHODS: This study used the Cardiff Diabetes Model to illustrate the relationship between costs and health outcomes associated with first-, second-, and third-line therapy as a function of time on each. Data from routine clinical practice were used to contrast predicted costs and health outcomes associated with guideline therapy escalation thresholds compared with clinical practice. The impact of baseline HbA1c and therapy escalation thresholds on cost-effectiveness was investigated, comparing a sodium/glucose cotransporter 2 inhibitor v. sulfonylurea added to metformin monotherapy. RESULTS: Lower thresholds are associated with a shorter time spent on monotherapy, ranging from 1.1 years (escalation at 6.5%) to 13 years (escalation at 9.0%) and an increase in total lifetime cost of therapy. Treatment-related disutility is minimized with higher thresholds because progression to insulin is delayed. Using metformin combined with either dapagliflozin or a sulfonylurea to illustrate lower baseline HbA1c and/or higher therapy escalation thresholds was associated with increased cost-effectiveness ratios, driven by a longer duration of therapy. DISCUSSION: A marked difference in treatment cost-effectiveness was demonstrated when comparing routine clinical practice with guideline-advocated therapy escalation. This is important to both health care professionals and the wider health economic community with respect to understanding the true cost-effectiveness profile of any particular T2DM therapy option.

Risk preferences: consequences for test and treatment thresholds and optimal cutoffs.

Risk attitudes include risk aversion as well as higher-order risk preferences such as prudence and temperance. This article analyzes the effects of such preferences on medical test and treatment decisions, represented either by test and treatment thresholds or-when the test result is not given-by optimal cutoff values for diagnostic tests. For a risk-averse decision maker, effective treatment is a risk-reducing strategy since it prevents the low health outcome of forgoing treatment in the sick state. Compared with risk neutrality, risk aversion thus lowers both the test and the treatment threshold and decreases the optimal test cutoff value. Risk vulnerability, which combines risk aversion, prudence, and temperance, is relevant if there is a comorbidity risk: thresholds and optimal cutoff values decrease even more. Since common utility functions imply risk vulnerability, our findings suggest that diagnostics in low prevalence settings (e.g., screening) may be considered more beneficial when risk preferences are taken into account.