Barbara Bokhour, PhD

 A false-positive mammogram can result in anxiety, distress, and increased perceptions of breast cancer risk, potentially changing how women utilize healthcare. This study examined whether having an abnormal mammogram, considered a proxy for elevated risk perception, was associated with greater future health service use (outpatient visits and referrals).

 A retrospective cohort study using electronic health record data, spanning 2008 to 2012, from Boston Medical Center, a safety-net hospital.

 We grouped 3920 women aged 40 to 75 years receiving primary care and who had a mammogram between 2010 and 2011 into 3 categories: false-positive mammogram at index date; previous false positive, but normal index mammogram; and no history of false-positive mammograms. We contrasted the longitudinal changes in outpatient visits and provider referrals, before versus after the index mammogram, between women with false-positive mammogram and those without using Poisson regression models with a difference-in-differences specification. Clinical, visit, and demographic data were obtained from the institutional clinical data warehouse.

 Adjusting for baseline differences in sociodemographic characteristics across risk groups and for secular changes between pre- and postindex periods, a current false-positive mammogram was associated with an 18% increase in overall outpatient visits (incidence rate ratio [IRR], 1.18; 95% CI, 1.07-1.51), but no corresponding increase in provider referrals (IRR, 1.15; 95% CI, 0.99&#8209;1.34), relative to never having a false positive. A previous false-positive mammogram had no associated change in outpatient utilization (IRR, 0.99; 95% CI, 0.91-1.07).

 Providers should discuss the implications of mammography findings at the time of screening to help mitigate potential detrimental effects and promote appropriate engagement in health services.

We used a difference-in-differences approach to measure changes in healthcare utilization associated with false-positive mammography. A current false positive was associated with an 18% increase in outpatient visits, but no increase in provider referrals, relative to women with no false positive.

Trends encouraging mammography adherence increase opportunities for false positives, which we have shown to impact short-term health service use.

Counseling about potential false positives and their meaning prior to screening may mitigate the anxiety experienced at the time of an abnormal mammogram.

Interventions to ensure appropriate utilization are needed to address women’s concerns while promoting evidence-based care.

Despite debate about the benefits and harms of screening mammography,

 it remains the best available tool to detect breast cancer early and prevent morbidity and mortality. As such, the majority of women participate in mammography screening. In 2013, the CDC estimated that 69.1% of women older than 50 years underwent mammography

 as recommended by the United States Preventive Services Task Force.

 Identified harms of mammography include a high prevalence of false positives, need for additional imaging and biopsies, potential overdiagnosis of breast cancer, radiation exposure, and masking bias in dense breast tissue.

 These issues have received extensive attention in the literature and are important concepts for women to understand when considering screening.

False-positive mammograms and the resulting psychosocial harms have garnered attention in recent years.

 Over a 10-year screening period, the cumulative probability of a false-positive mammogram is 42% to 61%, depending on screening interval.

 Anxiety and distress are common among those experiencing a false-positive mammogram, with effects persisting in the months following the test.

 The prevalence of false positives and documented negative psychosocial outcomes are, in part, the basis for not routinely screening women younger than 50 years, who are more frequently affected by these outcomes.

 Guidelines instead promote shared decision making for these women, although this ideal is not often realized in practice.

 Research has shown that women are not often aware of the harms of mammography, including the potential for false-positive findings and future testing.

Having a false-positive mammogram is further associated with increases in individuals’ risk perceptions, despite no actual change in risk or health threat,

 that can persist long after the abnormal test and affect health service use.

 Although there is interest in determining the multidimensional benefits and harms associated with screening and risk communication, the effects of designating individuals as “at risk” on healthcare utilization measures beyond the downstream diagnostic workup are understudied. This is a critical gap in knowledge at a time when improving cancer screening rates is emphasized through payment schemes intended to improve quality of care.

 Yet the process of undergoing a mammogram and receiving results may change the way a woman conceptualizes her health and engages with the medical system. Understanding the impact of these tests on how women utilize healthcare services over time is needed to improve the quality of care.

This study examined whether having an abnormal mammogram, considered a proxy for elevated risk perception,

 was associated with greater future health service use. Previous studies have examined breast-specific health service use in relation to other clinical markers of risk status, such as genetic mutations or family history.

 This study expanded the measure of healthcare utilization beyond breast-specific services among a population of women undergoing mammography. We hypothesized that women who experienced a recent or previous false positive would have higher postmammogram visit and referral rates relative to women without false-positive mammograms. Although we were unable to fully characterize the purpose and content of these outpatient visits and referrals, this study sought to deliver an initial assessment of healthcare utilization changes following a false-positive test result, establishing the basis for a detailed exploration of such visits and assessment of whether additional service use represents value-based care.

This retrospective cohort study examined whether experiencing a false-positive mammogram recently or in the past was associated with healthcare utilization by comparing rates of outpatient visits and referrals in the 2 years prior to an index mammogram with 1 year following. This study was determined to be exempt by the Boston University Medical Campus Institutional Review Board.

Utilization data came from Boston Medical Center (BMC), an urban safety-net hospital. Included women: 1) were aged 40 to 75 years, 2) received primary care at BMC, 3) had a screening mammogram at BMC in 2010 or 2011 that did not result in a cancer diagnosis, and 4) had their first mammogram at 40 years or older. Women receiving primary care at BMC were identified by a documented visit with a designated provider in the preceding 2 years. Prior work has demonstrated that these patients use the hospital system as their main source of care for all conditions, including emergency and specialist care.

 The first mammogram during 2010 or 2011 was defined as the index mammogram. Women with a prior cancer or cancer diagnosed during the study period or those who died during the study were excluded.

Administrative and clinical data were obtained through the clinical data warehouse, a comprehensive database that aggregates data from multiple electronic hospital sources. The use of retrospective clinical data provided a measure of actual utilization rates, eliminating bias from self-reported data. Data collected spanned calendar years 2008 to 2012.

We used a difference-in-differences (DID) approach, which measures the difference in utilization before and after the index mammogram for women who experienced a false-positive mammogram and contrasts this difference with the corresponding difference for women who experienced no false-positive mammogram.

 This approach adjusts for pre-index differences in utilization between the 2 groups and secular changes in utilization between pre-index and postindex periods. We defined the 2-year period before and 1-year period after the index mammogram visit as the pre-index and postindex periods, respectively. This provided a stable measure of utilization prior to the index mammogram and allowed for assessment of bias that may have threatened internal validity.

An abnormal mammogram was defined using criteria of the 

Breast Imaging Reporting and Data System (BI-RADS) Atlas

 1 (normal) or 2 (benign) classifications. 

 scores of 0 (incomplete), 3 (probably benign), 4 (suspicious), or 5 (highly suggestive of malignancy) were included in the abnormal mammogram group, as they required a follow-up or further testing. False positives were defined as those abnormal findings that did not result in a cancer diagnosis as assessed by the Tumor Registry.

 results were used to create 3 groups of women that reflected levels of risk designation

: 1) current false positive (high risk): women experiencing a false-positive mammogram at the index date and indicative of high risk perception; 2) previous false positive (intermediate risk): women who had a normal mammogram result on the index date with a false-positive result in the past; and 3) no false positives (low risk): women who had a normal index mammogram result and no previous false-positive results. We distinguished current from previous false-positive mammograms to test if changes in utilization following a current false positive would persist over time.

We examined 2 utilization indicators as outcomes: referrals and outpatient visits. The number of referrals measured provider-initiated orders for health services and was totaled for each time period. Referrals were captured as “orders,” and all types (ie, specialty visits, laboratory) were compiled to measure the total count documented in the medical record over each time frame. Counts of all outpatient visits attended for each 12-month period were also measured and included all primary care, specialty, emergency department, laboratory, and procedure visits. Diagnostic tests included in the follow-up for an abnormal mammogram were excluded.

Demographic covariates included age, race/ethnicity, insurance, education, and primary language. Baseline comorbidities were measured by identifiying all unique diagnosis codes (

International Classification of Diseases, Ninth Revision, Clinical Modification

]) in the pre-index period and grouping them into 30 categories using the Elixhauser classification.

 A dichotomous indicator variable for time (pre-index vs post index) was created and later interacted with the 3 groups to assess differences over time by group.

Comparison of Pre-Index Longitudinal Trends Between Comparison Cohorts

A critical assumption underlying the appropriateness of the DID design was that the longitudinal trends in utilization for the 2 comparison cohorts, women with a current or previous false-positive mammogram versus those without, diverged from a parallel trajectory only after the false-positive mammogram event; that is, prior to this event, the longitudinal trends between the 2 groups should have followed similar trends (ie, were parallel).

 We tested this “parallel trends” test by using only pre-index event data, dividing the 2 pre-index years of utilization into 2 single-year utilization periods; estimated a similarly specified DID model limited to only the pre-index data; and tested if the changes in utilization between the 2 years were similar between the 2 comparison groups (current vs never; previous vs never). Confirmation of parallel trends enhanced the ability of the main DID model (with complete data) to attribute postindex utilization changes to false-positive mammograms.

Another potential source of confounding was systematic differences in the prevalence of the observed demographic and socioeconomic covariates and pre-index utilization between the groups of women compared. One approach to adjust for potential imbalance was the use of propensity score weighting known as standardized mortality ratio weighting (SMRW).

 In this 2-step method, we first estimated a logistic regression of the indicator of false-positive mammogram (0/1) on age, race, language, education, insurance, Elixhauser categories, and pre-index visits (or referrals) to obtain the predicted probability of false-positive mammogram (propensity score); in the second step, we estimated the main regression model using SMRW, wherein women with false-positive mammograms were assigned a weight of 1 and women without false-positive mammograms were assigned a weight equal to the ratio of the propensity score to 1 minus the propensity score.

 The propensity score weighting was used to produce comparable groups with parallel pre-visit trends.

We performed descriptive analyses and examined patient characteristics by group. Our core analysis estimated the change in each utilization outcome associated with a current (at index mammogram) or previous false-positive mammogram (prior to index, with normal index mammogram) using a weighted Poisson regression model with a DID specification.

 Multivariable models adjusted for covariates, including comorbidities present at the index mammogram. Two models for each outcome were constructed: one to compare the current versus never false-positive groups and the other to compare the previous versus never false positive-groups. Thus, 4 final DID models were run to account for selection of appropriate comparison groups via propensity score weighting.

The primary independent variable of interest in the DID specification was the interaction between time and having a false-positive mammogram result, which compared the average difference in utilization in the pre- versus postindex mammogram periods for the current and previous false-positive mammogram groups compared with those with no false-positive mammograms. We hypothesized that a current false-positive would result in higher rates of referrals and outpatient visits in the follow-up period, as women might feel that they are at higher risk.

To perform the parallel trends test described above, we estimated an identically specified weighted Poisson DID model, with the data limited to the pre-index period and with utilization in the 2 pre-index years as the 2 periods compared. All analyses were perfomed in SAS version 9.3 (SAS Institute Inc; Cary, North Carolina). Estimates are reported as incidence rate ratios (IRRs) with 95% CIs. Statistical significance was set at α = .05 for all models.

False-positive rates may be confounded by age due to differences in the properties of mammography and breast tissue structure.

 We conducted a sensitivity analysis to assess the influence of age, stratifying the sample into 2 groups (40-49 and 50-75 years). As Poisson models may not capture overdispersion in outcomes, we performed estimation using negative binomial distribution models.

The sample included 3920 women who met inclusion criteria (

). Almost half (42%) were women for whom routine screening was universally recommended (aged 50-64 years), 52% were black, and 61% spoke English as their primary language. Most had public insurance (55%), and 41% had less than a high school education. Seventy-six percent of women had at least 1 Elixhauser-defined comorbid condition. The previous false-positive group had the highest prevalence of 1 or more comorbidities at 80.3% versus 75.6% in the no false-positive group and 71.4% in the current false-positive group (details in 

Associations Between Demographics and Risk Groups

Sample characteristics identified the demographic correlates of false-positive mammograms. The current false-positive group was younger than the other 2 groups (

= .02) was the only other characteristic significantly associated with risk group. Unadjusted visit rates over time by risk group are displayed in 

. Testing differences in these trends across the pre-index period using the SMRW propensity score method resulted in nonsignificant associations, suggesting that the parallel trends assumption was satisfied.

Changes in Utilization Associated With a False-Positive Mammogram

Adjusting for baseline differences in socio&shy;demographic characteristics across groups and for secular changes between the pre- and postindex periods, a current false-positive mammogram was associated with an 18% increase in overall outpatient visits (IRR, 1.18; 95% CI, 1.07-1.51) (

). In contrast, a previous false-positive mammogram had no associated change in utilization (IRR, 0.99; 95% CI, 0.91-1.07). Educational achievement, insurance coverage type, and baseline comorbidities were associated with systematic differences in outpatient visits in the pre- and postindex periods.

Contrary to the hypothesis, women with current false positives saw no increase in referral rates (IRR, 1.15; 95% CI, 0.99-1.34). Those with previous false positives also did not have a significant change in referral rates (IRR, 0.99; 95% CI, 0.83-1.20). Although point estimates for referrals were similar to the visit outcome, differing baseline outcome rates resulted in varying magnitudes, affecting the significance of the association. Nonwhite race, having public insurance, and baseline comorbidities were associated with higher referral rates.

A stratified analysis by age was conducted to account for the lower sensitivity and specificity of mammography for younger women

). The increase in visits associated with a false positive appeared to be driven by women younger than 50 years, with no significant change in utilization for older women (IRR, 1.13; 95% CI, 0.97-1.31); however, the general trend was similar. Stratifying by age, older women (aged 50-74 years) with current false positives received significantly fewer referrals compared with those without false positives (IRR, 0.85; 95% CI, 0.79-0.92), whereas there was no significant difference in referral rates across false-positive groups among younger women (aged 40-49 years). Estimates of change for the current and previous false-positive groups were robust when re-estimating the models using a negative binomial model.

Having a false-positive mammogram was associated with significantly increased rates of outpatient visits in the year following the test, suggesting that utilization may be driven by patients seeking care, but is likely not generated by the health system as there was no corresponding increase in referrals for care. Increased utilization dissipated over time: We found comparable visit and referral rates between those with a previous false positive and a recent normal mammogram and those with no false-positive mammograms.

One striking finding from this study was the marked increase in outpatient visits following an abnormal mammogram. Although increased breast-specific utilization is expected in order to rule out a cancer diagnosis,

 the reasons for increases in other types of care are less obvious. Our findings could indicate that women may conceptualize themselves as less healthy than prior to their false-positive mammogram

 or that they may experience increased anxiety, leading to additional visits that increase reassurance through monitoring. Prior study findings have confirmed that increases in utilization may be related to the negative psychosocial outcomes of having a false-positive mammogram, showing increases in mental health services following the receipt of an abnormal mammogram.

Undergoing imaging and receiving a normal result has been characterized as a “gift of knowing,” providing reassurance to those who engage in screening.

 This reassurance may be driving decreases in utilization in the previous false-positive group. This group was possibly reassured of good health with the normal mammogram result, thus removing the impetus to continue higher rates of utilization. The increase in immediate post—false-positive visits suggests that communication at the time of mammogram or in the immediate postmammogram period may be required to mitigate short-term anxiety and increased utilization. This may be particularly true for underserved populations similar to those studied here: We found that women with a high school education and black women had significantly more utilization associated with a false positive. This finding is similar to others that have noted that minority and low-literacy women experience higher distress and lower understanding when presented with abnormal mammogram results relative to white and high-literacy women.

 Interventions targeted toward these populations, such as patient navigation, have been shown to decrease anxiety following a false positive,

 but navigator effects on utilization beyond the diagnostic follow-up are limited. Prospectively understanding the role of anxiety generated by a false-positive test in subsequent healthcare utilization is required to tailor interventions to promote appropriate, high-quality care to women undergoing mammography screening.

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This study demonstrated that a false-positive mammogram was associated with increases in outpatient visits, but not provider referrals, for 1 year post mammogram.

False-Positive Mammography and Its Association With Health Service Use

 Polypharmacy and adverse drug events lead to considerable healthcare costs and morbidity, yet there is little to guide clinical providers in the area of discontinuing medications that may not be necessary. We sought to understand providers’ beliefs and attitudes about polypharmacy and medication discontinuation.

Qualitative study using semi-structured interviews of 20 providers with prescribing privileges at 2 US Veterans Affairs Medical Centers, from April 2012 to October 2012.

 Transcribed interviews were analyzed using grounded thematic analysis, a systematic approach to deriving qualitative themes from textual data.

 We identified 10 themes within 4 domains of medication discontinuation. Within the first domain (medication factors), we identified 2 themes: 1) medication characteristics, and 2) uncertainties of why a patient was taking a particular drug. Within the second domain (patient factors), we identified 3 themes: 3) clinical picture of the patient, 4) clinicians’ understanding of the patients’ knowledge and beliefs, and 5) patients’ adherence. Within the third domain (clinical provider factors), we identified 2 themes: 6) professional identity, and 7) providers’ decisions related to their own beliefs about medications. Within the fourth domain (system factors), we identified 3 themes: 8) multiple providers, 9) workload, and 10) external directives and policies such as structural components of a healthcare system.

 Provider decisions to discontinue medications are affected by factors at all levels of the clinical encounter. Our findings have implications for development and implementation of interventions to improve appropriate medication discontinuation via enhanced medication reviews, enriched patient-provider communication, and better system-level structures. This, in turn, may reduce the continued prescribing of potentially inappropriate medications that can lead to adverse outcomes or increased healthcare costs.

Clinical providers express concerns about polypharmacy but receive little guidance on how to make decisions about medication discontinuation. Until now, there has been little understanding of providers’ perceptions of factors affecting these decisions.

		Factors at the level of medications, patients, providers, and the healthcare system itself contribute to decision making about medication discontinuation.

		Understanding these factors will enable the development and implementation of interventions to improve appropriate discontinuation, and in turn, potentially reduce adverse drug events and uncontrolled healthcare costs.

Polypharmacy, often defined as a patient taking 5 or more medications,

is common. Roughly 40% of adults 65 years or older experience polypharmacy, with a similar prevalence in active users of Department of Veterans Affairs (VA) facilities.

 A greater number of medications is associated with risk of adverse drug events (ADEs), which leads to increased healthcare utilization, costs, and morbidity.

 Moreover, physicians may interpret subtle adverse physiologic effects as a distinct problem and add medication to treat them; such a “prescribing cascade” can lead to increased rates of polypharmacy.

Providers’ perceptions of polypharmacy, as well as barriers to and facilitators of mitigating it through proactive medication discontinuation, are unclear. Clinicians lack evidence of best practices for evaluating patients’ medication regimens to determine which drugs, if any, may safely be discontinued, especially for ambulatory care patients. Several studies have demonstrated the feasibility and safety of withdrawing particular classes of medications, but many focus on inpatients and residents of long-term care facilities.

 While medication adherence and medication reconciliation have emerged as health system priorities, little attention has been paid to promoting the discontinuation of medications that may not be necessary or whose benefits no longer outweigh associated risks. Experts have suggested that the “time until benefit” of a medication be compared with life expectancy in elderly populations to aid in decisions about its continued use.

Whether clinicians consider such risk-benefit balances in the general adult population is unknown.

Appropriate cessation of a medication could lead to a reduction in ADEs and to improved health outcomes, yet little is known about factors that inhibit or facilitate providers’ discontinuation of medication. Therefore, we sought to understand how providers make decisions about medications in a complex population by identifying their beliefs and attitudes about polypharmacy, as well as their perceptions of the factors that influence decisions and actions related to medication discontinuation. Based on prior literature, we hypothesized 4 domains related to discontinuation: medication, patient, provider, and system (

); and we sought to identify key themes within each domain to inform future interventions to improve medication discontinuation.

We conducted a qualitative study using in-depth interviews of primary care providers and pharmacists at 2 US VA Medical Centers. Qualitative methods are useful for understanding new areas and generating data to inform future research. We explored attitudes toward medication reconciliation, polypharmacy, patient-provider communication, and decision making about discontinuing medication. Institutional review boards at both sites approved the study.

At primary care staff meetings, the lead investigator (AL) introduced the study and distributed recruitment materials describing the project objective of understanding decision making, communication, and factors associated with medication discontinuation. Providers with prescribing privileges—including physicians, nurse practitioners (NPs), and pharmacists&mdash;were eligible to participate. Within the VA, clinical pharmacists are authorized to initiate, titrate, and discontinue medications. All eligible providers (n = 63) were subsequently invited to participate, and a convenience sample was scheduled for interviews. All participants provided written informed consent; no stipend was provided.

The lead investigator conducted individual, in-person, in-depth, semi-structured interviews of 30 to 60 minutes’ duration between April 2012 and October 2012. We queried providers’ views and conduct of medication reconciliation, communication with patients, interactions with colleagues, beliefs about medications, polypharmacy, and experience with discontinuing medications. The interviewer used the Interview Guide for Providers (see 

) flexibly and followed up on unanticipated issues raised by participants.

Interviews were audio-recorded, transcribed verbatim, and reviewed for accuracy. Transcripts were analyzed qualitatively using procedures informed by grounded theory methodology,

a systematic approach to deriving qualitative themes from textual data. This approach begins with open coding, in which investigators identify key concepts emerging from the language used by participants and assign codes (descriptive phrases) to segments of text. We began analyses using sensitizing concepts surrounding polypharmacy and medication discontinuation.

Using NVivo qualitative analysis software (QSR International, Doncaster, Australia),

the lead investigator and a research assistant (TBM) coded 4 interviews independently, and through discussion came to consensus on code definitions to develop a coding dictionary. The remaining interviews were coded by the lead investigator, who refined the dictionary as needed. Throughout, detailed coded text segments were reviewed, discussed, and revised if needed by 2 investigators (AL, BB) before the text was condensed into broader themes. Prominent themes and exemplifying quotes were discussed by the research team, and each theme was mapped to one of the 4 domains (medication, provider, patient, and system factors) that comprised our conceptual model. Themes that could have been mapped to multiple domains were assigned the best fit through consensus discussion.

We interviewed 20 providers (8 male, 12 female; 15 site A, 5 site B), with a range of experience in clinical practice (2 to 39 years; median 21) and in the VA (2 to 30 years; median 15). The majority (n = 11) were physicians, with 3 NPs and 6 pharmacists. Twenty interviews were sufficient to achieve thematic saturation, where at a certain point no new concepts appeared. Ten themes emerged, each mapping to 1 of 4 domains influencing the process of proactive medication discontinuation (Figure). Exemplifying quotes that best represent the general sense of each theme can be seen in the 

Medication characteristics. Characteristics of medications, such as the number of daily doses, therapeutic duplication, or whether 1 medication could address 2 problems, influenced clinicians’ decisions when reviewing regimens. Many reported paying particular attention to specific medication classes as potential targets for discontinuation (eg, proton pump inhibitors, statins, opioid pain medications). Reducing or discontinuing pain medications was described as more complicated due to perceived patient reluctance.

Providers spoke at length about the difficulties of decision making with unclear medication indications. Multiple reasons for uncertainty were suggested, such as a patient’s inability to state the reason for his medication, or the presence of an associated indication that might not reflect the true rationale for the medication’s use. For some of their patients, the default for some providers was to maintain the status quo in the absence of a clear reason to stop a medication, despite uncertainty. For other patients, a trial of discontinuation would evaluate its necessity.

 Providers noted that the presence of multiple comorbid conditions—each of which might require 1 or more medications&mdash;inhibited discontinuation. Conversely, a geriatric patient’s age sometimes triggered discontinuation because of concerns related to polypharmacy, decline in drug metabolism, or shifts in the risk-benefit ratio due to changes in perceived life expectancy&mdash;especially for patients with terminal cancer. Impaired patient cognition also made clinical decision making difficult because of uncertainties about whether the recommended changes would be accurately understood and implemented.

The intended and unintended medication effects were key to medical decision making. Providers felt it was important to elicit whether a medication was providing symptomatic relief, despite noting that paradoxically, such evaluations were infrequent. In a related process, medications were often stopped on a trial basis to see if symptoms returned after discontinuation. Providers thought it important to assess for side effects warranting reactive discontinuation, but patient-reported side effects (eg, dizziness) were felt to be more difficult to ascertain than measurable ones (eg, low blood pressure).

Perception of the patient’s knowledge and beliefs.

 Another important factor influencing providers’ decisions to discontinue medications was their perception of the patient’s knowledge, beliefs, and preferences about taking medications. Clinicians spoke about how patients’ better comprehension of their conditions and medications often facilitated conversations about stopping a medication, albeit not always resulting in discontinuation. Patients viewed as having limited understanding made it challenging for clinicians to ensure that medications were taken as directed. At the same time, providers recognized that such patients often would “follow doctor’s orders,” thus facilitating discontinuation if called for.

Providers were influenced by patients’ beliefs about a medication's importance; clinicians felt that patients generally prioritize medications that treat symptoms (eg, pain or heartburn). Moreover, some providers endorsed the notion that patients receive “psychological comfort” from continuing medicines they have been taking for a long time.

A major factor that challenged providers’ ability to make decisions about discontinuation was uncertainty regarding a patient’s adherence to medication. Clinicians often felt that even if they obtained an accurate medication list, questions remained about how consistently adherent patients were to those medicines. Many clinicians spoke about the need to have additional contact with the patient in order to derive an updated medication list—considered essential for prescribing decisions.

Providers discussed how their background and job descriptions created a sense of identity that enabled them to make prescribing decisions. Many spoke about the responsibility they felt to provide appropriate, comprehensive care with ultimate accountability for medication decisions. Previous experience—and success&mdash;in discontinuing medications provided confidence for providers to attempt discontinuation in the future. Other providers expressed hesitation to alter regimens for a medication that fell outside their scope of practice, for which they had little experience prescribing, or that another clinician was actively managing.

 Providers’ perceptions of polypharmacy—its definition, prevalence, and importance&mdash;may be critical to decisions about discontinuation. Deciding at what point patients were taking “too many” medications varied, and polypharmacy was considered to be quite prevalent and even the norm. When asked to define polypharmacy, numeric answers ranged from 2 to 12 medications, and many said it depended on the patient.

 For patients who obtained medications from providers in other healthcare systems, participants felt limited in their ability to make changes and noted that communication across systems was often difficult. Providers also discussed how the duration and quality of their relationships with patients influenced the patients’ views on whom they trusted most to make decisions.

 Core job duties and perceived workload were frequently cited as influential factors in prescribing decisions. Clinicians viewed discontinuing a medication as a complex process requiring an explicit decision, patient-provider communication, and possibly longitudinal monitoring to assess outcomes. These extra steps were seen as additional work compared with medication renewal.

Most physicians spoke of the potential for nurses and pharmacists to aid in medication reconciliation—an often time-consuming process&mdash;to allow time for other clinical issues; however, 1 physician had reservations about tasking another team member with this role. With better schedule capacity to monitor patients closely longitudinally, pharmacists embraced expanded roles that facilitated medication discontinuation.

Providers felt burdened by the current electronic clinical reminders, several of which are intended for performance measurement. Policies that dictate benchmarking goals were viewed as inhibiting discontinuation because of the need to use medications to achieve targets, regardless of patient age or treatment preferences.

Providers had mixed views regarding the influence of information technology (IT) on medication discontinuation. For example, by using the electronic health record, providers could ascertain whether the pharmacy had recently dispensed medications, at times leading them to discontinue medications that patients were no longer taking. In contrast, inaccurate problem lists led to uncertainties about the appropriateness of medications, and complicated decision making. Providers felt there was untapped potential for IT to aid in clinical decision making specifically related to discontinuing medications, but were wary of adding more electronic reminders or alerts.

Polypharmacy and adverse drug events lead to significant healthcare costs and morbidity, yet there is little information to guide clinical providers in the process of discontinuing medications in the general adult population. Providers in our study had clear, but varying, views on issues surrounding medication discontinuation, which supported the hypothesized domains in our conceptual model of factors affecting discontinuation decisions. Although themes were determined to primarily relate to 1 domain, overlap of codes from multiple domains was not uncommon. For example, indication uncertainty—a medication-related factor&mdash;also related to patient and system factors. This interrelatedness is informative for critical focus of interventions in the future to improve medication reviews, patient-provider communication, and systemlevel structures that will result in appropriate medication discontinuation.

Providers expressed concern about the adverse consequences of using medications inappropriately and supported the notion of reducing unnecessary drugs. However, they faced many difficulties in a typical clinical encounter, such as patient complexity, uncertainty, interactions with other healthcare providers, and constraints imposed by the healthcare system.

Participants indicated they generally attempt to minimize pill quantity, and thereby improve patient adherence,

although this approach was complicated by uncertainties about the medication’s original indication—particularly when another provider initiated the prescription. Given the frequency with which uncertainty was discussed, a potential IT-based intervention that requires each prescription to include the indication could facilitate future decision making. Some healthcare systems do this currently, but its effect on decision making is unknown.

 Including the indication would enhance communication between healthcare systems, and would be helpful when a provider “inherits” a patient from another clinician.

A key factor impacting discontinuation decisions was the provider’s perception of what the patient preferred. Providers may not accurately assess beliefs, and they may overestimate the degree to which they understand their patients.

The resulting knowledge gaps could result in continued prescribing of a particular drug, despite a lack of provider belief in its medical necessity.

 When a patient feels strongly about continuing a medication, understanding the underlying reasons through high-quality patient-provider communication may enable the provider to deliver information targeted to those beliefs, or lead to a compromise, such as a lower dose. Conversely, identifying patients who welcome a reduction in pills may facilitate appropriate discontinuation.

Finally, given that patients are nonadherent to approximately half of their medications,

discontinuing medicines with lower potential benefit may improve adherence to those remaining, with concomitant better health outcomes.

While research and performance measures frequently use a cutoff of 5 medications to define polypharmacy, many study participants felt that patients often require at least that many to manage their comorbidities. This observation is consistent with other research suggesting that defining polypharmacy using a specific numeric threshold is not clinically useful.

Consequently, any intervention to raise awareness of polypharmacy must be account for the possibility that 5 may not be a sufficient number of medications to prompt clinicians to review regimens for potential discontinuation. Further, discontinuation may also be relevant for patients not meeting a prespecified numeric definition of polypharmacy.

Clinicians may feel empowered by a successful prior experience discontinuing a medication, leading them to make similar decisions in the future. While our study was not intended to discern differences between types of providers, we did note that physicians appeared to be more comfortable discontinuing medications than other clinical providers, even if the medications were initially prescribed by subspecialists. As the scope of practice for NPs expands, their perceptions of autonomy may change and influence empowerment to make specific prescribing decisions.

Whether a provider felt “ownership” of a medication also varied, and the ability to make recommendations could be influenced by whom the patient trusted most to make those decisions. Identification of provider characteristics that are associated with proclivity to discontinue medications could provide focus for tailored interventions aimed at the clinical provider.

Interaction between providers was greatly affected by system-level factors. It was felt that better information transmission occurred between providers within the same healthcare system; however, while meaningful use of electronic health IT aims to break down these barriers, data transmission between sites is still limited.

Having a complete, accurate record of all prescription and nonprescription drugs for a patient is prerequisite to making informed clinical decisions and capitalizing on electronic decision support systems.

There is potential to tap into the power of electronic systems to support clinicians in determining whether a medication may be appropriate for discontinuation trial, such as when a relevant indication in the problem list is absent, or when the prescription has surpassed a specified duration of time. This consideration must be balanced with “alert fatigue,” so that the alerts are acted upon rather than ignored.

Participants were particularly frustrated with the use of alerts and clinical reminders that urged increasing healthcare use in order to achieve treatment targets.

We conducted our study at 2 VA medical centers; providers from other geographic regions or non-VA care settings may have different views. We had a limited number of participants, and thus may not be able to discern differences in beliefs among physicians, nurse practitioners, and pharmacists. Providers who volunteered to participate may differ from those who did not respond, and many participants had long tenure in their current position. Future research to survey a broader sample of providers will enable better understanding of the range of opinions and associations with specific provider characteristics. Finally, this study was limited to the perspectives of primary care providers, and patients’ perceptions of medication discontinuation should be examined.

A qualitative study to understand clinical providers' attitudes and beliefs about polypharmacy and their perceived barriers to and facilitators of appropriate medication discontinuation.

Barbara Bokhour, PhD

Articles

False-Positive Mammography and Its Association With Health Service Use

Clinical Provider Perceptions of Proactive Medication Discontinuation