A 5-year study period was used (January 2008 to December 2012). The first 3 years of data were sequestered and used to determine whether patients had a diagnosis of nonmelanoma skin cancer (NMSC). The latter 2 years of data were used to determine annual health care usage and cost related to actinic keratosis.
The adjusted mean annual costs for patients in a metropolitan statistical area are shown for patients from all regions in the metropolitan statistical area, and a metropolitan statistical area is defined as a geographical area with a relatively high population density and economic ties throughout the area. To display cost variation, we calculated the ratio of mean cost in the highest quintile (Q5) relative to the mean in the lowest quintile (Q1), or the Q5:Q1 ratio. Total cost includes the categories of office visits plus cryotherapy and/or prescription topical medications.
eTable 1. Q5:Q1 ratios for Annual Cost of Office Visits
eTable 2. Q5:Q1 ratios for Annual Cost of Prescription Topical Medications
eTable 3. Q5:Q1 ratios for Annual Cost of Cryotherapy
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Kirby JS, Gregory T, Liu G, Leslie DL, Miller JJ. Variation in the Cost of Managing Actinic Keratosis. JAMA Dermatol. 2017;153(4):264–269. doi:10.1001/jamadermatol.2016.4733
Is there an opportunity to decrease waste or recoup excess spending by investigating geographic variation in actinic keratosis (AK) management costs?
There is substantial variation in the mean annual costs for AK management. After adjustment for age, sex, and history of nonmelanoma skin cancer, the mean annual costs of the patients in the highest quintile were 72% to 80% higher than patients in the lowest quintile.
There is variation in AK management cost within and between regions that is not fully explained by differences in patient characteristics such as age, sex, or comorbidities.
Actinic keratosis (AK), a skin growth induced by ultraviolet light exposure, requires chronic management because a small proportion can progress into squamous cell skin cancer. Spending for AK management was more than $1 billion in 2004. Investigating geographic variation in AK spending presents an opportunity to decrease waste or recoup excess spending.
To evaluate geographic variation in health care cost for management of AKs and the association with patient-related and health-related factors.
Design, Setting, and Participants
This retrospective cohort study was performed using data from the MarketScan medical claims database of 488 324 continuously enrolled members with 2 or more claims for AK. Data from January 1, 2008, to December 31, 2012, was used.
Main Outcomes and Measures
Annual costs of care were calculated for outpatient visits, AK destruction, and medications for AKs, and the total of these components. Costs were adjusted for inflation to 2014 US dollars. To display cost variation, we calculated the ratio of mean cost in the highest quintile (Q5) relative to the mean in the lowest quintile (Q1), or the Q5:Q1 ratio; Q5:Q1 ratios were adjusted based on age, sex, history of nonmelanoma skin cancer, US geographic region, and population density (metropolitan statistical area).
Overall, data from 488 324 continuously enrolled members (mean [SD] age, 53.1 [7.5] years; 243 662 women) with 2 or more claims for AK were included. Overall, patients had 1 085 985 claims related to AK, and dermatologists accounted for 71.0% of claims. The 2-year total cost was $111.5 million, with $52.4 million in 2011 and $59.1 million in 2012. The unadjusted Q5:Q1 ratios for total annual cost per patient ranged from 9.49 to 15.10. Adjusted ratios ranged from 1.72 to 1.80.
Conclusions and Relevance
There is variation in AK management cost within and between regions. This is not fully explained by differences in patient characteristics such as age, sex, or comorbidities. The annual cost for 10 common conditions from Medicare had lower Q5:Q1 ratios that ranged from 1.33 (joint degeneration of back/neck) to 1.69 (chronic sinusitis) when compared with 1.72 to 1.80 for AKs. This suggests an opportunity to investigate and improve the value of health care delivery in the management of AKs.
Actinic keratoses (AKs) are common cutaneous lesions that affect approximately 49% of adult men and 28% of adult women.1 Actinic keratoses most commonly arise on sun-exposed areas of older adults and have the potential to progress to squamous cell carcinoma2,3 and are a chronic skin condition because they frequently develop on multiple anatomic sites and demonstrate a high rate of recurrence after therapy. In one study,4 84% of men and 69% of women who had AK at baseline developed new lesions in 1 year.4 The burden of managing AKs has resulted in an estimated 5 million dermatology office visits and $920 million in health care spending each year in the United States.5-7 This constitutes an important portion of annual overall health expenditures in the United States, which totaled $2.9 trillion in 2013, or $9257 per capita and 17.4% percent of the gross domestic product, an amount that is growing at unsustainable rates.8
One way to address rising health care costs is through payment reform. Dermatologists, like all other physicians in other fields, must prepare for the Medicare Access and Children's Health Insurance Program (CHIP) Reauthorization Act (MACRA), signed into law in 2015, which shifts fee-for-service payments to value-based payments. An example of value-based payment is a bundled payment, and preliminary investigations of bundled payments have been explored for AKs.9 With a bundled payment, a dermatologist would be paid a fixed amount for all services associated with an episode of care. Such a payment forces the physician to think critically about the services for that condition that provide the best patient outcome at the lowest cost.10
One way to approach this shift from volume to value is study the variability of treatment for common conditions seen in dermatology. Addressing variability in health care delivery has the potential to decrease health care spending by decreasing those sources of variability that do not add value to patient outcomes.11-13 For example, geographic variation in spending, not explained by disease or patient characteristics, may present an opportunity to decrease waste or recoup excess spending.14,15 Geographic variability of health care spending can be heterogeneous because a region may be high cost for some conditions and low cost for others.16
Geographic variability in spending across the United States for medical conditions such as hip fracture, colorectal cancer, and acute myocardial infarction has demonstrated that higher expenditures do not correlate with improved outcomes.14,17-19 The purpose of this study is to examine geographic variability in health care usage and spending for the management of AKs. In dermatology, studies of nonmelanoma skin cancer (NMSC) have demonstrated local differences in the use of treatment procedures, which were not explained by patient or tumor characteristics.20,21 Recent studies22,23 have also identified geographic variability in spending and the use of oral antibiotics for treatment of acne in adolescents and adults, but relatively few studies have correlated spending with outcomes within the field of dermatology.
A retrospective analysis of the Truven Health MarketScan Commercial Claims and Encounters Database (Truven Health Analytics) was performed. The MarketScan database contains health insurance claims that are voluntarily submitted by approximately 100 payers for over 120 million insured individuals in the United States, making the database representative of the commercially insured population in the United States. As a claims database, clinical outcomes are not included, and validation studies of the variables have not been performed.
A 5-year study period was used (January 2008–December 2012) (Figure 1). The study sample included only continuously enrolled individuals. Patients with 2 or more claims for AK, based on the International Classification of Diseases, Ninth Revision (ICD-9) code 702.0, at any time during the 5-year study period were included. The requirement for 2 or more claims was added because validation studies of AK diagnosis have not been performed on this data set. The first 3 years of data were sequestered to determine whether patients had a diagnosis of nonmelanoma skin cancer (NMSC). Patients with a claim indicating a prior NMSC diagnosis (V10.83) or diagnosis with a NMSC during the 3-year period (any claim with ICD-9 codes 173 or 232) were considered to have a history of NMSC for the latter 2 years. The latter 2 years of the data set were examined for health care usage and cost related to AKs.
Patient characteristics including age and sex and comorbid conditions based on the ICD-9 codes documented on claims were extracted. Demographic as well as health care usage and cost information were extracted. Costs for office visits, biopsies, and treatment costs, including procedures and prescription medications, were included; however, inpatient claims were excluded because AK are rarely treated in this setting. The cost of care was calculated from the health system perspective and was the sum of payments by the insurer and the patient. Only claims with the ICD-9 code for AK were included. Costs were adjusted for inflation based on the medical care component of the consumer price index and are reported in 2014 US dollars.11
Treatment data were extracted and included the health care usage and cost for destruction of AK (Current Procedural Terminology [CPT] codes 17000, 17003, or 17004), photodynamic therapy (CPT codes 96567, J7308, or J7309), or topical prescription therapy. Prescription treatments were limited to fluorouracil, imiquimod, diclofenac, and ingenol and were identified by drug name and national drug code number. Biopsy procedures (CPT codes 11100 or 11101) were also included. The study was considered exempt by the Penn State College of Medicine institutional review board.
Descriptive statistics, including the mean (SD), were performed for several variables including age, sex, health care usage, and cost. Comparisons of the continuous outcome variables were made using a t test or analysis of variance (ANOVA) test with a Tukey correction for groups of 3 or more. Comparisons of proportions were made using the χ2 test. Cost data are often highly skewed, with very high costs generated by a small number of individuals.24 We formed quintiles of cost for services for the entire sample and by geographic location. To display cost variation, we calculated the ratio of mean cost in the highest quintile (Q5) relative to the mean in the lowest quintile (Q1), or the Q5:Q1 ratio.16 We controlled for potential determinants of skin health by regressing costs for individual patients on variables including age, sex, and history of NMSC. The Q5:Q1 ratio was then recalculated based on the adjusted costs. Analyses were stratified by US regions, metropolitan statistical area (MSA) status, and both variables. An MSA is a geographical area with a relatively high population density and economic ties throughout the area, such as a city and surrounding suburban areas.25 Bootstrapping was performed with samples of 500 observations and 1000 repetitions to estimate the 95% CIs. Winsorization is a method that diminishes the effects of the outliers at the extremes of a distribution by identifying values that are higher or lower than the selected percentiles (eg, 5th and 95th) and replaces the value at the percentile for the actual value. At the lower end of the distribution this adds value to those that had very low spending or health care usage and decreases the value for those with very high health care usage or spending. This method can maintain the direction of outliers but decreases the magnitude of the effect on the mean (SD).26 A second transformation was performed; the sample in Q5 was replaced with the values of the middle quintile (Q3). Descriptive statistics were performed on these transformed data sets, and all other statistical analyses were performed with SAS 9.3 (SAS Institute, Inc). All statistical tests were 2-sided and a P values less than .05 were considered statistically significant.
The characteristics of the patient cohort (n = 488 324) are shown in Table 1. In this sample, 73.9% of patients were older than 50 years. Approximately half were male (50.1%), 9.0% had a history of skin cancer, and 85.2% lived in an MSA (non-rural). The majority of claims were submitted by dermatologists (71.0%) and 44.8% patients were ever managed by a dermatologist (Table 2). Cryotherapy was used as treatment for the majority of patients (50.7%) and a minority of patients (12.6%) received a topical therapy (Table 2).
Table 3 contains Q5:Q1 ratios of unadjusted and health-adjusted mean costs for AK management, which includes the sum of all office visits, cryotherapy, and prescriptions for topical therapy. These ratios are stratified by MSA status, US region, and both of these variables. Unadjusted Q5:Q1 ratios for MSA showed a higher variability in cost (Q5:Q1 ratio) for non-MSA (rural) patients; however, after adjustment for age, sex, and history of skin cancer, patients in an MSA had a higher variability for total annual costs (1.96; 95% CI, 1.96-1.97 vs 1.90; 95% CI, 1.89-1.91). Unadjusted Q5:Q1 ratios for total cost by US region showed a lower variability in the West (9.85) and higher variability in the South Atlantic (13.17); however, after adjustment, the Q5:Q1 ratios were similar across all regions. Adjusted ratios by region and MSA status ranged from 1.82 (95% CI, 1.82-1.83) to 1.89 (95% CI, 1.89-1.90) (Table 3). The adjusted Q5:Q1 ratios were slightly higher for the MSA patients in all of the US regions, except the Mid Atlantic.
Figure 2 illustrates adjusted mean annual costs by quintile and Q5:Q1 ratio for total cost (office visits plus cryotherapy and/or prescription topical medications), as well as separately for office visits, cryotherapy, and topical treatments for patients in an MSA. The highest Q5:Q1 ratios were found in total costs (1.96; 95% CI, 1.96-1.97) and cryotherapy costs (1.92; 95% CI, 1.91-1.92), while the smallest ratio was in topical treatment costs (1.66; 95% CI, 1.66-1.67). The unadjusted and adjusted ratios for annual costs of office visits, prescription topical medications, and cryotherapy for the regions are listed in eTables 1-3 in the Supplement. Across all types of service costs, the West region had some of the lowest unadjusted Q5:Q1 ratios across all types of service costs. The South Atlantic and Pacific regions had some of the highest unadjusted Q5:Q1 ratios across the service categories. However, these differences by region were lessened after adjustment for age, sex, and history of skin cancer. The adjusted Q5:Q1 ratio was lower for non-MSA (rural) patients except for topical prescription cost. The largest difference in adjusted Q5:Q1 ratios was for the cost of annual office visits between MSA and non-MSA patients (1.90; 95% CI, 1.90-1.91 vs 1.58; 95% CI, 1.57-1.58). However, when stratified by region and MSA status, the adjusted Q5:Q1 ratios were lower for annual office visit cost (1.26 [95% CI, 1.25-1.27] to1.29 [95% CI, 1.28-1.30]), indicating the least variability among patients. In contrast, the total annual costs had the highest variability across all regions and MSA status with adjusted Q5:Q1 ratios of 1.82 (95% CI, 1.82-1.83) to 1.89 (95% CI, 1.89-1.90). The adjusted Q5:Q1 ratios by region and MSA status for topical prescription ranged from 1.42 (95% CI, 1.41-1.42) to 1.43 (95% CI, 1.42-1.43) and for cryotherapy ranged from 1.79 (95% CI, 1.79-1.80) to 1.82 (95% CI, 1.82-1.83).
Patients had 1 085 985 claims related to AK, and the 2-year total cost was $111.5 million, with $52.4 million in 2011 and $59.1 million in 2012. The mean (SD) annual cost per patient was $176.70 ($264.40). Following Winsorization at the 5th and 95th percentiles, the total cost was $38.3 million in 2011 and $42.7 million in 2012. The mean (SD) cost per member per year decreased to $134.97 ($116.00). After further transformation, replacing the costs of Q5 with costs of Q3, the total cost was $25.4 million in 2011 and $28.1 million in 2012. The mean (SD) cost per member per year was $89.17 ($46.23).
We found that differences in age, sex, and comorbid skin cancer partially explained variation in the costs related to AK management, such as office visits, cryotherapy, prescription topical medications and the total cost of care. The South Atlantic and Pacific areas had some of the highest unadjusted Q5:Q1 ratios across the service categories. However, these differences by region were lessened after adjustment for age, sex, and history of skin cancer.
The mean total annual cost for AK management was 82%-89% higher for the group of patients in the top quintile compared with the lowest quintile (Q5:Q1 ratios = 1.82-1.89). Variability was lowest for office visit costs (95% CI, 1.27-1.29) and highest for total annual costs (95% CI, 1.82-1.89) and cryotherapy costs (95% CI, 1.79-1.82). The higher variability in cryotherapy may be related to several factors, including the possibility that claims may be for the procedure only, which contributes to cryotherapy costs but not to office visit costs. In addition, variability could be due to differences in health care usage, namely, the decision to perform cryotherapy or not and the number of lesions treated. The Q5:Q1 ratios for AK care in this study are higher than 10 common and costly conditions from Medicare claims. Specifically, the lowest Q5:Q1 ratio was 1.33 for joint degeneration, and the highest Q5:Q1 ratio was 1.69 for chronic sinusitis.16 Considering the prevalence of AK and the costs of care, this variation encourages us to reflect on opportunities to measure the value of care delivered and identify changes to improve value and decrease variation that does not contribute to better patient outcomes. However, it may be difficult to constrain variation when clinical practice guidelines for AK are out of date, lack a basis in recent scientific literature, or are difficult to apply.27
This study also investigated the differences in the magnitude of cost variation between patients in MSA or non-MSA areas and several regions of the country. Importantly, approximately 14% of the patients in this study were from a rural area. This is similar to the United States Census data, which showed that almost 15% of Americans were living in a rural area in 2014.28 Adjusting for age and sex diminished the differences in between most MSA and non-MSA ratios; however, 1 notable difference was the Q5:Q1 for office visit costs (1.58 vs 1.90, respectively). The sources for this difference are unknown but may be related to the challenges related to travel for patients in rural areas, resulting in fewer office visits. In addition, poor availability of health care providers, including primary care providers and dermatologists, can have a significant negative impact on both health care cost and melanoma survival.29-31 This is important to keep in mind for patients in rural areas, where access to clinicians, especially dermatologists, can be difficult. Conversely, the difference may be explained as higher health care usage in MSA due to easier access. Ready access may facilitate health care usage driven by patients or the clinician.
The findings of this study should be considered in the context of the study limitations. Assumptions were made about the accuracy of the data, including the characteristics of patients, including race and skin type, and diagnoses, which were extrapolated from ICD-9 codes. Multivariate adjustment effects on costs likely decreased, or underestimated, the amount of cost variation. In addition, differences in regional reimbursement, including contractual rates or labor costs, were not captured.
Cost savings can be achieved through systemic care process reforms but are likely to involve identification of specific clinical conditions where local care practices can be improved. Future research should attempt to determine factors that influence variations in local treatment patterns for specific conditions. For example, future study may investigate variation patterns related to clinician training, clinicians’ practice organization, patient preferences, unmeasured patient comorbidities or other factors, and local drug and procedures costs. It is also important to consider that not all variation is inefficient. In addition, we need to consider the role of the patient and the variation in costs that are reasonable given patient characteristics or comorbidities. It is important to recognize that patient preference has been shown to explain about 5% of the geographic variation in health care cost.32
Improving the value of health care for patients means thinking critically about outcomes and costs. This study showed that modifications in spending, particularly for the group of patients with the highest costs, could result in a substantial decrease in the cost of care across a patient cohort.
Dermatologists must prepare for payment reform (eg, bundled payments) to ensure adequate reimbursement for diagnosis and treatment. The value of health care delivery for AKs, a common and chronic medical condition treated by dermatologists, requires investigation. Using Q5:Q1 ratios, this study documents up to an 89% variation for total costs for management of AKs across all US regions (95% CI, 1.82-1.89), in addition to variation within and between regions. This ratio is higher than other common conditions studied in the Medicare population (eg, 1.69 for chronic sinusitis). For AKs, dermatologists must identify high-value treatment options and pathways of care. Understanding the sources of variation in AK costs and then implementing value-driven pathways of care will be both an opportunity and a challenge in the context of health care reform.
Corresponding Author: Joslyn S. Kirby, MD, MS, MEd, Associate Professor, Department of Dermatology, Penn State Milton S. Hershey Medical Center, 500 University Ave, HU 14, Hershey, PA 17033 (Jkirby1@hmc.psu.edu).
Accepted for Publication: September 7, 2016.
Published Online: March 1, 2017. doi:10.1001/jamadermatol.2016.4733
Author Contributions: Drs Liu and Kirby had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: All authors.
Acquisition, analysis, or interpretation of data: Kirby, Gregory, Liu, Leslie.
Drafting of the manuscript: Kirby, Gregory.
Critical revision of the manuscript for important intellectual content: Kirby, Liu, Leslie, Miller.
Statistical analysis: Gregory, Liu, Leslie.
Administrative, technical, or material support: Kirby.
Supervision: Kirby, Leslie, Miller.
Conflict of Interest Disclosures: None reported.
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