HPC DataPoints

The HPC is pleased to introduce HPC DataPoints, a series of online briefs that will spotlight new research and data findings relevant to the HPC's mission to drive down the cost of health care. HPC DataPoints will showcase brief overviews and interactive graphics on relevant health policy topics. The analysis underlying these briefs is conducted by staff on the HPC's Research and Cost Trends team. As you read through HPC DataPoints, we encourage you to engage with the interactive graphics by hovering your mouse over different data points to obtain additional information. Please note that the interactive graphics will not appear in Internet Explorer. 

To see past DataPoints, please click the links below:

Issue 4: The growing opioid epidemic in Massachusetts hospitals (July 26, 2017)

  • Between 2014 and 2015, the number of opioid-related hospital (ED and inpatient) discharges grew drastically, by 18%.
  • A new, interactive map displays the rate of opioid-related hospital discharges by zip code and provides new insights into the disproportionate impact of the opioid epidemic on certain residents, communities, and hospitals.
  • Young adults experienced the sharpest increase in discharges, rising by 192% from 2011 to 2015.

Issue 3: The ACA’s Preventative Coverage Mandate and MA (June 26, 2017)

  • Average out-of-pocket spending by women for prescription drugs declined 14.2% from 2011-2014.

Issue 2: Avoidable Emergency Department Use in Massachusetts (May 23, 2017)

  • 42% of all ED visits in Massachusetts in 2015 were avoidable with fairly consistent rates throughout the Commonwealth in 2015.

Issue 1: Update on preventable oral health ED visits in MA (April 27, 2017)

  • The HPC identified 33,467 oral health ED visits in Massachusetts in 2015.
  • The HPC found a five-fold regional variation in the number of oral health ED visits per population.

DataPoint 4 (July 26, 2017)

The growing opioid epidemic in Massachusetts hospitals

Like many states across the country, Massachusetts is facing a growing epidemic of opioid addiction and overdose deaths. From 2000 to 2015, the opioid-related death rate in Massachusetts quadrupled, and by 2015 it was twice the national average. As previously reported in the Massachusetts Health Policy Commission’s (HPC’s) 2016 Opioid Use Disorder and Cost Trends reports, this epidemic significantly impacts  the health care system as the number of patients seeking opioid-related care and treatment at Massachusetts hospitals is rapidly increasing. In 2014, Massachusetts had the highest rate of opioid-related emergency department (ED) visits in the U.S. and the second highest rate of opioid-related inpatient stays.

Later this summer, the HPC will publish a chartpack updating the data from the 2016 Opioid Use Disorder Report in order to better understand the impact of the epidemic on the health care system from 2011 to 2015. While the initial report focused on opioid-related hospital inpatient discharges, the new chartpack includes ED visits as well. Below are some highlights from this upcoming chartpack.

From 2011 to 2015, the number of opioid-related hospital (ED and inpatient) discharges in Massachusetts increased substantially. Heroin-related discharges grew 256%, while all other opioid-related discharges grew 50% [1]. The largest annual growth rate during this time period occurred between 2014 and 2015 when the number of opioid-related hospital discharges grew 18%.

Source: HPC analysis of the Center for Health Information and Analysis (CHIA), Hospital Inpatient Discharge and Emergency Department Databases, 2011 and 2015

As shown in the map below, though some geographic variation exists in opioid-related hospital discharges, this epidemic has affected every region in the Commonwealth. Further, from 2011 to 2015, the rate of opioid-related hospital discharges grew in almost every zip code. By 2015, a much higher proportion of communities were in excess of 1,000 opioid-related discharges per 100,000 residents (1 per 100): 28% in 2015 compared to 11% in 2011. The map also displays the rate of opioid-related hospital discharges by zip code and the hospital with the highest number of opioid-related discharges for residents in each zip code.  

Source: HPC analysis of the Center for Health Information and Analysis (CHIA), Hospital Inpatient Discharge and Emergency Department Databases, 2011 and 2015.

Correction: The original data for this entry, posted on Wednesday, July 26, 2017, included a transcription error that affected the results for 34 zip codes in the South Coast and Cape Cod regions. The DataPoints entry and map, “Opioid-related hospital discharges by patient zip code, 2011 and 2015,” were updated on Tuesday, August 8, 2017.

 

Zip Codes Affected: 02713, 02715, 02717, 02718, 02719, 02720, 02721, 02723, 02724, 02725, 02726, 02738, 02739, 02740, 02743, 02744, 02745, 02746, 02747, 02748, 02760, 02762, 02763, 02764, 02766, 02767, 02769, 02770, 02771, 02777, 02779, 02780, 02790, 02791

 

There was also variation in the number of opioid-related hospital discharges by age. Some age groups experienced declines in their rate of opioid-related hospital discharges between 2011 and 2015. For example, children aged 19 and under had a 23% decrease, and adults between the ages of 55 and 59 had a 12% decrease. However, opioid-related hospital discharges among young adults increased substantially. From 2011 to 2015, there was a 12% increase in opioid-related discharges among patients ages 20 to 24, a 78% increase among patients ages 35 to 44, and a striking 192% increase among patients ages 25 to 34. Despite accounting for only 34% of the Commonwealth’s population in 2015, patients between the ages of 20 to 44 comprised 70% of opioid-related hospital discharges.

Source: HPC analysis of the Center for Health Information and Analysis (CHIA), Hospital Inpatient Discharge and Emergency Department Databases, 2011 and 2015

Since many opioid-related overdose deaths occur at younger ages, the impact on life expectancy is particularly pronounced.  In 2015, life expectancy in the US dropped for the first time in decades. While there are many causes, including rising rates of diabetes and obesity, drug overdoses accounted for a substantial portion of the decline.  In Massachusetts, residents lost 60,000 years of life due to poisonings in 2015 (most of which are opioid-related) [3], when measured by years of potential life lost before age 75 [4]. The number of years of life lost due to poisonings was larger than from heart disease and any category other than cancer and unintentional injuries.

The data presented here, and in the forthcoming chartpack, demonstrate the growing need for improvements in the health care system, including access to coordinated mental health and substance use disorder treatment. HPC has previously outlined several care delivery reform recommendations, including that the Commonwealth increase access to and effectiveness of evidence-based opioid use disorder treatment by integrating pharmacologic interventions into medical care.

DataPoint 4 - Printable Version  pdf format of DataPoint 4 - Printable Version

[1]. Opioid-related discharges were identified using ICD-9 diagnosis codes designated by the Agency for Healthcare Research and Quality within the United States Department of Health and Human Services. Discharges with opioid-related diagnosis codes, primary or otherwise, were included in this analysis. These opioid-related diagnosis codes include: 304.00-304.03 (opioid type dependence), 304.70-304.73 (combinations of opioid type drug with any other drug dependence), 305.50-305.53 (nondependent opioid abuse), 965.00 965.01, and 965.09 (poisoning by heroin, opium (alkaloids), and related narcotics), E850.0 and E850.2 (accidental poisoning by other opiates and related narcotics), E935.0 and E935.2 (heroin and other opiates causing adverse effects in therapeutic use). As with all analyses dependent on ICD-9 codes, provider coding may not always accurately reflect the patient’s clinical condition. In particular, heroin-related codes are considered specific, but not necessarily sensitive. For example, some hospitals may only use heroin-related codes for cases of poisoning/overdose. As a result, some heroin abuse/dependence is likely captured in the “other opioids” category. Furthermore, some non-heroin-related opioid cases are likely captured in the “heroin-related” category. The heroin-related and other opioid categories are not mutually exclusive, but the “all opioid” category only counts each discharge once.
[2]. From 2011 to 2014 the Center for Health Information and Analysis databases included only the patient’s first 15 diagnosis codes. However, in 2015, all patient diagnosis codes were included. An additional 1,300 inpatient stays with an ‘other opioid’ diagnosis were counted in 2015 due the expansion of diagnoses codes available in the data, while less than 11 additional patients with heroin diagnoses were counted. The data presented here is based on the patient’s first 15 diagnosis codes.
[3]. Poisonings were identified using ICD-10 T36-T50, of which opioid overdoses are a main contributor.
[4]. Years of potential life lost (YPLL) or potential years of life lost (PYLL), is based on an estimate of the average years a person would have lived if he or she had not died prematurely. It is, therefore, a measure of premature mortality. Years of potential life lost analysis includes ages 0-75.

DataPoint 3 (June 26, 2017)

The ACA’s preventative coverage mandate: Impact on spending and utilization of contraception in Massachusetts

The Patient Protection and Affordable Care Act of 2010 (ACA) established requirements for health plans to cover certain preventive services with no patient cost sharing. The preventive services guidelines adopted by Health Resources and Services Administration (HRSA) include the full range of  contraceptive devices and services. With the possibility of Congressional repeal or revision of the ACA and the opportunity for the Trump Administration to make substantial regulatory changes, it is important to study the impact of coverage and cost sharing requirements on state health care spending and patient out-of-pocket costs.

In the 2016 Cost Trends Report, the Health Policy Commission (HPC) reported on an increase in prescription drug claims with no cost sharing in the years following the ACA’s implementation across the three largest commercial payers in the Commonwealth. The HPC has now expanded this analysis to better understand the nature of these claims, including the extent to which they comprised claims for contraception services, which represent high-value care.

Between 2011 and 2014, across all prescription drugs, claims with no cost sharing grew from 0.8% to 8.7% of pharmacy claims. Claims with no cost sharing increased more for women (from 0.9% of claims in 2011 to 13.4% in 2014) than for men (0.6% to 2.4% of claims). Average out-of-pocket spending per claim for women declined 14.2%, compared to 3.8% for men.

 

Note: Data include privately insured individuals covered by Blue Cross Blue Shield of Massachusetts, Harvard Pilgrim Health Care, and Tufts Health Plan who use the prescription drug benefit at least once in the calendar year.

Source: HPC analysis of Massachusetts All Payer Claims Database, 2011 – 2014

For women, the decline in out-of-pocket prescription spending was almost entirely due to a significant decrease in cost sharing for contraception. In 2011, less than 1% of all pharmacy claims had no patient cost sharing. Of those claims, 22% were for prescription contraception. By 2014, over 13% of claims had no cost sharing, and 80% of those claims were for contraceptive methods. Ninety four percent of prescription contraception claims the HPC identified were oral contraceptives. Other methods included hormonal rings and patches.

Prescription contraception

Overall, the percentage of prescription contraception claims with any patient cost sharing decreased significantly from 98% to 6.5%, leading to a decrease in average out-of-pocket spending per contraception claim from $16.00 in 2011 to $1.73 in 2014. This represents an 89% reduction in average cost sharing during this period. The total number of prescription contraception claims was relatively constant across the four years.

 

Note: Prescription contraceptive methods identified in the claims using 917 contraception National Drug Codes (NDCs). Data include privately insured individuals covered by Blue Cross Blue Shield of Massachusetts, Harvard Pilgrim Health Care, and Tufts Health Plan who use the prescription drug benefit at least once in the calendar year.

Source: HPC analysis of Massachusetts All Payer Claims Database, 2011 – 2014

Intrauterine Devices (IUDs)

The HPC also examined use and cost sharing for intrauterine devices (IUDs) over this period. IUDs are a form of long-acting, reversible contraception (LARC) that have been shown to be cost saving compared to other forms of contraception, including the pill and other hormonal methods.[1] While IUDs have higher upfront costs than the pill (which include the cost of the device itself and the insertion procedure), over a five-year time horizon, total costs of the monthly pill exceed the total costs of an IUD. [2] Cost savings are compounded by the device’s higher rate of effectiveness at preventing pregnancies.[2],[3],[i] The upfront costs of getting an IUD, however, can serve as a deterrent to use, particularly for younger women.[4],[5]

The percentage of women with any patient cost sharing on IUD insertion and devices decreased significantly from 52% to 7%, leading to a decrease in average out-of-pocket spending (including both the insertion and cost of the device) from $28.11 to $5.27. This represents an 81% reduction in average cost sharing during this period. Most women were therefore shielded from the full cost of the procedure, which averaged $957.09 in 2014 for the insertion and device. The HPC’s findings on prescription contraception and LARCs are consistent with national trends.[6],[7]

 

Note: The HPC defined new IUD users as women who had at least one insertion or device claim within the year. Women with no cost sharing are defined as those who had no cost sharing on all IUD-related claims within the year. Data include privately insured individuals covered by Blue Cross Blue Shield of Massachusetts, Harvard Pilgrim Health Care, and Tufts Health Plan who used the medical benefit at least once in the calendar year.

Source: HPC analysis of Massachusetts All Payer Claims Database, 2011 – 2014

Whereas the number of prescription contraception claims remained relatively constant each year, the number of women with IUD claims between 2011 and 2014 rose 34%, from 13,800 to 18,500.  The increase was substantially larger among younger women (an 83% increase over this time period among those aged 18 to 24), who may be relatively more sensitive to cost-sharing.[5]

 

Notes: Data include privately insured individuals covered by Blue Cross Blue Shield of Massachusetts, Harvard Pilgrim Health Care, and Tufts Health Plan who use the medical benefit at least once in the calendar year.

Source: HPC analysis of Massachusetts All Payer Claims Database, 2011 – 2014

The increased affordability of IUDs may have served as a driver of increased use in Massachusetts and the U.S. over this time period, although other factors such as increased clinical familiarity and acceptance of this method for women pre-childbirth could have also played a role.[8] Given that IUDs are a cost-effective form of contraception compared to other methods, the increase in IUD uptake likely represents an efficient use of healthcare resources.

Some studies have found that eliminating cost sharing for contraception resulted in lower rates of abortion and teen birth rates, such as in Missouri’s Contraceptive CHOICE Program.[9] As more recent data on birth rates and abortion rates in Massachusetts become available, it will be important to monitor trends in these health outcomes following periods of more affordable access to contraception.

As changes in national health care legislation remain uncertain, these findings can provide context for discussions about maintaining high-value contraceptive coverage at the state level.

DataPoint 3 - Printable Version  pdf format of DataPoint 3 - Printable Version


[i] In fact, a study from the U.S. Department of Health and Human Services concluded that comprehensive coverage of LARCs (such as IUDs) actually reduced net total spending on health care. The direct cost of comprehensive LARC coverage resulted in insurance premium increases of less than 1%, but that cost was offset by avoiding spending on unwanted pregnancies and childbirth. (Bertko et al. The cost of covering contraceptives through health insurance. 2012 Feb. Washington, DC: Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human services.)

[1] Sonnenberg et al. Costs and net health effects of contraceptive methods. Contraception. 2004; 69: 447-459.
[2] Trussell et al. Cost effectiveness of contraceptives in the United States. Contraception. 2009; 79:5-14.
[3] Trussell et al. The economic value of contraception: A comparison of 15 methods. American Journal of Public Health. 1995; 85:494-503.
[4] Kavanaugh et al. Long-acting reversible contraception for adolescents and young adults: Patient and provider perspectives. Journal of Pediatric and Adolescent Gynecology. 2013 April; 26(2):86-96.
[5] Eisenberg et al. Cost as a barrier to long-acting reversible contraceptive (LARC) use in adolescents. Journal of Adolescent Health. 2013; 52:S59-S63.
[6] Cox et al. Examining high prescription drug spending for people with employer sponsored health insurance. The Henry J. Kaiser Family Foundation; 2016 Oct 27. Available from: http://www.healthsystemtracker.org/insight/examining-high-prescription-drug-spending-for-people-with-employer-sponsored-health-insurance
[7] Sonfield et al. Impact of the federal contraceptive coverage guarantee on out-of-pocket payments for contraceptives: 2014 update. Contraception. 2015; 91:44-48.
[8] Ott et al. Contraception for Adolescents. Pediatrics. 2014 Oct; 134(4):e1257-e1281.
[9] Peipert et al. Preventing unintended pregnancies by providing no-cost contraception. Obstetrics and Gynecology. 2012 Dec; 120(6):1291-1297.

DataPoint 2 (May 23, 2017)

To ED or not to ED, that is the question: Avoidable Emergency Department Use in Massachusetts

The use of emergency departments (EDs) for non-urgent medical conditions is a growing policy focus in the United States and in Massachusetts. Many policymakers believe that it is essential to shift ED use for non-urgent health problems to community settings to relieve crowded EDs, lower the cost of care, and improve quality. Analyses of avoidable ED visits focus on two types of visit categories: visits that could have been treated by a primary care provider (e.g. a visit for an ear infection) and visits that did not require any immediate medical care (e.g. a visit for a bad sore throat with no fever).[1]

In the 2016 Cost Trends Report, the Health Policy Commission (HPC) reported that 42% of all ED visits in Massachusetts in 2015 were avoidable, a share that has remained constant since 2011. HPC expanded this analysis to better understand these avoidable ED visits. 

As seen in the map below, HPC also found that the share of all ED visits that was considered avoidable was fairly consistent throughout the Commonwealth in 2015. In other words, avoidable ED visits are a state-wide concern. There was some variation, however, in the most common condition by zip code. In 2015, the most common conditions for which people had an avoidable ED visit were [2]:

  1. Sinusitis
  2. Stomach pain
  3. Rashes and skin conditions
  4. Acid reflux
  5. Bronchitis
  6. Dental pain
  7. Back pain
  8. Allergies
  9. Urinary tract infections
  10. Ear and eye infections

Source: HPC analysis of Center for Health Information and Analysis Emergency Department Database, 2015

The use of EDs to treat conditions that are non-emergent or amenable to primary care can be an indicator of barriers to accessing primary care. Many studies have shown that when individuals are unable to visit or speak with providers, they are more likely to use the ED.

Source: HPC analysis of Center for Health Information and Analysis Emergency Department Database, 2015

As seen in the graph, the HPC found that a majority of avoidable ED visits in 2015 (69.2%) took place between the hours of 8am and 8pm. While limited access to care outside of normal daytime hours also represents a problem, the fact that most avoidable ED visits occur during daytime hours suggests deeper problems of access to care. Among respondents of the 2014 Massachusetts Health Insurance Survey who had been to the ED in the past year, over half said they had done so because they could not get a timely appointment with their usual source of care. Some potential solutions that could improve access to timely primary care include connecting patients with retail clinics and urgent care centers, expanding provider office hours and the availability of nurse hotlines and telehealth, and granting Nurse Practitioners full practice authority.

 

[1] The HPC used the Billings algorithm to categorize ED visits. The Billings algorithm uses the patient’s primary diagnosis to categorize a visit into broad categories: emergent, non-emergent (a patient’s initial complaint, presenting symptoms, vital signs, medical history and age indicated that immediate medical care was not required in 12 hours), and emergent, primary care treatable (treatment was required within 12 hours, but care could have been provided effectively and safely in a primary care setting). Behavioral health-related visits and injuries are identified by the algorithm, but are not classified into any of these category types. HPC considered non-emergent and emergent, primary care treatable visits “avoidable”.

[2] Any discharge that the Billings algorithm classified as being at least 75% non-emergent or emergent, primary care treatable was used for this analysis.

DataPoint 1 (April 27, 2017)

Nothing to Smile About: Update on preventable oral health ED visits in Massachusetts

In August 2016, the Health Policy Commission (HPC) reported its findings that a substantial number of emergency department (ED) visits are for preventable oral health conditions. ED visits for oral health complaints are a particularly poor use of the health system for both patients and providers alike. Hospital settings are not equipped to treat the majority of dental conditions and, as a result, patients may endure long waits and not receive the most appropriate treatment. Visits for conditions, such as dental pain due to cavities and abscesses, are also more expensive than treatment in dentist offices and put pressure on overburdened ED resources throughout Massachusetts.  

Updating previous research, the HPC identified 33,467 ED visits for preventable oral health conditions in Massachusetts in 2015. The HPC found a five-fold regional variation in the number of oral health ED visits per population, with highs of 13.4 visits per 1,000 in Fall River and 11.7 in the Berkshires and lows of 3.4 per 1,000 in Norwood/Attleboro and 2.5 in West Merrimack/Middlesex.

While the number of oral health ED visits declined 11.5% from 2013 to 2015, these visits increased among certain age groups. Among seniors ages 65 to 74, oral health ED visits increased 15%, and among seniors ages 75 to 84, visits increased 4%.  Senior populations often face barriers in accessing dental care, including cost and challenges obtaining dental care in offices due to mobility impairments. The number of oral health ED visits also grew almost 15% among children ages 5 to 10.

When examining oral health ED visits by income, the HPC found that the 25 percent of Massachusetts residents residing in the lowest-income areas of the state accounted for 45.3% of oral health ED visits in 2015. Factors that could contribute to higher rates of preventable oral health ED visits among lower-income patients include clinical risk factors, high out-of-pocket costs, and the fact that many dentists do not accept Medicaid patients. In 2014, just 35% of dentists in Massachusetts treated a MassHealth patient, compared to almost 70% of primary care physicians. These finding highlights the need to address barriers in access to dental care, including to coverage and provider access.

Health care advocates, clinicians, and researchers consider oral health ED visits an indicator of inadequate access to oral health care. A range of programs and policies may improve patient access to these services. One idea currently under debate in Massachusetts is augmenting the oral health workforce. There are several legislative proposals before the Massachusetts General Court that would authorize a new category of dental professionals -- dental hygiene practitioners (a similar bill was proposed last year). Dental hygiene practitioners undergo training that allows them to perform some procedures traditionally done by dentists, such as filling cavities. These types of providers are currently licensed to work in Minnesota, Maine, Vermont, and Alaskan native communities. Advocates for augmenting the oral health workforce maintain that these lower cost providers would expand access to dental care, particularly for elderly and lower income residents, due to increased capacity and their ability to work in community locations, such as at schools and nursing homes.

Data Notes:

Graph 1: 
Sources: HPC analysis of Center for Health Information and Analysis Emergency Department Database, 2015 (Oral health ED visits); Massachusetts Department of Public Health, Health Care Workforce Center, 2014 (Dentists per population)
Note: The data presented here have been aggregated to the HPC region level. Each zip code in a region displays the HPC region-level rates of dental professionals and oral health ED visits. The color gradient has been assigned by the rate of oral health ED visits per 1,000 population, with the darkest color representing the highest rate and the lightest color representing the lowest rate.

Graph 2:
Source: HPC analysis of Center for Health Information and Analysis Emergency Department Database, 2013-2015

Graph 3:
Source: HPC analysis of Center for Health Information and Analysis Emergency Department Database, 2015

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