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. Author manuscript; available in PMC: 2018 Jun 6.
Published in final edited form as: J Pharm Technol. 2017 Jan 10;33(2):60–65. doi: 10.1177/8755122516686226

Impact of Laws Regulating Pain Clinics on Opioid Prescribing and Opioid-Related Toxicity Among Texas Medicare Part D Beneficiaries

Mukaila A Raji 1, Yong-Fang Kuo 1, Nai-Wei Chen 1, Hunaid Hasan 1, Denise M Wilkes 1, James S Goodwin 1
PMCID: PMC5990015  NIHMSID: NIHMS968430  PMID: 29888344

Abstract

Background

Pain management clinics are major sources of prescription opioids. Texas government passed several laws regulating pain clinics between 2009 and 2011 to reduce opioid-related toxicity. Understanding the impact of these laws can inform policy geared toward making the laws more effective in curbing the growing epidemic of opioid overdose, especially among the elderly population.

Objectives

To examine the longitudinal association of laws regulating pain clinics on opioid-prescribing and opioid-related toxicity among Texas Medicare recipients.

Methods

The 2007 to 2012 claims data for Texas Medicare Part D recipients were used to assess temporal trends in the percentage of patients filling any schedule II or schedule III opioid prescription, hospitalization for opioid toxicity, and their relationships to the 2009 to 2011 Texas laws regulating pain clinics. We excluded those with a cancer diagnosis. Join-point trend analysis with Bayesian Information Criterion selection methods were used to evaluate the change in monthly percentages of patients filling opioid prescriptions and hospitalization over time.

Results

There was a short-lived decline in the monthly percentages of patients who filled a schedule II or schedule III opioid prescription after the 2009 laws regulating pain clinics. The decline lasted about 3 months. Subsequent new laws had no effect on the percentages of patients who filled any opioid prescription or were hospitalized for potential opioid toxicity. Hospitalizations for opioid toxicity were highest in the winter and lowest in the summer.

Conclusions

Changes in the percentages of opioid-prescribing or opioid-related hospitalizations over time were not associated with laws regulating pain clinics.

Keywords: Medicare, opioids, laws, public policy, overdose

Introduction

States and the federal government have passed an increasing number of laws and regulations to curb the use, misuse, and toxicity of opioids.1–3 Current laws and policies vary substantially across states.2,4–8 The Centers for Disease Control classifies opioid-regulating laws into 7 groups.9,10 Four groups are directed at patients and prescribers, and include laws that provide immunity from prosecution for persons seeking help during an overdose, prohibit patients from receiving opioids from multiple providers without the prescribers’ knowledge, require a physical examination before prescribing, and mandate the use of tamper-resistant prescription forms. Other laws regulate pharmacy and pain management clinic practices. These set prescription drug limits, require patient identification before dispensing, and impose registration and strict oversight for pain management clinics.

Findings from past studies on the impact of laws on opioid use and outcomes are mixed.1,5,10–14 The mixed findings reflect, at least in part, the differences in measured outcomes (eg, prescription opioid diversion investigations, medical examiner report for opioid overdose death, volume of opioid sold per month), duration of study, sample size, sources of data (medical examiner vs poison center vs drug treatment center vs pharmacy sources), sociodemographic factors (insurance status and age), and effects of single versus multiple opioid-regulating laws and policies.1,5,10,13,14 A recent cross-sectional analysis of national Medicare data and state laws regulating prescription opioids showed a significant relationship between laws regulating pain clinics and lower rates of schedule II opioid prescriptions.10 Pain clinics are major sources of prescription opioids.1,5,15 Laws regulating pain clinics set requirements and guidelines for clinic registration, inspection, and certification.1,2,4–8 They also regulate training and education of physicians, staff and clinic owners, process of patient care metrics, standards for storage of medications and medical records, and procedures for investigating complaints and assessing penalties for noncompliance.

To better understand the impact of laws passed in Texas between 2009 and 2011 to regulate pain clinics, we examined the longitudinal association of these laws on opioid prescribing and opioid-related toxicity among elderly Medicare recipients. Elderly Medicare recipients are particularly prone to opioid-related toxicity because of the age-related decline in drug metabolism and the high prevalence of multiple comorbidities and polypharmacy.10 Availability of Medicare Part D prescription medication data allowed us to investigate the temporal association of these laws with the change in percentage of patients who filled any opioid prescriptions or were hospitalized for opioid toxicity between January 2008 and December 2012. We hypothesized that implementation of laws regulating pain clinics would be temporally associated with a decrease in the monthly percentages of Medicare patients who filled a schedule II or schedule III opioid prescription or who were hospitalized for opioid toxicity. We used the older classification for the opioid schedule class because our data preceded the 2014 Drug Enforcement Administration (DEA)–mandated reclassification of hydrocodone products from a schedule III to schedule II drug.3

Methods

Establishment of the Cohort Study

Claims from 2007 and 2012 for Texas Medicare beneficiaries were used. These included Medicare beneficiary summary files, Medicare Provider Analysis and Review (MedPAR) files, Outpatient Standard Analytic Files, Medicare Carrier files, and Prescription Drug Event (PDE) files. We selected Medicare beneficiaries aged 66 or older with Medicare Parts A, B, and D coverage and who were not in a health maintenance organization (HMO) for the year before and the year of study or until death for each year from 2008 to 2012. Patients with a cancer diagnosis in the year before or the year of study were further excluded.

Summary of Texas Laws and Regulations

The Texas government implemented a number of regulations about opioid prescribing from 2009 to 2012.2,4,7,8 The laws regulating pain clinics are summarized below.

  1. 22 Tex. Admin. Code § 192.1, 192.4–192.7 (November 2009) establishes rules for definitions, registration, inspections, operations, staffing, standard of care, and billing of pain clinics.

  2. 22 Tex. Admin. Code § 195.4 (May 2010) establishes minimum requirements for quality assurance procedures and stricter standards of care (eg, periodic drug screening), qualifications of clinic owners, and mandatory continuing medical education for all clinic staff.

  3. Tex. Occ. Code § 168.001 (September 2010) requires a pain management clinic to operate only after registration and certification by the Texas Medical Board.

  4. Tex. Occ. Codes § 168.102, 201 & 202 (September 2011) require a pain clinic owner to be a licensed MD with no criminal history. The owner must periodically review patient files and be on clinic site at least 33 percent of the clinic hours.

Study Outcomes

We assessed opioid prescribing and also opioid-related toxicity in relation to changes in Texas laws regulating pain management clinics. For opioid prescribing, the outcome was the monthly percentages of Medicare patients who filled at least one prescription for either a schedule II or a schedule III opioid during the study years. This was determined by examining the PDE records for the study cohort. The RED BOOK SELECT databases were used to identify the opioid schedules. Opioids given by injections were not included. For toxicity, the outcome was acute hospitalization related to overdose. Acute hospitalization use was identified from all inpatient claims in MedPAR files. Any positions of admission diagnoses for—(1) opioid-related poisoning: ICD-9 965, E850.1, E950.0, E980.0; (2) opioid-specific adverse event: ICD-9 E935.0, E935.1, E935.2; or (3) overdose diagnosis: ICD-9 276.4, 292.1, 292.8, 486, 496, 518.81, 518.82, E950–E959—were included.16

Statistical Analyses

The monthly percentages of patients who filled a schedule II or schedule III opioid prescription or were hospitalized for potential opioid overdose during the study years were calculated and plotted. To identify the trend of opioid prescribing and toxicity over time, a joinpoint trend analysis, with the maximum of 9 joinpoints for opioid prescribing and hospitalization, was used through grid search of joinpoints by Bayesian information criterion selection methods. This method assumed a linear trend between joinpoints and continuity at joinpoints, also known as piecewise or segmented trend analysis with continuity constraint. All tests of statistical significance of increase or decline in slopes of the trends were 2-sided with a significance level of .05. Analyses were performed with SAS version 9.3 (SAS Inc, Cary, NC) and Joinpoint Regression Program version 3.5.17

Results

Opioid Prescribing in Relation to Changes in Laws

Figure 1 includes 3 curves and 4 arrows. The upper line shows the monthly percentage of patients who had at least one schedule III opioid prescription filled from 2008 to 2012. The middle line shows the monthly percentage of patients who had at least one schedule II prescription filled. The bottom line shows the percentage of patients per month who were hospitalized for diagnoses of opioid-related poisoning, opioid-specific adverse events, or opioid overdose. The black arrows A to D represent the dates of implementation of opioid-regulating laws.

Figure 1.

Figure 1

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The observed rates and joinpoint regression fitted lines of the monthly percentages of Texas Medicare patients who filled at least one schedule II or schedule III opioid prescription, or were hospitalized for potential opioid overdose between January 2008 and December 2012.

The percentages on the y-axis were shown individually within each block for (a) schedule III opioid prescription, (b) schedule II opioid prescription, and (c) hospitalization. The joinpoints for each situation were symbolized as arrows, “↑” or “↓”. The fitted regression lines between joinpoints colored as black solid lines had statistical significance of increase or decline in slopes of the trends and those colored as blue solid lines had no statistical significance in slopes of the trends. The dates of implementations of important opioid regulating laws were symbolized as arrows marked by letters along with the black dashed lines.

We conducted a joinpoint analysis to determine the points where there were significant changes in the percentage of patients per month filling at least one opioid prescription (Table 1). Figure 1 presents actual data points and a regression line that best fits those points. Both the schedule II and III curves showed a significant downward slope starting around November 2009 and ending around March 2010. The significant upward shift in slope of both schedule II and III opioids that started around March 2010 ended in March 2011. The decline in slope seen from March 2011 was steeper for schedule III than for schedule II opioids.

Table 1.

The Occurrence of Joinpoints on the Monthly Percentages of Texas Medicare Patients Who Filled at Least One Schedule II or Schedule III Opioid Prescription Between January 2008 and December 2012.

Joinpoint Fitted Line
Opioid Use Time 95% CI Time Period Slope (P Value)
Schedule II 10/2009 [05/2009, 12/2009] 10/2009 0.001 (.47)
02/2010 [12/2009, 05/2010] 10/2009 to 02/2010 −0.027 (.19)
03/2011 [11/2010, 09/2011] 02/2010 to 03/2011 0.015 (.00)
03/2011 0.001 (.42)
Schedule III 11/2009 [02/2009, 01/2010] 11/2009 0.035 (.00)
02/2010 [12/2009, 09/2010] 11/2009 to 02/2010 −0.235 (.49)
04/2011 [01/2011, 08/2011] 02/2010 to 04/2011 0.157 (.00)
04/2011 −0.028 (.00)
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Abbreviation: CI, confidence interval.

Arrows

The November 2009 laws (Arrow A in Figure 1) were associated with a temporary decline in the monthly percentage of patients who filled at least one schedule II or III opioid prescription. The decline started around November 2009 and ended around March 2010. The subsequent new laws had no association with the slope of the monthly percentages of patients filling schedule II or III opioid prescriptions.

Hospitalization for Potential Opioid Overdose in Relation to Changes in Laws

The rate of acute hospitalization for opioid toxicity showed 7 joinpoints (Table 2), but none were clearly associated with the laws regulating pain clinics. There was no correlation between the monthly percentages of patients filling a schedule II or III opioid prescription and hospitalization for toxicity (r = .054, P = .68, for schedule 2, and r = −.025, P = .85, for schedule III). Opioid-related hospitalizations from January 2008 to December 2012 followed a sinusoidal pattern with peaks in the winter months (February and March) and lows in the summer months (July and August).

Table 2.

The Occurrence of Joinpoints on the Monthly Percentage of Texas Medicare Patients Who Were Hospitalized for Opioid-Related Overdose Between January 2008 and December 2012.

Joinpoint Fitted Line
Time 95% CI Time Period Slope (P Value)
Hospitalization 07/2008 [03/2008, 12/2008] 07/2008 −0.056 (.00)
03/2009 [06/2008, 01/2010] 07/2008 to 03/2009 0.023 (.03)
08/2009 [12/2008, 04/2010] 03/2009 to 08/2009 −0.039 (.11)
03/2010 [05/2009, 08/2010] 08/2009 to 03/2010 0.031 (.02)
08/2010 [12/2009, 04/2011] 03/2010 to 08/2010 −0.048 (.05)
02/2011 [05/2010, 11/2011] 08/2010 to 02/2011 0.051 (.00)
05/2011 [11/2010, 10/2012] 03/2011 to 05/2011 −0.054 (.47)
05/2011 −0.002 (.34)
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Abbreviation: CI, confidence interval.

Discussion

There was a short-lived decline in the monthly percentage of Medicare patients who filled at least one schedule II or III opioid prescription after the November 2009 laws regulating the operations of pain clinics. The decline lasted about 3 months. There was no association between subsequent new laws and the monthly percentages of patients filling a schedule II or III opioid prescription. Also, no association was observed between Texas laws regulating pain clinics and the monthly percentages of Medicare patients hospitalized for opioid toxicity.

Although changes occurred in the monthly percentages of patients filling a schedule II or III opioid prescription over time, the changes were not clearly associated with the laws regulating pain clinics. These changes might however be related to other ongoing law enforcement activities in the state. For example, the March 2011 downward shift in the percentages of patients filling a schedule II or III opioid prescription could have been related to the unusually high number of opioid prescription-related disciplinary actions and license revocations by the Texas Medical Board in 2011 (71 physicians in 2011 vs 16 in 2006).18,19 It is possible that the increase in disciplinary actions in 2011 were the result of the enactment of Laws B and C in 2010, such that prescribers who did not comply with the new laws might have had substantial restriction or suspension of their opioid prescribing privileges. Also, in May 2011, the Texas government passed a law that made it a felony for a patient to seek schedule II or III opioids from multiple providers without disclosing prior opioid prescriptions to the new prescribers.20 The law however could not explain the downward shift in the slope of opioid prescribing that began 2 months earlier. Our Medicare claims database did not allow us to investigate these possibilities, but it is an important area for future study.

Other studies have found cross-sectional associations of laws regulating pain clinics and opioid prescribing but we did not see this association longitudinally.1,5,10,13,14 The short-term nature of the decline in the monthly percentages of Medicare patients filling a schedule II or III opioid prescription was a surprising finding as we expected the laws to have long-term effect. The reason for the temporary decrease was unclear, but the finding underscored the importance of longitudinal data analysis in evaluating the impact of policy and regulations on opioid prescribing. Because past studies showed lower rate of opioid prescribing in Texas than other states, it may have been difficult to detect longitudinal changes in response to the laws regulating pain clinics.10,21

It was also possible that the lack of sustained decrease in opioid prescribing reflected a shift of opioid prescribing from the pain management clinics to primary care offices, such that increasing number of patients receive opioid prescriptions from their primary care physicians instead of pain management specialists. Future study is needed to explore this possibility of unintended consequences of stricter regulation of pain clinic physicians. From a regulatory point of view, our finding underscored the importance of writing laws that better address the cause(s) of the increasing incidence of opioid-toxicity in order to achieve the desired societal outcome.

The rate of hospitalization related to opioid toxicity was highest in the winter months and lowest in the summer. Seasonal variations in opioid-related suicide have been described, with the highest rates in the fall and spring.22,23 In contrast, recent evidence showed that non–opioid-related suicides were lower in winter months.24,25 Further studies are needed to clarify the effect of seasonality on opioid-related death and other outcomes in the growing population of older adults.

Other studies have reported modest reductions in opioid-related death and opioid diversion in response to enactment of pain clinic laws and a substantial increase in law enforcement activities conducted by police, DEA agents, and other law enforcement agencies.1,5,13,14 Our study’s focus was not on law enforcement activities but on the potential association of laws regulating pain clinic and opioid prescribing by licensed prescribers. We also did not focus on patients who obtained opioids in the setting of illicit drugs, diverted drugs, and other illegal activities. Most seniors receive their opioids legally from licensed prescribers, and their patterns and outcomes of use and misuse are likely different from those of younger populations.

Limitations

We likely underestimated the overall percentage of opioid prescribing because we excluded opioid injections. We also had no information on opioids obtained from the Internet, friends, the street, and mail order. These sources of opioids were likely minimal in our cohorts as most elderly patients receive their opioids legally from licensed prescribers.26–28 Another limitation was the possibility of underdetection of opioid-related hospitalization due to underrecognition of opioid-related toxicity by clinicians. Finally, because of our exclusion criteria and our focus on the elderly population, our results might not be generalizable to patients in a HMO, those without Medicare Part D medication insurance or the younger population.

Conclusions

We found only a 3-month decline in the monthly percentages of Medicare patients filling a schedule II or III opioid prescription after the 2009 Texas laws; subsequent new laws had no effect on the percentage of opioid prescriptions filled or opioid-related hospitalizations. Our finding of short-term effect of the law underscored the need for periodic evaluations and long-term monitoring of opioid-regulating policies for durability and sustainability. For example, evaluating the effect of the 2014 DEA-mandated reclassification of hydrocodone combination products on opioid prescribing and toxicity could help answer questions about relative impact of federal versus state laws on opioid prescribing and outcomes.3 Findings from our current study have the potential to inform state policymakers on necessary changes to make future laws more effective in curbing opioid misuse. Our findings also underscored the need for policymakers or governments to clearly define and target the relevant outcome measures during the legislative process of enactment of laws regulating opioid prescribing.

Acknowledgments

We thank the anonymous reviewers of our article for their helpful comments.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Grants R24-HS022134 from the Agency for Healthcare Research and Quality, and R01-AG033134, R01-DA039192, P30-AG024832, and UL1TR001439 from the National Institutes of Health.

Footnotes

The study protocol was reviewed and approved by the institutional review board of the University of Texas Medical Branch.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

  • 1.Haegerich TM, Paulozzi LJ, Manns BJ, Jones CM. What we know, and don’t know, about the impact of state policy and systems-level interventions on prescription drug overdose. Drug Alcohol Depend. 2014;145:34–47. doi: 10.1016/j.drugalcdep.2014.10.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.American Academy of Physical Medicine and Rehabilitation Medicine. [Accessed December 21, 2015];Pain management and opioid prescribing policies by state. http://www.aapmr.org/docs/default-source/advocacy/pain-management/pain-management-and-opioid-prescribing-policies-by-state.pdf. Published 2014.
  • 3.US Department of Justice. Drug Enforcement Administration. Office of Diversion Control. [Accessed December 21, 2015];Rescheduling of hydrocodone combination products from schedule III to schedule II. FR Doc. 2014-19922 Filed 8-21-14; 8:45 am. http://www.deadiversion.usdoj.gov/fed_regs/rules/2014/fr0822.htm.
  • 4.Center for Disease Control and Prevention. [Accessed December 21, 2015];Menu of pain management clinic regulation. 2013 http://www.cdc.gov/phlp/docs/menu-pmcr.pdf. Published 2013.
  • 5.Rutkow L, Chang H, Daubresse M, Webster DW, Stuart EA, Alexander G. Effect of Florida’s Prescription Drug Monitoring Program and Pill Mill Laws on Opioid Prescribing and Use. JAMA Intern Med. 2015;175:1642–1649. doi: 10.1001/jamainternmed.2015.3931. [DOI] [PubMed] [Google Scholar]
  • 6.Franklin GM, Mai J, Turner J, Sullivan M, Wickizer T, Fulton-Kehoe D. Bending the prescription opioid dosing and mortality curves: impact of the Washington State opioid dosing guideline. Am J Ind Med. 2012;55:325–331. doi: 10.1002/ajim.21998. [DOI] [PubMed] [Google Scholar]
  • 7.National Alliance for Model State Drug Laws and the National Safety Council. [Accessed December 21, 2015];Prescription drug abuse, addiction and diversion. Overview of state legislative and policy initiatives. State Regulation of Pain Clinics. http://nationalrxdrugabusesummit.org/wp-content/uploads/2013/03/Green-pt2_PAIN_CLINICS.pdf. Published 2013.
  • 8.National Alliance for Model State Drug Laws and the National Safety Council. [Accessed December 21, 2015];State regulation of pain clinics and legislative trends relative to regulating pain clinics. http://www.namsdl.org/NAMSDL%20Part%202%20Revised%20April%204%202014.pdf. Published 2014.
  • 9.Center for Disease Control and Prevention, Office for State, Tribal, Local and Territorial Support, Public Health Law Program. [Accessed December 21, 2015];State laws on prescription drug misuse and abuse. http://www.cdc.gov/phlp/publications/topic/prescription.html.
  • 10.Kuo YF, Raji MA, Chen NW, Hasan H, Goodwin JS. Trend in opioid prescriptions among Part D Medicare recipients from 2007 to 2012. Am J Med. 2016;129:221.e21–e30. doi: 10.1016/j.amjmed.2015.10.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Chou R, Turner JA, Devine EB, et al. The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a National Institute of Health Pathways to Prevention Workshop. Ann Intern Med. 2015;162:276–286. doi: 10.7326/M14-2559. [DOI] [PubMed] [Google Scholar]
  • 12.Gomes T, Juurlink D, Yao Z, et al. Impact of legislation and a prescription monitoring program on the prevalence of potentially inappropriate prescriptions for monitored drugs in Ontario: a time series analysis. CMAJ Open. 2014;2(4):E256–E261. doi: 10.9778/cmajo.20140027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Surratt H, O’Grady C, Kurtz S, et al. Reductions in prescription opioid diversion following recent legislative interventions in Florida. Pharmacoepidemiol Drug Saf. 2014;23:314–320. doi: 10.1002/pds.3553. [DOI] [PubMed] [Google Scholar]
  • 14.Johnson H, Paulozzi L, Porucznik C, Mack K, Herter B. Decline in drug overdose deaths after state policy changes—Florida, 2010–2012. MMWR Morb Mortal Wkly Rep. 2014;63(26):569–574. [PMC free article] [PubMed] [Google Scholar]
  • 15.Kuehn BM. CDC: major disparities in opioid prescribing among states: some states crack down on excess prescribing. JAMA. 2014;312:684–686. doi: 10.1001/jama.2014.9253. [DOI] [PubMed] [Google Scholar]
  • 16.Dunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010;152:85–92. doi: 10.1059/0003-4819-152-2-201001190-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.National Cancer Institute. Joinpoint Regression Program, Version 3.5. Bethesda, MD: Statistical Methodology and Applications Branch and Data Modeling Branch, Surveillance Research Program, National Cancer Institute; 2011. [Google Scholar]
  • 18. [Accessed December 21, 2015];Texas Medical Board Statistics. http://www.tmb.state.tx.us/showdoc/statistics.
  • 19.Roser MA. Some patients suffer more amid crackdowns on prescribing strong painkillers. The Statesman [Google Scholar]
  • 20. [Accessed December 21, 2015];Texas Senate Bill 158. Sec. A 481.1285. http://www.capitol.state.tx.us/tlodocs/82R/billtext/pdf/SB00158F.pdf.
  • 21.Paulozzi LJ, Mack KA, Hockenberry JM. Vital signs: variation among States in prescribing of opioid pain relievers and benzodiazepines—United States, 2012. MMWR Morb Mortal Wkly Rep. 2014;63(26):563–568. [PMC free article] [PubMed] [Google Scholar]
  • 22.Pitts SR, Niska RW, Xu J, Burt CW. National Hospital Ambulatory Medical Care Survey: 2006 emergency department summary. Natl Health Stat Report. 2008;(7):1–38. [PubMed] [Google Scholar]
  • 23.Davis JM, Searles VB, Severtson SG, Dart RC, Bucher-Bartelson B. Seasonal variation in suicidal behavior with prescription opioid medication. J Affect Disord. 2014;158:30–36. doi: 10.1016/j.jad.2014.01.010. [DOI] [PubMed] [Google Scholar]
  • 24.White RA, Azrael D, Papadopoulos FC, Lambert GW, Miller M. Does suicide have a stronger association with seasonality than sunlight? BMJ Open. 2015;5(6):e007403. doi: 10.1136/bmjopen-2014-007403. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Vyssoki B, Kapusta ND, Praschak-Rieder N, Dorffner G, Willeit M. Direct effect of sunshine on suicide. JAMA Psychiatry. 2014;71:1231–1237. doi: 10.1001/jamapsychiatry.2014.1198. [DOI] [PubMed] [Google Scholar]
  • 26.Centers for Disease Control and Prevention. [Accessed December 21, 2015];Health, United States, 2013—Chartbook. http://www.cdc.gov/nchs/hus/chartbook.htm.
  • 27.Koechl B, Unger A, Fischer G. Age-related aspects of addiction. Gerontology. 2012;58:540–544. doi: 10.1159/000339095. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Culberson JW, Ziska M. Prescription drug misuse/abuse in the elderly. Geriatrics. 2008;63:22–31. [PubMed] [Google Scholar]

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