Objectives: To quantify geographic variation in home health expenditures per Medicare home health beneficiary and investigate factors associated with this variation.
Study Design: Retrospective study design analyzing US counties in which at least 1 home health agency served 11 or more beneficiaries in 2016. Several sources of 2016 national public data were used.
Methods: The key variable is county-level Medicare home health expenditures per home health beneficiary. Counties were grouped into quintiles based on per-beneficiary expenditures. Analyses included calculation of coefficients of variation, computation of the ratio of 90th percentile to 10th percentile in expenditures, and linear regression predicting expenditure. The control variables included characteristics of patients, agencies, and communities.
Results: Significant variation in home health expenditures was identified across county quintiles, with a 90th-to-10th-percentile expenditure ratio of 2.5. The percentage of for-profit agencies in the lowest quintile was 15.7 compared with 81.7 in the highest quintile of spending. Unadjusted spending differed by $3864 (95% CI, $3793-$3936), compared with $3611 (95% CI, $3514-$3708) in the adjusted model, between counties in spending quintiles 1 and 5. Although state fixed effects explained nearly 20% of the variation in home health expenditures, 42% of the variation remained unexplained.
Conclusions: Home health care exhibits considerable unwarranted variation in per-patient expenditures across counties, signifying inefficiency and waste. Given the expected growth in home health demand, strategies to reduce unwarranted geographic variation are needed.
Am J Manag Care. 2022;28(7):In Press
Existing research on home health expenditures uses home health data more than 2 decades old. US home health expenditures rose by 113% between 2000 and 2016, from $8.5 billion to $18.1 billion. The Medicare program has implemented several policies in the past decade to combat the growth in expenditures. This study finds the following:
Unwarranted variation in the utilization of health services, or variation not related to differences in patient needs or conditions, is pervasive across health care settings in the United States.1,2 Unwarranted variation in services typically leads to increased health care spending without a concomitant improvement in health care outcomes.3 Reducing unwarranted variation in health care services is necessary to Improve efficiency in both public and private health care delivery systems.4 Concerns over program inefficiency and variation in health care spending led to a 2013 Institute of Medicine (IOM) report that documented the extent of variation in service utilization and expenditures in Medicare. The IOM report found that at least 36% percent of variation in regional spending was unwarranted—not explained by differences in disease burden or severity among patients.1 The IOM report also raised serious concerns with services provided in postacute and long-term care settings, finding that variation in postacute care spending alone accounted for 73% of the total observed variation in Medicare spending.1
Home health care is a critical component of postacute and long-term care services in the United States, which, despite extensive variation, remains understudied.5,6 As of 2017, more than 12,000 Medicare-certified home health agencies participated in the program, delivering care to more than 3 million beneficiaries.7 The number of beneficiaries is expected to increase due to the aging US population and policy changes by CMS.8
Medicare home health expenditures increased 113% from $8.5 billion in 2000 to $18.1 billion in 2016 in part due to the implementation of Home Health Resource Groups (HHRG), a prospective payment system that replaced the Medicare fee-for-service (FFS) mechanism previously used to reimburse home health agencies.7 With the increasing number of participating home health agencies, beneficiaries served, and expenditures under HHRG, information describing the extent of variation in home health care is needed to help policy makers and other stakeholders identify potential reforms.
This study describes regional variation in US home health spending to better understand unwarranted variation. Additionally, the study seeks to identify the sources of variation in home health care spending to inform policy makers on strategies to reduce unwarranted variation.
The conceptual framework is based on the literature describing home health utilization, which is a function of patient, home health agency, and community characteristics. In addition to age and gender, evidence has shown that dual-eligible Medicare and Medicaid beneficiaries use more home health resources.9 The CMS Hierarchical Conditional Category (HCC) risk score, a score assigned to patients based on health status and health conditions, is associated with health care consumption and used to adjust payment for private insurance plans that cover Medicare beneficiaries under Medicare Part C.10 Agency characteristics include ownership type (for profit, not for profit, government) and whether market entry took place during the era of the HHRG prospective payment system implemented in 2000.11,12 The number of primary care physicians in the community affects coordination between physicians and home health professionals and the timeliness of care received.13 Competition among home health agencies, skilled nursing facilities, and hospitals also affects patient choice about the use of home health vs other long-term care services.14
Study Design and Study Sample
This is a retrospective study design that aggregated home health agency data at the county level to examine variation. Analysis of service variation commonly relies on specific geographic areas, such as hospital referral regions, health service areas, or counties.4 The county was used as the geographic unit for analysis because the majority of Medicare home health beneficiaries receive care from agencies in their home county.15 The study trial consists of all Medicare-certified home health agencies serving 11 or more beneficiaries in 2016 across all 50 states and the District of Columbia.
Data sources included the 2016 Medicare Provider Utilization and Payment Data files: the Public Use File Home Health Agencies (PUF HHA) file, the Provider of Services (POS) file, the Home Health Compare (HHC) file, and the Area Health Resources File (AHRF). The PUF HHA file contains agency-level information, including provider identification number, the total Medicare standard payment amount for beneficiaries who receive at least 5 home health visits during their episode of care (non–Low Utilization Payment Adjustment [non-LUPA] beneficiaries), and summarized characteristics of the beneficiaries per home health agency. These include the mean age of beneficiaries, the percentage of dual-eligible beneficiaries, and the mean HCC risk score for patients served. The HHC file provides the agency’s initial date of the contract with CMS and ownership type. The AHRF provides state and county Federal Information Processing Standards (FIPS) codes for each county and details for county-level community characteristics, such as the number of primary care physicians, nursing home beds, and long-term hospital beds. Medicare wage adjustment per county based on Social Security Administration (SSA) state and county codes are available in the Medicare Wage Adjustment files.
The dependent variable is county-level Medicare standard home health expenditure per home health beneficiary because it eliminates geographic factors incorporated by Medicare to adjust provider payment. Per-beneficiary payments were calculated by aggregating agency-level Medicare standard payment amounts at the county level as the numerator and agency-level unique Medicare non-LUPA home health beneficiaries as the denominator.
Quintiles of county-level spending per Medicare home health beneficiary and how quintile assignment relates to the characteristics of patients, providers, and the community are the key measures of interest. Home health agencies behave differently based on when they entered the market in relation to the implementation of HHRG in 2000, as profitable practices in the prospective payment system differed from those in the previous FFS payment system.9 Thus, a measure of tenure as the percentage of home health agencies entering the market before 2000 in each county is included. The percentages of agencies that were government owned and for profit per county, as well as an indicator of agencies operated as part of home care chains, were drawn from the POS file. A link between the wage adjustment file and the PUF HHA data set was created by utilizing a crosswalk between SSA and FIPS codes. For community characteristics, a county-level Herfindahl-Hirschman Index (HHI) of competition was calculated as the sum of the squared market share based on the number of home health beneficiaries served by each agency. Finally, the number of primary care physicians per 1000 population, the number of nursing home beds and long-term hospital beds per 1000 population, and county-level median household income were included at the county level.
Counties were divided into quintiles based on Medicare home health expenditures per home health beneficiary. Counties in quintile 1 had the lowest expenditures; those in quintile 5 had the highest. Additionally, the coefficient of variation (COV) and the ratio of the 90th to 10th percentile for all variables were used to analyze variation in expenditures within and across each quintile.
Ordinary least square regression models were used to assess factors associated with geographic variation in home health expenditure per home health beneficiary. The first model included only 4 dummy variables for counties in quintiles 2 to 5, with those in quintile 1 serving as the reference group. Each iteration of the model successively added patient, agency, and community characteristics. The changes in R2 in each subsequent model show how much variation in home health expenditure per beneficiary is explained by adding patient, agency, and community characteristics.
Counties in each quintile include state effects that influence expenditures. To estimate geographic variation resulting from state-level fixed effects, we excluded the dummy variable for quintiles and added patient, agency, and community characteristics successively and analyzed models with and without state-level fixed effects. Statistical analysis was conducted with Stata 14.2 (StataCorp).
The PUF HHA file contains information on 10,046 home health agencies that served 11 or more patients in the United States in 2016. A total of 1925 of 3141 counties in the United States had at least 1 agency in the PUF HHA file and were included in our analysis. Counties not included in the study were more likely to be rural, with lower population levels and lower median incomes.
Table 1 presents the mean of county-level Medicare home health expenditures per home health beneficiary and county-level patient, agency, and community characteristics of the study trial across quintiles of Medicare home health expenditure. On average, overall Medicare expenditures were $5050 per home health beneficiary, ranging from $3440 in quintile 1 to $7305 in quintile 5. The within-quintile 90th-to-10th-percentile ratio of expenditures was 2.5, and the same ratio for the HCC scores was 1.13. Approximately 30.4% of patients were dual-eligible Medicare and Medicaid beneficiaries, representing 25.8% of beneficiaries in quintile 1 vs 37.6% in quintile 5. Overall, non-White beneficiaries comprised 14.6% of the sample, but this ranged from 8.7% in quintile 1 to 22.5% in quintile 5. Agencies included in the study had an mean HCC score of 2.1. Across quintiles, agency HCC score ranged from a low of 2.0 in quintile 1 to a high of 2.2 in quintile 4. The majority (50.3%) of agencies in the study were for profit; 17.1% were government agencies. Major differences were observed across quintiles in agency ownership. Counties in quintile 1 had the lowest percentage of for-profit agencies (15.6%) but had the highest percentage of government-owned agencies (35.1%). Counties in quintile 5 had the highest percentage of for-profit agencies (81.6%) but the lowest percentage of government-owned agencies (6.7%). Overall, tenured agencies that entered the market before HHRG implementation made up approximately 40% of the study sample; they were 43.3% of agencies in quintile 1 and 34.0% of agencies in quintile 5. Overall, 22.5% of agencies in the trial operated as branches of home health chains, with the highest proportion of chain agencies in quintile 5 (30.5%) and the lowest in quintile 1 (11.2%). Medicare wage adjustments were higher in lower quintiles, with quintile 1 at a wage adjustment of 0.90 and quintile 5 at 0.81. Counties in the study had an mean of 0.2 long-term hospital beds, 0.6 physicians, and 0.4 nursing beds per 1000 population. Median household income was $50,792, and the mean HHI score was 7146.
Figure 1 provides a visualization of the extent of variation in county-level home health expenditure per beneficiary by quintiles. Intraquintile variation was low, with quintiles 1 (COV = 0.1) and 5 (COV = 0.14) exhibiting the highest variation. However, the overall COV for mean expenditures per beneficiary in all study counties was 0.3, indicating substantial overall variation across quintiles. The overall 90th-to-10th-percentile ratio of 2.5 indicates that the 90th percentile mean expenditure is 2.5 times that of the 10th percentile. Figure 2 adds context to the results, identifying counties by quintile of per-patient expenditure by color on a map. The South, particularly Texas, Oklahoma, and Louisiana, has a higher concentration of high-expenditure counties. The New England and West Coast regions have higher concentrations of low-expenditure counties. Counties colored in gray were not included in the study due to a lack of eligible agencies for analysis.
Table 2 provides results from models adjusted for selected variables based on our conceptual framework. Coefficients are first presented in dollar spending for each quintile of per-patient expenditure in an unadjusted model and are then adjusted as we add patient, agency, and community characteristics (the results are available in eAppendix A [eAppendices available at ajmc.com]). In the unadjusted model, unexplained spending differences ranged from $758.28 (95% CI, $686.83-$829.73) between quintiles 1 and 2 up to $3864.70 (95% CI, $3793.25-$3936.16) between quintiles 1 and 5, with an R2 of 0.87; R2 remained unchanged after adding beneficiary, agency, and community characteristics to the model.
State policies and other characteristics likely influence expenditures for home health at the county level. To estimate state effects on variation, we excluded dummy variables for county quintiles and applied the models with and without state fixed effects (Table 3). The R2 between models with (0.50) and without (0.16) state fixed effects changed to 0.58 and 0.39 once agency and community characteristics were added, representing a percent difference reduction from 212.5% to 48.7%. However, the full model with state fixed effects explained only 58% of the variation (the results are available in eAppendix B).
The IOM report on spending variation identified postacute care as the primary driver of spending inefficiency in Medicare, with postacute care accounting for approximately 70% of the variation in patient-level Medicare spending. The home health industry is an integral component of postacute care for Medicare beneficiaries and provides services to 3.5 million beneficiaries annually through more than 12,000 contracted home health agencies. This study provides new information on the extent of spending variation that exists among home health beneficiaries. A prior study suggested that the source of variation in home health services utilization stems from differences in organizational behavior, local resources, or Medicaid factors,16 but in the present study, these measures had a marginal impact on explaining variation. Excluding the 3 states with the highest rates of variation (Texas, Oklahoma, and Louisiana) resulted in a drop in the 90th-to-10th-percentile ratio from 2.5 to 2.0, indicating persistent unexplained variation. And although these 3 high-utilization states opted not to expand Medicaid, a sensitivity analysis exploring the possible impact of Medicaid expansion on home health utilization showed that Medicaid expansion status was not statistically significant in state-level fixed effects or random effects models. After adjusting for patient, agency, and community factors, a difference of more than $2500 remained between per-beneficiary home health expenditures in quintiles 1 and 5, and more than 40% of the variation remained unexplained by the models in the study, an indication of waste and inefficiency in the home health care delivery system.
Several characteristics of beneficiaries, physicians, and agencies likely contribute to this observed variation. To receive services, the Medicare Home Health Benefit requires beneficiaries to meet 3 criteria: being homebound, requiring intermitted skilled care, and receiving a physician referral through a face-to-face encounter assessment.17 Beneficiaries bear no cost sharing and can receive unlimited 60-day episodes of home health care with physician recertification.17 Without beneficiaries sharing financial responsibility for episodes of home health care, cost does not influence beneficiary decision-making about whether another episode of care is needed, what actions they can take themselves to Improve their conditions, and what home health providers can do for them.
Although physicians are required to conduct a face-to-face assessment in order to refer their patients for home health care,18 recent evidence shows that the majority of physicians spend less than 1 to 2 minutes completing the referral form, do not change the referral form once home health professionals submit the renewal certification, and fail to ask home health professionals to clarify any information in the form.13 This physician certification mechanism leaves room for home health agencies to induce unnecessary demand.
At the agency level, home health agencies require only small capital assets to enter and operate in the market and can easily adjust operating systems to maximize profit margins.19 Cabin and colleagues found that for-profit agencies were more costly but provided lower quality of care compared with not-for-profit agencies.11 Under the HHRG, Kim and Norton also found that for-profit agencies that entered the market after 2000 were more financially incentivized to provide therapy visits that yielded high margins than agencies established before the HHRG implementation.12 The success of these new market entrants influenced for-profit peers to adopt similar practice patterns and pursue profitable therapy visits. In addition to for-profit agencies and peer effects, medical fraud is an issue in the home health industry. According to a report by the US Government Accountability Office, home health agencies exhibited the highest rate of medical fraud among all types of health care providers, accounting for more than 40% of medical fraud in the nation in 2010. Although fraud may contribute to unwarranted variation,20 it is not a major source of variation in health care delivery identified by the IOM.1
There are limitations to the study. First, the study analyses rely on data from just 1925 of 3141 US counties due to limitations in the PUF HHA file, which suppresses agencies providing services to 10 or fewer patients in the calendar year. Should the behavior of agencies in counties excluded be different from that of those in our study, our results would not generalize to them. Second, our data include only patient risk factors for gender, race, age, dual eligibility, and CMS HCC score. Other health and social risk factors, such as measures of activities of daily living and the capability and availability of informal caregivers, may affect how often home health professionals visit their patients,21,22 for which our models could not control. Finally, the county, based on the location of the home health agencies, is our geographic unit of measurement. Although the majority of beneficiaries seek care from home health agencies located in their residential county,15 our data do not allow us to distinguish expenditures at the patient level, and some beneficiary spending will be captured in the county of the home health agency rather than their county of residence.
Despite these limitations, our findings have policy implications. First, the Medicare program is a primary payer of home health for older patients and has the purchasing power to set payment rates. However, states regulate the home health market, which influences agency practice patterns. For example, states with certificate-of-need regulations consume less home health care and have lower growth in home health expenditures than those without.23,24 Findings from this study indicate a large effect of state regulatory policies and characteristics on overall spending, with approximately 20% of the observed variation attributable to state fixed effects. These findings indicate that the Medicare program should work with states to address geographic variation through market regulation.
Second, although face-to-face physician assessment encounters are required by policy, evidence in the literature indicates that the physician referral system should be strengthened, either through incentivizing physicians to perform more meaningful assessments or through assignment of legal responsibility to physicians to certify the referral process. Finally, for individual beneficiaries, increasing cost-consciousness through co-pays when accessing the Medicare Home Health Benefit—as recommended by the Medicare Payment Advisory Commission to CMS25—could reduce unnecessary preference-sensitive home health care utilization.
The demand for home health care is expected to continue to grow, given both the preference to stay home and the changing demographics of the country.26 Reducing unwarranted variation is key to strengthening the Medicare home health care benefit. In 2020, CMS implemented a new payment system, the Patient Driven Groupings Model, which eliminates the number of therapy visits from the payment equation.7 We recommend strengthening the physician referral system, adding co-pays for each episode of home health care, and improving collaboration between states and the Medicare program to ensure that the home health care delivery system provides sustainable, efficient, high-quality care to beneficiaries in need.
Author Affiliations: Department of Health Policy and Management, College of Public Health, University of Arkansas for Medical Sciences (RFS, ALML, HFC, JMT), Little Rock, AR.
Source of Funding: None.
Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (RFS, HFC, JMT); acquisition of data (RFS); analysis and interpretation of data (RFS, HFC, JMT); drafting of the manuscript (RFS, ALML, HFC, JMT); critical revision of the manuscript for important intellectual content (RFS, ALML, HFC, JMT); statistical analysis (RFS, HFC); administrative, technical, or logistic support (ALML, JMT); and supervision (HFC, JMT).
Address Correspondence to: Robert F. Schuldt, PhD, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR 72205. Email: Rfschuldt@uams.edu.
1. Institute of Medicine. Variation in Health Care Spending: Target Decision Making, Not Geography. The National Academies Press; 2013. doi:10.17226/18393
2. Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending. part 1: the content, quality, and accessibility of care. Ann Intern Med. 2003;138(4):273-287. doi:10.7326/0003-4819-138-4-200302180-00006
3. Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending. part 2: health outcomes and satisfaction with care. Ann Intern Med. 2003;138(4):288-298. doi:10.7326/0003-4819-138-4-200302180-00007
4. Wennberg JE. Tracking Medicine: A Researcher’s Quest to Understand Health Care. Oxford University Press; 2010.
5. Talaga SR. Medicare home health benefit primer: benefit basics and issues. Federation of American Scientists. March 14, 2013. Accessed January 10, 2020. https://fas.org/sgp/crs/misc/R42998.pdf
6. Newquist DD, DeLiema M, Wilber KH. Beware of data gaps in home care research: the streetlight effect and its implications for policy making on long-term services and supports. Med Care Res Rev. 2015;72(5):622-640. doi:10.1177/1077558715588437
7. Medicare Payment Advisory Commission. Home health care services. In: Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2019:225-248. Accessed December 4, 2019.
8. Knickman JR, Snell EK. The 2030 problem: caring for aging baby boomers. Health Serv Res. 2002;37(4):849-884. doi:10.1034/j.1600-0560.2002.56.x
9. Joynt Maddox KE, Chen LM, Zuckerman R, Epstein AM. Association between race, neighborhood, and Medicaid enrollment and outcomes in Medicare home health care. J Am Geriatr Soc. 2018;66(2):239-246. doi:10.1111/jgs.15082
10. Pope GC, Ellis RP, Ash AS, et al. Diagnostic cost group hierarchical condition category models for Medicare risk adjustment. CMS. December 21, 2000. Accessed March 13, 2020. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Reports/downloads/pope_2000_2.pdf
11. Cabin W, Himmelstein DU, Siman ML, Woolhandler S. For-profit Medicare home health agencies’ costs appear higher and quality appears lower compared to nonprofit agencies. Health Aff (Millwood). 2014;33(8):1460-1465. doi:10.1377/hlthaff.2014.0307
12. Kim H, Norton EC. Practice patterns among entrants and incumbents in the home health market after the prospective payment system was implemented. Health Econ. 2015;24(suppl 1):118-131. doi:10.1002/hec.3147
13. Boyd CM, Leff B, Bellantoni J, et al. Interactions between physicians and skilled home health care agencies in the certification of Medicare beneficiaries’ plans of care: results of a nationally representative survey. Ann Intern Med. 2018;168(10):695-701. doi:10.7326/M17-2219
14. Li Q, Rahman M, Gozalo P, Keohane LM, Gold MR, Trivedi AN. Regional variations: the use of hospitals, home health, and skilled nursing in traditional Medicare and Medicare Advantage. Health Aff (Millwood). 2018;37(8):1274-1281. doi:10.1377/hlthaff.2018.0147
15. Franco SJ. Medicare home health care in rural America. Policy Anal Brief W Ser. 2004;(1):1-4.
16. Welch HG, Wennberg DE, Welch WP. The use of Medicare home health care services. N Engl J Med. 1996;335(5):324-329. doi:10.1056/NEJM199608013350506
17. Medicare & home health care. CMS. Updated September 2020. Accessed November 9, 2021. https://www.medicare.gov/Pubs/pdf/10969-Medicare-and-Home-Health-Care.pdf
18. Patient Protection and Affordable Care Act, Pub L No. 111-148 (2010) Sec. 6407. Accessed March 13, 2020. https://www.congress.gov/111/plaws/publ148/PLAW-111publ148.pdf
19. Medicare Payment Advisory Commission. Home health services. In: Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2011:173-199. Accessed January 10, 2020. https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/Mar11_Ch08.pdf
20. Health care fraud: types of providers involved in Medicare, Medicaid, and the Children’s Health Insurance Program cases. US Government Accountability Office. September 2012. Accessed March 13, 2020. https://www.gao.gov/assets/650/647849.pdf
21. Osakwe ZT, Larson E, Andrews H, Shang J. Activities of daily living of home healthcare patients. Home Healthc Now. 2019;37(3):165-173. doi:10.1097/NHH.0000000000000736
22. Cho E, Kim EY, Lee NJ. Effects of informal caregivers on function of older adults in home health care. West J Nurs Res. 2013;35(1):57-75. doi:10.1177/0193945911402847
23. Polsky D, David G, Yang J, Kinosian B, Werner R. The effect of entry regulation in the health care sector: the case of home health. J Public Econ. 2014;110:1-14. doi:10.1016/j.jpubeco.2013.11.003
24. Rahman M, Galarraga O, Zinn JS, Grabowski DC, Mor V. The impact of certificate-of-need laws on nursing home and home health care expenditures. Med Care Res Rev. 2016;73(1):85-105. doi:10.1177/1077558715597161
25. Medicare Payment Advisory Commission. Home health care services. In: Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2017:229-253. Accessed September 10, 2019. https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/mar17_medpac_ch9.pdf
26. Fixing to stay: a national survey on housing and home modification issues. AARP. May 2000. Accessed March 22, 2019. https://assets.aarp.org/rgcenter/il/home_mod.pdf
Several of the authors you read on Hackaday are ham radio operators and we’ve often kicked around having a Hacker Chat about “Why be a ham today?” After all, you can talk to anyone in the world over the Internet or via phone, right? What’s the draw?
The Radio Society of Great Britain had the same thought, apparently, and produced a great video to answer the question. They mention the usual things: learning about technology, learning about people in other parts of the world, disaster communications, and radiosport (which seems to be more popular outside the United States; people compete to find hidden transmitters).
In addition, they talked a lot about how hams get involved with space communications, ranging from talking via satellites, to talking to people on the space station, to actually building small satellites. As the narrator says, there are “hundreds of ways to have techie fun” with ham radio.
One thing we noticed they showed but didn’t say a lot about, though, is the educational opportunities. You can learn a lot, and working with kids to help them learn is often very rewarding (and you usually learn something, too). Just to forestall the comments that this post isn’t hack related, we’ll note two things: there is a Raspberry Pi shown and just past the two-minute mark, there is a very clever hacked together Morse code key.
We talk a lot about ham radio, ranging from Arduino-based digital modes to putting together portable stations (you can see a similar one in the video, too). One other thing we noticed they don’t mention: it is generally much easier to get a license today than ever before. Most countries (including the United States) have abolished the Morse code requirements, so while some hams still enjoy CW (hamspeak for operating Morse code), it isn’t a requirement.
When you start a business, there’s one thing you must be on top of once money starts rolling in – taxes. Conducting business in the U.S. without properly managing your tax payments to the local, state and federal government could result in massive fines, persistent bank liens, or even the government stepping in to shut you down.
Whether you’re starting a new business at the turn of the new year or looking forward to your first quarterly tax payment, this moment is critical for a small business owner. Depending on how your business is organized, you may have different tax requirements from other companies. Whether you’re an LLC, a partnership or an S corporation, you’ll always be paying taxes as you go, reporting income as you earn it throughout the tax year.
While there are countless experts and professionals to help you navigate your business’s fledgling months, we collected some tips and federal forms you can address right now to make sure your first or next quarterly tax payment goes smoothly.
Maybe you’ve already done this step, but for those who haven’t, establishing your business’s structure is just as important as finding a location and name for your business. There are many business structures to choose from, but most small businesses establish themselves as a limited liability company (LLC), a sole proprietorship or a partnership of some kind.
There are numerous tax, financial and legal benefits to each type of business entity, so finding the right configuration for your business is important. You will have to file within the state where your business will operate. The federal Small Business Association (SBA) can help you determine where and how you can do that in your state.
As a partnership, you’ll likely fill out Form 1065 with the IRS, while corporations file Form 1120. If you want to file as an S-corp, you will need to file Form 2553 and then annually file an 1120S. Sole proprietorships and self-employed individuals must file a 1040 Schedule C or 1040 C-EZ, though the latter requires that you turn a profit, have expenses no greater than $5,000, have no employees or inventory, and are not deducting or claiming the depreciation of your home.
Also remember that each type of entity files its taxes with the IRS at different times, with partnerships and corporations generally filing on March 15 and sole proprietorships and single-member LLCs filing on April 15.
While the federal government doesn’t get involved in your company’s structure, it will join your state in needing a business tax identification number from you. Businesses are required to have these numbers, also known as employer identification numbers (EINs), to pay taxes.
To get an EIN for your business, you must apply at your state’s department of taxation. While you’re there, you can also submit your SS-4 to cover your federal requirement.
If you have enough business that you need employees to help you run it, you’ll need to file a number of different tax forms based on their employment statuses.
Regardless of how many people you hire at the start, Anthony Mezzasalma, a CPA with Mezzasalma Advisors, said you should immediately consider engaging with a payroll provider. These companies help you handle things like quarterly payroll tax filings, W-2 forms and other important aspects of managing a staff. Automating some of the process, Mezzasalma said, helps ensure you won’t fall foul of payroll tax law.
If you only hire a small staff and feel confident in your abilities, however, you should remember to file W-2: Wage and Tax Statement Forms for each employee who receives a salary, wage or other form of compensation. This form reports wages or salaries your business pays to employees for the calendar year as well as the taxes withheld from them. It also reports FICA taxes to the Social Security Administration. While you can file those with the IRS, you can also submit them through the federal Social Security Administration’s website. This form must be filed by Jan. 31.
Each employee will also have to fill out Form W-4: Employee’s Withholding Allowance Certificate to note any deductions they want taken out and how much tax they want withheld from their wages. Ideally, it’s the exact amount due on an employee’s 1040 form at the end of the year, though the amounts often don’t match up.
If you intend to hire any independent contractors or vendors, you’ll need to file Form 1099-MISC. Required for anyone you pay at least $600 a year, this form can also be used to report any “direct sales of at least $5,000 of consumer products to a buyer for resale anywhere other than a permanent retail establishment,” according to the IRS. Once filed by the March 15 deadline, the 1099 is sent out as three copies, with the business, the individual and the IRS each getting one.
You’ll need any individuals covered by a 1099 to also file Form W-9: Request for Taxpayer Identification Number and Certification. Mezzasalma warns that the W-9, due on Jan. 31, is incredibly important to ensure your business complies with federal tax law.
“I suggest [new business owners] not pay any vendor until they are in possession of the W-9 form, as these are much harder to get after the fact,” he said. “This step is important because there are penalties for not issuing 1099 forms when you are supposed to.”
In addition to your employees’ wages or your personal income tax as a business owner, you will have other forms if you provide health insurance or retirement plans.
Following the passage of the Affordable Care Act, businesses must be aware of Form 1095-B or 1095-C, depending on how many employees they have. These forms are required if your business offers health insurance as a benefit for employees. Failure to file these forms will incur penalties from the government.
The U.S. tax code is a labyrinth that requires years of study to understand. Any business tax missteps can lead to major financial problems and even affect your personal life. You can take additional steps to avoid these problems.
It’s important to open a business bank account and keep your business books and records separate from your personal finances. The latter point is important, Mezzasalma said, as the IRS requires separate records for businesses. It’s also a good practice because it “helps to ensure there are no missed income and expense records.”
It’s imperative to keep your business tax deadlines straight, especially since the IRS has moved up some of them to combat identity theft.
“The IRS was making it rain, so to speak, by quickly disbursing tax returns without verifying the information,” Mezzasalma said, which led to scammers filing fake tax returns in other people’s names. “Now, the IRS wants the information earlier so they can go through all the information and verify it before paying out the returns.”
The best way to avoid missing tax forms or deadlines is to leave the tax requirements to the professionals. If you hire an accountant, they can ensure that you never miss a deadline and always remain in compliance with federal and state law.
If you’re hellbent on doing your own business taxes, Mezzasalma urges you to consider purchasing accounting software to keep your records straight.
“Being able to capture, organize and present your income and expenses will assist in income tax preparation,” he said. “A box of receipts will not do!”
The venerable ATX standard was developed in 1995 by Intel, as an attempt to standardize what had until then been a PC ecosystem formed around the IBM AT PC’s legacy. The preceding AT form factor was not so much a standard as it was the copying of the IBM AT’s approximate mainboard and with it all of its flaws.
With the ATX standard also came the ATX power supply (PSU), the standard for which defines the standard voltage rails and the function of each additional feature, such as soft power on (PS_ON). As with all electrical appliances and gadgets during the 1990s and beyond, the ATX PSUs became the subject of power efficiency regulations, which would also lead to the 80+ certification program in 2004.
Starting in 2019, Intel has been promoting the ATX12VO (12 V only) standard for new systems, but what is this new standard about, and will switching everything to 12 V really be worth any power savings?
As the name implies, the ATX12VO standard is essentially about removing the other voltage rails that currently exist in the ATX PSU standard. The idea is that by providing one single base voltage, any other voltages can be generated as needed using step-down (buck) converters. Since the Pentium 4 era this has already become standard practice for the processor and much of the circuitry on the mainboard anyway.
As the ATX PSU standard moved from the old 1.x revisions into the current 2.x revision range, the -5V rail was removed, and the -12V rail made optional. The ATX power connector with the mainboard was increased from 20 to 24 pins to allow for more 12 V capacity to be added. Along with the Pentium 4’s appetite for power came the new 4-pin mainboard connector, which is commonly called the “P4 connector”, but officially the “+12 V Power 4 Pin Connector” in the v2.53 standard. This adds another two 12 V lines.
In the ATX12VO standard, the -12 V, 5 V, 5 VSB (standby) and 3.3 V rails are deleted. The 24-pin connector is replaced with a 10-pin one that carries three 12 V lines (one more than ATX v2.x) in addition to the new 12 VSB standby voltage rail. The 4-pin 12 V connectors would still remain, and still require one to squeeze one or two of those through impossibly small gaps in the system’s case to get them to the top of the mainboard, near the CPU’s voltage regulator modules (VRMs).
While the PSU itself would be somewhat streamlined, the mainboard would gain these VRM sections for the 5 V and 3.3 V rails, as well as power outputs for SATA, Molex and similar. Essentially the mainboard would take over some of the PSU’s functions.
The folk over at GamersNexus have covered their research and the industry’s thoughts on the subject of ATX12VO in an article and video that were published last year. To make a long story short, OEM system builders and systems integrators are subject to pretty strong power efficiency regulations, especially in California. Starting in July of 2021, new Tier 2 regulations will come into force that add more strict requirements for OEM and SI computer equipment: see 1605.3(v)(5) (specifically table V-7) for details.
In order to meet these ever more stringent efficiency requirements, OEMs have been creating their own proprietary 12 V-only solutions, as detailed in GamersNexus’ recent video review on the Dell G5 5000 pre-built desktop system. Intel’s ATX12VO standard therefore would seem to be more targeted at unifying these proprietary standards rather than replacing ATX v2.x PSUs in DIY systems. For the latter group, who build their own systems out of standard ATX, mini-ITX and similar components, these stringent efficiency regulations do not apply.
The primary question thus becomes whether ATX12VO makes sense for DIY system builders. While the ability to (theoretically) increase power efficiency especially at low loads seems beneficial, it’s not impossible to accomplish the same with ATX v2.x PSUs. As stated by an anonymous PSU manufacturer in the GamersNexus article, SIs are likely to end up simply using high-efficiency ATX v2.x PSUs to meet California’s Tier 2 regulations.
Ever since the original ATX PSU standard, the improvements have been gradual and never disruptive. Although some got caught out by the negative voltage rails being left out when trying to power old mainboards that relied on -5 V and -12 V rails being present, in general these changes were minor enough to incorporate these into the natural upgrade cycle of computer systems. Not so with ATX12VO, as it absolutely requires an ATX12VO PSU and mainboard to accomplish the increased efficiency goals.
While the possibility of using an ATX v2.x to ATX12VO adapter exists that passively adapts the 12 V rails to the new 10-pin connector and boosts the 5 VSB line to 12 VSB levels, this actually lowers efficiency instead of increasing it. Essentially, the only way for ATX12VO to make a lot of sense is for the industry to switch over immediately and everyone to upgrade to it as well without reusing non-ATX12VO compatible mainboards and PSUs.
Another crucial point here is that OEMs and SIs are not required to adopt ATX12VO. Much like Intel’s ill-fated BTX alternative to the ATX standard, ATX12VO is a suggested standard that manufacturers and OEMs are free to adopt or ignore at their leisure.
Important here are probably the obvious negatives that ATX12VO introduces:
Add to this potential alternatives like Seasonic’s CONNECT module. This does effectively the same as the ATX12VO standard, removing the 5 V and 3.3 V rails from the PSU and moving them to an external module, off of the mainboard. It can be fitted into the area behind the mainboard in many computer cases, making for very clean cable management. It also allows for increased efficiency.
As PSUs tend to survive at least a few system upgrades, it could be argued that from an environmental perspective, having the minor rails generated on the mainboard is undesirable. Perhaps the least desirable aspect of ATX12VO is that it reduces the modular nature of ATX-style computers, making them more like notebook-style systems. Instead, a more reasonable solution here might be that of a CONNECT-like solution which offers both an ATX 24-pin and ATX12VO-style 10-pin connectivity option.
In the larger scheme of power efficiency it can be beneficial to take a few steps back from details like the innards of a computer system and look at e.g. the mains alternating current (AC) that powers these systems. A well-known property of switching mode power supplies (SMPS) like those used in any modern computer is that they’re more efficient at higher AC input voltages.
This can be seen clearly when looking for example at the rating levels for 80 Plus certification. Between 120 VAC and 230 VAC line voltage, the latter is significantly more efficient. To this one can also add the resistive losses from carrying double the amps over the house wiring for the same power draw at 120 V compared to 230 VAC. This is the reason why data centers in North America generally run on 208 VAC according to this APC white paper.
For crypto miners and similar, wiring up their computer room for 240 VAC (North American hot-neutral-hot) is also a popular topic, as it directly boosts their profits.
Whether ATX12VO will become the next big thing or fizzle out like BTX and so many other proposed standards is hard to tell. One thing which the ATX12VO standard has against it is definitely that it requires a lot of big changes to happen in parallel, and the creation of a lot of electronic waste through forced upgrades within a short timespan. If we consider that many ATX and SFX-style PSUs are offered with 7-10 year warranties compared to the much shorter lifespan of mainboards, this poses a significant obstacle.
Based on the sounds from the industry, it seems highly likely that much will remain ‘business as usual’. There are many efficient ATX v2.x PSUs out there, including 80 Plus Platinum and Titanium rated ones, and Seasonic’s CONNECT and similar solutions would appeal heavily to those who are into neat cable management. For those who buy pre-built systems, the use of ATX12VO is also not relevant, so long as the hardware is compliant to all (efficiency) regulations. The ATX v2.x standard and 80 Plus certification are also changing to set strict 2-10% load efficiency targets, which is the main target with ATX12VO.
What would be the point for you to switch to ATX12VO, and would you pick it over a solution like Seasonic CONNECT if both offered the same efficiency levels?
(Heading image: Asrock Z490 Phantom Gaming 4SR with SATA power connected, credit: c’t)
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The coexistence of HIV and cancer is a growing global health issue as more people living with HIV/AIDS (PLWHA) gain access to combined antiretroviral therapy (cART). In the cART era, PLWHA in high-income countries show a 10- to 20-fold higher incidence of AIDS-defining non-Hodgkin lymphomas (NHL), such as diffuse large B-cell lymphoma (DLBCL), than the general population.1 In such settings, treatment with cART, rituximab, and combination chemotherapy has resulted in outcomes for AIDS-related (AR) NHL (AR-NHL) comparable to those for HIV-negative individuals.2 However, the successful use of such treatments in PLWHA requires supportive measures to minimize treatment-related mortality and maximize overall survival (OS).
Countries in sub-Saharan Africa (SSA) bear the highest burdens of both HIV infection and AR-NHL. However, in most SSA settings, delivering complex chemotherapy regimens with adequate supportive care is difficult because of limited resources.3 Scarce resources also impede accurate pathologic classification, often resulting in suboptimal treatment, with many morphologically high-grade lymphomas, including Burkitt lymphoma, being treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP).4,5 A recent prospective registry study in Malawi showed that concurrent cART and CHOP could be delivered safely and with efficacy similar to that in resource-rich environments.6,7 However, these data were generated from a single urban referral center with strong external academic partnerships, with uncertain generalizability to other SSA settings. Although numerous efforts are ongoing to strengthen the cancer diagnostic and treatment infrastructure in SSA, patient access to centers with robust capabilities for administering intravenous chemotherapy with adequate supportive care remain limited. These realities have prompted interest in developing effective, less intensive treatments for AR-NHL.
The oral chemotherapy regimen (oCT), developed by Remick et al8 in the early 1990s, was used by Mwanda et al9 in SSA in the 2000s to address some of these challenges. The regimen, comprising lomustine, etoposide, cyclophosphamide, and procarbazine, was designed to avoid the need for intravenous administration, while minimizing myelosuppression. Of 49 participants recruited between 2001 and 2005 in Kenya and Uganda, 40 (82%) were assessable, with an overall response rate of 78%. Additionally, only 3 treatment-related deaths occurred, and only 5% of chemotherapy cycles required dose reduction for neutropenia.
Although these preliminary results were encouraging, this trial had several important limitations. Only 18 of 49 participants (37%) received concurrent cART, which does not reflect current HIV treatment patterns in SSA. Staging and response assessment were limited in most cases to clinical examination, chest radiograph, and abdominal ultrasound, with 16 participants (31%) classified as stage I or II. Initial diagnosis was based on hematoxylin and eosin (H&E) staining, but subsequent review of a subset of patients showed a range of morphologic subtypes, with only 25% being DLBCL. Given these limitations and interest in comparing the oCT regimen with CHOP, the regional standard-of-care (SOC), the AIDS Malignancy Consortium (AMC) developed a randomized, phase II trial of CHOP versus oCT in AR-DLBCL.
The trial, entitled Randomized, Phase II Trial of CHOP Versus Oral Chemotherapy With Concomitant Antiretroviral Therapy in Patients With HIV-Associated Lymphoma in Sub-Saharan Africa (AMC-068; ClinicalTrials.gov identifier: NCT01775475), was the first SSA therapeutic trial developed by the AMC and was eventually opened to accrual at 4 SSA AMC sites. Although the study was ultimately terminated early because of slow accrual, several important lessons were learned, and this experience has informed the expanding AMC international program. In this article, we review the AMC-068 experience, describing specific challenges faced by the investigative team, solutions identified, and how the lessons learned are being applied to future AMC clinical trials in SSA.
AMC-068 PROTOCOL DESIGN AND TIMELINE
AMC-068 was developed and approved by the AMC and National Cancer Institute (NCI) in 2012. The target population was PLWHA receiving effective cART who had biopsy-proven, untreated stage III or IV DLBCL. Participants were randomly assigned to receive CHOP or oCT. Relevant inclusion criteria were ability to provide informed consent; age ≥ 18 years; confirmed HIV infection; biopsy-proven DLBCL, defined by large-cell morphology on H&E staining, CD20, or Pax5 positivity based on immunostaining, and a proliferation rate of ≤ 90% determined by immunostaining for Ki67; Eastern Cooperative Oncology Group (ECOG) performance status 0-3; estimated life expectancy > 6 weeks; adequate bone marrow, renal, and liver function; negative CSF cytology within 4 weeks; and cART consistent with national guidelines. The proliferation rate specification was included to avoid potential administration of low-intensity treatment of Burkitt and other high-grade, highly proliferative B-cell lymphoma subtypes. Relevant exclusion criteria were > 10 days of corticosteroid treatment more than physiologic replacement, evidence of CNS lymphoma, and active infections. Participants were stratified by CD4 count (< or ≥ 100) and ECOG performance status (< 2 v ≥ 2). The primary outcome was OS. Secondary outcomes included overall response rate, progression-free survival, and safety and tolerance of the respective regimens. Exploratory objectives included treatment completion, adherence, and effects of protocol treatment on HIV control. Details of the drug regimens are provided in Table 1.
The target trial size of 90 evaluable participants, 45 in each arm, was based on the null hypothesis that CHOP and oCT did not differ with respect to OS, with the alternative hypothesis that the median OS duration would be 18 months for CHOP and 12 months for the oral regimen. Based on estimates of the number of potentially eligible participants at the participating AMC sites, accrual was expected to be completed in 24 months, with an additional 24 months of follow-up.
Although originally designed in 2011-2012, the study did not open to accrual until November 2016. Forty-two potential participants were screened over 24 months, but only 7 were successfully randomly assigned, leading ultimately to the decision to terminate the study. Of the 7 patients recruited, 2 remained in follow-up and 5 had relapsed or died as of February 2020. Despite this, the study made valuable contributions to site infrastructure, and important lessons were learned regarding protocol development and implementation.
CHALLENGES OF AMC-068
AMC-068 was originally conceived as a single-arm, multicenter study intended to further investigate the oCT regimen in a better-characterized patient population that was uniformly treated with concurrent cART. After discussion between investigators and NCI, the study was redesigned as a 2-arm randomized phase II trial to address concerns that the single-arm design would not establish the role of oCT in relation to the regional SOC, CHOP, and that the absence of an SOC arm in the trial was not ethically sound. Additional obstacles during protocol development included limited baseline data to inform study design; lack of consensus among investigators and regulatory bodies regarding appropriateness of the oral regimen and need for randomized comparison with CHOP; and heterogeneity across the SSA sites of standards for diagnosis, staging, and treatment. At the time of initial protocol development, limited published information existed on the epidemiology of AR-NHL in SSA. As highlighted by numerous authors, SSA cancer registries informing data sources, such as GLOBOCAN, have significant limitations,10 compounded by deficits in pathology infrastructure. This has contributed to uncertainty of AR-NHL classification, a key issue already encountered in the Mwanda et al9 study and also in separate studies in Malawi.6
The final challenge was the need to create a protocol that was feasible to implement at multiple sites across SSA. Typically, cancer clinical trial sites in high-income countries have modest differences in local SOC, which can be accommodated within a single clinical trial protocol without undermining the primary objectives. In contrast, the SOC and available resources at the SSA AMC sites varied widely, which changed rapidly, but inconsistently, across all sites. For example, the initial protocol draft assumed no access to hematopoietic colony stimulating factors to manage treatment-related neutropenia. However, after one site indicated that allowing use of granulocyte–colony stimulating factor (G-CSF) was needed to be consistent with their local SOC, the protocol was modified to incorporate 2 separate dose modification schemes for sites with and without G-CSF access. Thereafter, before the protocol was activated, the site that originally requested inclusion of G-CSF declined to participate because persistent concerns of consistency with local SOC, whereas other sites had variable access to G-CSF. By the time the protocol closed, all but 1 site had access to G-CSF, although local protocols for its use continued to vary greatly.
The pre-activation period lasted from final protocol approval in 2012 until the first site activation in 2016, significantly longer than for US-based AMC lymphoma protocols, which historically averaged approximately 100 days. Delays resulted from regulatory approval timelines, establishing and maintaining supply chains, and development of site capacity. Each site had multiple required levels of regulatory approval and an often rapidly changing regulatory environment. In addition, because the study was conducted with US NCI support, each of the local investigators was required to maintain NCI registration, a new and unfamiliar requirement for most SSA investigators.
Although meeting these regulatory requirements took longer than expected, the development and maintenance of a multinational supply chain was even more difficult. Sourcing of study agents was complex and costly. Not all study agents were available in-country. In addition, because of stockouts and unreliable source and quality of locally available drugs, a decision was made to centrally source all study drugs in the United States. Therefore, the AMC needed to maintain a continuous supply of 8 chemotherapeutic agents for each clinical trial site. Furthermore, the cyclophosphamide preparation supplied for the trial required 5% dextrose for intravenous (IV) administration, which was not readily available locally. The chemotherapy supply and procurement processes were complicated by rapid increases in cost of some agents (eg, IV cyclophosphamide), which exceeded the amounts originally budgeted for drugs and required the AMC to solicit donations from pharmaceutical companies. The drug importation process required procurement of documents not normally part of the clinical trial workflow (eg, certificates of analysis) to obtain import permits across multiple countries, while maintaining controlled ambient and cold-chain shipment. Because of delays during this period, donated and purchased pharmaceutical lots expired, and drugs needed replacement. Finally, this period coincided with shortages and escalating costs of specific drugs in the oCT investigational regimen.11 We also found supply chains for standard medical supplies (eg, cannulas, infusion lines) were often unreliable, but could be acquired through supply chains within SSA.
Development of Site Infrastructure
This period was marked by significant investment in site capacity to perform cancer research, building on established clinical and research infrastructure for HIV. Although prospective SSA AMC sites underwent evaluation and audit of readiness for clinical research, the initial site selection process was carried out with an explicit plan for targeted investment to ensure site adherence to international standards. Immunohistochemistry (IHC) expertise and capability, expertise in research pharmacy and nursing, and site-specific policies and procedures for clinical research were developed at all sites through a combination of workshops, facilitated training, ongoing site mentorship, and site audits and evaluations.
Pathology: A significant component of this process was the development of pathology certification, ongoing collaborative pathology reviews, and establishing access to IHC, led by experienced hematopathologists (E.C. and A.C.). Each site was required to have 2 certified pathologists. To qualify, each site pathologist had to show the ability to correctly identify patients with DLBCL based on H&E-stained slide images. To demonstrate proficiency with IHC, each laboratory was required to submit examples of H&E, CD20, and Ki67 slides prepared by the laboratory. Approved pathologists were also required to participate in and present screened study patients on monthly calls led by E.C. and A.C.
Pharmacy: The AMC provided group trainings focusing on pharmacy best practices (eg, familiarity with the US NCI Investigational Agent Drug Accountability Record Form) and engaged an expert South African oncology pharmacist to conduct onsite pharmacy training and review of site-specific pharmacy standard operating procedures (SOPs).
Nursing: Training for chemotherapy nurses was provided by an expert oncology nurse who conducted a centralized training workshop before study activation.
Support for Staging and Response Assessment: To facilitate accurate staging and response assessment, the AMC reimbursed sites for the cost of protocol-mandated computed tomography scans. Training in lymphoma response assessment was provided to investigators by a US-based lymphoma expert as part of study start-up activities.
Site-Specific Implementation Plans and SOPs: Guided development of site-specific SOPs for the research pharmacy, chemotherapy preparation, and administration were used to augment existing clinical pharmacy and nursing services.
AMC-068 opened to recruitment in Kenya in late 2016. By late 2018, 42 patients had been screened across 4 sites in Kenya, Malawi, Uganda, and Zimbabwe, but only 7 were eligible for randomization. Reasons for ineligibility are presented in Table 2. As shown, of the 35 ineligible patients, the majority were excluded because of non-DLBCL pathology, Ki67 greater than 90%, stage I or II disease, or end-organ dysfunction. Additionally, all sites had some patients who were never screened because of poor performance status or end-organ dysfunction. The mismatch between expected presentation rates of eligible patients with AR-NHL DLBCL versus the genuine accrual numbers highlights the impact that unreliable pathology and clinical data can have on study design and implementation in resource-constrained settings. Trials like AMC-068 can begin to bridge those gaps and better inform subsequent trial design. The late presentation arose from poor access of many potential patients to health care facilities and delays from initial presentation of lymphoma symptoms to referral to regional or national centers capable of diagnosing and treating lymphoma. Many of these delays arose from remediable issues such as lack of transport and available funds, and delays in procuring pathology specimens for initial review. On study closure, the AMC study team was continuing to work with sites to establish solutions to these logistic hurdles, including reimbursing sites for the cost of diagnostic biopsies performed as prescreening procedures.
KEY SOLUTIONS IDENTIFIED
Ultimately, the failure of AMC-068 to recruit eligible patients in a timely manner was due to accrual expectations based on scarce preexisting data and the realities of conducting a complex, multinational, randomized clinical trial in SSA for AR-NHL that met rigorous NCI standards. However, several key insights emerged from this effort.
Multidisciplinary site assessment and support are needed. The original site selection process by the AMC was undertaken by trial operations experts and US-based medical oncologists. Although sites were evaluated by survey and a structured audit tool informed by multiple disciplines (eg, pathology, laboratory services), early engagement at sites by multidisciplinary teams helped identify protocol-specific requirements for site development. As a result, the AMC succeeded in establishing working relationships among oncologists, pathologists, laboratory technicians, pharmacists, study coordinators, and nurses at multiple SSA sites to help assess local requirements, conduct trainings, and identify local solutions when logistical barriers arose. These connections across disciplines have since been leveraged for the successful conduct of other AMC trials in SSA and for the design and implementation of additional protocols currently in development.
Cancer registration and diagnostic facilities in SSA significantly affect the ability to accurately project accrual for clinical trials. Descriptive epidemiology related to cancer burden is highly dependent on pathology and cancer registration infrastructure. GLOBOCAN, a WHO-supported population cancer registry, is cited extensively, but important limitations exist in SSA, where 20 countries lack any registry. Even in countries with existing registries, population coverage ranges from 2.3%-100%, and crude population-level data, even in high-quality registries, often have major limitations with respect to staging or histologic classification,10 as is required for clinical trial planning. Contributing to and compounding this uncertainty, pathology across SSA is understaffed and underdeveloped.12 In 2013, many countries had < 1 pathologist per million population.13 Although AMC-068 sites were intentionally selected partly based on their strong pathology services, the impact of local diagnostic constraints was underestimated initially, and this trial provided a vehicle for working with sites to Improve access to and expertise in IHC essential for lymphoma classification.14,15 Despite this, delay in referrals to tertiary centers for biopsy often compounded late diagnosis and difficulties in identifying eligible patients. However, AMC-068 served to establish collaboration and certification procedures with site pathologists, Improve local IHC capabilities, and facilitate collaborations essential for the eventual creation of a regional biobank for HIV malignancy in SSA,16 all of which will support future clinical trials and routine care delivery.17
Establishing and maintaining reliable supply chains are critical. AMC-068 faced significant hurdles in procurement of drugs and supplies. During the pre-activation period, it quickly became evident that the time and effort required to oversee the procurement and import/export for these commodities was substantial. To address this, the AMC has developed a local procurement process for drugs and supplies. This approach has clear limitations, including limited availability and stockouts of pharmaceuticals that are well described in SSA,18,19 not to mention sometimes unreliable drug quality.20 However, when local supply chains for specific, high-quality commodities exist, these can be effectively used and diminish the logistical and administrative burden of conducting cancer clinical trials.
Foreign collaborators must work closely with SSA investigators to understand local SOCs and barriers to trial participation at the individual and health system level. Throughout the process of developing and conducting AMC-068, US and SSA investigators communicated extensively to develop and maintain a shared understanding of local capability and approaches. This was critical because members of the research team had limited experience outside their own health care environment. Creating clear channels for bilateral exchange and dialogue helped bridge these differences to develop a shared strategic vision for priority disease areas and interventions that AMC should pursue in future SSA clinical trials that are both innovative and implementable.
In retrospect, the AMC-068 protocol was an ambitious effort to initiate a multinational, collaborative, randomized clinical trial for AR-NHL at multiple sites in SSA. Because of a mismatch between the protocol-specified population and characteristics of the screened population, this trial was closed early because of poor accrual. However, the effort that went into AMC-068 over many years has yielded strategic insights that will inform the AMC agenda in SSA moving forward and help build a strong operational foundation that will support innovative trials for prevention and treatment of HIV-associated malignancies in SSA for years to come.
Supported by the National Cancer Institute of the National Institutes of Health under Award No. UM1CA121947. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Conception and design: Robert M. Strother, Satish Gopal, Amy Chadburn, Ariela Noy, Ethel Cesarman, Jeannette Y. Lee, Scot C. Remick, Naftali Busakhala, Elson Mberi, Ntokozo Ndlovu, Susan E. Krown
Administrative support: Robert M. Strother, Scot C. Remick
Provision of study materials or patients: Robert M. Strother, Jeannette Y. Lee, Naftali Busakhala, Elson Mberi, Ntokozo Ndlovu
Collection and assembly of data: Robert M. Strother, Satish Gopal, Meg Wirth, Amy Chadburn, Ariela Noy, Ethel Cesarman, Naftali Busakhala, Bongani Kaimila, Elson Mberi, Ntokozo Ndlovu, Abrahams Omoding, Susan E. Krown
Data analysis and interpretation: Robert M. Strother, Satish Gopal, Meg Wirth, Amy Chadburn, Ariela Noy, Ethel Cesarman, Naftali Busakhala, Bongani Kaimila, Susan E. Krown
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors
AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/go/site/misc/authors.html.
Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).
Robert M. Strother
Research Funding: Lilly (Inst)
Research Funding: Velosbios (Inst)
Consulting or Advisory Role: MorphoSys
Speakers' Bureau: Prime Oncology
Research Funding: Pharmacyclics, Rafael Pharmaceuticals
Travel, Accommodations, Expenses: Pharmacyclics, Janssen Oncology
Patents, Royalties, Other Intellectual Property: US Patent Application No. 16/092,628 entitled: Novel nucleoside analogs and use thereof in therapeutic treatment, filed 10/10/2018 (Inst), US Provisional Patent Application Ser. No. 62/483,563 entitled: TINY: Tiny isothermal nucleic acid amplification system, filed April 10, 2017 (Inst), PCT application No. US18/26865, filed on April 10, 2017, entitled System and method for isothermal nucleic acid amplification (Inst), Provisional Patent Application submitted LR No. 29527.2000 entitled: Use of IKKgamma mimics to treat cancer, submitted 11/16/2018 (Inst)
Scot C. Remick
Consulting or Advisory Role: Janssen Oncology
Travel, Accommodations, Expenses: Nanopharm
Research Funding: Lilly (Inst)
Susan E. Krown
Consulting or Advisory Role: Pfizer, ACI Clinical
Research Funding: Celgene (Inst), Gilead Sciences (Inst), Merck (Inst)
Patents, Royalties, Other Intellectual Property: Royalties from UpToDate for articles on classic Kaposi sarcoma
No other potential conflicts of interest were reported.
The authors thank Baxter Healthcare, Sigma Tau Pharmaceuticals/Lediant Biosciences, and Mylan Pharmaceuticals for their generous donations of drugs for this trial. The authors acknowledge the following pathologists who reviewed the biopsy specimens at the participating sites and contributed to the central pathology reviews: David Chumba, Yuri Fedoriw, Sam Kalungi, Teresa Lotodo, Rudo Makunike-Mutasa, Maurice Mulenga, Susan Nabadda Ndidde, Kirtika Patel, and Tamiwe Tomoka. We also gratefully acknowledge the contributions of the following individuals to the AMC-068 study: Carien Van Der Merwe, Jennifer Lynch, Edwards Kasonkanji, Takondwa Zuze, Job Kisuya, Gabriel Kigen, Evangeline Njiru, Margaret Borok, Ivy Gudza, Webster Kadzatsa, Immaculate Mbarusha, Annet Nakaganda, Clement Okello, and Yusuf Mulumba.
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Cancer management is shifting toward an era of precision oncology, with personalized cancer treatment as the ultimate goal. The ongoing development of targeted small molecules and immuno-oncology biopharmaceuticals largely drives this paradigm shift. Precision oncology relies on validated biomarkers and their companion diagnostics. The presence or absence of a biomarker determines whether a treatment strategy is appropriate. Biomarkers can classify patients according to their disease risk and prognosis.1
The study described real-world biomarker testing practices among medical oncologists in the Philippines in the management of breast, colorectal, and lung cancers, the top three malignancies in the country.
Medical oncologists in the Philippines would use biomarkers if these were clinically indicated and if cost were not a factor. Testing was driven most frequently by guideline recommendations. Patients’ limited finances and refusal to undergo testing, and the unavailability of biomarkers, were the most commonly cited barriers to testing.
Filipino medical oncologists treat patients in a resource-limited context where health expenditures are generally out-of-pocket and where biomarker tests are not readily accessible. Improved access to biomarker testing may be accomplished through programs that lower the cost of the tests, provide financial assistance, and increase the number of capable laboratories.
Personalized treatment strategies lead to improved clinical outcomes in many cancers. For instance, superior clinical outcomes were demonstrated for human epidermal growth factor receptor 2 (HER2)–directed therapy in HER2-positive metastatic breast cancer,2 epidermal growth factor receptor (EGFR)–directed therapy in metastatic colorectal cancer with wild-type RAS,3,4 and EGFR-directed therapy in non–small-cell lung cancer (NSCLC) with actionable EGFR driver mutations.5,6 As a result, many clinical practice guidelines now recommend biomarker-driven approaches. Table 1 lists the key biomarkers recommended by the National Comprehensive Cancer Network (NCCN), ASCO, and the European Society for Medical Oncology (ESMO) in breast, colorectal, and lung cancers.
Although precision oncology holds promise in improving clinical outcomes, there are many regions in the world where its use remains limited. In such places, the potential of biomarker-driven treatment strategies may be hindered by several factors, including the countries’ health policies and care delivery systems.20 For example, in the Philippines, a low- and middle-income country (LMIC) in Southeast Asia, patients often have to pay out-of-pocket for the tests. Laboratories are concentrated in highly urbanized cities, which limits access to testing for patients residing in remote areas. Because medical oncologists need to discuss the costs of biomarker tests and subsequent therapeutic options with their patients before treatment, the use of biomarkers as the lynchpin of treatment planning may prove difficult in the setting of LMICs. This is an important consideration in the effort to harmonize treatment guidelines on molecular diagnostics and patient-tailored treatment options between more progressive and developing regions of the world.21
The practice of medical oncology in the Philippines is governed by the Philippine Society of Medical Oncology (PSMO). In 2019, PSMO had 332 members (275 board-certified members and 57 fellows-in-training). The aim of this study was to describe the patterns of biomarker testing among medical oncologists in the Philippines for the management of breast, colorectal, and lung cancers, the country’s top three malignancies.22 In addition, we aimed to identify the driving factors and barriers to biomarker use in the country.
A total of 127 unique responses were collected. These comprised 38% of the 332 medical oncologists affiliated with PSMO. Eighty-two (65%) of respondents completed the printed questionnaire, and 45 (35%) answered the online form.
Sixty-three percent of respondents were staff consultants. Two thirds of the medical oncologists were affiliated with private hospitals or clinics, and 56.8% were in their first 3 years of practice. More than half of the medical oncologists practiced in Metro Manila (Table 2). Table 3 lists the average number of patients seen monthly by the respondents for each cancer type.
Biomarker Testing for Breast Cancer
If cost were not an issue, almost all respondents would order estrogen receptor (ER)/progesterone receptor (PR) and HER2 testing (Fig 1). Twenty-five percent would include protein encoded by the MKI67 gene (Ki-67). Other volunteered responses for testing were BRCA mutations (four respondents), Oncotype Dx (Genomic Health, Redwood City, CA; two respondents), and androgen receptor (one respondent). In genuine practice, ER/PR and HER2 testing were almost always used (Fig 2).
Biomarker Testing for Colorectal Cancer
Approximately half of the respondents saw three to 10 patients with colorectal cancer monthly (Table 2). If cost were not an issue and if the tests were clinically indicated, almost all respondents would test for KRAS mutation. Only 63.78% would test for BRAF mutations (Fig 3). In genuine practice, < 50% of respondents routinely requested KRAS/NRAS, BRAF, and microsatellite instability (MSI)/mismatch repair (MMR) tests (Fig 4). Sixty percent of the respondents never tested for BRAF mutations.
Biomarker Testing for Lung Cancer
Almost all respondents would request EGFR mutation testing if cost were not an issue and if clinically indicated. PD-L1 and anaplastic lymphoma kinase (ALK) were also common responses (Fig 5), and 54.33% of respondents would test for T790M mutation. In genuine clinical practice, 67.72% of the respondents always ordered EGFR testing (Fig 6).
Driving Factors for and Barriers to Biomarker Testing
The most frequent reason cited by respondents for why they would pursue biomarker testing was that the tests are recommended by clinical practice guidelines (Table 4). The guidelines used by the respondents were NCCN (32.28%), ASCO (4.72%), ESMO (1.57%), and all three of these (61.47%). Other factors that drove them to use biomarkers were their patients’ advanced or metastatic stage (76.38%) and their patients’ inclusion in clinical trials that made use of such biomarkers (49.61%; Table 4).
The respondents reported several barriers that hindered them from pursuing biomarker testing for their patients (Table 4). They would not pursue testing if their patients reported financial difficulties (94.49%), if their patients stated that they did not wish to be tested (60%), if the tests were not available in their areas of practice (58.27%), and if there was insufficient tissue trial for the tests to be reliably performed (47.24%).
Factors Associated With Biomarker Use
The respondents’ use of biomarkers was not significantly associated with their institutional affiliation (Appendix Table A1), their patients’ financial difficulties (Appendix Table A2), the availability of biomarkers in their areas of practice (Appendix Table A3), and the number of patients they saw monthly (Appendix Table A4). However, there were several exceptions. Respondents affiliated with academic institutions tested for EGFR T790M for lung cancer (P = .02) and NRAS (P = .01) for colorectal cancer more frequently than respondents who were not affiliated with academia (Appendix Table A5). There was a nonsignificant trend for an association between the use of EGFR for lung cancer among respondents affiliated with private hospitals compared with those affiliated with government-run hospitals (P = .08).
A significant association between the respondents’ use of biomarkers and the number of patients seen monthly was observed only in ROS1 for lung cancer (P = .04). It seemed that respondents who saw more patients with lung cancer monthly ordered EGFR (P = .08), PD-L1 (P = .11), and EGFR T790M (P = .08) tests, although the associations were not significant. Regardless of the number of patients seen, the medical oncologists tended to prescribe NTRK testing for patients with lung cancer less frequently (P = .07). The association between biomarker use and its availability in the area of practice was only significant for KRAS/NRAS in colorectal cancer (P < .01).
To our knowledge, this study is the first to describe real-world practices of medical oncologists in the Philippines with regard to precision medicine in cancer management. In genuine practice, patterns of biomarker use seemed heterogenous. Testing was driven most frequently by guideline recommendations. Patients’ limited finances and refusal to undergo testing, as well as the unavailability of biomarkers in oncologists’ areas of practice, were the most common barriers that hindered the respondents from pursuing the recommended tests.
This study was important to carry out for three reasons:
Filipino medical oncologists treat patients in a setting where health expenditures are generally out-of-pocket.
Filipino patients may opt to defer treatment to spare their families from economic and emotional hardships.23
Some medical oncologists practice in areas where biomarker tests may not be readily available. In this study, particular focus was given to breast, colorectal, and lung cancers because these were the most common malignancies in the Philippines.22
In breast cancer, we showed that the respondents used ER/PR and HER2 testing routinely. A quarter of respondents would test for Ki-67, despite the controversy about its value because of a lack of standardized assessments.24 It seemed that the respondents did not rely exclusively on guideline recommendations.
In colorectal cancer, the respondents would use KRAS, NRAS, BRAF, and MSI/MMR status testing if these were indicated and if cost were not an issue (Table 4). Approximately 40% of respondents, however, answered that they would not order BRAF testing despite guideline recommendations for its use in metastatic disease. In genuine clinical practice, < 30% of respondents requested all four tests routinely. A prominent finding was that 59.84% of respondents had never used BRAF. It seemed that on top of cost, other issues serve as barriers to biomarker use.
In lung cancer, almost all respondents (97.64%) would test for EGFR mutations. In genuine practice, however, only 67.72% tested for EGFR routinely. Of note, 55.2% and 44.8% of respondents had never used BRAF and ROS1, respectively, in real-world practice.
Guideline recommendation was the most frequent motivation for biomarker testing. This mirrored the results of a similar survey of oncologists from other countries.25 In the absence of local guidelines, medical oncologists in the Philippines refer to guidelines developed by NCCN, ASCO, and ESMO. Updated regularly, these reflect the standards of care in developed regions with ready access to cutting-edge molecular tests and targeted treatments that may not be available in the Philippines. Recently, regional guidelines have emerged to adapt western guidelines, taking into account ethnic differences associated with the treatment of metastatic NSCLC cancer in Asian patients. PSMO was not part of the consensus panel for these guidelines. Even these Pan-Asian guidelines might not be directly applicable in the Philippine setting.26
For the three cancers, evidence shows that biomarkers can guide treatment planning for the first and subsequent lines. Related to this, our results showed that medical oncologists used biomarker testing to explore alternative treatment options.
Of note, almost half reported using biomarker tests because their patients were included in clinical trials (Table 4). Testing was likely required before enrollment. Oncologists who practiced in academic medical centers would have more exposure to clinical trials. We showed a significant association between the use of EGFR T790M and NRAS with affiliation to academia.
Almost all the respondents indicated that they would not pursue biomarker testing if their patients reported financial difficulties (Table 4). Biomarker tests are expensive (Table 1). Given that the average monthly income of Filipino households is 26,000 Philippine pesos (US $500),27 the cost of cancer diagnosis and treatment would be prohibitive for many. According to one study, 40.6% of Filipinos with cancer will experience financial catastrophe that arises from their illness.23 The costs of cancer care consist of expenditures for medications and diagnostics, including biomarkers. This issue is not limited to LMICs.25
Sixty percent of the respondents would not pursue testing if their patients refused to be tested. Patients might not comprehend the benefits of testing,25 they might want to proceed with best supportive care instead, or they might be daunted by the cost of treatment.
Approximately 60% of respondents reported that the unavailability of tests in their areas of practice hindered testing (Table 4), similar to the findings of a multinational study.25 As of 2019, the tests for BRCA mutation, Oncotype Dx, KRAS, NRAS, BRAF, MSI, EGFR, ALK, BRAF, PD-L1, T790M, and ROS1 were only available in six centers in Metro Manila (Fig 7).
Insufficient tissue trial was another barrier. This reason should merit clarification from respondents because in at least some instances, it would seem remediable. Certainly, the quantity and quality of the tumor material is a limiting factor for adequate biomarker analysis.24
We determined the presence of an association between the physician’s use of biomarkers and select conditions. In general, we noted no statistically significant associations, likely because of our study’s trial size. Nevertheless, there were several key exceptions for which the association was significant—EGFR T790M and NRAS with academic center affiliation, ROS1 with more patients with lung cancer seen monthly, and KRAS/NRAS with its availability in the area of practice. Several points might explain these findings: (1) physicians from academic and private institutions would have greater access to the biomarker tests, (2) physicians from private hospitals would have more contact with patients who could afford treatment, and (3) physicians who saw more patients monthly would have more opportunities to pursue testing.
Our study had several limitations. First, there was a risk of social desirability bias; respondents might have felt pressured to supply more acceptable answers. While the effect of this bias could not be eliminated completely, maintaining respondent anonymity would mitigate it.28 In this study, we used anonymized questionnaires. Online submissions could not be traced back to the sender, and paper submissions were through a third party (PSMO secretariat). Another concern was nonresponse bias possibly as a result of indifference or busyness. Furthermore, studies have reported that physician response rates to surveys tend to be low.29,30 Regardless of the reasons, interventions that could Improve response rates include personalizing cover letters, incentivizing survey response, and implementing a thorough follow-up system for nonresponders.29-32 In our study, we aggressively pursued an advertising campaign through e-mail sent to the entire PSMO and supplemented by frequent announcements during plenary sessions. In addition, we made electronic and paper formats of the survey available to make participation more convenient. Despite these interventions, the response rate was only 38%, and respondents tended to be younger members of the society. Second, although we attempted to include all medical oncologists, our study had a response rate of < 40%, which is comparable to other similarly conducted studies.9.30,33,34 A strength of the study is the participation of medical oncologists from various institutions, including oncology trainees and attending physicians (Table 2). Because all medical oncologists affiliated with PSMO were invited, the probability of a differential response bias could have been lessened. Nevertheless, there was a higher response rate among respondents who were from Metro Manila and were in private practice. On the basis of the PSMO membership data, 43% of consultants practice in Metro Manila. The concentration of medical oncologists affiliated with private hospitals/clinics in urbanized areas was reflected in the distribution of respondents of this study. Third, we did not perform qualitative analysis (interviews or focus group discussions) to probe the underlying reasons. The study relied solely on a printed instrument to elicit responses. Nevertheless, the questionnaire provided the respondents an opportunity to volunteer other reasons if they saw fit to do so. Fourth, by leaving some questions open to interpretation due to the vagueness of the statement (ie, “as clinically indicated”), the survey might have assumed that the respondents were fully aware of the indications for each of the tests. Fifth, the survey did not attempt to measure the baseline knowledge of the respondents with respect to biomarker testing guidelines. This would have allowed better contextualization of the study’s results. Finally, the driving factors and barriers to testing were not analyzed separately for each cancer type; the responses could certainly vary depending on the cancer. In the end, the study described the general factors affecting physicians’ biomarker use in the Philippines.
In summary, medical oncologists in the Philippines would use biomarkers in the management of breast, colorectal, and lung cancers if these were clinically indicated and if cost were not an issue. Almost all the respondents indicated that they would not pursue testing if their patients reported financial difficulties.
Given our findings, we have the following recommendations. First, additional patient access programs may need to be developed and existing ones strengthened. These programs may involve lowering the costs of the tests through government regulations, increasing the number of certified and capable laboratories throughout the Philippines, and giving patients financial subsidies. Second, patient-centered education on the value of the tests in cancer treatment may need to be implemented in the clinics. Third, medical societies may provide avenues for continuing medical education on precision medicine. Finally, hospitals ought to engage in clinical trials whenever possible because these may allow free access to molecular diagnostics.
Lumineers are a special type of ultra-thin veneers by Cerinate. Just like traditional veneers, Lumineers can reshape your smile and supply you that perfect smile makeover. They can cover gaps between teeth and enhance the appearance of worn-down and discoloured teeth.
Photos showing how lumineers can transform a smile in this smile makeover case study
The main difference is that Lumineers are made from a special patented cerinate porcelain that is very strong but much thinner than traditional laboratory-fabricated veneers. Their thickness is comparable to contact lenses, and so they are often called contact lenses for your teeth. The main advantage of these ultra-thin veneers is that minimal tooth preparation is required. In other words, very little - if any - of your natural tooth structure needs to be removed through shaving or grinding prior to bonding the Lumineers over your natural teeth. As a result, the procedure is often reversible, since your natural tooth structure is left intact, unlike traditional veneers, where a significant amount of your tooth structure may need to be removed. Click here read more about traditional veneers and the procedure involved.
Lumineers are so versatile that they can be placed over existing crown and bridge work, without the need to replace them. They are the perfect solution for stained, chipped, discoloured or slightly misaligned teeth.
Photos showing how Lumineers have changed crooked teeth with gaps to a straight white smile for this gentleman.
Not all cosmetic dentists offer Lumineer veneers, as they need to be registered with the company that manufactures them. They can only be made from patented Cerinate porcelain, which is not available anywhere other than in the Cerinate Smile Design Studio in the States. In as little as two appointments with your Lumineers dentist, you can have a beautifully designed smile that is clinically proven to last over 20 years.
More Lumineers smiles:
The above case study shows slightly crooked and stained teeth treated with Lumineers to supply a much brighter and symmetrical smile.
The patient above has some large gaps between his front upper teeth and these have been closed with Lumineers, giving a more uniform smile.
The photos above show that Lumineers can be used to treat badly stained teeth that cannot be removed my simple cleaning and Improve the shape of a smile
Lumineers tend to be more expensive than traditional veneers as they are manufactured by one one laboratory that is specialised in producing these veneers. This cost can also vary depending on the dentist that fits them and thier level of expertise in this area. Expect to pay between £500 and £800 per Lumineer veneer.
Sleep is essential for good health. It can directly impact your mood, productivity, stress level, overall well-being, and your ability to think clearly. The Optum Sleep Center addresses health problems that make a good night’s sleep elusive to many people.
At the Center, individuals’ specific needs are identified during a sleep study, and treatment is provided to Improve their ability to rest and enhance their quality of life. “Sleep disorders are very common and could cause a significant burden to someone's health and quality of life. Fortunately, there are very effective treatments available,” said Dr. Hazem Ubaissi, who is the sleep specialist at the Optum Sleep Center. “Sleep apnea is a very common condition that sometimes runs in families. One’s age, weight and facial features need to be taken into consideration, as well as medical problems such as high blood pressure or irregular heart rhythm. It should also be noted that the altitude in Colorado affects oxygen levels during sleep, with some people experiencing significant drop in the oxygen level."
What keeps people from sleeping well?
Poor sleep hygiene, sleep disorders like obstructive sleep apnea, insomnia, restless leg syndrome and other general medical issues like pain and depression are among many causes of disturbed sleep. “People often seek help for sleep disorders when they are struggling with daytime sleepiness, fatigue, lack of energy, morning headaches, difficulty falling asleep or staying asleep, snoring or gasping for air while sleeping," said Dr. Ubaissi. “They may also seek our services when behaviors or symptoms are noted by a significant other or a physician – primary care, ENT, cardiologist, or psychiatrist among the most likely referrals. Most of the time a sleep study will be needed to further evaluate the cause of the patient's symptoms."
There are two options for those undergoing a sleep study: in-home testing or on-site testing. Each has its own benefit but neither require much preparation. For in-home sleep studies, the Optum Sleep Center provides training on how to use the diagnostic tool. Additionally, in-home sleep study participants have access to in-lab technicians via telephone in case questions arise. Participant wait time is approximately three weeks and our goal is to reduce wait time to less than two weeks.
Sleep Study participants at the Optum Sleep Center rest comfortably at a newly renovated six-bed facility. Six sleep rooms welcome up to 42 studies each week. The expanded space has minimized the wait time to between four and six weeks. Private rooms feature comfortable beds with new mattresses and box springs, a dresser, television, sink, fan, clock radio, artwork, and access to restrooms, a private shower and laundry facilities. The sleep room for bariatric patients includes a hospital bed, an en suite bathroom, and a view of Pikes Peak. There are recliners or pullout beds to accommodate caregivers who may need to stay with patients. Snacks and beverages are also available.
Once participants are settled in bed, technicians measure the quality and quantity of sleep. Brainwaves, muscle tension, heart rate and rhythm, breathing and nocturnal oxygen levels are measured via sensors on the skin.
Both courses of action require pre-approval from the patient's insurer so there are no billing surprises. Most sleep studies take place over the course of one night. Participants do not have to alter their medication schedule, though it is recommended that they do not nap or consume alcohol prior to monitoring.
Results are available within a few days of the study, and include an outline of test scoring, diagnosis, and a treatment plan. Sleep study participants will understand their symptoms and treatment options, which often involve breathing devices such as a CPAP machine. “The right size and shape of a mask can make a major difference to patients,” said Dr. Ubaissi. “We have multiple masks available for a proper fit.” Dr. Ubaissi and the experienced team members at the Optum Sleep Center provide "a personal touch,” taking time to communicate with patients. They work with durable medical equipment companies, handling the ordering of insurance-approved devices best suited to each person’s study outcome.
Hazem Ubaissi, M.D., has been a member of the Optum team since May 2020. He develops a personal relationship with his patients and their families in Colorado Springs and strives to provide the best standard of care to those with sleep disorders. He has been featured on KRDO Radio’s “Ask the Doctor” series, speaking on many aspects of sleep. He is board certified in pulmonary, critical care and sleep medicine. A graduate of the Medical School of Aleppo University, Dr. Ubaissi completed his training in internal medicine, pulmonary, critical care, and sleep medicine at George Washington University, where he was voted Fellow of the Year in the department of medicine for two consecutive years.
Outside the office, Dr. Ubaissi enjoys spending time with his family, running, cycling, swimming, and exploring Colorado Springs. “I love Colorado and Colorado Springs,” he said. “There is a community feeling here that I had been seeking; a small-town feel where I am happy to be able to raise my family.”