Tag Archives: academia

Academia, Health Care

Challenges Developing Measurement Tools

Common sense would dictate that a person should want to purchase quality when choosing any product or service, and as health care costs soar in the United States, we also want to ensure that we, as consumers of health care and taxpayers who subsidize health care, are reaping maximum quality for that cost (Buck, Godfrey, & Morgan, 1996). According to McGlynn (1997), the costs for health care in the U.S. have been rising dramatically causing disruption in the manner of which professionals provide care and patients seek it out. It is important to realize the impact that these increasing costs and other changes have on the delivery of care, and, as McGlynn points out, assessment of quality measures are the means of evaluation. Unfortunately, McGlynn and others at the time have found quality measures to be lacking the requisite data needed to make an accurate evaluation of the delivery of health care (Brook, McGlynn, & Shekelle, 2000; Grimshaw & Russell, 1993; McGlynn, 1997).

Over the past decade, many efforts have been made to develop quality measures in order to direct quality improvement; however, these efforts, though effective, have been disjointed and ad hoc at best. McGlynn and Asch (1998) cautions that careful attention to methodology is essential when developing these measures. Accurate methodologies can be reproduced and used to effectively compare efforts between institutions. This leads to a best practices continuum of health care provision.

Recently, researchers have studied teamwork behaviors and their influence on patient and staff-related outcomes, but many of the discussions were institution-centric and may not have applied in the macro environment of U.S. health care. Reader, Flin, Mearns, and Cuthbertson (2009) recently attempted to organize these studies and develop a portable and robust framework which would lead to the development of effective team performance and provide means of further testing and improvement of team dynamics. Their findings suggest that effective teamwork is crucial to providing patient care in critical settings. Reader et al. shows one of the shortcomings of recent quality measure development but also illustrates a manner in which to overcome the limitations.

Developing methods for measuring and evaluating performance in health care have been challenging, overall. Campbell, Braspenning, Hutchinson, and Marshall (2002) identify three component issues to addressing these challenges: “(1) which stakeholder perspective(s) are the indicators intended to reflect; (2) what aspects of health care are being measured; and (3) what evidence is available?” (p. 358). This addresses the qualitative concerns of capturing indicators, while efforts like those of Steyerberg et al. (2010) concern themselves with quantitative abstraction and portability, as well as predictive value. Steyerberg et al. promotes the use of reclassification, discrimination, and calibration when using statistical models to develop valid prediction models and novel performance measures.

Performance indicators that are an accurate reflection of health care provision can lead to development of best practices, lower overall health care costs, and improve the delivery of care which will decrease mortality and morbidity. When considering these performance indicators, especially during development, researchers and administrators need to ensure the validity of the measurements. Approaches to developing quality improvement measures are constantly evolving, and new and novel methods are being designed to standardize the instruments, the application, and the reporting. Quality improvement is still, however, a challenge to many health care providers.

References

Brook, R. H., McGlynn, E. A., & Shekelle, P. G. (2000). Defining and measuring quality of care: a perspective from US researchers. International Journal of Quality in Health Care, 12(4), 281–95. doi:10.1093/intqhc/12.4.281

Buck, D., Godfrey, C., & Morgan, A. (1996). Performance indicators and health promotion targets (Discussion paper No. 150). York, UK: Centre for Health Economics, University of York. Retrieved from http://www.york.ac.uk/che/pdf/DP150.pdf

Campbell, S. M., Braspenning, J., Hutchinson, A., & Marshall, M. (2002). Research methods used in developing and applying quality indicators in primary care. Quality and Safety in Health Care, 11(4), 358–364. doi:10.1136/qhc.11.4.358

Grimshaw, J. M. & Russell, I. T. (1993). Effect of clinical guidelines on medical practice: A systematic review of rigorous evaluations. Lancet, 342(8883), 1317-1322. doi:10.1016/0140-6736(93)92244-N

McGlynn, E. A. (1997). Six challenges in measuring the quality of health care.Health Affairs, 16(3), 7-21. doi:10.1377/hlthaff.16.3.7

McGlynn, E. A. & Asch, S. M. (1998). Developing a clinical performance measure. American Journal of Preventive Medicine, 14(3), Supp. 1, 14–21. doi:10.1016/S0749-3797(97)00032-9

Reader, T. W., Flin, R., Mearns, K., & Cuthbertson, B. H. (2009). Developing a team performance framework for the intensive care unit. Critical Care Medicine, 37(5), 1787-1793. doi:10.1097/CCM.0b013e31819f0451

Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., … Kattane, M. W. (2010). Assessing the performance of prediction models: A framework for traditional and novel measures. Epidemiology, 21(1), 128–138. doi:10.1097/EDE.0b013e3181c30fb2

Academia, Clinical, Culture, Emergency Medical Services, Health Care, Society

Quality and Safety Measurement

In regards to the incident surrounding the death of Josie King (Josie King Foundation, 2002), there have been many great improvements in the delivery of care at Johns Hopkins (Niedowski, 2003; Zimmerman, 2004). Those aside, and if I was faced with having to develop performance measures of quality and safety in the context of such a tragedy, I would strive to ensure that my measures were accurate and valid to identify areas of grave concern where Johns Hopkins would do good to improve.

First, I would consider measuring the structure of the care delivered. In Josie’s case, a medical response team responded when it was identified that she was in the midst of a medical crisis. The first measurement would serve to identify the availability of such teams and the adequacy of the team’s staffing. The measure would indicate the response time of the team and the licensing and certification level of each team member.

Second, I would consider measuring processes that might have contributed to the death of Josie King. In this instance, Josie was administered a narcotic while suffering acute dehydration. The administration of this medication was contrary to the physician’s orders regarding pain medication for this patient. This measure would indicate the appropriate use of narcotic analgesia in patients faced with contraindications, such as acute dehydration or shock. This measure would be a cross tabulation of recent vital signs and laboratory results.

Third, I would consider measuring outcomes. In cases where pediatric patients are downgraded from the pediatric intensive care unit (PICU) to a general ward, any adverse condition should prompt an upgrade back to the PICU. This measure would identify the number of cases in each reporting period that any recently downgraded patient was upgraded back to the PICU. This measure should account for the time between a crisis and upgrade along with a statement indicating the cause of the crisis and resultant upgrade. This measure should be augmented by a mortality and morbidity subset involving any patients who were downgraded from PICU.

My considerations for these processes are to determine if general ward nurses should be administering any medications on standing order or if there should be a requirement to ensure that any medication administered to a general ward patient is explicitly written in the patient’s chart at the time of administration. Also, nurses should be acutely aware of the contraindications of any medications that they are administering. The process measure will, hopefully, identify misuse of narcotic analgesia and any failure to assess the patient for other possible causes of distress before assuming the distress is in response to pain. Ultimately, a more timely and efficient use of medical response teams should result, which would avail physicians and more experienced nurses to the original patient care team. This should lead to an open discussion of how to better manage the patient post crisis. Also, a greater understanding of medication administration concepts should result, benefiting all patients.

References

Josie King Foundation. (2002). About: What happened. Retrieved from http://www.josieking.org/page.cfm?pageID=10

Niedowski, E. (2003, December 15). From tragedy, a quest for safer care; Cause: After medical mistakes led to her little girl’s death, Sorrel King joined with Johns Hopkins in a campaign to spare other families such anguish. The Sun, pp. 1A. Retrieved from http://teacherweb.com/NY/StBarnabas/Quality/JohnsHopkinsErrors.pdf

Zimmerman, R. (2004, May 18). Doctors’ new tool to fight lawsuits: Saying ‘I’m sorry’. Wall Street Journal, pp. A1. Retrieved from http://www.theoma.org/files/wsj%20-%20medical%20error%20-%2005-18-2004.pdf

Academia, Culture, Health Care, Society

The Patient Perspective: Patient Safety

The Speak Up materials provided by The Joint Commission (2011a, 2011b) do a great service in succinctly illustrating the need to be educated about health care issues. Patients and their families have a unique perspective to understanding their (or, their family member’s) health (Vincent & Coulter, 2002). Although physicians, nurses, and allied health providers are responsible for providing quality care, it remains the domain of the patient to express uncertainty or provide additional information to guide the provider. Ultimately, the patient or surrogate decision-maker must provide consent for treatment and must do so with full understanding. There are times, however, that the scope of treatment is so drastic, emergent, or specialized that the patient may not have the facilities to gain a full understanding of care needing to be rendered (Vincent & Coulter, 2002). This is the exception.

In the case of Josie King (Josie King Foundation, 2002; Niedowski, 2003; Zimmerman, 2004), which I elaborated on last week, Sorrel King, Josie’s mother, was educated about her daughter’s condition and spoke up as The Joint Commission recommends. Unfortunately, this case turned into tragedy not because Sorrel King did wrong but because the nurse disregarded her apprehension. This was tantamount to malpractice and no patient or family member could have prevented this, save for using force to physically prevent the administration of medicine. According to MacDonald (2009), there are nurses that believe “[patients] have no say and that medications are the domain of doctors, leaving the nurse and the patient to trust that the doctors would do the right thing” (p. 29).

Perhaps things were slightly different, however. As MacDonald (2009) explains, patient’s who are knowledgeable of their illness and take an active role in their health care decisions add another layer of safety, especially when considering medication action, reaction, and interaction. Medication prescription errors are numerous within health care, and as in the case of Josie King, improved communication between the physicians, nurses, and Sorrel King might have prevented Josie from being administered the narcotic and instead receiving the fluid she so desparately needed (Vincent & Coulter, 2002).

Health care should be patient-centric as it remains the responsibility of the patient to be educated about the care they receive and to provide consent for that care and treatment to be rendered. An uneducated patient does add risk, but sometimes this is unavoidable. It is in these instances that special care should be taken until a full medical history can be attained.

References

The Joint Commission. (2011a, March 7). Speak up: Prevent errors in your care [Video podcast]. Retrieved from http://www.jointcommission.org/multimedia/speak-up-prevent-errors-in-your-care-/

The Joint Commission. (2011b, April 5). Speak up: Prevent the spread of infection [Video podcast]. Retrieved from http://www.jointcommission.org/multimedia/speak-up–prevent-the-spread-of-infection/

Josie King Foundation. (2002). About: What happened. Retrieved from http://www.josieking.org/page.cfm?pageID=10

Macdonald, M. (2009). Pilot study: The role of the hospitalized patient in medication administration safety. Patient Safety & Quality Healthcare, 6(3), 28-31. Retrieved from http://www.psqh.com/

Niedowski, E. (2003, December 15). From tragedy, a quest for safer care; Cause: After medical mistakes led to her little girl’s death, Sorrel King joined with Johns Hopkins in a campaign to spare other families such anguish. The Sun, pp. 1A. Retrieved from http://teacherweb.com/NY/StBarnabas/Quality/JohnsHopkinsErrors.pdf

Vincent, C. A. & Coulter, A. (2002). Patient safety: what about the patient? Quality & Safety in Health Care, 11(1), 76–80. doi:10.1136/qhc.11.1.76

Zimmerman, R. (2004, May 18). Doctors’ new tool to fight lawsuits: Saying ‘I’m sorry’. Wall Street Journal, pp. A1. Retrieved from http://www.theoma.org/files/wsj%20-%20medical%20error%20-%2005-18-2004.pdf

Academia, Health Care, Public Health

Comparing Hospital Care in My Area

Living in northeastern Connecticut, I find myself equidistant from two area hospitals. As a health care provider and consumer, I feel that it is important to choose the professionals who will provide my care based on fact. Websites created by the Joint Commission (2011) and the U.S. Department of Health and Human Services (HHS; 2011) prove to be a helpful repository of information regarding the safety and quality of care delivered by hospitals and practitioners across the country.

Using these two websites, I will compare the three closest hospitals to my zip code: 1) Day Kimball Hospital (10.3 mi), 2) Harrington Memorial Hospital (10.0 mi), and 3) Windham Community Memorial Hospital (21.7 mi). The mean distance from my home to these hospitals is 15.85 mi. with all three being acceptable by me in distance and time in the case of an emergency. Day Kimball Hospital (DKH; 2011) is a 104-bed acute care facility located in Putnam, Connecticut. Harrington Memorial Hospital (HMH; 2009) is a 114-bed acute care facility located in Southbridge, Massachusetts. Windham Community Memorial Hospital (WCMH; n.d.) is a 130-bed acute care facility located in Windham, Connecticut.

General process of care measures account for best practices in medicine and health care. The Surgical Care Improvement Project has set goals preventing untoward cardiac effects during certain surgical procedures along with infection control measures. According to Health Compare (HHS, 2011), cumulative scores for each hospital based on general process of care measures in the Surgical Care Improvement Project are as follows: DKH=0.954, HMH=0.901, WCMH=0.935. Another general process measure aimed at providing the standard of care of heart attack victims is the Heart Attack or Chest Pain Process of Care. The cumulative scores for these reported measures are: DKH=0.967, HMH=0.973, WCMH=0.956. Another cardiac related measure is the heart failure process of care measure. The cumulative results are: DKH=0.950, HMH=0.873, WCMH=0.893. Pneumonia process of care measures are important to gauge the appropriateness of treatments provided to stave off further development of respiratory failure and sepsis, two highly conditions with increase mortality. The cumulative scores for the pneumonia process of care measures are: DKH=0.932, HMH=0.860, WCMH=0.955. The last general process of care measure reflects the adherence to best practices in treating and managing children’s asthma; however, none of the three hospitals provided data for any of the process measures of this category.

Along with process of care measures, outcome of care measures are also important as they reflect the ability of each hospital to manage the risks of mortality and morbidity in caring for their patients. Outcome measures are based on both death and readmission of heart attack, heart failure, and pneumonia patients. For all three hospitals, DKH, HMH, and WCMH, the cumulative results for outcome of care measures were not statistically different from than the national rates in all categories. Health Compare (HHS, 2011) reports these measures as such.

One final measure that I find important in choosing a hospital is the patient satisfaction scores. Cumulative scores of the Survey of Patients’ Hospital Experience allow us to compare the three hospitals: DKH=0.695, HMH=0.701, WCMH=0.677.

In ranking each of the three hospitals, I used an average of the cumulative scores for each hospital’s measure discussed above. The final score, according to the averages of the Hospital Compare (HHS, 2011) scores, is: DKH=0.900, HMH=0.862, WCMH=0.883; therefore, my first choice of hospitals, according to the data presented in Hospital Compare is DKH with WCMH being second and HMH third. According to this data, though, each of the three hospitals appears to be equitable with the others striving in some measures and faltering in others. This is also evidenced by Quality Check (The Joint Commission, 2011), which shows a graphic representation of the same overall data, National Quality Improvement Goals and the Surgical Care Improvement Project, used by HHS (2011). Quality Check (The Joint Commission, 2011) compares quality data with the target ranges of other hospitals.

According to Quality Check (The Joint Commission, 2011), DKH met all the target goals while exceeding the goals set for infection prevention. HMH failed to meet the pneumonia care goal, but met all other goals. HMH did not exceed any of the goals. WCMH failed to meet the heart failure care goal, but met all other goals. WCMH did not exceed any of the goals.

In considering the data from Hospital Compare (HHS, 2011) and Quality Check (The Joint Commission, 2011), it is clear that this data can be used by consumers to make more informed decisions regarding their health care. Though the methods in this paper might be questionable and simple, consumers may disregard some measures while favoring others, depending on their perception of what measures are important in judging the provision of the care that they might receive. Additionally, the data used for the comparisons, many times, accounted for a small patient population; however, each hospital serves comparable communities with comparable levels of service. This may be a consideration when performing scientific statistical analyses, but that would be beyond the scope of this paper.

The provision of health care must be ethical, just, and equitable. Allowing consumers access to data regarding the performance of hospitals in their area can provide additional insight to patients when choosing their health care provider.

References

Day Kimball Hospital. (2011). Sevices and locations: Day Kimball Hospital. Retrieved from http://www.daykimball.org/services-and-locations/day-kimball-hospital/

Harrington Memorial Hospital. (2009). About us: Harrington at a glance. Retrieved from http://www.harringtonhospital.org/about_us/harrington_at_a_glance

The Joint Commission. (2011). Quality check. Retrieved from http://www.qualitycheck.org/ consumer/searchQCR.aspx

U.S. Department of Health and Human Services. (2011). Hospital compare. Retrieved from http://www.hospitalcompare.hhs.gov/

Windham Community Memorial Hospital. (n.d.). CEO’s message. Retrieved from http://www.windhamhospital.org/wh.nsf/View/CEOsMessage

Academia, Clinical, Emergency Management, Emergency Medical Services, Health Care, Public Health, Society

Medical Error: The Josie King Story

Josie King’s story (Josie King Foundation, 2002; Niedowski, 2003; Zimmerman, 2004) is heartbreaking, but the events told herein empowered Sorrel King, Josie’s mother, to take on a mission responsible for numerous patient care recommendations that have enhanced the safety of pediatric patients throughout the country. Josie King was only 18 months old when she climbed into a hot bath and suffered 1st and 2nd degree burns which led to her being admitted to Johns Hopkins pediatric intensive care unit (PICU). Within 10 days, Josie was released from the PICU and brought to the intermediate floor with all assurances that she was making a remarkable recovery and would be released home in a few days. Josie did not continue her remarkable recovery, however.

According to Sorrel King (Josie King Foundation, 2002), Josie began acting strangely, exhibiting extreme thirst and lethargy, after her central intravenous line had been removed. After much demanding by Sorrel, a medication was administered to Josie to counteract the narcotic analgesia she had been administered. Josie was also allowed to drink, which she did fervently. Josie, again, began recovering quickly. Unfortunately, the next day, a nurse administered methadone, a narcotic, to Josie as Sorrel told her that Josie was not supposed to have any narcotics… that the order had been removed. Josie became limp and the medical team had to rush to her aid. Josie was moved back up to the PICU and placed on life support, but it was fruitless. Josie died two days later and was taken off life support.

The Institute of Medicine (2001) published six dimensions of health care: safety, effectiveness, patient-centered, timeliness, efficiency, and equality. In Josie’s case, the care was not delivered efficiently, effectively, safely, or in a patient- or family-centered fashion. The overuse of narcotics in Josie’s case was certainly not effective or safe. Additionally, withholding fluids and allowing her to become dehydrated was detrimental to her recovery, which was neither safe nor effective. As Josie exhibited extreme thirst, her symptoms were dismissed, which does not follow patient-centeredness. Moreso, when the nurse administered the narcotic to Josie despite the pleadings of her mother, it demonstrated a lack of family-centered care, safety (in that, the order should have been double checked), efficacy (further demonstrating overuse of narcotic analgesia), and efficiency, as medication orders were either unclearly written or removed.

This story is clearly a demonstration that mistakes can happen at even the best of hospitals.

References

Institute of Medicine. (2001, July). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press.

Josie King Foundation. (2002). About: What happened. Retrieved from http://www.josieking.org/page.cfm?pageID=10

Niedowski, E. (2003, December 15). From tragedy, a quest for safer care; Cause: After medical mistakes led to her little girl’s death, Sorrel King joined with Johns Hopkins in a campaign to spare other families such anguish. The Sun, pp. 1A. Retrieved from http://teacherweb.com/NY/StBarnabas/Quality/JohnsHopkinsErrors.pdf

Zimmerman, R. (2004, May 18). Doctors’ New Tool To Fight Lawsuits: Saying ‘I’m Sorry’. Wall Street Journal, pp. A1. Retrieved from http://www.theoma.org/files/wsj%20-%20medical%20error%20-%2005-18-2004.pdf

Academia, Emergency Management, Health Care, Public Health, Society

Public Health Risks in the 21st Century

Within the next 30 years, I foresee a significant public health risk of viral pandemic, a concern outlined in the recently published CISIS commission report (Fallon & Gayle, 2010). According to many, the next significant pandemic to be a global threat will occur anytime between now and 70 years (Gostin, 2004; Monto, Comanor, Shay, & Thompson, 2006; Ravilious, 2005; Smil, 2008; Tapper, 2006; Taubenberger, Morens, & Fauci, 2007). Although many scientists have their focus on influenza as the most probable for pandemic exposure, other novel virii, such as SARS, HIV, et al., have the facets to make them just as potentially significant (Gostin, 2004; Smil, 2008; Tapper, 2006). Regardless of the particular pathogen, history has shown pandemics to create and environment of negative net effects to humanity. According to Billings (1997) and Ravilious (2005), the Spanish influenza pandemic of 1918, caused by a mutated avian flu strain, claimed between 20-million and 40-million lives in a single year (Monto et al., 2006; Taubenberger et al., 2007). Spreading quickly along major international trade routes, the Spanish flu infected many servicemen returning from duty at the end of World War I. As these infected servicemen returned and celebrated the armistice in crowds of people, a severe strain on the public health system in the United States was unknowingly developing. Considering the hypervirilence and increased mortality (2.5%, compared to the typical 0.1%) caused by the 1918 Spaish flu, the world’s economy was in turmoil (Billings, 1997). As most of the American workforce was recently embroiled in overseas combat duty, upon their return they must now face the possibility of infection, an inability to work, and possible death.

Monto et al. (2006) outline a useful model of surveillance techniques that would not only be useful in detecting and improving response to influenza outbreaks, but it would certainly help to detect any new significant diseases that could be a public health risk and threaten a population or society. Additionally, Taubenberger et al. (2007) focuses on learning the biology of the influenza virus to predict the possibility of outbreak and, thus, pandemic potential. Coupling these two approaches makes sense to both identify potential pathogens and use surveillance techniques to track and direct responses to mitigate actual outbreaks as they occur. These efforts, however, should be directed by an organization that values independant operation, impartiality, neutrality, and universality, just a few of the principles of the Red Cross and Red Crescent movements (International Federation of Red Cross and Red Crescent Societies, 2010). Adoption of these principles will allow valuable health information to flow freely to other entities positioned to respond appropriately without regard to local politics, ensuring a just and equitable solution to help to mitigate the potential for great harm.

References

Billings, M. (1997/2005). The influenza pandemic of 1918. Retrieved from http://virus.stanford.edu/uda/

Fallon, W. J. & Gayle, H. D. (2010). Report of the CISIS commission on smart global health policy: A healthier, safer and more prosperous world. Washington, DC: Center for Strategic & International Studies.

Gostin, L. O. (2004). Pandemic influenza: Public health preparedness for the next global health emergency. The Journal of Law, Medicine & Ethics, 32(4), 565-573. doi:10.1111/j.1748-720X.2004.tb01962.x

International Federation of Red Cross and Red Crescent Societies. (2010, July). Haiti: From sustaining lives to sustainable solutions – the challenge of sanitation. Geneva, Switzerland: Author.

Monto, A. S., Comanor, L., Shay, D. K., & Thompson, W. W. (2006). Epidemiology of pandemic influenza: use of surveillance and modeling for pandemic preparedness. Journal of Infectious Diseases, 194(Suppl. 2), S92-S97. doi:10.1086/507559

Ravilious, K. (2005, April 14). What a way to go. The Guardian. Retrieved from http://www.guardian.co.uk/science/2005/apr/14/research.science2

Smil, V. (2008). Global catastrophes and trends: the next fifty years. Cambridge, MA: The MIT Press.

Tapper, M. L. (2006). Emerging viral diseases and infectious disease risks. Haemophilia, 12(Suppl. 1), 3–7. doi:10.1111/j.1365-2516.2006.01194.x

Taubenberger, J. K., Morens, D. M., & Fauci, A. S. (2007). The next influenza pandemic: Can it be predicted? Journal of the American Medical Association, 297(18), 2025–2027. doi:10.1001/jama.297.18.2025.

Academia, Health Care, Public Health

A Novel Approach to Combat Heart Disease

According to Hansson (2005), cardiovascular disease is fast becoming the number one killer in the world among in developing countries and the Western world, due mainly to the correlation of increased rates of obesity and diabetes (Haffner, Lehto, Rönnemaa, Pyörälä, & Laakso, 1998; Miller, 2011; Willer et al., 2008). The goal of eradicating heart disease by the end of the twentieth century has been missed as cardiovascular disease is still responsible for 38% of deaths in North America. There has been much research over the last three decades regarding correlations between cardiovascular disease, obesity, and diabetes. Miller et al. (2011) identifies, based on the current literature, a number of metabolic syndromes in which elevated triglyceride levels are responsible for significantly increasing the risk of cardiovascular disease and the risk of death from a cardiac event.

Risk factors for cardiovascular disease, including smoking, hypercholesterolemia, and diabetes, which have positive predictive value for CVD, include a positive family history, hypertension, male gender, and age (Haffner, Lehto, Rönnemaa, Pyörälä, & Laakso, 1998; Hansson, 2005; Koliaki, 2011).

Demographically, according to NHANES 1999-2008 (as cited in Miller, 2011), Mexican American men (50 to 59 years old, 58.8%) are at the greatest risk with the highest prevalence of elevated triglyceride levels ( 150 mg/dL) followed by (in order of decreasing prevalence) Mexican American women ( 70 years old, 50.5%), non-Hispanic White men (60 to 69 years old, 43.6%), non-Hispanic White women (60 to 69 years old, 42.2%), non-Hispanic Black men (40 to 49 years old, 30.4%), and non-Hispanic Black women (60 to 69 years old, 25.3%).

Haffner et al. (1998) describe the importance of lowering cholesterol levels in those with diabetes mellitus type II as they both contribute to increases in mortality and morbidity from cardiovascular disease; therefore, efforts should be focused on identifying risks to heart health starting at age 30 with concomitant risk factors of diabetes or dyslipidemia, or any combination of two or more identified risk factors. More specific screening should begin at age 40 with Mexican American males and all other demographics suffering from any one of the secondary risk-factors, and at age 50 with all other ethnic demographics, regardless of the presence of risk-factors.

Specific screening for the at-risk population should include diagnostic percutaneous transthoracic coronary angiography (PTCA) and angioplasty, if needed. PTCA is a method of introducing a catheter through an artery to the coronary arteries of the heart, guided by radiology, to diagnose specific narrowing of these vessels, at which time a repair (angioplasty) can proceed immediately. PTCA, according to Koliaki et al. (2011), is the gold standard of diagnosing the presence and degree of atherosclerotic CVD. Currently, the standard for initiating PTCA requires a more acute presentation, typically complaints of chest pain or some other cardiac related illness. However, the proven safety and efficacy of PTCA may allow it to be used more as a screening tool as well as a primary coronary intervention in acute cases.

Utilizing the diffusions of innovations model of behavior change, public health entities can provide specific information to encourage interventional cardiologists to employ this technique as a focused CVD screening tool for at-risk populations (“Culture and health,” 2012). Adoption, however, is conditional on remuneration; therefore, a public health task force at the national level should investigate the potential for spending versus savings, and if significant, should disseminate the information to third-party payors (heath insurance providers, etc.) to ensure coverage when required. Additionally, grassroots efforts should be two-pronged, focusing on both the affected communities and the physicians most likely to contact the at-risk community. For the at-risk community, using mass-media, the message should simply be to discuss your risk with your physician, stop smoking, eat healthy, and exercise. The message, itself, needs to be conveyed in an effective manner, however. For the physicians, using mass-mailing and professional development campaigns, the message needs to more complex outlining risk versus reward, cost-effectiveness, and the potential for impacting a growing trend of heart-related death and disability. The American Heart Association has a proven track record of effective mass-media campaigns as well as professional development programs. So long as PTCA can be considered as an effective and cost-saving screening tool, the American Heart Association should certainly be involved in sending the message out.

Like with the proliferation of television advertisement of pharmaceuticals, using diffusions of innovations, we can get the heart-healthy message to the communities that would most benefit and the providers who can facilitate appropriate and novel screening and treatment techniques. We have already failed to eradicate CVD by the turn of the century, but if we think outside the box and develop novel approaches to consider, we may still have a chance at effectively lowering the incidence and prevalence of CVD in the years to come.

References

Culture and health. (2012). Public health and global essentials (Custom ed.; pp. 213-226). Sudbury, MA: Jones & Bartlett.

Haffner, S. M., Lehto, S., Rönnemaa, T., Pyörälä, K., & Laakso, M. (1998). Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. New England Journal of Medicine, 339(4), 229-234. doi:10.1056/NEJM199807233390404

Hansson, G. K. (2005). Inflammation, atherosclerosis, and coronary artery disease. New England Journal of Medicine, 352(16), 1685-1695. doi:10.1056/NEJMra043430

Koliaki, C., Sanidas, E., Dalianis, N., Panagiotakos, D., Papadopoulos, D., Votteas, V., & Katsilambros, N. (2011). Relationship between established cardiovascular risk factors and specific coronary angiographic findings in a large cohort of Greek catheterized patients. Angiology, 62(1), 74-80. doi:10.1177/0003319710370960

Miller, M., Stone, N. J., Ballantyne, C., Bittner, V., Criqui, M. H., Henry N. Ginsberg, H. N., … Council on the Kidney in Cardiovascular Disease (2011). Triglycerides and cardiovascular disease: A scientific statement from the American Heart Association. Circulation, 123(20), 2292-2333. doi:10.1161/CIR.0b013e3182160726

Willer, C. J., Sanna, S., Jackson, A. U., Scuteri, A., Bonnycastle, L. L., Clarke, R., … Abecasis, G. R. (2008). Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nature, 40(2), 161-169. doi:10.1038/ng.76

Appendix

P.E.R.I. Problem Identification

The health problem I have identified is cardiovascular disease (CVD). According to Hansson (2005), CVD was expected to be significantly reduced or eliminated by the turn of the century; however, cardiovascular disease remains one of the leading cause of death globally with a rise in obesity and diabetes incidence (Willer et al., 2008). The two primary factors contributing to CVD are thought to be hypercholesterolemia, or high cholesterol levels in the blood, and hypertension, or high blood pressure, and although Koliaki et al. (2011) shows no predictive value between obesity and CVD, there remains a strong correlation between obesity and diabetes (Haffner, Lehto, Rönnemaa, Pyörälä, & Laakso, 1998; Hansson, 2005). A better look at the emerging literature might provide insight as to why attempts to control cholesterol and blood pressure have largely failed to eradicate CVD.

Koliaki et al. (2011) contend that smoking, hypercholesterolemia, and diabetes have positive predictive value for CVD while a positive family history, hypertension, male gender, and age, though predictive, are significantly less specific. Considering the causative risk factors and admitting the difficulty in changing age, family history, and gender, altering smoking status, cholesterol levels, and severity of diabetes and blood pressure have all been shown to decrease the risk of CVD. However, like genetic factors such as family history and gender, researchers are finding difficulty in controlling cholesterol levels effectively in many patients, especially those with concommitant diabetes mellitus (Haffner et al., 1998; Willer, 2008). However, statin-type cholesterol-lowering medications appear to have other protective effects than merely lowering cholesterol (Hansson, 2005).

In order to combat the growing concern of cardiovascular disease and, ultimately, the increasing mortality from the same, the American Heart Association (AHA) has published a scientific statement paper regarding the latest literature and research (Miller et al., 2011). AHA has taken the lead in cardiovascular health and strives to promote best practices based on the available evidence. By promoting AHA’s position using mass-mailing campaigns to physicians practicing in primary care, emergency, cardiology, and endocrinology, we can be assured that the right message is being disseminated rapidly to those most inclined to intervene. As more physicans in the identified roles adopt the latest evidence-based practice, more at-risk patients can be screened for CVD and the contributing factors. As screening paradigms become more focused, more of the at-risk population will be identified sooner which will allow for earlier intervention decreasing overall mortality and morbidity from CVD.

P cardiovascular disease
E Causes: DM, type II; dyslipidemia (hypercholesterolemia); smoking; diet; exercise; gender; age
Burden: increasing mortality and morbidity globally
R Diabetes mellitus screening and control, HTN screening and control, statin-type medication prescription, PTCA screening recommendations, smoking cessation
I AHA position, public health mailing campaign, cadre of physician groups
Academia, Health Care, Public Health, Society

Determinants of Health – Mental Illness

When attempting to solve many of the issues relevant to public health, it is essential to understand the factors that contribute to disparities across various ethnic, racial, cultural and socioeconomic boundaries (Satcher & Higginbotham, 2008). In northeastern Connecticut, however, health disparities are primarily related to the socioeconomic strata, as much of the population is Caucasian and there are identifiable health disparities within this group (U.S. Census Bureau, 2002, 2008; U.S. Department of Health and Human Services, 2009). The disparity that I will focus on in this paper is mental illness.

According to Adler and Rehkopf (2008), unjust social disparity leads to greater health disparity, but what is unjust about social disparity? Adler and Rehkopf continue to describe efforts of researchers to evaluate how socioeconomic status, both, in conjunction with and independent of race or ethnicity, contribute to health disparities. There exists a significant difference in the manner in which different cultures approach mental health needs (Hatzenbuehler, Keyes, Narrow, Grant, & Hasin, 2008). Whites, who are more prone to suffering mental health issues, according to McGuire and Miranda (2008), preferring to seek professional care while Blacks are more likely to opt for self-directed care. Though Wang, Burglund, and Kessler (2001) tell of mental health treatment disparities between Whites and Blacks, in their study, 14 times more Whites responded than Blacks which may suggest that Whites are more apt to discuss mental health issues and Blacks might not unless they are motivated by extrinsic factors, such as poor care or the impression thereof. As long as Blacks are not prevented or discouraged from seeking care, there is no injustice in choosing self-care; however, it may not be the most effective option. Cultural awareness on the part of health care providers who may have an opportunity to provide health education to Blacks may alone increase the utilization of mental health services among the Black demographic.

More importantly, mental illness often exists in the presence of poverty and the lack of education. Much of the literature, such as Schwartz and Meyer (2010), seems to make the implication that low socioeconomic status is a causative risk-factor for mental illness, yet the literature also makes the distinction that one of the lowest groups on the socioeconomic ladder, Blacks, have a lower incidence, overall, of mental illness. This may be true in some instances; however, it is more likely that mental illness may be the proximal cause for an afflicted person’s socioeconomic status, especially if the illness manifested early enough to interfere with the person’s education.

More research needs to be undertaken to identify effective programs that aim to mitigate bias of mental health conditions within the community. As mental health disorders lose their stigma, more people who suffer from mental health issues will be able to seek care comfortably and unafraid, leading to increased treatment rates and increased synthesis within the community. This synthesis alone would alleviate much of the socioeconomic burden. Additionally, we need to shift our focus and strive to fix health issues locally, not nationally or globally. The world is comprised of a network of communities of individuals. Impacting the individual is the first step to affecting positive social change. Focusing on individual health will ultimately impact community, national, and global health.

The U.S. Health care system is overtaxed in caring for people with mental illness. According to Insel (2008), we need to refocus our efforts on providing care for mental illness to reduce the enormous indirect costs estimated at $193.2-billion per year. A viable solution in addressing mental illness as a health disparity, I feel, lies in understanding the manner that mental illness causes lower socioeconomic status which, in turn, causes risk of disparate care. Programs designed to aim for situational mitigation instead of mental health recovery will be less costly, more effective and, overall, more ideal. There will still be an obvious and great need for treatment and recovery programs, but with mitigation, I posit that they will be more effective, also.

References

Adler, N. E. & Rehkopf, D. H. (2008). U.S. disparities in health: descriptions, causes, and mechanisms. Annual Review of Public Health, 29(1), 235-252. doi:10.1146/annurev.publhealth.29.020907.090852

Hatzenbuehler, M. L., Keyes, K. M., Narrow, W. E., Grant, B. F., & Hasin, D. S. (2008). Racial/ethnic disparities in service utilization for individuals with co-occurring mental health and substance use disorders in the general population. Journal of Clinical Psychology, 69(7), 1112-1121. doi:10.4088/JCP.v69n0711

Insel, T. R. (2008). Assessing the economic costs of serious mental illness. American Journal of Psychiatry, 165, 663-665. doi:10.1176/appi.ajp.2008.08030366

McGuire, T. G. & Miranda, J. (2008). New evidence regarding racial and ethnic disparities in mental health: policy implications. Health Affairs, 27(2), 393-403. doi:10.1377/hlthaff.27.2.393

Newport, F. & Mendes, E. (2009, July 22). About one in six U.S. adults are without health insurance: Highest uninsured rates among Hispanics, the young, and those with low incomes. Gallup-Heathways Well-Being Index. Retrieved from http://www.gallup.com/poll/121820/one-six-adults-without-health-insurance.aspx

Satcher, D. & Higginbotham, E. J. (2008). The public health approach to eliminating health disparities. American Journal of Public Health, 98(3), 400–403. doi:10.2105/AJPH.2007.123919

Schwartz, S. & Meyer, I. H. (2010). Mental health disparities research: The impact of within and between group analyses on tests of social stress hypotheses. Social Science and Medicine, 70, 1111-1118. doi:10.1016/j.socscimed.2009.11.032

U.S. Census Bureau. (2002). Census 2000. Retrieved from http://www.ct.gov/ecd/cwp/view.asp?a=1106&q=250616

U.S. Census Bureau. (2008). Population estimates: Annual estimates of the resident population by age, sex, race, and Hispanic origin for counties in Connecticut: April 1, 2000 to July 1, 2008 [Data]. Retrieved from http://www.census.gov/popest/counties/asrh/files/cc-est2008-alldata-09.csv

U.S. Department of Health and Human Services. (2009). Community health status indicators report. Retrieved from http://communityhealth.hhs.gov/

Academia, Culture, Emergency Medical Services, Health Care

Motivation: A Career that I Enjoy

I am lucky to work in a career that I absolutely enjoy. As a paramedic in the emergency medical services (EMS), I am called upon to help those in my community in the worst of circumstances to help them when they feel helpless. There are drawbacks, however. Many people rely on EMS for problems that even they do not view as emergent, and others just plainly abuse the system. Still, I enjoy being the one called upon to help. My primary motivations are my sense of community, my ability to reduce suffering, and my ability to raise the standard of care within the system. Maslow (1943) includes some of the earliest accepted work on motivational theory, and more contemporary work is based on the acceptance, rejection or modification of his theories, so I will focus on Maslow to begin. My needs, according to Maslow, are not as important to motivation. Need fulfillment will not motivate me to perform; however, a lack of fulfillment may prevent me from performing. This is especially true for Maslow’s lower-order needs. Maslow discusses how emergency situations can “obscure the ‘higher’ motivations [and create] a lopsided view of human capacities and human nature” (p. 375), and while my career is focused on responding to emergencies, this may hold true for me. While Maslow’s theory is not wholly accepted motivational schema (Robbins & Judge, 2010), EMS managers, and other public safety managers, would do well to understand this exception to motivational theory.

Many EMS managers, it seems, subscribe to McGregor’s (1957/2000) theory X without understanding the ramifications or the competing theory Y. There is a deep-seated belief that the workforce is lazy and will do anything possible to undermine the operation. This results in micromanagement tactics that seem to promote an unwillingness to promote the goals of the employer. McGregor highlights this and cautions that it a result of poor management technique, not a cause that is easily rectified by the chosen technique.

Other theories, such as goal-setting, equity theory, and expectancy theory, as described in Robbins and Judge (2010), are all lacking in one particular constant: there is no constant in human behavior. There are a number of ways that a single motivational factor might influence a particular person on any particular day. For any theory to always be true in every situation, it would cease to be a theory and become a law. This being said, as managers, we need to measure the importance of certain tasks and focus our efforts on communicating this importance to the workforce. It is the manner of this communication that will tend to fail or succeed, based on both the needs of the manager and the needs of the employee at the moment the message is passed.

References

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396. doi:10.1037/h0054346

McGregor, D. (2000). The Human Side of Enterprise (Reprinted from Adventure in thought and action: Proceedings of the fifth anniversary convocation of the School of Industrial Management, Massachusetts Institute of Technology, Cambridge, 1957, April 9. Cambridge, MA: MIT School of Industrial Management). Reflections, 2(1), 6-14. doi:10.1162/152417300569962

Robbins, S. P. & Judge, T. A. (2010). Motivation concepts. Essentials of organizational behavior (pp. 62-79). Upper Saddle River, NJ: Pearson Prentice Hall.

Academia, Health Care, Public Health, Society

Community Health: How Healthy is My Community?

I currently reside in Windham County, Connecticut. Windham County is primarily rural with one community, Willimantic, comprising most of the urban demographic. Windham County is functionally divided in half (north to south) in regards to health and hospital services. Primarily, Windham Community Memorial Hospital serves the west and Day Kimball Hospital serves the east. Accordingly, the eastern and western portions of the county may not be representative of each other, yet both are represented as a singular group when considering county-based statistics. This is a shortcoming of county-based statistics. In this instance, Willimantic, in the western portion of Windham County, may negatively affect the statistics of towns like Killingly, Pomfret, and Putnam, in the eastern portion of the county, due primarily to an increase in impoverished populations residing in Willimantic (U.S. Census Bureau, 2002). Additionally, data is lacking for a number of measures, according to the Community Health Status Indicators Project Working Group (2009), but continuing efforts will be made to increase reporting over time.

According to the U.S. Census Bureau (2008) and the U.S. Department of Health and Human Services (2009), the population of Windham County is 117,345 and is predominantly white (94.3%) with the remaining (5.7%) divided among, in order of predominance, Hispanics, Blacks, Asians and Pacific Islanders, and American Indians. The particularly vulnerable populations identified are adults age 25 and older who do not hold a high school diploma, are unemployed, are severely disabled and unable to work, suffer major depression, or have recently used illicit drugs. The uninsured rate in Windham County is well below the 16% national average at 9.5% (Newport & Mendes, 2009; U.S. Department of Health and Human Services, 2009).

Windham County fares equal or better in most measures, at least within the margin of error; therefore, I feel that Windham County, though not exceptionally healthy, is better than most and striving to meet the national standards (U.S. Department of Health and Human Services, 2009). For example, though the incidence of cancer and subsequent death resulting remains higher than peer counties, Windham County falls well within the expected range of death measures and exceeds peer counties in homicide, stroke, suicide, and unintentional injuries. Windham County also falls below the national standardized target for both stroke and coronary heart disease deaths. Infant mortality and birth measures seem representative of peer counties. Windham County also meets or exceeds environmental standards in all cases except for two reports of E. coli infections. There were also reports of five cases of Haemophilus influenzae B, two cases of Hepatitis A, and three cases of Hepatitis B — the only unexpected cases of infectious diseases reported. Pertussis incidence was limited to 25% of expected cases.

Windham County is not exceptional, but living here gives me the sense that the focus is on preventative care rather than acute care, which might explain how the health goals are being achieved overall. The report from the U.S. Department of Health and Human Services (2009) is in agreement.

References

Community Health Status Indicators Project Working Group. (2009). Data sources, definitions, and notes for CHSI2009. Retrieved from http://communityhealth.hhs.gov/

Newport, F. & Mendes, E. (2009, July 22). About one in six U.S. adults are without health insurance: Highest uninsured rates among Hispanics, the young, and those with low incomes. Gallup-Heathways Well-Being Index. Retrieved from http://www.gallup.com/poll/121820/one-six-adults-without-health-insurance.aspx

U.S. Census Bureau. (2002). Census 2000. Retrieved from http://www.ct.gov/ecd/cwp/view.asp?a=1106&q=250616

U.S. Census Bureau. (2008). Population estimates: Annual estimates of the resident population by age, sex, race, and Hispanic origin for counties in Connecticut: April 1, 2000 to July 1, 2008 [Data]. Retrieved from http://www.census.gov/popest/counties/asrh/files/cc-est2008-alldata-09.csv

U.S. Department of Health and Human Services. (2009). Community health status indicators report. Retrieved from http://communityhealth.hhs.gov/