A New Paradigm to Improve Patient Outcomes

A Tongue-in-Cheek Look at the Cost of Patient Satisfaction

A landmark article entitled “The cost of satisfaction: a national study of patient satisfaction, health care utilization, expenditures, and mortality” was recently published in the Archives of Internal Medicine by Fenton et al. (1). The authors conducted a prospective cohort study of adult respondents (n=51,946) to the 2000 through 2007 national Medical Expenditure Panel Survey. The results showed higher patient satisfaction was associated with higher admission rates to the hospital, higher overall health care expenditures, and increased mortality.

The higher costs are probably not surprising to many health care administrators. Programs to improve patient satisfaction such as advertising, valet parking, gourmet meals for patients and visitors, massages, never-ending patient and family satisfaction surveys, etc. are expensive and would be expected to increase costs. Some would argue that these costs are simply the price of competing for patients in the present health care environment. Although the outcomes are poorer, substituting patient satisfaction as a surrogate marker for quality of care is probably still valid as a business goal (2). Furthermore, administrators and some healthcare providers are paid bonuses based on patient satisfaction. These bonuses are necessary to maintain salaries at a level to attract the best and brightest.

Although it seems logical that most ill patients wish to live and get well as quickly and cheaply as possible, the Archives article demonstrates that this is a fallacy. Otherwise, higher patient satisfaction would clearly correlate with lower mortality, admission rates and expenses. Since the hospitals and other health care organizations are here to serve the public, some would argue that giving the patients what they want is more important that boring outcomes such as hospital admission rates, costs and mortality.

The contention of this study – that dissatisfaction might improve patient survival – may have biological plausibility.  Irritation with the healthcare process might induce adrenal activation, with resulting increases in beneficial endogenous catecholamines and cortisol.  The resulting increase in global oxygen delivery might reduce organ failure.  Furthermore, the irritated patient is less likely to consent to unnecessary medical procedures and is therefore protected from ensuing complications.  An angry patient is likely to have less contact with healthcare providers who are colonized with potentially dangerous multi-drug resistant bacteria.

Specific bedside practices can be implemented in order to increase patient dissatisfaction, and thereby benefit mortality.   Nurses can concentrate on techniques of sleep deprivation such as waking the patient to ask if they want a sleeping pill.  Third year medical students can be employed to start all IVs and perform all lumbar punctures.  Attending physicians can do their part by being aloof and standoffish.  For instance, a patient suffering an acute myocardial infarction might particularly benefit from hearing about the minor inconveniences the attending suffered aboard a recent south Pacific cruise ship – “I ordered red caviar, and they brought black!”  During the medical interview, non-pregnant women should always be asked “when is the baby due?”  Repeatedly confusing the patient’s name, or calling them by multiple erroneous names on purpose, can heighten their sense of insecurity.  Simply making quotation signs with your fingers whenever the physician refers to themselves as their “doctor” can be quite off-putting. 

Simple props can be useful.  Wads of high-denomination cash, conspicuously bulging from all pockets of the attending’s white coat, can promote a sense of moral outrage.  Conspicuously placing a clothespin on your nose upon entering the patient’s room can be quite effective.  Simply placing your stethoscope in ice water for a few minutes before applying it to the patient’s bare chest can make a difference   

Other more innovative techniques might arise.  Charging the patient in cash for each individual medical intervention might be quite useful, emphasizing the magnitude of overcharging.  This would be made apparent to the patient who for instance might be asked to pay $40 cash on the barrelhead for a single aspirin pill.

Often the little things make a big difference – dropping a pile of aluminum food trays on the floor at 4 AM, clamping the Foley tube, purposely ignoring requests for a bedpan, or making the patient NPO for extended periods for no apparent reason can be quite effective. 

However, we fear that health care professionals may have difficulty overcoming their training to be responsive to patients. Therefore, we suggest a different strategy to National health care planners seeking to reduce costs and improve patient mortality, what we term the designated institutional offender (DIO). A DIO program where an employee is hired to offend patients would likely be quite cost effective. The DIO would not need expensive equipment or other resources. The DIO role is best suited for someone with minimal education and a provocative attitude. Only the most deficient and densest (as opposed to the best and brightest) should be hired.

Clearly, an authoritative group must be formed to establish guidelines and bundles for both the DIO and healthcare providers. We suggest formation of the Institute of Healthcare Irritation, or IHI.  They could certify DIOs to insure that the 7 habits of highly offensive people are used (3).  IHI can also establish clinical practice bundles like the rudeness bundle, the physical discomfort bundle, the moral outrage bundle, etc.

We suggest the following as an example to muster compliance with the physical discomfort bundle. The patient must be documented to be experiencing:

• Hunger
• Thirst
• Too cold (or too hot)
• Sleep deprivation
• Drug-related constipation
• And the inability to evacuate their bladder

Patient satisfaction with even a single component indicates failure of bundle compliance. Of course a cadre of personnel will need to be hired to ensure compliance with the bundles.

Based on the evidence from the Archives article, there was a 9.1% cost differential between the highest and the lowest satisfaction quartile. Shifting patients to lower satisfaction quartiles could result in huge cost savings. If the DIO and IHI strategies to offend are particularly effective, many patients will not return for health care at all, resulting in further savings. Targeting those who are the largest consumers of care could result in even larger savings.

The DIO and IHI would also save lives. Those patients in the highest satisfaction quartile had a 26% higher mortality rate than the lowest quartile. If patients who have poor self-related health and > 3 chronic diseases are excluded, the mortality rate is 44% higher in the highest satisfaction quartile.

Administrators could now be paid bonuses for not only compliance with the IHI bundles, but also lower patient satisfaction scores, since they can argue that lower satisfaction is actually good for patients. Furthermore, the administrators should receive higher compensation since the DIO and the personnel hired to ensure compliance with the IHI guidelines would be additional employees in their administrative chain of command and administrative salaries are often based on the number of employees they supervise.   

Richard A. Robbins, MD

Robert A. Raschke, MD

References

1. Fenton JJ, Jerant AF, Bertakis KD, Franks P. The cost of satisfaction: a national study of patient satisfaction, health care utilization, expenditures, and mortality. Arch Intern Med 2012;172:405-11.
2. Browne K, Roseman D, Shaller D, Edgman-Levitan S. Analysis & commentary. Measuring patient experience as a strategy for improving primary care. Health Aff (Millwood). 2010 May;29(5):921-5
3. Bing S. The seven habits of highly offensive people. Fortune magazine available at http://money.cnn.com/magazines/fortune/fortune_archive/1995/11/27/208025/index.htm (accessed 7-7-12).

Reference as: Robbins RA, Raschke RA. A new paradigm to improve patient outcomes: a tongue-in-cheek look at the cost of patient satisfaction. Southwest J Pulm Crit Care 2012;5:33-5. (Click here for a PDF version of the editorial) 

A Little Knowledge is a Dangerous Thing

An article entitled “A Comprehensive Care Management Program to Prevent Chronic Obstructive Pulmonary Disease Hospitalizations: A Randomized, Controlled Trial” from the VA cooperative studies program was recently published in the Annals of Internal Medicine (1).  This article describes the BREATH trial mentioned in a previous editorial (2). BREATH was a randomized, controlled, multi-center trial performed at 20 VA medical centers comparing an educational comprehensive care management program to guideline-based usual care for patients with chronic obstructive pulmonary disease (COPD). The intervention included COPD education during 4 individual and 1 group sessions, an action plan for identification and treatment of exacerbations, and scheduled proactive telephone calls for case management. After enrolling 426 (44%) of the planned total of 960 the trial was stopped because there were 28 deaths from all causes in the intervention group versus 10 in the usual care group (hazard ratio, 3.00; 95% CI, 1.46 to 6.17; p = 0.002). Deaths due to COPD accounted for the largest difference (10 deaths in the intervention group versus 3 in usual care; hazard ratio, 3.60; 95% CI, 0.99 to 13.08). This trial led us to perform a meta-analysis of educational interventions in COPD (3). In this meta-analysis of 2476 subjects we found no difference in mortality between intervention and usual care groups and that the recent Annals study was heterogenous compared to the other studies.

Should the recent VA study have been stopped early? Several reports demonstrate that studies stopped early usually overestimate treatment effects (4-7). Some have even suggested that stopping trials early is unethical (7). A number of articles suggest that trials should only be stopped if predetermined statistical parameters are exceeded, with the p value for stopping set at a very low level (4-7).  There was no planned interim analysis for any outcome in the recent VA trial. The rationale for stopping a study for an adverse effect when there is no a priori reasonable link between the intervention and the adverse effect is missing in this instance.  It seems unlikely that education would actually lead to increased deaths in COPD patients.  Any effect should logically have impacted the COPD related mortality, yet there was no significant increase for COPD related deaths in the intervention group. An accompanying editorial by Stuart Pocock makes most of these points and suggests that chance was the most likely cause of the excess deaths (8).

The VA Coop Trials coordinating center told the investigators that the reason for stopping the trial was that there were “significant adverse events” in the intervention group. Inquires regarding what adverse events went unanswered. This would seem to be a breakdown in VA research oversight. The information provided to both investigators and research subjects was incomplete and would seem to be a violation of the informed consent, which states the subject would be notified of any new information that significantly altered their risk.

Lastly, investigators were repeatedly warned by the VA coordinating center that “all communications with the media should occur through your facility Public Affairs office”. It seems very unlikely that personnel in any public affairs office have sufficient research training to answer any medical, statistical or ethical inquiries into the conduct of this study.

In our meta-analysis we have shown that self-management education is associated with a reduction in hospital admissions with no indication for detrimental effects in other outcome parameters. This would seem sufficient to justify a recommendation of self-management education in COPD. However, due to variability in interventions, study populations, follow-up time, and outcome measures, data are still insufficient to formulate clear recommendations regarding the form and content of self-management education programs in COPD.

Richard A. Robbins, M.D.*

Editor, Southwest Journal of Pulmonary

   and Critical Care

References

1. Fan VS, Gaziano JM, Lew R, et al. A comprehensive care management program to prevent chronic obstructive pulmonary disease hospitalizations: a randomized, controlled trial. Ann Intern Med 2012;156:673-683.
2. Robbins RA. COPD, COOP and BREATH at the VA. Southwest J Pulm Crit Care 2011;2:27-28.
3. Hurley J, Gerkin R, Fahy B, Robbins RA. Meta-analysis of self-management education for patients with chronic obstructive pulmonary disease. Southwest J Pulm Crit Care 2012;4:?-?.
4. Pocock SJ, Hughes MD. Practical problems in interim analyses, with particular regard to estimation.Control Clin Trials 1989;10:209S-221S.
5. Montori VM, Devereaux PJ, Adhikari NK, et al. Randomized trials stopped early for benefit: a systematic review. JAMA 2005;294:2203-9.
6. Bassler D, Briel M, Montori VM, et al. Stopping randomized trials early for benefit and estimation of treatment effects: systematic review and meta-regression analysis. JAMA 2010;303:1180-7.
7. Mueller PS, Montori VM, Bassler D, Koenig BA, Guyatt GH. Ethical issues in stopping randomized trials early because of apparent benefit. Ann Intern Med. 2007;146:878-81.
8. Pocock SJ. Ethical dilemmas and malfunctions in clinical trials research. Ann Intern Med 2012;156:746-747.

*Dr. Robbins was an investigator and one of the co-authors of the Annals of Internal Medicine manuscript (reference #1).

Reference as: Robbins RA. A little knowledge is a dangerous thing. Southwest J Pulm Crit Care 2012;4:203-4. (Click here for a PDF version of the editorial) 

VA Administrators Gaming the System

On 4-23-12 the Department of Veterans Affairs (VA) Office of Inspector General (OIG) issued a report of the accuracy of the Veterans Healthcare Administration (VHA) wait times for mental health services. The report found that “VHA does not have a reliable and accurate method of determining whether they are providing patients timely access to mental health care services. VHA did not provide first-time patients with timely mental health evaluations and existing patients often waited more than 14 days past their desired date of care for their treatment appointment. As a result, performance measures used to report patient’s access to mental health care do not depict the true picture of a patient’s waiting time to see a mental health provider.” (1). The OIG made several recommendations and the VA administration quickly concurred with these recommendations. Only four days earlier the VA announced plans to hire 1900 new mental health staff (2).

This sounded familiar and so a quick search on the internet revealed that about a year ago the United States Court of Appeals for the Ninth Circuit issued a scathing ruling saying that the VA had failed to provide adequate mental health services to Veterans (3). A quick review of the Office of Inspector General’s website revealed multiple instances of similar findings dating back to at least 2002 (4-7). In each instance, unreliable data regarding wait times was cited, VA administration agreed, and no or inadequate action was taken.

Inadequate Numbers of Providers

One of the problems is that inadequate numbers of clinical physicians and nurses are employed by the VA to care for the patients. In his “Prescription for Change”, Dr. Ken Kizer, then VA Undersecretary for Health, made bold changes to the VA system in the mid 1990’s (8). Kizer cut the numbers of hospitals but also the numbers of clinicians while the numbers of patients increased (9). The result was a marked drop in the number of physicians and nurses per VA enrollee (Figure 1).

Figure 1. Nurses (squares) and physicians (diamonds) per 1000 VA enrollees for selected years (10,11).

This data is consistent with a 2011 VA survey that asked VA mental health professionals whether their medical center had adequate mental health staff to meet current veteran demands for care; 71 percent responded no. According to the OIG, VHA’s greatest challenge has been to hire psychiatrists (1). Three of the four sites visited by the OIG had vacant psychiatry positions. One site was trying to replace three psychiatrists who left in the past year. This despite psychiatrists being one of the lowest paid of the medical specialties (12). The VA already has about 1,500 vacancies in mental-health specialties. This prompted Sen. Patty Murray, Chairman of the Senate Committee on Veterans Affairs to ask about the new positions, "How are you going to ensure that 1,600 positions ... don't become 1,600 vacancies?" (13).

Administrative Bonuses

A second problem not identified by the OIG is administrative bonuses. Since 1996, wait times have been one of the hospital administrators’ performance measures on which administrative bonuses are based. According to the OIG these numbers are unreliable and frequently “gamed” (1,4-7). This includes directions from VA supervisors to enter incorrect data shortening wait times (4-7).

At a hearing before the Senate Committee on Veterans' Affairs Linda Halliday from the VA OIG said "They need a culture change. They need to hold facility directors accountable for integrity of the data." (13). VA "greatly distorted" the waiting time for appointments, Halliday said, enabling the department to claim that 95 percent of first-time patients received an evaluation within 14 days when, in reality, fewer than half were seen in that time. Nicholas Tolentino, a former mental-health administrative officer at the VA Medical Center in Manchester, N.H., told the committee that managers pressed the staff to see as many veterans as possible while providing the most minimal services possible. "Ultimately, I could not continue to work at a facility where the well-being of our patients seemed secondary to making the numbers look good," he said.

Although falsifying wait times has been known for years, there has been inadequate action to correct the practice according to the VA OIG. Sen. Murray said the findings show a "rampant gaming of the system." (13). This should not be surprising. Clerical personnel who file the data have their evaluations, and in many cases pay, determined by supervisors who financially benefit from a report of shorter wait times. There appears no apparent penalty for filing falsified data. If penalties did exist, it seems likely that the clerks or clinicians would be the ones to shoulder the blame.

The Current System is Ineffective

A repeated pattern of the OIG being called to look at wait times, stating they are false, making recommendations, the VA concurring, and nothing being done has been going on for years (1, 3-7). Based on these previous experiences, the VA will likely be unable to hire the numbers of clinicians needed and wait times will continue to be unacceptably long but will be “gamed” to “make the numbers look good”. Pressure will be placed on the remaining clinicians to do more with less. Some will become frustrated and leave the VA. The administrators will continue to receive bonuses for inaccurate short wait times. If past events hold true, in 2-5 years another VA OIG report will be requested. It will restate that the VA falsified the wait times. This will be followed by a brief outcry, but nothing will be done.

The VA OIG apparently has no real power and the VA administrators have no real oversight. The VA OIG continues to make recommendations regarding additional administrative oversight which smacks of putting the fox in charge of the hen house. Furthermore, the ever increasing numbers of administrators likely rob the clinical resources necessary to care for the patients. Decreased clinical expenses have been shown to increase standardized mortality rates, in other words, hiring more administrators at the expense of clinicians likely contributes to excess deaths (14). Although this might seem obvious, when the decrease of physicians and nurses in the VA began in the mid 1990’s there seemed little questioning that the reduction was an “improvement” in care.

Traditional measures such as mortality, morbidity, etc. are slow to change and difficult to measure. In order to demonstrate an “improvement” in care what was done was to replace outcome measures with process measures. Process measures assess the frequency that an intervention is performed.  The problem appears that poor process measures were chosen. The measures included many ineffective measures such as vaccination with the 23 polyvalent pneumococcal vaccine in adult patients and discharge instructions including advice to quit smoking at hospital discharge (15). Many were based on opinion or poorly done trials, and when closely examined, were not associated with better outcomes. Most of the “improvement” appeared to occur in performance of these ineffective measures. However, these measures appeared to be quite popular with the administrators who were paid bonuses for their performance.

Root Causes of the Problems

The root causes go back to Kizer’s Prescription for Change. The VA decreased the numbers of clinicians, but especially specialists, while increasing the numbers of administrators and patients. The result has been what we observe now. Specialists such as psychiatrists are in short supply. They were often replaced by a cadre of physician extenders more intent on satisfying a checklist of ineffective process measures rather than providing real help to the patient. Waiting times lengthened and the administrative solution was cover up the problem by lying about the data.

VA medical centers are now usually run by administrators with no real medical experience. From the director down through their administrative chain of command, many are insufficiently medically trained to supervise a medical center. These administrators could not be expected to make good administrative decisions especially when clinicians have no meaningful input (10).

The present system is not transparent. My colleagues and I had to go through a FOIA request to obtain data on the numbers of physicians and nurses presented above. Even when data is known, the integrity of the data may be called into question as illustrated by the data with the wait times. 

The falsification of the wait times illustrates the lack of effective oversight. VA administration appears to be the problem and hiring more administrators who report to the same administrators will not solve the problem as suggested by the VA OIG (3-7). What is needed is a system where problems such as alteration of wait times can be identified on the local level and quickly corrected.

Solutions to the Problems

The first and most important solution is to provide meaningful oversight by at the local level by someone knowledgeable in healthcare. Currently, no system is in place to assure that administrators are accountable.  Despite concurring with the multitude of VA OIG’s recommendations, VA central office and the Veterans Integrated Service Networks have not been effective at correcting the problem of falsified data. In fact, their bonuses also depend on the data looking good. Locally, there exists a system of patient advocates and compliance officers but they report to the same administrators that they should be overseeing. The present system is not working. Therefore, I propose a new solution, the concept of the physician ombudsman. The ombudsman would be answerable to the VA OIG’s office. The various compliance officers, patient advocates, etc. should be reassigned to work for the ombudsman and not for the very people that they should be scrutinizing.

The physician ombudsman should be a part-time clinician, say 20% at a minimum. The latter is important in maintaining local clinical knowledge and identifying falsified clinical data. One of the faults of the present VA OIG system is that when they look at a complaint, they seem to have difficulty in identifying the source of the problem (16). Local knowledge would likely help and clinical experience would be invaluable. For example, it would be hard to say waiting times are short when the clinician ombudsman has difficulty referring a patient to a specialist at the VA or even booking a new or returning patient into their own clinic.

The overseeing ombudsman needs to have real oversight power, otherwise we have a repeat of the present system where problems are identified but nothing is done. Administrators should be privileged similar to clinicians. Administrators should undergo credentialing and review. This should be done by the physician ombudsman’s office.  Furthermore, the physician ombudsman should have the capacity to suspend administrative privileges and decisions that are potentially dangerous. For example, cutting the nursing staffing to dangerous levels in order to balance a budget might be an example of a situation where an ombudsman could rescind the action.

The paying of administrative bonuses for clinical work done by clinicians should stop. Administrators do not have the necessary medical training to supervise clinicians, and furthermore, do nothing to improve efficiency or clinically benefit Veterans (14). The present system only encourages further expansion of an already bloated administration (17). Administrators hire more administrators to reduce their workload. However, since they now supervise more people, they argue for an increase in pay. If a bonus must be paid, why not pay for something over which the administrators have real control, such as administrative efficiency (18). Perhaps this will stop the spiraling administrative costs that have been occurring in healthcare (17).

These suggestions are only some of the steps that could be taken to improve the chronic falsification of data by administrators with a financial conflict of interest. The present system appears to be ineffective and unlikely to change in the absence of action outside the VA. Otherwise, the repeating cycle of the OIG being called to look at wait times, noting that they are gamed, and nothing being done will continue.

Richard A. Robbins, M.D.*

Editor, Southwest Journal of Pulmonary

            and Critical Care

References

1. http://www.va.gov/oig/pubs/VAOIG-12-00900-168.pdf  (accessed 4-26-12).
2. http://www.va.gov/opa/pressrel/pressrelease.cfm?id=2302 (accessed 4-26-12).
3. http://www.ca9.uscourts.gov/datastore/opinions/2011/07/12/08-16728.pdf (accessed 4-26-12).
4. http://www.va.gov/oig/52/reports/2003/VAOIG-02-02129-95.pdf (accessed 4-26-12).
5. http://www.va.gov/oig/54/reports/VAOIG-05-03028-145.pdf (accessed 4-26-12).
6. http://www.va.gov/oig/54/reports/VAOIG-05-03028-145.pdf (accessed 4-26-12).
7. http://www.va.gov/oig/52/reports/2007/VAOIG-07-00616-199.pdf (accessed 4-26-12).
8. www.va.gov/HEALTHPOLICYPLANNING/rxweb.pdf (accessed 4-26-12).
9. http://veterans.house.gov/107th-congress-hearing-archives (accessed 3/18/2012).
10. Robbins RA. Profiles in medical courage: of mice, maggots and Steve Klotz. Southwest J Pulm Crit Care 2012;4:71-7.
11. Robbins RA. Unpublished observations obtained from the Department of Veterans Affairs by FOIA request.
12. http://www.medscape.com/features/slideshow/compensation/2012/psychiatry (accessed 4-26-12).
13. http://seattletimes.nwsource.com/html/localnews/2018071724_mentalhealth26.html (accessed 4-26-12).
14. Robbins RA, Gerkin R, Singarajah CU. Correlation between patient outcomes and clinical costs in the VA healthcare system. Southwest J Pulm Crit Care 2012;4:94-100.
15. Robbins RA, Klotz SA. Quality of care in U.S. hospitals. N Engl J Med 2005;353:1860-1 [letter].
16. Robbins RA. Mismanagement at the VA: where's the problem? Southwest J Pulm Crit Care 2011;3:151-3.
17. Woolhandler S, Campbell T, Himmelstein DU. Health care administration in the United States and Canada: micromanagement, macro costs. Int J Health Serv 2004;34:65-78.
18. Gao J, Moran E, Almenoff PL, Render ML, Campbell J, Jha AK. Variations in efficiency and the relationship to quality of care in the Veterans health system. Health Aff (Millwood) 2011;30:655-63.

*The author is a former VA physician who retired July 2, 2011 after 31 years.

The opinions expressed in this editorial are the opinions of the author and not necessarily the opinions of the Southwest Journal of Pulmonary and Critical Care or the Arizona Thoracic Society.

Reference as: Robbins RA. VA administrators gaming the system. Southwest J Pulm Crit Care 2012;4:149-54. (Click here for a PDF version of the editorial)

Will Fewer Tests Improve Healthcare or Profits?

Earlier this month, the American Board of Internal Medicine (ABIM) Foundation, in partnership with Consumer Reports, announced an educational initiative called Choosing Wisely (1). Nine medical organizations were asked to name five things physicians and patients should question. The initiative lists specific, evidence-based recommendations physicians and patients should discuss to make wise decisions on their individual situation. The list of tests and procedures Choosing Wisely advises against include common procedures and treatments such as EKGs done routinely during a physical examination, routine MRI’s for back pain, antibiotics for mild sinusitis, and routine EKG and chest X-rays preoperatively. Some experts estimate that up to one-third of the $2 trillion of annual health care costs in the United States each year is spent on unnecessary hospitalizations and tests, unproven treatments, ineffective new drugs and medical devices, and futile care at the end of life (2). We at the Southwest Journal of Pulmonary and Critical Care (SWJPCC) applaud the use of evidence-based medicine in determining testing and treatment. Any information that can inform medical decision making is welcome.

With most of the Choosing Wisely recommendations there is solid evidence that the procedures do not improve patient outcomes (1). Nevertheless several previous efforts to limit testing have failed and even provoked backlashes. For example, in November 2009, new mammography guidelines issued by the U.S. Preventive Services Task Force advised women to be screened less frequently for breast cancer, stoking fear among patients about increasing government control over personal health care decisions and the rationing of treatment (2). An area of further concern is that the Choosing Wisely recommendations will be used not just to make informed decisions, but by payers to limit decisions that a patient and physician can make. This is especially true since the motivation for these recommendations may not be to improve care but to decrease expenses and increase profits by insurers and other payers.

Several of the quality improvement and training organizations affiliated with the ABIM have recommendations and guidelines that are either non- or weakly-evidence based and have not been shown to improve patient outcomes. Surely, these should also be questioned. These include most of the hospital performance measures for acute myocardial infarction, congestive heart failure, pneumonia and surgical process of care, the ventilator-associated pneumonia guidelines, and the central line associated bloodstream infection guidelines (3-5).  Furthermore, in examining the requirements for recertification by the ABIM, the parent organization that sponsored the Choosing Wisely initiative, the evidence basis for the ever increasing frequency of examinations for ever increasing fees and the quality improvement initiative in individual practices is unclear (6).

The recommendations number only 5 from each society (with several overlapping) and come from only 9 of the over 50 medical societies, organizations and boards affiliated with the ABIM. Why recommendations from other medical societies including pulmonary and critical care organizations such as the American Thoracic Society (ATS)* and the American College of Chest Physicians (ACCP) were not included was not stated. In order to help the ABIM, ATS and ACCP, we list some procedures and treatments below that pulmonary and critical care physicians might consider for inclusion in the Choosing Wisely recommendations:

1. Pneumococcal vaccination with the 23 polyvalent vaccine in adults
2. Chest X-ray after bronchoscopy or needle biopsy in the absence of symptoms
3. Routine use of heparin for deep venous thrombosis prophylaxis 
4. Routine chest X-ray in the absence of clinical suspicion of intrathoracic pathology
5. Pulmonary consultation for bronchoscopy for nonobstructive atelectasis
6. Ordering blood troponin levels in the absence of a clinical suspicion of myocardial infarction
7. Admission of a patient to the ICU who has chosen not to be resuscitated (DNR) and without clear goals of what is be accomplished in the ICU
8. Provision of powered mobility devices where there is not a clear medical necessity. 
9. Diagnosis and management of  COPD without spirometry
10. Developing and calling guidelines “evidence-based” when they are opinion or developed from nonrandomized trials.

Overall, the Choosing Wisely recommendations are a welcome start provided they are put to the use intended by the ABIM and contributing organizations. These should be expanded by contributions from other specialty groups and societies, but only if the evidence basis for each recommendation is clearly stated and based on adequate trials. Efforts to use these recommendations to control physician practice by proxy for financial gain are unethical and should be prominently noted and publicized if found to occur.

Richard A. Robbins, MD

Allen R. Thomas, MD

References

1. http://choosingwisely.org/?page_id=13
2. http://www.nytimes.com/2012/04/04/health/doctor-panels-urge-fewer-routine-tests.html?_r=1&permid=67
3. Robbins RA, Gerkin R, Singarajah CU. Relationship between the Veterans Healthcare Administration hospital performance measures and outcomes. Southwest J Pulm Crit Care 2011;3:92-133.
4. Padrnos L, Bui T, Pattee JJ, Whitmore EJ, Iqbal M, Lee S, Singarajah CU, Robbins RA. Analysis of overall level of evidence behind the Institute of Healthcare Improvement ventilator-associated pneumonia guidelines. Southwest J Pulm Crit Care 2011;3:40-8.
5. Hurley J, Garciaorr R, Leudy H et al. Correlation of compliance with central line associated blood stream infection guidelines and outcomes: a review of the evidence. (Submitted)
6. http://www.abim.org/research/seminal-bibliography/certification.aspx

*The Southwest Journal of Pulmonary and Critical Care is the official publication of the Arizona Thoracic Society which is the Arizona state affiliate of the  American Thoracic Society.

The opinions expressed in this editorial are the opinions of the authors and not necessarily the opinions of the Southwest Journal of Pulmonary and Critical Care or the Arizona Thoracic Society.

Reference as: Robbins RA, Thomas AR. Will fewer tests improve healthcare or profits? Southwest J Pulm Crit Care 2012;4:111-3. (Click here for a PDF version of the editorial)

Identification of a Biomarker of Sleep Deficiency—Are We Tilting Windmills?

The amount of time spent asleep by adults in the United States and other developing countries is decreasing. It is estimated that over 40 years ago, adults slept in excess of 8 hours per night, but now sleep barely 7 hours per night (1) During this time frame, there has been a corresponding increase in obesity and diabetes mellitus which in part has been attributed to a reduction in time sleeping (2). In addition, sleep deficiency and other sleep disorders have been implicated as risk factors for hypertension, cardiovascular disease and cancer (3-5). Consequently, billions of excess health care dollars are spent on medical conditions associated with sleep deficiency or sleep disorders (6,7). Their impact also include substantial costs resulting from lost productivity as well as increased absenteeism, presenteeism and motor vehicle or industrial accidents (6,7).  Thus, sleep disorders and sleep deficiency are significant threats to public health and productivity in the United States and worldwide and no evidence of a decline is on the horizon. One barrier to reducing their impact is the difficulty in identifying on a societal and personal level the major consequence of sleep deficiency, sleepiness.

Despite the extraordinary progress made by sleep and circadian science in recent years, developing an accurate and easy to use biomarker for sleepiness and/or sleep deficiency has been elusive. Currently used objective assessments of sleepiness such as the multiple sleep latency test or the psychomotor vigilance test are either difficult to use outside the laboratory environment or do not evaluate all domains of sleep deficiency. Subjective assessments of sleepiness are unreliable because many individuals cannot recognize their impairment (8) and in some occupational scenarios (e.g., truck drivers, railroad engineers); there is personal incentive to deny its presence because of the fear of losing employment or income (9).

If developed, there would be several uses for a sleepiness or sleep deficiency biomarker. These include:

• Research: especially in field studies of the impact of sleep deficiency and/or sleepiness in both small and large size cohorts;
• Fitness for duty: in clinical and occupational settings (e.g., operating a motor vehicle, aircraft pilot) where objective assessment of sleepiness would be important in determining whether an individual could perform their job;
• Personal health: such testing might ultimately provide a means for an individual to determine his/her level of sleepiness and allow self adjustment of medication or positive airway pressure in the case of obstructive sleep apnea patients, analogous to currently used home glucose testing in persons with diabetes mellitus;
• Disease risk stratification: level of sleep deficiency might identify individuals with a greater likelihood of developing other medical conditions such as cardiovascular disease or diabetes.

In an attempt to “jumpstart” interest and research into developing a sleepiness or sleep deficiency biomarker, the Division of Sleep Medicine at Harvard Medical School hosted a conference on September 21-22, 2010 supported by the National Heart, Lung and Blood Institute and commercial entities entitled “Finding a Research Path for the Identification of Biomarkers of Sleepiness” (10). A number of prominent national and international speakers presented possible approaches to achieving this goal including behavioral, physiologic, genomic and proteomic solutions. This conference was followed by a panel discussion on this same topic at the annual Sleep 2011 international conference. Despite these high profile public discourses, there has been little progress in finding a sleepiness/sleep deficiency biomarker. A brief search of PubMed identified only one paper published since the conference directly relevant to this area (11).

Why has there been so little progress? I would propose the major reason is lack of a public “outcry”. Despite high profile incidences such as the crash of Colgan Air Flight #3407 (12) and the grounding of the Exxon Valdez (13), and a report from the Institute of Medicine (6) the general public has not adopted sleep issues as a major public health concern. In contrast, cancer, heart disease, obesity and diabetes, all of which may in part be consequences of sleep deficiency or a sleep disorder, are higher in the public consciousness. As a result, it is unlikely that funding initiatives such as a RFA on research into sleepiness or sleep deficiency biomarkers from the National Institutes of Health will be forthcoming.

What can be done? It should be the mission of all of us who are involved in sleep research and clinical Sleep Medicine to promote to the public the importance of sleep deficiency and sleep disorders in adversely impacting public health. Until there is a ground swell of public support, I fear attempts to identify biomarkers for sleepiness or sleep deficiency may be similar to “tilting at windmills.”

Stuart F. Quan, M.D.

Division of Sleep Medicine,

Brigham and Women’s Hospital and Harvard Medical School

401 Park Dr., 2^nd Floor East

Boston, MA 02215

Voice: 617-998-8842

Fax: 617-998-8823

Email: Stuart_Quan@hms.harvard.edu

References

1. McAllister EJ, Dhurandhar NV, Keith SW, et al. Ten putative contributors to the obesity epidemic. Crit Rev Food Sci Nutr 2009;49:868-913.
2. Spiegel K, Tasali E, Leproult R, Van Cauter E. Effects of poor and short sleep on glucose metabolism and obesity risk. Nat Rev Endocrinol 2009;5:253-261.
3. Budhiraja R, Sharief I, Quan SF. Sleep disordered breathing and hypertension. J Clin Sleep Med 2005; 1:401-4.
4. Kakizaki M, Kuriyama S, Sone T, et al. Sleep duration and the risk of breast cancer: the Ohsaki Cohort Study. Br J Cancer 2008; 99:1502-5.
5. Quan SF. Sleep Disturbances and their Relationship to Cardiovascular Disease. Am J Lifestyle Med 2009; 3:55s-59s.
6. Colten HR, Altevogt BM, Institute of Medicine. Committee on Sleep Medicine and Research. Sleep disorders and sleep deprivation: an unmet public health problem. Washington, DC: Institute of Medicine: National Academies Press, 2006; 404.
7. Anonymous. The Price of Fatigue: the surprising economic costs of unmanaged sleep apnea. 2010. https://sleep.med.harvard.edu/what-we-do/public-policy-research
8. Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol 2005;25:117-129.
9. Smith B, Phillips BA. Truckers drive their own assessment for obstructive sleep apnea: a collaborative approach to online self-assessment for obstructive sleep apnea. J Clin Sleep Med 2011;7:241-245.
10. Anonymous. Harvard Biomarkers of Sleepiness Conference. 2011. https://sleep.med.harvard.edu/what-we-do/biomarkers-conference
11. Goel N, Banks S, Lin L, Mignot E, Dinges DF. Catechol-O-methyltransferase Val158Met polymorphism associates with individual differences in sleep physiologic responses to chronic sleep loss. PLoS One 2011;6:e29283.
12. Anonymous. Colgan Air Flight 3407. 2012. http://en.wikipedia.org/wiki/Colgan_Air_Flight_3407#cite_note-ntsb.2Faar-10.2F01-20
13. Anonymous. Details about the Accident SPILL: The wreck of the Exxon Valdez Final Report, Alaska Oil Spill Commission. 1990. http://www.evostc.state.ak.us/facts/details.cfm

Reference as: Quan SF. Identification of a biomarker of sleep deficiency-Are we tilting windmills? Southwest J Pulm Crit Care 2012;4:58-60. (Click here for a PDF version of the editorial)