A 39‐year‐old woman presented to the emergency department (ED) with fever and headache. One to two weeks prior to presentation, she developed nightly fevers that gradually increased to as high as 39.4C. She subsequently developed generalized throbbing headaches, malaise, and diffuse body pain. The headache gradually worsened. The day prior to presentation, she developed photophobia, nausea, and vomiting. She also reported right scalp pain while combing her hair, difficulty emptying her bladder, and left buttock pain radiating down the leg. She denied rash, joint pain, visual changes, dysarthria, cough, chest pain, abdominal pain, or diarrhea.

Fever and headache can be explained by meningitis, encephalitis, or brain abscess. The combination is seen far more frequently, however, in patients with common systemic infections such as influenza. For either bacterial meningitis or influenza, a 2‐week course is prolonged and atypical. The progressive nature of the symptoms and photophobia suggest a chronic meningitis, and the development of nausea and vomiting, although nonspecific, is also consistent with elevated intracranial pressure. In a young woman, subacute fever and aches should prompt consideration of an autoimmune disorder such as systemic lupus erythematosus (SLE), although early central nervous system (CNS) involvement is atypical. Migraine headaches are characterized by light sensitivity, nausea, and vomiting and can be precipitated by a viral syndrome, but in this case, the headaches were present at the outset, and 2 weeks is too long for a migraine attack.

Pain while combing hair is not characteristic of the aforementioned syndromes. The scalp should be examined to confirm that there are no skin lesions associated with herpes zoster and no arterial prominence associated with temporal arteritis. She is young for the latter, which would otherwise be a suitable explanation for fever, headache, scalp tenderness, and visual complaints (usually impairment not photophobia).

Incomplete bladder emptying and left buttock pain suggest that there might be a concomitant lumbosacral myelopathy or radiculopathy. Some nonbacterial causes of meningitis such as cytomegalovirus (CMV), syphilis, and cancer simultaneously involve the CNS and peripheral nerve roots. It is also possible that the scalp tenderness associated with combing reflects a cervical sensory radiculopathy.

She had presented to the ED 2 and 4 days before the current (third) ED visit. Both times her main complaint was left buttock pain and left leg paresthesias. Although she had no skin lesions, she was diagnosed with prodromal herpes zoster in the S2 dermatomal distribution and was prescribed valacyclovir (to be started should eruptions develop, which never occurred).

She reported intermittent self‐limited fevers at 3‐ to 4‐week intervals during the prior 6 months; two fever episodes were accompanied by an influenza‐like illness, and one was associated with gastrointestinal symptoms. Her last fever prior to this evaluation was 6 weeks earlier when she was treated with azithromycin for suspected pneumonia at an outside facility.

Her past medical history included hypothyroidism, gastroesophageal reflux disease, diverticulitis, and gluten intolerance. Her medications included porcine (natural) thyroid, fish oil, ibuprofen, and acetaminophen. She lived in Michigan and traveled to the northeast United States (Maine, Cape Cod, New Hampshire, Connecticut, and Vermont) 7 months prior to this evaluation. She was married and had no pets at home. She denied any tobacco, alcohol, or illicit drug use.

Her illness now appears to be chronic, associated with fever, and multisystem (potentially involving the pulmonary and gastrointestinal tract). None of her medical problems would predispose her to subacute meningitis, myelopathy, or radiculopathy. Hypothyroidism raises the possibility of a concomitant autoimmune disorder which causes meningitis, such as SLE or Behet's disease. Sarcoidosis can cause chronic meningitis and neuropathy with concomitant lung and gastrointestinal involvement and rarely fever.

Residency in the upper Midwest increases exposure to chronic infections that rarely cause subacute meningitis such as histoplasmosis, blastomycosis, or human granulocytic anaplasmosis. Travel to the northeast United States 1 month before the onset of her symptoms raises the possibility of other endemic infections like Lyme disease, babesiosis, and tularemia, which may account for her recurrent fevers. Of these, Lyme is most likely to present as chronic meningitis with cranial neuropathy and radiculoneuropathy.

Although the diagnosis of pneumonia was made late in her 6‐month illness, its etiology and treatment may be relevant. If the recent pneumonia was viral, a subsequent viral meningitis may be manifesting now or may have triggered an autoimmune process, such as acute disseminated encephalomyelitis. Bacterial pneumonia is a common precursor to bacterial meningitis, and treatment with azithromycin for the pneumonia may have delayed the meningitis onset or muted its course; this should be taken into account when interpreting cerebrospinal fluid (CSF) culture results.

On physical examination, her temperature was 39.1C, blood pressure was 135/91 mm Hg, with pulse of 87 beats per minute, respiratory rate of 16 breaths per minute, and oxygenation saturation of 97% on room air. She appeared in distress and was covering her eyes. She was alert and oriented. She had photophobia and mild nuchal rigidity. Pupils were equal and reactive to light, but she could not tolerate the eye exam for papilledema. Lung, heart, and abdominal exam were normal. No cranial nerve abnormalities were noted, and muscle strength was 5/5 in all 4 extremities. She had decreased sensation to light touch with allodynia throughout her lower extremities in addition to the lateral portion of the right scalp, which was also tender to palpation. Deep tendon reflexes were 2+ and symmetric in her bilateral upper and lower extremities. She did not have joint swelling, edema, lymphadenopathy, or a rash.

Her fever, headache, nuchal rigidity and photophobia collectively suggest meningitis, which requires evaluation by a lumbar puncture. There is no rash that supports herpes zoster or SLE. She does not have signs of myelopathy that would explain the urinary complaints, but lower motor neuron involvement has not been excluded. The sensory abnormalities in the scalp and leg are consistent with a polyneuroradiculopathy. Anterior lateral scalp tenderness may signal trigeminal nerve involvement, whereas posterior scalp tenderness would localize to the upper cervical cord nerve roots. The contralateral distribution of the scalp and leg sensory deficits suggests a multifocal peripheral nervous system process rather than a single CNS lesion.

Initial laboratory data showed serum white blood cell count (WBC) of 12,000/mm³ (79% polymorphonuclear leukocytes). Hemoglobin was 14.2 g/dL, and platelets were 251,000/mm³. Electrolytes, renal function, and liver function were normal. Thyroid‐stimulating hormone, erythrocyte sedimentation rate, and C‐reactive protein were normal. Urinalysis was negative. Chest x‐ray was normal. Noncontrast head computed tomography (CT) was normal. The patient was unable to void; 500 mL of urine returned when catheterization was performed.

CSF WBC count was 1,280/mm³ (39% neutrophils and 49% lymphocytes). CSF total protein was 175 mg/dL, and glucose was 48 mg/dL; serum glucose was 104 mg/dL. Opening pressure was not recorded. Gram stain was negative. Ceftriaxone, vancomycin, ampicillin, and acyclovir were administered for presumed bacterial or viral meningitis. Magnetic resonance imaging (MRI) of the brain and spine showed diffuse leptomeningeal enhancement (Figure 1).

Figure 1

The urinary retention in the absence of myelopathic findings on exam or MRI suggests a sacral polyradiculoneuropathy. Diffuse leptomeningeal enhancement is consistent with many, if not all, causes of meningitis. The high WBC count, elevated protein, and low glucosecollectively signaling active inflammation in the CNSare highly compatible with bacterial meningitis, although the lymphocytic predominance and other clinical data point to nonbacterial etiologies. The negative Gram stain further lowers the probability of bacterial meningitis, but it has limited sensitivity, may be affected by recent antibiotics, and is typically negative with Listeria. Enterovirus, acute human immunodeficiency virus (HIV), and herpes viruses (eg, CMV or herpes simplex virus [HSV]) are important considerations, with the latter 2 causing associated polyneuroradiculopathy. Patients with genital HSV (not detected here) can have a concomitant sacral radiculitis leading to urinary retention.

Fungal and mycobacterial meningitis is a possibility (especially with the high protein), but the patient does not have the typical multisystem disease or immunosuppression that frequently accompanies those conditions when CNS disease is present. Autoimmune conditions like SLE, Behet's disease, and sarcoidosis remain important conditions, especially with the polyneuroradiculopathy or mononeuritis multiplex, which may reflect multifocal nerve infarction or invasion. Similarly, lymphomatous or carcinomatous meningitis should be considered, although an isolated manifestation in the CNS is unusual. Based on the multifocal neurologic deficits, I favor a viral, spirochete, or malignant etiology of her meningoencephalitis.

Despite ongoing broad spectrum antibiotics and supportive care, she became confused on hospital day 3 and developed anomia, agitation, and worsening headache. A repeat CT of the brain did not show any new abnormalities, but repeat lumbar puncture demonstrated elevated intracranial pressure (opening pressure of 47 cm water) with 427 WBC/mm³. Blood and CSF cultures remained negative.

Detailed questioning of the family revealed that she had been horseback riding 3 weeks prior to admission; there were no other livestock where she rode horses. In addition, the family reported that she and other family members routinely drank raw milk from a cow share program.

HIV antibody test was negative. Herpes simplex, varicella zoster, enteroviruses, and adenovirus CSF polymerase chain reaction (PCR) were negative. Cytomegalovirus and Epstein‐Barr virus PCR were negative in serum and CSF. Arbovirus, lymphocytic choriomeningitis, Coccidioides, Blastomyces, Histoplasma, Brucella, and Lyme serologies were negative. Cryptococcus neoformans antigen was negative in CSF. Serum QuantiFERON‐TB test was negative. Blood and CSF acid‐fast bacilli smears (and eventually mycobacterial cultures) were also negative. Her CSF flow cytometry and cytology were negative for lymphoma.

Unpasteurized milk conveys multiple infectious risks. Listeriosis is a food‐borne illness that can cause meningoencephalitis, but peripheral neuropathies are not characteristic. Brucellosis is usually characterized by severe bone pain, pancytopenia, and hepatosplenomegaly, which are absent. Infection with Mycobacterium bovis mimics Mycobacterium tuberculosis and can cause multisystem disease, typically involving the lung. Campylobacter infection is characterized by gastroenteritis, which has not been prominent.

Rhodococcus equi is a horse‐related pathogen which leads to pulmonary infections in immunocompromised hosts but not meningitis. Rather than focusing on horse exposure alone, however, it may be useful to consider her at risk for vector‐borne pathogens based on her time outdoors, such as Lyme disease (which can cause radiculopathy and encephalopathy), West Nile virus (although motor weakness rather than sensory symptoms is typical), or eastern equine encephalitis.

The absence of weight loss, cytopenias, lymphadenopathy, and organomegaly with the negative CSF cytology and flow cytometry makes lymphomatous meningitis unlikely. The case for an autoimmune disorder is not strong in the absence of joint pains, rash, or autoimmune serologies. In a young woman with unexplained encephalitis, antibodies to the N‐methyl‐D‐aspartate receptor should be assayed.

Although the CSF leukocytosis is declining, the elevated pressure and clinical deterioration signal that the disease process is not controlled. At this point I am uncertain as to the cause of her progressive meningoencephalitis with polyneuroradiculopathy. The latter feature makes me favor a viral or spirochete etiology.

On hospital day 4, Coxiella burnetii serologies were reported as positive (phase II immunoglobulin [Ig] G 1:256; phase II IgM <1:16; phase I IgG <1:16; phase I IgM <1:16) suggesting acute Q fever. Antibiotics were changed to intravenous doxycycline and ciprofloxacin. Her increased intracranial pressure was managed with serial lumbar punctures. The patient was discharged after 12 days of hospitalization taking oral doxycycline and ciprofloxacin. Her symptoms resolved over 10 weeks. No vegetations were seen on transesophageal echocardiogram. She had no evidence of chronic Q fever on repeat serologies.

I was not aware that Q fever causes meningitis or meningoencephalitis. However, I should have considered it in light of her indirect exposure to cows. It is possible that her pneumonia 6 weeks earlier represented acute Q fever, as pneumonia and hepatitis are among the most typical acute manifestations of this infection.

COMMENTARY

Hospitalists are commonly confronted by the combination of fever, headache, and confusion and are familiar with the diagnostic and therapeutic dilemmas related to prompt discrimination between CNS and non‐CNS processes, particularly infections. At the time of this patient's final ED presentation, her illness unambiguously localized to the CNS. As common and emergent conditions such as acute bacterial meningitis were excluded, the greatest challenge was finding the clue that could direct investigations into less common causes of meningoencephalitis.

The Infectious Disease Society of America has developed clinical practice guidelines for the diagnosis and management of encephalitis which highlight the importance of epidemiology and risk factor assessment.[1] This approach requires the clinician to examine potential clues and to go beyond initial associationsfor instance, not simply linking horseback riding to horse‐associated pathogens, but interpreting horseback riding as a proxy for outdoor exposure, which places her at risk for contact with mosquitos, which transmit West Nile virus or eastern equine encephalitis. Similarly, ingestion of raw milk, which is typically linked to Listeria monocytogenes, Brucella, and other pathogens prompted the infectious disease consultant to think more broadly and include livestock (cow)‐associated pathogens including C. burnetii.

Although involvement of the CNS is common in chronic Q fever endocarditis due to septic embolism, neurologic involvement in acute Q fever varies in prevalence (range of 1.7%22%).[2, 3, 4] The 3 major neurological syndromes of acute Q fever are (1) meningoencephalitis or encephalitis, (2) lymphocytic meningitis, and (3) peripheral neuropathy (myelitis, polyradiculoneuritis, or peripheral neuritis). CSF analysis usually shows mild pleocytosis with a predominance of lymphocytic cells; CSF protein elevation is variable, and glucose is usually normal. Neuroradiologic examination is usually normal, and there are no pathognomonic imaging abnormalities for Q fever meningoencephalitis.[2, 3] The mechanism by which C. burnetii causes neurologic injury and dysfunction is unknown.

The diagnosis of Q fever is usually established by serologic testing. In acute Q fever, antibodies to phase II antigen are higher than the phase I antibody titer. Phase II IgM antibodies are the first to appear, but then decline on average after week 8, often reaching undetectable levels 10 to 12 weeks after disease onset.[5] If this patient's pneumonia 6 weeks prior to this presentation was acute Q fever pneumonia, her IgM titers may have been declining by the time her neurologic illness developed. A false negative test result is also possible; immunofluorescence assays are more specific than sensitive in acute Q fever.[5]

Evaluating this case in isolation may raise some doubt as to the accuracy of the diagnosis as she did not have a 4‐fold rise in the phase II IgG titer and did not have a detectable phase II IgM. However, she was part of a cluster of individuals who regularly consumed raw milk from the same dairy and had evidence of C. burnetii infection. This group included her spouse, who had a robust serologic evidence of C. burnetii, characterized by a >4‐fold rise in phase II IgM and IgG titers.[6]

C. burnetii is found primarily in cattle, sheep, and goats and is shed in large quantities by infected periparturient animals in their urine, feces, and milk.[7] Inhalation of contaminated aerosols is the principal route of transmission.[7, 8] Acute Q fever is underdiagnosed because the majority of acute infections are asymptomatic (60%) or present as a nonspecific flu‐like illness.[7] This case represents a rare manifestation of a rare infection acquired through a rare route of transmission, but highlights the importance of epidemiology and risk factor assessment when clinicians are faced with a diagnostic challenge.

TEACHING POINTS

• Exploration of epidemiology and exposure history is central to diagnosing meningoencephalitis with negative bacterial cultures and undetectable HSV PCR, although the etiology of meningoencephalitis can elude identification even after exhaustive investigation.
• Inhalation of contaminated aerosols is the principal route of transmission for C. burnetii, but it can also be transmitted via infected unpasteurized milk.[7, 9]
• Acute presentations of Q fever, which may warrant admission, include pneumonia, hepatitis, or meningoencephalitis.
• Q fever is diagnosed by serologic testing, and doxycycline is the antibiotic of choice.

Disclosures

This case was presented at the 2012 Annual Meeting of the Society of Hospital Medicine. It was subsequently reported in the epidemiologic report of the outbreak.[6] The authors report no conflicts of interest.

A 39‐year‐old woman presented to the emergency department (ED) with fever and headache. One to two weeks prior to presentation, she developed nightly fevers that gradually increased to as high as 39.4C. She subsequently developed generalized throbbing headaches, malaise, and diffuse body pain. The headache gradually worsened. The day prior to presentation, she developed photophobia, nausea, and vomiting. She also reported right scalp pain while combing her hair, difficulty emptying her bladder, and left buttock pain radiating down the leg. She denied rash, joint pain, visual changes, dysarthria, cough, chest pain, abdominal pain, or diarrhea.

Fever and headache can be explained by meningitis, encephalitis, or brain abscess. The combination is seen far more frequently, however, in patients with common systemic infections such as influenza. For either bacterial meningitis or influenza, a 2‐week course is prolonged and atypical. The progressive nature of the symptoms and photophobia suggest a chronic meningitis, and the development of nausea and vomiting, although nonspecific, is also consistent with elevated intracranial pressure. In a young woman, subacute fever and aches should prompt consideration of an autoimmune disorder such as systemic lupus erythematosus (SLE), although early central nervous system (CNS) involvement is atypical. Migraine headaches are characterized by light sensitivity, nausea, and vomiting and can be precipitated by a viral syndrome, but in this case, the headaches were present at the outset, and 2 weeks is too long for a migraine attack.

Pain while combing hair is not characteristic of the aforementioned syndromes. The scalp should be examined to confirm that there are no skin lesions associated with herpes zoster and no arterial prominence associated with temporal arteritis. She is young for the latter, which would otherwise be a suitable explanation for fever, headache, scalp tenderness, and visual complaints (usually impairment not photophobia).

Incomplete bladder emptying and left buttock pain suggest that there might be a concomitant lumbosacral myelopathy or radiculopathy. Some nonbacterial causes of meningitis such as cytomegalovirus (CMV), syphilis, and cancer simultaneously involve the CNS and peripheral nerve roots. It is also possible that the scalp tenderness associated with combing reflects a cervical sensory radiculopathy.

She had presented to the ED 2 and 4 days before the current (third) ED visit. Both times her main complaint was left buttock pain and left leg paresthesias. Although she had no skin lesions, she was diagnosed with prodromal herpes zoster in the S2 dermatomal distribution and was prescribed valacyclovir (to be started should eruptions develop, which never occurred).

She reported intermittent self‐limited fevers at 3‐ to 4‐week intervals during the prior 6 months; two fever episodes were accompanied by an influenza‐like illness, and one was associated with gastrointestinal symptoms. Her last fever prior to this evaluation was 6 weeks earlier when she was treated with azithromycin for suspected pneumonia at an outside facility.

Her past medical history included hypothyroidism, gastroesophageal reflux disease, diverticulitis, and gluten intolerance. Her medications included porcine (natural) thyroid, fish oil, ibuprofen, and acetaminophen. She lived in Michigan and traveled to the northeast United States (Maine, Cape Cod, New Hampshire, Connecticut, and Vermont) 7 months prior to this evaluation. She was married and had no pets at home. She denied any tobacco, alcohol, or illicit drug use.

Her illness now appears to be chronic, associated with fever, and multisystem (potentially involving the pulmonary and gastrointestinal tract). None of her medical problems would predispose her to subacute meningitis, myelopathy, or radiculopathy. Hypothyroidism raises the possibility of a concomitant autoimmune disorder which causes meningitis, such as SLE or Behet's disease. Sarcoidosis can cause chronic meningitis and neuropathy with concomitant lung and gastrointestinal involvement and rarely fever.

Residency in the upper Midwest increases exposure to chronic infections that rarely cause subacute meningitis such as histoplasmosis, blastomycosis, or human granulocytic anaplasmosis. Travel to the northeast United States 1 month before the onset of her symptoms raises the possibility of other endemic infections like Lyme disease, babesiosis, and tularemia, which may account for her recurrent fevers. Of these, Lyme is most likely to present as chronic meningitis with cranial neuropathy and radiculoneuropathy.

Although the diagnosis of pneumonia was made late in her 6‐month illness, its etiology and treatment may be relevant. If the recent pneumonia was viral, a subsequent viral meningitis may be manifesting now or may have triggered an autoimmune process, such as acute disseminated encephalomyelitis. Bacterial pneumonia is a common precursor to bacterial meningitis, and treatment with azithromycin for the pneumonia may have delayed the meningitis onset or muted its course; this should be taken into account when interpreting cerebrospinal fluid (CSF) culture results.

On physical examination, her temperature was 39.1C, blood pressure was 135/91 mm Hg, with pulse of 87 beats per minute, respiratory rate of 16 breaths per minute, and oxygenation saturation of 97% on room air. She appeared in distress and was covering her eyes. She was alert and oriented. She had photophobia and mild nuchal rigidity. Pupils were equal and reactive to light, but she could not tolerate the eye exam for papilledema. Lung, heart, and abdominal exam were normal. No cranial nerve abnormalities were noted, and muscle strength was 5/5 in all 4 extremities. She had decreased sensation to light touch with allodynia throughout her lower extremities in addition to the lateral portion of the right scalp, which was also tender to palpation. Deep tendon reflexes were 2+ and symmetric in her bilateral upper and lower extremities. She did not have joint swelling, edema, lymphadenopathy, or a rash.

Her fever, headache, nuchal rigidity and photophobia collectively suggest meningitis, which requires evaluation by a lumbar puncture. There is no rash that supports herpes zoster or SLE. She does not have signs of myelopathy that would explain the urinary complaints, but lower motor neuron involvement has not been excluded. The sensory abnormalities in the scalp and leg are consistent with a polyneuroradiculopathy. Anterior lateral scalp tenderness may signal trigeminal nerve involvement, whereas posterior scalp tenderness would localize to the upper cervical cord nerve roots. The contralateral distribution of the scalp and leg sensory deficits suggests a multifocal peripheral nervous system process rather than a single CNS lesion.

Initial laboratory data showed serum white blood cell count (WBC) of 12,000/mm³ (79% polymorphonuclear leukocytes). Hemoglobin was 14.2 g/dL, and platelets were 251,000/mm³. Electrolytes, renal function, and liver function were normal. Thyroid‐stimulating hormone, erythrocyte sedimentation rate, and C‐reactive protein were normal. Urinalysis was negative. Chest x‐ray was normal. Noncontrast head computed tomography (CT) was normal. The patient was unable to void; 500 mL of urine returned when catheterization was performed.

CSF WBC count was 1,280/mm³ (39% neutrophils and 49% lymphocytes). CSF total protein was 175 mg/dL, and glucose was 48 mg/dL; serum glucose was 104 mg/dL. Opening pressure was not recorded. Gram stain was negative. Ceftriaxone, vancomycin, ampicillin, and acyclovir were administered for presumed bacterial or viral meningitis. Magnetic resonance imaging (MRI) of the brain and spine showed diffuse leptomeningeal enhancement (Figure 1).

Figure 1

The urinary retention in the absence of myelopathic findings on exam or MRI suggests a sacral polyradiculoneuropathy. Diffuse leptomeningeal enhancement is consistent with many, if not all, causes of meningitis. The high WBC count, elevated protein, and low glucosecollectively signaling active inflammation in the CNSare highly compatible with bacterial meningitis, although the lymphocytic predominance and other clinical data point to nonbacterial etiologies. The negative Gram stain further lowers the probability of bacterial meningitis, but it has limited sensitivity, may be affected by recent antibiotics, and is typically negative with Listeria. Enterovirus, acute human immunodeficiency virus (HIV), and herpes viruses (eg, CMV or herpes simplex virus [HSV]) are important considerations, with the latter 2 causing associated polyneuroradiculopathy. Patients with genital HSV (not detected here) can have a concomitant sacral radiculitis leading to urinary retention.

Fungal and mycobacterial meningitis is a possibility (especially with the high protein), but the patient does not have the typical multisystem disease or immunosuppression that frequently accompanies those conditions when CNS disease is present. Autoimmune conditions like SLE, Behet's disease, and sarcoidosis remain important conditions, especially with the polyneuroradiculopathy or mononeuritis multiplex, which may reflect multifocal nerve infarction or invasion. Similarly, lymphomatous or carcinomatous meningitis should be considered, although an isolated manifestation in the CNS is unusual. Based on the multifocal neurologic deficits, I favor a viral, spirochete, or malignant etiology of her meningoencephalitis.

Despite ongoing broad spectrum antibiotics and supportive care, she became confused on hospital day 3 and developed anomia, agitation, and worsening headache. A repeat CT of the brain did not show any new abnormalities, but repeat lumbar puncture demonstrated elevated intracranial pressure (opening pressure of 47 cm water) with 427 WBC/mm³. Blood and CSF cultures remained negative.

Detailed questioning of the family revealed that she had been horseback riding 3 weeks prior to admission; there were no other livestock where she rode horses. In addition, the family reported that she and other family members routinely drank raw milk from a cow share program.

HIV antibody test was negative. Herpes simplex, varicella zoster, enteroviruses, and adenovirus CSF polymerase chain reaction (PCR) were negative. Cytomegalovirus and Epstein‐Barr virus PCR were negative in serum and CSF. Arbovirus, lymphocytic choriomeningitis, Coccidioides, Blastomyces, Histoplasma, Brucella, and Lyme serologies were negative. Cryptococcus neoformans antigen was negative in CSF. Serum QuantiFERON‐TB test was negative. Blood and CSF acid‐fast bacilli smears (and eventually mycobacterial cultures) were also negative. Her CSF flow cytometry and cytology were negative for lymphoma.

Unpasteurized milk conveys multiple infectious risks. Listeriosis is a food‐borne illness that can cause meningoencephalitis, but peripheral neuropathies are not characteristic. Brucellosis is usually characterized by severe bone pain, pancytopenia, and hepatosplenomegaly, which are absent. Infection with Mycobacterium bovis mimics Mycobacterium tuberculosis and can cause multisystem disease, typically involving the lung. Campylobacter infection is characterized by gastroenteritis, which has not been prominent.

Rhodococcus equi is a horse‐related pathogen which leads to pulmonary infections in immunocompromised hosts but not meningitis. Rather than focusing on horse exposure alone, however, it may be useful to consider her at risk for vector‐borne pathogens based on her time outdoors, such as Lyme disease (which can cause radiculopathy and encephalopathy), West Nile virus (although motor weakness rather than sensory symptoms is typical), or eastern equine encephalitis.

The absence of weight loss, cytopenias, lymphadenopathy, and organomegaly with the negative CSF cytology and flow cytometry makes lymphomatous meningitis unlikely. The case for an autoimmune disorder is not strong in the absence of joint pains, rash, or autoimmune serologies. In a young woman with unexplained encephalitis, antibodies to the N‐methyl‐D‐aspartate receptor should be assayed.

Although the CSF leukocytosis is declining, the elevated pressure and clinical deterioration signal that the disease process is not controlled. At this point I am uncertain as to the cause of her progressive meningoencephalitis with polyneuroradiculopathy. The latter feature makes me favor a viral or spirochete etiology.

On hospital day 4, Coxiella burnetii serologies were reported as positive (phase II immunoglobulin [Ig] G 1:256; phase II IgM <1:16; phase I IgG <1:16; phase I IgM <1:16) suggesting acute Q fever. Antibiotics were changed to intravenous doxycycline and ciprofloxacin. Her increased intracranial pressure was managed with serial lumbar punctures. The patient was discharged after 12 days of hospitalization taking oral doxycycline and ciprofloxacin. Her symptoms resolved over 10 weeks. No vegetations were seen on transesophageal echocardiogram. She had no evidence of chronic Q fever on repeat serologies.

I was not aware that Q fever causes meningitis or meningoencephalitis. However, I should have considered it in light of her indirect exposure to cows. It is possible that her pneumonia 6 weeks earlier represented acute Q fever, as pneumonia and hepatitis are among the most typical acute manifestations of this infection.

COMMENTARY

Hospitalists are commonly confronted by the combination of fever, headache, and confusion and are familiar with the diagnostic and therapeutic dilemmas related to prompt discrimination between CNS and non‐CNS processes, particularly infections. At the time of this patient's final ED presentation, her illness unambiguously localized to the CNS. As common and emergent conditions such as acute bacterial meningitis were excluded, the greatest challenge was finding the clue that could direct investigations into less common causes of meningoencephalitis.

The Infectious Disease Society of America has developed clinical practice guidelines for the diagnosis and management of encephalitis which highlight the importance of epidemiology and risk factor assessment.[1] This approach requires the clinician to examine potential clues and to go beyond initial associationsfor instance, not simply linking horseback riding to horse‐associated pathogens, but interpreting horseback riding as a proxy for outdoor exposure, which places her at risk for contact with mosquitos, which transmit West Nile virus or eastern equine encephalitis. Similarly, ingestion of raw milk, which is typically linked to Listeria monocytogenes, Brucella, and other pathogens prompted the infectious disease consultant to think more broadly and include livestock (cow)‐associated pathogens including C. burnetii.

Although involvement of the CNS is common in chronic Q fever endocarditis due to septic embolism, neurologic involvement in acute Q fever varies in prevalence (range of 1.7%22%).[2, 3, 4] The 3 major neurological syndromes of acute Q fever are (1) meningoencephalitis or encephalitis, (2) lymphocytic meningitis, and (3) peripheral neuropathy (myelitis, polyradiculoneuritis, or peripheral neuritis). CSF analysis usually shows mild pleocytosis with a predominance of lymphocytic cells; CSF protein elevation is variable, and glucose is usually normal. Neuroradiologic examination is usually normal, and there are no pathognomonic imaging abnormalities for Q fever meningoencephalitis.[2, 3] The mechanism by which C. burnetii causes neurologic injury and dysfunction is unknown.

The diagnosis of Q fever is usually established by serologic testing. In acute Q fever, antibodies to phase II antigen are higher than the phase I antibody titer. Phase II IgM antibodies are the first to appear, but then decline on average after week 8, often reaching undetectable levels 10 to 12 weeks after disease onset.[5] If this patient's pneumonia 6 weeks prior to this presentation was acute Q fever pneumonia, her IgM titers may have been declining by the time her neurologic illness developed. A false negative test result is also possible; immunofluorescence assays are more specific than sensitive in acute Q fever.[5]

Evaluating this case in isolation may raise some doubt as to the accuracy of the diagnosis as she did not have a 4‐fold rise in the phase II IgG titer and did not have a detectable phase II IgM. However, she was part of a cluster of individuals who regularly consumed raw milk from the same dairy and had evidence of C. burnetii infection. This group included her spouse, who had a robust serologic evidence of C. burnetii, characterized by a >4‐fold rise in phase II IgM and IgG titers.[6]

C. burnetii is found primarily in cattle, sheep, and goats and is shed in large quantities by infected periparturient animals in their urine, feces, and milk.[7] Inhalation of contaminated aerosols is the principal route of transmission.[7, 8] Acute Q fever is underdiagnosed because the majority of acute infections are asymptomatic (60%) or present as a nonspecific flu‐like illness.[7] This case represents a rare manifestation of a rare infection acquired through a rare route of transmission, but highlights the importance of epidemiology and risk factor assessment when clinicians are faced with a diagnostic challenge.

TEACHING POINTS

• Exploration of epidemiology and exposure history is central to diagnosing meningoencephalitis with negative bacterial cultures and undetectable HSV PCR, although the etiology of meningoencephalitis can elude identification even after exhaustive investigation.
• Inhalation of contaminated aerosols is the principal route of transmission for C. burnetii, but it can also be transmitted via infected unpasteurized milk.[7, 9]
• Acute presentations of Q fever, which may warrant admission, include pneumonia, hepatitis, or meningoencephalitis.
• Q fever is diagnosed by serologic testing, and doxycycline is the antibiotic of choice.

Disclosures

This case was presented at the 2012 Annual Meeting of the Society of Hospital Medicine. It was subsequently reported in the epidemiologic report of the outbreak.[6] The authors report no conflicts of interest.

A 39‐year‐old woman presented to the emergency department (ED) with fever and headache. One to two weeks prior to presentation, she developed nightly fevers that gradually increased to as high as 39.4C. She subsequently developed generalized throbbing headaches, malaise, and diffuse body pain. The headache gradually worsened. The day prior to presentation, she developed photophobia, nausea, and vomiting. She also reported right scalp pain while combing her hair, difficulty emptying her bladder, and left buttock pain radiating down the leg. She denied rash, joint pain, visual changes, dysarthria, cough, chest pain, abdominal pain, or diarrhea.

Fever and headache can be explained by meningitis, encephalitis, or brain abscess. The combination is seen far more frequently, however, in patients with common systemic infections such as influenza. For either bacterial meningitis or influenza, a 2‐week course is prolonged and atypical. The progressive nature of the symptoms and photophobia suggest a chronic meningitis, and the development of nausea and vomiting, although nonspecific, is also consistent with elevated intracranial pressure. In a young woman, subacute fever and aches should prompt consideration of an autoimmune disorder such as systemic lupus erythematosus (SLE), although early central nervous system (CNS) involvement is atypical. Migraine headaches are characterized by light sensitivity, nausea, and vomiting and can be precipitated by a viral syndrome, but in this case, the headaches were present at the outset, and 2 weeks is too long for a migraine attack.

Pain while combing hair is not characteristic of the aforementioned syndromes. The scalp should be examined to confirm that there are no skin lesions associated with herpes zoster and no arterial prominence associated with temporal arteritis. She is young for the latter, which would otherwise be a suitable explanation for fever, headache, scalp tenderness, and visual complaints (usually impairment not photophobia).

Incomplete bladder emptying and left buttock pain suggest that there might be a concomitant lumbosacral myelopathy or radiculopathy. Some nonbacterial causes of meningitis such as cytomegalovirus (CMV), syphilis, and cancer simultaneously involve the CNS and peripheral nerve roots. It is also possible that the scalp tenderness associated with combing reflects a cervical sensory radiculopathy.

She had presented to the ED 2 and 4 days before the current (third) ED visit. Both times her main complaint was left buttock pain and left leg paresthesias. Although she had no skin lesions, she was diagnosed with prodromal herpes zoster in the S2 dermatomal distribution and was prescribed valacyclovir (to be started should eruptions develop, which never occurred).

She reported intermittent self‐limited fevers at 3‐ to 4‐week intervals during the prior 6 months; two fever episodes were accompanied by an influenza‐like illness, and one was associated with gastrointestinal symptoms. Her last fever prior to this evaluation was 6 weeks earlier when she was treated with azithromycin for suspected pneumonia at an outside facility.

Her past medical history included hypothyroidism, gastroesophageal reflux disease, diverticulitis, and gluten intolerance. Her medications included porcine (natural) thyroid, fish oil, ibuprofen, and acetaminophen. She lived in Michigan and traveled to the northeast United States (Maine, Cape Cod, New Hampshire, Connecticut, and Vermont) 7 months prior to this evaluation. She was married and had no pets at home. She denied any tobacco, alcohol, or illicit drug use.

Her illness now appears to be chronic, associated with fever, and multisystem (potentially involving the pulmonary and gastrointestinal tract). None of her medical problems would predispose her to subacute meningitis, myelopathy, or radiculopathy. Hypothyroidism raises the possibility of a concomitant autoimmune disorder which causes meningitis, such as SLE or Behet's disease. Sarcoidosis can cause chronic meningitis and neuropathy with concomitant lung and gastrointestinal involvement and rarely fever.

Residency in the upper Midwest increases exposure to chronic infections that rarely cause subacute meningitis such as histoplasmosis, blastomycosis, or human granulocytic anaplasmosis. Travel to the northeast United States 1 month before the onset of her symptoms raises the possibility of other endemic infections like Lyme disease, babesiosis, and tularemia, which may account for her recurrent fevers. Of these, Lyme is most likely to present as chronic meningitis with cranial neuropathy and radiculoneuropathy.

Although the diagnosis of pneumonia was made late in her 6‐month illness, its etiology and treatment may be relevant. If the recent pneumonia was viral, a subsequent viral meningitis may be manifesting now or may have triggered an autoimmune process, such as acute disseminated encephalomyelitis. Bacterial pneumonia is a common precursor to bacterial meningitis, and treatment with azithromycin for the pneumonia may have delayed the meningitis onset or muted its course; this should be taken into account when interpreting cerebrospinal fluid (CSF) culture results.

On physical examination, her temperature was 39.1C, blood pressure was 135/91 mm Hg, with pulse of 87 beats per minute, respiratory rate of 16 breaths per minute, and oxygenation saturation of 97% on room air. She appeared in distress and was covering her eyes. She was alert and oriented. She had photophobia and mild nuchal rigidity. Pupils were equal and reactive to light, but she could not tolerate the eye exam for papilledema. Lung, heart, and abdominal exam were normal. No cranial nerve abnormalities were noted, and muscle strength was 5/5 in all 4 extremities. She had decreased sensation to light touch with allodynia throughout her lower extremities in addition to the lateral portion of the right scalp, which was also tender to palpation. Deep tendon reflexes were 2+ and symmetric in her bilateral upper and lower extremities. She did not have joint swelling, edema, lymphadenopathy, or a rash.

Her fever, headache, nuchal rigidity and photophobia collectively suggest meningitis, which requires evaluation by a lumbar puncture. There is no rash that supports herpes zoster or SLE. She does not have signs of myelopathy that would explain the urinary complaints, but lower motor neuron involvement has not been excluded. The sensory abnormalities in the scalp and leg are consistent with a polyneuroradiculopathy. Anterior lateral scalp tenderness may signal trigeminal nerve involvement, whereas posterior scalp tenderness would localize to the upper cervical cord nerve roots. The contralateral distribution of the scalp and leg sensory deficits suggests a multifocal peripheral nervous system process rather than a single CNS lesion.

Initial laboratory data showed serum white blood cell count (WBC) of 12,000/mm³ (79% polymorphonuclear leukocytes). Hemoglobin was 14.2 g/dL, and platelets were 251,000/mm³. Electrolytes, renal function, and liver function were normal. Thyroid‐stimulating hormone, erythrocyte sedimentation rate, and C‐reactive protein were normal. Urinalysis was negative. Chest x‐ray was normal. Noncontrast head computed tomography (CT) was normal. The patient was unable to void; 500 mL of urine returned when catheterization was performed.

CSF WBC count was 1,280/mm³ (39% neutrophils and 49% lymphocytes). CSF total protein was 175 mg/dL, and glucose was 48 mg/dL; serum glucose was 104 mg/dL. Opening pressure was not recorded. Gram stain was negative. Ceftriaxone, vancomycin, ampicillin, and acyclovir were administered for presumed bacterial or viral meningitis. Magnetic resonance imaging (MRI) of the brain and spine showed diffuse leptomeningeal enhancement (Figure 1).

Figure 1

The urinary retention in the absence of myelopathic findings on exam or MRI suggests a sacral polyradiculoneuropathy. Diffuse leptomeningeal enhancement is consistent with many, if not all, causes of meningitis. The high WBC count, elevated protein, and low glucosecollectively signaling active inflammation in the CNSare highly compatible with bacterial meningitis, although the lymphocytic predominance and other clinical data point to nonbacterial etiologies. The negative Gram stain further lowers the probability of bacterial meningitis, but it has limited sensitivity, may be affected by recent antibiotics, and is typically negative with Listeria. Enterovirus, acute human immunodeficiency virus (HIV), and herpes viruses (eg, CMV or herpes simplex virus [HSV]) are important considerations, with the latter 2 causing associated polyneuroradiculopathy. Patients with genital HSV (not detected here) can have a concomitant sacral radiculitis leading to urinary retention.

Fungal and mycobacterial meningitis is a possibility (especially with the high protein), but the patient does not have the typical multisystem disease or immunosuppression that frequently accompanies those conditions when CNS disease is present. Autoimmune conditions like SLE, Behet's disease, and sarcoidosis remain important conditions, especially with the polyneuroradiculopathy or mononeuritis multiplex, which may reflect multifocal nerve infarction or invasion. Similarly, lymphomatous or carcinomatous meningitis should be considered, although an isolated manifestation in the CNS is unusual. Based on the multifocal neurologic deficits, I favor a viral, spirochete, or malignant etiology of her meningoencephalitis.

Despite ongoing broad spectrum antibiotics and supportive care, she became confused on hospital day 3 and developed anomia, agitation, and worsening headache. A repeat CT of the brain did not show any new abnormalities, but repeat lumbar puncture demonstrated elevated intracranial pressure (opening pressure of 47 cm water) with 427 WBC/mm³. Blood and CSF cultures remained negative.

Detailed questioning of the family revealed that she had been horseback riding 3 weeks prior to admission; there were no other livestock where she rode horses. In addition, the family reported that she and other family members routinely drank raw milk from a cow share program.

HIV antibody test was negative. Herpes simplex, varicella zoster, enteroviruses, and adenovirus CSF polymerase chain reaction (PCR) were negative. Cytomegalovirus and Epstein‐Barr virus PCR were negative in serum and CSF. Arbovirus, lymphocytic choriomeningitis, Coccidioides, Blastomyces, Histoplasma, Brucella, and Lyme serologies were negative. Cryptococcus neoformans antigen was negative in CSF. Serum QuantiFERON‐TB test was negative. Blood and CSF acid‐fast bacilli smears (and eventually mycobacterial cultures) were also negative. Her CSF flow cytometry and cytology were negative for lymphoma.

Unpasteurized milk conveys multiple infectious risks. Listeriosis is a food‐borne illness that can cause meningoencephalitis, but peripheral neuropathies are not characteristic. Brucellosis is usually characterized by severe bone pain, pancytopenia, and hepatosplenomegaly, which are absent. Infection with Mycobacterium bovis mimics Mycobacterium tuberculosis and can cause multisystem disease, typically involving the lung. Campylobacter infection is characterized by gastroenteritis, which has not been prominent.

Rhodococcus equi is a horse‐related pathogen which leads to pulmonary infections in immunocompromised hosts but not meningitis. Rather than focusing on horse exposure alone, however, it may be useful to consider her at risk for vector‐borne pathogens based on her time outdoors, such as Lyme disease (which can cause radiculopathy and encephalopathy), West Nile virus (although motor weakness rather than sensory symptoms is typical), or eastern equine encephalitis.

The absence of weight loss, cytopenias, lymphadenopathy, and organomegaly with the negative CSF cytology and flow cytometry makes lymphomatous meningitis unlikely. The case for an autoimmune disorder is not strong in the absence of joint pains, rash, or autoimmune serologies. In a young woman with unexplained encephalitis, antibodies to the N‐methyl‐D‐aspartate receptor should be assayed.

Although the CSF leukocytosis is declining, the elevated pressure and clinical deterioration signal that the disease process is not controlled. At this point I am uncertain as to the cause of her progressive meningoencephalitis with polyneuroradiculopathy. The latter feature makes me favor a viral or spirochete etiology.

On hospital day 4, Coxiella burnetii serologies were reported as positive (phase II immunoglobulin [Ig] G 1:256; phase II IgM <1:16; phase I IgG <1:16; phase I IgM <1:16) suggesting acute Q fever. Antibiotics were changed to intravenous doxycycline and ciprofloxacin. Her increased intracranial pressure was managed with serial lumbar punctures. The patient was discharged after 12 days of hospitalization taking oral doxycycline and ciprofloxacin. Her symptoms resolved over 10 weeks. No vegetations were seen on transesophageal echocardiogram. She had no evidence of chronic Q fever on repeat serologies.

I was not aware that Q fever causes meningitis or meningoencephalitis. However, I should have considered it in light of her indirect exposure to cows. It is possible that her pneumonia 6 weeks earlier represented acute Q fever, as pneumonia and hepatitis are among the most typical acute manifestations of this infection.

COMMENTARY

Hospitalists are commonly confronted by the combination of fever, headache, and confusion and are familiar with the diagnostic and therapeutic dilemmas related to prompt discrimination between CNS and non‐CNS processes, particularly infections. At the time of this patient's final ED presentation, her illness unambiguously localized to the CNS. As common and emergent conditions such as acute bacterial meningitis were excluded, the greatest challenge was finding the clue that could direct investigations into less common causes of meningoencephalitis.

The Infectious Disease Society of America has developed clinical practice guidelines for the diagnosis and management of encephalitis which highlight the importance of epidemiology and risk factor assessment.[1] This approach requires the clinician to examine potential clues and to go beyond initial associationsfor instance, not simply linking horseback riding to horse‐associated pathogens, but interpreting horseback riding as a proxy for outdoor exposure, which places her at risk for contact with mosquitos, which transmit West Nile virus or eastern equine encephalitis. Similarly, ingestion of raw milk, which is typically linked to Listeria monocytogenes, Brucella, and other pathogens prompted the infectious disease consultant to think more broadly and include livestock (cow)‐associated pathogens including C. burnetii.

Although involvement of the CNS is common in chronic Q fever endocarditis due to septic embolism, neurologic involvement in acute Q fever varies in prevalence (range of 1.7%22%).[2, 3, 4] The 3 major neurological syndromes of acute Q fever are (1) meningoencephalitis or encephalitis, (2) lymphocytic meningitis, and (3) peripheral neuropathy (myelitis, polyradiculoneuritis, or peripheral neuritis). CSF analysis usually shows mild pleocytosis with a predominance of lymphocytic cells; CSF protein elevation is variable, and glucose is usually normal. Neuroradiologic examination is usually normal, and there are no pathognomonic imaging abnormalities for Q fever meningoencephalitis.[2, 3] The mechanism by which C. burnetii causes neurologic injury and dysfunction is unknown.

The diagnosis of Q fever is usually established by serologic testing. In acute Q fever, antibodies to phase II antigen are higher than the phase I antibody titer. Phase II IgM antibodies are the first to appear, but then decline on average after week 8, often reaching undetectable levels 10 to 12 weeks after disease onset.[5] If this patient's pneumonia 6 weeks prior to this presentation was acute Q fever pneumonia, her IgM titers may have been declining by the time her neurologic illness developed. A false negative test result is also possible; immunofluorescence assays are more specific than sensitive in acute Q fever.[5]

Evaluating this case in isolation may raise some doubt as to the accuracy of the diagnosis as she did not have a 4‐fold rise in the phase II IgG titer and did not have a detectable phase II IgM. However, she was part of a cluster of individuals who regularly consumed raw milk from the same dairy and had evidence of C. burnetii infection. This group included her spouse, who had a robust serologic evidence of C. burnetii, characterized by a >4‐fold rise in phase II IgM and IgG titers.[6]

C. burnetii is found primarily in cattle, sheep, and goats and is shed in large quantities by infected periparturient animals in their urine, feces, and milk.[7] Inhalation of contaminated aerosols is the principal route of transmission.[7, 8] Acute Q fever is underdiagnosed because the majority of acute infections are asymptomatic (60%) or present as a nonspecific flu‐like illness.[7] This case represents a rare manifestation of a rare infection acquired through a rare route of transmission, but highlights the importance of epidemiology and risk factor assessment when clinicians are faced with a diagnostic challenge.

TEACHING POINTS

• Exploration of epidemiology and exposure history is central to diagnosing meningoencephalitis with negative bacterial cultures and undetectable HSV PCR, although the etiology of meningoencephalitis can elude identification even after exhaustive investigation.
• Inhalation of contaminated aerosols is the principal route of transmission for C. burnetii, but it can also be transmitted via infected unpasteurized milk.[7, 9]
• Acute presentations of Q fever, which may warrant admission, include pneumonia, hepatitis, or meningoencephalitis.
• Q fever is diagnosed by serologic testing, and doxycycline is the antibiotic of choice.

Disclosures

This case was presented at the 2012 Annual Meeting of the Society of Hospital Medicine. It was subsequently reported in the epidemiologic report of the outbreak.[6] The authors report no conflicts of interest.

Although hospital readmissions have been a problem for at least the past 5 decades, they are now receiving more attention than ever before. Starting with the 2007 Medicare Payment Advisory Commission report detailing the vast scope of the problem,[1] readmissions have garnered substantial policy interest, culminating with Congress' inclusion of a penalty for hospitals with excessive readmission rates in the Affordable Care Act. Clinical leaders have become increasingly active in this issue as well, and hospitals around the nation have become engaged in finding ways to reduce the number of times patients return after discharge.

The Hospital Readmissions Reduction Program (HRRP), which is the penalty program put in place by Congress to address readmissions, has been controversial from its inception. Supporters point to the large number of patients whose discharge is fraught with poor communication, ineffective medication management, and inadequate handoffs to the primary care physician. Critics have countered that only a small proportion of readmissions are likely preventable by what hospitals can control,[2] and that patient factors, especially social and economic circumstances,[3] primarily drive readmissions. Despite this debate, we can all agree there is ample opportunity to improve the care of patients at the time of discharge.

In this context, we see important evidence emerging from the Better Outcomes by Optimizing Safe Transitions (BOOST) program. Funded by the Hartford Foundation among others, BOOST is specifically aimed at improving care transitions among older hospitalized adults. BOOST focuses on identifying those at highest risk for readmissions, communicating the discharge plan effectively, and ensuring close follow‐up, both through phone calls after discharge and timely appointments with primary care providers. These are all interventions that seem intuitively like good ideas. In this issue of the Journal of Hospital Medicine, leaders of the BOOST program report on the impact on readmissions rate.[4] However, as the accompanying editorial points out, the data are disappointing.[5] The evidence, seen in the best possible light, suggests a small improvement among a very select group of hospitals. Although the authors should be commended for writing up their findings, the fact that 19 of the 30 hospitals that received substantial training and assistance through the BOOST program chose not to report their data is unconscionable. The decision by those 19 hospitals to withhold data makes the results nearly uninterpretable and jeopardizes the hard work that so many others have engaged in. BOOST should require that hospitals agree to share data as a condition of participation in the program.

The Hansen study,[4] despite its disappointing findings, may signal that it is time for a new approach. First of all, we may need to focus on different metrics. Looking ahead, the most important question may not be Does BOOST lower readmission rates? but rather Does BOOST improve the care for patients at the time of discharge from the hospital? There are several good measures of the quality of a care transition, such as those by Coleman and colleagues,[6] and these could be used to measure the quality of care hospitals deliver at discharge. We could also develop new metrics of transitions of care. For example, hospitals truly committed to improvement could field an ongoing survey of primary care physicians in their community to ensure that care transitions are happening smoothly from the primary care providers' perspective. Patient experience metrics, beyond those captured in the Hospital Consumer Assessment of Healthcare Providers and Systems survey, may be necessary to better assess patient and family perspectives on the transition from the hospital to home. These and other approaches can help hospitals better understand how effectively they manage the handoff as patients leave their doors.

However, we should also recognize that although such approaches may improve care transitions, they are unlikely to substantially reduce readmissions. Instead, hospitals serious about reducing readmissions may need to reconsider their business model.[7] In the days following a discharge, patients are medically and socially vulnerable. Patients without robust social support at home may need more than just the right medications, a phone call, or a follow‐up appointment. They may need help with groceries, having their meals prepared, or getting a ride to the doctor's office. Hospitals that want to reduce readmissions may need to make investments in creating the community and social support that so many patients lack when they leave the hospital. This has never been part of the hospital business model before, but it may be time for a change.

The HRRP, an effort by federal policymakers to drive down readmissions through penalties, has clearly begun to make hospitals think about changing their business models in precisely these ways. Readmission rates are falling, although a concurrent increase in the number of patients being admitted to observation status makes it unclear whether patient care has actually improved. More data and time will tell. Furthermore, the program as currently designed targets hospitals that care for the sickest and poorest patients for penalties.[8] There are plenty of good options for addressing these unintended consequences, such as comparing safety‐net hospitals' performance to other similar institutions, or focusing only on preventable readmissions. However, regardless of its limitations, the HRRP in some form or another is here to stay. Therefore, hospitals will need to find ways to reduce readmissions, and programs like BOOST, even when executed perfectly, will be necessary but likely insufficient. Improving the quality of care transitions is critically important. But to truly get to better outcomes for older Americans, hospitals will need to think beyond their 4 walls.

Although hospital readmissions have been a problem for at least the past 5 decades, they are now receiving more attention than ever before. Starting with the 2007 Medicare Payment Advisory Commission report detailing the vast scope of the problem,[1] readmissions have garnered substantial policy interest, culminating with Congress' inclusion of a penalty for hospitals with excessive readmission rates in the Affordable Care Act. Clinical leaders have become increasingly active in this issue as well, and hospitals around the nation have become engaged in finding ways to reduce the number of times patients return after discharge.

The Hospital Readmissions Reduction Program (HRRP), which is the penalty program put in place by Congress to address readmissions, has been controversial from its inception. Supporters point to the large number of patients whose discharge is fraught with poor communication, ineffective medication management, and inadequate handoffs to the primary care physician. Critics have countered that only a small proportion of readmissions are likely preventable by what hospitals can control,[2] and that patient factors, especially social and economic circumstances,[3] primarily drive readmissions. Despite this debate, we can all agree there is ample opportunity to improve the care of patients at the time of discharge.

In this context, we see important evidence emerging from the Better Outcomes by Optimizing Safe Transitions (BOOST) program. Funded by the Hartford Foundation among others, BOOST is specifically aimed at improving care transitions among older hospitalized adults. BOOST focuses on identifying those at highest risk for readmissions, communicating the discharge plan effectively, and ensuring close follow‐up, both through phone calls after discharge and timely appointments with primary care providers. These are all interventions that seem intuitively like good ideas. In this issue of the Journal of Hospital Medicine, leaders of the BOOST program report on the impact on readmissions rate.[4] However, as the accompanying editorial points out, the data are disappointing.[5] The evidence, seen in the best possible light, suggests a small improvement among a very select group of hospitals. Although the authors should be commended for writing up their findings, the fact that 19 of the 30 hospitals that received substantial training and assistance through the BOOST program chose not to report their data is unconscionable. The decision by those 19 hospitals to withhold data makes the results nearly uninterpretable and jeopardizes the hard work that so many others have engaged in. BOOST should require that hospitals agree to share data as a condition of participation in the program.

The Hansen study,[4] despite its disappointing findings, may signal that it is time for a new approach. First of all, we may need to focus on different metrics. Looking ahead, the most important question may not be Does BOOST lower readmission rates? but rather Does BOOST improve the care for patients at the time of discharge from the hospital? There are several good measures of the quality of a care transition, such as those by Coleman and colleagues,[6] and these could be used to measure the quality of care hospitals deliver at discharge. We could also develop new metrics of transitions of care. For example, hospitals truly committed to improvement could field an ongoing survey of primary care physicians in their community to ensure that care transitions are happening smoothly from the primary care providers' perspective. Patient experience metrics, beyond those captured in the Hospital Consumer Assessment of Healthcare Providers and Systems survey, may be necessary to better assess patient and family perspectives on the transition from the hospital to home. These and other approaches can help hospitals better understand how effectively they manage the handoff as patients leave their doors.

However, we should also recognize that although such approaches may improve care transitions, they are unlikely to substantially reduce readmissions. Instead, hospitals serious about reducing readmissions may need to reconsider their business model.[7] In the days following a discharge, patients are medically and socially vulnerable. Patients without robust social support at home may need more than just the right medications, a phone call, or a follow‐up appointment. They may need help with groceries, having their meals prepared, or getting a ride to the doctor's office. Hospitals that want to reduce readmissions may need to make investments in creating the community and social support that so many patients lack when they leave the hospital. This has never been part of the hospital business model before, but it may be time for a change.

The HRRP, an effort by federal policymakers to drive down readmissions through penalties, has clearly begun to make hospitals think about changing their business models in precisely these ways. Readmission rates are falling, although a concurrent increase in the number of patients being admitted to observation status makes it unclear whether patient care has actually improved. More data and time will tell. Furthermore, the program as currently designed targets hospitals that care for the sickest and poorest patients for penalties.[8] There are plenty of good options for addressing these unintended consequences, such as comparing safety‐net hospitals' performance to other similar institutions, or focusing only on preventable readmissions. However, regardless of its limitations, the HRRP in some form or another is here to stay. Therefore, hospitals will need to find ways to reduce readmissions, and programs like BOOST, even when executed perfectly, will be necessary but likely insufficient. Improving the quality of care transitions is critically important. But to truly get to better outcomes for older Americans, hospitals will need to think beyond their 4 walls.

Although hospital readmissions have been a problem for at least the past 5 decades, they are now receiving more attention than ever before. Starting with the 2007 Medicare Payment Advisory Commission report detailing the vast scope of the problem,[1] readmissions have garnered substantial policy interest, culminating with Congress' inclusion of a penalty for hospitals with excessive readmission rates in the Affordable Care Act. Clinical leaders have become increasingly active in this issue as well, and hospitals around the nation have become engaged in finding ways to reduce the number of times patients return after discharge.

The Hospital Readmissions Reduction Program (HRRP), which is the penalty program put in place by Congress to address readmissions, has been controversial from its inception. Supporters point to the large number of patients whose discharge is fraught with poor communication, ineffective medication management, and inadequate handoffs to the primary care physician. Critics have countered that only a small proportion of readmissions are likely preventable by what hospitals can control,[2] and that patient factors, especially social and economic circumstances,[3] primarily drive readmissions. Despite this debate, we can all agree there is ample opportunity to improve the care of patients at the time of discharge.

In this context, we see important evidence emerging from the Better Outcomes by Optimizing Safe Transitions (BOOST) program. Funded by the Hartford Foundation among others, BOOST is specifically aimed at improving care transitions among older hospitalized adults. BOOST focuses on identifying those at highest risk for readmissions, communicating the discharge plan effectively, and ensuring close follow‐up, both through phone calls after discharge and timely appointments with primary care providers. These are all interventions that seem intuitively like good ideas. In this issue of the Journal of Hospital Medicine, leaders of the BOOST program report on the impact on readmissions rate.[4] However, as the accompanying editorial points out, the data are disappointing.[5] The evidence, seen in the best possible light, suggests a small improvement among a very select group of hospitals. Although the authors should be commended for writing up their findings, the fact that 19 of the 30 hospitals that received substantial training and assistance through the BOOST program chose not to report their data is unconscionable. The decision by those 19 hospitals to withhold data makes the results nearly uninterpretable and jeopardizes the hard work that so many others have engaged in. BOOST should require that hospitals agree to share data as a condition of participation in the program.

The Hansen study,[4] despite its disappointing findings, may signal that it is time for a new approach. First of all, we may need to focus on different metrics. Looking ahead, the most important question may not be Does BOOST lower readmission rates? but rather Does BOOST improve the care for patients at the time of discharge from the hospital? There are several good measures of the quality of a care transition, such as those by Coleman and colleagues,[6] and these could be used to measure the quality of care hospitals deliver at discharge. We could also develop new metrics of transitions of care. For example, hospitals truly committed to improvement could field an ongoing survey of primary care physicians in their community to ensure that care transitions are happening smoothly from the primary care providers' perspective. Patient experience metrics, beyond those captured in the Hospital Consumer Assessment of Healthcare Providers and Systems survey, may be necessary to better assess patient and family perspectives on the transition from the hospital to home. These and other approaches can help hospitals better understand how effectively they manage the handoff as patients leave their doors.

However, we should also recognize that although such approaches may improve care transitions, they are unlikely to substantially reduce readmissions. Instead, hospitals serious about reducing readmissions may need to reconsider their business model.[7] In the days following a discharge, patients are medically and socially vulnerable. Patients without robust social support at home may need more than just the right medications, a phone call, or a follow‐up appointment. They may need help with groceries, having their meals prepared, or getting a ride to the doctor's office. Hospitals that want to reduce readmissions may need to make investments in creating the community and social support that so many patients lack when they leave the hospital. This has never been part of the hospital business model before, but it may be time for a change.

The HRRP, an effort by federal policymakers to drive down readmissions through penalties, has clearly begun to make hospitals think about changing their business models in precisely these ways. Readmission rates are falling, although a concurrent increase in the number of patients being admitted to observation status makes it unclear whether patient care has actually improved. More data and time will tell. Furthermore, the program as currently designed targets hospitals that care for the sickest and poorest patients for penalties.[8] There are plenty of good options for addressing these unintended consequences, such as comparing safety‐net hospitals' performance to other similar institutions, or focusing only on preventable readmissions. However, regardless of its limitations, the HRRP in some form or another is here to stay. Therefore, hospitals will need to find ways to reduce readmissions, and programs like BOOST, even when executed perfectly, will be necessary but likely insufficient. Improving the quality of care transitions is critically important. But to truly get to better outcomes for older Americans, hospitals will need to think beyond their 4 walls.

Anemia is associated with poor quality of life and increased risk for death and hospitalization in population‐based and cohort investigations.[1, 2, 3, 4, 5, 6, 7] Evidence suggests that patients with normal hemoglobin (Hgb) values on hospital admission who subsequently develop hospital‐acquired anemia (HAA) have increased morbidity and mortality compared with those who do not.[8, 9] HAA is multifaceted and may occur as a result of processes of care during hospitalization, such as hemodilution from intravenous fluid administration, procedural blood loss and phlebotomy, and impaired erythropoiesis associated with critical illness.[8, 9] Moreover, correcting anemia by red blood cell transfusion also carries risk.[10, 11, 12, 13]

Our primary objective was to examine the prevalence of HAA in a population of medical and surgical patients admitted to a large quaternary referral health system. Our secondary objectives were to examine whether HAA is associated with increased mortality, length of stay (LOS), and total hospital charges compared to patients without HAA.

METHODS

Patient Population and Data Sources

The patient population consisted of 417,301 hospitalizations in adult patients (18 years of age) who were admitted to the Cleveland Clinic Health System from January 2009 to September 2011. Data for these hospitalizations came from 2 sources. Patient demographics, baseline comorbidities, and outcomes were extracted from the University HealthSystem Consortium's (UHC) clinical database/resource manager. UHC is an alliance of 116 US academic medical centers and their 272 affiliated hospitals, representing more than 90% of the nation's nonprofit academic medical centers. These data had originally been retrieved from our hospitals' administrative data systems, normalized according to UHC standardized data specifications, and submitted for inclusion in the UHC repository. Data quality was assessed using standardized error checking and data completeness algorithms and was required to meet established minimum thresholds to be included in the UHC repository.

The second source of data was measured Hgb values retrieved from the hospitals' electronic medical record from complete blood count testing. Present‐on‐admission (POA) anemia was defined by an International Classification of Diseases, 9th Revision, Clinical Modification diagnosis code of anemia with a positive POA indicator; these patients were excluded from the analysis (Figure 1). Patients without available Hgb values and those with Hgb data dated 3 days or more after discharge date were also excluded. In addition, 2 hospitals within the health system did not have electronically available laboratory data and therefore were excluded from the analysis as well. The final dataset consisted of 188,447 patient hospitalizations. The institutional review board approved this investigation, with individual patient consent waived.

Figure 1

RESULTS

Prevalence of HAA

Among the 188,447 hospitalizations, 139,807 patients (74%) developed HAA and 48,640 (26%) did not. Of the 74%, 40,828 developed mild, 57,184 moderate, and 41,795 severe HAA (Figure 2). Patients who developed HAA were older than those who did not and had more comorbidities, including hypertension, heart failure, peripheral arterial disease, and renal and liver disease. They were hospitalized more commonly for surgical intervention than were those who did not develop HAA (Table 1). Time‐related patterns for developing HAA, however, showed that it developed earlier in men and more frequently with medical versus surgical hospitalization (Figure 3).

Figure 2

Figure 3

Hospital Mortality and HAA

Unadjusted mortality progressively increased with increasing degree of HAA: no HAA, 0.78% (n=378); mild HAA, 0.99% (n=405); moderate HAA, 1.5% (n=881); and severe HAA, 4.6% (n=1936) (P<0.001) (Figure 4A). Patients with mild HAA did not have higher risk‐adjusted mortality than those not having HAA (odds ratio: 1.02, 95% confidence interval [CI]: 0.88‐1.17). However, as HAA increased to moderate and severe, risk of hospital mortality increased in a dose‐dependent manner compared with patients not developing HAA: moderate HAA, 1.51 (95% CI: 1.33‐1.71, P<0.001) and severe HAA, 3.28 (95% CI: 2.90‐3.72, P<0.001) (Figure 5A) (see Supporting Information, Supplement A, in the online version of this article).

Figure 4

Figure 5

DISCUSSION

A substantial number of patients entering our health system became anemic during the course of their hospitalization. Among those who developed HAA, in‐hospital mortality was higher, LOS longer, and total hospital charges greater in a dose‐dependent manner. A recent editorial noted that HAA might be a hazard of hospitalization similar to other complications, such as infections and deep vein thrombosis.[15] Our findings have significance in terms of demonstrating increased mortality and resource utilization associated with a potentially modifiable hospital‐acquired condition. Even mild HAA was associated with increased resource utilization, although not increased hospital mortality.

Others have noted negative consequences of HAA in subpopulations of hospital patients. Salisbury and colleagues examined 17,676 patients with acute myocardial infarction who had normal Hgb on admission.[16] They defined HAA as development of new anemia during hospitalization based on nadir Hgb. HAA developed in 57.5% of patients and was associated with increased mortality in a progressive manner. Risk‐adjusted odds ratios for in‐hospital death were greater in patients with moderate and severe HAA, 1.38 (95% CI: 1.10‐1.73) and 3.39 (95% CI: 2.59‐4.44), respectively.[16] A separate investigation of 2902 patients from a multicenter registry of patients admitted to the hospital with acute myocardial infarction reported that nearly half of those with normal Hgb values on admission developed HAA.[17] Most of these patients did not have documented bleeding; therefore, the authors suggested that HAA was not a surrogate for bleeding during hospitalization. Moreover, HAA was associated with higher mortality and worse health status 1 year after myocardial infarction.[17] Others have reported that development of HAA is not uncommon in the setting of acute myocardial infarction and is associated with increased long‐term mortality.[18]

Development of anemia during hospitalization is multifactorial and may result from procedural bleeding, phlebotomy, occult bleeding, hemodilution from intravenous fluid administration, and blunted erythropoietin production associated with critical illness.[8, 9] An investigation of general internal medicine patients reported phlebotomy was highly associated with changes in Hgb levels and contributed to anemia during hospitalization.[19] The authors reported that for every 1 mL of blood drawn, mean decreases in Hgb and hematocrit were 0.070.011 g/L¹ and 0.0190.003%, respectively. They suggested reporting cumulative phlebotomy volumes to physicians and use of pediatric‐sized tubes for collection.[19] Salisbury and colleagues reported that mean phlebotomy volume was higher in patients who developed HAA; for every 50 mL of blood drawn, the risk of moderate to severe HAA increased by 18%.[20] In an intensive care population, Chant and colleagues reported small decreases in phlebotomy volume were associated with reduced transfusion requirements in patients with prolonged stay.[21]

Attempts to ameliorate HAA should focus on modifiable processes‐of‐care factors. Patients with chronic illness have blunted erythropoiesis[8] and therefore cannot mount an adequate response to blood loss from procedures or phlebotomy. Whether use of erythropoietin, iron, or both would be effective in this population requires further investigation. One of the most studied risk factors for HAA is blood loss from hospital laboratory testing.[20] Sanchez‐Giron and Alvarez‐Mora found that all laboratory tests could be performed with smaller‐volume collection tubes without need for additional samples.[22] Others have proposed batching laboratory requests, recording cumulative daily blood loss due to phlebotomy for individual patients,[23] and use of blood conservation devices in intensive care units.

Figure 3 suggests that surgical patients develop anemia slightly later than medical patients. Features specific to surgery, such as perioperative intravenous fluid loading, third spacing, and subsequent plasma volume expansion when reabsorption occurs days later, likely contribute to differences in trends for development of HAA.[24, 25, 26] In addition, specific surgical cases with highly anticipated red blood cell loss should make use of antifibrinolytic agents to reduce blood loss and red cell salvage devices to reprocess and infuse shed blood.

CONCLUSION

Development of HAA is common and has important healthcare implications, including higher in‐hospital mortality and increased resource utilization. Treating HAA by transfusion has attendant morbidity risks and increased costs.[11, 12, 30] Hospitals must continue to focus on improving patient safety and raising awareness of HAA and other modifiable hospital‐acquired conditions. Closer prospective investigation for both medical and surgical patients of cumulative blood loss from laboratory testing, procedural blood loss, and a risk‐benefit analysis of treatment options is necessary.

Disclosure

Nothing to report.

Anemia is associated with poor quality of life and increased risk for death and hospitalization in population‐based and cohort investigations.[1, 2, 3, 4, 5, 6, 7] Evidence suggests that patients with normal hemoglobin (Hgb) values on hospital admission who subsequently develop hospital‐acquired anemia (HAA) have increased morbidity and mortality compared with those who do not.[8, 9] HAA is multifaceted and may occur as a result of processes of care during hospitalization, such as hemodilution from intravenous fluid administration, procedural blood loss and phlebotomy, and impaired erythropoiesis associated with critical illness.[8, 9] Moreover, correcting anemia by red blood cell transfusion also carries risk.[10, 11, 12, 13]

Our primary objective was to examine the prevalence of HAA in a population of medical and surgical patients admitted to a large quaternary referral health system. Our secondary objectives were to examine whether HAA is associated with increased mortality, length of stay (LOS), and total hospital charges compared to patients without HAA.

METHODS

Patient Population and Data Sources

The patient population consisted of 417,301 hospitalizations in adult patients (18 years of age) who were admitted to the Cleveland Clinic Health System from January 2009 to September 2011. Data for these hospitalizations came from 2 sources. Patient demographics, baseline comorbidities, and outcomes were extracted from the University HealthSystem Consortium's (UHC) clinical database/resource manager. UHC is an alliance of 116 US academic medical centers and their 272 affiliated hospitals, representing more than 90% of the nation's nonprofit academic medical centers. These data had originally been retrieved from our hospitals' administrative data systems, normalized according to UHC standardized data specifications, and submitted for inclusion in the UHC repository. Data quality was assessed using standardized error checking and data completeness algorithms and was required to meet established minimum thresholds to be included in the UHC repository.

The second source of data was measured Hgb values retrieved from the hospitals' electronic medical record from complete blood count testing. Present‐on‐admission (POA) anemia was defined by an International Classification of Diseases, 9th Revision, Clinical Modification diagnosis code of anemia with a positive POA indicator; these patients were excluded from the analysis (Figure 1). Patients without available Hgb values and those with Hgb data dated 3 days or more after discharge date were also excluded. In addition, 2 hospitals within the health system did not have electronically available laboratory data and therefore were excluded from the analysis as well. The final dataset consisted of 188,447 patient hospitalizations. The institutional review board approved this investigation, with individual patient consent waived.

Figure 1

RESULTS

Prevalence of HAA

Among the 188,447 hospitalizations, 139,807 patients (74%) developed HAA and 48,640 (26%) did not. Of the 74%, 40,828 developed mild, 57,184 moderate, and 41,795 severe HAA (Figure 2). Patients who developed HAA were older than those who did not and had more comorbidities, including hypertension, heart failure, peripheral arterial disease, and renal and liver disease. They were hospitalized more commonly for surgical intervention than were those who did not develop HAA (Table 1). Time‐related patterns for developing HAA, however, showed that it developed earlier in men and more frequently with medical versus surgical hospitalization (Figure 3).

Figure 2

Figure 3

Hospital Mortality and HAA

Unadjusted mortality progressively increased with increasing degree of HAA: no HAA, 0.78% (n=378); mild HAA, 0.99% (n=405); moderate HAA, 1.5% (n=881); and severe HAA, 4.6% (n=1936) (P<0.001) (Figure 4A). Patients with mild HAA did not have higher risk‐adjusted mortality than those not having HAA (odds ratio: 1.02, 95% confidence interval [CI]: 0.88‐1.17). However, as HAA increased to moderate and severe, risk of hospital mortality increased in a dose‐dependent manner compared with patients not developing HAA: moderate HAA, 1.51 (95% CI: 1.33‐1.71, P<0.001) and severe HAA, 3.28 (95% CI: 2.90‐3.72, P<0.001) (Figure 5A) (see Supporting Information, Supplement A, in the online version of this article).

Figure 4

Figure 5

DISCUSSION

A substantial number of patients entering our health system became anemic during the course of their hospitalization. Among those who developed HAA, in‐hospital mortality was higher, LOS longer, and total hospital charges greater in a dose‐dependent manner. A recent editorial noted that HAA might be a hazard of hospitalization similar to other complications, such as infections and deep vein thrombosis.[15] Our findings have significance in terms of demonstrating increased mortality and resource utilization associated with a potentially modifiable hospital‐acquired condition. Even mild HAA was associated with increased resource utilization, although not increased hospital mortality.

Others have noted negative consequences of HAA in subpopulations of hospital patients. Salisbury and colleagues examined 17,676 patients with acute myocardial infarction who had normal Hgb on admission.[16] They defined HAA as development of new anemia during hospitalization based on nadir Hgb. HAA developed in 57.5% of patients and was associated with increased mortality in a progressive manner. Risk‐adjusted odds ratios for in‐hospital death were greater in patients with moderate and severe HAA, 1.38 (95% CI: 1.10‐1.73) and 3.39 (95% CI: 2.59‐4.44), respectively.[16] A separate investigation of 2902 patients from a multicenter registry of patients admitted to the hospital with acute myocardial infarction reported that nearly half of those with normal Hgb values on admission developed HAA.[17] Most of these patients did not have documented bleeding; therefore, the authors suggested that HAA was not a surrogate for bleeding during hospitalization. Moreover, HAA was associated with higher mortality and worse health status 1 year after myocardial infarction.[17] Others have reported that development of HAA is not uncommon in the setting of acute myocardial infarction and is associated with increased long‐term mortality.[18]

Development of anemia during hospitalization is multifactorial and may result from procedural bleeding, phlebotomy, occult bleeding, hemodilution from intravenous fluid administration, and blunted erythropoietin production associated with critical illness.[8, 9] An investigation of general internal medicine patients reported phlebotomy was highly associated with changes in Hgb levels and contributed to anemia during hospitalization.[19] The authors reported that for every 1 mL of blood drawn, mean decreases in Hgb and hematocrit were 0.070.011 g/L¹ and 0.0190.003%, respectively. They suggested reporting cumulative phlebotomy volumes to physicians and use of pediatric‐sized tubes for collection.[19] Salisbury and colleagues reported that mean phlebotomy volume was higher in patients who developed HAA; for every 50 mL of blood drawn, the risk of moderate to severe HAA increased by 18%.[20] In an intensive care population, Chant and colleagues reported small decreases in phlebotomy volume were associated with reduced transfusion requirements in patients with prolonged stay.[21]

Attempts to ameliorate HAA should focus on modifiable processes‐of‐care factors. Patients with chronic illness have blunted erythropoiesis[8] and therefore cannot mount an adequate response to blood loss from procedures or phlebotomy. Whether use of erythropoietin, iron, or both would be effective in this population requires further investigation. One of the most studied risk factors for HAA is blood loss from hospital laboratory testing.[20] Sanchez‐Giron and Alvarez‐Mora found that all laboratory tests could be performed with smaller‐volume collection tubes without need for additional samples.[22] Others have proposed batching laboratory requests, recording cumulative daily blood loss due to phlebotomy for individual patients,[23] and use of blood conservation devices in intensive care units.

Figure 3 suggests that surgical patients develop anemia slightly later than medical patients. Features specific to surgery, such as perioperative intravenous fluid loading, third spacing, and subsequent plasma volume expansion when reabsorption occurs days later, likely contribute to differences in trends for development of HAA.[24, 25, 26] In addition, specific surgical cases with highly anticipated red blood cell loss should make use of antifibrinolytic agents to reduce blood loss and red cell salvage devices to reprocess and infuse shed blood.

CONCLUSION

Development of HAA is common and has important healthcare implications, including higher in‐hospital mortality and increased resource utilization. Treating HAA by transfusion has attendant morbidity risks and increased costs.[11, 12, 30] Hospitals must continue to focus on improving patient safety and raising awareness of HAA and other modifiable hospital‐acquired conditions. Closer prospective investigation for both medical and surgical patients of cumulative blood loss from laboratory testing, procedural blood loss, and a risk‐benefit analysis of treatment options is necessary.

Disclosure

Nothing to report.

Anemia is associated with poor quality of life and increased risk for death and hospitalization in population‐based and cohort investigations.[1, 2, 3, 4, 5, 6, 7] Evidence suggests that patients with normal hemoglobin (Hgb) values on hospital admission who subsequently develop hospital‐acquired anemia (HAA) have increased morbidity and mortality compared with those who do not.[8, 9] HAA is multifaceted and may occur as a result of processes of care during hospitalization, such as hemodilution from intravenous fluid administration, procedural blood loss and phlebotomy, and impaired erythropoiesis associated with critical illness.[8, 9] Moreover, correcting anemia by red blood cell transfusion also carries risk.[10, 11, 12, 13]

Our primary objective was to examine the prevalence of HAA in a population of medical and surgical patients admitted to a large quaternary referral health system. Our secondary objectives were to examine whether HAA is associated with increased mortality, length of stay (LOS), and total hospital charges compared to patients without HAA.

METHODS

Patient Population and Data Sources

The patient population consisted of 417,301 hospitalizations in adult patients (18 years of age) who were admitted to the Cleveland Clinic Health System from January 2009 to September 2011. Data for these hospitalizations came from 2 sources. Patient demographics, baseline comorbidities, and outcomes were extracted from the University HealthSystem Consortium's (UHC) clinical database/resource manager. UHC is an alliance of 116 US academic medical centers and their 272 affiliated hospitals, representing more than 90% of the nation's nonprofit academic medical centers. These data had originally been retrieved from our hospitals' administrative data systems, normalized according to UHC standardized data specifications, and submitted for inclusion in the UHC repository. Data quality was assessed using standardized error checking and data completeness algorithms and was required to meet established minimum thresholds to be included in the UHC repository.

The second source of data was measured Hgb values retrieved from the hospitals' electronic medical record from complete blood count testing. Present‐on‐admission (POA) anemia was defined by an International Classification of Diseases, 9th Revision, Clinical Modification diagnosis code of anemia with a positive POA indicator; these patients were excluded from the analysis (Figure 1). Patients without available Hgb values and those with Hgb data dated 3 days or more after discharge date were also excluded. In addition, 2 hospitals within the health system did not have electronically available laboratory data and therefore were excluded from the analysis as well. The final dataset consisted of 188,447 patient hospitalizations. The institutional review board approved this investigation, with individual patient consent waived.

Figure 1

RESULTS

Prevalence of HAA

Among the 188,447 hospitalizations, 139,807 patients (74%) developed HAA and 48,640 (26%) did not. Of the 74%, 40,828 developed mild, 57,184 moderate, and 41,795 severe HAA (Figure 2). Patients who developed HAA were older than those who did not and had more comorbidities, including hypertension, heart failure, peripheral arterial disease, and renal and liver disease. They were hospitalized more commonly for surgical intervention than were those who did not develop HAA (Table 1). Time‐related patterns for developing HAA, however, showed that it developed earlier in men and more frequently with medical versus surgical hospitalization (Figure 3).

Figure 2

Figure 3

Hospital Mortality and HAA

Unadjusted mortality progressively increased with increasing degree of HAA: no HAA, 0.78% (n=378); mild HAA, 0.99% (n=405); moderate HAA, 1.5% (n=881); and severe HAA, 4.6% (n=1936) (P<0.001) (Figure 4A). Patients with mild HAA did not have higher risk‐adjusted mortality than those not having HAA (odds ratio: 1.02, 95% confidence interval [CI]: 0.88‐1.17). However, as HAA increased to moderate and severe, risk of hospital mortality increased in a dose‐dependent manner compared with patients not developing HAA: moderate HAA, 1.51 (95% CI: 1.33‐1.71, P<0.001) and severe HAA, 3.28 (95% CI: 2.90‐3.72, P<0.001) (Figure 5A) (see Supporting Information, Supplement A, in the online version of this article).

Figure 4

Figure 5

DISCUSSION

A substantial number of patients entering our health system became anemic during the course of their hospitalization. Among those who developed HAA, in‐hospital mortality was higher, LOS longer, and total hospital charges greater in a dose‐dependent manner. A recent editorial noted that HAA might be a hazard of hospitalization similar to other complications, such as infections and deep vein thrombosis.[15] Our findings have significance in terms of demonstrating increased mortality and resource utilization associated with a potentially modifiable hospital‐acquired condition. Even mild HAA was associated with increased resource utilization, although not increased hospital mortality.

Others have noted negative consequences of HAA in subpopulations of hospital patients. Salisbury and colleagues examined 17,676 patients with acute myocardial infarction who had normal Hgb on admission.[16] They defined HAA as development of new anemia during hospitalization based on nadir Hgb. HAA developed in 57.5% of patients and was associated with increased mortality in a progressive manner. Risk‐adjusted odds ratios for in‐hospital death were greater in patients with moderate and severe HAA, 1.38 (95% CI: 1.10‐1.73) and 3.39 (95% CI: 2.59‐4.44), respectively.[16] A separate investigation of 2902 patients from a multicenter registry of patients admitted to the hospital with acute myocardial infarction reported that nearly half of those with normal Hgb values on admission developed HAA.[17] Most of these patients did not have documented bleeding; therefore, the authors suggested that HAA was not a surrogate for bleeding during hospitalization. Moreover, HAA was associated with higher mortality and worse health status 1 year after myocardial infarction.[17] Others have reported that development of HAA is not uncommon in the setting of acute myocardial infarction and is associated with increased long‐term mortality.[18]

Development of anemia during hospitalization is multifactorial and may result from procedural bleeding, phlebotomy, occult bleeding, hemodilution from intravenous fluid administration, and blunted erythropoietin production associated with critical illness.[8, 9] An investigation of general internal medicine patients reported phlebotomy was highly associated with changes in Hgb levels and contributed to anemia during hospitalization.[19] The authors reported that for every 1 mL of blood drawn, mean decreases in Hgb and hematocrit were 0.070.011 g/L¹ and 0.0190.003%, respectively. They suggested reporting cumulative phlebotomy volumes to physicians and use of pediatric‐sized tubes for collection.[19] Salisbury and colleagues reported that mean phlebotomy volume was higher in patients who developed HAA; for every 50 mL of blood drawn, the risk of moderate to severe HAA increased by 18%.[20] In an intensive care population, Chant and colleagues reported small decreases in phlebotomy volume were associated with reduced transfusion requirements in patients with prolonged stay.[21]

Attempts to ameliorate HAA should focus on modifiable processes‐of‐care factors. Patients with chronic illness have blunted erythropoiesis[8] and therefore cannot mount an adequate response to blood loss from procedures or phlebotomy. Whether use of erythropoietin, iron, or both would be effective in this population requires further investigation. One of the most studied risk factors for HAA is blood loss from hospital laboratory testing.[20] Sanchez‐Giron and Alvarez‐Mora found that all laboratory tests could be performed with smaller‐volume collection tubes without need for additional samples.[22] Others have proposed batching laboratory requests, recording cumulative daily blood loss due to phlebotomy for individual patients,[23] and use of blood conservation devices in intensive care units.

Figure 3 suggests that surgical patients develop anemia slightly later than medical patients. Features specific to surgery, such as perioperative intravenous fluid loading, third spacing, and subsequent plasma volume expansion when reabsorption occurs days later, likely contribute to differences in trends for development of HAA.[24, 25, 26] In addition, specific surgical cases with highly anticipated red blood cell loss should make use of antifibrinolytic agents to reduce blood loss and red cell salvage devices to reprocess and infuse shed blood.

CONCLUSION

Development of HAA is common and has important healthcare implications, including higher in‐hospital mortality and increased resource utilization. Treating HAA by transfusion has attendant morbidity risks and increased costs.[11, 12, 30] Hospitals must continue to focus on improving patient safety and raising awareness of HAA and other modifiable hospital‐acquired conditions. Closer prospective investigation for both medical and surgical patients of cumulative blood loss from laboratory testing, procedural blood loss, and a risk‐benefit analysis of treatment options is necessary.

Disclosure

Nothing to report.