As clinicians who have been in practice for even a relatively short period of time know, patient compliance is an integral aspect of achieving optimal patient outcomes. However, studies show that patient compliance with treatment of many dermatologic disorders, including acne and psoriasis, is often poor.^1,2

In 2007, Feldman showed that patients are more likely to use their products in the days before and the days after their dermatologist visit.³ He suggested that more frequent office visits would boost compliance. I have found that this is true and I recommend seeing patients every 4 weeks when implementing a new treatment regimen. I have also found that combining prescription medications with the proper corresponding skin care products helps decrease side effects and speed results when patients apply the products correctly.

To achieve good patient outcomes, the patient needs to:

• Understand what medications and products to use.
• Understand when and how to use the products.
• Understand the order in which to use the products (step 1, step 2, etc.).
• Purchase the products (from you or elsewhere).
• Tell you if they do not purchase the products, for whatever reason (insurance will not cover, too expensive, could not find them, etc.).
• Use the products consistently.
• Inform you if they do not use the products (too busy, did not have them on a trip, etc.).
• Report any side effects so you can adjust the therapy accordingly.

You can see why it is so difficult to get patients to be compliant. Many factors – such as time, memory, education level, understanding, motivation, cost, convenience, and insurance coverage – can get in the way of these important components. Giving patients a printed regimen with instructions, selling the products in your practice, and providing some sort of interaction to keep patients engaged is key. In my June 2015 Dermatology News column, I discussed why you should consider selling products in your practice. In the future, I will discuss ways to engage your patients, but for now, let’s focus on how to quickly and effectively provide your patients with printed regimens and patient instructions without increasing office visit times.
 

Streamlining the Process of Generating a Skin Care Regimen That Includes Prescription Medications

Identify patients’ phenotypes

Divide patients into phenotypes based on skin care needs to save yourself time with the recommendation process.

Many doctors do this with a disease-based approach, such as acne, rosacea, eczema, psoriasis, etc. I prefer to classify my patients according to 16 Baumann Skin Types based on four parameters: hydration status, propensity for inflammation; presence or absence of uneven pigmentation; and presence of lifestyle habits, such as sun exposure, that increase an individual’s risk of skin aging.^4,5,6 To quickly diagnose the patient as a particular Baumann Skin Type, I use a tablet-based validated questionnaire called the Baumann Skin Type Indicator (BSTI).⁷ This questionnaire is self-administered by the patient in the waiting room and serves several purposes that facilitate my practice:

• To collect historical and current data.
• To diagnose skin type.
• To ask specifically about skin allergies.
• To learn preferences such as tinted vs. nontinted, or chemical vs. physical sunscreen.
• To inquire about what issues the patient wants to discuss, such as thinning eyelashes, hair loss, dry body skin, toenail fungus, warts, eczema, and other topics that might not come up during the appointment.
• To learn and document habits that affect the skin, such as tanning bed exposure, sun exposure, and smoking.
• To stimulate the patient to think about how daily actions such as sunscreen use and sun exposure affect their skin health.

Whether you choose to use my questionnaire or one of your own, using a validated method that can be initiated by staff in the waiting room saves time in the exam room.
 

Include prescription medications in the skin care regimen

Often, we think of skin care regimens and prescription medications as two different entities. In actuality, these should be combined.

For example, when treating acne, every item the patient uses plays a role. For example, if they are washing the face with Ivory soap and then applying benzoyl peroxide and a retinoid they will experience dryness and irritation. Then they will buy a moisturizer that might cause acne. (It is very hard for them to know which moisturizers and sunscreens will not worsen acne). By providing them with the exact names of cleansers, moisturizers, and sunscreens to use, they will be better able to tolerate their prescription acne medications.

The same is true with psoriasis, eczema, seborrheic dermatitis, contact dermatitis, and most of the other ailments that dermatologists treat. You must also tell them the order to use them in. For example, I always have patients apply the retinoid over the noncomedogenic moisturizer for the first few weeks to help them adjust to the retinoid. Later, once they have passed the high-risk period of retinoid dermatitis, I move the retinoid to under the moisturizer.

Psoriasis treatment (topical) is another good example. If they are going to use a surfactant-laden soap on their skin, they will impair their barrier and absorb more of the topically applied drug. Conversely, if they use a barrier repair moisturizer, they will absorb less. Telling the patients exactly which body cleansers and moisturizers to use with topical psoriasis medications will help standardize the response. For this reason, giving patients printed regimens is not limited to treatment of acne, rosacea, and photoaging, but rather should be done for patients with all skin issues and phenotypes.

Have informational material for each phenotype at your fingertips

You can have a plan for each patient phenotype that is designed ahead of time. You will save yourself hours of time if you have preprinted instructions sheets made for each of these phenotypes. You can use Touch MD, The Canfield Visia Camera Patient Portal, your EMR, or other systems to organize this material and deliver it to patients.

I personally use the Skin Type Solutions Software System (STSFranchise.com) that I developed and patented to house and export my patient instructions. Using a standardized methodology to provide educational information through video, preprinted sheets, emails, and other methods allows you to educate your patients at their pace and in the media with which they are most comfortable. To have this flexibility, the educational information must be developed prior to the patient visit. Categorizing the education information by phenotype makes this possible.

What the informational material should contain

Educational information should include important information about the phenotype, the do’s and don’ts for the phenotype, an exact skin care regimen containing clear steps that include product names including brand names, prescription medications, the order in which the products should be applied, and clear instructions on how to use the products.

The patient should be informed about what to do if anticipated adverse events occur, such as redness and peeling from retinoids or dryness from benzoyl peroxide. The same is true about injectable biologic medications for psoriasis. The patients need information on where to inject the product, how often, how to clean the skin beforehand, and what to put on the skin after the injections. It is always important with any skin issue for the patient to know when to contact the office. The American Academy of Dermatology and other organizations offer educational brochures for patients, but they cannot be customized. Patients prefer a customized approach to educational material. They don’t want to read information that does not apply to them. I have found that dividing patients into 16 distinct Baumann Skin Types helps target the right information to the corresponding skin phenotypes.

Summary

Patients need education and guidance to be compliant and improve their outcomes. Your staff needs to be a part of the education process, but taking the time to train your staff and educate your patients is always an issue. Developing a standardized methodology will help overcome these hurdles and solve this problem. The methodology should provide directed education and clear communication with written instructions delivered in the media of the patient’s choice. Doing this will yield better compliance and outcomes.

If you have any questions, suggestions or ideas of how to solve these issues, please share them with me at [email protected].

Dr. Baumann is a private practice dermatologist, researcher, author, and entrepreneur who practices in Miami. She founded the Cosmetic Dermatology Center at the University of Miami in 1997. Dr. Baumann wrote two textbooks: “Cosmetic Dermatology: Principles and Practice” (New York: McGraw-Hill, 2002), and “Cosmeceuticals and Cosmetic Ingredients,” (New York: McGraw-Hill, 2014), and a New York Times Best Sellers book for consumers, “The Skin Type Solution” (New York: Bantam Dell, 2006). Dr. Baumann has received funding for advisory boards and/or clinical research trials from Allergan, Evolus, Galderma, and Revance. She is the founder and CEO of Skin Type Solutions Franchise Systems LLC.

References

1. JAMA Dermatol. 2015 Jun;151(6):623-6.

2. J Am Acad Dermatol. 2004 Aug;51(2):212-6.

3. J Am Acad Dermatol. 2007 Jul;57(1):81-3.

4. Dermatol Clin. 2008 Jul;26(3):359-73.

5. Baumann L. Cosmetics and skin care in dermatology. In: Wolff K, ed. Fitzpatrick’s Dermatology in General Medicine, 7th ed. New York, NY: McGraw-Hill; 2008:2357-2364.

6. Baumann L. The Baumann skin typing system. In: Farage MA, Miller KW, Maibach HI, eds. Textbook of Aging Skin. Berling, Germany: Springer-Verlag; 2010:929-944.

7. Journal of Cosmetics, Dermatological Sciences and Applications. 2016;6(1):34-40.

As clinicians who have been in practice for even a relatively short period of time know, patient compliance is an integral aspect of achieving optimal patient outcomes. However, studies show that patient compliance with treatment of many dermatologic disorders, including acne and psoriasis, is often poor.^1,2

In 2007, Feldman showed that patients are more likely to use their products in the days before and the days after their dermatologist visit.³ He suggested that more frequent office visits would boost compliance. I have found that this is true and I recommend seeing patients every 4 weeks when implementing a new treatment regimen. I have also found that combining prescription medications with the proper corresponding skin care products helps decrease side effects and speed results when patients apply the products correctly.

To achieve good patient outcomes, the patient needs to:

• Understand what medications and products to use.
• Understand when and how to use the products.
• Understand the order in which to use the products (step 1, step 2, etc.).
• Purchase the products (from you or elsewhere).
• Tell you if they do not purchase the products, for whatever reason (insurance will not cover, too expensive, could not find them, etc.).
• Use the products consistently.
• Inform you if they do not use the products (too busy, did not have them on a trip, etc.).
• Report any side effects so you can adjust the therapy accordingly.

You can see why it is so difficult to get patients to be compliant. Many factors – such as time, memory, education level, understanding, motivation, cost, convenience, and insurance coverage – can get in the way of these important components. Giving patients a printed regimen with instructions, selling the products in your practice, and providing some sort of interaction to keep patients engaged is key. In my June 2015 Dermatology News column, I discussed why you should consider selling products in your practice. In the future, I will discuss ways to engage your patients, but for now, let’s focus on how to quickly and effectively provide your patients with printed regimens and patient instructions without increasing office visit times.
 

Streamlining the Process of Generating a Skin Care Regimen That Includes Prescription Medications

Identify patients’ phenotypes

Divide patients into phenotypes based on skin care needs to save yourself time with the recommendation process.

Many doctors do this with a disease-based approach, such as acne, rosacea, eczema, psoriasis, etc. I prefer to classify my patients according to 16 Baumann Skin Types based on four parameters: hydration status, propensity for inflammation; presence or absence of uneven pigmentation; and presence of lifestyle habits, such as sun exposure, that increase an individual’s risk of skin aging.^4,5,6 To quickly diagnose the patient as a particular Baumann Skin Type, I use a tablet-based validated questionnaire called the Baumann Skin Type Indicator (BSTI).⁷ This questionnaire is self-administered by the patient in the waiting room and serves several purposes that facilitate my practice:

• To collect historical and current data.
• To diagnose skin type.
• To ask specifically about skin allergies.
• To learn preferences such as tinted vs. nontinted, or chemical vs. physical sunscreen.
• To inquire about what issues the patient wants to discuss, such as thinning eyelashes, hair loss, dry body skin, toenail fungus, warts, eczema, and other topics that might not come up during the appointment.
• To learn and document habits that affect the skin, such as tanning bed exposure, sun exposure, and smoking.
• To stimulate the patient to think about how daily actions such as sunscreen use and sun exposure affect their skin health.

Whether you choose to use my questionnaire or one of your own, using a validated method that can be initiated by staff in the waiting room saves time in the exam room.
 

Include prescription medications in the skin care regimen

Often, we think of skin care regimens and prescription medications as two different entities. In actuality, these should be combined.

For example, when treating acne, every item the patient uses plays a role. For example, if they are washing the face with Ivory soap and then applying benzoyl peroxide and a retinoid they will experience dryness and irritation. Then they will buy a moisturizer that might cause acne. (It is very hard for them to know which moisturizers and sunscreens will not worsen acne). By providing them with the exact names of cleansers, moisturizers, and sunscreens to use, they will be better able to tolerate their prescription acne medications.

The same is true with psoriasis, eczema, seborrheic dermatitis, contact dermatitis, and most of the other ailments that dermatologists treat. You must also tell them the order to use them in. For example, I always have patients apply the retinoid over the noncomedogenic moisturizer for the first few weeks to help them adjust to the retinoid. Later, once they have passed the high-risk period of retinoid dermatitis, I move the retinoid to under the moisturizer.

Psoriasis treatment (topical) is another good example. If they are going to use a surfactant-laden soap on their skin, they will impair their barrier and absorb more of the topically applied drug. Conversely, if they use a barrier repair moisturizer, they will absorb less. Telling the patients exactly which body cleansers and moisturizers to use with topical psoriasis medications will help standardize the response. For this reason, giving patients printed regimens is not limited to treatment of acne, rosacea, and photoaging, but rather should be done for patients with all skin issues and phenotypes.

Have informational material for each phenotype at your fingertips

You can have a plan for each patient phenotype that is designed ahead of time. You will save yourself hours of time if you have preprinted instructions sheets made for each of these phenotypes. You can use Touch MD, The Canfield Visia Camera Patient Portal, your EMR, or other systems to organize this material and deliver it to patients.

I personally use the Skin Type Solutions Software System (STSFranchise.com) that I developed and patented to house and export my patient instructions. Using a standardized methodology to provide educational information through video, preprinted sheets, emails, and other methods allows you to educate your patients at their pace and in the media with which they are most comfortable. To have this flexibility, the educational information must be developed prior to the patient visit. Categorizing the education information by phenotype makes this possible.

What the informational material should contain

Educational information should include important information about the phenotype, the do’s and don’ts for the phenotype, an exact skin care regimen containing clear steps that include product names including brand names, prescription medications, the order in which the products should be applied, and clear instructions on how to use the products.

The patient should be informed about what to do if anticipated adverse events occur, such as redness and peeling from retinoids or dryness from benzoyl peroxide. The same is true about injectable biologic medications for psoriasis. The patients need information on where to inject the product, how often, how to clean the skin beforehand, and what to put on the skin after the injections. It is always important with any skin issue for the patient to know when to contact the office. The American Academy of Dermatology and other organizations offer educational brochures for patients, but they cannot be customized. Patients prefer a customized approach to educational material. They don’t want to read information that does not apply to them. I have found that dividing patients into 16 distinct Baumann Skin Types helps target the right information to the corresponding skin phenotypes.

Summary

Patients need education and guidance to be compliant and improve their outcomes. Your staff needs to be a part of the education process, but taking the time to train your staff and educate your patients is always an issue. Developing a standardized methodology will help overcome these hurdles and solve this problem. The methodology should provide directed education and clear communication with written instructions delivered in the media of the patient’s choice. Doing this will yield better compliance and outcomes.

If you have any questions, suggestions or ideas of how to solve these issues, please share them with me at [email protected].

Dr. Baumann is a private practice dermatologist, researcher, author, and entrepreneur who practices in Miami. She founded the Cosmetic Dermatology Center at the University of Miami in 1997. Dr. Baumann wrote two textbooks: “Cosmetic Dermatology: Principles and Practice” (New York: McGraw-Hill, 2002), and “Cosmeceuticals and Cosmetic Ingredients,” (New York: McGraw-Hill, 2014), and a New York Times Best Sellers book for consumers, “The Skin Type Solution” (New York: Bantam Dell, 2006). Dr. Baumann has received funding for advisory boards and/or clinical research trials from Allergan, Evolus, Galderma, and Revance. She is the founder and CEO of Skin Type Solutions Franchise Systems LLC.

References

1. JAMA Dermatol. 2015 Jun;151(6):623-6.

2. J Am Acad Dermatol. 2004 Aug;51(2):212-6.

3. J Am Acad Dermatol. 2007 Jul;57(1):81-3.

4. Dermatol Clin. 2008 Jul;26(3):359-73.

5. Baumann L. Cosmetics and skin care in dermatology. In: Wolff K, ed. Fitzpatrick’s Dermatology in General Medicine, 7th ed. New York, NY: McGraw-Hill; 2008:2357-2364.

6. Baumann L. The Baumann skin typing system. In: Farage MA, Miller KW, Maibach HI, eds. Textbook of Aging Skin. Berling, Germany: Springer-Verlag; 2010:929-944.

7. Journal of Cosmetics, Dermatological Sciences and Applications. 2016;6(1):34-40.

As clinicians who have been in practice for even a relatively short period of time know, patient compliance is an integral aspect of achieving optimal patient outcomes. However, studies show that patient compliance with treatment of many dermatologic disorders, including acne and psoriasis, is often poor.^1,2

In 2007, Feldman showed that patients are more likely to use their products in the days before and the days after their dermatologist visit.³ He suggested that more frequent office visits would boost compliance. I have found that this is true and I recommend seeing patients every 4 weeks when implementing a new treatment regimen. I have also found that combining prescription medications with the proper corresponding skin care products helps decrease side effects and speed results when patients apply the products correctly.

To achieve good patient outcomes, the patient needs to:

• Understand what medications and products to use.
• Understand when and how to use the products.
• Understand the order in which to use the products (step 1, step 2, etc.).
• Purchase the products (from you or elsewhere).
• Tell you if they do not purchase the products, for whatever reason (insurance will not cover, too expensive, could not find them, etc.).
• Use the products consistently.
• Inform you if they do not use the products (too busy, did not have them on a trip, etc.).
• Report any side effects so you can adjust the therapy accordingly.

You can see why it is so difficult to get patients to be compliant. Many factors – such as time, memory, education level, understanding, motivation, cost, convenience, and insurance coverage – can get in the way of these important components. Giving patients a printed regimen with instructions, selling the products in your practice, and providing some sort of interaction to keep patients engaged is key. In my June 2015 Dermatology News column, I discussed why you should consider selling products in your practice. In the future, I will discuss ways to engage your patients, but for now, let’s focus on how to quickly and effectively provide your patients with printed regimens and patient instructions without increasing office visit times.
 

Streamlining the Process of Generating a Skin Care Regimen That Includes Prescription Medications

Identify patients’ phenotypes

Divide patients into phenotypes based on skin care needs to save yourself time with the recommendation process.

Many doctors do this with a disease-based approach, such as acne, rosacea, eczema, psoriasis, etc. I prefer to classify my patients according to 16 Baumann Skin Types based on four parameters: hydration status, propensity for inflammation; presence or absence of uneven pigmentation; and presence of lifestyle habits, such as sun exposure, that increase an individual’s risk of skin aging.^4,5,6 To quickly diagnose the patient as a particular Baumann Skin Type, I use a tablet-based validated questionnaire called the Baumann Skin Type Indicator (BSTI).⁷ This questionnaire is self-administered by the patient in the waiting room and serves several purposes that facilitate my practice:

• To collect historical and current data.
• To diagnose skin type.
• To ask specifically about skin allergies.
• To learn preferences such as tinted vs. nontinted, or chemical vs. physical sunscreen.
• To inquire about what issues the patient wants to discuss, such as thinning eyelashes, hair loss, dry body skin, toenail fungus, warts, eczema, and other topics that might not come up during the appointment.
• To learn and document habits that affect the skin, such as tanning bed exposure, sun exposure, and smoking.
• To stimulate the patient to think about how daily actions such as sunscreen use and sun exposure affect their skin health.

Whether you choose to use my questionnaire or one of your own, using a validated method that can be initiated by staff in the waiting room saves time in the exam room.
 

Include prescription medications in the skin care regimen

Often, we think of skin care regimens and prescription medications as two different entities. In actuality, these should be combined.

For example, when treating acne, every item the patient uses plays a role. For example, if they are washing the face with Ivory soap and then applying benzoyl peroxide and a retinoid they will experience dryness and irritation. Then they will buy a moisturizer that might cause acne. (It is very hard for them to know which moisturizers and sunscreens will not worsen acne). By providing them with the exact names of cleansers, moisturizers, and sunscreens to use, they will be better able to tolerate their prescription acne medications.

The same is true with psoriasis, eczema, seborrheic dermatitis, contact dermatitis, and most of the other ailments that dermatologists treat. You must also tell them the order to use them in. For example, I always have patients apply the retinoid over the noncomedogenic moisturizer for the first few weeks to help them adjust to the retinoid. Later, once they have passed the high-risk period of retinoid dermatitis, I move the retinoid to under the moisturizer.

Psoriasis treatment (topical) is another good example. If they are going to use a surfactant-laden soap on their skin, they will impair their barrier and absorb more of the topically applied drug. Conversely, if they use a barrier repair moisturizer, they will absorb less. Telling the patients exactly which body cleansers and moisturizers to use with topical psoriasis medications will help standardize the response. For this reason, giving patients printed regimens is not limited to treatment of acne, rosacea, and photoaging, but rather should be done for patients with all skin issues and phenotypes.

Have informational material for each phenotype at your fingertips

You can have a plan for each patient phenotype that is designed ahead of time. You will save yourself hours of time if you have preprinted instructions sheets made for each of these phenotypes. You can use Touch MD, The Canfield Visia Camera Patient Portal, your EMR, or other systems to organize this material and deliver it to patients.

I personally use the Skin Type Solutions Software System (STSFranchise.com) that I developed and patented to house and export my patient instructions. Using a standardized methodology to provide educational information through video, preprinted sheets, emails, and other methods allows you to educate your patients at their pace and in the media with which they are most comfortable. To have this flexibility, the educational information must be developed prior to the patient visit. Categorizing the education information by phenotype makes this possible.

What the informational material should contain

Educational information should include important information about the phenotype, the do’s and don’ts for the phenotype, an exact skin care regimen containing clear steps that include product names including brand names, prescription medications, the order in which the products should be applied, and clear instructions on how to use the products.

The patient should be informed about what to do if anticipated adverse events occur, such as redness and peeling from retinoids or dryness from benzoyl peroxide. The same is true about injectable biologic medications for psoriasis. The patients need information on where to inject the product, how often, how to clean the skin beforehand, and what to put on the skin after the injections. It is always important with any skin issue for the patient to know when to contact the office. The American Academy of Dermatology and other organizations offer educational brochures for patients, but they cannot be customized. Patients prefer a customized approach to educational material. They don’t want to read information that does not apply to them. I have found that dividing patients into 16 distinct Baumann Skin Types helps target the right information to the corresponding skin phenotypes.

Summary

Patients need education and guidance to be compliant and improve their outcomes. Your staff needs to be a part of the education process, but taking the time to train your staff and educate your patients is always an issue. Developing a standardized methodology will help overcome these hurdles and solve this problem. The methodology should provide directed education and clear communication with written instructions delivered in the media of the patient’s choice. Doing this will yield better compliance and outcomes.

If you have any questions, suggestions or ideas of how to solve these issues, please share them with me at [email protected].

Dr. Baumann is a private practice dermatologist, researcher, author, and entrepreneur who practices in Miami. She founded the Cosmetic Dermatology Center at the University of Miami in 1997. Dr. Baumann wrote two textbooks: “Cosmetic Dermatology: Principles and Practice” (New York: McGraw-Hill, 2002), and “Cosmeceuticals and Cosmetic Ingredients,” (New York: McGraw-Hill, 2014), and a New York Times Best Sellers book for consumers, “The Skin Type Solution” (New York: Bantam Dell, 2006). Dr. Baumann has received funding for advisory boards and/or clinical research trials from Allergan, Evolus, Galderma, and Revance. She is the founder and CEO of Skin Type Solutions Franchise Systems LLC.

References

1. JAMA Dermatol. 2015 Jun;151(6):623-6.

2. J Am Acad Dermatol. 2004 Aug;51(2):212-6.

3. J Am Acad Dermatol. 2007 Jul;57(1):81-3.

4. Dermatol Clin. 2008 Jul;26(3):359-73.

5. Baumann L. Cosmetics and skin care in dermatology. In: Wolff K, ed. Fitzpatrick’s Dermatology in General Medicine, 7th ed. New York, NY: McGraw-Hill; 2008:2357-2364.

6. Baumann L. The Baumann skin typing system. In: Farage MA, Miller KW, Maibach HI, eds. Textbook of Aging Skin. Berling, Germany: Springer-Verlag; 2010:929-944.

7. Journal of Cosmetics, Dermatological Sciences and Applications. 2016;6(1):34-40.

AMSTERDAM – Prolonged oral treatment with norfloxacin improved the survival of patients with Child-Pugh class C liver disease versus no antibiotic prophylaxis in a randomized, double-blind, placebo-controlled, phase III multicenter trial.

Fewer patients (15.3% vs. 24.5%) treated with norfloxacin for 6 months died by the 6-month mortality primary endpoint than did those treated with placebo, with a hazard ratio of 0.59 (95% confidence interval, 0.35-0.99; P = .047) favoring prolonged antibiotic treatment. Adjustments for the concomitant use of nonselective beta-blockers and corticosteroids did not greatly alter the significance of the findings (adjusted HR, 0.58; 95% CI, 0.34-0.98; P = .042).

AMSTERDAM – Prolonged oral treatment with norfloxacin improved the survival of patients with Child-Pugh class C liver disease versus no antibiotic prophylaxis in a randomized, double-blind, placebo-controlled, phase III multicenter trial.

Fewer patients (15.3% vs. 24.5%) treated with norfloxacin for 6 months died by the 6-month mortality primary endpoint than did those treated with placebo, with a hazard ratio of 0.59 (95% confidence interval, 0.35-0.99; P = .047) favoring prolonged antibiotic treatment. Adjustments for the concomitant use of nonselective beta-blockers and corticosteroids did not greatly alter the significance of the findings (adjusted HR, 0.58; 95% CI, 0.34-0.98; P = .042).

AMSTERDAM – Prolonged oral treatment with norfloxacin improved the survival of patients with Child-Pugh class C liver disease versus no antibiotic prophylaxis in a randomized, double-blind, placebo-controlled, phase III multicenter trial.

Fewer patients (15.3% vs. 24.5%) treated with norfloxacin for 6 months died by the 6-month mortality primary endpoint than did those treated with placebo, with a hazard ratio of 0.59 (95% confidence interval, 0.35-0.99; P = .047) favoring prolonged antibiotic treatment. Adjustments for the concomitant use of nonselective beta-blockers and corticosteroids did not greatly alter the significance of the findings (adjusted HR, 0.58; 95% CI, 0.34-0.98; P = .042).

With patient co-management arrangements between hospitalists and other surgical and medical subspecialists becoming more common, HM17 attendees won’t want to miss Tuesday afternoon’s session at 3:15–4:20 p.m., “Redefining Co-management in Hospital Medicine.”

“We’ll provide hospitalists effective co-management programs at their respective hospitals,” said copresenter William Atchley Jr., MD, FACP, SFHM, a hospitalist with Sentara Heart Hospital in Norfolk, Va.

Redefining Co-management in Hospital Medicine
Tuesday, 3:15–4:20 p.m.

With patient co-management arrangements between hospitalists and other surgical and medical subspecialists becoming more common, HM17 attendees won’t want to miss Tuesday afternoon’s session at 3:15–4:20 p.m., “Redefining Co-management in Hospital Medicine.”

“We’ll provide hospitalists effective co-management programs at their respective hospitals,” said copresenter William Atchley Jr., MD, FACP, SFHM, a hospitalist with Sentara Heart Hospital in Norfolk, Va.

Redefining Co-management in Hospital Medicine
Tuesday, 3:15–4:20 p.m.

With patient co-management arrangements between hospitalists and other surgical and medical subspecialists becoming more common, HM17 attendees won’t want to miss Tuesday afternoon’s session at 3:15–4:20 p.m., “Redefining Co-management in Hospital Medicine.”

“We’ll provide hospitalists effective co-management programs at their respective hospitals,” said copresenter William Atchley Jr., MD, FACP, SFHM, a hospitalist with Sentara Heart Hospital in Norfolk, Va.

Redefining Co-management in Hospital Medicine
Tuesday, 3:15–4:20 p.m.

The Food and Drug Administration has approved midostaurin for the treatment of FLT3 mutation–positive acute myeloid leukemia (FLT3+ AML) in adult patients in combination with standard cytarabine and daunorubicin induction and cytarabine consolidation.

Approval was based on results from a randomized, double-blind, placebo-controlled trial of 717 patients with previously untreated FLT3+ AML. The hazard ratio for overall survival in patients receiving midostaurin, compared with a placebo, was 0.77 (P = .016). A companion diagnostic tool, the LeukoStrat CDx FLT3 Mutation Assay manufactured by Invivoscribe Technologies, was also approved.

[email protected]

The Food and Drug Administration has approved midostaurin for the treatment of FLT3 mutation–positive acute myeloid leukemia (FLT3+ AML) in adult patients in combination with standard cytarabine and daunorubicin induction and cytarabine consolidation.

Approval was based on results from a randomized, double-blind, placebo-controlled trial of 717 patients with previously untreated FLT3+ AML. The hazard ratio for overall survival in patients receiving midostaurin, compared with a placebo, was 0.77 (P = .016). A companion diagnostic tool, the LeukoStrat CDx FLT3 Mutation Assay manufactured by Invivoscribe Technologies, was also approved.

[email protected]

The Food and Drug Administration has approved midostaurin for the treatment of FLT3 mutation–positive acute myeloid leukemia (FLT3+ AML) in adult patients in combination with standard cytarabine and daunorubicin induction and cytarabine consolidation.

Approval was based on results from a randomized, double-blind, placebo-controlled trial of 717 patients with previously untreated FLT3+ AML. The hazard ratio for overall survival in patients receiving midostaurin, compared with a placebo, was 0.77 (P = .016). A companion diagnostic tool, the LeukoStrat CDx FLT3 Mutation Assay manufactured by Invivoscribe Technologies, was also approved.

[email protected]

Aggressive resection to negative margins, combined with neoadjuvant chemotherapy and postsurgical radiation, resulted in a 96% 5-year locoregional recurrence-free survival in nonmetastatic inflammatory breast cancer, Kelly Rosso, MD, reported.

Dr. Rosso of MD Anderson Cancer Center, Houston, and her colleagues identified 277 women diagnosed with inflammatory breast cancer between 2007 and 2015 from a prospective database; 114 of those had nonmetastatic disease and received aggressive trimodality therapy with curative intent.

Aggressive resection to negative margins, combined with neoadjuvant chemotherapy and postsurgical radiation, resulted in a 96% 5-year locoregional recurrence-free survival in nonmetastatic inflammatory breast cancer, Kelly Rosso, MD, reported.

Dr. Rosso of MD Anderson Cancer Center, Houston, and her colleagues identified 277 women diagnosed with inflammatory breast cancer between 2007 and 2015 from a prospective database; 114 of those had nonmetastatic disease and received aggressive trimodality therapy with curative intent.

Aggressive resection to negative margins, combined with neoadjuvant chemotherapy and postsurgical radiation, resulted in a 96% 5-year locoregional recurrence-free survival in nonmetastatic inflammatory breast cancer, Kelly Rosso, MD, reported.

Dr. Rosso of MD Anderson Cancer Center, Houston, and her colleagues identified 277 women diagnosed with inflammatory breast cancer between 2007 and 2015 from a prospective database; 114 of those had nonmetastatic disease and received aggressive trimodality therapy with curative intent.

BIRMINGHAM, ENGLAND – One in five people with ankylosing spondylitis could have comorbid fibromyalgia, according to data from the British Society for Rheumatology Biologics Register for Ankylosing Spondylitis (BSRBR-AS).

The analysis, which included more than 880 patients with axial spondyloarthritis (SpA), found that 20.7% met 2011 research criteria for the chronic pain condition.

The prevalence of fibromyalgia was similar when the modified New York (mNY) criteria were used to diagnose SpA, at 19.7%, but slightly higher at 25.2% when SpA patients met the Assessment of SpondyloArthritis international Society (ASAS) imaging criteria but not mNY criteria, and substantially lower at 9.5% when SpA patients met ASAS clinical criteria only.

Courtesy Dr. Gary J. Macfarlane

BIRMINGHAM, ENGLAND – One in five people with ankylosing spondylitis could have comorbid fibromyalgia, according to data from the British Society for Rheumatology Biologics Register for Ankylosing Spondylitis (BSRBR-AS).

The analysis, which included more than 880 patients with axial spondyloarthritis (SpA), found that 20.7% met 2011 research criteria for the chronic pain condition.

The prevalence of fibromyalgia was similar when the modified New York (mNY) criteria were used to diagnose SpA, at 19.7%, but slightly higher at 25.2% when SpA patients met the Assessment of SpondyloArthritis international Society (ASAS) imaging criteria but not mNY criteria, and substantially lower at 9.5% when SpA patients met ASAS clinical criteria only.

Courtesy Dr. Gary J. Macfarlane

BIRMINGHAM, ENGLAND – One in five people with ankylosing spondylitis could have comorbid fibromyalgia, according to data from the British Society for Rheumatology Biologics Register for Ankylosing Spondylitis (BSRBR-AS).

The analysis, which included more than 880 patients with axial spondyloarthritis (SpA), found that 20.7% met 2011 research criteria for the chronic pain condition.

The prevalence of fibromyalgia was similar when the modified New York (mNY) criteria were used to diagnose SpA, at 19.7%, but slightly higher at 25.2% when SpA patients met the Assessment of SpondyloArthritis international Society (ASAS) imaging criteria but not mNY criteria, and substantially lower at 9.5% when SpA patients met ASAS clinical criteria only.

Courtesy Dr. Gary J. Macfarlane

BOSTON – Both the soon-to-be chair and vice chair of the AGA Center for GI Innovation and Technology, which sponsors the AGA Tech Summit, are looking forward to building upon the successes of this year’s meeting.

“Giving folks a road map and seeing physicians come to the meeting to network and meet the right people, that is the really satisfying part for me,” V. Raman Muthusamy, MD, the incoming chair of the committee, said in an interview.

“I was honored to be asked to take over this position,” he said. “I have been contemplating . . .where we are and where we’ve been and where we need to go next.”

Dr. Muthusamy, director of interventional endoscopy and general GI endoscopy and current professor of medicine at the University of California, Los Angeles, is keenly interested in the intersection of technical innovation and gastroenterology, especially concerning endoscopic technology.

The committee’s incoming vice chair, Srinadh Komanduri, MD, of Northwestern University’s Feinberg School of Medicine, Chicago, takes a deep interest in innovative medical technologies that are applicable to gastroenterology. “A lot of what I’m doing at Northwestern is cutting-edge techniques and looking for new innovation, especially for early cancers in the GI tract,” Dr. Komanduri said.

Dr. Muthusamy and Dr. Komanduri will assume their new roles June 1 when Michael L. Kochman, MD, AGAF, of the University of Pennsylvania, Philadelphia, retires from his position as executive chairman of the committee, shortly after the close of this year’s AGA Tech Summit. “It’s been an honor and humbling to have been entrusted with running the CGIT over the past term; we solidified a number of critical relationships and added new programs. I am thrilled that Raman and Sri will be taking the reins as the plans that they have will build on the foundation and take the CGIT to a new level.”

The meeting, according to the incoming chairs, offers a great opportunity for physician-innovators to share their interests and ideas.

“The Tech Summit is unlike any other meeting I’ve gone to. It is a time to see the business of science and the gaps in technology as well as the technicalities of business that are not part of the standard medical training,” said Dr. Muthusamy, who moderated this year’s “Shark Tank” session, considered the highlight event of the meeting during which entrepreneurs present their ideas to a panel of doctors and business leaders to gain a diverse range of insight on how to take their projects to the next level.

Learn more about the AGA Center for GI Innovation and Technology at www.gastro.org/CGIT.

[email protected]

On Twitter @EAZTweets

BOSTON – Both the soon-to-be chair and vice chair of the AGA Center for GI Innovation and Technology, which sponsors the AGA Tech Summit, are looking forward to building upon the successes of this year’s meeting.

“Giving folks a road map and seeing physicians come to the meeting to network and meet the right people, that is the really satisfying part for me,” V. Raman Muthusamy, MD, the incoming chair of the committee, said in an interview.

“I was honored to be asked to take over this position,” he said. “I have been contemplating . . .where we are and where we’ve been and where we need to go next.”

Dr. Muthusamy, director of interventional endoscopy and general GI endoscopy and current professor of medicine at the University of California, Los Angeles, is keenly interested in the intersection of technical innovation and gastroenterology, especially concerning endoscopic technology.

The committee’s incoming vice chair, Srinadh Komanduri, MD, of Northwestern University’s Feinberg School of Medicine, Chicago, takes a deep interest in innovative medical technologies that are applicable to gastroenterology. “A lot of what I’m doing at Northwestern is cutting-edge techniques and looking for new innovation, especially for early cancers in the GI tract,” Dr. Komanduri said.

Dr. Muthusamy and Dr. Komanduri will assume their new roles June 1 when Michael L. Kochman, MD, AGAF, of the University of Pennsylvania, Philadelphia, retires from his position as executive chairman of the committee, shortly after the close of this year’s AGA Tech Summit. “It’s been an honor and humbling to have been entrusted with running the CGIT over the past term; we solidified a number of critical relationships and added new programs. I am thrilled that Raman and Sri will be taking the reins as the plans that they have will build on the foundation and take the CGIT to a new level.”

The meeting, according to the incoming chairs, offers a great opportunity for physician-innovators to share their interests and ideas.

“The Tech Summit is unlike any other meeting I’ve gone to. It is a time to see the business of science and the gaps in technology as well as the technicalities of business that are not part of the standard medical training,” said Dr. Muthusamy, who moderated this year’s “Shark Tank” session, considered the highlight event of the meeting during which entrepreneurs present their ideas to a panel of doctors and business leaders to gain a diverse range of insight on how to take their projects to the next level.

Learn more about the AGA Center for GI Innovation and Technology at www.gastro.org/CGIT.

[email protected]

On Twitter @EAZTweets

BOSTON – Both the soon-to-be chair and vice chair of the AGA Center for GI Innovation and Technology, which sponsors the AGA Tech Summit, are looking forward to building upon the successes of this year’s meeting.

“Giving folks a road map and seeing physicians come to the meeting to network and meet the right people, that is the really satisfying part for me,” V. Raman Muthusamy, MD, the incoming chair of the committee, said in an interview.

“I was honored to be asked to take over this position,” he said. “I have been contemplating . . .where we are and where we’ve been and where we need to go next.”

Dr. Muthusamy, director of interventional endoscopy and general GI endoscopy and current professor of medicine at the University of California, Los Angeles, is keenly interested in the intersection of technical innovation and gastroenterology, especially concerning endoscopic technology.

The committee’s incoming vice chair, Srinadh Komanduri, MD, of Northwestern University’s Feinberg School of Medicine, Chicago, takes a deep interest in innovative medical technologies that are applicable to gastroenterology. “A lot of what I’m doing at Northwestern is cutting-edge techniques and looking for new innovation, especially for early cancers in the GI tract,” Dr. Komanduri said.

Dr. Muthusamy and Dr. Komanduri will assume their new roles June 1 when Michael L. Kochman, MD, AGAF, of the University of Pennsylvania, Philadelphia, retires from his position as executive chairman of the committee, shortly after the close of this year’s AGA Tech Summit. “It’s been an honor and humbling to have been entrusted with running the CGIT over the past term; we solidified a number of critical relationships and added new programs. I am thrilled that Raman and Sri will be taking the reins as the plans that they have will build on the foundation and take the CGIT to a new level.”

The meeting, according to the incoming chairs, offers a great opportunity for physician-innovators to share their interests and ideas.

“The Tech Summit is unlike any other meeting I’ve gone to. It is a time to see the business of science and the gaps in technology as well as the technicalities of business that are not part of the standard medical training,” said Dr. Muthusamy, who moderated this year’s “Shark Tank” session, considered the highlight event of the meeting during which entrepreneurs present their ideas to a panel of doctors and business leaders to gain a diverse range of insight on how to take their projects to the next level.

Learn more about the AGA Center for GI Innovation and Technology at www.gastro.org/CGIT.

[email protected]

On Twitter @EAZTweets

Supply of the only U.S.-licensed yellow fever vaccine will be depleted by mid-2017 because of manufacturing issues, according to the Centers for Disease Control and Prevention.

Sanofi Pasteur, the manufacturer of the YF-VAX vaccine, notified the CDC and the Food and Drug Administration in 2016 there could be a shortage this year after the manufacturing complications during a factory switch over led to the loss of a large amount of vaccine supply, according to an article published online in the Morbidity and Mortality Weekly Report.

[email protected]

On Twitter @eaztweets

Supply of the only U.S.-licensed yellow fever vaccine will be depleted by mid-2017 because of manufacturing issues, according to the Centers for Disease Control and Prevention.

Sanofi Pasteur, the manufacturer of the YF-VAX vaccine, notified the CDC and the Food and Drug Administration in 2016 there could be a shortage this year after the manufacturing complications during a factory switch over led to the loss of a large amount of vaccine supply, according to an article published online in the Morbidity and Mortality Weekly Report.

[email protected]

On Twitter @eaztweets

Supply of the only U.S.-licensed yellow fever vaccine will be depleted by mid-2017 because of manufacturing issues, according to the Centers for Disease Control and Prevention.

Sanofi Pasteur, the manufacturer of the YF-VAX vaccine, notified the CDC and the Food and Drug Administration in 2016 there could be a shortage this year after the manufacturing complications during a factory switch over led to the loss of a large amount of vaccine supply, according to an article published online in the Morbidity and Mortality Weekly Report.

[email protected]

On Twitter @eaztweets

The deleterious impact of inappropriate and/or excessive antimicrobial usage is well recognized. In the United States, the Centers for Disease Control and Prevention (CDC) estimates that at least 2 million people become infected with antimicrobial-resistant bacteria with 23,000 subsequent deaths and at least $1 billion in excess medical costs per year.¹

In response, many healthcare organizations have developed antimicrobial stewardship programs (ASPs). Guidelines co-sponsored by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America, as well as recent statements from the CDC and the Transatlantic Taskforce on Antimicrobial Resistance, all recommend core ASP elements.^2-5 The guidelines provide general recommendations on ASP structure, strategies, and activities. The recommended ASP structure is a team of physicians and pharmacists that collaborates with facility governing committees and other stakeholders to optimize antimicrobial use. While personnel with expertise in infectious diseases (ID) often lead ASPs, hospitalists are also recognized as key contributors, especially in quality improvement.^6,7 Recommended strategies include prospective audit of antimicrobial use with intervention and feedback and formulary restriction with preauthorization. Recommended activities include education, creation of guidelines, clinical pathways, and order forms, and programs to promote de-escalation and conversion from parenteral (IV) to oral (PO) antimicrobial therapy. However, limited evidence exists regarding the effectiveness of these ASP core elements.^8,9 While Cochrane reviews found clear evidence that particular stewardship strategies (eg, audit and feedback, formulary restriction, guidelines implemented with or without feedback, protocols, computerized decision support) can be effective in reducing antimicrobial usage and improving clinical outcomes over the long term, little evidence exists favoring 1 strategy over another.⁸ Furthermore, most individual studies of ASPs are single-center, making their conclusions less generalizable.

In 2012, the VA National Antimicrobial Stewardship Task Force (ASTF), in conjunction with the VA Healthcare Analysis and Information Group (HAIG) administered a survey on the characteristics of ASPs at all 130 acute care VA facilities (Appendix A). We used these survey results to build an implementation model and then assess associations between facility-level variables and 4 antimicrobial utilization measures.

Survey and Data

In 2011, the ASTF was chartered to develop, deploy, and monitor a strategic plan for optimizing antimicrobial therapy management. Monthly educational webinars and sample policies were offered to all facilities, including a sample business plan for stewardship and policies to encourage de-escalation from broad-spectrum antimicrobials, promote conversion from parenteral to oral antimicrobial therapy, avoid unnecessary double anaerobic coverage, and mitigate unnecessary antimicrobial usage in the context of Clostridium difficile infection.¹⁰

At the time that ASTF was chartered, the understanding of how ASP structures across VA facilities operated was limited. Hence, to capture baseline institutional characteristics and stewardship activities, ASTF and HAIG developed an inventory assessment of ASPs that was distributed online in November 2012. All 130 VA facilities providing inpatient acute care services responded.

We derived 57 facility characteristics relevant to antimicrobial utilization and conducted a series of factor analyses to simplify the complex dataset, and identify underlying latent constructs. We categorized resulting factors into domains of evidence, context, or facilitation as guided by the Promoting Action on Research Implementation in Health Services framework.¹¹ Briefly, the evidence domain describes how the facility uses codified and noncodified sources of knowledge (eg, research evidence, clinical experience). Organizational context comprises a facility’s characteristics that ensure a more conducive environment to put evidence into practice (eg, supportive leadership, organizational structure, evaluative systems). Facilitation emphasizes a facility personnel’s “state of preparedness” and receptivity to implementation.

Using factor analysis to identify facility factors as correlates of the outcomes, we first examined polychoric correlations among facility characteristics to assess multicollinearity. We performed independent component analysis to create latent constructs of variables that were defined by factor loadings (that indicated the proportion of variance accounted for by the construct) and uniqueness factors (that determined how well the variables were interpreted by the construct). Factors retained included variables that had uniqueness values of less than 0.7 and factor loadings greater than 0.3. Those associated with uniqueness values greater than 0.7 were left as single items, as were characteristics deemed a priori to be particularly important to antimicrobial stewardship. Factor scales that had only 2 items were converted into indices, while factor scores were generated for those factors that contained 3 or more items.^12-15

Data for facility-level antimicrobial utilization measures were obtained from the VA Corporate Data Warehouse from calendar year 2012. The analysis was conducted within the VA Informatics and Computing Infrastructure. All study procedures were approved by the VA Central Institutional Review Board.

Measures

Four utilization measures were defined as dependent measures: overall antimicrobial use; antimicrobial use in patients with non-infectious discharge diagnoses; missed opportunities to convert from parenteral to oral antimicrobial therapy; and missed opportunities to avoid double anaerobic coverage with metronidazole.

Overall antimicrobial use was defined as total acute care (ie, medical/surgical/intensive care) antibacterial use for each facility aggregated as per CDC National Healthcare Safety Network Antimicrobial Use Option guidelines (antimicrobial days per 1000 patient days present). A subanalysis of overall antimicrobial use was restricted to antimicrobial use among patients without an infection-related discharge diagnosis, as we surmised that this measure may capture a greater proportion of potentially unnecessary antimicrobial use. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)¹⁶ codes for infectious processes were identified by a combination of those classified previously in the literature,¹⁷ and those identified by finding the descendants of all infections named in the Systematized Nomenclature of Medicine--Clinical Terms.¹⁸ Next, all remaining codes for principal discharge diagnoses for which antimicrobials were administered were reviewed for potential indications for systemic antibacterial use. Discharges were considered noninfectious if no codes were identified when systemic antimicrobials were or could be indicated. For this measure, antimicrobial days were not counted if administered on or 1 day after the calendar day of surgery warranting antimicrobial prophylaxis.

Missed opportunities for conversion from parenteral to oral (IV to PO) formulations of highly bioavailable oral antimicrobials (ciprofloxacin, levofloxacin, moxifloxacin, azithromycin, clindamycin, linezolid, metronidazole, and fluconazole) were defined as the percentage of days of unnecessary IV therapy that were given when PO therapy could have been used among patients who were not in intensive care units at the time of antimicrobial administration who were receiving other oral medications, using previously described methodology.¹⁹ Missed opportunities for avoiding redundant anaerobic coverage with metronidazole were defined as the percentage of days in which patients receiving metronidazole also received antibiotics with activity against anaerobic bacteria, specifically beta-lactam/beta-lactamase inhibitors, carbapenems, cefotetan/cefoxitin, clindamycin, moxifloxacin, or tigecycline), using previously described methodology.²⁰ Patients for whom C. difficile testing was either ordered or positive within the prior 28 days (indicating potential clinical concern for C. difficile infection) were excluded from this endpoint.

Analysis

The variables derived above were entered into a multivariable model for each of the 4 antimicrobial utilization measures. The least absolute shrinkage and selection operator (LASSO) regression was used to determine significant associations between variables and individual utilization measures.²¹ LASSO was chosen because it offers advantages over traditional subset selection approaches in large multivariable analyses by assessing covariates simultaneously rather than sequentially, supporting prediction rather than estimation of effect.²²P values were not reported as they are not useful in determining statistical significance in this methodology. A tuning parameter of 0.025 was determined for the model based on a cross-validation approach. Significant variables remaining in the model were reported with the percent change in each utilization measure per unit change in the variable of interest. For binary factors, percent change was reported according to whether the variable was present or not. For ordinal variables, percent change was reported according to incremental increase in ordinal score. For continuous variables or variables represented by factor or index scores, percent change was reported per each 25% increase in the range of the score.

Inpatient Facility Antimicrobial Stewardship Characteristics and Antimicrobial Utilization

Frequencies of key facility characteristics that contributed to variable development are included in Table 1. Full survey results across all facilities are included in Appendix B. Factor analysis reduced the total number of variables to 32; however, we also included hospital size and VA complexity score. Thus, 34 variables were evaluated for association with antimicrobial utilization measures: 4 in the evidence domain, 23 in the context domain, and 7 in the facilitation domain (Table 2).

Median facility antimicrobial use was 619 antimicrobial days per 1000 days present (interquartile range [IQR], 554-700; overall range, 346-974). Median facility noninfectious antimicrobial use was 236 per 1000 days present (IQR, 200-286). Missed opportunities for conversion from IV to PO antimicrobial therapy were common, with a median facility value of 40.4% (391/969) of potentially eligible days of therapy (IQR, 32.2-47.8%). Missed opportunities to avoid double anaerobic coverage were less common (median 15.3% (186/1214) of potentially eligible days of therapy (IQR, 11.8%-20.2%; Figure).

Overall Antimicrobial Use

Four variables were associated with decreased overall antimicrobial use, although with small magnitude of change: presence of postgraduate physician/pharmacy training programs (0.03% decrease per quarter increase in factor score; on the order of 0.2 antimicrobial days per 1000 patient days present), presence of pharmacists and/or ID attendings on general medicine ward teams (0.02% decrease per quarter increase in index score), frequency of systematic de-escalation review (0.01% decrease per ordinal increase in score), and degree of involvement of ID physicians and/or fellows in antimicrobial approvals (0.007% decrease per quarter increase in index score). No variables were associated with increased overall antimicrobial use.

Antimicrobial Use among Discharges without Infectious Diagnoses

Six variables were associated with decreased antimicrobial use in patients without infectious discharge diagnoses, while 4 variables were associated with increased use. Variables associated with the greatest magnitude of decreased use included facility educational programs for prudent antimicrobial use (1.8% on the order of 4 antimicrobial days per 1000 patient days present), frequency of systematic de-escalation review (1.5% per incremental increase in score), and whether a facility’s lead antimicrobial stewardship pharmacist had ID training (1.3%). Also significantly associated with decreased use was a factor summarizing the presence of 4 condition-specific stewardship processes (de-escalation policies, policies for addressing antimicrobial use in the context of C. difficile infection, blood culture review, and automatic ID consults for certain conditions) (0.6% per quarter increase in factor score range), the extent to which postgraduate physician/pharmacy training programs were present (0.6% per quarter increase in factor score range), and the number of electronic antimicrobial-specific order sets present (0.4% per order set). The variables associated with increased use of antimicrobials included the presence of antimicrobial stop orders (4.6%), the degree to which non-ID physicians were involved in antimicrobial approvals (0.7% per increase in ordinal score), the level engagement with ASTF online resources (0.6% per quarter increase in factor score range), and hospital size (0.6% per 50-bed increase).

Missed Opportunities for Parenteral to Oral Antimicrobial Conversion

Missed opportunities for IV to PO antimicrobial conversion had the largest number of significant associations with organizational variables: 14 variables were associated with fewer missed opportunities, while 5 were associated with greater missed opportunities. Variables associated with the largest reductions in missed opportunities for IV to PO conversion included having guidelines for antimicrobial duration (12.8%), participating in regional stewardship collaboratives (8.1%), number of antimicrobial-specific order sets (6.0% per order set), ID training of the ASP pharmacist (4.9%), and VA facility complexity designation (4.2% per quarter increase in score indicating greater complexity).²³ Variables associated with more missed opportunities included stop orders (11.7%), overall perceived receptiveness to antimicrobial stewardship among clinical services (9.4%), the degree of engagement with ASTF online resources (6.9% per quarter increase in factor score range), educational programs for prudent antimicrobial use (4.1%), and hospital size (1.0% per 50-bed increase).

Missed Opportunities for Avoidance of Double Anaerobic Coverage

Four variables were associated with more avoidance of double anaerobic coverage: ID training of the lead ASP pharmacist (8.8%), presence of pharmacists and/or ID attendings on acute care ward teams (6.2% per quarter increase in index score), degree of ID pharmacist involvement in antimicrobial approvals, ranging from not at all (score=0) to both weekdays and nights/weekends (score=2; 4.3% per ordinal increase), and the number of antimicrobial-specific order sets (1.5% per order set). No variables were associated with less avoidance of double anaerobic coverage.

Variables Associated with Multiple Favorable or Unfavorable Antimicrobial Utilization Measures

To better assess the consistency of the relationship between organizational variables and measures of antimicrobial use, we tabulated variables that were associated with at least 3 potentially favorable (ie, reduced overall or noninfectious antimicrobial use or fewer missed opportunities) measures. Altogether, 5 variables satisfied this criterion: the presence of postgraduate physician/pharmacy training programs, the number of antimicrobial-specific order sets, frequency of systematic de-escalation review, the presence of pharmacists and/or ID attendings on acute care ward teams, and formal ID training of the lead ASP pharmacist (Table 3). Three other variables were associated with at least 2 unfavorable measures: hospital size, the degree to which the facility engaged with ASTF online resources, and presence of antimicrobial stop orders.

Variability in ASP implementation across VA allowed us to assess the relationship between ASP and facility elements and baseline patterns of antimicrobial utilization. Hospitalists and hospital policy-makers are becoming more and more engaged in inpatient antimicrobial stewardship. While our results suggest that having pharmacists and/or physicians with formal ID training participate in everyday inpatient activities can favorably improve antimicrobial utilization, considerable input into stewardship can be made by hospitalists and policy makers. In particular, based on this work, the highest yield from an organizational standpoint may be in working to develop order sets within the electronic medical record and systematic efforts to promote de-escalation of broad-spectrum therapy, as well as encouraging hospital administration to devote specific physician and pharmacy salary support to stewardship efforts.

While we noted that finding the ASTF online resources helpful was associated with potentially unfavorable antimicrobial utilization, we speculate that this may represent reverse causality due to facilities recognizing that their antimicrobial usage is suboptimal and thus seeking out sample ASTF policies to implement. The association between the presence of automatic stop orders and potentially unfavorable antimicrobial utilization is less clear since the timeframe was not specified in the survey; it may be that setting stop orders too far in advance may promote an environment in which critical thinking about antimicrobial de-escalation is not encouraged or timely. The larger magnitude of association between ASP characteristics and antimicrobial usage among patients without infectious discharge diagnoses versus overall antimicrobial usage also suggests that clinical situations where infection was of low enough suspicion to not even have the providers eventually list an infectious diagnosis on their discharge summaries may be particularly malleable to ASP interventions, though further exploration is needed in determining how useful this utilization measure may be as a marker for inappropriate antimicrobial use.

Our results complement those of Pakyz et al.²⁴ who surveyed 44 academic medical facilities in March 2013 to develop an ASP intensity score and correlate this score and its specific components to overall and targeted antimicrobial use. This study found that the overall ASP intensity score was not significantly associated with total or targeted antimicrobial use. However, ASP strategies were more associated with decreased total and targeted antimicrobial use than were specific ASP resources. In particular, the presence of a preauthorization strategy was associated with decreased targeted antimicrobial use. Our particular findings that order set establishment and de-escalation efforts are associated with multiple antibiotic outcomes also line up with the findings of Schuts et al, who performed a meta-analysis of the effects of meeting antimicrobial stewardship objectives and found that achieving guideline concordance (such as through establishment of order sets) and successfully de-escalating antimicrobial therapy was associated with reduced mortality.^25,26 This meta-analysis, however, was limited by low rigor of its studies and potential for reverse causality. While our study has the advantages of capturing an entire national network of 130 acute care facilities with a 100% response rate, it, too, is limited by a number of issues, most notably by the fact that the survey was not specifically designed for the analysis of antimicrobial utilization measures, patient-level risk stratification was not available, the VA population does not reflect the U.S. population at-large, recall bias, and that antimicrobial prescribing and stewardship practices have evolved in VA since 2012. Furthermore, all of the antimicrobial utilization measures studied are imperfect at capturing inappropriate antibiotic use; in particular, our reliance on principal ICD-9 codes for noninfectious outcomes requires prospective validation. Many survey questions were subjective and subject to misinterpretation; other unmeasured confounders may also be present. Causality cannot be inferred from association. Nevertheless, our findings support many core indicators for hospital ASP recommended by the CDC and the Transatlantic Taskforce on Antimicrobial Resistance,^3,4 most notably, having personnel with ID training involved in stewardship and establishing a formal procedure for ASP review for the appropriateness of an antimicrobial at or after 48 hours from the initial order.

In summary, the VA has made efforts to advance the practice of antimicrobial stewardship system-wide, including a 2014 directive that all VA facilities have an ASP,²⁷ since the 2012 HAIG assessment reported considerable variability in antimicrobial utilization and antimicrobial stewardship activities. Our study identifies areas of stewardship that may correlate with, positively or negatively, antimicrobial utilization measures that will require further investigation. A repeat and more detailed antimicrobial stewardship survey was recently completed and will help VA gauge ongoing effects of ASTF activities. We hope to re-evaluate our model with newer data when available.

Acknowledgments

The authors wish to thank Michael Fletcher, Jaime Lopez, and Catherine Loc-Carrillo for their administrative and organizational support of the project and Allison Kelly, MD, for her pivotal role in survey development and distribution. This work was supported by the VA Health Services Research and Development Service Collaborative Research to Enhance and Advance Transformation and Excellence (CREATE) Initiative; Cognitive Support Informatics for Antimicrobial Stewardship project (CRE 12-313).

Disclosure

 The authors report no financial conflicts of interest.

The deleterious impact of inappropriate and/or excessive antimicrobial usage is well recognized. In the United States, the Centers for Disease Control and Prevention (CDC) estimates that at least 2 million people become infected with antimicrobial-resistant bacteria with 23,000 subsequent deaths and at least $1 billion in excess medical costs per year.¹

In response, many healthcare organizations have developed antimicrobial stewardship programs (ASPs). Guidelines co-sponsored by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America, as well as recent statements from the CDC and the Transatlantic Taskforce on Antimicrobial Resistance, all recommend core ASP elements.^2-5 The guidelines provide general recommendations on ASP structure, strategies, and activities. The recommended ASP structure is a team of physicians and pharmacists that collaborates with facility governing committees and other stakeholders to optimize antimicrobial use. While personnel with expertise in infectious diseases (ID) often lead ASPs, hospitalists are also recognized as key contributors, especially in quality improvement.^6,7 Recommended strategies include prospective audit of antimicrobial use with intervention and feedback and formulary restriction with preauthorization. Recommended activities include education, creation of guidelines, clinical pathways, and order forms, and programs to promote de-escalation and conversion from parenteral (IV) to oral (PO) antimicrobial therapy. However, limited evidence exists regarding the effectiveness of these ASP core elements.^8,9 While Cochrane reviews found clear evidence that particular stewardship strategies (eg, audit and feedback, formulary restriction, guidelines implemented with or without feedback, protocols, computerized decision support) can be effective in reducing antimicrobial usage and improving clinical outcomes over the long term, little evidence exists favoring 1 strategy over another.⁸ Furthermore, most individual studies of ASPs are single-center, making their conclusions less generalizable.

In 2012, the VA National Antimicrobial Stewardship Task Force (ASTF), in conjunction with the VA Healthcare Analysis and Information Group (HAIG) administered a survey on the characteristics of ASPs at all 130 acute care VA facilities (Appendix A). We used these survey results to build an implementation model and then assess associations between facility-level variables and 4 antimicrobial utilization measures.

Survey and Data

In 2011, the ASTF was chartered to develop, deploy, and monitor a strategic plan for optimizing antimicrobial therapy management. Monthly educational webinars and sample policies were offered to all facilities, including a sample business plan for stewardship and policies to encourage de-escalation from broad-spectrum antimicrobials, promote conversion from parenteral to oral antimicrobial therapy, avoid unnecessary double anaerobic coverage, and mitigate unnecessary antimicrobial usage in the context of Clostridium difficile infection.¹⁰

At the time that ASTF was chartered, the understanding of how ASP structures across VA facilities operated was limited. Hence, to capture baseline institutional characteristics and stewardship activities, ASTF and HAIG developed an inventory assessment of ASPs that was distributed online in November 2012. All 130 VA facilities providing inpatient acute care services responded.

We derived 57 facility characteristics relevant to antimicrobial utilization and conducted a series of factor analyses to simplify the complex dataset, and identify underlying latent constructs. We categorized resulting factors into domains of evidence, context, or facilitation as guided by the Promoting Action on Research Implementation in Health Services framework.¹¹ Briefly, the evidence domain describes how the facility uses codified and noncodified sources of knowledge (eg, research evidence, clinical experience). Organizational context comprises a facility’s characteristics that ensure a more conducive environment to put evidence into practice (eg, supportive leadership, organizational structure, evaluative systems). Facilitation emphasizes a facility personnel’s “state of preparedness” and receptivity to implementation.

Using factor analysis to identify facility factors as correlates of the outcomes, we first examined polychoric correlations among facility characteristics to assess multicollinearity. We performed independent component analysis to create latent constructs of variables that were defined by factor loadings (that indicated the proportion of variance accounted for by the construct) and uniqueness factors (that determined how well the variables were interpreted by the construct). Factors retained included variables that had uniqueness values of less than 0.7 and factor loadings greater than 0.3. Those associated with uniqueness values greater than 0.7 were left as single items, as were characteristics deemed a priori to be particularly important to antimicrobial stewardship. Factor scales that had only 2 items were converted into indices, while factor scores were generated for those factors that contained 3 or more items.^12-15

Data for facility-level antimicrobial utilization measures were obtained from the VA Corporate Data Warehouse from calendar year 2012. The analysis was conducted within the VA Informatics and Computing Infrastructure. All study procedures were approved by the VA Central Institutional Review Board.

Measures

Four utilization measures were defined as dependent measures: overall antimicrobial use; antimicrobial use in patients with non-infectious discharge diagnoses; missed opportunities to convert from parenteral to oral antimicrobial therapy; and missed opportunities to avoid double anaerobic coverage with metronidazole.

Overall antimicrobial use was defined as total acute care (ie, medical/surgical/intensive care) antibacterial use for each facility aggregated as per CDC National Healthcare Safety Network Antimicrobial Use Option guidelines (antimicrobial days per 1000 patient days present). A subanalysis of overall antimicrobial use was restricted to antimicrobial use among patients without an infection-related discharge diagnosis, as we surmised that this measure may capture a greater proportion of potentially unnecessary antimicrobial use. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)¹⁶ codes for infectious processes were identified by a combination of those classified previously in the literature,¹⁷ and those identified by finding the descendants of all infections named in the Systematized Nomenclature of Medicine--Clinical Terms.¹⁸ Next, all remaining codes for principal discharge diagnoses for which antimicrobials were administered were reviewed for potential indications for systemic antibacterial use. Discharges were considered noninfectious if no codes were identified when systemic antimicrobials were or could be indicated. For this measure, antimicrobial days were not counted if administered on or 1 day after the calendar day of surgery warranting antimicrobial prophylaxis.

Missed opportunities for conversion from parenteral to oral (IV to PO) formulations of highly bioavailable oral antimicrobials (ciprofloxacin, levofloxacin, moxifloxacin, azithromycin, clindamycin, linezolid, metronidazole, and fluconazole) were defined as the percentage of days of unnecessary IV therapy that were given when PO therapy could have been used among patients who were not in intensive care units at the time of antimicrobial administration who were receiving other oral medications, using previously described methodology.¹⁹ Missed opportunities for avoiding redundant anaerobic coverage with metronidazole were defined as the percentage of days in which patients receiving metronidazole also received antibiotics with activity against anaerobic bacteria, specifically beta-lactam/beta-lactamase inhibitors, carbapenems, cefotetan/cefoxitin, clindamycin, moxifloxacin, or tigecycline), using previously described methodology.²⁰ Patients for whom C. difficile testing was either ordered or positive within the prior 28 days (indicating potential clinical concern for C. difficile infection) were excluded from this endpoint.

Analysis

The variables derived above were entered into a multivariable model for each of the 4 antimicrobial utilization measures. The least absolute shrinkage and selection operator (LASSO) regression was used to determine significant associations between variables and individual utilization measures.²¹ LASSO was chosen because it offers advantages over traditional subset selection approaches in large multivariable analyses by assessing covariates simultaneously rather than sequentially, supporting prediction rather than estimation of effect.²²P values were not reported as they are not useful in determining statistical significance in this methodology. A tuning parameter of 0.025 was determined for the model based on a cross-validation approach. Significant variables remaining in the model were reported with the percent change in each utilization measure per unit change in the variable of interest. For binary factors, percent change was reported according to whether the variable was present or not. For ordinal variables, percent change was reported according to incremental increase in ordinal score. For continuous variables or variables represented by factor or index scores, percent change was reported per each 25% increase in the range of the score.

Inpatient Facility Antimicrobial Stewardship Characteristics and Antimicrobial Utilization

Frequencies of key facility characteristics that contributed to variable development are included in Table 1. Full survey results across all facilities are included in Appendix B. Factor analysis reduced the total number of variables to 32; however, we also included hospital size and VA complexity score. Thus, 34 variables were evaluated for association with antimicrobial utilization measures: 4 in the evidence domain, 23 in the context domain, and 7 in the facilitation domain (Table 2).

Median facility antimicrobial use was 619 antimicrobial days per 1000 days present (interquartile range [IQR], 554-700; overall range, 346-974). Median facility noninfectious antimicrobial use was 236 per 1000 days present (IQR, 200-286). Missed opportunities for conversion from IV to PO antimicrobial therapy were common, with a median facility value of 40.4% (391/969) of potentially eligible days of therapy (IQR, 32.2-47.8%). Missed opportunities to avoid double anaerobic coverage were less common (median 15.3% (186/1214) of potentially eligible days of therapy (IQR, 11.8%-20.2%; Figure).

Overall Antimicrobial Use

Four variables were associated with decreased overall antimicrobial use, although with small magnitude of change: presence of postgraduate physician/pharmacy training programs (0.03% decrease per quarter increase in factor score; on the order of 0.2 antimicrobial days per 1000 patient days present), presence of pharmacists and/or ID attendings on general medicine ward teams (0.02% decrease per quarter increase in index score), frequency of systematic de-escalation review (0.01% decrease per ordinal increase in score), and degree of involvement of ID physicians and/or fellows in antimicrobial approvals (0.007% decrease per quarter increase in index score). No variables were associated with increased overall antimicrobial use.

Antimicrobial Use among Discharges without Infectious Diagnoses

Six variables were associated with decreased antimicrobial use in patients without infectious discharge diagnoses, while 4 variables were associated with increased use. Variables associated with the greatest magnitude of decreased use included facility educational programs for prudent antimicrobial use (1.8% on the order of 4 antimicrobial days per 1000 patient days present), frequency of systematic de-escalation review (1.5% per incremental increase in score), and whether a facility’s lead antimicrobial stewardship pharmacist had ID training (1.3%). Also significantly associated with decreased use was a factor summarizing the presence of 4 condition-specific stewardship processes (de-escalation policies, policies for addressing antimicrobial use in the context of C. difficile infection, blood culture review, and automatic ID consults for certain conditions) (0.6% per quarter increase in factor score range), the extent to which postgraduate physician/pharmacy training programs were present (0.6% per quarter increase in factor score range), and the number of electronic antimicrobial-specific order sets present (0.4% per order set). The variables associated with increased use of antimicrobials included the presence of antimicrobial stop orders (4.6%), the degree to which non-ID physicians were involved in antimicrobial approvals (0.7% per increase in ordinal score), the level engagement with ASTF online resources (0.6% per quarter increase in factor score range), and hospital size (0.6% per 50-bed increase).

Missed Opportunities for Parenteral to Oral Antimicrobial Conversion

Missed opportunities for IV to PO antimicrobial conversion had the largest number of significant associations with organizational variables: 14 variables were associated with fewer missed opportunities, while 5 were associated with greater missed opportunities. Variables associated with the largest reductions in missed opportunities for IV to PO conversion included having guidelines for antimicrobial duration (12.8%), participating in regional stewardship collaboratives (8.1%), number of antimicrobial-specific order sets (6.0% per order set), ID training of the ASP pharmacist (4.9%), and VA facility complexity designation (4.2% per quarter increase in score indicating greater complexity).²³ Variables associated with more missed opportunities included stop orders (11.7%), overall perceived receptiveness to antimicrobial stewardship among clinical services (9.4%), the degree of engagement with ASTF online resources (6.9% per quarter increase in factor score range), educational programs for prudent antimicrobial use (4.1%), and hospital size (1.0% per 50-bed increase).

Missed Opportunities for Avoidance of Double Anaerobic Coverage

Four variables were associated with more avoidance of double anaerobic coverage: ID training of the lead ASP pharmacist (8.8%), presence of pharmacists and/or ID attendings on acute care ward teams (6.2% per quarter increase in index score), degree of ID pharmacist involvement in antimicrobial approvals, ranging from not at all (score=0) to both weekdays and nights/weekends (score=2; 4.3% per ordinal increase), and the number of antimicrobial-specific order sets (1.5% per order set). No variables were associated with less avoidance of double anaerobic coverage.

Variables Associated with Multiple Favorable or Unfavorable Antimicrobial Utilization Measures

To better assess the consistency of the relationship between organizational variables and measures of antimicrobial use, we tabulated variables that were associated with at least 3 potentially favorable (ie, reduced overall or noninfectious antimicrobial use or fewer missed opportunities) measures. Altogether, 5 variables satisfied this criterion: the presence of postgraduate physician/pharmacy training programs, the number of antimicrobial-specific order sets, frequency of systematic de-escalation review, the presence of pharmacists and/or ID attendings on acute care ward teams, and formal ID training of the lead ASP pharmacist (Table 3). Three other variables were associated with at least 2 unfavorable measures: hospital size, the degree to which the facility engaged with ASTF online resources, and presence of antimicrobial stop orders.

Variability in ASP implementation across VA allowed us to assess the relationship between ASP and facility elements and baseline patterns of antimicrobial utilization. Hospitalists and hospital policy-makers are becoming more and more engaged in inpatient antimicrobial stewardship. While our results suggest that having pharmacists and/or physicians with formal ID training participate in everyday inpatient activities can favorably improve antimicrobial utilization, considerable input into stewardship can be made by hospitalists and policy makers. In particular, based on this work, the highest yield from an organizational standpoint may be in working to develop order sets within the electronic medical record and systematic efforts to promote de-escalation of broad-spectrum therapy, as well as encouraging hospital administration to devote specific physician and pharmacy salary support to stewardship efforts.

While we noted that finding the ASTF online resources helpful was associated with potentially unfavorable antimicrobial utilization, we speculate that this may represent reverse causality due to facilities recognizing that their antimicrobial usage is suboptimal and thus seeking out sample ASTF policies to implement. The association between the presence of automatic stop orders and potentially unfavorable antimicrobial utilization is less clear since the timeframe was not specified in the survey; it may be that setting stop orders too far in advance may promote an environment in which critical thinking about antimicrobial de-escalation is not encouraged or timely. The larger magnitude of association between ASP characteristics and antimicrobial usage among patients without infectious discharge diagnoses versus overall antimicrobial usage also suggests that clinical situations where infection was of low enough suspicion to not even have the providers eventually list an infectious diagnosis on their discharge summaries may be particularly malleable to ASP interventions, though further exploration is needed in determining how useful this utilization measure may be as a marker for inappropriate antimicrobial use.

Our results complement those of Pakyz et al.²⁴ who surveyed 44 academic medical facilities in March 2013 to develop an ASP intensity score and correlate this score and its specific components to overall and targeted antimicrobial use. This study found that the overall ASP intensity score was not significantly associated with total or targeted antimicrobial use. However, ASP strategies were more associated with decreased total and targeted antimicrobial use than were specific ASP resources. In particular, the presence of a preauthorization strategy was associated with decreased targeted antimicrobial use. Our particular findings that order set establishment and de-escalation efforts are associated with multiple antibiotic outcomes also line up with the findings of Schuts et al, who performed a meta-analysis of the effects of meeting antimicrobial stewardship objectives and found that achieving guideline concordance (such as through establishment of order sets) and successfully de-escalating antimicrobial therapy was associated with reduced mortality.^25,26 This meta-analysis, however, was limited by low rigor of its studies and potential for reverse causality. While our study has the advantages of capturing an entire national network of 130 acute care facilities with a 100% response rate, it, too, is limited by a number of issues, most notably by the fact that the survey was not specifically designed for the analysis of antimicrobial utilization measures, patient-level risk stratification was not available, the VA population does not reflect the U.S. population at-large, recall bias, and that antimicrobial prescribing and stewardship practices have evolved in VA since 2012. Furthermore, all of the antimicrobial utilization measures studied are imperfect at capturing inappropriate antibiotic use; in particular, our reliance on principal ICD-9 codes for noninfectious outcomes requires prospective validation. Many survey questions were subjective and subject to misinterpretation; other unmeasured confounders may also be present. Causality cannot be inferred from association. Nevertheless, our findings support many core indicators for hospital ASP recommended by the CDC and the Transatlantic Taskforce on Antimicrobial Resistance,^3,4 most notably, having personnel with ID training involved in stewardship and establishing a formal procedure for ASP review for the appropriateness of an antimicrobial at or after 48 hours from the initial order.

In summary, the VA has made efforts to advance the practice of antimicrobial stewardship system-wide, including a 2014 directive that all VA facilities have an ASP,²⁷ since the 2012 HAIG assessment reported considerable variability in antimicrobial utilization and antimicrobial stewardship activities. Our study identifies areas of stewardship that may correlate with, positively or negatively, antimicrobial utilization measures that will require further investigation. A repeat and more detailed antimicrobial stewardship survey was recently completed and will help VA gauge ongoing effects of ASTF activities. We hope to re-evaluate our model with newer data when available.

Acknowledgments

The authors wish to thank Michael Fletcher, Jaime Lopez, and Catherine Loc-Carrillo for their administrative and organizational support of the project and Allison Kelly, MD, for her pivotal role in survey development and distribution. This work was supported by the VA Health Services Research and Development Service Collaborative Research to Enhance and Advance Transformation and Excellence (CREATE) Initiative; Cognitive Support Informatics for Antimicrobial Stewardship project (CRE 12-313).

Disclosure

 The authors report no financial conflicts of interest.

The deleterious impact of inappropriate and/or excessive antimicrobial usage is well recognized. In the United States, the Centers for Disease Control and Prevention (CDC) estimates that at least 2 million people become infected with antimicrobial-resistant bacteria with 23,000 subsequent deaths and at least $1 billion in excess medical costs per year.¹

In response, many healthcare organizations have developed antimicrobial stewardship programs (ASPs). Guidelines co-sponsored by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America, as well as recent statements from the CDC and the Transatlantic Taskforce on Antimicrobial Resistance, all recommend core ASP elements.^2-5 The guidelines provide general recommendations on ASP structure, strategies, and activities. The recommended ASP structure is a team of physicians and pharmacists that collaborates with facility governing committees and other stakeholders to optimize antimicrobial use. While personnel with expertise in infectious diseases (ID) often lead ASPs, hospitalists are also recognized as key contributors, especially in quality improvement.^6,7 Recommended strategies include prospective audit of antimicrobial use with intervention and feedback and formulary restriction with preauthorization. Recommended activities include education, creation of guidelines, clinical pathways, and order forms, and programs to promote de-escalation and conversion from parenteral (IV) to oral (PO) antimicrobial therapy. However, limited evidence exists regarding the effectiveness of these ASP core elements.^8,9 While Cochrane reviews found clear evidence that particular stewardship strategies (eg, audit and feedback, formulary restriction, guidelines implemented with or without feedback, protocols, computerized decision support) can be effective in reducing antimicrobial usage and improving clinical outcomes over the long term, little evidence exists favoring 1 strategy over another.⁸ Furthermore, most individual studies of ASPs are single-center, making their conclusions less generalizable.

In 2012, the VA National Antimicrobial Stewardship Task Force (ASTF), in conjunction with the VA Healthcare Analysis and Information Group (HAIG) administered a survey on the characteristics of ASPs at all 130 acute care VA facilities (Appendix A). We used these survey results to build an implementation model and then assess associations between facility-level variables and 4 antimicrobial utilization measures.

Survey and Data

In 2011, the ASTF was chartered to develop, deploy, and monitor a strategic plan for optimizing antimicrobial therapy management. Monthly educational webinars and sample policies were offered to all facilities, including a sample business plan for stewardship and policies to encourage de-escalation from broad-spectrum antimicrobials, promote conversion from parenteral to oral antimicrobial therapy, avoid unnecessary double anaerobic coverage, and mitigate unnecessary antimicrobial usage in the context of Clostridium difficile infection.¹⁰

At the time that ASTF was chartered, the understanding of how ASP structures across VA facilities operated was limited. Hence, to capture baseline institutional characteristics and stewardship activities, ASTF and HAIG developed an inventory assessment of ASPs that was distributed online in November 2012. All 130 VA facilities providing inpatient acute care services responded.

We derived 57 facility characteristics relevant to antimicrobial utilization and conducted a series of factor analyses to simplify the complex dataset, and identify underlying latent constructs. We categorized resulting factors into domains of evidence, context, or facilitation as guided by the Promoting Action on Research Implementation in Health Services framework.¹¹ Briefly, the evidence domain describes how the facility uses codified and noncodified sources of knowledge (eg, research evidence, clinical experience). Organizational context comprises a facility’s characteristics that ensure a more conducive environment to put evidence into practice (eg, supportive leadership, organizational structure, evaluative systems). Facilitation emphasizes a facility personnel’s “state of preparedness” and receptivity to implementation.

Using factor analysis to identify facility factors as correlates of the outcomes, we first examined polychoric correlations among facility characteristics to assess multicollinearity. We performed independent component analysis to create latent constructs of variables that were defined by factor loadings (that indicated the proportion of variance accounted for by the construct) and uniqueness factors (that determined how well the variables were interpreted by the construct). Factors retained included variables that had uniqueness values of less than 0.7 and factor loadings greater than 0.3. Those associated with uniqueness values greater than 0.7 were left as single items, as were characteristics deemed a priori to be particularly important to antimicrobial stewardship. Factor scales that had only 2 items were converted into indices, while factor scores were generated for those factors that contained 3 or more items.^12-15

Data for facility-level antimicrobial utilization measures were obtained from the VA Corporate Data Warehouse from calendar year 2012. The analysis was conducted within the VA Informatics and Computing Infrastructure. All study procedures were approved by the VA Central Institutional Review Board.

Measures

Four utilization measures were defined as dependent measures: overall antimicrobial use; antimicrobial use in patients with non-infectious discharge diagnoses; missed opportunities to convert from parenteral to oral antimicrobial therapy; and missed opportunities to avoid double anaerobic coverage with metronidazole.

Overall antimicrobial use was defined as total acute care (ie, medical/surgical/intensive care) antibacterial use for each facility aggregated as per CDC National Healthcare Safety Network Antimicrobial Use Option guidelines (antimicrobial days per 1000 patient days present). A subanalysis of overall antimicrobial use was restricted to antimicrobial use among patients without an infection-related discharge diagnosis, as we surmised that this measure may capture a greater proportion of potentially unnecessary antimicrobial use. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)¹⁶ codes for infectious processes were identified by a combination of those classified previously in the literature,¹⁷ and those identified by finding the descendants of all infections named in the Systematized Nomenclature of Medicine--Clinical Terms.¹⁸ Next, all remaining codes for principal discharge diagnoses for which antimicrobials were administered were reviewed for potential indications for systemic antibacterial use. Discharges were considered noninfectious if no codes were identified when systemic antimicrobials were or could be indicated. For this measure, antimicrobial days were not counted if administered on or 1 day after the calendar day of surgery warranting antimicrobial prophylaxis.

Missed opportunities for conversion from parenteral to oral (IV to PO) formulations of highly bioavailable oral antimicrobials (ciprofloxacin, levofloxacin, moxifloxacin, azithromycin, clindamycin, linezolid, metronidazole, and fluconazole) were defined as the percentage of days of unnecessary IV therapy that were given when PO therapy could have been used among patients who were not in intensive care units at the time of antimicrobial administration who were receiving other oral medications, using previously described methodology.¹⁹ Missed opportunities for avoiding redundant anaerobic coverage with metronidazole were defined as the percentage of days in which patients receiving metronidazole also received antibiotics with activity against anaerobic bacteria, specifically beta-lactam/beta-lactamase inhibitors, carbapenems, cefotetan/cefoxitin, clindamycin, moxifloxacin, or tigecycline), using previously described methodology.²⁰ Patients for whom C. difficile testing was either ordered or positive within the prior 28 days (indicating potential clinical concern for C. difficile infection) were excluded from this endpoint.

Analysis

The variables derived above were entered into a multivariable model for each of the 4 antimicrobial utilization measures. The least absolute shrinkage and selection operator (LASSO) regression was used to determine significant associations between variables and individual utilization measures.²¹ LASSO was chosen because it offers advantages over traditional subset selection approaches in large multivariable analyses by assessing covariates simultaneously rather than sequentially, supporting prediction rather than estimation of effect.²²P values were not reported as they are not useful in determining statistical significance in this methodology. A tuning parameter of 0.025 was determined for the model based on a cross-validation approach. Significant variables remaining in the model were reported with the percent change in each utilization measure per unit change in the variable of interest. For binary factors, percent change was reported according to whether the variable was present or not. For ordinal variables, percent change was reported according to incremental increase in ordinal score. For continuous variables or variables represented by factor or index scores, percent change was reported per each 25% increase in the range of the score.

Inpatient Facility Antimicrobial Stewardship Characteristics and Antimicrobial Utilization

Frequencies of key facility characteristics that contributed to variable development are included in Table 1. Full survey results across all facilities are included in Appendix B. Factor analysis reduced the total number of variables to 32; however, we also included hospital size and VA complexity score. Thus, 34 variables were evaluated for association with antimicrobial utilization measures: 4 in the evidence domain, 23 in the context domain, and 7 in the facilitation domain (Table 2).

Median facility antimicrobial use was 619 antimicrobial days per 1000 days present (interquartile range [IQR], 554-700; overall range, 346-974). Median facility noninfectious antimicrobial use was 236 per 1000 days present (IQR, 200-286). Missed opportunities for conversion from IV to PO antimicrobial therapy were common, with a median facility value of 40.4% (391/969) of potentially eligible days of therapy (IQR, 32.2-47.8%). Missed opportunities to avoid double anaerobic coverage were less common (median 15.3% (186/1214) of potentially eligible days of therapy (IQR, 11.8%-20.2%; Figure).

Overall Antimicrobial Use

Four variables were associated with decreased overall antimicrobial use, although with small magnitude of change: presence of postgraduate physician/pharmacy training programs (0.03% decrease per quarter increase in factor score; on the order of 0.2 antimicrobial days per 1000 patient days present), presence of pharmacists and/or ID attendings on general medicine ward teams (0.02% decrease per quarter increase in index score), frequency of systematic de-escalation review (0.01% decrease per ordinal increase in score), and degree of involvement of ID physicians and/or fellows in antimicrobial approvals (0.007% decrease per quarter increase in index score). No variables were associated with increased overall antimicrobial use.

Antimicrobial Use among Discharges without Infectious Diagnoses

Six variables were associated with decreased antimicrobial use in patients without infectious discharge diagnoses, while 4 variables were associated with increased use. Variables associated with the greatest magnitude of decreased use included facility educational programs for prudent antimicrobial use (1.8% on the order of 4 antimicrobial days per 1000 patient days present), frequency of systematic de-escalation review (1.5% per incremental increase in score), and whether a facility’s lead antimicrobial stewardship pharmacist had ID training (1.3%). Also significantly associated with decreased use was a factor summarizing the presence of 4 condition-specific stewardship processes (de-escalation policies, policies for addressing antimicrobial use in the context of C. difficile infection, blood culture review, and automatic ID consults for certain conditions) (0.6% per quarter increase in factor score range), the extent to which postgraduate physician/pharmacy training programs were present (0.6% per quarter increase in factor score range), and the number of electronic antimicrobial-specific order sets present (0.4% per order set). The variables associated with increased use of antimicrobials included the presence of antimicrobial stop orders (4.6%), the degree to which non-ID physicians were involved in antimicrobial approvals (0.7% per increase in ordinal score), the level engagement with ASTF online resources (0.6% per quarter increase in factor score range), and hospital size (0.6% per 50-bed increase).

Missed Opportunities for Parenteral to Oral Antimicrobial Conversion

Missed opportunities for IV to PO antimicrobial conversion had the largest number of significant associations with organizational variables: 14 variables were associated with fewer missed opportunities, while 5 were associated with greater missed opportunities. Variables associated with the largest reductions in missed opportunities for IV to PO conversion included having guidelines for antimicrobial duration (12.8%), participating in regional stewardship collaboratives (8.1%), number of antimicrobial-specific order sets (6.0% per order set), ID training of the ASP pharmacist (4.9%), and VA facility complexity designation (4.2% per quarter increase in score indicating greater complexity).²³ Variables associated with more missed opportunities included stop orders (11.7%), overall perceived receptiveness to antimicrobial stewardship among clinical services (9.4%), the degree of engagement with ASTF online resources (6.9% per quarter increase in factor score range), educational programs for prudent antimicrobial use (4.1%), and hospital size (1.0% per 50-bed increase).

Missed Opportunities for Avoidance of Double Anaerobic Coverage

Four variables were associated with more avoidance of double anaerobic coverage: ID training of the lead ASP pharmacist (8.8%), presence of pharmacists and/or ID attendings on acute care ward teams (6.2% per quarter increase in index score), degree of ID pharmacist involvement in antimicrobial approvals, ranging from not at all (score=0) to both weekdays and nights/weekends (score=2; 4.3% per ordinal increase), and the number of antimicrobial-specific order sets (1.5% per order set). No variables were associated with less avoidance of double anaerobic coverage.

Variables Associated with Multiple Favorable or Unfavorable Antimicrobial Utilization Measures

To better assess the consistency of the relationship between organizational variables and measures of antimicrobial use, we tabulated variables that were associated with at least 3 potentially favorable (ie, reduced overall or noninfectious antimicrobial use or fewer missed opportunities) measures. Altogether, 5 variables satisfied this criterion: the presence of postgraduate physician/pharmacy training programs, the number of antimicrobial-specific order sets, frequency of systematic de-escalation review, the presence of pharmacists and/or ID attendings on acute care ward teams, and formal ID training of the lead ASP pharmacist (Table 3). Three other variables were associated with at least 2 unfavorable measures: hospital size, the degree to which the facility engaged with ASTF online resources, and presence of antimicrobial stop orders.

Variability in ASP implementation across VA allowed us to assess the relationship between ASP and facility elements and baseline patterns of antimicrobial utilization. Hospitalists and hospital policy-makers are becoming more and more engaged in inpatient antimicrobial stewardship. While our results suggest that having pharmacists and/or physicians with formal ID training participate in everyday inpatient activities can favorably improve antimicrobial utilization, considerable input into stewardship can be made by hospitalists and policy makers. In particular, based on this work, the highest yield from an organizational standpoint may be in working to develop order sets within the electronic medical record and systematic efforts to promote de-escalation of broad-spectrum therapy, as well as encouraging hospital administration to devote specific physician and pharmacy salary support to stewardship efforts.

While we noted that finding the ASTF online resources helpful was associated with potentially unfavorable antimicrobial utilization, we speculate that this may represent reverse causality due to facilities recognizing that their antimicrobial usage is suboptimal and thus seeking out sample ASTF policies to implement. The association between the presence of automatic stop orders and potentially unfavorable antimicrobial utilization is less clear since the timeframe was not specified in the survey; it may be that setting stop orders too far in advance may promote an environment in which critical thinking about antimicrobial de-escalation is not encouraged or timely. The larger magnitude of association between ASP characteristics and antimicrobial usage among patients without infectious discharge diagnoses versus overall antimicrobial usage also suggests that clinical situations where infection was of low enough suspicion to not even have the providers eventually list an infectious diagnosis on their discharge summaries may be particularly malleable to ASP interventions, though further exploration is needed in determining how useful this utilization measure may be as a marker for inappropriate antimicrobial use.

Our results complement those of Pakyz et al.²⁴ who surveyed 44 academic medical facilities in March 2013 to develop an ASP intensity score and correlate this score and its specific components to overall and targeted antimicrobial use. This study found that the overall ASP intensity score was not significantly associated with total or targeted antimicrobial use. However, ASP strategies were more associated with decreased total and targeted antimicrobial use than were specific ASP resources. In particular, the presence of a preauthorization strategy was associated with decreased targeted antimicrobial use. Our particular findings that order set establishment and de-escalation efforts are associated with multiple antibiotic outcomes also line up with the findings of Schuts et al, who performed a meta-analysis of the effects of meeting antimicrobial stewardship objectives and found that achieving guideline concordance (such as through establishment of order sets) and successfully de-escalating antimicrobial therapy was associated with reduced mortality.^25,26 This meta-analysis, however, was limited by low rigor of its studies and potential for reverse causality. While our study has the advantages of capturing an entire national network of 130 acute care facilities with a 100% response rate, it, too, is limited by a number of issues, most notably by the fact that the survey was not specifically designed for the analysis of antimicrobial utilization measures, patient-level risk stratification was not available, the VA population does not reflect the U.S. population at-large, recall bias, and that antimicrobial prescribing and stewardship practices have evolved in VA since 2012. Furthermore, all of the antimicrobial utilization measures studied are imperfect at capturing inappropriate antibiotic use; in particular, our reliance on principal ICD-9 codes for noninfectious outcomes requires prospective validation. Many survey questions were subjective and subject to misinterpretation; other unmeasured confounders may also be present. Causality cannot be inferred from association. Nevertheless, our findings support many core indicators for hospital ASP recommended by the CDC and the Transatlantic Taskforce on Antimicrobial Resistance,^3,4 most notably, having personnel with ID training involved in stewardship and establishing a formal procedure for ASP review for the appropriateness of an antimicrobial at or after 48 hours from the initial order.

In summary, the VA has made efforts to advance the practice of antimicrobial stewardship system-wide, including a 2014 directive that all VA facilities have an ASP,²⁷ since the 2012 HAIG assessment reported considerable variability in antimicrobial utilization and antimicrobial stewardship activities. Our study identifies areas of stewardship that may correlate with, positively or negatively, antimicrobial utilization measures that will require further investigation. A repeat and more detailed antimicrobial stewardship survey was recently completed and will help VA gauge ongoing effects of ASTF activities. We hope to re-evaluate our model with newer data when available.

Acknowledgments

The authors wish to thank Michael Fletcher, Jaime Lopez, and Catherine Loc-Carrillo for their administrative and organizational support of the project and Allison Kelly, MD, for her pivotal role in survey development and distribution. This work was supported by the VA Health Services Research and Development Service Collaborative Research to Enhance and Advance Transformation and Excellence (CREATE) Initiative; Cognitive Support Informatics for Antimicrobial Stewardship project (CRE 12-313).

Disclosure

 The authors report no financial conflicts of interest.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.