Younger age at diagnosis of breast cancer predicts poor survival only with certain molecular subtypes of tumor, according to a report published online Aug. 1 in the Journal of Clinical Oncology.

An age of 40 years or younger “has long been considered a poor prognostic factor, because young women, on average, have an increased risk of disease recurrence and decreased survival. In recent years, however, with improved understanding of tumor biology, this assertion has been challenged with increased recognition of the prognostic and predictive role of tumor subtype and awareness that young women are more likely to develop more aggressive phenotypes,” said Ann H. Partridge, MD, of the Dana-Farber Cancer Institute, and Brigham and Women’s Hospital, both in Boston, and her associates.

To examine the relationships among patient age, tumor subtypes, and outcomes, they analyzed data for 17,575 women treated at eight U.S. cancer centers in 2000-2007 and enrolled in a National Comprehensive Cancer Network registry. The study participants (mean age, 35 years) all had newly diagnosed unilateral stage I, II, or III breast cancer and were followed for a median of 6.4 years. Their data were stratified by age at diagnosis: 40 years or younger, 41-50 years, 51-60 years, 61-70 years, or over 70 years.

In the initial analysis, younger women were 90% more likely to die of breast cancer than older women. This probability decreased to 50% when the data were adjusted to control for treatment, stage at diagnosis, and tumor grade, then decreased further to 30% when the data were further adjusted to control for tumor molecular subtype and method of detection, the investigators said (J Clin Oncol. 2016 Aug 1; doi:10.1200/JCO.2015.65.8013).

However, when the data were analyzed according to tumor subtype, women who had luminal A breast cancer (7,738 participants) were more than twice as likely to die of their disease if they were aged 40 or younger at diagnosis than if they were older (hazard ratio, 2.1). The age-related increase in risk was slightly lower for luminal B breast cancer (HR, 1.4), and appeared to be largely confined to those with HER2-negative luminal B tumors.

There also was a borderline increased risk of death in younger women who had triple-negative breast cancer (HR, 1.4), compared with older women who had that tumor subtype. In contrast, younger age did not correlate with increased breast cancer mortality among women with HER2-positive disease.

These findings “support the growing evidence that the relationship between age at diagnosis and breast-cancer-specific survival varies by tumor subtype, which has implications for both treatment decisions and future research directions. ....In women with luminal disease, younger age does have a substantial prognostic role, which may reflect inadequate therapy, including lower treatment efficacy and less therapeutic adherence and persistence, as well as residual differences in tumor biology,” Dr. Partridge and her associates said.

No specific source of funding was identified for this study. Dr. Partridge reported serving as a consultant for Pfizer; her associates reported ties to Pfizer, Tokai, Bristol-Myers Squibb, Carevive Systems, Oncothyreon, Amgen, and BeyondSpring Pharmaceuticals.

Younger age at diagnosis of breast cancer predicts poor survival only with certain molecular subtypes of tumor, according to a report published online Aug. 1 in the Journal of Clinical Oncology.

An age of 40 years or younger “has long been considered a poor prognostic factor, because young women, on average, have an increased risk of disease recurrence and decreased survival. In recent years, however, with improved understanding of tumor biology, this assertion has been challenged with increased recognition of the prognostic and predictive role of tumor subtype and awareness that young women are more likely to develop more aggressive phenotypes,” said Ann H. Partridge, MD, of the Dana-Farber Cancer Institute, and Brigham and Women’s Hospital, both in Boston, and her associates.

To examine the relationships among patient age, tumor subtypes, and outcomes, they analyzed data for 17,575 women treated at eight U.S. cancer centers in 2000-2007 and enrolled in a National Comprehensive Cancer Network registry. The study participants (mean age, 35 years) all had newly diagnosed unilateral stage I, II, or III breast cancer and were followed for a median of 6.4 years. Their data were stratified by age at diagnosis: 40 years or younger, 41-50 years, 51-60 years, 61-70 years, or over 70 years.

In the initial analysis, younger women were 90% more likely to die of breast cancer than older women. This probability decreased to 50% when the data were adjusted to control for treatment, stage at diagnosis, and tumor grade, then decreased further to 30% when the data were further adjusted to control for tumor molecular subtype and method of detection, the investigators said (J Clin Oncol. 2016 Aug 1; doi:10.1200/JCO.2015.65.8013).

However, when the data were analyzed according to tumor subtype, women who had luminal A breast cancer (7,738 participants) were more than twice as likely to die of their disease if they were aged 40 or younger at diagnosis than if they were older (hazard ratio, 2.1). The age-related increase in risk was slightly lower for luminal B breast cancer (HR, 1.4), and appeared to be largely confined to those with HER2-negative luminal B tumors.

There also was a borderline increased risk of death in younger women who had triple-negative breast cancer (HR, 1.4), compared with older women who had that tumor subtype. In contrast, younger age did not correlate with increased breast cancer mortality among women with HER2-positive disease.

These findings “support the growing evidence that the relationship between age at diagnosis and breast-cancer-specific survival varies by tumor subtype, which has implications for both treatment decisions and future research directions. ....In women with luminal disease, younger age does have a substantial prognostic role, which may reflect inadequate therapy, including lower treatment efficacy and less therapeutic adherence and persistence, as well as residual differences in tumor biology,” Dr. Partridge and her associates said.

No specific source of funding was identified for this study. Dr. Partridge reported serving as a consultant for Pfizer; her associates reported ties to Pfizer, Tokai, Bristol-Myers Squibb, Carevive Systems, Oncothyreon, Amgen, and BeyondSpring Pharmaceuticals.

Younger age at diagnosis of breast cancer predicts poor survival only with certain molecular subtypes of tumor, according to a report published online Aug. 1 in the Journal of Clinical Oncology.

An age of 40 years or younger “has long been considered a poor prognostic factor, because young women, on average, have an increased risk of disease recurrence and decreased survival. In recent years, however, with improved understanding of tumor biology, this assertion has been challenged with increased recognition of the prognostic and predictive role of tumor subtype and awareness that young women are more likely to develop more aggressive phenotypes,” said Ann H. Partridge, MD, of the Dana-Farber Cancer Institute, and Brigham and Women’s Hospital, both in Boston, and her associates.

To examine the relationships among patient age, tumor subtypes, and outcomes, they analyzed data for 17,575 women treated at eight U.S. cancer centers in 2000-2007 and enrolled in a National Comprehensive Cancer Network registry. The study participants (mean age, 35 years) all had newly diagnosed unilateral stage I, II, or III breast cancer and were followed for a median of 6.4 years. Their data were stratified by age at diagnosis: 40 years or younger, 41-50 years, 51-60 years, 61-70 years, or over 70 years.

In the initial analysis, younger women were 90% more likely to die of breast cancer than older women. This probability decreased to 50% when the data were adjusted to control for treatment, stage at diagnosis, and tumor grade, then decreased further to 30% when the data were further adjusted to control for tumor molecular subtype and method of detection, the investigators said (J Clin Oncol. 2016 Aug 1; doi:10.1200/JCO.2015.65.8013).

However, when the data were analyzed according to tumor subtype, women who had luminal A breast cancer (7,738 participants) were more than twice as likely to die of their disease if they were aged 40 or younger at diagnosis than if they were older (hazard ratio, 2.1). The age-related increase in risk was slightly lower for luminal B breast cancer (HR, 1.4), and appeared to be largely confined to those with HER2-negative luminal B tumors.

There also was a borderline increased risk of death in younger women who had triple-negative breast cancer (HR, 1.4), compared with older women who had that tumor subtype. In contrast, younger age did not correlate with increased breast cancer mortality among women with HER2-positive disease.

These findings “support the growing evidence that the relationship between age at diagnosis and breast-cancer-specific survival varies by tumor subtype, which has implications for both treatment decisions and future research directions. ....In women with luminal disease, younger age does have a substantial prognostic role, which may reflect inadequate therapy, including lower treatment efficacy and less therapeutic adherence and persistence, as well as residual differences in tumor biology,” Dr. Partridge and her associates said.

No specific source of funding was identified for this study. Dr. Partridge reported serving as a consultant for Pfizer; her associates reported ties to Pfizer, Tokai, Bristol-Myers Squibb, Carevive Systems, Oncothyreon, Amgen, and BeyondSpring Pharmaceuticals.

Biomarker-driven targeted therapy was found feasible for heavily pretreated, metastatic non–small-cell lung cancer in a phase II trial reported online Aug. 1 in the Journal of Clinical Oncology.

The open-label multicenter umbrella study under the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial, called the BATTLE-2, involved 200 patients with advanced NSCLC refractory to platinum-based chemotherapy and multiple other treatments. All patients underwent tumor tissue biopsies for biomarker and gene expression analyses.

The results of those assessments were then used to perform “adaptive randomization” in which the patients were assigned to one of four treatment arms deemed most likely to control their particular malignancy, said Vassiliki Papadimitrakopoulou, MD, professor of medicine in the department of thoracic/head and neck medical oncology at the University of Texas MD Anderson Cancer Center, Houston, and her associates.

One group of 22 patients received 150 mg erlotinib once daily; the second group (42 patients) received 150 mg erlotinib daily plus 135 mg of the AKT inhibitor MK-2206 once weekly; the third group (75 patients) received 100 mg per week of MK-2206 plus 100 mg of the MEK inhibitor AZD6244 once daily; and the fourth group (61 patients) received 400 mg of sorafenib twice daily. A total of 186 patients were evaluable at 8 weeks, and the overall rate of disease control was 48% at that time. After a median follow-up of 20 months, the median progression-free survival was 2.0 months, median overall survival was 6.5 months, and the 1-year survival was 28%.

The primary endpoint of the study – disease control rate at 8 weeks – was not significantly different among the four treatment groups. It was 32% in group 1, 50% in group 2, 53% in group 3, and 46% in group 4. There were no complete responses and only 6 partial responses: 3 patients in group 3 and 3 patients in group 4. However, the study demonstrated “the utility of real-time biopsies for broad profiling of tumors that serve as a discovery vehicle for better target selection,” the investigators said (J Clin Oncol. 2016 Aug 1. doi:10.1200/JCO.2015.66.0084).

“We are currently pursuing alternative strategies in targeting KRAS mut+ tumors by incorporating knowledge derived from BATTLE 2,” they added.

This study was supported by Merck, Bayer Healthcare Pharmaceuticals, and the National Cancer Institute. Dr. Papadimitrakopoulou and her associates reported ties to numerous industry sources.

Biomarker-driven targeted therapy was found feasible for heavily pretreated, metastatic non–small-cell lung cancer in a phase II trial reported online Aug. 1 in the Journal of Clinical Oncology.

The open-label multicenter umbrella study under the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial, called the BATTLE-2, involved 200 patients with advanced NSCLC refractory to platinum-based chemotherapy and multiple other treatments. All patients underwent tumor tissue biopsies for biomarker and gene expression analyses.

The results of those assessments were then used to perform “adaptive randomization” in which the patients were assigned to one of four treatment arms deemed most likely to control their particular malignancy, said Vassiliki Papadimitrakopoulou, MD, professor of medicine in the department of thoracic/head and neck medical oncology at the University of Texas MD Anderson Cancer Center, Houston, and her associates.

One group of 22 patients received 150 mg erlotinib once daily; the second group (42 patients) received 150 mg erlotinib daily plus 135 mg of the AKT inhibitor MK-2206 once weekly; the third group (75 patients) received 100 mg per week of MK-2206 plus 100 mg of the MEK inhibitor AZD6244 once daily; and the fourth group (61 patients) received 400 mg of sorafenib twice daily. A total of 186 patients were evaluable at 8 weeks, and the overall rate of disease control was 48% at that time. After a median follow-up of 20 months, the median progression-free survival was 2.0 months, median overall survival was 6.5 months, and the 1-year survival was 28%.

The primary endpoint of the study – disease control rate at 8 weeks – was not significantly different among the four treatment groups. It was 32% in group 1, 50% in group 2, 53% in group 3, and 46% in group 4. There were no complete responses and only 6 partial responses: 3 patients in group 3 and 3 patients in group 4. However, the study demonstrated “the utility of real-time biopsies for broad profiling of tumors that serve as a discovery vehicle for better target selection,” the investigators said (J Clin Oncol. 2016 Aug 1. doi:10.1200/JCO.2015.66.0084).

“We are currently pursuing alternative strategies in targeting KRAS mut+ tumors by incorporating knowledge derived from BATTLE 2,” they added.

This study was supported by Merck, Bayer Healthcare Pharmaceuticals, and the National Cancer Institute. Dr. Papadimitrakopoulou and her associates reported ties to numerous industry sources.

Biomarker-driven targeted therapy was found feasible for heavily pretreated, metastatic non–small-cell lung cancer in a phase II trial reported online Aug. 1 in the Journal of Clinical Oncology.

The open-label multicenter umbrella study under the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial, called the BATTLE-2, involved 200 patients with advanced NSCLC refractory to platinum-based chemotherapy and multiple other treatments. All patients underwent tumor tissue biopsies for biomarker and gene expression analyses.

The results of those assessments were then used to perform “adaptive randomization” in which the patients were assigned to one of four treatment arms deemed most likely to control their particular malignancy, said Vassiliki Papadimitrakopoulou, MD, professor of medicine in the department of thoracic/head and neck medical oncology at the University of Texas MD Anderson Cancer Center, Houston, and her associates.

One group of 22 patients received 150 mg erlotinib once daily; the second group (42 patients) received 150 mg erlotinib daily plus 135 mg of the AKT inhibitor MK-2206 once weekly; the third group (75 patients) received 100 mg per week of MK-2206 plus 100 mg of the MEK inhibitor AZD6244 once daily; and the fourth group (61 patients) received 400 mg of sorafenib twice daily. A total of 186 patients were evaluable at 8 weeks, and the overall rate of disease control was 48% at that time. After a median follow-up of 20 months, the median progression-free survival was 2.0 months, median overall survival was 6.5 months, and the 1-year survival was 28%.

The primary endpoint of the study – disease control rate at 8 weeks – was not significantly different among the four treatment groups. It was 32% in group 1, 50% in group 2, 53% in group 3, and 46% in group 4. There were no complete responses and only 6 partial responses: 3 patients in group 3 and 3 patients in group 4. However, the study demonstrated “the utility of real-time biopsies for broad profiling of tumors that serve as a discovery vehicle for better target selection,” the investigators said (J Clin Oncol. 2016 Aug 1. doi:10.1200/JCO.2015.66.0084).

“We are currently pursuing alternative strategies in targeting KRAS mut+ tumors by incorporating knowledge derived from BATTLE 2,” they added.

This study was supported by Merck, Bayer Healthcare Pharmaceuticals, and the National Cancer Institute. Dr. Papadimitrakopoulou and her associates reported ties to numerous industry sources.

By now the upheaval of changing to the new International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) diagnostic coding system has settled. The code freeze that was initiated in 2012 has ended, and the new and revised codes that will go into effect on October 1, 2016, are being revealed. Good documentation will lead to more accurate diagnostic coding, which in turn assists decision makers in their quest to report the health of our population and to make good decisions for resource allocation. You are in the unique position to assist in this process, so keep up the good work.

In this article, I focus on ICD-10 diagnostic coding for obstetric services. I will cover diagnostic coding for gynecologic services in the September issue of OBG Management.

Code revisions for uterine scar and more changes to note

With the upcoming edition of ICD-10, the code Z3A, Weeks’ gestation, will be changed from mandatory reporting to reporting if known. This means that if the patient is no longer pregnant, a Z3A code no longer needs to be reported, and if at the time of service the provider does not know the weeks’ gestation, Z3A would not be required. However, this information should be readily available during the antepartum period and should still be considered important to record and report. And it would still be reported for hospitalization for delivery.

If the code O09.81, Supervision of pregnancy resulting from assisted reproductive technology, is reported, the code Z33.3, Gestational carrier status, may be reported in addition for informational purposes.

When the code O34.29, Maternal care due to uterine scar from other previous surgery, is reported, the tabular index clarifies that this refers to a uterine scar from a transmural uterine incision other than that used for cesarean delivery. This would include incision into the uterine wall to remove fibroids.

The O42 code category, relating to Premature rupture of membranes, should now be interpreted to mean rupture of membranes at or after 37 completed weeks of gestation, rather than after 37 completed weeks.

The code category O99.6, Diseases of the digestive system complicating pregnancy, childbirth, and the puerperium, has been clarified: it does not include hemorrhoids in pregnancy. Therefore, a code from O22.4_ (a final digit of 0 [unspecified], 1, 2, or 3 is required for the trimester) also can be reported if hemorrhoids are present.

A note now clarifies that O99.82, Streptococcus B carrier state complicating pregnancy, childbirth, and the puerperium, cannot be reported with Z22.330, Carrier of streptococcus group B (GBS) in a nonpregnant woman.

New codes for specifying types of ectopic pregnancy

ICD-10 did not initially recognize ectopic pregnancy with and without intrauterine pregnancy, as was the case in ICD-9, but starting in October it will do so. In addition, a history of ectopic or molar pregnancy during a current pregnancy is now reported separately. Each of these codes will require a final digit to indicate the trimester (TABLE).

Codes added for complicating conditions of childbirth and the puerperium

Missing from the ICD-10 lineup last year were codes for conditions related to hypertension, edema, proteinuria, HELLP (hemolysis, elevated liver enzymes, and low platelet count) syndrome, and eclampsia that were complicating the pregnancy at the time of delivery or after delivery (TABLE).

Note that the “childbirth” code is reported only when a patient delivers at the current episode of care. Once a patient delivers and is discharged, the “puerperium” code should be selected.

Revised descriptions, new reporting instruction for diabetes

The code descriptions for preexisting type 1 and type 2 diabetes were revised, but this change does not impact reporting the codes. However, for type 2 diabetes, the instruction for reporting an additional code has changed. Now, in addition to reporting the code for current use of insulin (Z79.4), when appropriate, report the new added code for use of hypoglycemic agents (Z79.84), such as glyburide or metformin.

For gestational diabetes, new codes have been added for the use of hypoglycemic agents; therefore, no additional code is reported (TABLE).

Disproportion code includes numeric specifier for fetus

The disproportion code category was expanded to include a final digit for the fetus with the deformity (TABLE). The final digit of the code number denotes which fetus; for example, “0” means a singleton pregnancy, “1” means fetus 1 (number range from 1 to 5), and “9” denotes any fetus after the fifth.

Cesarean delivery scar codes expanded

The code for maternal care for a scar from a previous cesarean delivery has been expanded to 3 different codes (TABLE). Clinicians should make every effort to document and report the location of the previous cesarean as low transverse or vertical. From a coding standpoint, a vertical scar can also be referred to as a classical scar.

Changes to placenta previa codes

The code category for placenta previa has been expanded to capture the degree of previa as complete, partial, or low lying and with or without hemorrhage (TABLE). Going forward, it will be important to carefully document the circumstances so that the most specific code can be reported and tracked. Trimester specification is required as the final digit.

New subclassifications for perineal laceration

The code category for perineal laceration has been expanded with new codes to capture subclassifications for a third-degree laceration that can involve the external and internal anal sphincter (TABLE). Through its collaborative hub, the Women’s Health Registry Alliance (reVITALize) initiative, the American Congress of Obstetricians and Gynecologists (ACOG) worked on the current classification of third- and fourth-degree perineal lacerations, which has been adopted by the Royal College of Obstetricians and Gynaecologists.¹

Under this subclassification, a 3a laceration would involve a tear of less than 50% of the external anal sphincter (EAS); 3b would involve a tear of more than 50% of the EAS; and 3c would mean that both the external and internal anal sphincter are torn. ACOG and its collaborative group encourage clinicians to use these subclassifications in documentation to allow for more robust data collection and complete repair information. From a payment standpoint, such information may go a long way to substantiating the severity of a tear, which may require more physician work.

Z code additions

Finally, the ever-popular diagnostic code for Rho(D) immunization is back, and 2 codes have been added for a gestational carrier and 1 for a family history of sudden infant death syndrome. The codes are:

• Z29.13 Encounter for prophylactic Rho(D) immune globulin
• Z31.7 Encounter for procreative management and counseling for gestational carrier
• Z33.3 Pregnant state, gestational carrier
• Z84.82 Family history of sudden infant death syndrome.

By now the upheaval of changing to the new International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) diagnostic coding system has settled. The code freeze that was initiated in 2012 has ended, and the new and revised codes that will go into effect on October 1, 2016, are being revealed. Good documentation will lead to more accurate diagnostic coding, which in turn assists decision makers in their quest to report the health of our population and to make good decisions for resource allocation. You are in the unique position to assist in this process, so keep up the good work.

In this article, I focus on ICD-10 diagnostic coding for obstetric services. I will cover diagnostic coding for gynecologic services in the September issue of OBG Management.

Code revisions for uterine scar and more changes to note

With the upcoming edition of ICD-10, the code Z3A, Weeks’ gestation, will be changed from mandatory reporting to reporting if known. This means that if the patient is no longer pregnant, a Z3A code no longer needs to be reported, and if at the time of service the provider does not know the weeks’ gestation, Z3A would not be required. However, this information should be readily available during the antepartum period and should still be considered important to record and report. And it would still be reported for hospitalization for delivery.

If the code O09.81, Supervision of pregnancy resulting from assisted reproductive technology, is reported, the code Z33.3, Gestational carrier status, may be reported in addition for informational purposes.

When the code O34.29, Maternal care due to uterine scar from other previous surgery, is reported, the tabular index clarifies that this refers to a uterine scar from a transmural uterine incision other than that used for cesarean delivery. This would include incision into the uterine wall to remove fibroids.

The O42 code category, relating to Premature rupture of membranes, should now be interpreted to mean rupture of membranes at or after 37 completed weeks of gestation, rather than after 37 completed weeks.

The code category O99.6, Diseases of the digestive system complicating pregnancy, childbirth, and the puerperium, has been clarified: it does not include hemorrhoids in pregnancy. Therefore, a code from O22.4_ (a final digit of 0 [unspecified], 1, 2, or 3 is required for the trimester) also can be reported if hemorrhoids are present.

A note now clarifies that O99.82, Streptococcus B carrier state complicating pregnancy, childbirth, and the puerperium, cannot be reported with Z22.330, Carrier of streptococcus group B (GBS) in a nonpregnant woman.

New codes for specifying types of ectopic pregnancy

ICD-10 did not initially recognize ectopic pregnancy with and without intrauterine pregnancy, as was the case in ICD-9, but starting in October it will do so. In addition, a history of ectopic or molar pregnancy during a current pregnancy is now reported separately. Each of these codes will require a final digit to indicate the trimester (TABLE).

Codes added for complicating conditions of childbirth and the puerperium

Missing from the ICD-10 lineup last year were codes for conditions related to hypertension, edema, proteinuria, HELLP (hemolysis, elevated liver enzymes, and low platelet count) syndrome, and eclampsia that were complicating the pregnancy at the time of delivery or after delivery (TABLE).

Note that the “childbirth” code is reported only when a patient delivers at the current episode of care. Once a patient delivers and is discharged, the “puerperium” code should be selected.

Revised descriptions, new reporting instruction for diabetes

The code descriptions for preexisting type 1 and type 2 diabetes were revised, but this change does not impact reporting the codes. However, for type 2 diabetes, the instruction for reporting an additional code has changed. Now, in addition to reporting the code for current use of insulin (Z79.4), when appropriate, report the new added code for use of hypoglycemic agents (Z79.84), such as glyburide or metformin.

For gestational diabetes, new codes have been added for the use of hypoglycemic agents; therefore, no additional code is reported (TABLE).

Disproportion code includes numeric specifier for fetus

The disproportion code category was expanded to include a final digit for the fetus with the deformity (TABLE). The final digit of the code number denotes which fetus; for example, “0” means a singleton pregnancy, “1” means fetus 1 (number range from 1 to 5), and “9” denotes any fetus after the fifth.

Cesarean delivery scar codes expanded

The code for maternal care for a scar from a previous cesarean delivery has been expanded to 3 different codes (TABLE). Clinicians should make every effort to document and report the location of the previous cesarean as low transverse or vertical. From a coding standpoint, a vertical scar can also be referred to as a classical scar.

Changes to placenta previa codes

The code category for placenta previa has been expanded to capture the degree of previa as complete, partial, or low lying and with or without hemorrhage (TABLE). Going forward, it will be important to carefully document the circumstances so that the most specific code can be reported and tracked. Trimester specification is required as the final digit.

New subclassifications for perineal laceration

The code category for perineal laceration has been expanded with new codes to capture subclassifications for a third-degree laceration that can involve the external and internal anal sphincter (TABLE). Through its collaborative hub, the Women’s Health Registry Alliance (reVITALize) initiative, the American Congress of Obstetricians and Gynecologists (ACOG) worked on the current classification of third- and fourth-degree perineal lacerations, which has been adopted by the Royal College of Obstetricians and Gynaecologists.¹

Under this subclassification, a 3a laceration would involve a tear of less than 50% of the external anal sphincter (EAS); 3b would involve a tear of more than 50% of the EAS; and 3c would mean that both the external and internal anal sphincter are torn. ACOG and its collaborative group encourage clinicians to use these subclassifications in documentation to allow for more robust data collection and complete repair information. From a payment standpoint, such information may go a long way to substantiating the severity of a tear, which may require more physician work.

Z code additions

Finally, the ever-popular diagnostic code for Rho(D) immunization is back, and 2 codes have been added for a gestational carrier and 1 for a family history of sudden infant death syndrome. The codes are:

• Z29.13 Encounter for prophylactic Rho(D) immune globulin
• Z31.7 Encounter for procreative management and counseling for gestational carrier
• Z33.3 Pregnant state, gestational carrier
• Z84.82 Family history of sudden infant death syndrome.

By now the upheaval of changing to the new International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) diagnostic coding system has settled. The code freeze that was initiated in 2012 has ended, and the new and revised codes that will go into effect on October 1, 2016, are being revealed. Good documentation will lead to more accurate diagnostic coding, which in turn assists decision makers in their quest to report the health of our population and to make good decisions for resource allocation. You are in the unique position to assist in this process, so keep up the good work.

In this article, I focus on ICD-10 diagnostic coding for obstetric services. I will cover diagnostic coding for gynecologic services in the September issue of OBG Management.

Code revisions for uterine scar and more changes to note

With the upcoming edition of ICD-10, the code Z3A, Weeks’ gestation, will be changed from mandatory reporting to reporting if known. This means that if the patient is no longer pregnant, a Z3A code no longer needs to be reported, and if at the time of service the provider does not know the weeks’ gestation, Z3A would not be required. However, this information should be readily available during the antepartum period and should still be considered important to record and report. And it would still be reported for hospitalization for delivery.

If the code O09.81, Supervision of pregnancy resulting from assisted reproductive technology, is reported, the code Z33.3, Gestational carrier status, may be reported in addition for informational purposes.

When the code O34.29, Maternal care due to uterine scar from other previous surgery, is reported, the tabular index clarifies that this refers to a uterine scar from a transmural uterine incision other than that used for cesarean delivery. This would include incision into the uterine wall to remove fibroids.

The O42 code category, relating to Premature rupture of membranes, should now be interpreted to mean rupture of membranes at or after 37 completed weeks of gestation, rather than after 37 completed weeks.

The code category O99.6, Diseases of the digestive system complicating pregnancy, childbirth, and the puerperium, has been clarified: it does not include hemorrhoids in pregnancy. Therefore, a code from O22.4_ (a final digit of 0 [unspecified], 1, 2, or 3 is required for the trimester) also can be reported if hemorrhoids are present.

A note now clarifies that O99.82, Streptococcus B carrier state complicating pregnancy, childbirth, and the puerperium, cannot be reported with Z22.330, Carrier of streptococcus group B (GBS) in a nonpregnant woman.

New codes for specifying types of ectopic pregnancy

ICD-10 did not initially recognize ectopic pregnancy with and without intrauterine pregnancy, as was the case in ICD-9, but starting in October it will do so. In addition, a history of ectopic or molar pregnancy during a current pregnancy is now reported separately. Each of these codes will require a final digit to indicate the trimester (TABLE).

Codes added for complicating conditions of childbirth and the puerperium

Missing from the ICD-10 lineup last year were codes for conditions related to hypertension, edema, proteinuria, HELLP (hemolysis, elevated liver enzymes, and low platelet count) syndrome, and eclampsia that were complicating the pregnancy at the time of delivery or after delivery (TABLE).

Note that the “childbirth” code is reported only when a patient delivers at the current episode of care. Once a patient delivers and is discharged, the “puerperium” code should be selected.

Revised descriptions, new reporting instruction for diabetes

The code descriptions for preexisting type 1 and type 2 diabetes were revised, but this change does not impact reporting the codes. However, for type 2 diabetes, the instruction for reporting an additional code has changed. Now, in addition to reporting the code for current use of insulin (Z79.4), when appropriate, report the new added code for use of hypoglycemic agents (Z79.84), such as glyburide or metformin.

For gestational diabetes, new codes have been added for the use of hypoglycemic agents; therefore, no additional code is reported (TABLE).

Disproportion code includes numeric specifier for fetus

The disproportion code category was expanded to include a final digit for the fetus with the deformity (TABLE). The final digit of the code number denotes which fetus; for example, “0” means a singleton pregnancy, “1” means fetus 1 (number range from 1 to 5), and “9” denotes any fetus after the fifth.

Cesarean delivery scar codes expanded

The code for maternal care for a scar from a previous cesarean delivery has been expanded to 3 different codes (TABLE). Clinicians should make every effort to document and report the location of the previous cesarean as low transverse or vertical. From a coding standpoint, a vertical scar can also be referred to as a classical scar.

Changes to placenta previa codes

The code category for placenta previa has been expanded to capture the degree of previa as complete, partial, or low lying and with or without hemorrhage (TABLE). Going forward, it will be important to carefully document the circumstances so that the most specific code can be reported and tracked. Trimester specification is required as the final digit.

New subclassifications for perineal laceration

The code category for perineal laceration has been expanded with new codes to capture subclassifications for a third-degree laceration that can involve the external and internal anal sphincter (TABLE). Through its collaborative hub, the Women’s Health Registry Alliance (reVITALize) initiative, the American Congress of Obstetricians and Gynecologists (ACOG) worked on the current classification of third- and fourth-degree perineal lacerations, which has been adopted by the Royal College of Obstetricians and Gynaecologists.¹

Under this subclassification, a 3a laceration would involve a tear of less than 50% of the external anal sphincter (EAS); 3b would involve a tear of more than 50% of the EAS; and 3c would mean that both the external and internal anal sphincter are torn. ACOG and its collaborative group encourage clinicians to use these subclassifications in documentation to allow for more robust data collection and complete repair information. From a payment standpoint, such information may go a long way to substantiating the severity of a tear, which may require more physician work.

Z code additions

Finally, the ever-popular diagnostic code for Rho(D) immunization is back, and 2 codes have been added for a gestational carrier and 1 for a family history of sudden infant death syndrome. The codes are:

• Z29.13 Encounter for prophylactic Rho(D) immune globulin
• Z31.7 Encounter for procreative management and counseling for gestational carrier
• Z33.3 Pregnant state, gestational carrier
• Z84.82 Family history of sudden infant death syndrome.

PHM16’s Visual Diagnosis: Signs and Why They Matter session led by Dr. Kenneth Roberts and guest presenters was a review of case presentations in which visual clues were vital to establishing a diagnosis. Though much of the content was presented with pictures, the emphasis was placed on the importance of correct diagnosis to avoid both misdiagnoses/over-diagnoses and the potential harm that may result from inappropriate treatment. This may also translate into poor utilization of resources and significant financial burden that can result from the unnecessary hospitalization of a patient.

Many of the presented cases (such as the Gianotti-Crosti toddler over-diagnosed as eczema herpeticum, a child with pseudochromhidrosis misdiagnosed as a cyanotic disease, the case of phytophotodermatitis mistaken as child abuse, and a teen treated for 2 years for JIA before diagnosis of hypertrophic osteoarthropathy was made) highlighted examples in which there was extensive workup, hospitalization, subspecialty evaluation, and even incorrect treatment of patients.

In other instances, such as Henoch-Schonlein purpura, Waardenburg syndrome, or McCune-Albright syndrome, the correct diagnosis is necessary to help guide management and future treatment, including subspecialty evaluation.

Many diseases with visual presentations also have a benign course and require no treatment, and acknowledging this is important in providing reassurance to a family that may be very anxious over the physical appearance of their child.

This session underscores the need for experience and exposure to various signs, not only with rare medical conditions, but also in common illnesses such as Kawasaki and scarlet fever that may present similarly.

Key Takeaway:

Providers should have a high index of suspicion and use visual clues to make the correct diagnosis in order to guide treatment, avoid harm in children, and ensure appropriate utilization of resources.

PHM16’s Visual Diagnosis: Signs and Why They Matter session led by Dr. Kenneth Roberts and guest presenters was a review of case presentations in which visual clues were vital to establishing a diagnosis. Though much of the content was presented with pictures, the emphasis was placed on the importance of correct diagnosis to avoid both misdiagnoses/over-diagnoses and the potential harm that may result from inappropriate treatment. This may also translate into poor utilization of resources and significant financial burden that can result from the unnecessary hospitalization of a patient.

Many of the presented cases (such as the Gianotti-Crosti toddler over-diagnosed as eczema herpeticum, a child with pseudochromhidrosis misdiagnosed as a cyanotic disease, the case of phytophotodermatitis mistaken as child abuse, and a teen treated for 2 years for JIA before diagnosis of hypertrophic osteoarthropathy was made) highlighted examples in which there was extensive workup, hospitalization, subspecialty evaluation, and even incorrect treatment of patients.

In other instances, such as Henoch-Schonlein purpura, Waardenburg syndrome, or McCune-Albright syndrome, the correct diagnosis is necessary to help guide management and future treatment, including subspecialty evaluation.

Many diseases with visual presentations also have a benign course and require no treatment, and acknowledging this is important in providing reassurance to a family that may be very anxious over the physical appearance of their child.

This session underscores the need for experience and exposure to various signs, not only with rare medical conditions, but also in common illnesses such as Kawasaki and scarlet fever that may present similarly.

Key Takeaway:

Providers should have a high index of suspicion and use visual clues to make the correct diagnosis in order to guide treatment, avoid harm in children, and ensure appropriate utilization of resources.

PHM16’s Visual Diagnosis: Signs and Why They Matter session led by Dr. Kenneth Roberts and guest presenters was a review of case presentations in which visual clues were vital to establishing a diagnosis. Though much of the content was presented with pictures, the emphasis was placed on the importance of correct diagnosis to avoid both misdiagnoses/over-diagnoses and the potential harm that may result from inappropriate treatment. This may also translate into poor utilization of resources and significant financial burden that can result from the unnecessary hospitalization of a patient.

Many of the presented cases (such as the Gianotti-Crosti toddler over-diagnosed as eczema herpeticum, a child with pseudochromhidrosis misdiagnosed as a cyanotic disease, the case of phytophotodermatitis mistaken as child abuse, and a teen treated for 2 years for JIA before diagnosis of hypertrophic osteoarthropathy was made) highlighted examples in which there was extensive workup, hospitalization, subspecialty evaluation, and even incorrect treatment of patients.

In other instances, such as Henoch-Schonlein purpura, Waardenburg syndrome, or McCune-Albright syndrome, the correct diagnosis is necessary to help guide management and future treatment, including subspecialty evaluation.

Many diseases with visual presentations also have a benign course and require no treatment, and acknowledging this is important in providing reassurance to a family that may be very anxious over the physical appearance of their child.

This session underscores the need for experience and exposure to various signs, not only with rare medical conditions, but also in common illnesses such as Kawasaki and scarlet fever that may present similarly.

Key Takeaway:

Providers should have a high index of suspicion and use visual clues to make the correct diagnosis in order to guide treatment, avoid harm in children, and ensure appropriate utilization of resources.

A recent small study suggested that, in the age of endovascular aortic aneurysm repair (EVAR), the mortality rates between symptomatic and asymptomatic abdominal aortic aneurysm (AAA) repair have become similar, according to Peter A. Soden, MD, of Beth Deaconess Medical Center, Boston, and his colleagues. However, in their large database study, Dr. Soden and his colleagues found that outcomes for the repair of abdominal aortic aneurysms were increasingly worse from asymptomatic to symptomatic to ruptured AAA.

The researchers assessed all patients undergoing endovascular and open AAA repair in the 2011-2013 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data set, according to a report published in the August issue of the Journal of Vascular Surgery.

D.G.S.V.D. Gajasinghe/Wikimedia Commons/Creative Commons License

Symptomatic AAA was defined as lack of evidence of rupture but with the presence of abdominal or back pain or symptoms from local compression by the aneurysm causing early satiety, hydronephrosis, or deep vein thrombosis. Ruptured aneurysms were divided into two categories: hypotensive (defined as systolic blood pressure less than 90 mmm Hg or drop of greater than 40 mm HG from baseline) and nonhypotensive (J Vasc Surg. 2016;64:297-305).

There were numerous demographic and comorbidity differences between asymptomatic and symptomatic patients and between symptomatic and ruptured patients, with a general trend of increasing of commodities and factors influencing operative risk.

The final study included 5,502 patients undergoing repair of infrarenal (85%; 92% EVAR) or juxtarenal (15%;20% EVAR) aneurysms. These differences in the use of EVAR were statistically significant.

This population comprised 4,495 asymptomatic patients (82% EVAR), 455 symptomatic patients (69% EVAR), and 552 ruptured patients (52% EVAR).

The overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (5.1% vs. 1.9%; P less than .001).Similarly, for EVAR, the overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (3.8% vs. 1.4%; P less than .001). For open repair, there was no significant difference in mortality (7.7% vs. 4.3%) between symptomatic and asymptomatic patients, respectively.

Multivariate analysis showed that symptomatic patients had twice the operative mortality as asymptomatic patients (odds ratio, 2.1). A symptomatic aneurysm was also predictive of a major adverse event (OR, 1.5). Ruptured aneurysms had a significant nearly sevenfold increase in mortality risk vs. symptomatic aneurysms (OR, 6.5) and a fivefold increase of risk of a major adverse event (OR 5.1), with all ORs within their 95% confidence interval levels).

“In this large contemporary study of symptomatic AAA patients, in which the majority were treated with EVAR, we found that symptomatic patients have twice the perioperative mortality compared with asymptomatic patients. Despite this, we also find a reduction in perioperative mortality for symptomatic aneurysms compared with prior reports in which the majority were treated with open repair, and we believe this supports an EVAR-first approach for symptomatic aneurysms with suitable anatomy,” the researchers concluded.

The authors reported that they had no relevant disclosures.

[email protected]

A recent small study suggested that, in the age of endovascular aortic aneurysm repair (EVAR), the mortality rates between symptomatic and asymptomatic abdominal aortic aneurysm (AAA) repair have become similar, according to Peter A. Soden, MD, of Beth Deaconess Medical Center, Boston, and his colleagues. However, in their large database study, Dr. Soden and his colleagues found that outcomes for the repair of abdominal aortic aneurysms were increasingly worse from asymptomatic to symptomatic to ruptured AAA.

The researchers assessed all patients undergoing endovascular and open AAA repair in the 2011-2013 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data set, according to a report published in the August issue of the Journal of Vascular Surgery.

D.G.S.V.D. Gajasinghe/Wikimedia Commons/Creative Commons License

Symptomatic AAA was defined as lack of evidence of rupture but with the presence of abdominal or back pain or symptoms from local compression by the aneurysm causing early satiety, hydronephrosis, or deep vein thrombosis. Ruptured aneurysms were divided into two categories: hypotensive (defined as systolic blood pressure less than 90 mmm Hg or drop of greater than 40 mm HG from baseline) and nonhypotensive (J Vasc Surg. 2016;64:297-305).

There were numerous demographic and comorbidity differences between asymptomatic and symptomatic patients and between symptomatic and ruptured patients, with a general trend of increasing of commodities and factors influencing operative risk.

The final study included 5,502 patients undergoing repair of infrarenal (85%; 92% EVAR) or juxtarenal (15%;20% EVAR) aneurysms. These differences in the use of EVAR were statistically significant.

This population comprised 4,495 asymptomatic patients (82% EVAR), 455 symptomatic patients (69% EVAR), and 552 ruptured patients (52% EVAR).

The overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (5.1% vs. 1.9%; P less than .001).Similarly, for EVAR, the overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (3.8% vs. 1.4%; P less than .001). For open repair, there was no significant difference in mortality (7.7% vs. 4.3%) between symptomatic and asymptomatic patients, respectively.

Multivariate analysis showed that symptomatic patients had twice the operative mortality as asymptomatic patients (odds ratio, 2.1). A symptomatic aneurysm was also predictive of a major adverse event (OR, 1.5). Ruptured aneurysms had a significant nearly sevenfold increase in mortality risk vs. symptomatic aneurysms (OR, 6.5) and a fivefold increase of risk of a major adverse event (OR 5.1), with all ORs within their 95% confidence interval levels).

“In this large contemporary study of symptomatic AAA patients, in which the majority were treated with EVAR, we found that symptomatic patients have twice the perioperative mortality compared with asymptomatic patients. Despite this, we also find a reduction in perioperative mortality for symptomatic aneurysms compared with prior reports in which the majority were treated with open repair, and we believe this supports an EVAR-first approach for symptomatic aneurysms with suitable anatomy,” the researchers concluded.

The authors reported that they had no relevant disclosures.

[email protected]

A recent small study suggested that, in the age of endovascular aortic aneurysm repair (EVAR), the mortality rates between symptomatic and asymptomatic abdominal aortic aneurysm (AAA) repair have become similar, according to Peter A. Soden, MD, of Beth Deaconess Medical Center, Boston, and his colleagues. However, in their large database study, Dr. Soden and his colleagues found that outcomes for the repair of abdominal aortic aneurysms were increasingly worse from asymptomatic to symptomatic to ruptured AAA.

The researchers assessed all patients undergoing endovascular and open AAA repair in the 2011-2013 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data set, according to a report published in the August issue of the Journal of Vascular Surgery.

D.G.S.V.D. Gajasinghe/Wikimedia Commons/Creative Commons License

Symptomatic AAA was defined as lack of evidence of rupture but with the presence of abdominal or back pain or symptoms from local compression by the aneurysm causing early satiety, hydronephrosis, or deep vein thrombosis. Ruptured aneurysms were divided into two categories: hypotensive (defined as systolic blood pressure less than 90 mmm Hg or drop of greater than 40 mm HG from baseline) and nonhypotensive (J Vasc Surg. 2016;64:297-305).

There were numerous demographic and comorbidity differences between asymptomatic and symptomatic patients and between symptomatic and ruptured patients, with a general trend of increasing of commodities and factors influencing operative risk.

The final study included 5,502 patients undergoing repair of infrarenal (85%; 92% EVAR) or juxtarenal (15%;20% EVAR) aneurysms. These differences in the use of EVAR were statistically significant.

This population comprised 4,495 asymptomatic patients (82% EVAR), 455 symptomatic patients (69% EVAR), and 552 ruptured patients (52% EVAR).

The overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (5.1% vs. 1.9%; P less than .001).Similarly, for EVAR, the overall 30-day mortality rate was significantly higher in symptomatic over asymptomatic patients (3.8% vs. 1.4%; P less than .001). For open repair, there was no significant difference in mortality (7.7% vs. 4.3%) between symptomatic and asymptomatic patients, respectively.

Multivariate analysis showed that symptomatic patients had twice the operative mortality as asymptomatic patients (odds ratio, 2.1). A symptomatic aneurysm was also predictive of a major adverse event (OR, 1.5). Ruptured aneurysms had a significant nearly sevenfold increase in mortality risk vs. symptomatic aneurysms (OR, 6.5) and a fivefold increase of risk of a major adverse event (OR 5.1), with all ORs within their 95% confidence interval levels).

“In this large contemporary study of symptomatic AAA patients, in which the majority were treated with EVAR, we found that symptomatic patients have twice the perioperative mortality compared with asymptomatic patients. Despite this, we also find a reduction in perioperative mortality for symptomatic aneurysms compared with prior reports in which the majority were treated with open repair, and we believe this supports an EVAR-first approach for symptomatic aneurysms with suitable anatomy,” the researchers concluded.

The authors reported that they had no relevant disclosures.

[email protected]

One of PHM16’s most highly-attended sessions was an update on the anticipated AAP guidelines for febrile infants between ages 7-90 days given by Dr. Kenneth Roberts. The goal is to give evidence-based guidelines, not rules, from the most recent literature available. It also stresses the need to separate individual components of serious bacterial infections (UTI, bacteremia, and meningitis) as the incidence and clinical course can vary greatly in this population.

The inclusion criteria for infants for this upcoming algorithm require an infant to be full-term (37-43 weeks gestation), aged 7-90 days, well-appearing, and presenting with a temperature of 38 degrees Celsius.

Exclusion criteria include perinatal/prenatal/neonatal: maternal fever, infection, or antimicrobial treatment, the presence of any evident infection, being technology-dependent, and the presence of congenital anomalies.

The updated guideline will aim to stratify management by age 7-28 days, 29-60 days, and 61 to 90 days to provide the most appropriate and directed treatment.

It will also include a role for inflammatory markers, and allow for a “kinder, gentler” approach to the management of febrile infants aged 7-90 days including withholding certain treatments and procedures if infants are at low risk of infection. An active, not passive, need for observation may be appropriate for certain infants as well. These guidelines should be tailored for individual patients to provide the best care possible while minimizing risk in this population.

Key Takeaway:

An updated AAP Practice guideline algorithm for the management of well-appearing febrile infants 7-28 days, 29-60 days, and 60-90 days will be coming in the near future that will help standardize care in this population, but should not be used as a substitute for clinical judgment.

One of PHM16’s most highly-attended sessions was an update on the anticipated AAP guidelines for febrile infants between ages 7-90 days given by Dr. Kenneth Roberts. The goal is to give evidence-based guidelines, not rules, from the most recent literature available. It also stresses the need to separate individual components of serious bacterial infections (UTI, bacteremia, and meningitis) as the incidence and clinical course can vary greatly in this population.

The inclusion criteria for infants for this upcoming algorithm require an infant to be full-term (37-43 weeks gestation), aged 7-90 days, well-appearing, and presenting with a temperature of 38 degrees Celsius.

Exclusion criteria include perinatal/prenatal/neonatal: maternal fever, infection, or antimicrobial treatment, the presence of any evident infection, being technology-dependent, and the presence of congenital anomalies.

The updated guideline will aim to stratify management by age 7-28 days, 29-60 days, and 61 to 90 days to provide the most appropriate and directed treatment.

It will also include a role for inflammatory markers, and allow for a “kinder, gentler” approach to the management of febrile infants aged 7-90 days including withholding certain treatments and procedures if infants are at low risk of infection. An active, not passive, need for observation may be appropriate for certain infants as well. These guidelines should be tailored for individual patients to provide the best care possible while minimizing risk in this population.

Key Takeaway:

An updated AAP Practice guideline algorithm for the management of well-appearing febrile infants 7-28 days, 29-60 days, and 60-90 days will be coming in the near future that will help standardize care in this population, but should not be used as a substitute for clinical judgment.

One of PHM16’s most highly-attended sessions was an update on the anticipated AAP guidelines for febrile infants between ages 7-90 days given by Dr. Kenneth Roberts. The goal is to give evidence-based guidelines, not rules, from the most recent literature available. It also stresses the need to separate individual components of serious bacterial infections (UTI, bacteremia, and meningitis) as the incidence and clinical course can vary greatly in this population.

The inclusion criteria for infants for this upcoming algorithm require an infant to be full-term (37-43 weeks gestation), aged 7-90 days, well-appearing, and presenting with a temperature of 38 degrees Celsius.

Exclusion criteria include perinatal/prenatal/neonatal: maternal fever, infection, or antimicrobial treatment, the presence of any evident infection, being technology-dependent, and the presence of congenital anomalies.

The updated guideline will aim to stratify management by age 7-28 days, 29-60 days, and 61 to 90 days to provide the most appropriate and directed treatment.

It will also include a role for inflammatory markers, and allow for a “kinder, gentler” approach to the management of febrile infants aged 7-90 days including withholding certain treatments and procedures if infants are at low risk of infection. An active, not passive, need for observation may be appropriate for certain infants as well. These guidelines should be tailored for individual patients to provide the best care possible while minimizing risk in this population.

Key Takeaway:

An updated AAP Practice guideline algorithm for the management of well-appearing febrile infants 7-28 days, 29-60 days, and 60-90 days will be coming in the near future that will help standardize care in this population, but should not be used as a substitute for clinical judgment.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

An updated risk model based on data from patients presenting after acute myocardial infarction to a broad spectrum of U.S. hospitals appears to predict with a high degree of accuracy which patients are at the greatest risk for in-hospital mortality, investigators say.

Created from data on more than 240,000 patients presenting to one of 655 U.S. hospitals in 2012 and 2013 following ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation MI (NSTEMI), the model identified the following independent risk factors for in-hospital mortality: age, heart rate, systolic blood pressure, presentation to the hospital after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio, reported Robert L. McNamara, MD, of Yale University, New Haven, Conn.

megaflopp/ThinkStock

The investigators are participants in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry–GWTG (Get With the Guidelines).

“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment. The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix,” they wrote (J Am Coll Cardiol. 2016 Aug 1;68[6]:626-35).

The revised risk model has the potential to facilitate hospital quality assessments and help investigators to identify specific factors that could help clinicians even further lower death rates, the investigators write.

Further mortality reductions?

Although improvements in care of patients with acute MI over the last several decades have driven the in-hospital death rate from 29% in 1969 down to less than 7% today, there are still more than 100,000 AMI-related in-hospital deaths in the United States annually, with wide variations across hospitals, Dr. McNamara and colleagues noted.

A previous risk model published by ACTION Registry–GWTG members included data on patients treated at 306 U.S. hospitals and provided a simple, validated in-hospital mortality and risk score.

Since that model was published, however, the dataset was expanded to include patients presenting after cardiac arrest at the time of AMI presentation.

“Being able to adjust for cardiac arrest is critical because it is a well-documented predictor of mortality. Moreover, continued improvement in AMI care mandates periodic updates to the risk models so that hospitals can assess their quality as contemporary care continues to evolve,” the authors wrote.

To see whether they could develop a new and improved model and risk score, they analyzed data on 243,440 patients treated at one of 655 hospitals in the voluntary network. Data on 145,952 patients (60% of the total), 57,039 of whom presented with STEMI, and 88,913 of whom presented with NSTEMI, were used to for the derivation sample.

Data on the remaining 97,488 (38,060 with STEMI and 59,428 with NSTEMI) were used to create the validation sample.

The authors found that for the total cohort, the in-hospital mortality rate was 4.6%. In multivariate models controlled for demographic and clinical factors, independent risk factors significantly associated with in-hospital mortality (validation cohort) were:

• Presentation after cardiac arrest (odds ratio, 5.15).

• Presentation in cardiogenic shock (OR, 4.22).

• Presentation in heart failure (OR, 1.83).

• STEMI on electrocardiography (OR, 1.81).

• Age, per 5 years (OR, 1.24).

• Systolic BP, per 10 mm Hg decrease (OR, 1.19).

• Creatinine clearance per 5/mL/min/1.73 m² decrease (OR, 1.11).

• Heart rate per 10 beats/min (OR, 1.09).

• Troponin ratio, per 5 units (OR, 1.05).

The 95% confidence intervals for all of the above factors were significant.

The C-statistic, a standard measure of the predictive accuracy of a logistic regression model, was 0.88, indicating that the final ACTION Registry–GWTG in-hospital mortality model had a high level of discrimination in both the derivation and validation populations, the authors state.

The ACTION Registry–GWTG is a Program of the American College of Cardiology and the American Heart Association, with funding from Schering-Plough and the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. Dr. McNamara serves on a clinical trials endpoint adjudication committee for Pfizer. Other coauthors reported multiple financial relationships with pharmaceutical and medical device companies.

When our second daughter was born, she came home from the hospital in a box. All the babies born at Duke University Medical Center in 1973 were sent home in a cardboard box that had served as their bassinets during their stay in the newborn nursery. As I recall, the boxes were decorated with storks and musical notes; had spaces for the babies’ names, measurements, and birth dates; and had open slots that functioned as carrying handles.

Of course, 1973 predated crash-tested car seats, and so we put little Emily and her box in what we referred to as the “wayback” of our Ford Pinto wagon, a car that subsequently earned a reputation for turning into a fireball when involved in a rear-end collision. However, I believe I did take the extra precaution of “securing” the box in place with a bungee cord.

But Emily survived, and I filed away the memory of her cardboard bassinet until a few weeks ago when I read a story in the New York Times, “Why Finland’s Newborns Sleep in Cardboard Cribs” (Eli Rosenberg, July 6, 2016). It turns out the Finnish government gives out 40,000 cardboard boxes to pregnant women who agree to have a medical exam during the first trimester of their pregnancy. The gift boxes come along with 50 items of baby ware appropriate for Finland’s frigid climate, including a warm coat and a balaclava.

The baby box program began in the late 1930s as a way to encourage mothers to visit physicians. The current Finnish infant mortality is one of the lowest in the world and less than half of ours in the United States. There are some who have been tempted to attribute this dramatic decline to the baby box program. But it is hard to tease out one factor in a country that offers a 10-month paid parental leave and guarantees that a stay-at-home parent may return to his or her job at any time before the child’s third birthday.

Even without a broad social service support system, the cardboard box crib can save lives. For families who can’t afford a crib, the box offers a safer alternative to a couch with soft cushions and face-trapping gaps between its cushions, or to a bed shared with a sleep-deprived or inebriated parent, or to an antique crib with neck-pinching slats and layers of lead-laced paint.

Given this high costs of raising a child, the option of a no-cost cardboard box crib should appeal to most young families. But you know as well as I do that parents to be (and grandparents to be) are primed to buy and are focused on creating nurseries that match the images they see in the glossy magazines targeted at their vulnerable demographic.

It will require a major public relations campaign to counteract the image that bedding one’s precious newborn in a cardboard box conjures up. But maybe there is a role for us. If pediatricians began promoting the advantages of cardboard cribs, they might just catch on. On second thought, maybe we should focus our energies on promoting more child-friendly parental leave policies.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics including “How to Say No to Your Toddler.”

When our second daughter was born, she came home from the hospital in a box. All the babies born at Duke University Medical Center in 1973 were sent home in a cardboard box that had served as their bassinets during their stay in the newborn nursery. As I recall, the boxes were decorated with storks and musical notes; had spaces for the babies’ names, measurements, and birth dates; and had open slots that functioned as carrying handles.

Of course, 1973 predated crash-tested car seats, and so we put little Emily and her box in what we referred to as the “wayback” of our Ford Pinto wagon, a car that subsequently earned a reputation for turning into a fireball when involved in a rear-end collision. However, I believe I did take the extra precaution of “securing” the box in place with a bungee cord.

But Emily survived, and I filed away the memory of her cardboard bassinet until a few weeks ago when I read a story in the New York Times, “Why Finland’s Newborns Sleep in Cardboard Cribs” (Eli Rosenberg, July 6, 2016). It turns out the Finnish government gives out 40,000 cardboard boxes to pregnant women who agree to have a medical exam during the first trimester of their pregnancy. The gift boxes come along with 50 items of baby ware appropriate for Finland’s frigid climate, including a warm coat and a balaclava.

The baby box program began in the late 1930s as a way to encourage mothers to visit physicians. The current Finnish infant mortality is one of the lowest in the world and less than half of ours in the United States. There are some who have been tempted to attribute this dramatic decline to the baby box program. But it is hard to tease out one factor in a country that offers a 10-month paid parental leave and guarantees that a stay-at-home parent may return to his or her job at any time before the child’s third birthday.

Even without a broad social service support system, the cardboard box crib can save lives. For families who can’t afford a crib, the box offers a safer alternative to a couch with soft cushions and face-trapping gaps between its cushions, or to a bed shared with a sleep-deprived or inebriated parent, or to an antique crib with neck-pinching slats and layers of lead-laced paint.

Given this high costs of raising a child, the option of a no-cost cardboard box crib should appeal to most young families. But you know as well as I do that parents to be (and grandparents to be) are primed to buy and are focused on creating nurseries that match the images they see in the glossy magazines targeted at their vulnerable demographic.

It will require a major public relations campaign to counteract the image that bedding one’s precious newborn in a cardboard box conjures up. But maybe there is a role for us. If pediatricians began promoting the advantages of cardboard cribs, they might just catch on. On second thought, maybe we should focus our energies on promoting more child-friendly parental leave policies.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics including “How to Say No to Your Toddler.”

When our second daughter was born, she came home from the hospital in a box. All the babies born at Duke University Medical Center in 1973 were sent home in a cardboard box that had served as their bassinets during their stay in the newborn nursery. As I recall, the boxes were decorated with storks and musical notes; had spaces for the babies’ names, measurements, and birth dates; and had open slots that functioned as carrying handles.

Of course, 1973 predated crash-tested car seats, and so we put little Emily and her box in what we referred to as the “wayback” of our Ford Pinto wagon, a car that subsequently earned a reputation for turning into a fireball when involved in a rear-end collision. However, I believe I did take the extra precaution of “securing” the box in place with a bungee cord.

But Emily survived, and I filed away the memory of her cardboard bassinet until a few weeks ago when I read a story in the New York Times, “Why Finland’s Newborns Sleep in Cardboard Cribs” (Eli Rosenberg, July 6, 2016). It turns out the Finnish government gives out 40,000 cardboard boxes to pregnant women who agree to have a medical exam during the first trimester of their pregnancy. The gift boxes come along with 50 items of baby ware appropriate for Finland’s frigid climate, including a warm coat and a balaclava.

The baby box program began in the late 1930s as a way to encourage mothers to visit physicians. The current Finnish infant mortality is one of the lowest in the world and less than half of ours in the United States. There are some who have been tempted to attribute this dramatic decline to the baby box program. But it is hard to tease out one factor in a country that offers a 10-month paid parental leave and guarantees that a stay-at-home parent may return to his or her job at any time before the child’s third birthday.

Even without a broad social service support system, the cardboard box crib can save lives. For families who can’t afford a crib, the box offers a safer alternative to a couch with soft cushions and face-trapping gaps between its cushions, or to a bed shared with a sleep-deprived or inebriated parent, or to an antique crib with neck-pinching slats and layers of lead-laced paint.

Given this high costs of raising a child, the option of a no-cost cardboard box crib should appeal to most young families. But you know as well as I do that parents to be (and grandparents to be) are primed to buy and are focused on creating nurseries that match the images they see in the glossy magazines targeted at their vulnerable demographic.

It will require a major public relations campaign to counteract the image that bedding one’s precious newborn in a cardboard box conjures up. But maybe there is a role for us. If pediatricians began promoting the advantages of cardboard cribs, they might just catch on. On second thought, maybe we should focus our energies on promoting more child-friendly parental leave policies.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics including “How to Say No to Your Toddler.”