hmgt 420 disc 6

Published Online: August 5, 2019. doi:10.1001/jamainternmed.2019.3107

Author Contributions: Dr Growdon had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Growdon, Sacks, Avorn. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Growdon. Critical revision of the manuscript for important intellectual content: Sacks, Kesselheim, Avorn. Statistical analysis: Growdon, Avorn. Obtained funding: Kesselheim, Avorn. Administrative, technical, or material support: Avorn. Study supervision: Kesselheim, Avorn.

Conflict of Interest Disclosures: None reported.

Funding/Support: Work at PORTAL is supported by Arnold Ventures, with additional support from the Engelberg Foundation and Harvard-MIT Center for Regulatory Science. Dr Sacks also receives support from the Carney Family Foundation.

Role of the Funder/Sponsor: Arnold Ventures, the Engelberg Foundation, the Harvard-MIT Center for Regulatory Science, and the Carney Family Foundation had no roles in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

1. Kesselheim AS, Avorn J, Sarpatwari A. The high cost of prescription drugs in the United States origins and prospects for reform. JAMA. 2016;316(8):858-871. doi:10.1001/jama.2016.11237

2. Johansen ME, Richardson C. Estimation of potential savings through therapeutic substitution. JAMA Intern Med. 2016;176(6):769-775. doi:10.1001/ jamainternmed.2016.1704

3. Centers for Medicare and Medicaid Services. Medicare Part D Drug Spending Dashboard and Data. https://www.cms.gov/Research-Statistics-Data-and- Systems/Statistics-Trends-and-Reports/Information-on-Prescription-Drugs/ MedicarePartD.html. Published March 14, 2019. Accessed March 20, 2019.

4. Whelton PK, Carey RM, Aronow WS, et al. ACC/AHA/AAPA/ABC/ACPM/AGS/ APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults. Hypertension. 2018;71(6):1269-1324. doi:10.1161/HYP.0000000000000066

5. Vanderholm T, Klepser D, Adams AJ. State approaches to therapeutic interchange in community pharmacy settings: legislative and regulatory authority. J Manag Care Spec Pharm. 2018;24(12):1260-1263.

6. Sacks CA, Lee CC, Kesselheim AS, Avorn J. Medicare spending on brand-name combination medications vs their generic constituents. JAMA. 2018;320(7):650-656. doi:10.1001/jama.2018.11439

Trends in Hospitalization vs Observation Stay for Ambulatory Care–Sensitive Conditions Hospitalizations related to ambulatory care–sensitive condi- tions (ACSCs) are widely considered a key measure of access to high-quality primary care.1 The Agency for Healthcare Re- search and Quality defines ACSCs as conditions, such as uri- nary tract infection and dehydration, for which hospitaliza- tion is generally avoidable if patients have access to effective primary care.2 In recent years, there has been substantial fo- cus on improving ambulatory care nationally.3 Therefore, rates of hospital admissions related to ACSCs are used with increas- ing frequency to assess and incentivize the performance in the ambulatory setting of health care professionals participating in national Medicare alternative payment programs, such as accountable care organizations and alternative quality con- tracts administered by private payers, which increase pres- sure on hospitals to admit fewer patients.4 To date, there is some evidence that rates of avoidable hospitalizations have in- deed been falling.2 However, during this same period, the rates of hospital admissions “for observation,” which do not count

as inpatient admissions, have been increasing.5 The degree to which reported drops in avoidable hospitalizations related to ACSCs represent real gains in ambulatory care and not simply an artifact of an increasing shift from inpatient status to ob- servation status is unknown.

Methods | We obtained a national 20% sample of the Medicare Fee-for-Service Inpatient and Outpatient Claim Files from 2011 to 2015 and used the Agency for Healthcare Research and Qual- ity Prevention Quality Indicators software to identify avoid- able hospitalizations and observation stays related to ACSCs.6

These included all hospital stays related to both acute con- ditions (dehydration, bacterial pneumonia, urinary tract in- fection, and perforated appendix) and chronic conditions (including diabetes short-term complications, diabetes long- term complications, uncontrolled diabetes, lower extremity amputation related to diabetes, asthma in adults, chronic ob- structive pulmonary disease, hypertension, heart failure, and angina without procedure). The Harvard T. H. Chan School of Public Health institutional review board’s Committee on the Use of Human Subjects approved this study and waived the need for informed patient consent because all data were ret- rospective and deidentified. We used multivariable linear re- gression models to estimate yearly rates of avoidable hospi- talizations and observation stays within each hospital referral region (HRR), the geographic territory representing each re- gional tertiary care market. The models included adjust- ments for patient age, sex, race, dual Medicare and Medicaid status, and comorbidities (using comorbidities data obtained from the Chronic Conditions Data Warehouse) and treated time as a categorical variable. We then estimated yearly slopes, simi- larly adjusting for patient demographics and comorbidities and using time as a continuous variable. Statistical analyses were performed from November 2018 to March 2019 using SAS soft- ware, version 9.4 (SAS Institute Inc). A 2-sided P < .05 was con- sidered statistically significant.

Figure. Trends in Potentially Avoidable Hospitalizations and Hospital Observation Stays Related to Ambulatory Care–Sensitive Conditions

10 000

8000

6000

4000

2000

0

Po te

nt ia

lly A

vo id

ab le

S ta

ys , N

o.

pe r 1

00 0

00 B

en ef

ic ia

rie s

Year 20152014201320122011

Hospitalization

Observation

All avoidable stays

Multivariable linear regression models were used to estimate yearly hospitalization rates and observation stays while adjusting for patient demographics and comorbidities, treating time as a categorical variable, and including hospital referral region–fixed effects.

Letters

1714 JAMA Internal Medicine December 2019 Volume 179, Number 12 (Reprinted) jamainternalmedicine.com

© 2019 American Medical Association. All rights reserved.

Downloaded From: https://jamanetwork.com/ on 03/25/2022

Results | In 2011, there were 5517 ACSC-related, potentially avoidable inpatient hospitalizations and 3743 similarly avoid- able observation stays per 100 000 Medicare beneficiaries (Figure). By 2015, the rate of potentially avoidable inpatient hospitalizations had decreased to 4158 and the rate of poten- tially avoidable hospital observation stays had increased to 4718 per 100 000 beneficiaries. The risk-adjusted slopes were −326.2 per 100 000 beneficiaries per year (95% CI, −332.8 to −319.7; P < .001) for avoidable inpatient hospitalizations and 245.6 per 100 000 beneficiaries per year (95% CI, 233.4 to 257.7; P < .001) for avoidable observation stays (Table). Approximately 75.2% of the decrease in national avoidable hospitalizations from 2011 to 2015 was offset by the increase in hospital stays under ob- servation status. A greater shift from inpatient to observation stays was seen for chronic ACSCs than for acute ACSCs.

Discussion | The rates of avoidable hospitalizations related to ACSCs have declined over time in the Medicare population. However, there has been a concomitant increase in the rates of avoidable observation stays for the same types of condi- tions, especially for chronic ACSCs. Our study results suggest that the major part of the improvement in hospitalization rates for ACSCs is likely related to increased designation of pa- tients for observation status. Although the observational na- ture of this study limits our ability to establish a definitive causal relationship between these trends, the findings have im- portant policy implications. First, they call into question how much progress is being made in improving ambulatory care, particularly for chronic conditions such as diabetes and heart failure. Second, they suggest that any alternative payment model that uses avoidable hospitalizations as a quality mea- sure to assess performance in the primary care setting should also account for potentially avoidable observation stays.

Jose F. Figueroa, MD, MPH Laura G. Burke, MD, MPH

Jie Zheng, PhD E. John Orav, PhD Ashish K. Jha, MD, MPH

Author Affiliations: Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts (Figueroa, Burke, Zheng, Orav, Jha); Division of General Internal Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts (Figueroa, Orav); Department of Medicine, Harvard Medical School, Boston, Massachusetts (Figueroa, Burke, Jha); Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts (Burke); Harvard Global Health Institute, Harvard University, Cambridge, Massachusetts (Jha).

Accepted for Publication: June 7, 2019.

Corresponding Author: Jose F. Figueroa, MD, MPH, Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, 42 Church St, Cambridge, MA 02138 ([email protected]).

Published Online: August 26, 2019. doi:10.1001/jamainternmed.2019.3177

Author Contributions: Drs Figueroa and Jha had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Figueroa, Burke, Jha. Acquisition, analysis, or interpretation of data: Figueroa, Zheng, Orav, Jha. Drafting of the manuscript: Figueroa, Burke, Jha. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Zheng, Orav. Obtained funding: Figueroa, Jha. Administrative, technical, or material support: Figueroa, Jha. Supervision: Figueroa, Burke, Jha.

Conflict of Interest Disclosures: Dr Burke reported receiving grants from Emergency Medicine Foundation outside the submitted work. No other disclosures were reported.

Funding/Support: Dr Figueroa was partially funded by the Harvard Catalyst KL2TR1100-5 grant and Harvard Medical School’s Office for Diversity Inclusion and Community Partnership.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

1. Gao J, Moran E, Li YF, Almenoff PL. Predicting potentially avoidable hospitalizations. Med Care. 2014;52(2):164-171. doi:10.1097/MLR. 0000000000000041

Table. Change in Rates of Hospitalization and Observation Stays Related to Overall, Acute, and Chronic ACSCsa

Admission Status by ACSC Category

Year

Yearly Change, Slope (95% CI) P Value for Trend2011 2015 All ACSCs, No. per 100 000 Medicare beneficiaries

Hospitalization 5517 4158 −326.2 (−332.8 to −319.7) <.001

Observation 3743 4718 245.6 (233.4 to 257.7) <.001

Chronic ACSCs, No. per 100 000 Medicare beneficiariesb

Hospitalization 3055 2340 −167.8 (−172.9 to −162.7) <.001

Observation 2617 3350 188.6 (178.5 to 198.7) .001

Acute ACSCs, No. per 100 000 Medicare beneficiariesc

Hospitalization 2463 1819 −158.4 (−162.4 to −154.4) <.001

Observation 1126 1368 57.0 (51.7 to 62.3) <.001

Abbreviation: ACSCs, ambulatory care–sensitive conditions. a Multivariable linear regression models were used to estimate yearly

hospitalization rates and observation stays by using a 20% national sample of Medicare inpatient and outpatient data for 2011 to 2015 after adjusting for patient demographics and comorbidities, and treating time as a categorical variable. Yearly slopes were estimated by treating time as a continuous variable. All models included HRR fixed effects. The study baseline was 2011, and 2015 was the latest year for which relevant national data were available.

b Chronic ACSCs included short-term and long-term complications of diabetes, uncontrolled diabetes, lower extremity amputation related to diabetes, asthma in adults, chronic obstructive pulmonary disease, hypertension, heart failure, and angina without procedure.

c Acute ACSCs included dehydration, bacterial pneumonia, urinary tract infection, and perforated appendix.

Letters

jamainternalmedicine.com (Reprinted) JAMA Internal Medicine December 2019 Volume 179, Number 12 1715

© 2019 American Medical Association. All rights reserved.

Downloaded From: https://jamanetwork.com/ on 03/25/2022

2. Agency for Healthcare Research and Quality (AHRQ). Potentially avoidable hospitalizations. http://www.ahrq.gov/research/findings/nhqrdr/chartbooks/ carecoordination/measure3.html. Published 2016. Accessed April 3, 2019.

3. Blumenthal D, Abrams M, Nuzum R. The Affordable Care Act at 5 years. N Engl J Med. 2015;373(16):1580.

4. CMS Medicare Shared Savings Program. Accountable Care Organization (ACO) 2018 Quality Measures: Narrative Specifications Document. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ sharedsavingsprogram/Downloads/2018-reporting-year-narrative- specifications.pdf. Published January 20, 2018. Accessed July 1, 2019.

5. Dharmarajan K, Qin L, Bierlein M, et al. Outcomes after observation stays among older adult Medicare beneficiaries in the USA: retrospective cohort study. BMJ. 2017;357:j2616. doi:10.1136/bmj.j2616

6. Agency for Healthcare Research and Quality (AHRQ). QI modules. https://www.qualityindicators.ahrq.gov/Archive/default.aspx#. Accessed March 12, 2019.

Inclusion of Clinical Trial Registration Numbers in Conference Abstracts and Conformance of Abstracts to CONSORT Guidelines Clinical trial registration facilitates identification, tracking, and assessment of clinical trials and limits publication bias caused by the selective reporting of trial results.1 Inclusion of trial reg- istration numbers in conference abstracts, as recommended by the Consolidated Standards of Reporting Trials (CONSORT) guidelines for abstracts2 is particularly important because many conference presentations of trials remain unpublished.3 In the present study, we reviewed abstracts presented at 8 major medi- cal and surgical conferences held in 2017 to assess the extent to which conference abstracts reporting randomized clinical trial

(RCT) results cite trial registration numbers and conform to other key CONSORT guidelines.

Methods | For this cross-sectional study, 8 major conferences held in 2017 in the fields of cardiology, endocrinology, gastro- enterology, hepatology, nephrology, and urology (medical spe- cialties of special interest to the authors) and with readily avail- able abstracts were selected for review (Table). Abstracts were identified by searching for the word randomized (or randomised). Abstracts that reported primary results of an RCT were then examined for inclusion of a trial registration number, and the following 5 additional key elements of the CONSORT guidelines for abstracts2: the word randomized or randomised or RCT in the title, statement of a primary out- come, number of participants randomized in each group, and number of participants analyzed in each group, and dates of recruitment and follow-up. Inclusion of a trial registration num- ber and the additional 5 CONSORT reporting items in the ab- stract were each given a score of 1 if present and 0 if absent and then combined to obtain a summary score with a range of 0 to 6.

Results | We identified 1546 abstracts with the word random- ized (or randomised), representing approximately 7.0% of more than 22 000 abstracts accepted for poster or oral presenta- tions at the 8 conferences examined. Of these, 1124 abstracts (72.7%) reported RCT results, of which 720 (64.1%) reported primary results (Figure). Of these 720 abstracts, only 97 (13.5%)

Table. Abstracts Reporting Primary Clinical Trial Results

Criteria

Conference Abstracts, No. (%)

AASLD ACC ADA AUA DDW EASL KW OW All Primary abstracts, No. 62 34 198 122 107 70 90 37 720

CONSORT criteria

Registration number in abstract

20 (32.3) 4 (11.8) 20 (10.1) 16 (13.1) 13 (12.1) 10 (14.3) 14 (15.6) 0 97 (13.5)

Word randomized or randomised or RCT in title

33 (53.2) 10 (29.4) 42 (21.2) 93 (76.2) 92 (86.0) 30 (42.9) 45 (50.0) 8 (21.6) 353 (49.0)

Primary outcome specified

30 (48.4) 14 (41.2) 57 (28.8) 44 (36.1) 58 (54.2) 35 (50.0) 41 (45.6) 4 (10.8) 283 (39.3)

Participants randomized in each group provided

43 (69.4) 17 (50.0) 118 (59.6) 82 (67.2) 78 (72.9) 40 (57.1) 46 (51.1) 18 (48.6) 442 (61.4)

Participants analyzed in each group provided

21 (33.9) 8 (23.5) 41 (20.7) 26 (21.3) 46 (43.0) 18 (25.7) 16 (17.8) 5 (13.5) 181 (25.1)

Trial dates included 8 (12.9) 4 (11.8) 5 (2.5) 38 (31.1) 28 (26.2) 6 (8.6) 11 (12.2) 1 (2.7) 101 (14.0)

≥3 of 6 CONSORT items

30 (48.4) 6 (17.6) 29 (14.6) 57 (46.7) 71 (66.4) 25 (35.7) 29 (32.2) 2 (5.4) 249 (34.6)

Trial registration

Trial registered 47 (75.8) 18 (52.9) 145 (73.2) 45 (36.9) 79 (73.8) 54 (77.1) 67 (74.4) 22 (59.5) 477 (66.3)

Registered prospectivelya

29 (46.8) 10 (29.4) 79 (39.9) 21 (17.2) 34 (31.8) 31 (44.3) 34 (37.8) 10 (27.0) 248 (34.4)

Abbreviations: AASLD, American Association for the Study of Liver Diseases, The Liver Meeting, October 20-24, 2017, Washington, DC; ACC, American College of Cardiology, Annual Scientific Session, March 17-19, 2017, Washington, DC; ADA, American Diabetes Association, Scientific Sessions, June 9-17, 2017, San Diego, California; AUA, American Urological Association, Annual Meeting, May 12-16. 2017, Boston, Massachusetts; DDW, American Gastroenterological Association, Digestive Disease Week, May 6-9, 2017, Chicago, Illinois; CONSORT, Consolidated Standards of Reporting Trials; EASL, European Association for the Study of the Liver, Annual Meeting, April 19-23, 2017,

Amsterdam, the Netherlands; KW, American Society of Nephrology, Kidney Week, October 31 to November 5, 2017, New Orleans, Louisiana; OW, Obesity Society and American Society for Metabolic & Bariatric Surgery, Obesity Week, October 29 to November 2, 2017. a For trials registered at ClinicalTrials.gov, the number of days from the receipt

of the registration information to the start date was used to determine prospective registration. For other trials, the classification was obtained from the World Health Organization International Clinical Trials Registry Platform.4

Letters

1716 JAMA Internal Medicine December 2019 Volume 179, Number 12 (Reprinted) jamainternalmedicine.com

© 2019 American Medical Association. All rights reserved.

Downloaded From: https://jamanetwork.com/ on 03/25/2022