Literature DB >> 28129332

Relationship between Early Physician Follow-Up and 30-Day Readmission after Acute Myocardial Infarction and Heart Failure.

Yu-Chi Tung1, Guann-Ming Chang2,3, Hsien-Yen Chang4, Tsung-Hsien Yu5.   

Abstract

BACKGROUND: Thirty-day readmission rates after acute myocardial infarction (AMI) and heart failure are important patient outcome metrics. Early post-discharge physician follow-up has been promoted as a method of reducing 30-day readmission rates. However, the relationships between early post-discharge follow-up and 30-day readmission for AMI and heart failure are inconclusive. We used nationwide population-based data to examine associations between 7-day physician follow-up and 30-day readmission, and further associations of 7-day same physician (during the index hospitalization and at follow-up) and cardiologist follow-up with 30-day readmission for non-ST-segment-elevation myocardial infarction (NSTEMI) or heart failure.
METHODS: We analyzed all patients 18 years or older with NSTEMI and heart failure and discharged from hospitals in 2010 in Taiwan through Taiwan's National Health Insurance Research Database. Cox proportional hazard models with robust sandwich variance estimates and propensity score weighting were performed after adjustment for patient and hospital characteristics to test associations between 7-day physician follow-up and 30-day readmission.
RESULTS: The study population for NSTEMI and heart failure included 5,008 and 13,577 patients, respectively. Early physician follow-up was associated with a lower hazard ratio of readmission compared with no early physician follow-up for patients with NSTEMI (hazard ratio [HR], 0.47; 95% confidence interval [CI], 0.39-0.57), and for patients with heart failure (HR, 0.54; 95% CI, 0.48-0.60). Same physician follow-up was associated with a reduced hazard ratio of readmission compared with different physician follow-up for patients with NSTEMI (HR, 0.56; 95% CI, 0.48-0.65), and for patients with heart failure (HR, 0.69; 95% CI, 0.62-0.76).
CONCLUSIONS: For each condition, patients who have an outpatient visit with a physician within 7 days of discharge have a lower risk of 30-day readmission. Moreover, patients who have an outpatient visit with the same physician within 7 days of discharge have a much lower risk of 30-day readmission.

Entities:  

Mesh:

Year:  2017        PMID: 28129332      PMCID: PMC5271349          DOI: 10.1371/journal.pone.0170061

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Policy makers, clinicians, and payers who seek to improve outcomes in health care are focusing on 30-day readmission rates for patients with acute myocardial infarction and those with heart failure.[1] Early post-discharge physician follow-up has been promoted as a method of reducing readmission rates.[2] However, studies on the relationships between early post-discharge follow-up and patient outcomes for acute myocardial infarction and heart failure are not only rare but also inconclusive. Of only two studies we are aware of on this topic, one showed that discharge from hospitals that have higher early follow-up rates is associated with a reduction in 30-day readmission for heart failure,[3] but another did not establish such relationship for acute myocardial infarction.[4] Moreover, to our knowledge, no study has examined whether early follow-up with the same physician or with a cardiologist is associated with lower 30-day readmission for patients with acute myocardial infarction and those with heart failure. Early or timely outpatient follow-up with a physician for further assessment or treatment has been hypothesized to have an effect on reduced readmission among discharged patients with heart failure and those with acute myocardial infarction.[3-7] The transition from hospital to home is a period of particularly higher risk. Timely post-discharge follow-up has been suggested as an important component of efforts to optimize transitional care during the high-risk peri-discharge period.[8, 9] With physiological stress and allostatic load derived from hospitalization, the risks in the critical 30-day period after discharge might exist.[10] More importantly, the immediate days that follow discharge are also a vulnerable period owing to the additional therapies or changes in existing medical therapy that may worsen patient outcomes.[3, 11] Seven-day follow-up with the physicians may have the benefit of improving patient outcomes through providing clinical interventions on disease instability (such as diagnostic testing and medication changes),[12] and 7-day follow-up with the same physician (because of physician continuity) or with a specialist (because of physician specialty) may be associated with better outcomes than follow-up with other physicians.[3, 4] However, few studies have examined the relationship between 7-day physician follow-up and patient outcomes. In Taiwan, the National Health Insurance Administration has been the sole insurer and implemented national health insurance since March 1, 1995. The coverage rate of national health insurance has reached 99.9%, and almost all health care facilities are national health insurance contracted providers. Every enrollee is free to go to any hospital or clinic, and enjoys comprehensive benefits with a low cost-sharing policy (10% coinsurance for inpatient care with a yearly cap of about US$1700, and a US$1.7–12.0 copayment for outpatient visits). The National Health Insurance Administration has reimbursed providers mainly on a fee-for-service basis since the beginning of the national health insurance program. The Hospital Readmissions Reduction Program, which, under the Affordable Care Act, requires the Centers for Medicare & Medicaid Services to reduce payments to hospitals with excessive readmission rates regarding acute myocardial infarction and heart failure,[13] has not yet been introduced in Taiwan. Therefore, Taiwan’s healthcare system provides an excellent opportunity to examine whether early post-discharge follow-up improves patient outcomes for patients with acute myocardial infarction and those with heart failure. To better understand the relationship between early post-discharge follow-up and patient outcomes, we used nationwide population-based data from Taiwan to examine whether physician follow-up within 7 days of discharge was associated with a reduction in 30-day readmission for patients with acute myocardial infarction and those with heart failure. We also further determined whether early follow-up with the same physician or with a cardiologist was associated with much better patient outcomes.

Methods

Database

In this study, we used the National Health Insurance Research Database, provided by the National Health Insurance Administration and managed by the National Health Research Institutes in Taiwan. The database, which is released annually, consists of the following dimensions: inpatient medical benefit claims, ambulatory care medical benefit claims, pharmaceutical benefit claims, contracted medical care institutions, health professionals in contracted medical care institutions, and beneficiaries. Therefore, the database provides an opportunity to examine the relationship between early post-discharge follow-up and patient outcomes.

Ethical Statement

The protocol for this study was approved by the Institutional Review Board of the National Taiwan University Hospital (protocol # 201601056RINB). The dataset we used in this study was secondary data; all information was de-identified by data owners.

Study Population

This study included all patients aged 18 years and over who were discharged from general acute care hospitals in 2010, with a principal diagnosis of acute myocardial infarction without ST-segment elevation (International Classification of Diseases, 9th revision, clinical modification [ICD-9-CM] code 410.7)[4, 14–16] and heart failure with or without preserved ejection fraction (ICD-9-CM code 428), respectively.[17-20] Only the first admission of patients with multiple hospitalizations was included for the same medical condition.[3, 4] We excluded patients who were admitted with the same medical condition during the past 6 years, died in the hospital, were transferred out, left the hospital against medical advice, or were discharged against medical advice in a terminally critical condition.[4, 21]

Measures of Variables

Early follow-up

Early follow-up was defined as whether discharged patients had an outpatient visit with a physician within 7 days after discharge.[3, 4] The length of seven days was selected to be consistent with current efforts to improve transitional care.[22] Early follow-up with the same physician was measured as whether discharged patients visited the same physician during the hospitalization and during early follow-up.[3] Patients who visit the same physician during the hospitalization and at follow-up are considered to have better continuity of care.[3, 19] Early follow-up with a cardiologist was defined as whether discharged patients visited a cardiologist within 7 days after discharge.[3, 4] To explore whether the combined effect of same physician follow-up and cardiologist follow-up on patient outcomes, the interaction term between same physician follow-up and cardiologist follow-up was also considered.

Patient and hospital characteristics

The covariates included patient and hospital characteristics. The patient covariates included sex, age, comorbid conditions, medical history, in-hospital treatment (percutaneous coronary intervention use, intensive care unit use, administration of surgical operation), length of stay, baseline medications (aspirin, β-blocker, statin, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker), medications within 7 days of discharge, low income, rural residence, number of hospitalizations during the past year, and number of office visits during the past year.[3, 4, 9, 19, 23–26]. The Charlson-Deyo index was used to quantify patient comorbidities.[27] This index is the sum of the weighted scores based on the presence or absence of 17 different medical conditions during the past year and the index hospitalization. A score of 0 means that no comorbid index is present, and higher scores point to a greater burden of comorbidity. In addition, we also measured patients’ medical history specially related to cardiovascular conditions during the past year and the index hospitalization, which included cardiac risk factors (hypertension, diabetes mellitus), prior cardiac conditions (myocardial infarction, heart failure, atrial fibrillation or flutter), and medical comorbidities (peripheral vascular disease, renal disease).[28] The use of the baseline medications was measured according to whether the medications were prescribed during hospital stays and at discharge. Low income was measured as whether the patient was enrolled as a low-income beneficiary. Rural residence was measured whether the patient lived in a rural area based on previous studies using National Health Insurance Research Database.[29-32] The hospital covariates included hospital volume (low, medium, high), hospital level (academic medical center, regional, district), teaching status (yes/no), and geographic location (Taipei, northern, central, southern, Kao-Ping, eastern). We determined the volume of patients who were treated at hospitals using annual condition-specific volume, and then we divided these “annualized” volumes into tertiles.

Outcome measures

Our primary outcome was 30-day all-cause readmission, which was defined as any re-hospitalization to any acute care hospital within 30 days from index discharge.[3, 4] Hospital readmissions are regarded as potential indicators of poor care or missed opportunities to better coordinate care.[33, 34] Additionally, readmission is expensive to the health care system and commonly represents a preventable adverse event for patients.[24] Secondary outcomes of interest were readmission within 30 days of discharge for cardiovascular cause (primary and secondary ICD-9-CM codes 390–459)[17, 35] and readmission within 30 days of discharge for the same cause as the index hospitalization.

Statistical Analysis

We used Cox proportional hazard models with robust sandwich variance estimates and propensity score weighting, adjusted for all patient and hospital characteristics, to examine the association between 7-day physician follow-up and 30-day readmission for acute myocardial infarction and heart failure.[28, 36] Cox proportional hazard models allows us to take into account the length of survival after discharge to avoid the problem that patients with early visit are the most severe ones and then they were less likely to be re-hospitalized because they die more often. The models focused on time from discharge until the first re-hospitalization date during the 30 days of follow-up. Patients were censored on date of death, or 30 days post-discharge, whichever came first. All analyses were adjusted for clustering at the hospital level with the use of robust sandwich variance estimates. We modeled 30-day readmission as a function of 7-day physician follow-up, sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, hospital level, teaching status, and geographic location. Moreover, we used propensity score analyses to reduce the selection bias and the potential baseline differences between the early follow-up and the no early follow-up groups.[9, 28] Propensity scores were computed by modeling a logistic regression model in which the dependent variable was whether the discharged patient had an outpatient visit with a physician within 7 days after discharge. The independent variables were patient sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, hospital level, teaching status, and geographic location. Then, each patient was weighted by the inverse propensity score when performing Cox proportional hazard models with robust sandwich variance estimates to reduce the selection bias.[25, 37–40] Finally, we further used Cox proportional hazard models with robust sandwich variance estimates, adjusted for all patient (including medications after discharge) and hospital characteristics, to examine the individual and combined associations of early same physician and early cardiologist follow-up with 30-day readmission among the early follow-up group. In sensitivity analyses, we changed the definition of early physician follow-up by allowing early follow-up to occur within 14 days after discharge.[3] Statistical significance was indicated by a 2-tailed value of P<0.05. All analyses were performed with SAS version 9.3 (SAS Institute Inc, Cary, NC).

Results

Baseline Characteristics and Outcomes

Regarding non-ST-segment-elevation myocardial infarction (NSTEMI), we identified 6596 patients discharged from hospital in 2010. We excluded patients under age 18 (N = 0), and patients who had subsequent admission with NSTEMI (N = 397), or had previous admission with NSTEMI during the past 6 years (N = 249). After exclusions (Fig 1), the final NSTEMI population included 5008 patients. The final population with heart failure consisted of 13577 patients.
Fig 1

Flow diagram of patient selection.

Shown are inclusions and exclusions and the final study cohort. HF indicates heart failure; NSTEMI, non-ST-segment-elevation myocardial infarction.

Flow diagram of patient selection.

Shown are inclusions and exclusions and the final study cohort. HF indicates heart failure; NSTEMI, non-ST-segment-elevation myocardial infarction. Table 1 presents these patient characteristics. Among patients with NSTEMI, rates of early follow-up with a physician, with the same physician, and with a cardiologist were 76.7%, 56.1%, and 44.8%, respectively. Among those with heart failure, rates of early follow-up with a physician, with the same physician, and with a cardiologist were 74.9%, 52.9%, and 37.6%, respectively. Thirty-day all-cause readmission rates for patients with NSTEMI and those with heart failure were 19.9% and 23.3%, respectively.
Table 1

Characteristics of the study population.

NSTEMIHeart failure
N(%)N(%)
No. of patients5008(100.0)13577(100.0)
Follow-up with a physician
 7-day3841(76.7)10164(74.9)
 14-day4664(93.1)12197(89.8)
Follow-up with the same physician
 7-day2807(56.1)7178(52.9)
 14-day3614(72.2)8996(66.3)
Follow-up with a cardiologist
 7-day2242(44.8)5103(37.6)
 14-day2862(57.1)6455(47.5)
Patient Characteristics
 Male sex3367(67.2)6824(50.3)
 Age, y
  18–49520(10.4)1026(7.6)
  50–641456(29.1)2345(17.3)
  65–791920(38.3)5058(37.3)
  80+1112(22.2)5148(37.9)
 Charlson score
  0–12181(43.6)3838(28.3)
  2–31518(30.3)4988(36.7)
  4+1309(26.1)4751(35.0)
 Medical history
  Hypertension3829(76.5)10617(78.2)
   No1179(23.5)2960(21.8)
  Diabetes mellitus2439(48.7)6194(45.6)
   No2569(51.3)7383(54.4)
  Myocardial infarction650(13.0)1304(9.6)
   No4358(87.0)12273(90.4)
  Heart Failure827(16.5)5930(43.7)
   No4181(83.5)7647(56.3)
  Atrial fibrillation or flutter511(10.2)3889(28.6)
   No4497(89.8)9688(71.4)
  Peripheral vascular disease182(3.6)564(4.2)
   No4826(96.4)13013(95.8)
  Renal disease923(18.4)2697(19.9)
   No4085(81.6)10880(80.1)
 In-hospital treatment
  PCI2893(57.8)458(3.4)
  Intensive care unit use4311(86.1)2969(21.9)
  Surgery use471(9.4)582(4.3)
 Length of stay, d
  <52039(40.7)5671(41.8)
  6–91512(30.2)4366(32.2)
  10+1457(29.1)3540(26.1)
 Baseline medications
  Aspirin4710(94.0)6573(48.4)
  β-Blocker3183(63.6)5268(38.8)
  Statin2961(59.1)2283(16.8)
  ACEI/ARB3610(72.1)7995(58.9)
 Medications within 7 days of discharge
  Aspirin2590(51.7)3571(26.3)
  β-Blocker1832(36.6)3233(23.8)
  Statin1670(33.3)1292(9.5)
  ACEI/ARB1792(35.8)4305(31.7)
 Medications within 14 days of discharge
  Aspirin3425(68.4)4637(34.2)
  β-Blocker2450(48.9)4380(32.3)
  Statin2272(45.4)1752(12.9)
  ACEI/ARB2403(48.0)5660(41.7)
 Low income98(2.0)305(2.2)
 Rural residence1205(24.1)3687(27.2)
 Number of hospitalizations during the past year
  03312(66.1)6935(51.1)
  1942(18.8)3344(24.6)
  2+754(15.1)3298(24.3)
 Number of outpatient visits during the past year
  Low1696(33.9)4610(34.0)
  Medium1648(32.9)4447(32.8)
  High1664(33.2)4520(33.3)
Hospital Characteristics
 Hospital volume
  Low1685(33.6)4675(34.4)
  Medium1693(33.8)4575(33.7)
  High1630(32.5)4327(31.9)
 Hospital level
  Academic medical center2797(55.9)4571(33.7)
  Regional2077(41.5)6984(51.4)
  District134(2.7)2022(14.9)
 Teaching4939(98.6)12003(88.4)
 Location
  Taipei1743(34.8)4608(33.9)
  Northern581(11.6)1841(13.6)
  Central799(16.0)2534(18.7)
  Southern858(17.1)2054(15.1)
  Kao-Ping855(17.1)2073(15.3)
  Eastern172(3.4)467(3.4)
Patient outcomes
 30-day readmission
  All-cause998(19.9)3169(23.3)
  Specific-cause
   Cardiovascular935(18.7)2842(20.9)
   Same diagnosis182(3.6)1983(14.6)

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention.

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention.

Associations of Early Follow-Up with Patient and Hospital Characteristics

Table 2 shows the comparison of the discharges followed by outpatient visits with a physician within 7 days to those without. For NSTEMI, baseline characteristics that differed between the follow-up and the no follow-up groups were medical history (heart failure, atrial fibrillation or flutter),PCI use, length of saty, statin use, number of outpatient visits during the past year, hospital volume, level, and location. For heart failure, baseline characteristics that differed between the follow-up and the no follow-up groups were medical history (hypertension, heart failure), PCI use, length of stay, number of hospitalizations during the past year, number of outpatient visits during the past year, hospital volume, level, teaching status, and location. After propensity score weighting, the two groups for NSTEMI and heart failure were well balanced for the baseline characteristics.
Table 2

Baseline characteristics by early follow-up.

NSTEMIHeart failure
UnweightingWeightingaUnweightingWeightinga
Follow-upFollow-upFollow-upFollow-up
Yes, %No, %P valueYes, %No, %P valueYes, %No, %P valueYes, %No, %P value
Patient Characteristics
 Sex
  Male67.167.70.70167.266.70.60250.051.00.31250.249.80.495
  Female32.932.332.933.350.049.049.850.2
 Age, y
  18–4910.310.80.64210.410.90.8517.38.30.0707.67.60.974
  50–6429.228.729.128.417.217.617.217.0
  65–7938.737.238.338.637.835.737.337.3
  80+21.923.322.222.237.838.437.938.1
 Charlson score
  0–143.543.60.21443.643.50.99628.128.70.79628.328.40.796
  2–329.832.030.330.436.836.436.837.1
  4+26.724.426.226.235.034.835.034.6
 Medical history
  Hypertension
   Yes76.875.50.37576.577.00.52978.776.70.01778.278.10.850
   No23.224.523.523.021.323.321.821.9
  Diabetes mellitus
   Yes48.648.90.86048.748.70.98045.844.90.36045.645.40.781
   No51.451.151.351.354.255.154.454.6
  Myocardial infarction
   Yes12.713.80.34313.012.50.4599.310.40.0799.69.60.961
   No87.386.287.087.590.789.690.490.4
  Heart Failure
   Yes15.619.50.00216.516.40.91743.045.60.00943.743.50.828
   No84.480.583.583.657.054.456.356.5
  Atrial fibrillation or flutter
   Yes9.711.90.02810.210.00.78828.828.10.41528.728.90.642
   No90.388.189.890.071.271.971.371.1
  Peripheral vascular disease
   Yes3.73.50.8013.63.70.8654.14.20.7494.24.10.835
   No96.396.596.496.395.995.895.995.9
  Renal disease
   Yes18.617.90.60018.518.60.88219.819.90.92019.819.50.552
   No81.482.181.581.480.280.180.280.5
 In-hospital treatment
  PCI
   Yes59.153.3<0.00157.757.40.7483.72.3<0.0013.43.30.583
   No40.946.742.342.696.397.796.696.8
  Intensive care unit use
   Yes86.086.50.67086.186.10.93421.722.40.39821.921.80.966
   No14.013.513.913.978.377.678.178.2
  Surgery use
   Yes9.59.20.7529.410.00.3844.24.60.2534.34.20.850
   No90.590.890.690.095.895.495.795.8
 Length of stay, d
  <541.438.30.04340.740.70.99342.639.4<0.00141.841.80.916
  6–930.329.830.230.332.531.232.232.4
  10+28.231.929.129.024.929.426.125.9
 Baseline medications
  Aspirin
   Yes94.492.90.05594.194.20.77348.548.10.68348.448.30.832
   No5.67.15.95.851.551.951.651.7
  β-Blocker
   Yes63.862.70.49963.664.00.70738.739.10.69338.838.60.739
   No36.237.336.436.061.360.961.261.4
  Statin
   Yes58.361.70.04159.159.40.80016.816.70.87816.816.80.995
   No41.738.340.940.683.283.383.283.2
  ACEI/ARB
   Yes71.673.80.14172.171.60.64458.958.90.96158.958.60.681
   No28.426.228.028.441.141.141.141.4
 Low income
  Yes1.92.10.7792.02.10.6692.12.60.0752.22.20.679
  No98.197.998.097.997.997.497.897.8
 Rural residence
  Yes24.423.00.31724.123.90.87227.426.30.18427.227.30.776
  No75.677.076.076.172.673.772.872.7
 Number of hospitalizations during the past year
  066.963.80.10566.165.60.78452.148.1<0.00151.151.50.798
  118.220.718.919.424.525.024.624.5
  2+14.915.515.115.023.426.924.324.0
 Number of outpatient visits during the past year
  Low32.737.6<0.00133.833.40.88931.940.0<0.00133.933.90.982
  Medium32.035.933.033.432.334.032.832.9
  High35.326.533.233.235.726.033.333.3
Hospital Characteristics
 Hospital volume
  Low35.328.2<0.00133.734.40.78335.531.4<0.00134.434.30.819
  Medium33.933.533.833.633.933.233.734.1
  High30.838.332.532.130.735.431.931.6
 Hospital level
  Academic medical center53.962.4<0.00155.855.00.74231.540.1<0.00133.733.70.967
  Regional43.235.741.642.353.046.751.451.3
  District2.91.92.72.715.513.214.915.0
 Teaching
  Yes98.598.90.3771.41.40.87488.189.40.04388.488.40.946
  No1.51.198.698.611.910.611.611.6
 Location
  Taipei34.037.4<0.00134.733.80.93432.937.0<0.00133.933.90.997
  Northern10.913.911.611.613.713.013.513.4
  Central15.218.316.016.218.618.718.718.8
  Southern18.213.517.217.816.012.615.115.2
  Kao-Ping18.412.917.117.315.215.615.315.3
  Eastern3.34.03.43.33.63.13.43.4

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention.

aBased on propensity score weighting.

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention. aBased on propensity score weighting.

Associations between Early Follow-Up and 30-Day Readmission

Table 3 shows the unadjusted associations of early physician follow-up, and patient and hospital characteristics with 30-day readmission. For each condition, early follow-up with a physician, early follow-up with the same physician, and early follow-up with a cardiologist were associated with reduced 30-day readmission. For two conditions, patient and hospital characteristics associated with 30-day readmission were patient sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, medications within 7 days of discharge, low income, number of hospitalizations during the past year, number of outpatient visits during the past year, hospital volume, level, and teaching status.
Table 3

30-day all-cause readmission rates by follow-up and baseline characteristics.

NSTEMIHeart failure
%P value%P value
Early follow-up
 Yes17.4<0.00120.7<0.001
 No28.331.2
Early follow-up with the same physician
 Yes14.4<0.00118.1<0.001
 No27.029.2
Early follow-up with a cardiologist
 Yes15.3<0.00118.1<0.001
 No23.626.5
Patient Characteristics
 Sex
  Male18.5<0.00123.80.205
  Female22.922.9
 Age (yr)
  18–4911.7<0.00118.4<0.001
  50–6416.920.0
  65–7921.223.3
  80+25.525.9
 Charlson score
  0–112.3<0.00117.9<0.001
  2–322.022.0
  4+30.229.1
 Medical history
  Hypertension
   Yes21.1<0.00123.70.086
   No16.022.2
  Diabetes mellitus
   Yes24.3<0.00124.8<0.001
   No15.822.1
  Myocardial infarction
   Yes22.90.04026.50.005
   No19.523.0
  Heart Failure
   Yes30.2<0.00125.6<0.001
   No17.921.6
  Atrial fibrillation or flutter
   Yes24.70.00522.40.090
   No19.423.7
  Peripheral vascular disease
   Yes25.30.06628.90.001
   No19.723.1
  Renal disease
   Yes30.3<0.00128.6<0.001
   No17.622.0
 In-hospital treatment
  PCI
   Yes13.4<0.00117.70.004
   No28.823.5
  Intensive care unit use
   Yes19.90.75126.3<0.001
   No20.422.5
  Surgery use
   Yes27.4<0.00126.50.069
   No19.223.2
 Length of stay (d)
  <514.4<0.00119.7<0.001
  6–918.822.7
  10+28.929.9
 Baseline medications
  Aspirin
   Yes19.50.00522.50.028
   No26.224.1
  β-Blocker
   Yes19.20.07421.5<0.001
   No21.324.5
  Statin
   Yes17.8<0.00121.50.020
   No23.023.7
  ACEI/ARB
   Yes18.90.00321.8<0.001
   No22.625.6
 Medications within 7 days of discharge
  Aspirin
   Yes14.4<0.00119.4<0.001
   No25.824.8
  β-Blocker
   Yes15.1<0.00118.1<0.001
   No22.725.0
  Statin
   Yes13.8<0.00117.0<0.001
   No23.024.0
  ACEI/ARB
   Yes15.1<0.00117.1<0.001
   No22.626.2
 Medications within 14 days of discharge
  Aspirin
   Yes14.6<0.00119.3<0.001
   No31.525.4
  β-Blocker
   Yes15.3<0.00118.1<0.001
   No24.425.8
  Statin
   Yes13.8<0.00117.6<0.001
   No25.024.2
  ACEI/ARB
   Yes14.6<0.00117.0<0.001
   No24.927.8
 Low income
  Yes32.70.00127.90.059
  No19.723.2
 Rural residence
  Yes21.20.21923.40.876
  No19.523.3
 Number of hospitalizations during the past year
  015.5<0.00118.2<0.001
  126.023.4
  2+32.034.0
 Number of outpatient visits during the past year
  Low14.8<0.00120.3<0.001
  Medium19.723.3
  High25.426.5
Hospital Characteristics
 Hospital volume
  Low21.20.04125.5<0.001
  Medium20.623.4
  High17.921.0
 Hospital level
  Academic medical center18.0<0.00120.0<0.001
  Regional22.024.3
  District28.427.6
 Teaching
  Yes19.70.00122.9<0.001
  No36.226.9
 Location
  Taipei18.10.12722.10.134
  Northern19.123.1
  Central20.324.1
  Southern22.125.1
  Kao-Ping21.123.7
  Eastern23.323.6

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention.

NSTEMI indicates non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention. The results of the series of Cox proportional hazard models with robust sandwich variance estimates and propensity score weighting as provided in Table 4 demonstrate the associations between early follow-up and 30-day readmission, after adjustment for patient and hospital characteristics. In model 1, early physician follow-up was associated with a lower hazard ratio of all-cause readmission compared with no early physician follow-up for patients with NSTEMI (hazard ratio [HR], 0.47; 95% confidence interval [CI], 0.39–0.57), and for patients with heart failure (HR, 0.54; 95% CI, 0.48–0.60). Early physician follow-up was also associated with lower 30-day cardiovascular-cause and same-cause readmission.
Table 4

Adjusted relationships between early physician follow-up and 30-day readmission.

All-causeCardiovascular-causeSame-cause
HR(95% CI)HR(95% CI)HR(95% CI)
NSTEMI
Model 1: early physician follow-upaN = 5008
 Yes (ref: No)0.47(0.39–0.57)0.48(0.40–0.57)0.59(0.41–0.86)
Model 2: early physician follow-upbN = 3841
 Same physician follow-up (ref: No)0.56(0.48–0.65)0.56(0.47–0.66)0.62(0.38–0.99)
 Cardiologist follow-up (ref: No)0.97(0.81–1.16)1.03(0.86–1.24)0.81(0.54–1.23)
Model 3: 14-Day physician follow-upaN = 5008
 Yes (ref: No)0.18(0.14–0.24)0.20(0.15–0.26)0.26(0.17–0.39)
Model 4: 14-Day physician follow-upbN = 4664
 Same physician follow-up (ref: No)0.53(0.44–0.62)0.51(0.43–0.61)0.59(0.39–0.92)
 Cardiologist follow-up (ref: No)0.85(0.73–1.00)0.89(0.76–1.05)0.85(0.58–1.24)
Heart failure
Model 1: early physician follow-upaN = 13577
 Yes (ref: No)0.54(0.48–0.60)0.57(0.51–0.64)0.59(0.52–0.66)
Model 2: early physician follow-upbN = 10164
 Same physician follow-up (ref: No)0.69(0.62–0.76)0.69(0.62–0.76)0.77(0.68–0.87)
 Cardiologist follow-up (ref: No)0.94(0.85–1.04)0.99(0.90–1.10)1.03(0.91–1.17)
Model 3: 14-Day physician follow-upaN = 13577
 Yes (ref: No)0.28(0.25–0.32)0.31(0.27–0.34)0.32(0.28–0.36)
Model 4: 14-Day physician follow-upbN = 12197
 Same physician follow-up (ref: No)0.63(0.58–0.68)0.64(0.59–0.70)0.71(0.64–0.80)
 Cardiologist follow-up (ref: No)0.94(0.86–1.03)1.00(0.91–1.09)1.05(0.94–1.18)

CI indicates confidence interval; HR, hazard ratio; NSTEMI, non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention.

aModels included sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, level, teaching status, and location, and were weighted by the inverse of a propensity score

bModels included sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, medications within 7(14) days of discharge, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, level, teaching status, and location.

CI indicates confidence interval; HR, hazard ratio; NSTEMI, non-ST-segment-elevation myocardial infarction; and PCI, percutaneous coronary intervention. aModels included sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, level, teaching status, and location, and were weighted by the inverse of a propensity score bModels included sex, age, comorbid conditions, medical history, in-hospital treatment, length of stay, baseline medications, medications within 7(14) days of discharge, low income, rural residence, number of hospitalizations during the past year, number of office visits during the past year, hospital volume, level, teaching status, and location. To further determine the individual and combined associations of same physician and cardiologist follow-up with 30-day readmission among patients with early follow-up, we did not find the synergistic associations between the effects of same physician and cardiologist follow-up. Therefore, an interaction term between same physician and cardiologist follow-up was removed in model 2. Same physician follow-up was associated with a lower hazard ratio of all-cause readmission compared with different physician follow-up for patients with NSTEMI (HR, 0.56; 95% CI, 0.48–0.65), and for patients with heart failure (HR, 0.69; 95% CI, 0.62–0.76). Same physician follow-up was also associated with lower 30-day cardiovascular-cause and same-cause readmission. The robustness of our primary results were evaluated by sensitivity analysis. Results were similar when we changed the transitional period from 7 days to 14 days.

Discussion

This study was the first research using nationwide population-based data to examine the association between early physician follow-up and 30-day readmission, and the relative association of early same physician and early cardiologist follow-up with 30-day readmission for NSTEMI and heart failure. For each condition, we found that early physician follow-up was associated with decreased 30-day readmission compared with no early physician follow-up. Moreover, early follow-up with the same physician was associated with lower 30-day readmission compared with early follow-up with a different physician. In Taiwan, about 75% percent of hospitalized patients with NSTEMI and heart failure had an outpatient visit within 7 days of discharge. Most early follow-up care was handled by the same physician who treated the patient during the index hospitalization, and usually by cardiologists. The rates of early physician, early same physician and early cardiologist follow-up in Taiwan were higher than those in the United States (38.3%, 18.1%, and 7.5%, respectively, for heart failure).[3] These results are because all hospitals in Taiwan are closed systems and are reimbursed for both inpatient and outpatient services on a fee-for-service basis by the National Health Insurance Administration (NHIA). Thus, physicians only employed by hospitals can be allowed to treat inpatients, and hospitals also use variable pay to encourage staff physicians to provide inpatient and outpatient services. Moreover, clinical guidelines recommend early physician follow-up. Therefore, most hospital physicians not only prescribe a week's supply of medicine at discharge, but also schedule a follow-up appointment within 7 days of discharge. This study had two major findings about the association between early physician follow-up and 30-day readmission for NSTEMI and heart failure. First, we found that early follow-up with any physician was associated with lower 30-day readmission for each condition. This result is consistent with the finding of Hernandez et al.[3] Hernandez et al verified the association between hospital-level early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure. However, the aggregate group-level (hospital-level) variable may be tapping into a different construct than its individual-level (patient-level) namesake.[41-43] Thus, the limitations of using an aggregate measure as a proxy for its individual-level namesake relate not only to measurement errors but also to construct validity, that is, whether it is indeed the same construct that is measured by both variables.[41, 43, 44] It also must be noted that at the patient level, the association between time from hospital discharge to outpatient follow-up with a physician and risk of readmission is confounded by severity of illness. Patients who have more severe acute myocardial infarction or heart failure, or who are medically less stable are not only commonly seen sooner after hospital discharge but also at a greater risk of readmission.[3, 4] Therefore, we used a propensity score approach to correct for the selection bias. The use of a propensity score method can help reduce the selection bias and provide more valid analysis results. This study may support current clinical guidelines advocating for patients with heart failure or NSTEMI who have been discharged from hospital to receive early or timely outpatient follow-up with a physician for further assessment or treatment.[5, 7] Another notable finding was that early same physician follow-up (physician continuity) was associated with a further reduction in 30-day readmission. This finding is consistent with that of van Walraven et al[23] and of McAlister et al.[19] In Ontario, Canada, Walraven et al found that 30-day follow-up with the same physician, rather than with another physician, was associated with reduced 30-day post-discharge mortality or non-elective readmission for non-elective medical or surgical conditions. In Alberta, Canada, McAlister et al found that 30-day follow-up with a familiar physician was associated with lower 3-month post-discharge mortality or urgent readmission for heart failure compared with no follow-up. Although at discharge disease progression is improved, remission is not achieved. Because of early follow-up with a different physician, if the physician does not know a particular patient’s disease progression, their progression could possibly be interpreted as a deterioration requiring readmission.[23] Moreover, early same physician follow-up is more likely to early determine therapeutic effectiveness and early identify complications of hospital therapies or procedures due to familiarity with the hospital course. Early evaluation and treatment could avoid more serious subsequent problems leading to readmission. Some limitations existed in this study. First of all, patients were not assigned randomly. This is an observational and retrospective study; therefore, we cannot assign study subjects randomly. The propensity score weighting was adopted for alleviating selection bias.[25, 37–40] Moreover, although, like other studies using administrative databases, no information on disease severity was available for risk adjustment, we adjusted for patient age, comorbid conditions, intensive care unit use, and surgical operation, which are also important for the adjustment of disease complexity.[9, 19, 23–26] However, we cannot completely exclude the possibility of unmeasured confounders such as behavioral risk factors. Differences in outcomes between follow-up and non-follow-up groups may be confounded by unmeasured behavioral risk factors that may influence access to care. Second, this study defined early follow-up as an outpatient visit that occurred within 7 days of discharge. The 7-day window has previously been discussed and was chosen according to historical precedent and clinical plausibility.[3, 4] However, we also did a sensitivity analysis examining the association between 14-day follow-up and 30-day readmission. Finally, in Taiwan, follow-up with a trained and specialized nurse (care manager) is not common until now. This may be because the service is not reimbursed by the NHIA. Based on two related studies, one study regarding discharged patient with heart failure in Northern California, United States finds that early outpatient follow-up with a physician is associated with a lower chance of 30-day readmission, but telephone follow-up with a trained and specialized nurse or pharmacist is not.[45] Another study regarding ambulatory patients with heart failure in the Apulia Region of Italy finds that the introduction of care managers into the primary health care system has the potential of reducing readmissions because of the strong partnership between the care manager and the patient and the collaboration between the physician and the care manager.[46] Future research needs to examine whether the effect of early follow-up visit with a care manager is the same as that with a physician among discharged patients with heart failure or acute myocardial infarction.

Conclusion

Our national population-based study showed that 7-day physician follow-up was associated with lower 30-day readmission, and physician continuity (7-day same physician follow-up) was associated with much lower 30-day readmission for patients with NSTEMI and those with heart failure. This study may provide evidence in support of guidelines recommending scheduling an early follow-up visit after discharge, and it may provide an evidenced-based approach to improve 30-day readmission following NSTEMI and heart failure.
  36 in total

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Authors:  Terry S Field; Jessica Ogarek; Lawrence Garber; George Reed; Jerry H Gurwitz
Journal:  J Gen Intern Med       Date:  2014-12-02       Impact factor: 5.128

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Authors:  Yu-Chi Tung; Guann-Ming Chang; Kuo-Liong Chien; Yu-Kang Tu
Journal:  Med Care       Date:  2014-06       Impact factor: 2.983

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Authors:  Yuting Zhang; Cameron M Kaplan; Seo Hyon Baik; Chung-Chou H Chang; Judith R Lave
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Authors:  Keane K Lee; Jingrong Yang; Adrian F Hernandez; Anthony E Steimle; Alan S Go
Journal:  Med Care       Date:  2016-04       Impact factor: 2.983

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Authors:  Carl van Walraven; Muhammad Mamdani; Jiming Fang; Peter C Austin
Journal:  J Gen Intern Med       Date:  2004-06       Impact factor: 5.128

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