Palliative Care Consults in the Southeast: Lower Readmissions Despite Increased Length of Stay

Abstract

Background

: Inpatient palliative care (PC) consultations are increasingly used to address operational challenges. We aimed to understand how PC consultations in a southeastern program, affected by pandemic-related care delays, impacted common clinical performance metrics.

Methods

: This is a retrospective analysis of a tertiary system’s adult patients who received PC consultations from December 2021 to August 2022. A Medicare Severity Diagnosis Related Groups (MS-DRG) code was identified for each PC encounter, and a comparison cohort was created from non-PC encounters.

Outcomes

: There were 1906 patients who received a PC consultation and 7730 patients in the matched cohort. Patients receiving a PC consultation were older (mean age 68.55 years) compared with the matched cohort (mean age 62.75 years). Despite a significantly longer length of stay (LOS) (12.46 days vs. 6.99 days, p < 0.001), the PC group experienced a lower readmission rate (adjusted odds ratio 0.54, 95% confidence interval 0.44–0.65, p < 0.001).

Conclusions

: Our cohort study using MS-DRG matching indicates that despite increased LOS, PC consultations were associated with significantly lower readmission rates. This suggests their potential to improve resource utilization, especially in regions affected by pandemic-deferred care.

Background

Early initiation of palliative care (PC) consults in patients with serious illness has been observed to improve patient-centered outcomes and act as cost-saving measures for health care systems.^1–3 Although length of stay (LOS) and readmission rates are clinical performance metrics that have been described in other studies,^4–6 what is not known is how these measures are affected while controlling for similar pathologies.

Medicare Severity Diagnosis Related Groups (MS-DRGs) are a set of classifications that encompass patient diagnoses and demographics to facilitate government payment of services. Patients with the same MS-DRGs are expected to use similar amounts of resources.^3,7 These differ from International Classification of Disease (ICD) codes, which stratify health conditions for medical documentation and research purposes. In contrast to ICD codes, only one MS-DRG is assigned for each patient encounter, so most institutions assign the highest severity MS-DRG code that applies. As of April 2024, there are 766 MS-DRGs and 73,202 ICD-10 codes.^8,9 Recent health analytic studies have demonstrated that the predictive power of MS-DRGs is not inferior to ICD-10 codes for outcomes such as morbidity, LOS, and readmission rates and require much less computing performance.^10,11 Consequently, MS-DRGs may be an important tool to group patients in PC comparative analyses.

Quality and access to PC are region dependent.¹² Factors that contribute to disparities in PC equity include socioeconomic status, diversity of cultures and races, and geographic distance to services.^13–15 Although services are expanding each year, the southeastern region continues to have the lowest penetration of PC services.¹⁶ Further, this region faced even increased challenges during the COVID-19 pandemic with increased delays in patient treatment.^17,18

This systems analysis used MS-DRG matching to compare patient groups who received PC consultations with those who did not in order to assess the impact of PC on clinical performance metrics in a southeastern academic medical center, particularly in the context of increased pandemic-deferred care. To our knowledge, this is the first study to utilize MS-DRGs for this purpose.

Methods

This retrospective study included all consecutive adult patients who received a PC consultation from December 2021 to August 2022 at an urban level-one trauma center located in the southeastern United States. Our academic 710-bed institution has a PC program that was initiated in March 2008. As of December 2021, the program consisted of two fellowship-trained physicians who worked collaboratively with 12 advanced practice providers. The service had a typical daily census of approximately 50–70 patients. Any hospital-associated service physician or provider was able to place an electronic consult for PC services at any time during the hospitalization. The mean time from electronic consult order placement to the consult note being signed was 11.2 hours during the study period. Patients were seen anywhere in the hospital including the emergency department, inpatient units (floors), and intensive care units (ICUs).

All patients admitted to the hospital who received PC consultation were sorted by their assigned MS-DRGs as determined by our Department of Medical Records and captured in the hospital’s billing database provided by HealthQuest Data Systems^©. All coders were certified per industry standards and per the Centers for Medicare and Medicaid Services guidelines, and only one MS-DRG of the highest applicable severity was assigned per patient encounter. A case-controlled, comparison cohort was created from patients with the same MS-DRGs but who did not receive any PC encounters during the same timeframe. MS-DRGs with a low volume of PC consults, considered to be less than three consults, were not included in the cohort group. Patients under 18, imprisoned or associated with an MS-DRG who qualified for business lines of obstetrics or neonatology, were excluded from analyses.

Primary outcomes were LOS and readmission rates. We reviewed admission notes, progress notes, and discharge summaries to gather these data. LOS was calculated by subtracting the discharge date from the admission date. Readmission rates were limited to the first 30 days postdischarge date and to the same hospital system. Secondary outcomes included the mean age of both cohorts and the most frequently used MS-DRGs.

Given that this project was for quality improvement purposes, our institutional review board, the University of Tennessee Graduate School of Medicine in Knoxville, waived the need for informed consent. There was no funding for this study. Deidentified data were procured from our hospital’s electronic medical record and stored in a password-protected database.

Frequency and percentage statistics were performed to describe the demographic and clinical characteristics of the sample. Chi-square analysis was performed to compare the categorical parameters between the two cohorts. An unadjusted odds ratio (OR) with a 95% confidence interval (95% CI) was calculated for any significant main effects found with chi-square analysis. Age and LOS were compared between the cohorts using independent samples t test. Means and standard deviations were reported and interpreted for the groups. To control for age, analysis of covariance (ANCOVA) was performed when testing for differences in LOS between the cohorts. Adjusted means with 95% CIs were reported and interpreted for the ANCOVA analysis. Statistical assumptions for parametric tests (normality, homogeneity of variance, and homogeneity of regression slopes) were assessed before interpretation. Logistic regression analysis was performed to adjust for age when testing the association between the cohorts and readmission. The adjusted odds ratio (AOR) with 95% CI was reported for the regression analysis. Statistical significance was assumed at an alpha value of 0.05, and all analyses were performed using SPSS Version 29 (Armonk, NY: IBM Corp.).

Outcomes

Between December 2021 and August 2022, there were 32,156 inpatient admissions that did not meet exclusion criteria. Of those, 1906 (5.93%) received a PC consult (Fig. 1), leaving 30,250 encounters that did not have PC involvement. For those who received PC consultation, 295 patients (15.5%) were seen in the emergency department, 960 patients (50.3%) were seen on the floors, and 651 patients (34.2%) were seen in the ICU. From the nonpalliative encounters, 7730 (25.6%) were matched via an MS-DRG code to a palliative encounter.

FIG. 1.

Flow diagram for selection of patients included in the study. PC, palliative care; non-PC, nonpalliative care.

MS-DRG Code “871 SEPTICEMIA OR SEVERE SEPSIS WITHOUT MECHANICAL VENTILATION >96 HOURS WITH MAJOR COMPLICATION OR COMORBIDITY” had the highest frequency of palliative consults with 277 from a total of 1500 patients (18.5%; Table 1). However, code “146 EAR MOUTH AND THROAT MALIGNANCY WITH MAJOR COMPLICATION OR COMORBIDITY” had the highest proportion (83.3%) of PC involvement. There were a total of 101 MS-DRG codes captured.

Table 1.

MS-DRGs That Had an Associated Palliative Care Consult

MS-DRG	PC consults	Total volume	Percentage
871: SEPTICEMIA OR SEVERE SEPSIS WO MV >96 HR W MCC	277	1500	18.5%
64: INTRACRANIAL HEMORRHAGE OR CEREBRAL INFARCTION W MCC	77	338	22.8%
853: INFECTIOUS AND PARASITIC DISEASES W O.R. PROC W MCC	71	338	21.0%
870: SEPTICEMIA OR SEVERE SEPSIS W MV >96 HR OR PERIPHERAL EXTRACORPOREAL MEMBRANE OXYGENATION (ECMO)	59	97	60.8%
291: HEART FAILURE AND SHOCK W MCC	55	479	11.5%
23: CRANIOTOMY W MAJOR DEVICE IMPLANT W MCC	41	124	33.1%
3: ECMO OR TRACHEOSTOMY WITH MV >96 HR OR PDX EXCEPT FACE, MOUTH AND NECK WITH MAJOR O.R. PROC	39	83	47.0%
177: RESPIRATORY INFECTIONS AND INFLAMMATIONS W MCC	39	402	9.7%
25: CRANIOTOMY AND ENDOVASCULAR INTRACRANIAL PROC W MCC	33	165	20.0%
4: TRACHEOSTOMY WITH MV >96 HR OR PDX EXCEPT FACE, MOUTH AND NECK WITHOUT MAJOR O.R. PROC	31	55	56.4%
640: MISCELLANEOUS DISORDERS OF NUTRITION, METABOLISM, FLUIDS AND ELECTROLYTES W MCC	26	133	19.5%
54: NERVOUS SYSTEM NEOPLASMS W MCC	24	47	51.1%
193: SIMPLE PNEUMONIA AND PLEURISY W MCC	23	136	16.9%
435: MALIGNANCY OF HEPATOBILIARY SYSTEM OR PANCREAS W MCC	19	35	54.3%
280: ACUTE MYOCARDIAL INFARCTION, DISCHARGED ALIVE W MCC	18	178	10.1%
82: TRAUMATIC STUPOR AND COMA, COMA >1 HR W MCC	18	55	32.7%
377: GASTROINTESTINAL HEMORRHAGE W MCC	18	101	17.8%
85: TRAUMATIC STUPOR AND COMA, COMA <1 HR W MCC	17	66	25.8%
432: CIRRHOSIS AND ALCOHOLIC HEPATITIS W MCC	17	89	19.1%
283: ACUTE MYCARDIAL INFARCTION, EXPIRED W MCC	17	27	63.0%
872: SEPTICEMIA OR SEVERE SEPSIS WO MV >96 HR WO MCC	15	415	3.6%
682: RENAL FAILURE W MCC	15	78	19.2%
957: OTHER O.R. PROC FOR MULTIPLE SIGNIFICANT TRAUMA W MCC	14	103	13.6%
375: DIGESTIVE MALIGNANCY W CC	14	23	60.9%
65: INTRACRANIAL HEMORRHAGE OR CEREBRAL INFARCTION W CC OR TPA IN 24 HR	13	263	4.9%
180: RESPIRATORY NEOPLASMS W MCC	13	33	39.4%
963: OTHER MULTIPLE SIGNIFICANT TRAUMA W MCC	13	62	21.0%
308: CARDIAC ARRHYTHMIA AND CONDUCTION DISORDERS W MCC	11	104	10.6%
190: CHRONIC OBSTRUCTIVE PULMONARY DISEASE W MCC	11	152	7.2%
208: RESPIRATORY SYSTEM DIAGNOSIS WITH VENTILATOR SUPPORT <=96 HR	11	53	20.8%
391: ESOPHAGITIS, GASTROENTERITIS AND MISCELLANEOUS DIGESTIVE DISORDERS W MCC	11	82	13.4%
689: KIDNEY AND URINARY TRACT INFECTION W MCC	11	85	12.9%
641: MISCELLANEOUS DISORDERS OF NUTRTION, METABOLISM, FLUIDS AND ELECTROLYTES WO MCC	10	149	6.7%
20: INTRACRANIAL VASCULAR PROC W PDX HEMORRHAGE W MCC	9	50	18.0%
329: MAJOR SMALL AND LARGE BOWEL PROCS W MCC	9	81	11.1%
286: CIRCULATORY DISORDERS EXCEPT ACUTE MYOCARDIAL INFARCTION, WITH CARDIAC CATETERIZATION WITH MCC	9	85	10.6%
393: OTHER DIGESTIVE SYSTEM DIAGNOSES W MCC	9	45	20.0%
207: RESPIRATORY SYSTEM DIAGNOSIS W VENTILATOR SUPPORT >96 HOURS	9	26	34.6%
163: MAJOR CHEST PROC W MCC	9	60	15.0%
637: DIABETES W MCC	9	98	9.2%
314: OTHER CIRCULATORY SYSTEM DIAGNOSES W MCC	9	57	15.8%
70: NONSPECIFIC CEREBROVASCULAR DISORDERS W MCC	9	53	17.0%
441: DISORDERS OF LIVER EXCEPT MALIGNANCY, CIRRHOSIS OR ALCOHOLIC HEPATITIS W MCC	9	32	28.1%
374: DIGESTIVE MALIGNANCY W MCC	8	18	44.4%
175: PULMONARY EMBOLISM W MCC OR ACUTE COR PULMONALE	8	69	11.6%
948: SIGNS AND SYMPTOMS WO MCC	8	51	15.7%
100: SEIZURES W MCC	7	95	7.4%
86: TRAUMATIC STUPOR AND COMA, COMA <1 HR W CC	7	53	13.2%
270: OTHER MAJOR CARDIOVASCULAR PROCS W MCC	7	59	11.9%
61: ISCHEMIC STROKE, PRECEREBRAL OCCLUSION OR TRANSIENT ISCHEMIA W THROMBOLYTIC AGENT W MCC	7	24	29.2%
83: TRAUMATIC STUPOR AND COMA, COMA >1 HR W CC	7	32	21.9%
917: POISONING AND TOXIC EFFECTS OF DRUGS W MCC	7	92	7.6%
392: ESOPHAGITIS, GASTROENTERITIS AND MISCELLANEOUS DIGESTIVE DISORDERS WO MCC	7	184	3.8%
551: MEDICAL BACK PROBLEMS W MCC	7	31	22.6%
987: NON-EXTENSIVE O.R. PROC UNRELATED TO PDX WITH MCC	6	29	20.7%
480: HIP AND FEMUR PROCEDURES EXCEPT MAJOR JOINT W MCC	6	62	9.7%
91: OTHER DISORDERS OF NERVOUS SYSTEM W MCC	6	36	16.7%
829: MYELOPROLIFERATIVE DISORDERS OR POORLY DIFFERNTIATED NEOPLASMS WITH OTHER O.R. PROC W CC/MCC	6	10	60.0%
296: CARDIAC ARREST, UNEXPLAINED W MCC	6	10	60.0%
433: CIRRHOSIS AND ALCOHOLIC HEPATITIS W CC	6	65	9.2%
371: MAJOR GASTROINTESTINAL DISORDERS AND PERITONEAL INFECTIONS W MCC	6	25	24.0%
955: CRANIOTOMY FOR MULTIPLE SIGNIFICANT TRAUMA	6	9	66.7%
683: RENAL FAILURE W CC	6	91	6.6%
690: KIDNEY AND URINARY TRACT INFECTIONS WITHOUT MCC	6	136	4.4%
981: EXTENSIVE O.R. PROC UNRELATED TO PDX WITH MCC	5	57	8.8%
57: DEGENERATIVE NERVOUS SYSTEM DISORDERS WITHOUT MCC	5	48	10.4%
189: PULMONARY EDEMA AND RESPIRATORY FAILURE	5	31	16.1%
436: MALIGNANCY OF HEPATOBILIARY SYSTEM OR PANCREAS WITH CC	5	10	50.0%
389: GASTROINTESTINAL OBSTRUCTION W CC	5	26	19.2%
378: GASTROINTESTINAL HEMORRHAGE W CC	5	131	3.8%
463: WOUND DEBRIDEMENT AND SKIN GRAFT EXCEPT HAND FOR MUSCULOSKELETAL SYSTEM AND CONNECTIVE TISSUE DISORDERS WITH MCC	5	25	20.0%
146: EAR MOUTH AND THROAT MALIGNANCY W MCC	5	6	83.3%
840: LYMPHOMA AND NON-ACUTE LEUKEMIA W MCC	5	16	31.3%
698: OTHER KIDNEY AND URINARY TRACT DIAGNOSES WITH MCC	5	67	7.5%
292: HEART FAILURE AND SHOCK WITH CC	5	35	14.3%
919: COMPLICATIONS OF TREATMENT W MCC	5	29	17.2%
199: PNEUMOTHORAX W MCC	5	36	13.9%
673: OTHER KIDNEY AND URINARY TRACT PROCEDURES WITH MCC	5	42	11.9%
659: KIDNEY AND URETER PROCEDURES FOR NON-NEOPLASM WITH MCC	4	17	23.5%
178: RESPIRATORY INFECTIONS AND INFLAMMATIONS WITH CC	4	75	5.3%
356: OTHER DIGESTIVE SYSTEM O.R. PROCS WITH MCC	4	20	20.0%
215: OTHER HEART ASSIST SYSTEM IMPLANT	4	21	19.0%
62: ISCHEMIC STROKE, PRECEREBRAL OCCLUSION OR TRANSIENT ISCHEMIA WITH THROMBOLYTIC AGENT WITH CC	4	62	6.5%
264: OTHER CIRCULATORY SYSTEM O.R. PROCS	4	38	10.5%
300: PERIPHERAL VASCULAR DISORDERS WITH CC	4	48	8.3%
186: PLEURAL EFFUSION W MCC	4	19	21.1%
166: OTHER RESPIRATORY SYSTEM O.R. PROCS WITH MCC	4	25	16.0%
181: RESPIRATORY NEOPLASMS W CC	4	11	36.4%
183: MAJOR CHEST TRAUMA W MCC	4	32	12.5%
699: OTHER KIDNEY AND URINARY TRACT DIAGNOSES WITH CC	4	47	8.5%
11: TRACHEOSTOMY FOR FACE, MOUTH & NECK DIAGNOSES OR LARYNGECTOMY WITH MCC	4	15	26.7%
380: COMPLICATED PEPTIC ULCER W MCC	4	12	33.3%
862: POSTOPERATIVE AND POST-TRAUMATIC INFECTIONS WITH MCC	4	36	11.1%
809: MAJOR HEMATOLOGICAL AND IMMUNOLOGICAL DIAGNOSES EXCEPT SICKLE CELL CRISIS AND COAGULATION DISORDERS WITH CC	4	23	17.4%
252: OTHER VASCULAR PROCS WITH MCC	4	72	5.6%
564: OTHER MUSCULOSKELETAL SYSTEM AND CONNECTIVE TISSUE DIAGNOSES WITH MCC	4	8	50.0%
326: STOMACH, ESOPHAGEAL AND DUODENAL PROCS WITH MCC	4	27	14.8%
964: OTHER MULTIPLE SIGNIFICANT TRAUMA W CC	4	77	5.2%
834: ACUTE LEUKEMIA WO MAJOR O.R. PROC W MCC	4	15	26.7%
196: INTERSTITIAL LUNG DISEASE W MCC	3	20	15.0%
246: PERCUTANEOUS CARDIOVASCULAR PROCS WITH DRUG-ELUTING STENT WITH MCC OR 4+ ARTERIES OR STENTS	3	104	2.9%

MS-DRG, Medicare Severity Diagnosis Related Group; PC Consult, palliative care group; MV, mechanical ventilation; CC, complication or comorbidity; MCC, major complication or comorbidity; W, with; WO, without; HR, hour; O.R, operating room; PROC, procedure; PDX, principal diagnosis.

The two groups were well-matched in regard to gender and racial identity (Table 2). There were significant differences found between the groups in age and LOS (p < 0.001). Those in the PC group were older (mean (M) = 68.55, standard deviation (SD) = 15.03 vs. M = 62.75, SD = 16.92 years of age) and hospitalized longer (M = 12.18, SD = 13.22 vs. M = 7.05, SD = 9.11 days). Even when adjusting for the age, the differences remained, with LOS being 12.46 days 95% CI (12.00, 12.91) in the PC group versus 6.99 days 95% CI (6.76, 7.21) in the non-PC group (p < 0.001).

Table 2.

Cohort Comparisons on Demographic Characteristics and Outcomes

Variable/level	PC consult, n = 1906	No PC consult, n = 7730	p Value
Gender^a
Male	1016 (53.3%)	3996 (51.7%)
Female	890 (46.7%)	3734 (48.3%)	0.21
Racial identity^a
White	1690 (88.7%)	6835 (88.4%)
Black or African American	121 (6.3%)	516 (6.7%)
Unknown	34 (1.8%)	110 (1.4%)
Other	30 (1.6%)	174 (2.3%)
Multiracial	21 (1.1%)	57 (0.7%)
Asian	7 (0.4%)	16 (0.2%)
American Indian or Alaska Native	3 (0.2%)	12 (0.2%)
Native Hawaiian or Other Pacific Islander	0 (0%)	6 (0.1%)
Declined/unavailable	0 (0%)	4 (0.1%)	0.12
Age (years)^b	68.55 (15.03)	62.75 (16.92)	<0.001
LOS (days)^b	12.18 (13.22)	7.05 (9.11)	<0.001
Adjusted LOS (days)^c	12.46 (12.00–12.91)	6.99 (6.76–7.21)	<0.001
Readmissions^a (unadjusted)	129 (6.8%)	905 (11.7%)	<0.001
OR (95% CI)^d	0.55 (0.45, 0.66)	Referent	<0.001
Readmissions,Adjusted for AgeAOR (95% CI)^e	0.54 (0.44, 0.65)	Referent	<0.001

Categorical outcome, values are frequency (percentage).

Continuous outcome, values are mean (standard deviation).

ANCOVA analysis, values are adjusted means (95% confidence intervals).

OR, values are unadjusted odds ratio (95% confidence interval).

Logistic regression, values are adjusted odds ratios (AOR) with 95% confidence interval; PC consult, palliative care group; no PC consult, nonpalliative group.

There was a significantly higher proportion of readmissions in the group that did not receive PC consults [p < 0.001, OR = 0.55 (95% CI 0.45, 0.66)]. This control cohort group had 905 (11.7%) of its 7730 patients readmitted, whereas the 1906 patients who received a PC consult only had 129 (6.77%) patients readmitted. Even when controlling for age, there were 0.54 lesser odds of a readmission in the PC group (AOR = 0.54, 95% CI 0.44, 0.65, p < 0.001) versus the control cohort.

Conclusion/Lessons Learned

To our knowledge, this study is the first to use MS-DRGs to create comparative case and control groups to characterize the association between PC consultations and patient outcomes. Recently, MS-DRGs have been used to evaluate PC utilization between trauma, medical, and surgery patients,¹⁹ but the outcomes of those consultations were not analyzed. We found that we were easily able to create an adequately matched cohort, allowing us to better understand how PC consults correlated with LOS and readmission rates.

Sepsis is a broad category that could apply simultaneously to many different primary pathologies and unfortunately lacks a unifying definition. SEPTICEMIA OR SEVERE SEPSIS WITHOUT MECHANICAL VENTILATION >96 HOURS WITH MAJOR COMPLICATION OR COMORBIDITY, MS-DRG 871, is the most frequently billed MS-DRG in ICU populations.²⁰ This data aligned well with our southeastern population, as it was the code with the most PC consults. Although it is difficult to determine whether the diagnosis attached to the MS-DRG was the only pathology prompting initiation of PC utilization, studies have demonstrated that vulnerable and disadvantaged populations, such as those we would expect to find in the southeast with pandemic-deferred care, have higher rates of stay for septicemia and increased rates of readmissions.^20,21 EAR MOUTH AND THROAT MALIGNANCY WITH MAJOR COMPLICATION OR COMORBIDITY, MS-DRG 146, had the largest proportion of PC utilization in our sample. However, the sample size was small in comparison with MS-DRG 871 (five PC consults out of six total patients, 83.3%). No previous studies observed trends for this MS-DRG. A recent study did demonstrate PC consultation in advanced head and neck cancer patients, with presumed major complications, was commonly late and subsequently close to end-of-life.²² These results may explain the difference between the higher proportion of PC consults for this high-severity MS-DRG compared with its counterpart otolaryngology codes.

There is good precedent that increasing age is associated with increased PC consultation.²³ Consequently, it follows that our PC consultation group was older than our matched control group. However, it was not expected that even when controlling for age, patients who received a PC consultation had an increased LOS. There are several preceding studies that reported the PC consults were associated with reduced LOS.^5,24 We hypothesize that this finding may be secondary to the time required to arrange access to outpatient resources for continued pain management or end-of-life care in our resource-limited region. Our lower readmission rates for patients with PC involvement agree with other investigations,^5,25 and adjusting for age between the two groups did not significantly change this result.

We acknowledge several limitations associated with our study. Although a large sample size was achieved, this was a retrospective study at a single institution and may not correlate well globally. Second, the LOS may have been affected by a certain selection bias naturally inherent in providers deciding to place a PC consult. Third, there is likely significant variability in the clinical characteristics of patients within each specific MS-DRG group. Lastly, by utilizing MS-DRGs, our population was limited to those enrolled in Medicare and excluded non-fee-for-service patients such as those enrolled in commercial insurance programs or Medicaid. Although we believe we captured an appropriately diverse group to compare differences between cohorts, insurance type may have some unknown effect on post-discharge risks and follow-up. Further work should better characterize the type of clinician who places a PC consult and their reasons for the consult in addition to mortality, cost, and patient satisfaction between groups.

In conclusion, our study demonstrates that, despite increased LOS, PC consultations at our southeastern hospital are associated with significantly lower readmission rates, highlighting their potential to improve resource utilization, particularly in resource-constrained regions.

Footnotes

Author Disclosure Statement

The authors have no conflicts of interest to declare.

Funding Information

No funding was received for this article.

References

Albanese

, Radwany

, Mason

, et al. Assessing the financial impact of an inpatient acute palliative care unit in a tertiary care teaching hospital. J Palliat Med, 2013; 16(3):289–294.

Courtright

, Madden

, Bayes

, et al. Default palliative care consultation for seriously ill hospitalized patients: A pragmatic cluster randomized trial. JAMA, 2024; 331(3):224–232.

Spencer

, Nunn

, Miller

, et al. The value of compassion: Healthcare savings of palliative care consults in trauma. Injury, 2023; 54(1):249–255.

Barkley

, McCall

, Maslow

, et al. Chen X. Timing of palliative care consultation and the impact on thirty-day readmissions and inpatient mortality. J Palliat Med, 2019; 22(4):393–399.

Davis

, Van Enkevort

, Elder

, et al. The influence of palliative care in hospital length of stay and the timing of consultation. Am J Hosp Palliat Care, 2022; 39(12):1403–1409.

Glasgow

, Zhang

, O’Donnell

, et al. Hospital palliative care consult improves value-based purchasing outcomes in a propensity score–matched cohort. Palliat Med, 2019; 33(4):452–456.

Gluckman

, Spinelli

, Wang

, et al. Trends in diagnosis related groups for inpatient admissions and associated changes in payment from 2012 to 2016. JAMA Netw Open, 2020; 3(12):e2028470.

Centers for Medicare and Medicaid Services. ICD code lists. 2024. Available from: https://www.cms.gov/medicare/coordination-benefits-recovery/overview/icd-code-lists [Last accessed: May 3, 2024].

Centers for Medicare and Medicaid Services. MS-DRG classifications and software. 2024. Available from: https://www.cms.gov/medicare/payment/prospective-payment-systems/acute-inpatient-pps/ms-drg-classifications-and-software [Last accessed: May 3, 2024].

10.

Levy

, Hammes

, Anoff

, et al. Acute myocardial infarction cohorts defined by international classification of diseases, tenth revision versus diagnosis-related groups. Circ Cardiovasc Qual Outcomes, 2021; 14(3):e006570.

11.

Zikos

, DeLellis

. Comparison of the predictive performance of medical coding diagnosis classification systems. Technologies, 2022; 10(6):122.

12.

Quan Vega

, Chihuri

, Lackraj

, et al. Place of death from cancer in US states with vs without palliative care laws. JAMA Netw Open, 2023; 6(6):e2317247.

13.

Hong

Y-R

, Huo

. Trends in U.S. Population interest in palliative care and its association with prevalence of palliative care programs in U.S. states. J Pain Symptom Manage, 2020; 60(1):e89-91–e91.

14.

Shalev

, Phongtankuel

, Kozlov

, et al. Awareness and misperceptions of hospice and palliative care: A population-based survey study. Am J Hosp Palliat Care, 2018; 35(3):431–439.

15.

Griggs

. Disparities in palliative care in patients with cancer. J Clin Oncol, 2020; 38(9):974–979.

16.

Dumanovsky

, Augustin

, Rogers

, et al. The growth of palliative care in U.S. hospitals: A status report. J Palliat Med, 2016; 19(1):8–15.

17.

Abbott

, Kassner

. Palliative care and hospice in the pandemic: A review of state planning and lessons not yet learned. J Pain Symptom Manage, 2023; 66(2):87–92.e3.

18.

Zhao

D-Y

, Hu

S-Q

, Hu

F-H

, et al. Palliative care for cancer patients during the COVID-19 pandemic: A narrative synthesis from 36 studies of 16 countries. J Clin Nurs, 2023; 32(17–18):6120–6135.

19.

Fakhry

, Carrick

, Hoffman

, et al. Hospice and palliative care utilization in 16 004 232 medicare claims: Comparing trauma to surgical and medical inpatients. Trauma Surg Acute Care Open, 2024; 9(1):e001329.

20.

Sand

, Kuqi

. Current challenges in sepsis documentation and coding: A review of the literature. Perspect Health Inf Manag, 2023; 20:1g.

21.

Fingar

, Barrett

, Jiang

. A comparison of all-cause 7-day and 30-day readmissions, 2014. Healthc Cost Util Proj HCUP Stat Briefs [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US) 2017. Available from: http://www.ncbi.nlm.nih.gov/books/NBK487973 [Last accessed: June 13, 2024].

22.

Cannon

, Gabbard

, Walsh

, et al. Concordant palliative care delivery in advanced head and neck cancer. Am J Otolaryngol, 2023; 44(1):103675.

23.

Feder

, Jean

, Bastian

, et al. National trends in palliative care use among older adults with cardiopulmonary and malignant conditions. Heart Lung, 2020; 49(4):370–376.

24.

Zaborowski

, Scheu

, Glowacki

, et al. Early palliative care consults reduce patients’ length of stay and overall hospital costs. Am J Hosp Palliat Care, 2022; 39(11):1268–1273.

25.

O’Connor

, Moyer

, Behta

, et al. The impact of inpatient palliative care consultations on 30-day hospital readmissions. J Palliat Med, 2015; 18(11):956–961.