Discharge care quality in hospitalised elderly patients: Extended validation of the Discharge Care Experiences Survey.

BACKGROUND: The Discharge Care Experiences Survey (DICARES) was previously developed to measure quality of discharge care in elderly patients (≥ 65 years). The objective of this study was to test the factorial validity of responses of the DICARES, and to investigate its association with existing quality indicators.
METHODS: We conducted a cross-sectional study at two hospitals in Bergen, Western Norway. A survey, including DICARES, was sent by postal mail to 1,418 patients 30 days after discharge from hospital. To test the previously identified three-factor structure of the DICARES we applied a first order confirmatory factor analysis with corresponding fit indices and reliability measures. Spearman's correlation coefficients, and linear regression, was used to investigate the association of DICARES scores with the quality indicators Nordic Patient Experiences Questionnaire and emergency readmission within 30 days.
RESULTS: A total of 493 (35%) patients completed the survey. The mean age of the respondents was 79 years (SD = 8) and 52% were women. The confirmatory factor analysis showed acceptable fit. Cronbach's α between items within factors was 0.82 (Coping after discharge), 0.71 (Adherence to treatment), and 0.66 (Participation in discharge planning). DICARES was moderately correlated with the Nordic Patient Experiences Questionnaire (rho = 0.49, P < 0.001). DICARES overall score was higher in patients with no readmissions compared to those who were emergency readmitted within 30 days (P < 0.001), indicating that more positive experiences were associated with fewer readmissions.
CONCLUSIONS: DICARES appears to be a feasible instrument for measuring quality of discharge care in elderly patients (≥ 65 years). This brief questionnaire seems to be sensitive with regard to readmission, and independent of comorbidity. Further studies of patients' experiences are warranted to identify elements that impact on discharge care in other patient groups.

Background

Hospital discharge is a complex process starting before admission where possible, or immediately after admission [1]. In recent years, modern medical treatment and cost-effective use have ensued shorter length of hospital stay and pressure on discharge of patients [2]. A variety of adverse events are related to discharge such as drug errors, hospital-acquired infections, and procedure-related complications [3], were elderly patients are particular at risk of poorer outcomes and admissions to hospital as an emergency within 30 days of discharge (emergency readmission) [4]. A vast body of literature focuses on the patient’s condition, especially cognitive impairment and vulnerability, can complicate care in the discharge process [5, 6], and cause difficulties in managing post hospitalization care [2]. Vulnerability may be related to a number of challenges, such as side effects of new drugs [7], reduced mobility and increased risk of falls [8, 9], depression [10], and lack of support system [11]. Additionally, insufficient discharge documentation and poor communication may limit the patient’s ability to cope with health issues after hospitalization, contributing to increased risk of adverse events [11, 12], and rehospitalisation [11].

Over the past years, special emphasis has been placed on patient participation by involving the patients and their care givers in their own care, in accordance to their individual needs, circumstances and priorities [13]. Patient participation may be described as the state when patients’ themselves become the distinct starting point for all care actions [14]. The extent of patient participation is an important indicator of the quality of healthcare [14], and has been associated with improved treatment outcomes [15, 16]. However, patients and their caregivers often feel frustrated by poor preparation for their discharge to home [16, 17], or experience that they did not have an opportunity to be involved in issues they found important to influence; like medical treatment, practical conditions and the time of discharge [18-20].

Obviously, there is a need to monitor the quality of discharge care. Monitoring and measuring quality of hospital services has a long tradition. In the days of Florence Nightingale the ultimate goal of a hospital was to manage quality by monitoring and measuring care services [21]. Today, emergency readmissions is commonly used as a general quality indicator in hospitals despite its’ many inherent limitations, for instance with higher readmission rates when comorbidity increases [2, 8, 22, 23]. Better tools to investigate central factors supporting quality of transitional care, including discharge from hospital to home has been called for [16]. I has been proposed that such tools, at least partly, should be based on measuring patients’ experiences [24]. Combining data on patient experiences; “the sum of all interactions influenced by all interactions shaped by an organization’s culture across the continuum of care” [25], and health outcomes, are essential components used to understand and to improve the quality of hospital care [26, 27]. Positive associations between patient experiences and health outcomes have been demonstrated in several studies [28], indicating that patient experience surveys may pose as an appropriate quality indicator. Instruments measuring health condition [29, 30], comorbidity [31], and healthcare quality have been developed and validated for in-hospital use and use after hospitalisation [26]. However, discharge care covers a variety of tasks that may influence the patients’ self-care capability after hospitalisation [18, 32–35]. Hence, tools for measuring discharge care quality should have the potential to mirror how these tasks are performed by health care professionals by including questions related to important issues patients may experience after hospitalisation. Such instruments need to primarily reflect the quality of the care process rather than health conditions and comorbidity.

In a previous study we developed a patient experience instrument to measure the quality of discharge care in elderly patients (≥65 years) named as the Discharge Care Experiences Survey (DICARES) [36]. The first version comprised 10 items reflecting three factors related to discharge care: Coping after discharge, Adherence to treatment, and Participation in discharge planning [2, 35, 37]. The aim of this study was to investigate the DICARES’ psychometric properties, and its previously identified factor structure, in a slightly modified survey. The psychometric properties and the factor structure were confirmed.

Methods

A cross-sectional survey was conducted at two hospitals in Bergen, Western Norway, situated within the same regional health authority trust. The largest hospital is a referral tertiary teaching hospital with all specialities and covers about one million inhabitants. The smaller non-commercial private community hospital covers emergency functions for a population of approximately 150,000 inhabitants. The patients were recruited from a 22-bed internal medicine ward specialised in gastroenterology at the largest hospital, and a 32-bed general internal medicine ward at the community hospital. The distribution of patients with diseases of the digestive system at the specialized gastroenterology ward versus the general internal medicine ward was 48% and 18%, respectively. In the planning phase of our study the protocol was discussed with the hospital patient representative committee. Patient representative also participated in the study’s reference group.

Data collection

A survey was sent by postal mail to 1,418 patients ≥65 years hospitalized more than 24 hours approximately 30 days after discharge from hospital between June 2015 and April 2016. After three weeks non-responders received a reminder by mail.

The survey comprised 11 DICARES items [36], and six validated items of the Nordic Patient Experiences Survey (NORPEQ) [38, 39]. NORPEQ is commonly used as a quality indicator in Norwegian hospitals and consists of eight items designed to measure patient experiences of hospital care across the Nordic countries. The six validated items assess staff interested in problem, professional skills of nurses/doctors, nursing care, understanding doctors, and information on tests. Additionally, the survey included three questions related to patients’ characteristics. Patients completing six or more DICARES-items were included in the study, corresponding to the 50% cut-off point applied in the original version of NORPEQ [38].

Data were plotted twice by the same research assistant and quality controlled for errors by two of the researchers.

Development and previous validation of DICARES

Literature reviews, including a systematic literature review in the electronic databases PubMed, Cinahl, Embase, SweMed and PsycINFO, were conducted [36]. Our search strategy comprised the following terms: patient experience, patients satisfaction, patient perspective, patient discharge, patient transfer, continuity of patient care, patient hand over, patient hand off, primary health care, home based care, nursing homes, community health services and community based care. In collaboration with an expert panel 16 items were extracted. Forward-translations and back-translations were conducted in order to adjust the items to fit a Norwegian context. Face validity was assessed by a group of patients, and content validity by the expert panel. The answers for each item of DICARES had five Likert-scaled choices ranging from 1 (Not at all) to 5 (To a very large extent) [40], indicating that higher scores were associated with more positive experiences. Principal component analysis identified a three factor structure comprising 10 items [36].

The previous 10-item version of the DICARES [36] was evaluated by health care professionals. Consensus was made to adjust the instrument by adding one item: I received information about the effects and side effects of my medication. The additional item was included due to medical care errors are one of the most commonly reported adverse events after hospitalisation [7]. The response to negative phrased items (number 1, 2, 3, 4, 9 10 and 11) were inverted to a positive scale. Minor linguistic changes were made to the current version. Principal component analysis was applied to evaluate and approve the modification (S1 File).

Concurrent validation

We investigated concurrent validity, a type of criterion-related validity suitable for use in measuring related concepts, to examine how well DICARES correlated to two established quality indicators; the Nordic Patient Experiences Questionnaire (NORPEQ) and emergency readmission, adjusted for comorbidity. The NORPEQ- items have a five-point descriptive scale, and the NORPEQ total score is scored on a 0–100 scale from the worst experience to the best experience [38]. Emergency readmission up to 30 days to the discharging hospital was recorded from the hospitals’ patient administrative system [41]. Additional information obtained from this source was age, sex, date of admission, and length of stay. Characteristics collected from the patients included educational level, housing status, and emergency readmission.

Charlson Comorbidity Index

Charlson Comorbidity Index (CCI) [31] was used to categorize comorbidity of the patients. Each comorbidity category has an associated weight (0, 1–2, 3–4 and >5), and the sum of all the weights results in a single comorbidity score for a patient. CCI was calculated based on diagnosis codes registered by the hospitals by the International Classification of Diseases, 10th version (ICD-10) [42], and the index data were added to the dataset.

Statistical analysis

To obtain optimal statistical power and to retain the same number of all data in the DICARES, missing data in items for a person were imputed using the mean of responses of other items for that person (within person imputation), as recommended by Siddiqui and colleagues when missing responses are ≤ 50% [43]. The differences between the non-imputed and imputed data are shown in the results, and in the supporting information files. Dependent on the distribution of the responses and the number of missing of data on each item, the mean and standard deviation may differ slightly in both directions. To obtain a measure for internal reliability for the three developed factors Coping after discharge (4 items), Adherence to treatment (3 items), and Participation in discharge planning (4 items), we calculated Cronbach’s α. To test the factorial validity of responses of the DICARES, we applied a first order confirmatory factor analysis with the maximum likelihood estimation method [44]. Goodness of fit was assessed by use of common model fit indices with the following acceptance levels: minimum discrepancy (CMIN/df < 3.0) [45], comparative fit index (CFI ≥ 0.95) [46], root mean square error of approximation (RMSEA < 0.06) [46], and standardised root mean square residual (SRMR < 0.05) [44]. To examine the relation between DICARES and its factors with NORPEQ and other characteristics, we used Spearman’s correlation coefficient (rho). For this analysis, we used the total mean responses of DICARES and NORPEQ, i.e., we summarized the individual responses over the relevant items, and then divided this sum on the number of items for that scale. This was also done for the three factors of DICARES, e.g., the responses of the four items of factor Coping after discharge for each individual were summarized and then averaged on 4. Correlation values between 0.30 and 0.49 were considered to be satisfactory [47]. Finally, we evaluated the association of the DICARES scale and its factors with the established hospital quality indicator emergency readmission within 30 days (yes/no). This was done using DICARES and its factors as dependent variables and readmission as a dichotomous independent variable in a simple linear regression model. The analysis was repeated also after controlling for patient characteristics. To avoid list-wise deletion of individuals with missing patients’ characteristics and NORPEQ responses in the adjusted analysis, we used a multiple imputation technique. We created 200 imputed datasets and the imputation model included all variables that were included in adjusted regression model. Statistical analyses were performed by Stata SE version 15 (StataCorp, College Station, Texas), SPSS version 23.0 (IBM Corp., Armonk, NY), and AMOS version 23.0 (IBM SPSS, Chicago). All P-values were two sided and values P < 0.05 were considered statistically significant.

Ethics

This study was conducted in accordance with the Helsinki Declaration, and was approved by the Western Norway Regional Committee for Medical and Health Research Ethics (Ref.: 2015/329). A declaration of consent was attached to the survey. Patients who returned the survey with a signed consent form were included in the study. We obtained anonymous patient characteristics for all invited patients at group level from the patient administrative system. Data from the survey were stored in a designated research server at the hospital, whereas the anonymised forms were stored in a lockable cabinet according to hospital regulations.

Results

In all, 493 (35%) patients returned questionnaires eligible for further analysis (Fig 1). Sample characteristics are shown in Table 1. The mean age was 79 years, 52% were women, 44% had a single household, and 21% reported to have obtained higher education (high school or university). The mean length of hospital stay was 3.6 days, 25% of the participants were readmitted to the hospital within 30 days, and mean score on the CCI was 0.9 (SD = 1.4). The difference in readmission rate between the two hospital wards was insignificant (P = 0.865).

Fig 1

Inclusion of participants in the study.

Elderly patients (≥65) were recruited from two hospitals in Bergen, Western Norway, situated within the same regional health authority. Data collection: June 2015 to April 2016.

Table 1

Characteristics of the study sample.

Characteristics, categorical		n	%
All patients		493	100
Sex
	Female	257	52.1
	Male	236	47.9
Patient’s age, years
	65–75	195	39.6
	76–85	187	37.9
	86–99	111	22.5
Household
	Single household	218	44.2
	Shared household	266	54.0
	Missing	9	1.8
Education
	Primary school	189	38.3
	High school low	167	33.9
	High school high /University	105	21.3
	Missing	32	6.5
Hospital discharge
	Haukeland University Hospital, Bergen, Norway	207	42.0
	Haraldsplass Deaconess Hospital, Bergen, Norway	286	58.0
Emergency readmission a
	No	372	75.5
	Yes	121	24.5
Characteristics, continuous		Mean	SD
Age, years		78.5	8.27
Charlson Comorbidity Index		0.93	1.36
Length of hospital stay, days b		3.59	3.29
NORPEQ c		4.03	0.66

Abbreviations: SD = standard deviation; NORPEQ = Nordic Patient Experiences Questionnaire

a Emergency readmitted within 30 days after discharge

b Data was missing for 4 patients on length of hospital stay

c Data was missing for 2 patients on the Nordic Patient Experiences Questionnaire

Frequency and mean item responses of the 11 DICARES items for the study sample are shown in Table 2. Missing values for single items was 4.9%. Imputing person mean for missing item response did not markedly change the means or SD for any of the items.

Table 2

Item, factor, and total mean scores of the Discharge Care Experiences Survey.

	Respondents	Number of scores (valid %)						With imputation of missing data a
	n (%)	1	2	3	4	5	Mean (SD)	n	Mean (SD)
Item scores
1. I have felt stressed b	488 (99)	14 (3)	32 (7)	82 (17)	138 (28)	222 (45)	4.07 (1.07)	493 (100)	4.06 (1.07)
2. I have felt blueb	493 (100)	18 (4)	47 (9)	127 (26)	110 (22)	191 (39)	3.83 (1.15)	493 (100)	3.83 (1.15)
3. I have experienced problems in performing daily activities (e.g. personal hygiene, getting dressed or cooking) b	488 (99)	46 (9)	35 (7)	79 (16)	90 (19)	239 (49)	3.90 (1.33)	493 (100)	3.90 (1.33)
4. I have experienced problems in getting sufficient nutrition b	488 (99)	21 (4)	42 (9)	90 (18)	62 (13)	273 (56)	4.07 (1.21)	493 (100)	4.07 (1.21)
5. In connection with being discharged, I had an opportunity to notify hospital personnel about what I thought was important	445 (90)	57 (13)	53 (12)	96 (22)	161 (36)	78 (17)	3.34 (1.26)	493 (100)	3.41 (1.23)
6. When I was discharged from hospital, I understood thoroughly the purpose of taking my medication	428 (87)	45 (11)	21 (5)	43 (10)	125 (29)	194 (45)	3.94 (1.30)	493 (100)	3.94 (1.24)
7. I got information about effects and side effects of my medications	432 (88)	141 (33)	84 (19)	76 (17)	72 (17)	59 (14)	2.59 (1.43)	493 (100)	2.79 (1.46)
8. When I was discharged from hospital, I had a good understanding of my responsibility in terms of looking after my health	478 (97)	32 (7)	40 (8)	112 (23)	203 (43)	91 (19)	3.59 (1.09)	493 (100)	3.59 (1.08)
9. I have experienced problems in understanding the instructions I received when I was discharged from hospital b	472 (96)	15 (3)	15 (3)	32 (7)	101 (21)	309 (66)	4.43 (0.98)	493 (100)	4.38 (1.00)
10. I have experienced problems in following the instructions I received when discharged from the hospital b	464 (94)	12 (3)	15 (3)	37 (8)	88 (19)	312 (67)	4.45 (0.95)	493 (100)	4.38 (0.99)
11. I felt I was discharged too early b	484 (98)	27 (6)	34 (7)	53 (11)	78 (16)	292 (60)	4.19 (1.21)	493 (100)	4.18 (1.21)
Factor mean scores
Factor CAD (Item 1,2,3 and 4)	493 (100)						3.97 (0.97)	493 (100)	3.97 (0.96)
Factor ATT (Item 5,6 and 7)	493 (100)						4.34 (0.86)	493 (100)	4.31 (0.85)
Factor PiPD (Item 8,9,10 and 11)	493 (100)						3.38 (0.93)	493 (100)	3.43 (0.89)
Total mean scores	493 (100)						3.85 (0.73)	493 (100)	3.87 (0.71)

Abbreviations: SD = Standard deviation; CAD = Coping after discharge; ATT = Adherence to treatment; PiDP = Participation in discharge planning

a Person mean imputation.

b Negative statements were inverted to a positive scale.

Cronbach’s α, calculated using imputed data, was estimated to be 0.82 for Coping after discharge (4 items), 0.71 for Adherence to treatment (3 items), and 0.66 for Participation in discharge planning (4 items) (S2 File). Confirmatory factor analysis verified satisfactory fit of the three-factor structure of the DICARES (Fig 2): CMIN/df 2.45, CFI 0.97, RMSEA 0.055 (90% CI = 0.041, 0.068) and SRMR 0.048.

Fig 2

Confirmatory factor analysis of the Discharge Care Experiences Survey.

Elderly patients (≥65) were recruited from two hospitals in Bergen, Western Norway, situated within the same regional health authority. Data collection: June 2015 to April 2016.

Estimation of Spearman’s correlation coefficient, based on imputed data, showed a moderate relationship between the DICARES factors (S3 File): Coping after discharge vs Participation in discharge planning (rho = 0.38, P < 0.001), Participation in discharge planning vs Adherence to treatment (rho = 0.40, P < 0.001), and Coping after discharge vs Adherence to treatment (rho = 0.49, P < 0.001). DICARES overall (11 items) correlated moderately with NORPEQ (6 items) (rho = 0.49, P < 0.001). Correlations between the two of the three DICARES factors and NORPEQ were somewhat smaller: Adherence to treatment vs NORPEQ (rho = 0.40, P < 0.001), and Coping after discharge vs NORPEQ (rho = 0.34, P < 0.001), while there was a moderate correlation between factor Participation in discharge planning and NORPEQ (rho = 0.51, P < 0.001). DICARES overall, and the three factors, correlated inversely with age and had no correlation with CCI (S3 File).

The relations of scores on DICARES, and the three factors, with readmission within 30 days are shown in Table 3. Patients who were readmitted to the hospital had lower mean response than those who were not readmitted to the hospital for all factors, as well as for DICARES overall. The difference was upheld even after controlling for patient characteristics. Notably, no relation of NORPEQ with readmission was observed in unadjusted or adjusted analyses.

Table 3

Difference in total mean and factor mean scores between readmitted and not readmitted patients.

Scale		Emergency readmission					Estimated group difference a
		No (n = 372)			Yes (n = 121)
		Mean	SD		Mean	SD	Unadjusted b (95% CI)		P value		Adjusted b (95% CI) b		P value
DICARES c
	Total (11 items)	4.01	0.69		3.62	0.74	-0.39	(-0.53, -0.24)	<0.001		-0.42	(-0.57, -0.28)	<0.001
	Factor CAD (4 items)	4.09	0.88		3.57	1.10	-0.52	(-0.71, -0.33)	<0.001		-0.57	(-0.76, -0.38)	<0.001
	Factor ATT (3 items)	4.40	0.78		4.04	0.99	-0.36	(-0.54, -0.19)	<0.001		-0.38	(-0.56, -0.21)	<0.001
	Factor PiDP (4 items)	3.47	0.91		3.32	0.81	-0.15	(-0.33, 0.03)	0.11		-0.20	(-0.30, -0.01)	0.035
NORPEQ
	Total (6 items)	4.05	0.67		4.04	0.99	-0.06	(-0.20, 0.07)	0.37		-0.09	(-0.23, 0.04)	0.17

Abbreviations: SD = standard deviation; CI = confidence interval; DICARES = Discharge Care Experiences Survey; CAD = Coping after discharge

ATT = Adherence to treatment; PiDP = Participation in discharge planning; NORPEQ, Nordic Patient Experiences Questionnaire

a By linear regression model

b Adjusted for all categorical variables in Table 1; missing data in household (n = 9), education (n = 32), and Nordic Patient Experiences Questionnaire

(n = 2) was imputed using a multiple imputation technique

c Missing data in items for a person were imputed using the mean of responses of other items for that person (within person imputation)

Discussion

This study tested the factor structure of the DICARES, developed for monitoring discharge care quality. We found the confirmatory factor analysis to support the three factor structure; Coping after discharge, Adherence to treatment and Participation in discharge planning. We observed that DICARES’ correlated moderately with the NORPEQ–questionnaire [38, 39]. This finding indicates that DICARES’ reflects some similar aspects as the NORPEQ, and further, provide additional knowledge particularly related to discharge care quality. We found that patients with more positive experience scores on the DICARES had significantly fewer readmissions. The DICARES did not correlate with comorbidity, as measured by the CCI.

The measured indicators CMIN/df, CFI, RMSEA and SRMR showed that the hypothesized factor structure was very well adapted to the data [45, 46]. We compared the DICARES with a large inpatient care quality study by Smirnova and colleagues from 2017 [48], that in contrast to the NORPEQ-study [39], applied confirmatory factor analysis. The study included nearly 23,000 participants, were half of the respondents were > 65 years. The mean values of the subscale Information at discharge were 0.7 (scale from 0 to 1) and almost identical to the mean total DICARES score (3.85 on a scale from 1 to 5), corresponding to 70% and 71% of the respective maximum values [48]. We believe these similarities support the acceptability of DICARES in terms of being useful as an additional instrument to measure hospital discharge quality. Elderly are considerable consumers of hospital care [49] and the DICARES was developed particularly to survey experiences in this vulnerable patient group, unlike the NORPEQ [38, 39].

In a systematic review Beattie and colleagues identified 11 instruments measuring patient experience of healthcare quality [26]. We were not able to find that the instruments covered questions related to patients experience the first period after hospitalisation. Additionally, differences in methodology and timing limited comparison with the DICARES [36]. We included NORPEQ as one of the comparators in the current study since it is an established general quality indicator used in Norwegian hospitals [26]. NORPEQ and Smirnova claim their instruments reflect the quality of care. This is attributed to variation in the results between or within organisations and at different organisational levels [39, 48]. Such an approach has been discussed by Bezold [50], who claims that quality will then be measured from an institutional level rather than through the eyes of the patient. Our approach has been to measure discharge care quality by comparing the DICARES with external instruments covering conditions of importance for the patients in order to identify how underlying issues may reflect specific areas of discharge.

As in our previous study [36] no correlations were found between the DICARES and the CCI, indicating that comorbidity did not have a significant impact on the DICARES scores. We may have succeeded to develop an instrument that measures health service quality rather than the patients’ health conditions influenced by comorbidity, in our study measured by CCI. The DICARES is simple, brief and its three factors have the potential, directly or indirectly, to reflect specific areas discharge care quality [51]. The response of each item indicates sufficient variation in the responses and normal distribution [52].

According to Manary and colleagues [53], patient experience measures do not simply reflect clinical adherence-driven outcomes, but also another dimension of quality which otherwise is difficult to measure objectively. We believe the DICARES’ three-factor structure makes it possible to identify and measure underlying issues in quality of care and that suitable strategies may be developed and implemented through quality improvement work [54, 55].

In the current study we chose to use emergency readmission for concurrent validation of the DICARES. The factors Coping after discharge and Adherence to treatment were associated with readmission, indicating emergency readmission as a quality indicator, and the DICARES covers some similar aspects. This is in line with results in the study of Kangovi and colleagues who found that one of the most commonly reported issues that contributed to readmission was difficulties in performing daily tasks [34]. Factor Adherence to treatment was significantly lower for the readmitted patients versus the non-readmitted patients in the current study. Adherence is the primary determinant of the effectiveness of treatment and is affected by the patient-provider relationship, and also by numbers of patient-related factors such as low motivation, lack of a self-perceived need for treatment, feeling of being discharged too early from previous hospitalisation, or multiple hospital admissions [34, 54, 56–58].

Patients reported the lowest scores for the factor Participation in discharge planning.

This result is similar to the findings in the previous DICARES’ study [20], and corresponds with elderly patients’ experiences of not being involved in discharge planning from hospital [18, 59, 60]. Despite the lack of participation, elderly patients’ interviewed in a study of Hvalvik and colleagues [60] were humble and expressed gratefulness for the care system they were a part of. The authors claim a patient-oriented approach as essential in the process to support the elderly patients because they are challenged during the transition between hospital and home. To support care of elderly patients, health care professionals need to understand the patient’s present situation in the context and coherence of past and future [60]. Patients with positive care experiences are often more engaged in their care, more committed to treatment plans, and more receptive to medical advices [51].

A limitation of the current study may be the relatively low response rate, though it is comparable to the study by Smirnova and colleagues [48]. Low participation is a major concern in patient experience surveys [38]. One concern could be that elderly persons with a high CCI would participate to a lesser extent. In a previous study of DICARES [36] investigating patient experiences in a similar population of elderly, the response rate was 64% and the CCI was 0.7 higher than in the current study. This indicate that comorbidity may not be the reason for the limited number of responders in the current study. However, the response rate may have been influenced by geriatric syndromes; clinical conditions that is common in elderly and that do not fall into distinct disease categories, like weight loss, pain and depressive symptoms [61]. Another limitation may be that patients who completed less than six DICARES items were not included in the study. Poor condition or cognitive impairment could be reasons for lack of completion of the questionnaire. Exclusion of these patients may have biased the results.

Unlike findings in the previous study of the DICARES [20], Cronbach’s α was somewhat lower for the factor Participation in discharge planning than required according to quality criteria for measurements [26]. However, instruments for quality improvement may tolerate lower levels of reliability in favour of other aspects of utility, such as it is brief and there are good theoretical and practical reasons for the instrument [62] due to educational impact, cost and acceptability [26]. Measurement error is not calculated, similar to results in Beattie and colleagues systematic review where only one of the studies reported on this criterion [26]. Except from these possible weaknesses DICARES’ fulfils the other quality criteria for measurement properties.

The DICARES meet with recommendations of Manary and colleagues [53] who claim that patient experiences measurement should address a specific event or visit, focus on provider patient interactions, and be assessed in a timely manner. Furthermore, the DICARES is in accordance with the usual distribution of surveys to patients in clinical improvement work. We find it important to keep the questionnaire brief, otherwise elderly sick patients may find it too demanding to complete. The survey was distributed to the patients one month after discharge as this was relevant due to comparison with the quality indicator emergency readmission within 30 days. There may be patients who did not receive the questionnaire because they were already readmitted at the time the questionnaire was sent. Further, there may be patients who did not answer the questionnaire because they had already been readmitted at that time, which may have resulted in a failure to answer the questionnaire even though a poor discharge process was the reason for re-admission. Additionally, there is a risk of recall-bias that patients who have been readmitted confuse the experiences of more admissions. However, test-retest showed satisfactory results in a previous study [36]. The CCI is limited to cover only the prognostic aspect as a risk of early mortality [31], and unlike the previous study of the DICARES [36], a health status survey is not included in this study. The amount of missing data was acceptable [63]. By applying imputation the power of the analyses has been strengthen, and the risk of bias reduced.

Conclusions

The DICARES appears to be a valid questionnaire for measuring discharge care quality. The survey provides additional value to the knowledge of challenges faced by patients, and contributes to verify the feasibility of the DICARES. When compared with established hospital quality indicators, the results indicate that DICARES could be a feasible tool to add to discharge improvement measures. DICARES seems to have sensitive properties with regard to the readmitted patients, and to be independent of comorbidity. The three factor structure may reflect directly and indirectly underlying issues related to discharge. The psychometric evaluation of the DICARES suggests acceptable internal consistency, and adequate construct validity of the instrument as a whole. DICARES is a brief, generic, non-diagnostic, and specific questionnaire. Further validation may also include elderly patients discharged from general surgical units.

Principal component analysis.

(DOCX)

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Reliability analysis.

(DOCX)

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Spearman’s correlation coefficient.

(DOCX)

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Available data.

Anonymous data set including 493 respondents.

(XLSX)

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15 Jul 2019

PONE-D-19-15237

Discharge care quality in hospitalised elderly patients: Extended validation of the Discharge Care Experiences Survey

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Reviewers' comments:

Comments to the Author

Reviewer #1: Summary of research

The publication "Discharge care quality in hospitalized elderly patients..." shows an interesting study on the extended validation of DICARES. The previously developed and validated questionnaire DICARES was subjected to an extended validation at 2 hospitals with different levels of care in Bergen (Norway) by means of a cross sectional design study. The patients were recruited from a specialized gastroenterological ward of a maximum care hospital and a general internal ward of a community hospital. The aim was to investigate the psychometric properties of DICARES and the previously identified structure of the factors. Testing was performed against other validated questionnaires.

The special feature of DICARES is its focus on accompanying the discharge ("discharge care"). The patients who were not re-admitted showed a higher DICARES score than the patients who were re-admitted. The study was conducted 30 days after discharge and the discharged patients received the questionnaire by post. The results show appropriately high values of Cronbach's alpha of the items within the factors "Coping after discharge", "Adherence to treatment" and "Participation in discharge planning" with decreasing values of 0.82, 0.71 and 0.66. The statistical tests carried out are comprehensibly documented and comprehensible.

The study, well conducted in an appropriate design and with appropriate methods, has demonstrated that DICARES is an applicable tool that can capture the quality of nursing preparation of the discharge process sensitively in terms of patient readmission and independently in terms of patient comorbidity.

The study thus proves the effectiveness of the instrument for the intended purpose.

Overall impression

The study meets the required ethical requirements through approval by the responsible ethics committee. The statistical analysis was carried out appropriately. An informed consent was obtained from the patients. The personal data collected was anonymized and data protection requirements for the processing and storage of the data have been fulfilled.

The study presents a well-developed and two-stage validated instrument that, with its focus on the quality of the preparation of the discharge process. The study makes an important contribution to the quality assurance of the treatment process at the interface inpatient to outpatient.

Overall comment

The question I am thinking about while I’m working out this peer-review is whether the fact that the questionnaire was sent 30 days after the discharge, but the readmission rate was evaluated within those 30 days, could have biased the results, and in what extent.

The questionnaires were sent at day 30 after discharge. At the same time, however, the patient readmissions were evaluated within 30 days. The study provides no information whether and how many patients who were readmitted within 30 days (especially early after discharge) got and/or completed the questionnaire.

It is correct to focus on an established hospital quality indicator such as "readmission within 30 days", as this is easy to measure. There may be patients who did not receive the questionnaire because they were already readmitted at the time the questionnaire was sent. And there may be patients who did not answer the questionnaire because they had already been re-admitted at that time, which may have resulted in a failure to answer the questionnaire even though a poor discharge process was the reason for re-admission. Despite these possible dropouts, however, the results obtained are to be regarded as correct and meaningful, as the suitability of the questionnaire was determined.

To address these thoughts, a table, graph or plot of the data showing which patients (proportions) got the questionnaire, and which answered the questionnaire depending of the status “readmitted” could be helpful.

It would be interesting to know a textual or other description of the extent to which the results differ in relation to the level of care (specialized ward / community ward).

Maybe – because this study provides a solid answer to the question to be dealt with – it would be interesting to conduct another study in which the questionnaire will be given within the first few days (e.g. 3 or 5 days) after discharge to see if the results of the questionnaire can predict the risk of a readmission.

Overall Recommendation

The study raises a small number of questions, some of which can be resolved by simple explanations and clarifications in the text.

Clarification should be provided on the issue of imputation and the corresponding presentation of results and textual presentation in order to remove minor ambiguities.

The planned extended validation of DICARES was carried out properly and the effectiveness and value of the instrument was proven.

The Issues to address should be worked out. The study should be published.

Issues to address

Line 98-100: The patients were recruited from a specialized gastroenterological ward of a maximum care hospital and a general internal ward of a community hospital.

> Consideration should be given in the text to whether the patient population was comparable (enough), maybe with just a few sentences. Since the wards differ in terms of specialization, the more specialized ward may have had lower readmission rates than the less specialized ward or vice versa.

Maybe consideration should be given on an adjustment of the analysis of the data depending on the level of specialization of the ward, but maybe this will be worked out in the further analysis planned as addressed in the article.

Lines 134 ff and 155-159: For questions addressing the imputations of data see Issues Line 201 (Table 2) and Supporting information (File 2) as follows.

Line 201 (Table 2) and Supporting information (File 2): Table 2 shows information and results for calculations with imputations for missing data. The mean values with the imputations deviate in both directions (+/-) from the mean values without the imputations or remain stable. The SD sometimes gets narrower, wider or remains stable, too. Thus, it becomes clear that the imputations have an influence on the mean values shown.

> The meaning of the change in the mean values due to the imputations should be explained or presented in the text.

The total mean score is only calculated for the data without imputations.

> The total mean score in Table 2 should also be calculated for the column with the imputations.

> It should be clearly stated in the text on which mean score given in table 2 (with or without imputations) the further statements are based, as the imputations could have distorted the results.

The File 2 provides a kind of sensitivity-analysis by calculating the average covariance and Cronbach's alpha for the data with and without imputations.

> A representation of the mean scores as in File 2 separated into data with and without imputation should be checked.

Minor issues

References: The DOI of Reference No. 28 is not correct, the article could not be retrieved via that DOI. All References should be checked, I didn’t check them systematically.

Line 90/91: The sentence “The psychometric…” impresses as a part of the results.

The sentence should be moved to the results section or reworded.

Line 108/109: Only patients who completed more than 50% of the DICARES-Items were included in the study.

This criterion led to the exclusion of feedback forms that might have indicated a link between discharge preparation and readmission. The reason for the decision to set this 50% cut-off should be given in the text, as should the possible effects of this decision. Any kind of re-analysis of the data regarding this aspect seems not to be necessary.

Line 124: the word “patients” in the sentence “…, length of stay and patients” seems to be out of context, as long it does not address the height of the patient

Line 176: the percentage “53%” differs from the value given in the abstract (52%)

Line 244/245: There is an incomplete sentence “The concurrent validity of the.” If a complete paragraph or section is missing, I’d like to know what it was.

Line 276: doubled words “in order”

Line 278: wording should be “no correlation was found” or “no correlations were found”

Line 283: wording should be “reflect specific areas of discharge”

Line 294: wording should be “DICARES covers some similar aspects”

Line 296: doubled word “Factor Adherence to treatment factor was…”

Line 340: wording should be “The CCI is limited to only cover…” or “The CCI is limited to cover only…”

Line 248: wording should be “…contributes to verify…”

Line 350: wording should be “DICARES seems to have…”

Reviewer #2: General comments:

- Pay attention to punctuation, for instance line 39.

Introduction:

- The section needs major revision. The rationale for the study should be strengthened. Why is this study important to do in elderly patients? Authors must add more literature about the issue.

Methods:

- In general, this section should be more organized. Create some subheadings like Concurrent validity, Charlson comorbidity index and …, then provide a complete explanation for each of them.

- In the methods section it has been stated that development and validation of the DICARES comprised literature reviews, consultations with an expert panel, patients’ evaluation and principal component analysis. This section should be enriched with additional details such as search flow and so on.

- More information is needed about the NORPEQ.

Discussion

- Line 245, it seems to be incomplete.

**********

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: PONE-D-19-15237-english.docx

Click here for additional data file.

11 Aug 2019

We are grateful for the reviewers’ and Editor’s comments and their suggestions to improve the manuscript. We hope that our responses have addressed the comments sufficiently and that our manuscript would be acceptable for publication.

Response to reviewers’

Reviewers’ comments

Response to reviewer #1

Overall comment

The question I am thinking about while I’m working out this peer-review is whether the fact that the questionnaire was sent 30 days after the discharge, but the readmission rate was evaluated within those 30 days, could have biased the results, and in what extent.

The questionnaires were sent at day 30 after discharge. At the same time, however, the patient readmissions were evaluated within 30 days. The study provides no information whether and how many patients who were readmitted within 30 days (especially early after discharge) got and/or completed the questionnaire.

It is correct to focus on an established hospital quality indicator such as "readmission within 30 days", as this is easy to measure. There may be patients who did not receive the questionnaire because they were already readmitted at the time the questionnaire was sent. And there may be patients who did not answer the questionnaire because they had already been re-admitted at that time, which may have resulted in a failure to answer the questionnaire even though a poor discharge process was the reason for re-admission. Despite these possible dropouts, however, the results obtained are to be regarded as correct and meaningful, as the suitability of the questionnaire was determined.

To address these thoughts, a table, graph or plot of the data showing which patients (proportions) got the questionnaire, and which answered the questionnaire depending of the status “readmitted” could be helpful.

It would be interesting to know a textual or other description of the extent to which the results differ in relation to the level of care (specialized ward / community ward).

Response: Thank you. Unfortunately, we do not have permission to obtain data from patients who did not consent to participate. However, in the Discussion we have added “There may be patients who did not receive the questionnaire because they were already readmitted at the time the questionnaire was sent. Further, there may be patients who did not answer the questionnaire because they had already been readmitted at that time, which may have resulted in a failure to answer the questionnaire even though a poor discharge process was the reason for re-admission.

Issues to address

Line 98-100: The patients were recruited from a specialized gastroenterological ward of a maximum care hospital and a general internal ward of a community hospital.

> Consideration should be given in the text to whether the patient population was comparable (enough), maybe with just a few sentences. Since the wards differ in terms of specialization, the more specialized ward may have had lower readmission rates than the less specialized ward or vice versa.

Response: Agree. We added information to the Methods section: “The distribution of patients with diseases of the digestive system at the specialized gastroenterology ward versus the general internal medicine ward was 48% and 18%, respectively. (line 124-126)

We also added information to the Results section: “The difference in readmission rate between the two hospital wards was insignificant (P=0.865).” (line 231-232)

Maybe consideration should be given on an adjustment of the analysis of the data depending on the level of specialization of the ward, but maybe this will be worked out in the further analysis planned as addressed in the article.

Response: We agree, this could be interesting to examine in future studies of DICARES.

Lines 134 ff and 155-159: For questions addressing the imputations of data see Issues Line 201 (Table 2) and Supporting information (File 2) as follows.

Line 201 (Table 2) and Supporting information (File 2): Table 2 shows information and results for calculations with imputations for missing data. The mean values with the imputations deviate in both directions (+/-) from the mean values without the imputations or remain stable. The SD sometimes gets narrower, wider or remains stable, too. Thus, it becomes clear that the imputations have an influence on the mean values shown.

> The meaning of the change in the mean values due to the imputations should be explained or presented in the text.

Response: Agree. Sentences added to clarify: “The differences between the non-imputed and imputed data are shown in the results, and in the supporting information files. Dependent on the distribution of the responses, and the number of missing of data on each item, the mean and standard deviation may differ slightly in both directions.” (line 186-189)

We added the following text in the Discussion section: “By applying imputation the power of the analyses has been strengthen, and the risk of bias reduced. (line 411-412)

The total mean score is only calculated for the data without imputations.

> The total mean score in Table 2 should also be calculated for the column with the imputations.

Response: Agree. Total mean score for the column with the imputations have been added to Table 2. Line (line 255).

> It should be clearly stated in the text on which mean score given in table 2 (with or without imputations) the further statements are based, as the imputations could have distorted the results.

Response: Agree. Information added: “Cronbach’s α, calculated using imputed data, was estimated to be 0.82 for Coping after discharge (4 items), 0.71 for Adherence to treatment (3 items), and 0.66 for Participation in discharge planning (4 items) (S2 file).” (line 248)

“Estimation of Spearman’s correlation coefficient based on imputed data, showed a moderate relationship between the DICARES factors (S3 file),….” (line 271)

The File 2 provides a kind of sensitivity-analysis by calculating the average covariance and Cronbach's alpha for the data with and without imputations.

> A representation of the mean scores as in File 2 separated into data with and without imputation should be checked

Response: Agree. Mean scores with and without imputations for the three factors have been added to Table 2. (line 255)

Minor issues

References: The DOI of Reference No. 28 is not correct, the article could not be retrieved via that DOI. All References should be checked, I didn’t check them systematically.

Response: All references are checked and corrections made. We opened DOI of reference No. 28 successfully. Reference 43 (line 574-576).

Line 90/91: The sentence “The psychometric…” impresses as a part of the results. The sentence should be moved to the results section or reworded.

Response: We do not agree to this point with respect to Plos One’s Submission guidelines for “Introduction”: “Conclude with a brief statement of the overall aim of the work and a comment about whether that aim was achieved”. https://journals.plos.org/plosone/s/submission-guidelines#loc-abstract

Line 108/109: Only patients who completed more than 50% of the DICARES-Items were included in the study.

This criterion led to the exclusion of feedback forms that might have indicated a link between discharge preparation and readmission. The reason for the decision to set this 50% cut-off should be given in the text, as should the possible effects of this decision. Any kind of re-analysis of the data regarding this aspect seems not to be necessary.

Response: Agree. Text added in two sections:

“Patients completing six or more DICARES-items were included in the study, corresponding to the 50% cut-off point applied in the original version of NORPEQ”. (line 140-141)

“To obtain optimal statistical power and to retain the same number of all data in the DICARES, missing data in items for a person were imputed using the mean of responses of other items for that person (within person imputation), as recommended by Siddiqui and colleagues when missing responses are ≤ 50%.” (line 183-186)

In discussion: “Patients who completed less than six DICARES items were not included in the study. Poor condition or cognitive impairment could be reasons for lack of completion of the questionnaire. Exclusion of these patients may have biased the results”. (line 381-382)

Line 124: the word “patients” in the sentence “…, length of stay and patients” seems to be out of context, as long it does not address the height of the patient

Response: Agree. Sentence reworded to: Additional information obtained from this source was age, sex, date of admission and length of stay. (line 170-171)

Line 176: the percentage “53%” differs from the value given in the abstract (52%)

Response: Agree. Changed to 52%. (line 228)

Line 244/245: There is an incomplete sentence “The concurrent validity of the.” If a complete paragraph or section is missing, I’d like to know what it was.

Response: Sentence removed.

Line 276: doubled words “in order”

Response: Removed.

Line 278: wording should be “no correlation was found” or “no correlations were found”

Response: Corrected. (line 334)

Line 283: wording should be “reflect specific areas of discharge”

Response: Corrected. (line 333)

Line 294: wording should be “DICARES covers some similar aspects”

Response: Corrected. (line 349-350)

Line 296: doubled word “Factor Adherence to treatment factor was…”

Response: Corrected. (line 352)

Line 340: wording should be “The CCI is limited to only cover…” or “The CCI is limited to cover only…”

Response: Corrected. (line 408-409)

Line 248: wording should be “…contributes to verify…”

Response: Corrected. (line 417)

Line 350: wording should be “DICARES seems to have…”

Response: Corrected.

Response to reviewer #2

Reviewer #2: General comments:

- Pay attention to punctuation, for instance line 39.

Response: Thank you. The manuscript has been checked with respect to punctuation.

Introduction:

- The section needs major revision. The rationale for the study should be strengthened. Why is this study important to do in elderly patients? Authors must add more literature about the issue.

Response: We agree. More text and 17 references added. (line 61 to 64, line 66-71, line 72-73, line 75-84).

Methods:

- In general, this section should be more organized. Create some subheadings like Concurrent validity, Charlson comorbidity index and …, then provide a complete explanation for each of them.

Response: Response: Agree. Several changes made in Methods between line 124 and line 180, several subheadings added and explanation provided:

Concurrent validation

“We investigated concurrent validity, a type of criterion-related validity that is suitable to measure related concepts, to examine how well DICARES correlated to two established quality indicators; the Nordic Patient Experiences Questionnaire (NORPEQ) and emergency readmission, adjusted for comorbidity”. (line 163-167)

Charlson Comorbidity Index

“Charlson Comorbidity Index (CCI) [16] was used to categorize comorbidity of the patients. Each comorbidity category has an associated weight (0, 1-2, 3-4 and >5), and the sum of all the weights results in a single comorbidity score for a patient”. (line 175-178)

- In the methods section it has been stated that development and validation of the DICARES comprised literature reviews, consultations with an expert panel, patients’ evaluation and principal component analysis. This section should be enriched with additional details such as search flow and so on.

Response: Agree. Changed made, and text added between line 146 and 161.

- More information is needed about the NORPEQ.

Response: Agree. Changed to: “The survey comprised 11 DICARES items[36], and six validated items of the Nordic Patient Experiences Survey (NORPEQ)[38, 39]. NORPEQ is commonly used as a quality indicator in Norwegian hospitals and consists of eight items designed to measure patient experiences of hospital care across the Nordic countries. The six validated items assess staff interested in problem, professional skills of nurses/doctors, nursing care, understanding doctors, and information on tests. (line 134-139)

Discussion

- Line 245, it seems to be incomplete.

Response: We agree. Sentence removed.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

27 Aug 2019

PONE-D-19-15237R1

Discharge care quality in hospitalised elderly patients: Extended validation of the Discharge Care Experiences Survey

PLOS ONE

Dear Ms Boge,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Oct 11 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Prof, Mojtaba Vaismoradi, PhD, MScN, BScN

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer #1: All my comments from the first round of the review were adequatly adressed. There are only 4 minor issues left, that should be worked out prior to publication.

Line 81: missing "to", should be ...for their discharge to home

Line 123: should be ....medicine ward specialised in gastroenterology

Line 321: should be "In a systematic review Beattie and colleagues identified 11 instruments measuring patient experience of healthcare quality [26]." or "Beattie and colleagues identified 11 instruments of measuring patient

experience of healthcare quality in a systematic review [26]."

And - sorry for grouching, but - the DOI for Reference 43 leads me to the wrong publication, I cannot retrieve the right publication with the given DOI 10.12788/jhm.3037 via doi.org. In the citation 43 as given I can only find another publication, were the title and one authors name match.

The DOI 10.12788/jhm.3037 given in the citation 43 leads to the following publication:

Brotman DJ, Siddiqui Z, Siddiqui Z, Durkin N. Does Patient Experience Predict 30-Day Readmission? A Patient-Level Analysis of HCAHPS Data. Journal of Hospital Medicine. 2018;13. doi:10.12788/jhm.3037

The publication you cited as No. 43 has another DOI, when I look for the title only:

Siddiqui OI. Methods for Computing Missing Item Response in Psychometric Scale Construction. Current Research in Biostatistics. 2015;5: 1–6. doi:10.3844/amjbsp.2015.1.6

Reviewer #2: One additional suggestion to improve the manuscript content: line 147, add brief details of the search strategy.

Line 283: wording should be “discharge”

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

8 Sep 2019

We are grateful for the reviewers’ comments and for the opportunity to improve the manuscript.

Response to reviewers’

Reviewers' comments:

Reviewer #1: All my comments from the first round of the review were adequately addressed. There are only 4 minor issues left, that should be worked out prior to publication.

Line 81: missing "to", should be ...for their discharge to home

Response: Thank you, we have added “to”.

Line 123: should be ....medicine ward specialised in gastroenterology

Response: Thank you. Corrected.

Line 321: should be "In a systematic review Beattie and colleagues identified 11 instruments measuring patient experience of healthcare quality [26]." or "Beattie and colleagues identified 11 instruments of measuring patient experience of healthcare quality in a systematic review [26]."

Response: Agree. Changed to: In a systematic review Beattie and colleagues identified 11 instruments measuring patient experience of healthcare quality [26]." (line 325-326)

And - sorry for grouching, but - the DOI for Reference 43 leads me to the wrong publication, I cannot retrieve the right publication with the given DOI 10.12788/jhm.3037 via doi.org. In the citation 43 as given I can only find another publication, were the title and one authors name match.

The DOI 10.12788/jhm.3037 given in the citation 43 leads to the following publication:

Brotman DJ, Siddiqui Z, Siddiqui Z, Durkin N. Does Patient Experience Predict 30-Day Readmission? A Patient-Level Analysis of HCAHPS Data. Journal of Hospital Medicine. 2018;13. doi:10.12788/jhm.3037

The publication you cited as No. 43 has another DOI, when I look for the title only:

Siddiqui OI. Methods for Computing Missing Item Response in Psychometric Scale Construction. Current Research in Biostatistics. 2015;5: 1–6. doi:10.3844/amjbsp.2015.1.6

Response: Thank you for your thoroughness! We agree and have corrected to:

“43. Siddiqui OI. Methods for Computing Missing Item Response in Psychometric Scale Construction. Am J Biostat, 2015. doi:10.3844/amjbsp.2015.1.6” (line 578-579)

Reviewer #2: One additional suggestion to improve the manuscript content: line 147, add brief details of the search strategy.

Response: Thank you. We agree and have added: “Our search strategy comprised the following terms: patient experience, patients satisfaction and patient perspective, and further patient discharge, patient transfer, continuity of patient care, patient hand over, patient hand off, primary health care, home based care, nursing homes, community health services and and community based care. (line 147-151).

Line 283: wording should be “discharge”

Response: Thank you. We think this sentence was imprecise, and have added “scores on” to clarify: “The relations of scores on DICARES, and the three factors, with readmission within 30 days are shown in Table 3.” (line 287-288)

We hope that our responses have addressed the comments sufficiently and that our manuscript would be acceptable for publication.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

16 Sep 2019

Discharge care quality in hospitalised elderly patients: Extended validation of the Discharge Care Experiences Survey

PONE-D-19-15237R2

Dear Dr. Boge,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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Prof, Mojtaba Vaismoradi, PhD, MScN, BScN

Academic Editor

PLOS ONE,

Nord University, Bodø, Norway

19 Sep 2019

PONE-D-19-15237R2

Discharge care quality in hospitalised elderly patients: Extended validation of the Discharge Care Experiences Survey

Dear Dr. Boge:

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on behalf of

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