COMMITMENT • INTEGRITY • LEADERSHIP	View PDF report View Fact Sheet View Selected Abbreviations
In-Home Supportive Services Program It Is Not Providing Needed Services to All Californians Approved for the Program, Is Unprepared for Future Challenges, and Offers Low Pay to Caregivers Report Number: 2020-109

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• Appendix A—Survey of Counties Regarding IHSS
• Appendix B—County IHSS Populations and Performance Metrics
• Appendix C—Comparison of Living Wage to Actual Caregiver Wages in California Counties
• Appendix D—Effect of Reducing the Inflation Factor on Certain Counties
• Appendix E—Scope and Methodology

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Appendix A

Survey of Counties Regarding IHSS

We surveyed directors of county IHSS programs to obtain additional information on how the IHSS program is performing statewide. We received 51 responses, and seven counties did not respond: Fresno, Lassen, Modoc, Placer, San Mateo, Sierra, and Solano. Table A provides a selection of questions and summarizes county answers.

Table A

Selected Answers From the Survey of Counties

Please note that where answers are not Yes/No, respondents were allowed to select more than one answer.
Does your county have a sufficient number of IHSS caregivers to provide all approved services to each IHSS recipient?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Yes	19	37%
No	32	63

If no, what hurdles exist that prevent your county from having enough caregivers for each recipient to receive all approved services?
The percentages shown here are out of total “No” respondents, above, 32.
	NUMBER	PERCENT
Insufficient pay rates to attract caregivers.	14	44%
Difficulty matching caregivers with recipients in isolated geographic areas.	26	81
Recipients with specific or challenging needs that few caregivers can or will satisfy.	30	94
Recipients are reluctant to hire nonfamily members as caregivers.	10	31
Caregivers do not have enough time to provide services to all recipients.	16	50
Other*	18	56

If no, other than maintaining the mandated registry of caregivers, what activities has the county undertaken to ensure each recipient has a provider?
The percentages shown here are out of total “No” respondents, above, 32.
	NUMBER	PERCENT
When recipients indicate short-term or specific needs, notify them of caregivers who can deliver services as needed.	26	81%
Assist recipients in interviewing caregivers.	25	78
We have taken no additional steps.	1	3
Other†	23	72

Has your county performed any analysis to identify how many caregivers it needs currently and in the future?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Yes	2	4%
No	49	96

Does your county actively recruit caregivers?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Yes	45	88%
No	45	12%

What obstacles, if any, do recipients in your county typically face in hiring caregivers?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Insufficient pay rates to draw applicants.	22	43%
Potential caregivers may not have knowledge of the program.	14	27
Potential caregivers do not pass background checks.	11	22
Potential caregivers do not have transportation.	29	57
Potential caregivers are unwilling to provide care in certain geographic areas.	45	88
Potential caregivers are unwilling to provide certain types of care.	42	82
Other‡	20	39

Has your county created a plan to account for future growth in the number of recipients in your county?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Yes	4	8%
No	47	92

Has your county performed any analysis to identify its future budgetary needs for the IHSS program?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
Yes	14	27%
No	37	73

What concerns, if any, does your county have with its county contribution payments to the State?
The percentages shown here are out of total respondents, 51.
	NUMBER	PERCENT
None, there are no concerns with the county contribution.	14	27%
The county contribution penalizes the county for negotiated increases in wages.	15	29
The county contribution inflation rate is arbitrary and does not reflect realities in the county.	27	53
The county contribution does not reflect actual program costs.	26	51
Other§	24	47

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Appendix B

County IHSS Populations and Performance Metrics

The Audit Committee asked us to provide a variety of information related to IHSS populations and performance metrics. The following tables summarize additional or more detailed results of our review of data related to the IHSS populations and performance metrics.

Table B.1

The Overall Number of Authorized Hours Not Provided Increased Between 2015 and 2019

	2015				2019
COUNTY	AUTHORIZED HOURS	PROVIDED HOURS	DIFFERENCE	PERCENTAGE OF AUTHORIZED HOURS NOT PROVIDE	AUTHORIZED HOURS	PROVIDED HOURS	DIFFERENCE	PERCENTAGE OF AUTHORIZED HOURS NOT PROVIDED
Alameda	27,699,069	26,239,186	1,459,883	5%	34,542,303	32,307,236	2,235,067	6%
Alpine	28,670	27,747	923	3	28,546	27,574	972	3
Amador	254,536	241,095	13,441	5	397,265	371,670	25,595	6
Butte	5,179,122	4,958,298	220,824	4	5,364,090	5,063,563	300,527	6
Calaveras	440,439	416,704	23,735	5	589,614	559,765	29,849	5
Colusa	139,063	119,626	19,437	14	340,838	318,370	22,468	7
Contra Costa	9,460,235	9,015,226	445,009	5	14,232,654	13,167,108	1,065,546	7
Del Norte	524,385	501,878	22,507	4	606,537	582,042	24,495	4
El Dorado	1,564,393	1,511,045	53,348	3	2,416,545	2,332,701	83,844	3
Fresno	19,312,101	18,782,620	529,481	3	28,608,173	27,708,588	899,585	3
Glenn	634,768	602,205	32,563	5	769,898	723,391	46,507	6
Humboldt	1,919,902	1,764,651	155,251	8	2,793,535	2,559,540	233,995	8
Imperial	4,857,191	4,755,612	101,579	2	6,606,213	6,468,131	138,082	2
Inyo	163,464	147,506	15,958	10	203,995	182,369	21,626	11
Kern	4,134,188	3,973,487	160,701	4	9,416,063	8,748,498	667,565	7
Kings	2,096,066	2,012,112	83,954	4	3,441,272	3,297,510	143,762	4
Lake	2,754,551	2,631,031	123,520	4	2,968,445	2,812,899	155,546	5
Lassen	179,323	172,317	7,006	4	231,430	217,263	14,167	6
Los Angeles	226,780,272	219,182,471	7,597,801	3	291,929,309	283,021,908	8,907,401	3
Madera	1,946,516	1,860,971	85,545	4	2,758,274	2,645,947	112,327	4
Marin	2,237,161	2,132,082	105,079	5	2,497,071	2,344,087	152,984	6
Mariposa	213,764	209,244	4,520	2	354,342	331,896	22,446	6
Mendocino	2,159,003	2,010,563	148,440	7	2,296,328	2,130,115	166,213	7
Merced	3,131,631	3,009,596	122,035	4	3,799,322	3,648,242	151,080	4
Modoc	85,172	78,135	7,037	8	193,411	183,343	10,068	5
Mono	50,665	48,851	1,814	4	52,507	50,304	2,203	4
Monterey	4,392,101	4,249,592	142,509	3	6,303,741	6,115,148	188,593	3
Napa	1,482,768	1,434,300	48,468	3	1,764,120	1,660,626	103,494	6
Nevada	886,464	847,246	39,218	4	844,071	802,553	41,518	5
Orange	26,801,852	25,016,981	1,784,871	7	41,315,549	39,082,983	2,232,566	5
Placer	4,106,491	3,978,314	128,177	3	6,364,662	6,102,582	262,080	4
Plumas	322,901	302,592	20,309	6	399,286	368,843	30,443	8
Riverside	30,153,378	28,942,908	1,210,470	4	50,218,411	48,385,172	1,833,239	4
Sacramento	29,941,130	29,049,376	891,754	3	41,537,689	40,238,254	1,299,435	3
San Benito	760,831	735,011	25,820	3	826,475	789,029	37,446	5
San Bernardino	31,254,378	30,229,611	1,024,767	3	44,444,956	42,866,454	1,578,502	4
San Diego	28,979,647	27,947,145	1,032,502	4	39,463,190	37,948,092	1,515,098	4
San Francisco	24,763,481	23,458,848	1,304,633	5	28,233,554	26,884,997	1,348,557	5
San Joaquin	6,080,578	5,840,280	240,298	4	7,952,765	7,581,942	370,823	5
San Luis Obispo	2,203,212	2,091,462	111,750	5	2,742,328	2,624,372	117,956	4
San Mateo	5,821,686	5,514,749	306,937	5	7,637,085	7,304,711	332,374	4
Santa Barbara	3,572,189	3,405,447	166,742	5	4,382,499	4,125,687	256,812	6
Santa Clara	23,506,657	22,519,972	986,685	4	35,652,022	34,102,657	1,549,365	4
Santa Cruz	3,137,991	2,979,588	158,403	5	3,429,624	3,153,759	275,865	8
Shasta	3,505,889	3,362,997	142,892	4	4,278,714	4,041,440	237,274	6
Sierra	39,601	36,912	2,689	7	53,443	49,496	3,947	7
Siskiyou	532,175	492,243	39,932	8	639,753	595,706	44,047	7
Solano	5,708,046	5,501,307	206,739	4	7,185,453	6,875,431	310,022	4
Sonoma	6,731,314	6,454,524	276,790	4	8,612,697	8,167,172	445,525	5
Stanislaus	6,001,204	5,764,981	236,223	4	8,325,044	7,887,891	437,153	5
Sutter	1,166,519	1,124,526	41,993	4	1,462,948	1,381,572	81,376	6
Tehama	1,105,774	1,053,656	52,118	5	1,570,273	1,470,632	99,641	6
Trinity	202,813	187,877	14,936	7	245,641	226,504	19,137	8
Tulare	2,762,742	2,595,488	167,254	6	6,006,782	5,649,047	357,735	6
Tuolumne	372,870	340,587	32,283	9	572,579	513,943	58,636	10
Ventura	5,919,667	5,647,497	272,170	5	9,438,129	8,992,967	445,162	5
Yolo	2,935,329	2,805,649	129,680	4	3,874,233	3,674,987	199,246	5
Yuba	775,185	746,553	28,632	4	1,075,896	1,000,476	75,420	7
STATEWIDE	583,872,513	561,062,478	22,810,035	4	794,291,592	762,469,185	31,822,407	4

Source: Auditor’s analysis of Social Services’ CMIPS II data.

Table B.2

Varying Numbers of Recipients in All Counties Experienced Gaps in Care

	2015		2019
COUNTY	MONTHLY AVERAGE RECIPIENTS	MONTHLY AVERAGE RECIPIENTS WITHOUT IHSS CARE	MONTHLY AVERAGE RECIPIENTS	MONTHLY AVERAGE RECIPIENTS WITHOUT IHSS CARE
Alameda	21,553	1,560	25,388	2,382
Alpine	27	2	24	2
Amador	233	26	330	41
Butte	3,766	378	4,015	406
Calaveras	385	35	445	42
Colusa	164	35	269	35
Contra Costa	8,812	664	11,419	1,268
Del Norte	346	27	381	34
El Dorado	1,022	80	1,392	116
Fresno	16,132	731	21,414	1,148
Glenn	471	40	539	50
Humboldt	1,748	286	2,149	343
Imperial	5,658	219	6,540	217
Inyo	141	29	151	26
Kern	4,382	296	8,319	923
Kings	1,982	163	2,699	205
Lake	2,100	170	2,285	188
Lassen	183	19	216	29
Los Angeles	210,093	9,668	236,443	10,179
Madera	1,884	117	2,281	149
Marin	1,840	168	2,028	222
Mariposa	163	7	247	30
Mendocino	1,802	217	1,845	241
Merced	3,171	235	3,518	239
Modoc	93	15	140	12
Mono	31	4	31	3
Monterey	4,464	278	5,242	273
Napa	1,104	66	1,246	121
Nevada	713	65	708	62
Orange	26,989	2,773	34,509	3,010
Placer	2,632	171	3,627	316
Plumas	319	43	352	51
Riverside	27,392	1,820	37,980	2,513
Sacramento	24,041	1,312	29,955	1,645
San Benito	603	33	654	54
San Bernardino	26,884	1,490	34,200	2,066
San Diego	27,171	1,811	31,797	2,194
San Francisco	23,072	1,721	23,251	1,726
San Joaquin	6,255	471	7,176	553
San Luis Obispo	1,848	197	1,971	185
San Mateo	4,690	389	5,623	426
Santa Barbara	3,272	304	3,704	396
Santa Clara	21,580	1,338	26,114	1,681
Santa Cruz	2,573	272	2,901	444
Shasta	3,052	260	3,439	385
Sierra	32	5	44	8
Siskiyou	570	83	618	86
Solano	4,251	289	5,209	387
Sonoma	5,701	445	6,401	612
Stanislaus	6,507	436	7,687	679
Sutter	1,084	91	1,317	130
Tehama	983	105	1,203	153
Trinity	183	26	236	33
Tulare	3,157	366	4,981	530
Tuolumne	364	63	463	81
Ventura	5,031	414	7,196	583
Yolo	2,471	213	2,816	271
Yuba	720	48	946	106
STATEWIDE	527,890	32,589	628,074	40,290

Source: Auditor analysis of Social Services’ CMIPS II data.

Table B.3

Counties Did Not Meet the 30-Day Deadline for Approving Applications for New Recipients

	2015		2019
COUNTY	NUMBER OF NEW RECIPIENTS	AVERAGE DAYS FROM APPLICATION TO APPROVAL	NUMBER OF NEW RECIPIENTS	AVERAGE DAYS FROM APPLICATION TO APPROVAL
Alameda	3,184	82	3,208	61
Alpine	2	12	4	45
Amador	55	47	52	43
Butte	702	51	513	55
Calaveras	84	43	96	54
Colusa	47	43	68	60
Contra Costa	1,216	104	1,763	144
Del Norte	47	41	66	51
El Dorado	221	64	253	73
Fresno	3,010	78	3,427	73
Glenn	84	42	74	44
Humboldt	416	49	370	46
Imperial	697	148	950	123
Inyo	18	44	32	32
Kern	972	69	2,245	83
Kings	346	68	464	84
Lake	401	46	323	53
Lassen	41	55	52	65
Los Angeles	25,329	90	27,480	66
Madera	270	125	373	89
Marin	247	62	261	78
Mariposa	21	36	53	51
Mendocino	302	63	293	66
Merced	551	68	533	74
Modoc	22	35	24	52
Mono	11	62	4	60
Monterey	680	77	863	55
Napa	165	56	171	56
Nevada	148	63	125	58
Orange	4,320	80	4,645	66
Placer	463	75	553	71
Plumas	69	45	69	53
Riverside	5,149	68	6,533	56
Sacramento	3,580	97	4,778	63
San Benito	84	81	110	83
San Bernardino	4,281	72	5,445	85
San Diego	3,784	70	5,387	60
San Francisco	2,031	49	2,221	61
San Joaquin	964	117	1,084	156
San Luis Obispo	305	95	326	62
San Mateo	934	50	1,012	54
Santa Barbara	487	56	670	64
Santa Clara	3,116	109	3,585	83
Santa Cruz	352	82	391	81
Shasta	508	49	652	39
Sierra	11	42	8	42
Siskiyou	118	48	121	49
Solano	725	96	721	87
Sonoma	897	84	869	83
Stanislaus	855	115	1,087	117
Sutter	173	50	234	94
Tehama	174	56	218	65
Trinity	31	58	47	85
Tulare	704	79	1,073	131
Tuolumne	47	69	87	65
Ventura	945	54	1,102	55
Yolo	331	78	400	74
Yuba	119	38	143	135
STATEWIDE	74,846	82	87,711	72

Source: Auditor analysis of Social Services’ CMIPS II data.

Table B.4

Counties Did Not Meet the 15-Day Deadline for Ensuring Prompt Care for New Recipients Who Did Not Receive Services Until After They Entered the Program

	2015		2019
COUNTY	NUMBER OF NEW RECIPIENTS*	AVERAGE DAYS FROM APPROVAL TO FIRST SERVICE	NUMBER OF NEW RECIPIENT*	AVERAGE DAYS FROM APPROVAL TO FIRST SERVICE†
Alameda	598	132	602	56
Alpine	0	N/A	1	334
Amador	27	64	11	46
Butte	175	68	121	55
Calaveras	20	59	24	49
Colusa	12	191	18	55
Contra Costa	227	123	224	67
Del Norte	20	29	18	60
El Dorado	51	101	45	59
Fresno	278	89	249	46
Glenn	20	94	25	49
Humboldt	126	157	107	51
Imperial	105	33	90	27
Inyo	12	130	14	50
Kern	159	77	322	58
Kings	57	80	46	54
Lake	88	103	63	48
Lassen	13	44	14	40
Los Angeles	2,366	120	2,369	57
Madera	19	82	32	76
Marin	78	57	61	49
Mariposa	5	67	17	67
Mendocino	80	69	54	63
Merced	95	96	69	36
Modoc	16	47	11	43
Mono	5	31	0	N/A
Monterey	75	48	117	41
Napa	36	54	51	49
Nevada	42	52	34	66
Orange	719	153	695	48
Placer	74	80	96	49
Plumas	22	34	17	53
Riverside	664	67	801	51
Sacramento	503	87	505	45
San Benito	14	127	15	35
San Bernardino	483	75	609	55
San Diego	752	73	991	50
San Francisco	416	70	459	39
San Joaquin	112	97	113	54
San Luis Obispo	68	72	69	60
San Mateo	203	123	206	42
Santa Barbara	128	76	135	48
Santa Clara	449	111	394	57
Santa Cruz	79	108	86	70
Shasta	143	45	194	34
Sierra	8	25	1	6
Siskiyou	38	48	42	35
Solano	133	114	84	61
Sonoma	204	78	147	58
Stanislaus	125	125	125	52
Sutter	71	44	45	60
Tehama	58	68	52	50
Trinity	7	76	7	56
Tulare	169	96	152	50
Tuolumne	14	52	16	110
Ventura	192	97	159	50
Yolo	76	69	72	50
Yuba	59	44	47	52
STATEWIDE	10,788	98	11,143	52

Table B.5

Most Counties Have Experienced Significant Growth In Their IHSS Programs Since 2015

COUNTY	GROUP	2015	2019	PERCENTAGE INCREASE FROM 2015 TO 2019
Alameda	Caregivers	23,548	26,754	14%
Alameda	Recipients	24,489	28,618	17
Alpine	Caregivers	36	27	-25
Alpine	Recipients	32	28	-13
Amador	Caregivers	231	320	39
Amador	Recipients	295	389	32
Butte	Caregivers	4,491	4,583	2
Butte	Recipients	4,507	4,829	7
Calaveras	Caregivers	453	492	9
Calaveras	Recipients	470	531	13
Colusa	Caregivers	148	285	93
Colusa	Recipients	209	350	67
Contra Costa	Caregivers	9,910	12,001	21
Contra Costa	Recipients	10,108	13,016	29
Del Norte	Caregivers	420	473	13
Del Norte	Recipients	406	451	11
El Dorado	Caregivers	1,255	1,682	34
El Dorado	Recipients	1,224	1,651	35
Fresno	Caregivers	17,967	22,923	28
Fresno	Recipients	18,536	24,114	30
Glenn	Caregivers	545	609	12
Glenn	Recipients	562	614	9
Humboldt	Caregivers	1,867	2,350	26
Humboldt	Recipients	2,147	2,591	21
Imperial	Caregivers	5,513	6,393	16
Imperial	Recipients	6,320	7,337	16
Inyo	Caregivers	131	146	11
Inyo	Recipients	178	178	0
Kern	Caregivers	5,050	8,468	68
Kern	Recipients	5,374	10,106	88
Kings	Caregivers	2,163	2,953	37
Kings	Recipients	2,337	3,107	33
Lake	Caregivers	2,504	2,505	0
Lake	Recipients	2,510	2,637	5
Lassen	Caregivers	197	233	18
Lassen	Recipients	234	278	19
Los Angeles	Caregivers	191,913	222,529	16
Los Angeles	Recipients	233,346	260,971	12
Madera	Caregivers	2,005	2,540	27
Madera	Recipients	2,170	2,635	21
Marin	Caregivers	1,992	2,052	3
Marin	Recipients	2,131	2,313	9
Mariposa	Caregivers	215	279	30
Mariposa	Recipients	193	293	52
Mendocino	Caregivers	1,964	1,962	0
Mendocino	Recipients	2,111	2,128	1
Merced	Caregivers	3,329	3,839	15
Merced	Recipients	3,791	4,126	9
Modoc	Caregivers	87	170	95
Modoc	Recipients	118	171	45
Mono	Caregivers	37	40	8
Mono	Recipients	42	40	-5
Monterey	Caregivers	4,729	5,560	18
Monterey	Recipients	5,192	6,029	16
Napa	Caregivers	1,436	1,515	6
Napa	Recipients	1,276	1,415	11
Nevada	Caregivers	912	838	-8
Nevada	Recipients	867	839	-3
Orange	Caregivers	25,734	32,847	28
Orange	Recipients	30,784	38,870	26
Placer	Caregivers	3,340	4,152	24
Placer	Recipients	3,151	4,203	33
Plumas	Caregivers	342	367	7
Plumas	Recipients	396	419	6
Riverside	Caregivers	29,057	39,266	35
Riverside	Recipients	32,480	43,929	35
Sacramento	Caregivers	26,951	34,019	26
Sacramento	Recipients	27,380	34,111	25
San Benito	Caregivers	703	766	9
San Benito	Recipients	688	757	10
San Bernardino	Caregivers	28,457	35,805	26
San Bernardino	Recipients	31,446	39,384	25
San Diego	Caregivers	27,898	32,946	18
San Diego	Recipients	31,103	36,417	17
San Francisco	Caregivers	23,915	25,520	7
San Francisco	Recipients	25,581	25,538	0
San Joaquin	Caregivers	6,785	7,760	14
San Joaquin	Recipients	7,422	8,369	13
San Luis Obispo	Caregivers	1,979	2,169	10
San Luis Obispo	Recipients	2,138	2,307	8
San Mateo	Caregivers	5,666	6,900	22
San Mateo	Recipients	5,591	6,597	18
Santa Barbara	Caregivers	3,466	3,764	9
Santa Barbara	Recipients	3,833	4,309	12
Santa Clara	Caregivers	23,714	29,528	25
Santa Clara	Recipients	24,374	29,169	20
Santa Cruz	Caregivers	2,899	2,951	2
Santa Cruz	Recipients	2,981	3,311	11
Shasta	Caregivers	3,483	3,894	12
Shasta	Recipients	3,651	4,112	13
Sierra	Caregivers	37	52	41
Sierra	Recipients	44	54	23
Siskiyou	Caregivers	556	609	10
Siskiyou	Recipients	703	757	8
Solano	Caregivers	5,106	6,050	18
Solano	Recipients	5,075	5,971	18
Sonoma	Caregivers	6,298	6,660	6
Sonoma	Recipients	6,602	7,174	9
Stanislaus	Caregivers	6,564	7,573	15
Stanislaus	Recipients	7,498	8,700	16
Sutter	Caregivers	1,244	1,441	16
Sutter	Recipients	1,280	1,595	25
Tehama	Caregivers	1,131	1,408	24
Tehama	Recipients	1,166	1,455	25
Trinity	Caregivers	187	231	24
Trinity	Recipients	216	296	37
Tulare	Caregivers	3,211	5,113	59
Tulare	Recipients	3,800	5,875	55
Tuolumne	Caregivers	398	485	22
Tuolumne	Recipients	444	554	25
Ventura	Caregivers	5,376	7,646	42
Ventura	Recipients	5,943	8,263	39
Yolo	Caregivers	2,864	3,291	15
Yolo	Recipients	2,861	3,222	13
Yuba	Caregivers	834	1,026	23
Yuba	Recipients	867	1,140	31
STATEWIDE	Caregivers	525,166	628,281	20
STATEWIDE	Recipients	594,848	701,548	18

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Appendix C

Comparison of Living Wage to Actual Caregiver Wages in California Counties

The Audit Committee asked us to provide information related to caregiver wages. Table C indicates the actual caregiver wages and living wage in all 58 counties as of 2019. Our selected counties Butte, Kern, San Diego and Stanislaus, are indicated in blue shading.

Table C

Counties Did Not Pay IHSS Caregivers a Living Wage In 2019

COUNTY	IHSS CAREGIVER WAGE	COUNTY LIVING WAGE*	AMOUNT BY WHICH LIVING WAGE EXCEEDS CAREGIVER WAGE	CAREGIVER WAGE AS A PERCENTAGE OF LIVING WAGE
Alameda	$12.50	$25.38	$12.88	49%
Alpine	$12.00	$18.99	$6.99	63%
Amador	$12.00	$19.55	$7.55	61%
Butte	$12.00	$20.04	$8.04	60%
Calaveras	$12.00	$19.42	$7.42	62%
Colusa	$12.00	$19.00	$7.00	63%
Contra Costa	$12.25	$25.38	$13.13	48%
Del Norte	$12.00	$19.09	$7.09	63%
El Dorado	$12.00	$20.53	$8.53	58%
Fresno	$12.00	$19.22	$7.22	62%
Glenn	$12.00	$18.32	$6.32	66%
Humboldt	$12.00	$19.19	$7.19	63%
Imperial	$12.00	$18.98	$6.98	63%
Inyo	$12.00	$19.26	$7.26	62%
Kern	$12.00	$18.84	$6.84	64%
Kings	$12.00	$19.49	$7.49	62%
Lake	$12.00	$18.99	$6.99	63%
Lassen	$12.00	$18.38	$6.38	65%
Los Angeles	$12.60	$23.26	$10.66	54%
Madera	$12.00	$19.23	$7.23	62%
Marin	$14.20	$31.00	$16.80	46%
Mariposa	$12.00	$19.00	$7.00	63%
Mendocino	$12.00	$19.52	$7.52	61%
Merced	$12.00	$18.63	$6.63	64%
Modoc	$12.00	$17.64	$5.64	68%
Mono	$12.00	$20.38	$8.38	59%
Monterey	$12.50	$22.31	$9.81	56%
Napa	$12.10	$22.64	$10.54	53%
Nevada	$12.00	$20.18	$8.18	59%
Orange	$12.00	$24.89	$12.89	48%
Placer	$12.00	$20.53	$8.53	58%
Plumas	$12.00	$19.05	$7.05	63%
Riverside	$12.00	$20.64	$8.64	58%
Sacramento	$13.00	$20.53	$7.53	63%
San Benito	$12.00	$22.86	$10.86	52%
San Bernardino	$12.00	$20.64	$8.64	58%
San Diego	$12.50	$24.62	$12.12	51%
San Francisco	$15.00	$31.00	$16.00	48%
San Joaquin	$12.00	$19.59	$7.59	61%
San Luis Obispo	$13.00	$22.03	$9.03	59%
San Mateo	$13.90	$31.00	$17.10	45%
Santa Barbara	$12.10	$25.12	$13.02	48%
Santa Clara	$13.00	$29.39	$16.39	44%
Santa Cruz	$12.46	$26.29	$13.83	47%
Shasta	$12.60	$19.15	$6.55	66%
Sierra	$12.00	$20.63	$8.63	58%
Siskiyou	$12.00	$18.34	$6.34	65%
Solano	$12.50	$21.95	$9.45	57%
Sonoma	$13.00	$23.68	$10.68	55%
Stanislaus	$12.00	$19.44	$7.44	62%
Sutter	$12.00	$18.59	$6.59	65%
Tehama	$12.00	$18.32	$6.32	66%
Trinity	$12.50	$18.36	$5.86	68%
Tulare	$12.00	$18.76	$6.76	64%
Tuolumne	$12.50	$19.40	$6.90	64%
Ventura	$12.78	$23.12	$10.34	55%
Yolo	$12.00	$20.84	$8.84	58%
Yuba	$12.00	$18.59	$6.59	65%
STATEWIDE	$12.29	$21.19	$8.90	58%

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Appendix D

Effect of Reducing the Inflation Factor on Certain Counties

As we note in the main report, since 2012, the State’s method of calculating county contributions for IHSS funding has created significant disparities in the individual proportions of funding that counties provide to the IHSS program. Statewide IHSS costs have increased because of changes such as implementation of the Affordable Care Act and the State’s expansion of Medi-Cal, both of which increased the number of recipients, as well as increases in the number of hours of care recipients receive and increases in caregiver wages. However, although all counties’ IHSS costs have increased, growth in costs has not been proportional across counties because of variations in local populations and local caregiver wages. Despite this, since 2012 the State’s annual inflation factor has applied a flat percentage increase to the amount each county pays the State, regardless of the extent of the growth of its program costs. Over time, these disparities have resulted in some counties paying significantly more or less than their share of the overall IHSS program costs would suggest.

Although before 2012 each county paid the State a set proportion of about 18 percent of their overall IHSS program costs, by fiscal year 2018–19, counties paid between 6 percent and 29 percent of their costs, depending on how much faster or slower their costs grew compared to the State’s annual inflation factor. Returning to the pre‑2012 funding system would require some counties to pay over $20 million more annually. As the revenues from sources the Legislature dedicated to counties to support the program have not increased as rapidly as the program itself, it is unlikely that counties would be able to bear the expense of these increases, as Finance has noted. However, without state action, these disparities in the proportions that counties pay will continue to grow.

Immediately eliminating proportional overpayments by counties would require the State to increase its support of the program by $86 million per year, based on fiscal year 2018–19 ratios. However, by adjusting the IHSS inflation factor annually based on the availability of dedicated county funds and annual county program growth, as we recommend at the end of Chapter 2, the State could gradually move to a more equitable funding model. Selectively reducing the inflation factor for counties paying more than their proportional share would allow the State to gradually reduce overpayments. For example, by temporarily eliminating the inflation factor for 18 counties that pay more than their share, by year five overpayments would be eliminated for 12 of the 18 counties, and reduced for the remaining six counties, at a cost to the State of $215 million. Likewise, an annual review of the availability of dedicated funds may allow the State to increase the percentage of support paid by those counties not currently paying a proportional share. Table D demonstrates the effect a decrease in inflation factors at selected counties would have on the counties and the associated costs to the State.

Table D

Eliminating the Inflation Factor for Counties Paying More Than Their Share Would Gradually Reduce Overpayments

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Appendix E

Scope and Methodology

The Audit Committee directed the State Auditor to examine the expenditure of state funds for the IHSS program at four counties selected by the State Auditor. Table E below lists the objectives that the Audit Committee approved and the methods we used to address them.

Table E

Audit Objectives and the Methods Used to Address Them

AUDIT OBJECTIVE		METHOD
1	Review and evaluate the laws, rules, and regulations significant to the audit objectives.	Identified and reviewed relevant federal and state laws, rules, and regulations related to the IHSS program.
2	Analyze the counties’ expenditures of IHSS funding, including the counties’ costs to administer IHSS and the amount of funds paid for providers’ wages and benefits. Also, determine whether counties are spending all IHSS funding each year.	Interviewed relevant staff at each of the selected counties, IHSS public authorities, and Social Services. Reviewed financial documentation at the selected counties and public authorities. Reviewed Social Services’ IHSS data for the most recent five fiscal years. Determined the following: the percent of budgeted expenditures spent, expenditures on IHSS provider salary and benefits, administrative expenditures, and the costs related to the public authorities. Reviewed Social Services’ county expense claim system data to compare selected county administrative expenses to statewide averages.
3	Determine whether each county uses IHSS funding for anything other than provider wages, benefits, and county administrative costs. If so, assess the rationale for other uses.	Reviewed state law and found that the State funds IHSS caregivers wages and benefits, and that counties do not receive this funding from the State. Interviewed relevant staff at each of the selected counties and public authorities. Reviewed county financial documentation to identify any usage of IHSS funds for purposes not directly related to IHSS administration or benefits during the past five fiscal years. Reviewed a minimum of 95 percent of the dollar amount of each selected county’s IHSS administrative expenses to determine if the expenses were within allowable categories for IHSS under the State’s claiming rules. Compared counties financial documentation with expenditures they reported to Social Services.
4	Identify trends in the number of IHSS providers and recipients within each county. Assess whether each county has a shortage of providers given the IHSS hours authorized for recipients.	Interviewed relevant staff at Social Services and their contracted data experts as we developed our methodology and performed our analysis. Used data acquired from Social Services’ CMIPS II system as of June 2020 to determine the number of providers, recipients, approved hours, and hours provided at our selected counties for the past five calendar years. Also determined trends for providers, recipients, approved hours, and hour usage. To account for delays in providers submitting timesheets, we included all timesheet data through June 2020 but limited our analysis to services rendered through December 2019. Interviewed county staff to determine the rationale for differences in budgeted versus actual expenditures and care hours and for any shortages of providers. Conducted analysis to determine the extent of provider availability and associated trends. Conducted data reliability assessment testing of CMIPS II data using data from our selected counties and internal dataset verification. Surveyed counties throughout the State to determine whether gaps in care exist and the extent of current planning efforts, as well as to gain perspective related to their administration, hours utilization, recruitment, retention, and potential best practices.
5	Determine the average minimum wage of each county and compare it to the average wage rate for providers in each county. To the extent possible, determine the cost of living within each county and compare that to the average provider wage rate in that county.	Determined minimum wages in all counties for the most recent five calendar years. Used Social Services’ data to determine average provider wages in all counties over the past five fiscal years. Reviewed publicly available living wage analysis, including analysis previously conducted at universities. Conducted analysis comparing current wage data and living wage data by county for all counties. Further, compared current wage data to other data sets such as federal per diem, and federal poverty threshold.
6	Identify and assess the biggest challenges to increasing IHSS provider wages within each county.	Interviewed the provider union for our selected counties to determine challenges to IHSS provider wage increases. Utilized our survey of counties throughout the State to gain perspective on the extent of current planning to increase provider wages at all counties, and on the challenges to increasing IHSS wages. Reviewed the State’s IHSS funding mechanisms to determine whether they discourage counties from increasing provider wages.
7	Determine the costs incurred by each county to recruit and provide training to new IHSS providers.	Interviewed relevant staff, and to the extent it was available reviewed financial documentation related to recruiting and training efforts at each of the selected counties. Reviewed available county financial documentation. Determined that counties we reviewed perform minimal recruitment and do not track recruitment expenses. Determined that training costs in Butte and Kern counties were minimal. Found that Stanislaus has a memorandum of understanding with its caregiver union for the union to provide health and safety training for costs not to exceed $40,000 per year. Found that the San Diego County Public Authority has staff and other resources dedicated for training, but we were unable to determine their costs based on the financial documents the county provided. Used our survey of counties throughout the state to gain perspective and unaudited data related to recruitment and training issues and expenses.
8	To the extent possible, determine what challenges exist for IHSS recipients including, but not limited, to those without family support—when hiring and retaining providers. Specifically, assess the effect of wages on hiring and retention.	Used data obtained from Social Services’ CMIPS II data system to determine the average time between selected milestones including from application to initial home visit, home visit to approval for services, and approval until the provision of initial services. Conducted interviews at our selected counties and Social Services to determine the cause of delays. Used data obtained from Social Services’ CMIPS II data system to determine retention rate of providers at each counties in the State. To the extent possible, filtered data for recipients to determine turnover rate for those utilizing family support. We found that the providers who were family members had similar retention rates to providers who were not family members. Identified and interviewed a selection of nonrelated IHSS caregivers who left the program while their associated care recipient remained and determined the reason for their departure. Analyzed county complaint policies and processes. Requested plans from the four selected counties related to resolving issues with recruiting and retaining providers, including potential increases to wages. Surveyed counties about lack of available planning. Requested planning documents at our selected counties related to pending increases in recipients. Surveyed counties about lack of planning. Surveyed counties throughout the State to determine any potential challenges IHSS recipients experienced when hiring and retaining providers. Further, surveyed counties on potential challenges related to collective bargaining agreements. Analyzed gaps between IHSS provider wages and the living wage. Compared gaps against the retention rates of counties. Reviewed outside analysis related to IHSS worker availability. Our review did not identify a causal link, likely due to the disparity between existing wages and the living wage at all counties. However, we did note that counties with a smaller gap between the living wage and provider wage in some cases had greater retention for paid providers in the later years of our review.
9	Determine how long it takes for new providers, on average, to receive their first timesheet. To the extent possible, assess the impact that this timeline has on hiring and recruiting new non‑family IHSS providers.	Interviewed relevant staff at Social Services and their contracted data experts as we developed our methodology and performed our analysis. Used data from Social Services’ CMIPS II system to determine average time from initial hire until the issuance of timesheets for providers in our selected counties. Reviewed the length of time from initial eligibility to first timesheet, and calculated the average number of hours worked by providers within the selected counties. To the extent possible, filtered Social Services’ data to determine whether providers were non‑family providers. Used data from Social Services’ CMIPS II system to determine the number of approved providers in the selected counties who never received a time card and those that only worked for a limited period. Reviewed selected county and public authority onboarding materials and related policies and procedures to determine their compliance with state law. Analyzed the amount of time it took new IHSS caregivers to receive their first timesheets. Interviewed former non‑family IHSS caregivers to determine their reasons for leaving the program. No information identified to establish a causal link between potential timesheet delays and caregiver hiring and retention.
10	Review and assess any other issues that are significant to the audit.	Interviewed relevant staff at Social Services and their contracted data experts as we developed our methodology and performed our analysis. Reviewed the State’s IHSS funding mechanisms to determine whether incentives exist for counties to limit IHSS services. Reviewed the State’s IHSS funding mechanisms to determine whether they were equitable and provide for stable county IHSS funding.

Assessment of Data Reliability

The U.S. Government Accountability Office, whose standards we are statutorily required to follow, requires us to assess the sufficiency and appropriateness of computer‑processed information that we use to support our findings, conclusions, and recommendations. In performing this audit, we relied on IHSS program eligibility and timesheet data from Social Services’ CMIPS II system to calculate various program statistics and to evaluate trends about providers and recipients in the program. To evaluate these data, we reviewed existing information about the data, interviewed staff knowledgeable about the data, performed electronic testing of the data, and conducted accuracy testing on a selection of key data elements. We found that these data were of undetermined reliability. Although this determination may affect the precision of the numbers we present, sufficient evidence exists in total to support our audit finds, conclusions, and recommendations.

In addition, we obtained electronic expenditure data from each of the four counties we reviewed. We performed data validation and verification through logic testing of key elements. We determined that those data were reliable for the purposes of this audit.

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